Cerutti-Pereyra, Florencia, Elizabeth J Drenkard, Mario Espinoza, Brittany Finucci, Felipe Galván-Magaña, Ana Hacohen-Domené, Alexander Hearn, Mauricio E Hoyos-Padilla, James T Ketchum, Paola A Mejía-Falla, Ana V Moya-Serrano, Andres F Navia, Diana A Pazmiño, Deni Ramírez-Macías, Jodie L Rummer, Pelayo Salinas-de-León, Oscar Sosa-Nishizaki, Charles A Stock, and Andrew Chin, July 2024: Vulnerability of Eastern Tropical Pacific chondrichthyan fish to climate change. Global Change Biology, 30(7), DOI:10.1111/gcb.17373. Abstract
Climate change is an environmental emergency threatening species and ecosystems globally. Oceans have absorbed about 90% of anthropogenic heat and 20%–30% of the carbon emissions, resulting in ocean warming, acidification, deoxygenation, changes in ocean stratification and nutrient availability, and more severe extreme events. Given predictions of further changes, there is a critical need to understand how marine species will be affected. Here, we used an integrated risk assessment framework to evaluate the vulnerability of 132 chondrichthyans in the Eastern Tropical Pacific (ETP) to the impacts of climate change. Taking a precautionary view, we found that almost a quarter (23%) of the ETP chondrichthyan species evaluated were highly vulnerable to climate change, and much of the rest (76%) were moderately vulnerable. Most of the highly vulnerable species are batoids (77%), and a large proportion (90%) are coastal or pelagic species that use coastal habitats as nurseries. Six species of batoids were highly vulnerable in all three components of the assessment (exposure, sensitivity and adaptive capacity). This assessment indicates that coastal species, particularly those relying on inshore nursery areas are the most vulnerable to climate change. Ocean warming, in combination with acidification and potential deoxygenation, will likely have widespread effects on ETP chondrichthyan species, but coastal species may also contend with changes in freshwater inputs, salinity, and sea level rise. This climate-related vulnerability is compounded by other anthropogenic factors, such as overfishing and habitat degradation already occurring in the region. Mitigating the impacts of climate change on ETP chondrichthyans involves a range of approaches that include addressing habitat degradation, sustainability of exploitation, and species-specific actions may be required for species at higher risk. The assessment also highlighted the need to further understand climate change's impacts on key ETP habitats and processes and identified knowledge gaps on ETP chondrichthyan species.
Chen, Zhuomin, Samantha A Siedlecki, Matthew C Long, Colleen M Petrik, Charles A Stock, and Curtis A Deutsch, January 2024: Skillful multiyear prediction of marine habitat shifts jointly constrained by ocean temperature and dissolved oxygen. Nature Communications, 15, 900, DOI:10.1038/s41467-024-45016-5. Abstract
The ability to anticipate marine habitat shifts responding to climate variability has high scientific and socioeconomic value. Here we quantify interannual-to-decadal predictability of habitat shifts by combining trait-based aerobic habitat constraints with a suite of initialized retrospective Earth System Model forecasts, for diverse marine ecotypes in the North American Large Marine Ecosystems. We find that aerobic habitat viability, defined by joint constraints of temperature and oxygen on organismal energy balance, is potentially predictable in the upper-600 m ocean, showing a substantial improvement over a simple persistence forecast. The skillful multiyear predictability is dominated by the oxygen component in most ecosystems, yielding higher predictability than previously estimated based on temperature alone. Notable predictability differences exist among ecotypes differing in temperature sensitivity of hypoxia vulnerability, especially along the northeast coast with predictability timescale ranging from 2 to 10 years. This tool will be critical in predicting marine habitat shifts in face of a changing climate.
Dugenne, Mathilde, Marco Corrales-Ugalde, Jessica Y Luo, Rainer Kiko, Todd D O'Brien, Jean-Olivier Irisson, Fabien Lombard, Lars Stemmann, and Charles A Stock, et al., June 2024: First release of the Pelagic Size Structure database: global datasets of marine size spectra obtained from plankton imaging devices. Earth System Science Data, 16(6), DOI:10.5194/essd-16-2971-20242971-2999. Abstract
In marine ecosystems, most physiological, ecological, or physical processes are size dependent. These include metabolic rates, the uptake of carbon and other nutrients, swimming and sinking velocities, and trophic interactions, which eventually determine the stocks of commercial species, as well as biogeochemical cycles and carbon sequestration. As such, broad-scale observations of plankton size distribution are important indicators of the general functioning and state of pelagic ecosystems under anthropogenic pressures. Here, we present the first global datasets of the Pelagic Size Structure database (PSSdb), generated from plankton imaging devices. This release includes the bulk particle normalized biovolume size spectrum (NBSS) and the bulk particle size distribution (PSD), along with their related parameters (slope, intercept, and R2) measured within the epipelagic layer (0–200 m) by three imaging sensors: the Imaging FlowCytobot (IFCB), the Underwater Vision Profiler (UVP), and benchtop scanners. Collectively, these instruments effectively image organisms and detrital material in the 7–10 000 µm size range. A total of 92 472 IFCB samples, 3068 UVP profiles, and 2411 scans passed our quality control and were standardized to produce consistent instrument-specific size spectra averaged to 1° × 1° latitude and longitude and by year and month. Our instrument-specific datasets span most major ocean basins, except for the IFCB datasets we have ingested, which were exclusively collected in northern latitudes, and cover decadal time periods (2013–2022 for IFCB, 2008–2021 for UVP, and 1996–2022 for scanners), allowing for a further assessment of the pelagic size spectrum in space and time. The datasets that constitute PSSdb's first release are available at https://doi.org/10.5281/zenodo.11050013 (Dugenne et al., 2024b). In addition, future updates to these data products can be accessed at https://doi.org/10.5281/zenodo.7998799.
Friedrich, Tobias, Brian S. Powell, Jacob L Gunnarson, Guangpeng Liu, Sonja F Giardina, Malte F Stuecker, Lucia Hošeková, Kate Feloy, and Charles A Stock, February 2024: Submesoscale-permitting physical/biogeochemical future projections for the main Hawaiian Islands. Journal of Advances in Modeling Earth Systems, 16(2), DOI:10.1029/2023MS003855. Abstract
Global climate models provide useful tools to forecast large-scale anthropogenic trends and the impacts on ocean physics and marine biology and chemistry. Due to coarse spatial resolution, they typically lack the ability to represent important regional processes while underestimating mesoscale variability and vertical mixing. This means they provide limited value when it comes to regional climate projections. We developed a regional submesoscale-permitting physical/biogeochemical model to dynamically downscale the output of a CMIP6 Earth System Model for three different Socioeconomic Pathways for the main Hawaiian Islands. We describe the methodology for downscaling the CMIP6 ocean physics and biogeochemistry along with atmospheric conditions in order to offline nest a regional model. We expect the large-scale spatial and temporal features of the global model to be retained by the regional model, while adding representation of the regional processes that are crucial to understanding climate change on a local scale. We compare the regional model representation against both observed data and a regional reanalysis over the first two decades of the century. We show that the regional model maintains the large-scale trends and interannual variability provided by the CMIP6 model while well-representing the regional dynamics that drive the short-term variability. To better illustrate the benefit of the downscaling, we present preliminary analysis of the downscaled results to examine climate impacts on the island corals that are not resolved by the global models. This analysis reveals that coastal corals are likely to experience unprecedented ocean acidification and substantial warming over the course of the century.
Frieler, Katja, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P O Reyer, Dirk Nikolaus Karger, Johanna T Malle, Simon Treu, Christoph Menz, Julia L Blanchard, Cheryl S Harrison, Colleen M Petrik, Tyler D Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A Watson, Charles A Stock, and Xiao Liu, et al., January 2024: Scenario setup and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). Geoscientific Model Development, 17(1), DOI:10.5194/gmd-17-1-20241-51. Abstract
This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, http://www.isimip.org, last access: 2 November 2023) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human, and managed systems to climate change, rising CH4 and CO2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6.
Hagstrom, George I., Charles A Stock, Jessica Y Luo, and Simon A Levin, May 2024: Impact of Dynamic Phytoplankton Stoichiometry on Global Scale Patterns of Nutrient Limitation, Nitrogen Fixation, and Carbon Export. Global Biogeochemical Cycles, 38(5), DOI:10.1029/2023GB007991. Abstract
Phytoplankton stoichiometry modulates the interaction between carbon, nitrogen and phosphorus cycles. Environmentally driven variations in phytoplankton C:N:P can alter biogeochemical cycling compared to expectations under fixed ratios. In fact, the assumption of fixed C:N:P has been linked to Earth System Model (ESM) biases and potential misrepresentation of responses to future change. Here we integrate key elements of the Adaptive Trait Optimization Model (ATOM) for phytoplankton stoichiometry with the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) ocean biogeochemical model. Within a series of global ocean-ice-ecosystem retrospective simulations, ATOM-COBALT reproduced observations of phytoplankton N:P, and compared to static ratios, exhibited reduced phytoplankton P-limitation, enhanced N-fixation, and increased low-latitude export, improving consistency with observations and highlighting the biogeochemical implications of dynamic N:P. We applied ATOM-COBALT to explore the impacts of different physiological mechanisms hypothesized to underlie N:P variation, finding that two mechanisms together drove the observed patterns: proportionality of P-rich ribosomes in phytoplankton cells to growth rates and reductions in P-storage during scarcity. A third mechanism which linked temperature with phytoplankton biomass allocations to non-ribosomal proteins, led only to relatively modest impacts because this mechanism decreased the temperature dependence of phytoplankton growth rates, compensating for changes in N:P. We find that there are quantitative response differences that associate distinctive biogeochemical footprints with each mechanism, which are most apparent in highly productive low-latitude regions. These results suggest that variable phytoplankton N:P makes phytoplankton productivity and export resilient to environmental changes, and support further research on the physiological and environmental drivers of phytoplankton stoichiometry and biogeochemical role.
The capability to anticipate the exceptionally rapid warming of the Northwest Atlantic Shelf and its evolution over the next decade could enable effective mitigation for coastal communities and marine resources. However, global climate models have struggled to accurately predict this warming due to limited resolution; and past regional downscaling efforts focused on multi-decadal projections, neglecting predictive skill associated with internal variability. We address these gaps with a high resolution (1/12°) ensemble of dynamically downscaled decadal predictions. The downscaled simulations accurately predicted past oceanic variability at scales relevant to marine resource management, with skill typically exceeding global coarse-resolution predictions. Over the long term, warming of the Shelf is projected to continue; however, we forecast a temporary warming pause in the next decade. This predicted pause is attributed to internal variability associated with a transient, moderate strengthening of the Atlantic meridional overturning circulation and a southward shift of the Gulf Stream.
Estimating global river solids, nitrogen (N), and phosphorus (P), in both quantity and composition, is necessary for understanding the development and persistence of many harmful algal blooms, hypoxic events, and other water quality issues in inland and coastal waters. This requires a comprehensive freshwater model that can resolve intertwined algae, solid, and nutrient dynamics, yet previous global watershed models have limited mechanistic resolution of instream biogeochemical processes. Here we develop the global, spatially explicit, and process-based Freshwater Algae, Nutrient, and Solid cycling and Yields (FANSY) model and incorporate it within the Land Model (LM3). The resulting model, LM3-FANSY v1.0, is intended as a baseline for eventual linking of global terrestrial and ocean biogeochemistry in next-generation Earth system models to project global changes that may challenge empirical approaches. LM3-FANSY explicitly resolves interactions between algae, N, P, and solid dynamics in rivers and lakes at 1° spatial and 30 min temporal resolution. Simulated suspended solids (SS), N, and P in multiple forms (particulate or dissolved, organic or inorganic) agree well with measurement-based yield (kg km−2 yr−1), load (kt yr−1), and concentration (mg L−1) estimates across a globally distributed set of large rivers, with an accuracy comparable to other global nutrient and SS models. Furthermore, simulated global river loads of SS, N, and P in different forms to the coastal ocean are consistent with published ranges, though regional biases are apparent. River N loads are estimated to contain approximately equal contributions by dissolved inorganic N (41 %) and dissolved organic N (39 %), with a lesser contribution by particulate organic N (20 %). For river P load estimates, particulate P, which includes both organic and sorbed inorganic forms, is the most abundant form (64 %), followed by dissolved inorganic and organic P (25 % and 11 %). Time series analysis of river solid and nutrient loads in large US rivers for the period ∼ 1963–2000 demonstrates that simulated SS and N loads in different N forms covary with variations of measurement-based loads. LM3-FANSY, however, has less capability to capture interannual variability of P loads, likely due to the lack of terrestrial P dynamics in LM3. Analyses of the model results and sensitivity to components, parameters, and inputs suggest that fluxes from terrestrial litter and soils, wastewater, and weathering are the most critical inputs to the fidelity of simulated river nutrient loads for observation-based estimates. Sensitivity analyses further demonstrate a critical role of algal dynamics in controlling the ratios of inorganic and organic nutrient forms in freshwaters. While the simulations are able to capture significant cross-watershed contrasts at a global scale, disagreement for individual rivers can be substantial. This limitation is shared by other global river models and could be ameliorated through further refinements in nutrient sources, freshwater model dynamics, and observations. Current targets for future LM3-FANSY development include the additions of terrestrial P dynamics, freshwater carbon, alkalinity, enhanced sediment dynamics, and anthropogenic hydraulic controls.
Future socioeconomic climate pathways have regional water-quality consequences whose severity and equity have not yet been fully understood across geographic and economic spectra. We use a process-based, terrestrial-freshwater ecosystem model to project 21st-century river nitrogen loads under these pathways. We find that fertilizer usage is the primary determinant of future river nitrogen loads, changing precipitation and warming have limited impacts, and CO2 fertilization-induced vegetation growth enhancement leads to modest load reductions. Fertilizer applications to produce bioenergy in climate mitigation scenarios cause larger load increases than in the highest emission scenario. Loads generally increase in low-income regions, yet remain stable or decrease in high-income regions where agricultural advances, low food and feed production and waste, and/or well-enforced air pollution policies balance biofuel-associated fertilizer burdens. Consideration of biofuel production options with low fertilizer demand and rapid transfer of agricultural advances from high- to low-income regions may help avoid inequitable water-quality outcomes from climate mitigation.
Pelagic tunicates (salps, pyrosomes) and fishes generate jelly falls and/or fecal pellets that sink roughly 10 times faster than bulk oceanic detritus, but their impacts on biogeochemical cycles in the ocean interior are poorly understood. Using a coupled physical-biogeochemical model, we find that fast-sinking detritus decreased global net primary production and surface export, but increased deep sequestration and transfer efficiency in much of the extratropics and upwelling zones. Fast-sinking detritus generally decreased total suboxic and hypoxic volumes, reducing a “large oxygen minimum zone (OMZ)” bias common in global biogeochemical models. Newly aerobic regions at OMZ edges exhibited reduced transfer efficiencies in contrast with global tendencies. Reductions in water column denitrification resulting from improved OMZs improved simulated nitrate deficits relative to phosphate. The carbon flux to the benthos increased by 11% with fast-sinking detritus from fishes and pelagic tunicates, yet simulated benthic fluxes remained on the lower end of observation-based estimates.
Global Earth system models are often enlisted to assess the impacts of climate variability and change on marine ecosystems. In this study, we compare high frequency (daily) outputs of potential ecosystem stressors, such as sea surface temperature and surface pH, and associated variables from an Earth system model (GFDL ESM4.1) with high frequency time series from a global network of moorings to directly assess the capacity of the model to resolve local biogeochemical variability on time scales from daily to interannual. Our analysis indicates variability in surface temperature is most consistent between ESM4.1 and observations, with a Pearson correlation coefficient of 0.93 and bias of 0.40°C, followed by variability in surface salinity. Physical variability is reproduced with greater accuracy than biogeochemical variability, and variability on seasonal and longer time scales is more consistent between the model and observations than higher frequency variability. At the same time, the well-resolved seasonal and longer timescale variability is a reasonably good predictor, in many cases, of the likelihood of extreme events. Despite limited model representation of high frequency variability, model and observation-based assessments of the fraction of days experiencing surface T-pH and T-Ωarag multistressor conditions show reasonable agreement, depending on the stressor combination and threshold definition. We also identify circumstances in which some errors could be reduced by accounting for model biases.
van Denderen, P D., Nis Sand Jacobsen, Ken H Andersen, Julia L Blanchard, Camilla Novaglio, Charles A Stock, and Colleen M Petrik, October 2024: Estimating fishing exploitation rates to simulate global catches and biomass changes of pelagic and demersal fish. Earth's Future, 12(10), DOI:10.1029/2024EF004604. Abstract
Robust projections of future trends in global fish biomass, production and catches are needed for informed fisheries policy in a changing climate. Trust in future projections, however, relies on establishing that models can accurately simulate past relationships between exploitation rates and ecosystem states. In addition, historical simulations are important to describe how the oceans have changed due to fishing. Here we use fisheries catch, catch-only assessment models and effort data to estimate regional fishing exploitation levels, defined as the fishing mortality relative to fishing mortality at maximum sustainable yield (F/FMSY). These estimates are given for large pelagic, forage and demersal fish types across all large marine ecosystems and the high seas between 1961 and 2004; and with a ‘ramp-up’ between 1841 and 1960. We find that global exploitation rates for large pelagic and demersal fish consistently exceed those for forage fish and peak in the late 1980s. We use the rates to globally simulate historical fishing patterns in a mechanistic fish community model. The modeled catch aligns with the reconstructed catch, both for total catch and catch distribution by functional type. Simulations show a clear deviation from an unfished model state, with a 25% reduction in biomass in large pelagic and demersal fish in shelf regions in recent years and a 50% increase in forage fish, primarily due to reduced predation. The simulations can set a baseline for assessing the effect of climate change relative to fishing. The results highlight the influential role of fishing as a primary driver of global fish community dynamics.
Amaya, Dillon J., Michael G Jacox, Melanie R Fewings, Vincent S Saba, Malte F Stuecker, Ryan R Rykaczewski, Andrew C Ross, and Charles A Stock, et al., April 2023: Marine heatwaves need clear definitions so coastal communities can adapt. Nature, 616, DOI:10.1038/d41586-023-00924-2.
Deposition of mineral dust plays an important role in upper-ocean biogeochemical processes, particularly by delivering iron to iron-limited regions. Here we examine the impact of dynamically changing iron deposition on tropical Pacific Ocean biogeochemistry in fully coupled earth system model projections under several emissions scenarios. Projected end-of-21st-century increases in central tropical Pacific dust and iron deposition strengthen with increasing emissions/radiative forcing, and are aligned with projected soil moisture decreases in adjacent land areas and precipitation increases over the equatorial Pacific. Increased delivery of soluble iron results in a reduction in, and eastward contraction of, equatorial Pacific phytoplankton iron limitation and shifts primary production and particulate organic carbon flux projections relative to a high emissions projection (SSP5-8.5) wherein soluble iron deposition is prescribed as a static climatology. These results highlight modeling advances in representing coupled land-air-sea interactions to project basin-scale patterns of ocean biogeochemical change.
Gomez, Fabien A., Sang-Ki Lee, Charles A Stock, Andrew C Ross, Laure Resplandy, Samantha A Siedlecki, Filippos Tagklis, and Joseph E Salisbury, June 2023: RC4USCoast: a river chemistry dataset for regional ocean model applications in the US East Coast, Gulf of Mexico, and US West Coast. Earth System Science Data, 15(5), DOI:10.5194/essd-15-2223-20232223-2234. Abstract
A historical dataset of river chemistry and discharge is presented for 140 monitoring sites along the US East Coast, the Gulf of Mexico, and the US West Coast from 1950 to 2022. The dataset, referred to here as River Chemistry for the U.S. Coast (RC4USCoast), is mostly derived from the Water Quality Database of the US Geological Survey (USGS) but also includes river discharge from the USGS's Surface-Water Monthly Statistics for the Nation and the U.S. Army Corps of Engineers. RC4USCoast provides monthly time series as well as long-term averaged monthly climatological patterns for 21 variables including alkalinity and dissolved inorganic carbon concentration. It is mainly intended as a data product for regional ocean biogeochemical models and carbonate chemistry studies in the US coastal regions. Here we present the method to derive RC4USCoast and briefly describe the rivers' carbonate chemistry patterns. The dataset is publicly available at https://doi.org/10.25921/9jfw-ph50 (Gomez et al., 2022).
Henschke, Natasha, Boris Espinasse, Charles A Stock, Xiao Liu, Nicolas Barrier, and Evgeny A Pakhomov, May 2023: The role of water mass advection in staging of the Southern Ocean Salpa thompsoni populations. Scientific Reports, 13, 7088, DOI:10.1038/s41598-023-34231-7. Abstract
Salpa thompsoni is an important grazer in the Southern Ocean. Their abundance in the western Antarctic Peninsula is highly variable, varying by up to 5000-fold inter-annually. Here, we use a particle-tracking model to simulate the potential dispersal of salp populations from a source location in the Antarctic Circumpolar Current (ACC) to the Palmer Long Term Ecological Research (PAL LTER) study area. Tracking simulations are run from 1998 to 2015, and compared against both a stationary salp population model simulated at the PAL LTER study area and observations from the PAL LTER program. The tracking simulation was able to recreate closely the long-term trend and the higher abundances at the slope stations. The higher abundances observed at slope stations are likely due to the advection of salp populations from a source location in the ACC, highlighting the significant role of water mass circulation in the distribution and abundance of Southern Ocean salp populations.
Planchat, Alban, Lester Kwiatkowski, Laurent Bopp, Olivier Torres, James R Christian, Momme Butenschön, Tomas Lovato, Roland Séférian, Matthew A Chamberlain, Olivier Aumont, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, Tatiana Ilyina, Hiroyuki Tsujino, Kristen M Krumhardt, Jörg Schwinger, Jerry Tjiputra, John P Dunne, and Charles A Stock, April 2023: The representation of alkalinity and the carbonate pump from CMIP5 to CMIP6 Earth system models and implications for the carbon cycle. Biogeosciences, 20(7), DOI:10.5194/bg-20-1195-2023. Abstract
Ocean alkalinity is critical to the uptake of atmospheric carbon in surface waters and provides buffering capacity towards the associated acidification. However, unlike dissolved inorganic carbon (DIC), alkalinity is not directly impacted by anthropogenic carbon emissions. Within the context of projections of future ocean carbon uptake and potential ecosystem impacts, especially through Coupled Model Intercomparison Projects (CMIPs), the representation of alkalinity and the main driver of its distribution in the ocean interior, the calcium carbonate cycle, have often been overlooked. Here we track the changes from CMIP5 to CMIP6 with respect to the Earth system model (ESM) representation of alkalinity and the carbonate pump which depletes the surface ocean in alkalinity through biological production of calcium carbonate and releases it at depth through export and dissolution. We report an improvement in the representation of alkalinity in CMIP6 ESMs relative to those in CMIP5, with CMIP6 ESMs simulating lower surface alkalinity concentrations, an increased meridional surface gradient and an enhanced global vertical gradient. This improvement can be explained in part by an increase in calcium carbonate (CaCO3) production for some ESMs, which redistributes alkalinity at the surface and strengthens its vertical gradient in the water column. We were able to constrain a particulate inorganic carbon (PIC) export estimate of 44–55 Tmol yr−1 at 100 m for the ESMs to match the observed vertical gradient of alkalinity. Reviewing the representation of the CaCO3 cycle across CMIP5/6, we find a substantial range of parameterizations. While all biogeochemical models currently represent pelagic calcification, they do so implicitly, and they do not represent benthic calcification. In addition, most models simulate marine calcite but not aragonite. In CMIP6, certain model groups have increased the complexity of simulated CaCO3 production, sinking, dissolution and sedimentation. However, this is insufficient to explain the overall improvement in the alkalinity representation, which is therefore likely a result of marine biogeochemistry model tuning or ad hoc parameterizations. Although modellers aim to balance the global alkalinity budget in ESMs in order to limit drift in ocean carbon uptake under pre-industrial conditions, varying assumptions related to the closure of the budget and/or the alkalinity initialization procedure have the potential to influence projections of future carbon uptake. For instance, in many models, carbonate production, dissolution and burial are independent of the seawater saturation state, and when considered, the range of sensitivities is substantial. As such, the future impact of ocean acidification on the carbonate pump, and in turn ocean carbon uptake, is potentially underestimated in current ESMs and is insufficiently constrained.
We present the development and evaluation of MOM6-COBALT-NWA12 version 1.0, a 1/12∘ model of ocean dynamics and biogeochemistry in the northwest Atlantic Ocean. This model is built using the new regional capabilities in the MOM6 ocean model and is coupled with the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) biogeochemical model and Sea Ice Simulator version-2 (SIS2) sea ice model. Our goal was to develop a model to provide information to support living-marine-resource applications across management time horizons from seasons to decades. To do this, we struck a balance between a broad, coastwide domain to simulate basin-scale variability and capture cross-boundary issues expected under climate change; a high enough spatial resolution to accurately simulate features like the Gulf Stream separation and advection of water masses through finer-scale coastal features; and the computational economy required to run the long simulations of multiple ensemble members that are needed to quantify prediction uncertainties and produce actionable information. We assess whether MOM6-COBALT-NWA12 is capable of supporting the intended applications by evaluating the model with three categories of metrics: basin-wide indicators of the model's performance, indicators of coastal ecosystem variability and the regional ocean features that drive it, and model run times and computational efficiency. Overall, both the basin-wide and the regional ecosystem-relevant indicators are simulated well by the model. Where notable model biases and errors are present in both types of indicator, they are mainly consistent with the challenges of accurately simulating the Gulf Stream separation, path, and variability: for example, the coastal ocean and shelf north of Cape Hatteras are too warm and salty and have minor biogeochemical biases. During model development, we identified a few model parameters that exerted a notable influence on the model solution, including the horizontal viscosity, mixed-layer restratification, and tidal self-attraction and loading, which we discuss briefly. The computational performance of the model is adequate to support running numerous long simulations, even with the inclusion of coupled biogeochemistry with 40 additional tracers. Overall, these results show that this first version of a regional MOM6 model for the northwest Atlantic Ocean is capable of efficiently and accurately simulating historical basin-wide and regional mean conditions and variability, laying the groundwork for future studies to analyze this variability in detail, develop and improve parameterizations and model components to better capture local ocean features, and develop predictions and projections of future conditions to support living-marine-resource applications across timescales.
Smith, James A., Mercedes Pozo Buil, Barbara A Muhling, Desiree Tommasi, Stephanie Brodie, Timothy H Frawley, Jerome Fiechter, Stefan Koenigstein, Amber Himes-Cornell, Michael A Alexander, Steven J Bograd, Nathalí Cordero-Quirós, Larry B Crowder, Enrique N Curchitser, Stephanie J Green, Natasha A Hardy, Alan C Haynie, Elliot L Hazen, Kirstin Holsman, Gwendal Le Fol, Nerea Lezama-Ochoa, Ryan R Rykaczewski, Charles A Stock, Stephen Stohs, Jonathan Sweeney, Heather Welch, and Michael G Jacox, February 2023: Projecting climate change impacts from physics to fisheries: A view from three California Current fisheries. Progress in Oceanography, 211, 102973, DOI:10.1016/j.pocean.2023.102973. Abstract
Motivated by a need for climate-informed living marine resource management, increased emphasis has been placed on regional end-to-end modeling frameworks designed to project climate impacts on marine ecosystems and evaluate the efficacy of potential management strategies under changing conditions. The ‘Future Seas’ project was initiated with a focus on three fisheries (Pacific sardine, swordfish, and albacore tuna) in the California Current System (CCS). This work leverages a suite of climate, ocean, ecosystem, and economic models to project physical, ecological, and socio-economic change, evaluate management strategies, and quantify uncertainty in model projections. Here we describe the components of the modeling framework, considerations underlying choices made in model development, engagement with stakeholders, and key physical, ecological, and socio-economic results to date, including projections to 2100. Our broad aims are to (i) synthesize a large body of climate and fisheries research that has been conducted, and continues, under the Future Seas umbrella, and (ii) provide insight and recommendations to those pursuing similar efforts for other applications and in other regions. In general, our results indicate that all three species will likely shift their distributions (predominantly poleward) in the future, which impacts accessibility to fishing fleets, spatial management, and quota allocation. For similar integrative climate-to-fisheries projections, we recommend attention is given to: recognizing potential biases arising from differences between the climate products used for ecological model fitting and those used for model projection; how sources of projection uncertainty are prioritized, incorporated, and communicated; and quantitatively linking scenarios – especially socio-economic scenarios – with climate and ecological projections.
Taboada, Fernando G., Jong-Yeon Park, Barbara A Muhling, Desiree Tommasi, Kisei R Tanaka, Ryan R Rykaczewski, Charles A Stock, and Jorge L Sarmiento, March 2023: Anticipating fluctuations of bigeye tuna in the Pacific Ocean from three-dimensional ocean biogeochemistry. Journal of Applied Ecology, 60(3), DOI:10.1111/1365-2664.14346463-479. Abstract
1) Subseasonal to decadal ocean forecasting can make significant contributions to achieving effective management of living marine resources in a changing ocean. Most applications rely on indirect proxies, however, often measured at the ocean surface and lacking a direct mechanistic link to the dynamics of marine populations.
2) Here, we take advantage of three-dimensional, dynamical reconstructions and forecasts of ocean biogeochemistry based on a global Earth system model to hindcast and assess the capacity to anticipate fluctuations in the dynamics of bigeye tuna (Thunnus obesus Lowe) in the Pacific Ocean during the last six decades. We reconstructed spatial patterns in catch per unit effort (CPUE) through the combination of physiological indices capturing both habitat preferences and physiological tolerance limits in bigeye tuna.
3) Our analyses revealed a sequence of four distinct regimes characterized by changes in the zonal distribution and average CPUE of bigeye tuna in the Pacific Ocean. Habitat models accounting for basin-wide fluctuations in the thermal structure and oxygen concentration throughout the water column captured interannual fluctuations in CPUE and regime switches that models based solely on surface information were unable to reproduce. Decade-long forecast experiments further suggested that forecasts of three-dimensional biogeochemical information might enable anticipation of fluctuations in bigeye tuna several years ahead.
4) Synthesis and applications. Together, our results reveal the impact of variability of biogeochemical conditions in the ocean interior on the dynamics of bigeye tuna on the Pacific Ocean, raising concerns about the future impact of ocean warming and deoxygenation. The results also lend support to incorporating subsurface biogeochemical information into ecological forecasts to implement efficient dynamic management strategies and promote the sustainable use of marine living resources.
Tang, Weiyi, Bess B Ward, Michael Beman, Laura Bristow, Darren Clark, S E Fawcett, Claudia Frey, François Fripiat, Gerhard J Herndl, Mhlangabezi Mdutyana, Fabien Paulot, Xuefeng Peng, Alyson E Santoro, Takuhei Shiozaki, Eva Sintes, Charles A Stock, Xin Sun, Xianhui S Wan, Min N Xu, and Yao Zhang, November 2023: Database of nitrification and nitrifiers in the global ocean. Earth System Science Data, 15(11), DOI:10.5194/essd-15-5039-20235039-5077. Abstract
As a key biogeochemical pathway in the marine nitrogen cycle, nitrification (ammonia oxidation and nitrite oxidation) converts the most reduced form of nitrogen – ammonium–ammonia (NH+4–NH3) – into the oxidized species nitrite (NO−2) and nitrate (NO−3). In the ocean, these processes are mainly performed by ammoniaoxidizing archaea (AOA) and bacteria (AOB) and nitrite-oxidizing bacteria (NOB). By transforming nitrogen speciation and providing substrates for nitrogen removal, nitrification affects microbial community structure; marine productivity (including chemoautotrophic carbon fixation); and the production of a powerful greenhouse gas, nitrous oxide (N2O). Nitrification is hypothesized to be regulated by temperature, oxygen, light, substrate concentration, substrate flux, pH and other environmental factors. Although the number of field observations from various oceanic regions has increased considerably over the last few decades, a global synthesis is lacking, and understanding how environmental factors control nitrification remains elusive. Therefore, we have compiled a database of nitrification rates and nitrifier abundance in the global ocean from published literature and unpublished datasets. This database includes 2393 and 1006 measurements of ammonia oxidation and nitrite oxidation rates and 2242 and 631 quantifications of ammonia oxidizers and nitrite oxidizers, respectively. This community effort confirms and enhances our understanding of the spatial distribution of nitrification and nitrifiers and their corresponding drivers such as the important role of substrate concentration in controlling nitrification rates and nitrifier abundance. Some conundrums are also revealed, including the inconsistent observations of light limitation and high rates of nitrite oxidation reported from anoxic waters. This database can be used to constrain the distribution of marine nitrification, to evaluate and improve biogeochemical models of nitrification, and to quantify the impact of nitrification on ecosystem functions like marine productivity and N2O production. This database additionally sets a baseline for comparison with future observations and guides future exploration (e.g., measurements in the poorly sampled regions such as the Indian Ocean and method comparison and/or standardization). The database is publicly available at the Zenodo repository: https://doi.org/10.5281/zenodo.8355912 (Tang et al., 2023).
van Denderen, P D., Aurore A Maureaud, Ken H Andersen, Sarah K Gaichas, Martin Lindegren, Colleen M Petrik, Charles A Stock, and Jeremy Collie, September 2023: Demersal fish biomass declines with temperature across productive shelf seas. Global Ecology and Biogeography, 32(10), DOI:10.1111/geb.13732. Abstract
Theory predicts fish community biomass to decline with increasing temperature due to higher metabolic losses resulting in less efficient energy transfer in warm-water food webs. However, whether these metabolic predictions explain observed macroecological patterns in fish community biomass is virtually unknown. Here, we test these predictions by examining the variation in demersal fish biomass across productive shelf regions.
Sudden shifts in marine plankton communities in response to environmental changes are of special concern because of their low predictability and high potential impacts on ocean ecosystems. We explored how anthropogenic climate change influences the spatial extent and frequency of changepoints in plankton populations by comparing the behavior of a plankton community in a coupled Earth system model under pre-industrial, historical 20th century, and projected 21st century forcing. The ocean areas where surface ocean temperature, nutrient concentrations, and different plankton types exhibited changepoints expanded over time. In contrast, regional hotspots where changepoints occur frequently largely disappeared. Heterotrophy and larger organism sizes were associated with more changepoints. In the pre-industrial and 20th century, plankton changepoints were associated with shifts in physical fronts, and more often with changepoints for iron and silicate than for nitrate and phosphate. In the 21st century, climate change disrupts these interannual-variability-driven changepoint patterns. Together, our results suggest anthropogenic climate change may drive less frequent but more widespread changepoints simultaneously affecting several components of pelagic food webs.
Caracappa, Joseph C., Andrew Beet, Sarah K Gaichas, R J Gamble, Kimberly Hyde, S I Large, R E Morse, Charles A Stock, and Vincent S Saba, September 2022: A northeast United States Atlantis marine ecosystem model with ocean reanalysis and ocean color forcing. Ecological Modelling, 471, 110038, DOI:10.1016/j.ecolmodel.2022.110038. Abstract
The northeast United States Atlantis model (NEUSv2) is an end-to-end ecosystem model that can simulate biogeochemical, ecological, fishery, management, and socio-economic processes within marine ecosystems. As a major update to the original model, NEUSv2 includes changes to the model's functional group definitions and forcing data. NEUSv2 is the first Atlantis model to use a satellite-ocean-color-derived phytoplankton size class model that was tuned specifically for the region to force marine primary production. Additionally, physical ocean variables (currents, temperature, and salinity) were updated using a high-resolution global ocean reanalysis. Despite its coarse resolution, NEUSv2 was capable of reproducing the broad spatial patterns seen in the physical and biological forcing sources, with the exception of some circulation features. NEUSv2 produced plausible zooplankton and planktivore biomass, a stable lower trophic food web, and recent trends in zooplankton biomass. NEUSv2 meets calibration criteria for the persistence and long-term stability of functional group biomass. Given the success of this new Atlantis forcing approach, we detail the observations and challenges regarding spatial scale-related processes, data assimilation, and biological calibration. We also discuss possible tradeoffs with model scope, calibration, and the availability of feedback mechanisms. This NEUSv2 hindcast is well suited for exploring ecosystem-level sensitivity to lower trophic processes and for testing alternative biogeochemical forcing. Further developments will improve model performance for higher trophic levels.
Clark, Suzanna, Katherine A Hubbard, David K Ralston, Dennis J McGillicuddy, Jr, Charles A Stock, Michael A Alexander, and Enrique N Curchitser, June 2022: Projected effects of climate change on Pseudo-nitzschia bloom dynamics in the Gulf of Maine. Journal of Marine Systems, 230, DOI:10.1016/j.jmarsys.2022.103737. Abstract
Worldwide, warming ocean temperatures have contributed to extreme harmful algal bloom events and shifts in phytoplankton species composition. In 2016 in the Gulf of Maine (GOM), an unprecedented Pseudo-nitzschia bloom led to the first domoic-acid induced shellfishery closures in the region. Potential links between climate change, warming temperatures, and the GOM Pseudo-nitzschia assemblage, however, remain unexplored. In this study, a global climate change projection previously downscaled to 7-km resolution for the Northwest Atlantic was further refined with a 1–3-km resolution simulation of the GOM to investigate the effects of climate change on HAB dynamics. A 25-year time slice of projected conditions at the end of the 21st century (2073–2097) was compared to a 25-year hindcast of contemporary ocean conditions (1994–2018) and analyzed for changes to GOM inflows, transport, and Pseudo-nitzschia australis growth potential. On average, climate change is predicted to lead to increased temperatures, decreased salinity, and increased stratification in the GOM, with the largest changes occurring in the late summer. Inflows from the Scotian Shelf are projected to increase, and alongshore transport in the Eastern Maine Coastal Current is projected to intensify. Increasing ocean temperatures will likely make P. australis growth conditions less favorable in the southern and western GOM but improve P. australis growth conditions in the eastern GOM, including a later growing season in the fall, and a longer growing season in the spring. Combined, these changes suggest that P. australis blooms in the eastern GOM could intensify in the 21st century, and that the overall Pseudo-nitzschia species assemblage might shift to warmer-adapted species such as P. plurisecta or other Pseudo-nitzschia species that may be introduced.
The extension of seasonal to interannual prediction of the physical climate system to include the marine ecosystem has a great potential to inform marine resource management strategies. Along the east coast of Africa, recent findings suggest that skillful Earth system model (ESM)-based chlorophyll predictions may enable anticipation of fisheries fluctuations. The mechanisms underlying skillful chlorophyll predictions, however, were not identified, eroding confidence in potential adaptive management steps. This study demonstrates that skillful chlorophyll predictions up to two years in advance arise from the successful simulation of westward-propagating off-equatorial Rossby waves in the Indian ocean. Upwelling associated with these waves supplies nutrients to the surface layer for the large coastal areas by generating north- and southward propagating waves at the east African coast. Further analysis shows that the off-equatorial Rossby wave is initially excited by wind stress forcing caused by El Niño/Southern Oscillation-Indian Ocean teleconnections.
The El Niño-Southern Oscillation (ENSO) strongly influences phytoplankton in the tropical Pacific, with El Niño conditions suppressing productivity in the equatorial Pacific (EP) and placing nutritional stresses on marine ecosystems. The Geophysical Fluid Dynamics Laboratory's (GFDL) Earth System Model version 4.1 (ESM4.1) captures observed ENSO-chlorophyll patterns (r = 0.57) much better than GFDL's previous ESM2M (r = 0.23). Most notably, the observed post-El Niño “chlorophyll rebound” is substantially improved in ESM4.1 (r = 0.52). We find that an anomalous increase in iron propagation from western Pacific (WP) subsurface to the cold tongue via the equatorial undercurrent (EUC) and subsequent post-El Niño surfacing, unresolved in ESM2M, is the primary driver of chlorophyll rebound. We also find that this chlorophyll rebound is augmented by high post-El Niño dust-iron deposition anomalies in the eastern EP. This post-El Niño chlorophyll rebound provides a previously unrecognized source of marine ecosystem resilience independent from the La Niña that sometimes follows.
Lim, Hyung-Gyu, John P Dunne, Charles A Stock, and Minho Kwon, October 2022: Attribution and predictability of climate-driven variability in global ocean color. Journal of Geophysical Research: Oceans, 127(10), DOI:10.1029/2022JC019121. Abstract
For over two decades, satellite ocean color missions have revealed spatio-temporal variations in marine chlorophyll. Seasonal cycles and interannual changes of the physical environment drive the nutrient and chlorophyll variations. In order to identify contributions of seasonal and interannual components on chlorophyll, the present study investigates total chlorophyll variance (TCV) of a 24 year records (September 1997 to December 2021) across satellite generations. First-order contributions of the seasonal cycle in the mid-latitude (25°–35°) oceans in the Northern and Southern Hemispheres explain 59.5% and 69.9% of TCV, respectively. In contrast, the contribution of seasonal cycle only explain 30.9% in the tropical oceans (20°N–20°S). Both seasonal cycle- and climate-driven variability (26.3%) explain 57.2% on TCV in the tropical oceans. A multiple linear regression model was forced by instantaneous and delayed effects of oceanic memory of eight climate indices based on sea surface temperature anomalies to reconstruct chlorophyll anomalies. Delayed climate effects generally boost the anomaly correlation coefficients (ACC) between the observed and reconstructed chlorophyll timeseries (ACC skills: 0.64 to 0.72 in the Indian Ocean, 0.74 to 0.82 in off-equatorial Northern Pacific, and 0.58 to 0.71 in the off-equatorial Southern Pacific). Such delayed climate effects provide a source of predicted chlorophyll ACC (ACC_predic) skills one season ahead in some ocean regions (ACC_predic skill: 0.63 in the overall tropical ocean, 0.67 in the tropical Pacific, and 0.60 in the Indian Ocean). The attribution of chlorophyll variability indicates promising avenues for improving marine ecosystem predictions with Earth system models by incorporating delayed climate effects.
The pelagic tunicates, gelatinous zooplankton that include salps, doliolids, and appendicularians, are filter feeding grazers thought to produce a significant amount of particulate organic carbon (POC) detritus. However, traditional sampling methods (i.e., nets), have historically underestimated their abundance, yielding an overall underappreciation of their global biomass and contribution to ocean biogeochemical cycles relative to crustacean zooplankton. As climate change is projected to decrease the average plankton size and POC export from traditional plankton food webs, the ecological and biogeochemical role of pelagic tunicates may increase; yet, pelagic tunicates were not resolved in the previous generation of global earth system climate projections. Here we present a global ocean study using a coupled physical-biogeochemical model to assess the impact of pelagic tunicates in the pelagic food web and biogeochemical cycling. We added two tunicate groups, a large salp/doliolid and a small appendicularian to the NOAA-GFDL Carbon, Ocean Biogeochemistry, and Lower Trophics version 2 (COBALTv2) model, which was originally formulated to represent carbon flows to crustacean zooplankton. The new GZ-COBALT simulation was able to simultaneously satisfy new pelagic tunicate biomass constraints and existing ecosystem constraints, including crustacean zooplankton observations. The model simulated a global tunicate biomass of 0.10 Pg C, annual tunicate production of 0.49 Pg C y-1 in the top 100 m, and annual tunicate detritus production of 0.98 Pg C y-1 in the top 100 m. Tunicate-mediated export flux was 0.71 Pg C y-1, representing 11% of the total export flux past 100 m. Overall export from the euphotic zone remained largely constant, with the GZ-COBALT pe-ratio only increasing 5.3% (from 0.112 to 0.118) compared to the COBALTv2 control. While the bulk of the tunicate-mediated export production resulted from the rerouting of phytoplankton- and mesozooplankton-mediated export, tunicates also shifted the overall balance of the upper oceans away from recycling and towards export. Our results suggest that pelagic tunicates play important trophic roles in both directly competing with microzooplankton and indirectly shunting carbon export away from the microbial loop.
Muhling, Barbara A., Stephanie Snyder, Elliot L Hazen, Rebecca Whitlock, Heidi Dewar, Jong-Yeon Park, Charles A Stock, and Barbara A Block, March 2022: Risk and reward in foraging migrations of North Pacific albacore determined from estimates of energy intake and movement costs. Frontiers in Marine Science, DOI:10.3389/fmars.2022.730428. Abstract
North Pacific albacore (Thunnus alalunga) is a commercially important tuna species known to undertake extensive migratory movements between nearshore waters of the California Current and offshore environments in the central Pacific. However, these migration behaviors are highly variable, with some individuals traveling thousands of kilometers within a season, and others largely resident in the southern California Current throughout the year. In this study, we use data from 33 archival-tagged albacore (released between 2003 and 2011) to examine the movements, physiology and ecology of tuna following different migratory pathways. We used direct measurements of body temperature and ambient water temperature from internal archival tags to estimate energy intake via the Heat Increment of Feeding (HIF), the increased internal heat production associated with digestion of a meal. Our results indicate that HIF was variable in space and time, but it was highest for individuals foraging in the offshore North Pacific Transition Zone and southern California Current during spring and summer, and lowest in the Transition Zone in fall. None of the migratory strategies examined appeared to confer consistently higher energetic benefits than the others. Fish remaining resident in the southern California Current year-round incurred lower migration costs, and could access favorable foraging conditions off Baja California in spring and summer. In contrast, fish which undertook longer migrations had much higher energetic costs during periods of faster transit times, but were able to reach highly productive foraging areas in the central and western Pacific. HIF was generally higher in larger fish, and when ambient temperatures were cooler, but was not strongly correlated with other environmental covariates. Our analyses offer new avenues for studying the physiology of wild tuna populations, and can complement diet and isotopic studies to further understanding of fish ecology.
Ross, Andrew C., and Charles A Stock, October 2022: Probabilistic extreme SST and marine heatwave forecasts in Chesapeake Bay: A forecast model, skill assessment, and potential value. Frontiers in Marine Science, 9:896961, DOI:10.3389/fmars.2022.896961. Abstract
We test whether skillful 35-day probabilistic forecasts of estuarine sea surface temperature (SST) are possible and whether these forecasts could potentially be used to reduce the economic damages associated with extreme SST events. Using an ensemble of 35-day retrospective forecasts of atmospheric temperature and a simple model that predicts daily mean SST from past SST and forecast atmospheric temperature, we create an equivalent ensemble of retrospective SST forecasts. We compare these SST forecasts with reference forecasts of climatology and damped persistence and find that the SST forecasts are skillful for up to two weeks in the summer. Then, we post-process the forecasts using nonhomogeneous Gaussian regression and assess whether the resulting calibrated probabilistic forecasts are more accurate than the probability implied by the raw model ensemble. Finally, we use an idealized framework to assess whether these probabilistic forecasts can valuably inform decisions to take protective action to mitigate the effects of extreme temperatures and heatwaves. We find that the probabilistic forecasts provide value relative to a naive climatological forecast for 1-2 weeks of lead time, and the value is particularly high in cases where the cost of protection is small relative to the preventable losses suffered when a heatwave occurs. In most cases, the calibrated probabilistic forecasts are also more valuable than deterministic forecasts based on the ensemble mean and naive probabilistic forecasts based on damped persistence. Probabilistic SST forecasts could provide substantial value if applied to adaptively manage the rapid impacts of extreme SSTs, including managing the risks of catch-and-release mortality in fish and Vibrio bacteria in oysters.
Xue, Tianfei, I Frenger, A Oschlies, Charles A Stock, W Koeve, Jasmin G John, and A E Friederike Prowe, June 2022: Mixed layer depth promotes trophic amplification on a seasonal scale. Geophysical Research Letters, 49(12), DOI:10.1029/2022GL098720. Abstract
The Humboldt Upwelling System is of global interest due to its importance to fisheries, though the origin of its high productivity remains elusive. In regional physical-biogeochemical model simulations, the seasonal amplitude of mesozooplankton net production exceeds that of phytoplankton, indicating “seasonal trophic amplification.” An analytical approach identifies amplification to be driven by a seasonally varying trophic transfer efficiency due to mixed layer variations. The latter alters the vertical distribution of phytoplankton and thus the zooplankton and phytoplankton encounters, with lower encounters occurring in a deeper mixed layer where phytoplankton are diluted. In global model simulations, mixed layer depth appears to affect trophic transfer similarly in other productive regions. Our results highlight the importance of mixed layer depth for trophodynamics on a seasonal scale with potential significant implications, given mixed layer depth changes projected under climate change.
Cheng, Wei, Albert Hermann, Anne B Hollowed, Kirstin Holsman, Kelly A Kearney, Darren J Pilcher, Charles A Stock, and Kerim Y Aydin, November 2021: Eastern Bering Sea shelf environmental and lower trophic level responses to climate forcing: Results of dynamical downscaling from CMIP6. Deep Sea Research Part II: Topical Studies in Oceanography, 193, DOI:10.1016/j.dsr2.2021.104975. Abstract
In this study we present projected changes in the Eastern Bering Sea shelf (EBS) biophysical processes in response to climate forcing scenarios from the Coupled Model Intercomparison Phase 6 (CMIP6). These changes are obtained by dynamical downscaling using a Bering Sea regional model. Surface atmospheric and ocean boundary forcing from three Earth System Models (ESMs) in CMIP6, and a low and a high emission scenario of Shared Socioeconomic Pathway (SSP126 and SSP585) of each of the ESMs are considered. Ensemble mean results suggest that, contrary to an anticipated increase in ocean stratification under warming, diminishing ice cover in response to climate forcing and resultant reduced surface freshening weakens EBS stratification in the melt season. Modeled ensemble mean phytoplankton and zooplankton biomass on the EBS exhibits subsurface maxima during the growing season; the amplitude of these maxima decreases with warming, along with a reduction in primary productivity and oxygen concentration over much of the EBS water column. Phenology of both phytoplankton and zooplankton biomass on the EBS shifts earlier, leading to an increase (decrease) in biomass averaged between April–July (August–November), while annually averaged biomass decreases under warming. Projected changes of primary and secondary plankton biomass at the end of the 21st century are not well separated between the SSP126 and SSP585 scenario in light of the large across model spread under each scenario. The projected ensemble mean warming amplitude of the EBS summer bottom temperature is largely unchanged between results forced by the Coupled Model Intercomparison Phase 5 Representative Concentration Pathway 8.5 (CMIP5 RCP8.5) and CMIP6 SSP585 scenarios. Likewise, the reduction rate of annual mean phytoplankton and large zooplankton biomass are comparable between RCP8.5 and SSP585 projections, even though the absolute amplitudes of biomass are sensitive to modeling parameters such as the solar irradiance attenuation curve. Hence, within the Bering Sea dynamical downscaling framework, projected long-term warming trends in EBS bottom temperature and plankton biomass reduction rates are robust responses to climate forcing.
Efforts to manage living marine resources (LMRs) under climate change need projections of future ocean conditions, yet most global climate models (GCMs) poorly represent critical coastal habitats. GCM utility for LMR applications will increase with higher spatial resolution but obstacles including computational and data storage costs, obstinate regional biases, and formulations prioritizing global robustness over regional skill will persist. Downscaling can help address GCM limitations, but significant improvements are needed to robustly support LMR science and management. We synthesize past ocean downscaling efforts to suggest a protocol to achieve this goal. The protocol emphasizes LMR-driven design to ensure delivery of decision-relevant information. It prioritizes ensembles of downscaled projections spanning the range of ocean futures with durations long enough to capture climate change signals. This demands judicious resolution refinement, with pragmatic consideration for LMR-essential ocean features superseding theoretical investigation. Statistical downscaling can complement dynamical approaches in building these ensembles. Inconsistent use of bias correction indicates a need for objective best practices. Application of the suggested protocol should yield regional ocean projections that, with effective dissemination and translation to decision-relevant analytics, can robustly support LMR science and management under climate change.
du Pontavice, Hubert, Didier Gascuel, Gabriel Reygondeau, Charles A Stock, and William W L Cheung, June 2021: Climate-induced decrease in biomass flow in marine food webs may severely affect predators and ecosystem production. Global Change Biology, 27(11), DOI:10.1111/gcb.15576. Abstract
Climate change impacts on marine life in the world ocean are expected to accelerate over the 21st century, affecting the structure and functioning of food webs. We analyzed a key aspect of this issue, focusing on the impact of changes in biomass flow within marine food webs and the resulting effects on ecosystem biomass and production. We used a modeling framework based on a parsimonious quasi-physical representation of biomass flow through the food web, to explore the future of marine consumer biomass and production at the global scale over the 21st century. Biomass flow is determined by three climate-related factors: primary production entering the food web, trophic transfer efficiency describing losses in biomass transfers from one trophic level (TL) to the next, and flow kinetic measuring the speed of biomass transfers within the food web. Using climate projections of three earth system models, we calculated biomass and production at each TL on a 1° latitude ×1° longitude grid of the global ocean under two greenhouse gas emission scenarios. We show that the alterations of the trophic functioning of marine ecosystems, mainly driven by faster and less efficient biomass transfers and decreasing primary production, would lead to a projected decline in total consumer biomass by 18.5% by 2090–2099 relative to 1986–2005 under the “no mitigation policy” scenario. The projected decrease in transfer efficiency is expected to amplify impacts at higher TLs, leading to a 21.3% decrease in abundance of predators and thus to a change in the overall trophic structure of marine ecosystems. Marine animal production is also projected to decline but to a lesser extent than biomass. Our study highlights that the temporal and spatial projected changes in biomass and production would imply direct repercussions on the future of world fisheries and beyond all services provided by Ocean.
Eddy, Tyler D., Joey R Bernhardt, Julia L Blanchard, William W L Cheung, Mathieu Colléter, Hubert du Pontavice, Elizabeth A Fulton, Didier Gascuel, Kelly A Kearney, Colleen M Petrik, Tilla Roy, Ryan R Rykaczewski, Rebecca L Selden, Charles A Stock, Colette C C Wabnitz, and Reg A Watson, January 2021: Energy Flow Through Marine Ecosystems: Confronting Transfer Efficiency. Trends in Ecology and Evolution, 36(1), DOI:10.1016/j.tree.2020.09.006. Abstract
Transfer efficiency is the proportion of energy passed between nodes in food webs. It is an emergent, unitless property that is difficult to measure, and responds dynamically to environmental and ecosystem changes. Because the consequences of changes in transfer efficiency compound through ecosystems, slight variations can have large effects on food availability for top predators. Here, we review the processes controlling transfer efficiency, approaches to estimate it, and known variations across ocean biomes. Both process-level analysis and observed macroscale variations suggest that ecosystem-scale transfer efficiency is highly variable, impacted by fishing, and will decline with climate change. It is important that we more fully resolve the processes controlling transfer efficiency in models to effectively anticipate changes in marine ecosystems and fisheries resources.
The region around the main Hawaiian Islands (MHI) is characterized by a permanent thermocline, and numerous processes have been proposed to facilitate phytoplankton blooms in this oligotrophic province. Here, we use a coupled physical-biogeochemical model of the MHI to elucidate some of the different dynamics behind phytoplankton blooms. The model permits submesoscale processes and is integrated for the years 2010–2017 embedded in a physical state-estimate reanalysis using nearly 50 million observations. Model results exhibit good agreement between simulated values and observations at Station ALOHA for physical and biogeochemical parameters. The overall levels and the amplitude of the seasonal cycles are well captured for many variables. We show that variations in net primary production are mainly driven by domain-wide seasonal cycles of light and nitrogen fixers, respectively, as well as short-lived, stochastic bloom events resulting from the formation of eddies to the west of the island of Hawaii. Furthermore, sporadic wind- and current-driven upwelling is resulting in ephemeral enhancements of nearshore phytoplankton blooms mainly on the northeastern side of the islands.
Enhanced riverine delivery of terrestrial nitrogen (N) has polluted many freshwater and coastal ecosystems, degrading drinking water and marine resources. An emerging view suggests a contribution of land N memory effects—impacts of antecedent dry conditions on land N accumulation that disproportionately increase subsequent river N loads. To date, however, such effects have only been explored for several relatively small rivers covering a few episodes. Here we introduce an index for quantifying land N memory effects and assess their prevalence using regional observations and global terrestrial-freshwater ecosystem model outputs. Model analyses imply that land N memory effects are globally prevalent but vary widely in strength. Strong effects reflect large soil dissolved inorganic N (DIN) surpluses by the end of dry years. During the subsequent wetter years, the surpluses are augmented by soil net mineralization pulses, which outpace plant uptake and soil denitrification, resulting in disproportionately increased soil leaching and eventual river loads. These mechanisms are most prominent in areas with high hydroclimate variability, warm climates, and ecosystem disturbances. In 48 of the 118 basins analyzed, strong memory effects produce 43% (21%–88%) higher DIN loads following drought years than following average years. Such a marked influence supports close consideration of prevalent land N memory effects in water-pollution management efforts.
Lim, Hyung-Gyu, Jong-Yeon Park, John P Dunne, and Charles A Stock, et al., May 2021: Importance of human-induced nitrogen flux increases for simulated Arctic warming. Journal of Climate, 34(10), DOI:10.1175/JCLI-D-20-0180.13799-3819. Abstract
Human activities such as fossil fuel combustion, land-use change, nitrogen (N) fertilizer use, emission of livestock, and waste excretion accelerate the transformation of reactive N and its impact on the marine environment. This study elucidates that anthropogenic N fluxes (ANFs) from atmospheric and river deposition exacerbate Arctic warming and sea ice loss via physical–biological feedback. The impact of physical–biological feedback is quantified through a suite of experiments using a coupled climate–ocean–biogeochemical model (GFDL-CM2.1-TOPAZ) by prescribing the preindustrial and contemporary amounts of riverine and atmospheric N fluxes into the Arctic Ocean. The experiment forced by ANFs represents the increase in ocean N inventory and chlorophyll concentrations in present and projected future Arctic Ocean relative to the experiment forced by preindustrial N flux inputs. The enhanced chlorophyll concentrations by ANFs reinforce shortwave attenuation in the upper ocean, generating additional warming in the Arctic Ocean. The strongest responses are simulated in the Eurasian shelf seas (Kara, Barents, and Laptev Seas; 65°–90°N, 20°–160°E) due to increased N fluxes, where the annual mean surface temperature increase by 12% and the annual mean sea ice concentration decrease by 17% relative to the future projection, forced by preindustrial N inputs.
Over the past century, human activities have resulted in substantial global changes that threaten the stability and functionality of coastal habitats. One of these impacts was through nutrient pollution of river runoffs, which have triggered harmful algal blooms and caused low-oxygen conditions in many coastal regions. However, it is challenging for models to simulate coastal impacts of increasing river nutrient loads, especially on a global scale and over a long period of time. Here we take advantage of some recent modeling advances to provide a global perspective on coastal ecosystem responses to increasing river nitrogen loads over the half-century between 1961 and 2010. Overall, we show that the global coastal ocean accumulated more nitrogen over time as river nitrogen loads increased. This caused the primary production of the global coastal system (i.e., the conversion of inorganic to organic materials through photosynthesis) to increase as well. However, we found that the sensitivity of each coastal ecosystem to comparable changes in nitrogen loads varied considerably. This variability was to a large extent related to two factors: the rate of exchange between coastal waters and the adjacent ocean waters, and whether nutrients are limited for phytoplankton to conduct photosynthesis in that system.
McGinty, Niall, Andrew D Barton, Nicholas R Record, Zoe V Finkel, David G Johns, Charles A Stock, and Andrew J Irwin, April 2021: Anthropogenic climate change impacts on copepod trait biogeography. Global Change Biology, 27(7), DOI:10.1111/gcb.154991431-1442. Abstract
Copepods are among the most abundant marine metazoans and form a key link between marine primary producers, higher trophic levels, and carbon sequestration pathways. Climate change is projected to change surface ocean temperature by up to 4°C in the North Atlantic with many associated changes including slowing of the overturning circulation, areas of regional freshening, and increased salinity and reductions in nutrients available in the euphotic zone over the next century. These changes will lead to a restructuring of phytoplankton and zooplankton communities with cascading effects throughout the food web. Here we employ observations of copepods, projected changes in ocean climate, and species distribution models to show how climate change may affect the distribution of copepod species in the North Atlantic. On average species move northeast at a rate of 14.1 km decade−1. Species turnover in copepod communities will range from 5% to 75% with the highest turnover rates concentrated in regions of pronounced temperature increase and decrease. The changes in species range vary according to copepod traits with the largest effects found to occur in the cooling, freshening area in the subpolar North Atlantic south of Greenland and in an area of significant warming along the Scotian shelf. Large diapausing copepods (>2.5 mm) which are higher in lipids and a crucial food source for whales, may have an advantage in the cooling waters due to their life‐history strategy that facilitates their survival in the arctic environment. Carnivorous copepods show a basin wide increase in species richness and show significant habitat area increases when their distribution moves poleward while herbivores see significant habitat area losses. The trait‐specific effects highlight the complex consequences of climate change for the marine food web.
Patterns of population renewal in marine fishes are often irregular and lead to volatile fluctuations in abundance that challenge management and conservation efforts. Here, we examine the relationship between life‐history strategies and recruitment variability in exploited marine fish species using a macroecological approach.
Pozo Buil, Mercedes, Michael G Jacox, Jerome Fiechter, Michael A Alexander, Steven J Bograd, Enrique N Curchitser, Christopher A Edwards, Ryan R Rykaczewski, and Charles A Stock, April 2021: A dynamically downscaled ensemble of future projections for the California Current System. Frontiers in Marine Science, 8, DOI:10.3389/fmars.2021.612874. Abstract
Given the ecological and economic importance of eastern boundary upwelling systems like the California Current System (CCS), their evolution under climate change is of considerable interest for resource management. However, the spatial resolution of global earth system models (ESMs) is typically too coarse to properly resolve coastal winds and upwelling dynamics that are key to structuring these ecosystems. Here we use a high-resolution (0.1°) regional ocean circulation model coupled with a biogeochemical model to dynamically downscale ESMs and produce climate projections for the CCS under the high emission scenario, Representative Concentration Pathway 8.5. To capture model uncertainty in the projections, we downscale three ESMs: GFDL-ESM2M, HadGEM2-ES, and IPSL-CM5A-MR, which span the CMIP5 range for future changes in both the mean and variance of physical and biogeochemical CCS properties. The forcing of the regional ocean model is constructed with a “time-varying delta” method, which removes the mean bias of the ESM forcing and resolves the full transient ocean response from 1980 to 2100. We found that all models agree in the direction of the future change in offshore waters: an intensification of upwelling favorable winds in the northern CCS, an overall surface warming, and an enrichment of nitrate and corresponding decrease in dissolved oxygen below the surface mixed layer. However, differences in projections of these properties arise in the coastal region, producing different responses of the future biogeochemical variables. Two of the models display an increase of surface chlorophyll in the northern CCS, consistent with a combination of higher nitrate content in source waters and an intensification of upwelling favorable winds. All three models display a decrease of chlorophyll in the southern CCS, which appears to be driven by decreased upwelling favorable winds and enhanced stratification, and, for the HadGEM2-ES forced run, decreased nitrate content in upwelling source waters in nearshore regions. While trends in the downscaled models reflect those in the ESMs that force them, the ESM and downscaled solutions differ more for biogeochemical than for physical variables.
Tittensor, Derek P., Camilla Novaglio, Cheryl S Harrison, Ryan F Heneghan, Nicolas Barrier, Daniele Bianchi, Laurent Bopp, Andrea Bryndum-Buchholz, Gregory L Britten, Matthias Büchner, William W L Cheung, Villy Christensen, Marta Coll, John P Dunne, Tyler D Eddy, Jason D Everett, Jose A Fernandes-Salvador, Elizabeth A Fulton, Eric D Galbraith, Didier Gascuel, Jerome Guiet, Jasmin G John, Jason S Link, Heike K Lotze, Olivier Maury, Kelly Ortega-Cisneros, Juliano Palacios-Abrantes, Colleen M Petrik, Hubert du Pontavice, Jonathan Rault, Anthony J Richardson, Lynne Shannon, Yunne-Jai Shin, Jeroen Steenbeek, Charles A Stock, and Julia L Blanchard, October 2021: Next-generation ensemble projections reveal higher climate risks for marine ecosystems. Nature Climate Change, DOI:10.1038/s41558-021-01173-9. Abstract
Projections of climate change impacts on marine ecosystems have revealed long-term declines in global marine animal biomass and unevenly distributed impacts on fisheries. Here we apply an enhanced suite of global marine ecosystem models from the Fisheries and Marine Ecosystem Model Intercomparison Project (Fish-MIP), forced by new-generation Earth system model outputs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6), to provide insights into how projected climate change will affect future ocean ecosystems. Compared with the previous generation CMIP5-forced Fish-MIP ensemble, the new ensemble ecosystem simulations show a greater decline in mean global ocean animal biomass under both strong-mitigation and high-emissions scenarios due to elevated warming, despite greater uncertainty in net primary production in the high-emissions scenario. Regional shifts in the direction of biomass changes highlight the continued and urgent need to reduce uncertainty in the projected responses of marine ecosystems to climate change to help support adaptation planning.
van Denderen, P D., Colleen M Petrik, Charles A Stock, and Ken H Andersen, September 2021: Emergent global biogeography of marine fish food webs. Global Ecology and Biogeography, 30(9), DOI:10.1111/geb.13348. Abstract
Understanding how fish food webs emerge from planktonic and benthic energy pathways that sustain them is an important challenge for predicting fisheries production under climate change and quantifying the role of fish in carbon and nutrient cycling. We examine if a trait-based fish community model using the fish traits of maximum body weight and vertical habitat strategy can meet this challenge by globally representing fish food web diversity.
ROMS, a high-resolution regional ocean model, was used to study how climate change may affect the northwest Atlantic Ocean. A control (CTRL) simulation was conducted for the recent past (1976-2005), and simulations with additional forcing at the surface and lateral boundaries, obtained from three different global climate models (GCMs) using the RCP8.5 scenario, were conducted to represent the future (2070-2099). The climate change response was obtained from the difference between the CTRL and each of the three future simulations.
All three ROMS simulations indicated large increases in sea surface temperatures (SSTs) over most of the domain except off the eastern US seaboard due to weakening of the Gulf Stream. There are also substantial inter-model differences in the response, including a southward shift of the Gulf Stream in one simulation and a slight northward shift in the other two, with corresponding changes in eddy activity. The depth of maximum warming varied among the three simulations, resulting in differences in the bottom temperature response in coastal regions, including the Gulf of Maine and the west Florida Shelf. The surface salinity decreased (increased) in the northern (southern) part of the domain in all three experiments, but in one, the freshening extended much further south in ROMS than in the GCM that provided the large-scale forcing, associated with changes in the well resolved coastal currents. Thus, while high resolution allows for a better representation of currents and bathymetry, the response to climate change can vary considerably depending on the large-scale forcing.
Barton, Andrew D., Fernando Gonzalez Taboada, Angus Atkinson, Claire E Widdicombe, and Charles A Stock, August 2020: Integration of temporal environmental variation by the marine plankton community. Marine Ecology Progress Series, 647, DOI:10.3354/meps13432. Abstract
Theory and observations suggest that low frequency variation in marine plankton populations, or red noise, may arise through cumulative integration of white noise atmospheric forcing by the ocean and its amplification within food webs. Here, we revisit evidence for the integration of stochastic atmospheric variations by comparing the power spectra of time series of atmospheric and oceanographic conditions to the population dynamics of 150 plankton taxa at Station L4 in the Western English Channel. The power spectra of oceanographic conditions (sea surface temperature, surface nitrate) are redder than those of atmospheric forcing (surface wind stress, net heat fluxes) at Station L4. However, plankton populations have power spectral slopes across trophic levels and body sizes that are redder than atmospheric forcing but whiter than oceanographic conditions. While zooplankton have redder spectral slopes than phytoplankton, there is no significant relationship between power spectral slope and body size or generation length. Using a predator-prey model, we show that the whitening of plankton time series relative to oceanographic conditions arises from noisy plankton bloom dynamics in this strongly seasonal system. The model indicates that, for typical predator-prey interactions, where the predator is on average 10 times longer than the prey, grazing leads to a modest reddening of phytoplankton variability by their larger and longer lived zooplankton consumers. Our findings suggest that, beyond extrinsic forcing by the environment, predator-prey interactions play a role in influencing the power spectra of time series of plankton populations.
We describe the baseline coupled model configuration and simulation characteristics of GFDL's Earth System Model Version 4.1 (ESM4.1), which builds on component and coupled model developments at GFDL over 2013–2018 for coupled carbon‐chemistry‐climate simulation contributing to the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's CM4.0 development effort that focuses on ocean resolution for physical climate, ESM4.1 focuses on comprehensiveness of Earth system interactions. ESM4.1 features doubled horizontal resolution of both atmosphere (2° to 1°) and ocean (1° to 0.5°) relative to GFDL's previous‐generation coupled ESM2‐carbon and CM3‐chemistry models. ESM4.1 brings together key representational advances in CM4.0 dynamics and physics along with those in aerosols and their precursor emissions, land ecosystem vegetation and canopy competition, and multiday fire; ocean ecological and biogeochemical interactions, comprehensive land‐atmosphere‐ocean cycling of CO2, dust and iron, and interactive ocean‐atmosphere nitrogen cycling are described in detail across this volume of JAMES and presented here in terms of the overall coupling and resulting fidelity. ESM4.1 provides much improved fidelity in CO2 and chemistry over ESM2 and CM3, captures most of CM4.0's baseline simulations characteristics, and notably improves on CM4.0 in (1) Southern Ocean mode and intermediate water ventilation, (2) Southern Ocean aerosols, and (3) reduced spurious ocean heat uptake. ESM4.1 has reduced transient and equilibrium climate sensitivity compared to CM4.0. Fidelity concerns include (1) moderate degradation in sea surface temperature biases, (2) degradation in aerosols in some regions, and (3) strong centennial scale climate modulation by Southern Ocean convection.
Simulation of coupled carbon‐climate requires representation of ocean carbon cycling, but the computational burden of simulating the dozens of prognostic tracers in state‐of‐the‐art biogeochemistry ecosystem models can be prohibitive. We describe a six‐tracer biogeochemistry module of steady‐state phytoplankton and zooplankton dynamics in Biogeochemistry with Light, Iron, Nutrients and Gas (BLING version 2) with particular emphasis on enhancements relative to the previous version and evaluate its implementation in Geophysical Fluid Dynamics Laboratory's (GFDL) fourth‐generation climate model (CM4.0) with ¼° ocean. Major geographical and vertical patterns in chlorophyll, phosphorus, alkalinity, inorganic and organic carbon, and oxygen are well represented. Major biases in BLINGv2 include overly intensified production in high‐productivity regions at the expense of productivity in the oligotrophic oceans, overly zonal structure in tropical phosphorus, and intensified hypoxia in the eastern ocean basins as is typical in climate models. Overall, while BLINGv2 structural limitations prevent sophisticated application to plankton physiology, ecology, or biodiversity, its ability to represent major organic, inorganic, and solubility pumps makes it suitable for many coupled carbon‐climate and biogeochemistry studies including eddy interactions in the ocean interior. We further overview the biogeochemistry and circulation mechanisms that shape carbon uptake over the historical period. As an initial analysis of model historical and idealized response, we show that CM4.0 takes up slightly more anthropogenic carbon than previous models in part due to enhanced ventilation in the absence of an eddy parameterization. The CM4.0 biogeochemistry response to CO2 doubling highlights a mix of large declines and moderate increases consistent with previous models.
Dutkiewicz, Stephanie, Mark Baird, Stefano Ciavatta, Stephanie A Henson, Anna Hickman, Cecile S Rousseaux, and Charles A Stock, 2020: Chapter 1: Bridging Satellite Ocean Colour Remote Sensing and Biogeochemical/Ecosystem ModellingSynergy between Ocean Colour and Biogeochemical/Ecosystem Models. [Dutkiewicz, S. (ed.)], Dartmouth, NS, Canada: International Ocean Colour Coordinating Group (IOCCG), IOCCG Report Series, No. 19, DOI:10.25607/OBP-711 1-4pp.
Dutkiewicz, Stephanie, Cecile S Rousseaux, Stefano Ciavatta, Charles A Stock, Mark Baird, Fei Chai, Barbara A Muhling, and Marion Gehlen, 2020: Chapter 3: Biogeochemical And Ecosystem Models: What Are They And How Can They Be Used?Synergy between Ocean Colour and Biogeochemical/Ecosystem Models. [Dutkiewicz, S. (ed.)], Dartmouth, NS, Canada: International Ocean Colour Coordinating Group (IOCCG), IOCCG Report Series, No. 19, DOI:10.25607/OBP-711 31-52pp.
Dutkiewicz, Stephanie, Anna Hickman, Colleen Mouw, Cecile S Rousseaux, Stefano Ciavatta, Mark Baird, Charles A Stock, and Fei Chai, 2020: Chapter 4: The (Mis)match between Biogeochemical/Ecosystem Model Variables and Ocean Colour ProductsSynergy between Ocean Colour and Biogeochemical/Ecosystem Models. [Dutkiewicz, S. (ed.)], Dartmouth, NS, Canada: International Ocean Colour Coordinating Group (IOCCG), IOCCG Report Series, No. 19, DOI:10.25607/OBP-711 53-76pp.
Dutkiewicz, Stephanie, Mark Baird, Stefano Ciavatta, Stephanie A Henson, Anna Hickman, Colleen Mouw, Cecile S Rousseaux, and Charles A Stock, 2020: Chapter 9: Summary and RecommendationsSynergy between Ocean Colour and Biogeochemical/Ecosystem Models. [Dutkiewicz, S. (ed.)], Dartmouth, NS, Canada: International Ocean Colour Coordinating Group (IOCCG), IOCCG Report Series, No. 19, DOI:10.25607/OBP-711 145-152pp.
Hauri, Claudine, Cristina Schultz, Katherine Hedstrom, Seth Danielson, Brita Irving, Scott C Doney, Raphael Dussin, Enrique N Curchitser, David F Hill, and Charles A Stock, July 2020: A regional hindcast model simulating ecosystem dynamics, inorganic carbon chemistry and ocean acidification in the Gulf of Alaska. Biogeosciences, 17, DOI:10.5194/bg-17-3837-20203837-3857. Abstract
The coastal ecosystem of the Gulf of Alaska (GOA) is especially vulnerable to the effects of ocean acidification and climate change that can only be understood within the context of the natural variability of physical and chemical conditions. Controlled by its complex bathymetry, iron enriched freshwater discharge, and wind and solar radiation, the GOA is a highly dynamic system that exhibits large inorganic carbon variability from subseasonal to interannual timescales. This variability is poorly understood due to the lack of observations in this expansive and remote region. To improve our conceptual understanding of the system, we developed a new model set-up for the GOA that couples the three-dimensional Regional Oceanic Model System (ROMS), the Carbon, Ocean Biogeochemistry and Lower Trophic (COBALT) ecosystem model, and a high resolution terrestrial hydrological model. Here, we evaluate the model on seasonal to interannual timescales using the best available inorganic carbon observations. The model was particularly successful in reproducing observed aragonite oversaturation and undersaturation of near-bottom water in May and September, respectively. The largest deficiency of the model is perhaps its inability to adequately simulate spring time surface inorganic carbon chemistry, as it overestimates surface dissolved inorganic carbon, which translates into an underestimation of the surface aragonite saturation state at this time. We also use the model to describe the seasonal cycle and drivers of inorganic carbon parameters along the Seward Line transect in under-sampled months. As such, model output suggests that a majority of the near-bottom water along the Seward Line is seasonally under-saturated with regard to aragonite between June and January, as a result of upwelling and remineralization. Such an extensive period of reoccurring aragonite undersaturation may be harmful to CO2 sensitive organisms. Furthermore, the influence of freshwater not only decreases aragonite saturation state in coastal surface waters in summer and fall, but simultaneously also decreases surface pCO2, thereby decoupling the aragonite saturation state from pCO2. The full seasonal cycle and geographic extent of the GOA region is undersampled, and our model results give new and important insights for months of the year and areas that lack in situ inorganic carbon observations.
Kwiatkowski, Lester, O Torres, Laurent Bopp, Olivier Aumont, Matthew A Chamberlain, James R Christian, John P Dunne, Marion Gehlen, Tatiana Ilyina, Jasmin G John, A Lenton, Hongmei Li, Nicole S Lovenduski, James C Orr, Julien Palmieri, Jörg Schwinger, Roland Séférian, and Charles A Stock, et al., July 2020: Twenty-first century ocean warming, acidification, deoxygenation, and upper ocean nutrient decline from CMIP6 model projections. Biogeosciences, 17(13), DOI:10.5194/bg-17-3439-2020. Abstract
Anthropogenic climate change leads to ocean warming, acidification, deoxygenation and reductions in near-surface nutrient concentrations, all of which are expected to affect marine ecosystems. Here we assess projections of these drivers of environmental change over the twenty-first century from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) that were forced under the CMIP6 Shared Socioeconomic Pathways (SSPs). Projections are compared to those from the previous generation (CMIP5) forced under the Representative Concentration Pathways (RCPs). 10 CMIP5 and 13 CMIP6 models are used in the two multi-model ensembles. Under the high-emission scenario SSP5–8.5, the model mean change (2080–2099 mean values relative to 1870–1899) in sea surface temperature, surface pH, subsurface (100–600 m) oxygen concentration and euphotic (0–100 m) nitrate concentration is +3.48 ± 0.78 °C, −0.44 ± 0.005, −13.27 ± 5.28 mmol m−3 and −1.07 ± 0.45 mmol m−3, respectively. Under the low-emission, high-mitigation scenario SSP1–2.6, the corresponding changes are +1.42 ± 0.32 °C, −0.16 ± 0.002, −6.36 ± 2.92 mmol m−3 and −0.53 ± 0.23 mmol m−3. Projected exposure of the marine ecosystem to these drivers of ocean change depends largely on the extent of future emissions, consistent with previous studies. The Earth system models in CMIP6 generally project greater surface warming, acidification, deoxygenation and euphotic nitrate reductions than those from CMIP5 under comparable radiative forcing, with no reduction in inter-model uncertainties. Under the high-emission CMIP5 scenario RCP8.5, the corresponding changes in sea surface temperature, surface pH, subsurface oxygen and euphotic nitrate concentration are +3.04 ± 0.62 °C, −0.38 ± 0.005, −9.51 ± 2.13 mmol m−3 and −0.66 ± 0.49 mmol m−3, respectively. The greater surface acidification in CMIP6 is primarily a consequence of the SSPs having higher associated atmospheric CO2 concentrations than their RCP analogues. The increased projected warming results from a general increase in the climate sensitivity of CMIP6 models relative to those of CMIP5. This enhanced warming results in greater increases in upper ocean stratification in CMIP6 projections, which contributes to greater reductions in euphotic nitrate and subsurface oxygen ventilation.
Luo, Jessica Y., Robert H Condon, and Charles A Stock, et al., September 2020: Gelatinous zooplankton-mediated carbon flows in the global oceans: A data-driven modeling study. Global Biogeochemical Cycles, 34(9), DOI:10.1029/2020GB006704. Abstract
Among marine organisms, gelatinous zooplankton (GZ; cnidarians, ctenophores, and pelagic tunicates) are unique in their energetic efficiency, as the gelatinous body plan allows them to process and assimilate high proportions of oceanic carbon. Upon death, their body shape facilitates rapid sinking through the water column, resulting in carcass depositions on the seafloor (“jelly‐falls”). GZ are thought to be important components of the biological pump, but their overall contribution to global carbon fluxes remains unknown. Using a data‐driven, three‐dimensional, carbon cycle model resolved to a 1° global grid, with a Monte Carlo uncertainty analysis, we estimate that GZ consumed 7.9–13 Pg C y−1 in phytoplankton and zooplankton, resulting in a net production of 3.9–5.8 Pg C y−1 in the upper ocean (top 200 m), with the largest fluxes from pelagic tunicates. Non‐predation mortality (carcasses) comprised 25% of GZ production, and combined with the much greater fecal matter flux, total GZ particulate organic carbon (POC) export at 100 m was 1.6–5.2 Pg C y−1, equivalent to 32–40% of the global POC export. The fast sinking GZ export resulted in a high transfer efficiency (Teff) of 38–62% to 1,000 m and 25–40% to the seafloor. Finally, jelly‐falls at depths >50 m are likely unaccounted for in current POC flux estimates and could increase benthic POC flux by 8–35%. The significant magnitude of and distinct sinking properties of GZ fluxes support a critical yet underrecognized role of GZ carcasses and fecal matter to the biological pump and air‐sea carbon balance.
The imprint of anthropogenic activities on the marine nitrogen (N) cycle remains challenging to represent in global models, in part because of uncertainties regarding the source of marine N to the atmosphere. While N inputs of terrestrial origin present a truly external perturbation, a significant fraction of N deposition over the ocean arises from oceanic ammonia (NH3) outgassing that is subsequently deposited in other ocean regions. Here, we describe advances in the Geophysical Fluid Dynamics Laboratory's (GFDL) Earth System Model 4 (ESM4.1) aimed at improving the representation of the exchange of N between atmosphere and ocean and its response to changes in ocean acidity and N deposition. We find that the simulated present‐day NH3 outgassing (3.1 TgN yr−1) is 7% lower than under preindustrial conditions, which reflects the compensating effects of increasing CO2 (−16%) and N enrichment of ocean waters (+9%). This change is spatially heterogeneous, with decreases in the open ocean (−13%) and increases in coastal regions (+15%) dominated by coastal N enrichment. The ocean outgassing of ammonia is shown to increase the transport of N from N‐rich to N‐poor ocean regions, where carbon export at 100 m increases by 0.5%. The implications of the strong response of NH3 ocean outgassing to CO2 for the budget of NH3 in the remote marine atmosphere and its imprint in ice cores are discussed.
Petrik, Colleen M., and Charles A Stock, et al., November 2020: Large pelagic fish are most sensitive to climate change despite pelagification of ocean food webs. Frontiers in Marine Science, 7, DOI:10.3389/fmars.2020.588482. Abstract
Global climate change is expected to impact ocean ecosystems through increases in temperature, decreases in pH and oxygen, increased stratification, with subsequent declines in primary productivity. These impacts propagate through the food chain leading to amplified effects on secondary producers and higher trophic levels. Similarly, climate change may disproportionately affect different species, with impacts depending on their ecological niche. To investigate how global environmental change will alter fish assemblages and productivity, we used a spatially explicit mechanistic model of the three main fish functional types reflected in fisheries catches (FEISTY) coupled to an Earth system model (GFDL-ESM2M) to make projections out to 2100. We additionally explored the sensitivity of projections to uncertainties in widely used metabolic allometries and their temperature dependence. When integrated globally, the biomass and production of all types of fish decreased under a high emissions scenario (RCP 8.5) compared to mean contemporary conditions. Projections also revealed strong increases in the ratio of pelagic zooplankton production to benthic production, a dominant driver of the abundance of large pelagic fish vs. demersal fish under historical conditions. Increases in this ratio led to a “pelagification” of ecosystems exemplified by shifts from benthic-based food webs toward pelagic-based ones. The resulting pelagic systems, however, were dominated by forage fish, as large pelagic fish suffered from increasing metabolic demands in a warming ocean and from declines in zooplankton productivity that were amplified at higher trophic levels. Patterns of relative change between functional types were robust to uncertainty in metabolic allometries and temperature dependence, though projections of the large pelagic fish had the greatest uncertainty. The same accumulation of trophic impacts that underlies the amplification of productivity trends at higher trophic levels propagates to the projection spread, creating an acutely uncertain future for the ocean’s largest predatory fish.
Most present forecast systems for estuaries predict conditions for only a few days into the future. However, there are many reasons to expect that skillful estuarine forecasts are possible for longer time periods, including increasingly skillful extended atmospheric forecasts, the potential for lasting impacts of atmospheric forcing on estuarine conditions, and the predictability of tidal cycles. In this study, we test whether skillful estuarine forecasts are possible for up to 35 days into the future by combining an estuarine model of Chesapeake Bay with 35‐day atmospheric forecasts from an operational weather model. When compared with both a hindcast simulation from the same estuarine model and with observations, the estuarine forecasts for surface water temperature are skillful up to about two weeks into the future, and the forecasts for bottom temperature, surface and bottom salinity, and density stratification are skillful for all or the majority of the forecast period. Bottom oxygen forecasts are skillful when compared to the model hindcast, but not when compared with observations. We also find that skill for all variables in the estuary can be improved by taking the mean of multiple estuarine forecasts driven by an ensemble of atmospheric forecasts. Finally, we examine the forecasts in detail using two case studies of extreme events, and we discuss opportunities for improving the forecast skill.
Salinas-de-León, Pelayo, S Andrade, C Arnés-Urgellés, J R Bermudez, S Bucaram, S Buglass, F Cerutti, W Cheung, C De la Hoz, V Hickey, G Jíménez-Uzcátegui, I Keith, J R Marín Jarrín, P Martí-Puig, M Medina, A Moya, D J Pauly, D Orellana, R Ostergaard-Klem, Charles A Stock, J Witman, and Boris Worm, May 2020: Evolution of the Galapagos in the Anthropocene. Nature Climate Change, 10, DOI:10.1038/s41558-020-0761-9. Abstract
The combined effects of climate change and other human-induced stressors have severely degraded marine ecosystems worldwide and pose an unprecedented threat to humanity1. There is an urgent need to understand current and future rates of change while attempting to mitigate impact. We argue that the Galapagos Islands, once the inspiration for the ground-breaking theory of evolution by means of natural selection, now in the Anthropocene can serve as a natural laboratory to study co-evolutionary processes between humans and the species we interact with as climate change pushes ecosystems and dependent communities further away from historical baselines.
Séférian, Roland, Sarah Berthet, Andrew Yool, Julien Palmieri, Laurent Bopp, Alessandro Tagliabue, Lester Kwiatkowski, Olivier Aumont, James R Christian, John P Dunne, Marion Gehlen, Tatiana Ilyina, Jasmin G John, Hongmei Li, Matthew C Long, Jessica Y Luo, Hideyuki Nakano, Anastasia Romanou, Jörg Schwinger, and Charles A Stock, et al., August 2020: Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6. Current Climate Change Reports, 6, DOI:10.1007/s40641-020-00160-095-119. Abstract
Purpose of Review:
The changes or updates in ocean biogeochemistry component have been mapped between CMIP5 and CMIP6 model versions, and an assessment made of how far these have led to improvements in the simulated mean state of marine biogeochemical models within the current generation of Earth system models (ESMs).
Recent Findings:
The representation of marine biogeochemistry has progressed within the current generation of Earth system models. However, it remains difficult to identify which model updates are responsible for a given improvement. In addition, the full potential of marine biogeochemistry in terms of Earth system interactions and climate feedback remains poorly examined in the current generation of Earth system models.
Summary:
Increasing availability of ocean biogeochemical data, as well as an improved understanding of the underlying processes, allows advances in the marine biogeochemical components of the current generation of ESMs. The present study scrutinizes the extent to which marine biogeochemistry components of ESMs have progressed between the 5th and the 6th phases of the Coupled Model Intercomparison Project (CMIP).
This contribution describes the ocean biogeochemical component of the Geophysical Fluid Dynamics Laboratory's Earth System Model 4.1 (GFDL‐ESM4.1), assesses GFDL‐ESM4.1's capacity to capture observed ocean biogeochemical patterns, and documents its response to increasing atmospheric CO2. Notable differences relative to the previous generation of GFDL ESM's include enhanced resolution of plankton food web dynamics, refined particle remineralization, and a larger number of exchanges of nutrients across Earth system components. During model spin‐up, the carbon drift rapidly fell below the 10 Pg C per century equilibration criterion established by the Coupled Climate‐Carbon Cycle Model Intercomparison Project (C4MIP). Simulations robustly captured large‐scale observed nutrient distributions, plankton dynamics, and characteristics of the biological pump. The model overexpressed phosphate limitation and open ocean hypoxia in some areas but still yielded realistic surface and deep carbon system properties, including cumulative carbon uptake since preindustrial times and over the last decades that is consistent with observation‐based estimates. The model's response to the direct and radiative effects of a 200% atmospheric CO2 increase from preindustrial conditions (i.e., years 101–120 of a 1% CO2 yr−1 simulation) included (a) a weakened, shoaling organic carbon pump leading to a 38% reduction in the sinking flux at 2,000 m; (b) a two‐thirds reduction in the calcium carbonate pump that nonetheless generated only weak calcite compensation on century time‐scales; and, in contrast to previous GFDL ESMs, (c) a moderate reduction in global net primary production that was amplified at higher trophic levels. We conclude with a discussion of model limitations and priority developments.
Stock, Charles A., and Stefano Ciavatta, 2020: Chapter 5: Ocean Colour for Model Skill AssessmentSynergy between Ocean Colour and Biogeochemical/Ecosystem Models. [Dutkiewicz, S. (ed.)], Dartmouth, NS, Canada: International Ocean Colour Coordinating Group (IOCCG), IOCCG Report Series, No. 19, DOI:10.25607/OBP-711 77-94pp.
Tanaka, Kisei R., M P Torre, Vincent S Saba, Charles A Stock, and Yong Chen, August 2020: An ensemble high‐resolution projection of changes in the future habitat of American lobster and sea scallop in the Northeast US continental shelf. Diversity and Distributions, 26(8), DOI:10.1111/ddi.13069. Abstract
Aim
To address the uncertainty associated with climate‐driven biogeographical changes in commercial fisheries species through an ensemble species distribution modelling (SDM) approach.
Location
Northeast US Continental Shelf Large Marine Ecosystem (NEUS‐LME).
Methods
We combined an ensemble SDM platform (BIOMOD 2) and a high‐resolution global climate model (NOAA GFDL CM2.6) to quantify spatiotemporal changes in habitat of two commercially important species in the Northeast US Continental Shelf Large Marine Ecosystem (NEUS‐LME); American lobster (Homarus americanus); and sea scallop (Placopecten magellanicus). An ensemble SDM was calibrated using multi‐decadal fisheries‐independent surveys (1984–2016). Statistically weighted species‐specific ensemble SDM outputs were combined with 80 years of projected bottom temperature and salinity changes in response to a high greenhouse gas emissions scenario (an annual 1% increase in atmospheric CO2).
Results
Statistically significant changes (p < .05) in habitat suitability for both species were found over a large portion of the study area. Sea scallop undergoes a northward shift over the study period, while American lobster moves further offshore. The ensemble projections showed that several management zones were identified with increases and decreases in species‐specific habitat. Uncertainty due to variations in ensemble member models was also found in the direction of change within each management zone.
Main conclusions
This study provides ensemble estimates of climate‐driven changes and associated uncertainties in the biogeography of two economically important species in the United States. Projected climate change in the NEUS‐LME will pose management challenges, and our ensemble projections provide useful information for climate‐ready management of commercial fisheries.
Substantial interannual variability in marine fish recruitment (i.e., the number of young fish entering a fishery each year) has been hypothesized to be related to whether the timing of fish spawning matches that of seasonal plankton blooms. Environmental processes that control the phenology of blooms, such as stratification, may differ from those that influence fish spawning, such as temperature‐linked reproductive maturation. These different controlling mechanisms could cause the timing of these events to diverge under climate change with negative consequences for fisheries. We use an earth system model to examine the impact of a high‐emissions, climate‐warming scenario (RCP8.5) on the future spawning time of two classes of temperate, epipelagic fishes: “geographic spawners” whose spawning grounds are defined by fixed geographic features (e.g., rivers, estuaries, reefs) and “environmental spawners” whose spawning grounds move responding to variations in environmental properties, such as temperature. By the century's end, our results indicate that projections of increased stratification cause spring and summer phytoplankton blooms to start 16 days earlier on average (±0.05 days SE) at latitudes >40°N. The temperature‐linked phenology of geographic spawners changes at a rate twice as fast as phytoplankton, causing these fishes to spawn before the bloom starts across >85% of this region. “Extreme events,” defined here as seasonal mismatches >30 days that could lead to fish recruitment failure, increase 10‐fold for geographic spawners in many areas under the RCP8.5 scenario. Mismatches between environmental spawners and phytoplankton were smaller and less widespread, although sizable mismatches still emerged in some regions. This indicates that range shifts undertaken by environmental spawners may increase the resiliency of fishes to climate change impacts associated with phenological mismatches, potentially buffering against declines in larval fish survival, recruitment, and fisheries. Our model results are supported by empirical evidence from ecosystems with multidecadal observations of both fish and phytoplankton phenology.
Recent observations have revealed significant fluctuations in near-shore hypoxia in the California Current Ecosystem (CCE). These fluctuations have been linked to changes in the biogeochemical properties (e.g. oxygen and nutrient contents) of the oceanic source waters of the California Current upwelling, and projections suggest the potential for decreased oxygen and increased nutrients in the source water under climate change. We examine both the separate and combined influences of these projected changes through a sequence of perturbation experiments using a regional coupled ocean dynamics/biogeochemistry (BGC) model of the CCE. The direct effect of a projected decline in source water oxygen is to expand the hypoxic area by in winter to in summer. This exceeds the impact of a nitrate enrichment of source waters, which expands the hypoxic area by to via stimulation of nearshore Net Primary Productivity (NPP), increased organic matter export, and subsequent enhanced remineralization and dissolved oxygen (DO) consumption at depth. The combined effect of these perturbations consistently surpasses the sum of the individual impacts, leading to to more hypoxic area. The combined biogeochemical impact greatly exceeds the response resulting from a strengthening in upwelling-favorable winds ( in hypoxic area) or the decreased oxygen solubility associated with a ocean warming (). These results emphasize the importance of improved constraints on dynamic biogeochemical changes projected along the boundaries of shelf ecosystems. While such changes are often viewed as secondary impacts of climate change relative to local warming or stratification changes, they may prove dominant drivers of coastal ecosystem change.
Hervieux, G, Michael A Alexander, Charles A Stock, Michael G Jacox, Kathleen Pegion, E Becker, Frederic Castruccio, and Desiree Tommasi, December 2019: More reliable coastal SST forecasts from the North American multimodel ensemble. Climate Dynamics, 53(12), DOI:10.1007/s00382-017-3652-7. Abstract
The skill of monthly sea surface temperature (SST) anomaly predictions for large marine ecosystems (LMEs) in coastal regions of the United States and Canada is assessed using simulations from the climate models in the North American Multimodel Ensemble (NMME). The forecasts based on the full ensemble are generally more skillful than predictions from even the best single model. The improvement in skill is particularly noteworthy for probability forecasts that categorize SST anomalies into upper (warm) and lower (cold) terciles. The ensemble provides a better estimate of the full range of forecast values than any individual model, thereby correcting for the systematic over-confidence (under-dispersion) of predictions from an individual model. Probability forecasts, including tercile predictions from the NMME, are used frequently in seasonal forecasts for atmospheric variables and may have many uses in marine resource management.
Jacox, Michael G., M J Alexander, Charles A Stock, and G Hervieux, December 2019: On the skill of seasonal sea surface temperature forecasts in the California Current System and its connection to ENSO variability. Climate Dynamics, 53(12), DOI:10.1007/s00382-017-3608-y. Abstract
The California Current System (CCS) is a biologically productive Eastern Boundary Upwelling System that experiences considerable environmental variability on seasonal and interannual timescales. Given that this variability drives changes in ecologically and economically important living marine resources, predictive skill for regional oceanographic conditions is highly desirable. Here, we assess the skill of seasonal sea surface temperature (SST) forecasts in the CCS using output from Global Climate Forecast Systems in the North American Multi-Model Ensemble (NMME), and describe mechanisms that underlie SST predictability. A simple persistence forecast provides considerable skill for lead times up to ~4 months, while skill above persistence is mostly confined to forecasts of late winter/spring and derives primarily from predictable evolution of ENSO-related variability. Specifically, anomalously weak (strong) equatorward winds are skillfully forecast during El Niño (La Niña) events, and drive negative (positive) upwelling anomalies and consequently warm (cold) temperature anomalies. This mechanism prevails during moderate to strong ENSO events, while years of ENSO-neutral conditions are not associated with significant forecast skill in the wind or significant skill above persistence in SST. We find also a strong latitudinal gradient in predictability within the CCS; SST forecast skill is highest off the Washington/Oregon coast and lowest off southern California, consistent with variable wind forcing being the dominant driver of SST predictability. These findings have direct implications for regional downscaling of seasonal forecasts and for short-term management of living marine resources.
Jacox, Michael G., Desiree Tommasi, Michael A Alexander, G Hervieux, and Charles A Stock, July 2019: Predicting the evolution of the 2014-16 California Current System marine heatwave from an ensemble of coupled global climate forecasts. Frontiers in Marine Science, 6(497), DOI:10.3389/fmars.2019.00497. Abstract
Throughout 2014-2016, the California Current System (CCS) was characterized by large and persistent sea surface temperature anomalies (SSTa), which were accompanied by widespread ecological and socioeconomic consequences that have been documented extensively in the scientific literature and in the popular press. This marine heatwave and others have resulted in a heightened awareness of their potential impacts and prompted questions about if and when they may be predictable. Here, we use output from an ensemble of global climate forecast systems to document which aspects of the 2014-2016 CCS heatwave were predictable and how forecast skill, or lack thereof, relates to mechanisms driving the heatwave’s evolution. We focus on four prominent SSTa changes within the 2014-2016 period: (i) the initial onset of anomalous warming in early 2014, (ii) a second rapid SSTa increase in late 2014, (iii) a sharp reduction and subsequent return of warm SSTa in mid-2015, and (iv) another anomalous warming event in early 2016. Models exhibited clear forecast skill for the first and last of these fluctuations, but not the two in the middle. Taken together with the state of knowledge on the dominant forcing mechanisms of this heatwave, our results suggest that CCS SSTa forecast skill derives from predictable evolution of pre-existing SSTa to the west (as in early 2014) and the south (as in early 2016), while the inability of models to forecast wind-driven SSTa in late 2014 and mid-2015 is consistent with the lack of a moderate or strong El Niño or La Niña event preceding those periods. The multi-model mean forecast consistently outperformed a damped persistence forecast, especially during the period of largest SSTa, and skillful CCS forecasts were generally associated with accurate representation of large-scale dynamics. Additionally, a large forecast ensemble (85 members) indicated elevated probabilities for observed SSTa extremes even when ensemble mean forecasts exhibited limited skill. Our results suggest that different types or aspects of marine heat waves are more or less predictable depending on the forcing mechanisms at play, and events that are consistent with predictable ocean responses could inform ecosystem-based management of the ocean.
Nitrogen (N) pollution is shaped by multiple processes, the combined effects of which remain uncertain, particularly in the tropics. We use a global land biosphere model to analyze historical terrestrial-freshwater N budgets, considering the effects of anthropogenic N inputs, atmospheric CO2, land use, and climate. We estimate that globally, land currently sequesters 11 (10–13)% of annual N inputs. Some river basins, however, sequester >50% of their N inputs, buffering coastal waters against eutrophication and society against greenhouse gas-induced warming. Other basins, releasing >25% more than they receive, are mostly located in the tropics, where recent deforestation, agricultural intensification, and/or exports of land N storage can create large N pollution sources. The tropics produce 56 ± 6% of global land N pollution despite covering only 34% of global land area and receiving far lower amounts of fertilizers than the extratropics. Tropical land use should thus be thoroughly considered in managing global N pollution.
Exchanges between coastal and oceanic waters shape both coastal ecosystem processes and signatures that they impart on global biogeochemical cycles. The time‐scales of these exchanges, however, are poorly represented in current‐generation, coarse‐grid climate models. Here we provide a novel global perspective on coastal residence time (CRT) and its spatio‐temporal variability using a new age tracer implemented in global ocean models. Simulated CRTs range widely from several days in narrow boundary currents to multiple years on broader shelves and in semi‐enclosed seas, in agreement with available observations. Overall, CRT is better characterized in high‐resolution models (1/8° and 1/4°) than the coarser (1° and 1/2°) versions. This is in large part because coastal and open ocean grid cells are more directly connected in coarse models, prone to erroneous coastal flushing and an underestimated CRT. Additionally, we find that geometric enclosure of a coastal system places an important constraint on CRT.
Lotze, Heike K., Derek P Tittensor, Andrea Bryndum-Buchholz, Tyler D Eddy, William W L Cheung, Eric D Galbraith, M Barange, Nicolas Barrier, Daniele Bianchi, Julia L Blanchard, Laurent Bopp, Matthias Büchner, C Bulman, D A Carozza, Villy Christensen, Marta Coll, John P Dunne, Elizabeth A Fulton, S Jennings, M C Jones, S Mackinson, Olivier Maury, S Niranen, R Oliveros-Ramos, Tilla Roy, J A Fernandes, Jacob Schewe, Yunne-Jai Shin, T Silva, Jeroen Steenbeek, and Charles A Stock, et al., June 2019: Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change. Proceedings of the National Academy of Sciences, 116(26), DOI:10.1073/pnas.1900194116. Abstract
While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.
Climate variations have a profound impact on marine ecosystems and the communities that depend upon them. Anticipating ecosystem shifts using global Earth system models (ESMs) could enable communities to adapt to climate fluctuations and contribute to long-term ecosystem resilience. We show that newly developed ESM-based marine biogeochemical predictions can skillfully predict satellite-derived seasonal to multiannual chlorophyll fluctuations in many regions. Prediction skill arises primarily from successfully simulating the chlorophyll response to the El Niño–Southern Oscillation and capturing the winter reemergence of subsurface nutrient anomalies in the extratropics, which subsequently affect spring and summer chlorophyll concentrations. Further investigations suggest that interannual fish-catch variations in selected large marine ecosystems can be anticipated from predicted chlorophyll and sea surface temperature anomalies. This result, together with high predictability for other marine-resource–relevant biogeochemical properties (e.g., oxygen, primary production), suggests a role for ESM-based marine biogeochemical predictions in dynamic marine resource management efforts.
Petrik, Colleen M., and Charles A Stock, et al., September 2019: Bottom-up drivers of global patterns of demersal, forage, and pelagic fishes. Progress in Oceanography, 176, DOI:10.1016/j.pocean.2019.102124. Abstract
Large-scale spatial heterogeneity in fisheries production is predominantly controlled by the availability of zooplankton and benthic organisms, which have a complex relationship with primary production. To investigate how cross-ecosystem differences in these drivers determine fish assemblages and productivity, we constructed a spatially explicit mechanistic model of three fish functional types: forage, large pelagic, and demersal fishes. The model is based on allometric scaling principles, includes basic life cycle transitions, and has trophic interactions between the fishes and with their pelagic and benthic food resources. The model was applied to the global ocean, with plankton food web estimates and ocean conditions from a high-resolution earth system model. Further, a simple representation of fishing was included, and led to moderate matches with total, large pelagic, and demersal catches, including re-creation of observed variations in fish catch spanning two orders of magnitude. Our results highlight several ecologically meaningful model sensitivities. First, coexistence between forage and large pelagic fish in productive regions occurred when forage fish survival is promoted via both favorable metabolic allometry and enhanced predator avoidance in adult forage fish. Second, the prominence of demersal fish is highly sensitive to the efficiency of energy transfer to benthic invertebrates. Third, the latitudinal distribution of the total catch is modulated by the temperature dependence of metabolic rates, with increased sensitivity pushing fish biomass toward the poles. Fourth, forage fish biomass is suppressed by strong top-down controls on temperate and subpolar shelves, where mixed assemblages of large pelagic and demersal fishes exerted high predation rates. Last, spatial differences in the dominance of large pelagics vs. demersals is strongly related to the ratio of pelagic zooplankton production to benthic production. We discuss the potential linkages between model misfits and unresolved processes including movement, spawning phenology, seabird and marine mammal predators, and socioeconomically driven fishing pressure, which are identified as priorities for future model development. Ultimately, the model and analyses herein are intended as a baseline for a robust, mechanistic tool to understand, quantify, and predict global fish biomass and yield, now and in a future dominated by climate change and improved fishing technology.
Ross, Andrew C., and Charles A Stock, May 2019: An assessment of the predictability of column minimum dissolved oxygen concentrations in Chesapeake Bay using a machine learning model. Estuarine, Coastal and Shelf Science, 221, DOI:10.1016/j.ecss.2019.03.007. Abstract
Subseasonal to seasonal forecasts have the potential to be a useful tool for managing estuarine fisheries and water quality, and with increasing skill at forecasting conditions at these time scales in the atmosphere and open ocean, skillful forecasts of estuarine salinity, temperature, and biogeochemistry may be possible. In this study, we use a machine learning model to assess the predictability of column minimum dissolved oxygen in Chesapeake Bay at a monthly time scale. Compared to previous models for dissolved oxygen and hypoxia, our model has the advantages of resolving spatial variability and fitting more flexible relationships between dissolved oxygen and the predictor variables. Using a concise set of predictors with established relationships with dissolved oxygen, we find that dissolved oxygen in a given month can be skillfully predicted with knowledge of stratification and mean temperature during the same month. Furthermore, the predictions generated by the model are consistent with expectations from prior knowledge and basic physics. The model reveals that accurate knowledge or skillful forecasts of the vertical density gradient is the key to successful prediction of dissolved oxygen, and prediction skill disappears if stratification is only known at the beginning of the forecast. The lost skill cannot be recovered by replacing stratification as a predictor with variables that have a lagged correlation with stratification (such as river discharge); however, skill is obtainable in many cases if stratification can be forecast with an error of less than about 1 kg m−3. Thus, future research on hypoxia forecasting should focus on understanding and forecasting variations in stratification over subseasonal time scales (between about two weeks and two months).
Stock, Charles A., December 2019: Comparing apples to oranges: Perspectives on satellite-based primary production estimates drawn from a global biogeochemical model. Journal of Marine Research, 77(S1), DOI:10.1357/002224019828474296. Abstract
Net primary production (NPP) by microscopic phytoplankton underpins nearly all marine life, yet global NPP estimates differ substantially. Among satellite-based estimates, variation has been attributed to differing assumptions about the relationships between photosynthesis and sea surface temperature (SST). Maximum chlorophyll (Chl)–specific rates of carbon fixation in the water column (PB opt) increase monotonically with SST in some satellite algorithms, whereas others peak at intermediate values. Understanding and constraining such relationships is challenged by the many direct and indirect relationships between temperature and phytoplankton. In this article, the emergent PB opt-SST relationship was diagnosed in a global biogeochemical simulation and compared with widely used satellite NPP algorithms. The simulated PB opt-SST relationship for the aggregated phytoplankton community was highly significant (r 2= 0.83) and increased monotonically with temperature. The PB opt-SST relationships for small and large phytoplankton, however, were distinct and weaker than the aggregate relationship (r 2 = 0.52 and 0.36, respectively). For small phytoplankton, the inhibitory effect of nutrient limitation in warmer, more stratified waters was moderated by efficient nutrient scavenging. This, combined with photoacclimation and the stimulatory effect of warming on maximum growth produced steep PB opt increases with SST. For large phytoplankton, the need for higher Chl:C in productive regions (because of package effects) and the onset of severe nutrient limitation in warm, stratified regions decreased PB opt relative to small phytoplankton, though PB opt still increased modestly with SST. The PB opt-SST relationships for both small and large phytoplankton overestimated PB opt in nutrient-poor regions and underestimated it in nutrient-rich regions. This bias was greatly reduced in the aggregate relationship because the increased prominence of low-PB opt large phytoplankton in nutrient-rich environments tempered PB opt increases. Results support a strong, monotonically increasing PB opt-SST relationship but emphasize the role of the size structure of the phytoplankton community in shaping the emergent relationship. The implications of these results are discussed in relation to efforts to improve satellite NPP algorithms and partition NPP by phytoplankton size.
Stock, Charles A., William W L Cheung, Jorge L Sarmiento, and Elsie M Sunderland, 2019: Changing Ocean Systems: A Short Synthesis In Predicting Future Oceans: Sustainability of Ocean and Human Systems Amidst Global Environmental Change [Cisneros-Montemayor, A. M., W. W. L. Cheung, and Y. Ota (eds.)], Elsevier, DOI:10.1016/B978-0-12-817945-1.00002-219-34. Abstract
Variations in weather and climate create and interact with ocean fluctuations occurring over days to decades. In some cases these fluctuations are local. In others they stretch across ocean basins. Marine organisms respond to environmental changes in diverse and sometimes dramatic ways. Over the past century natural ocean fluctuations have been augmented by a variety of anthropogenic drivers. The ocean has absorbed vast amounts of carbon dioxide, excess heat arising from the accumulation of greenhouse gases, nutrients from fertilizers, and other pollutants. While this has moderated climate change and pollution impacts on terrestrial systems, it has had diverse consequences for the ocean. This chapter provides a brief overview of ocean changes of particular relevance for marine life, including ocean acidification, warming, melting ice, shifting ocean productivity baselines, deoxygenation, coastal development, and pollution. We highlight contributions from the Nereus Program, and attempt to provide a broad context for the more detailed discussion of select topics in other chapters in this section. Anthropogenic ocean changes pose a considerable challenge to sustaining marine resources. Continued advances in understanding and predicting ocean changes, such as those described herein, are essential for meeting this challenge.
Seasonal to interannual predictions of ecosystem dynamics have the potential to improve the management of living marine resources. Prediction of oceanic net primary production (NPP), the foundation of marine food webs and the biological carbon pump, is particularly promising, with recent analysis suggesting that ecosystem feedback processes may lead to higher predictability of NPP at interannual scales than for physical variables like sea surface temperature (SST). Here, we assessed the potential predictability of oceanic NPP and SST across seasonal to interannual lead times using reduced dimension, linear dynamical spatio-temporal models (rDSTM). This approach combines empirical orthogonal function (EOF) analysis with vector autoregressive (VAR) modeling to simplify the analysis of spatio-temporal data. The rDSTMs were fitted to monthly NPP and SST anomalies derived from 20 years of remote sensing data (1997-2017), considering two alternative algorithms commonly used to estimate NPP (VGPM and Eppley-VGPM) and optimally analyzed SST fields (AVHRR OISST). The local decay of anomalies provided high predictability up to three months, and subsequent interactions with remote forcing significantly extended predictability beyond the initial anomaly decay. Indeed, interactions among spatial modes associated with the propagation of major climate modes, particularly the El Niño-Southern Oscillation (ENSO), extended the predictability horizon above one year in some regions. Patterns of enhanced NPP predictability matched the location of oligotrophic gyres and transition regions between ocean biomes, where fluctuations in biome boundaries generate large biogeochemical perturbations that leave lasting imprints on NPP. In these areas, the predictability horizon for NPP was longer than for SST, although SST was more predictable over large areas of the equatorial and northeast Pacific. Our results support the potential for extending seasonal to interannual physical climate predictions to predict ocean productivity.
Ocean surface winds determine energy, material and momentum fluxes through the air-sea interface. Accounting for wind variability in time and space is thus essential to reliably analyze and simulate ocean circulation and the dynamics of marine ecosystems. Here, we present an assessment of surface winds from three widely used atmospheric reanalysis products (NCEP/NCAR, ERA-Interim and JRA-55) and their corresponding ocean forcing data sets (CORE v2.1, DFS v5.2 and JRA55-do), which include corrections for use in ocean simulations. We compared wind patterns most relevant to ocean circulation (surface wind stress, its curl and estimates of induced vertical upwelling velocity) across global and regional scales, with added emphasis on the main Eastern Boundary Upwelling Ecosystems (EBUEs). All products provided consistent large-scale patterns in surface winds and wind stress, although agreement was reduced for indices involving the calculation of spatial derivatives, like wind stress curl and Ekman pumping. Fidelity with respect to a reference reanalysis based on blended satellite and buoy observations (CCMP v2.0) improved in more recent, higher resolution products like JRA-55 and ERA-Interim. Adjustments applied when deriving ocean forcing data sets from atmospheric reanalysis robustly improved wind speed and wind stress vectors, but degraded wind stress curl (and implied Ekman upwelling) in two of the three ocean forcing products considered (DFS v5.2 and CORE v2.1).
At regional scales, we found significant inconsistencies in equatorial and polar regions, as well as in coastal areas. In EBUEs, upwelling favorable winds were weaker in atmospheric reanalysis products and ocean forcing data sets than estimates based on CCMP v2.0 and QuikSCAT. All reanalysis products featured lower amplitude seasonal cycles and contrasting patterns of low frequency variability within each EBUE, including the presence of sudden changes in mean upwelling only for some products.
Taken together, our results highlight the importance of incorporating uncertainties in wind forcing into ocean simulation experiments and retrospective analysis, and of correcting reanalysis products for ocean forcing data sets. Despite the continued improvement in the quality of wind data sets, prevailing limitations in reanalysis models demonstrate the need to confirm global products against regional measurements whenever possible and improve correction strategies across multiple ocean-relevant wind properties.
The supply of nitrogen is a primary limiting factor for the productivity of the Northeast United States (NEUS) continental shelf. In this study, a 12‐year (1996‐2007) retrospective physical‐biogeochemical simulation over the Northwest Atlantic (NWA) was used to analyze the mean and seasonal NEUS shelf nitrogen budget, including the connections between shelf subregions: the Gulf of Maine/Georges Bank (GoM/GB) and the Mid‐Atlantic Bight (MAB). The model captures the primary mean and seasonal patterns of shelf circulation, nitrate, and plankton dynamics. Results confirm aspects of previous nitrogen budget analyses, including the dominance of offshore nitrogen influxes into the GoM/GB and the prominent role of riverine influxes and sedimentary denitrification in the MAB. However, detailed spatiotemporal analysis of nitrogen fluxes highlights the importance of dispersed inflows of shallow to intermediate depth waters (0‐75m), which can at times exceed the deep nitrogen influx emphasized in previous studies. A seasonal analysis shows a pronounced shift from the net import of nitrogen to the GoM/GB region during late fall and winter, to the net export of nitrogen from the region in the spring and early summer. The MAB, in contrast, consistently exports nitrogen to offshore waters. The prominence of the 0‐75m nitrogen supply has implications for the roles of Labrador Slope Water (LSW) and Atlantic Temperate Slope Water (ATSW) on the NEUS ecosystems, as ATSW has greater nitrate concentrations than LSW at depth, but often less at the surface. Results suggest the need for further study of shallow to intermediate depth inflows beyond those from the Scotian Shelf, particularly during the fall/winter of net nitrogen inflow.
To gain understanding and predict how jellyfish populations will respond to anthropogenic changes, we first need to understand the factors that influence the distribution and abundance of current and historical populations. Hence, we have developed the first bioenergetic-based population model for the ubiquitous jellyfish Aurelia spp. that incorporates both benthic and pelagic life history stages. This model tracks cohorts of both life stages with temperature- and/or consumption-driven relationships for growth, reproduction and mortality. We present herein an initial model application to test hypotheses for the environmental factors that control the onset of strobilation and inter-annual variability in bloom timing and magnitude in Gulf of Mexico jellyfish populations between 1982 and 2007. To recreate the autumnal blooms of Aurelia spp. in the Gulf of Mexico, strobilation must commence while zooplankton biomass is increasing after the annual minimum. Under this scenario, the model simulated seasonal and inter-annual variability of Aurelia spp. biomass that corresponded well with observations. Markedly larger blooms in anomalously warm, high zooplankton autumns resulted from enhanced ephyrae production compounded by enhanced medusa growth under these conditions. This model confirms the importance of the polyp-to-ephyrae transition in regulating jellyfish bloom magnitude and provides a mechanistic model framework which can examine how future jellyfish populations might respond to climate change.
Icebergs and glacial meltwater have been observed to significantly affect chlorophyll concentrations, primary production and particle export locally, yet the quantitative influence of glacial iron on the carbon cycle of the Southern Ocean remains unknown. We analyse the impact of icebergs and glacial meltwater on the Southern Ocean carbon cycle in a global Earth System Model. We consider several simulations spanning low and high bounds of current estimates of glacial iron concentration. We find that a high glacial iron input produces the best agreement with observed iron and chlorophyll distributions. These high glacial iron input results indicate that about 30% of the Southern Ocean particle export production, i.e., the flux of particulate organic matter through the 100 m depth level, is driven by glacial iron sources. This export production is associated with an uptake of 0.14 Pg carbon per year, which reduces carbon outgassing in the Southern Ocean by 30%.
Lipton, Douglas, Madeleine A Rubenstein, Sarah R Weiskopf, Lisa Crozier, Michael J Fogarty, Sarah K Gaichas, Kimberly Hyde, Toni Lyn Morelli, Jeffrey Morisette, Hassan Moustahfid, Roldan Muñoz, Rajendra Poudel, Michelle Staudinger, and Charles A Stock, 2018: Ecosystems, Ecosystem Services, and Biodiversity. In Impacts, Risks, and Adaptation in the United States: Fourth National Climate Assessment, Volume II [Reidmiller, D.R., C.W. Avery, D.R. Easterling, K.E. Kunkel, K.L.M. Lewis, T.K. Maycock, and B.C. Stewart (eds.)], Washington, DC, USA, U.S. Global Change Research Program, DOI:10.7930/NCA4.2018.CH7268-321.
Muhling, Barbara A., Carlos F Gaitán, Charles A Stock, Vincent S Saba, Desiree Tommasi, and Keith W Dixon, March 2018: Potential Salinity and Temperature Futures for the Chesapeake Bay Using a Statistical Downscaling Spatial Disaggregation Framework. Estuaries and Coasts, 41(2), DOI:10.1007/s12237-017-0280-8. Abstract
Estuaries are productive and ecologically important ecosystems, incorporating environmental drivers from watersheds, rivers, and the coastal ocean. Climate change has potential to modify the physical properties of estuaries, with impacts on resident organisms. However, projections from general circulation models (GCMs) are generally too coarse to resolve important estuarine processes. Here, we statistically downscaled near-surface air temperature and precipitation projections to the scale of the Chesapeake Bay watershed and estuary. These variables were linked to Susquehanna River streamflow using a water balance model and finally to spatially resolved Chesapeake Bay surface temperature and salinity using statistical model trees. The low computational cost of this approach allowed rapid assessment of projected changes from four GCMs spanning a range of potential futures under a high CO2 emission scenario, for four different downscaling methods. Choice of GCM contributed strongly to the spread in projections, but choice of downscaling method was also influential in the warmest models. Models projected a ~2–5.5 °C increase in surface water temperatures in the Chesapeake Bay by the end of the century. Projections of salinity were more uncertain and spatially complex. Models showing increases in winter-spring streamflow generated freshening in the Upper Bay and tributaries, while models with decreased streamflow produced salinity increases. Changes to the Chesapeake Bay environment have implications for fish and invertebrate habitats, as well as migration, spawning phenology, recruitment, and occurrence of pathogens. Our results underline a potentially expanded role of statistical downscaling to complement dynamical approaches in assessing climate change impacts in dynamically challenging estuaries.
Ocean chlorophyll concentration, a proxy for phytoplankton, is strongly influenced by internal ocean dynamics such as those associated with El Niño–Southern Oscillation (ENSO). Observations show that ocean chlorophyll responses to ENSO generally lead sea surface temperature (SST) responses in the equatorial Pacific. A long-term global earth system model simulation incorporating marine biogeochemical processes also exhibits a preceding chlorophyll response. In contrast to simulated SST anomalies which significantly lag the wind-driven subsurface heat response to ENSO, chlorophyll anomalies respond rapidly. Iron was found to be the key factor connecting the simulated surface chlorophyll anomalies to the subsurface ocean response. Westerly wind bursts decrease central Pacific chlorophyll by reducing iron supply through wind-driven thermocline deepening, but increase western Pacific chlorophyll by enhancing the influx of coastal iron from the maritime continent. Our results mechanistically support the potential for chlorophyll-based indices to inform seasonal ENSO forecasts beyond previously identified SST-based indices.
Reliable estimates of historical and current biogeochemistry are essential for understanding past ecosystem variability and predicting future changes. Efforts to translate improved physical ocean state estimates into improved biogeochemical estimates, however, are hindered by high biogeochemical sensitivity to transient momentum imbalances that arise during physical data assimilation. Most notably, the breakdown of geostrophic constraints on data assimilation in equatorial regions can lead to spurious upwelling, resulting in excessive equatorial productivity and biogeochemical fluxes. This hampers efforts to understand and predict the biogeochemical consequences of El Niño and La Niña. We develop a strategy to robustly integrate an ocean biogeochemical model with an ensemble coupled-climate data assimilation system used for seasonal to decadal global climate prediction. Addressing spurious vertical velocities requires two steps. First, we find that tightening constraints on atmospheric data assimilation maintains a better equatorial wind stress and pressure gradient balance. This reduces spurious vertical velocities, but those remaining still produce substantial biogeochemical biases. The remainder is addressed by imposing stricter fidelity to model dynamics over data constraints near the equator. We determine an optimal choice of model-data weights that removed spurious biogeochemical signals while benefitting from off-equatorial constraints that still substantially improve equatorial physical ocean simulations. Compared to the unconstrained control run, the optimally constrained model reduces equatorial biogeochemical biases and markedly improves the equatorial subsurface nitrate concentrations and hypoxic area. The pragmatic approach described herein offers a means of advancing earth system prediction in parallel with continued data assimilation advances aimed at fully considering equatorial data constraints.
Tittensor, Derek P., Tyler D Eddy, Heike K Lotze, Eric D Galbraith, William W L Cheung, M Barange, Julia L Blanchard, Laurent Bopp, Andrea Bryndum-Buchholz, Matthias Büchner, C Bulman, D A Carozza, Villy Christensen, Marta Coll, John P Dunne, J A Fernandes, Elizabeth A Fulton, A J Hobday, V Huber, S Jennings, M Jones, P Lehodey, Jason S Link, S Mackinson, Olivier Maury, S Niiranen, R Oliveros-Ramos, Tilla Roy, Jacob Schewe, Yunne-Jai Shin, T Silva, and Charles A Stock, et al., April 2018: A protocol for the intercomparison of marine fishery and ecosystem models: Fish-MIP v1.0. Geoscientific Model Development, 11(4), DOI:10.5194/gmd-11-1421-2018. Abstract
Model intercomparison studies in the climate and Earth sciences communities have been crucial to building credibility and coherence for future projections. They have quantified variability among models, spurred model development, contrasted within- and among-model uncertainty, assessed model fits to historical data, and provided ensemble projections of future change under specified scenarios. Given the speed and magnitude of anthropogenic change in the marine environment and the consequent effects on food security, biodiversity, marine industries, and society, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. Here, we describe the Fisheries and Marine Ecosystem Model Intercomparison Project protocol version 1.0 (Fish-MIP v1.0), part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is a cross-sectoral network of climate impact modellers. Given the complexity of the marine ecosystem, this class of models has substantial heterogeneity of purpose, scope, theoretical underpinning, processes considered, parameterizations, resolution (grain size), and spatial extent. This heterogeneity reflects the lack of a unified understanding of the marine ecosystem and implies that the assemblage of all models is more likely to include a greater number of relevant processes than any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) Coupled Model Intercomparison Project Phase 5 (CMIP5) outputs under prescribed scenarios for historic (from the 1950s) and future (to 2100) time periods; it will be adapted to CMIP phase 6 (CMIP6) in future iterations. It also describes a standardized set of outputs for each participating Fish-MIP model to produce. This enables the broad characterization of differences between and uncertainties within models and projections when assessing climate and fisheries impacts on marine ecosystems and the services they provide. The systematic generation, collation, and comparison of results from Fish-MIP will inform an understanding of the range of plausible changes in marine ecosystems and improve our capacity to define and convey the strengths and weaknesses of model-based advice on future states of marine ecosystems and fisheries. Ultimately, Fish-MIP represents a step towards bringing together the marine ecosystem modelling community to produce consistent ensemble medium- and long-term projections of marine ecosystems.
Turi, G, M J Alexander, Nicole S Lovenduski, Antonietta Capotondi, J Scott, Charles A Stock, John P Dunne, Jasmin G John, and Michael G Jacox, February 2018: Response of O2 and pH to ENSO in the California Current System in a high resolution global climate model. Ocean Science, 14(1), DOI:10.5194/os-14-69-2018. Abstract
We use a novel, high-resolution global climate model (GFDL-ESM2.6) to investigate the influence of warm and cold El Niño/Southern Oscillation (ENSO) events on the physics and biogeochemistry of the California Current System (CalCS). We focus on the effect of ENSO on variations in the O2 concentration and the pH of the coastal waters of the CalCS. An assessment of the CalCS response to six El Niño and seven La Niña events in ESM2.6 reveals significant variations in the response between events. However, these variations overlay a consistent physical and biogeochemical (O2 and pH) response in the composite mean. Focusing on the mean response, our results demonstrate that O2 and pH are affected rather differently in the euphotic zone above ~100 m. The strongest O2 response reaches up to several 100 km offshore, whereas the pH signal occurs only within a ~100 km-wide band along the coast. By splitting the changes in O2 and pH into individual physical and biogeochemical components that are affected by ENSO variability, we found that O2 variability in the surface ocean is primarily driven by changes in surface temperature that affect the O2 solubility. In contrast, surface pH changes are predominantly driven by changes in dissolved inorganic carbon (DIC), which in turn is affected by upwelling, explaining the confined nature of the pH signal close to the coast. Below ~100 m, we find conditions with anomalously low O2 and pH, and by extension also anomalously low aragonite saturation, during La Niña. This result is consistent with findings from previous studies and highlights the stress that the CalCS ecosystem could periodically undergo in addition to impacts due to climate change.
The measured concentration of chlorophyll a in the surface ocean spans four orders of magnitude, from ∼0.01 mg m-3 in the oligotrophic gyres to >10 mg m-3 in coastal zones. Productive regions encompass only a small fraction of the global ocean area yet they contribute disproportionately to marine resources and biogeochemical processes, such as fish catch and coastal hypoxia. These regions and/or the full observed range of chlorophyll concentration, however, are often poorly represented in global earth system models (ESMs) used to project climate change impacts on marine ecosystems. Furthermore, recent high resolution (∼10 km) global earth system simulations suggest that this shortfall is not solely due to coarse resolution (∼100 km) of most global ESMs. By integrating a global biogeochemical model that includes two phytoplankton size classes (typical of many ESMs) into a regional simulation of the California Current System (CCS) we test the hypothesis that a combination of higher spatial resolution and enhanced resolution of phytoplankton size classes and grazer linkages may enable global ESMs to better capture the full range of observed chlorophyll. The CCS is notable for encompassing both oligotrophic (<0.1 mg m-3) and productive (>10 mg m-3) endpoints of the global chlorophyll distribution. As was the case for global high-resolution simulations, the regional high-resolution implementation with two size classes fails to capture the productive endpoint. The addition of a third phytoplankton size class representing a chain-forming coastal diatom enables such models to capture the full range of chlorophyll concentration along a nutrient supply gradient, from highly productive coastal upwelling systems to oligotrophic gyres. Weaker ‘top-down’ control on coastal diatoms results in stronger trophic decoupling and increased phytoplankton biomass, following the introduction of new nutrients to the photic zone. The enhanced representation of near-shore chlorophyll maxima allows the model to better capture coastal hypoxia along the continental shelf of the North American west coast and may improve the representation of living marine resources.
The Gulf Stream (GS) region has intense mesoscale variability that can affect the supply of nutrients to the euphotic zone (Zeu). In this study, a recently developed high-resolution coupled physical-biological model is used to conduct a 25-year simulation in the Northwest Atlantic. The Reynolds decomposition method is applied to quantify the nitrate budget and shows that the mesoscale variability is important to the vertical nitrate supply over the GS region. The decomposition, however, cannot isolate eddy effects from those arising from other mesoscale phenomena. This limitation is addressed by analyzing a large sample of eddies detected and tracked from the 25-year simulation. The eddy composite structures indicate that positive nitrate anomalies within Zeu exist in both cyclonic eddies (CEs) and anticyclonic eddies (ACEs) over the GS region, and are even more pronounced in the ACEs. Our analysis further indicates that positive nitrate anomalies mostly originate from enhanced vertical advective flux rather than vertical turbulent diffusion. The eddy-wind interaction-induced Ekman pumping is very likely the mechanism driving the enhanced vertical motions and vertical nitrate transport within ACEs. This study suggests that the ACEs in GS region may play an important role in modulating the oceanic biogeochemical properties by fueling local biomass production through the persistent supply of nitrate.
Accurate representation of the remineralization of sinking organic matter is crucial for reliable projections of the marine carbon cycle. Both water temperature and oxygen concentration are thought to influence remineralization rates, but limited data constraints have caused disagreement concerning the degree of these influences. We analyse a compilation of POC flux measurements from 19 globally distributed sites. Our results indicate that the attenuation of the flux of particulate organic matter depends on temperature with a Q10 between 1.5 and 2.01, and on oxygen described by a half saturation constant between 4 and 12 μmol/L. We assess the impact of the temperature and oxygen dependence in the biogeochemistry model COBALT, coupled to GFDL's Earth System Model ESM2M. The new remineralization parameterization results in shallower remineralization in the low latitudes but deeper remineralization in the high latitudes, redistributing POC flux towards the poles. It also decreases the volume of the oxygen minimum zones, partly addressing a long-standing bias in global climate models. Extrapolating temperature-dependent remineralization rates to the surface (i.e., beyond the depth range of POC flux data) resulted in rapid recycling and excessive surface nutrients. Surface nutrients could be ameliorated by reducing near surface rates in a manner consistent with bacterial colonization, suggesting the need for improved remineralization constraints within the euphotic zone. The temperature and oxygen dependence cause an additional 10% decrease in global POC flux at 500m depth, but no significant change in global POC flux at 2000m under the RCP8.5 future projection.
Morse, R E., K D Friedland, Desiree Tommasi, Charles A Stock, and Janet A Nye, January 2017: Distinct zooplankton regime shift patterns across ecoregions of the U.S. Northeast continental shelf Large Marine Ecosystem. Journal of Marine Systems, 165, DOI:10.1016/j.jmarsys.2016.09.011. Abstract
We investigated regime shifts in seasonal zooplankton communities of the Northeast continental shelf Large Marine Ecosystem (NES) and its subcomponent ecoregions over a multi-decadal period (1977–2013). Our cross ecoregion analysis shows that regime shifts in different ecoregions often exhibited very distinct characteristics, emphasizing more granular fluctuations in NES plankton communities relative to previous work. Shifts early in the time series generally reflected an increase in abundance levels. The response of zooplankton abundance within fall communities was more similar among ecoregions than for spring communities. The Gulf of Maine exhibited highly distinct patterns from other ecoregions, with regime shifts identified in the early 1980s, early 2000s, and mid-2000s for spring communities. Regime shifts were identified in the early to mid-1990s for the NES, Georges Bank, and the Mid-Atlantic Bight ecoregions, while the fall communities experienced shifts in the early 1990s and late 1980s for the NES and Georges Bank, but in the late 1990s in the Mid-Atlantic Bight. A constrained correspondence analysis of zooplankton community against local and basin-scale climatological indices suggests that water temperature, stratification, and the Atlantic multidecadal oscillation (AMO) were the predominant factors in driving the zooplankton community composition.
Muhling, Barbara A., John Jacobs, Charles A Stock, Carlos F Gaitán, and Vincent S Saba, September 2017: Projections of the future occurrence, distribution, and seasonality of three Vibrio species in the Chesapeake Bay under a high-emission climate change scenario. GeoHealth, 1(7), DOI:10.1002/2017GH000089. Abstract
Illness caused by pathogenic strains of Vibrio bacteria incurs significant economic and health care costs in many areas around the world. In the Chesapeake Bay, the two most problematic species are V. vulnificus and V. parahaemolyticus, which cause infection both from exposure to contaminated water and consumption of contaminated seafood. We used existing Vibrio habitat models, four global climate models, and a recently developed statistical downscaling framework to project the spatiotemporal probability of occurrence of V. vulnificus and V. cholerae in the estuarine environment, and the mean concentration of V. parahaemolyticus in oysters in the Chesapeake Bay by the end of the 21st century. Results showed substantial future increases in season length and spatial habitat for V. vulnificus and V. parahaemolyticus, while projected increase in V. cholerae habitat was less marked and more spatially heterogeneous. Our findings underscore the need for spatially variable inputs into models of climate impacts on Vibrios in estuarine environments. Overall, economic costs associated with Vibrios in the Chesapeake Bay, such as incidence of illness and management measures on the shellfish industry, may increase under climate change, with implications for recreational and commercial uses of the ecosystem.
Silber, G K., M D Lettrich, P O Thomas, J Baker, M Baumgartner, E Becker, P Boveng, Dorothy M Dick, Jerome Fiechter, J Forcada, K A Forney, R Griffis, J A Hare, A J Hobday, D Howell, K L Laidre, Nate Mantua, L Quackenbush, J A Santora, K M Stafford, P Spencer, and Charles A Stock, et al., December 2017: Projecting Marine Mammal Distribution in a Changing Climate. Frontiers in Marine Science, 4(413), DOI:10.3389/fmars.2017.00413. Abstract
Climate-related shifts in marine mammal range and distribution have been observed in some populations; however, the nature and magnitude of future responses are uncertain in novel environments projected under climate change. This poses a challenge for agencies charged with management and conservation of these species. Specialized diets, restricted ranges, or reliance on specific substrates or sites (e.g., for pupping) make many marine mammal populations particularly vulnerable to climate change. High-latitude, predominantly ice-obligate, species have experienced some of the largest changes in habitat and distribution and these are expected to continue. Efforts to predict and project marine mammal distributions to date have emphasized data-driven statistical habitat models. These have proven successful for short time-scale (e.g., seasonal) management activities, but confidence that such relationships will hold for multi-decade projections and novel environments is limited. Recent advances in mechanistic modeling of marine mammals (i.e., models that rely on robust physiological and ecological principles expected to hold under climate change) may address this limitation. The success of such approaches rests on continued advances in marine mammal ecology, behavior, and physiology together with improved regional climate projections. The broad scope of this challenge suggests initial priorities be placed on vulnerable species or populations (those already experiencing declines or projected to undergo ecological shifts resulting from climate changes that are consistent across climate projections) and species or populations for which ample data already exist (with the hope that these may inform climate change sensitivities in less well observed species or populations elsewhere). The sustained monitoring networks, novel observations, and modeling advances required to more confidently project marine mammal distributions in a changing climate will ultimately benefit management decisions across time-scales, further promoting the resilience of marine mammal populations.
Photosynthesis fuels marine food webs, yet differences in fish catch across globally distributed marine ecosystems far exceed differences in net primary production (NPP). We consider the hypothesis that ecosystem-level variations in pelagic and benthic energy flows from phytoplankton to fish, trophic transfer efficiencies, and fishing effort can quantitatively reconcile this contrast in an energetically consistent manner. To test this hypothesis, we enlist global fish catch data that include previously neglected contributions from small-scale fisheries, a synthesis of global fishing effort, and plankton food web energy flux estimates from a prototype high-resolution global earth system model (ESM). After removing a small number of lightly fished ecosystems, stark interregional differences in fish catch per unit area can be explained (r = 0.79) with an energy-based model that (i) considers dynamic interregional differences in benthic and pelagic energy pathways connecting phytoplankton and fish, (ii) depresses trophic transfer efficiencies in the tropics and, less critically, (iii) associates elevated trophic transfer efficiencies with benthic-predominant systems. Model catch estimates are generally within a factor of 2 of values spanning two orders of magnitude. Climate change projections show that the same macroecological patterns explaining dramatic regional catch differences in the contemporary ocean amplify catch trends, producing changes that may exceed 50% in some regions by the end of the 21st century under high-emissions scenarios. Models failing to resolve these trophodynamic patterns may significantly underestimate regional fisheries catch trends and hinder adaptation to climate change.
Tommasi, Desiree, Charles A Stock, A J Hobday, R Methot, Isaac C Kaplan, J P Eveson, Kirstin Holsman, Timothy J Miller, Sarah K Gaichas, Marion Gehlen, A Pershing, Gabriel A Vecchi, Rym Msadek, Thomas L Delworth, C M Eakin, Melissa A Haltuch, Roland Séférian, C M Spillman, J R Hartog, Samantha A Siedlecki, Jameal F Samhouri, Barbara A Muhling, R G Asch, Malin L Pinsky, Vincent S Saba, Sarah B Kapnick, and Carlos F Gaitán, et al., March 2017: Managing living marine resources in a dynamic environment: The role of seasonal to decadal climate forecasts. Progress in Oceanography, 152, DOI:10.1016/j.pocean.2016.12.011. Abstract
Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefitting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystem-relevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.
Tommasi, Desiree, Charles A Stock, Kathleen Pegion, and Gabriel A Vecchi, et al., March 2017: Improved management of small pelagic fisheries through seasonal climate prediction. Ecological Applications, 27(2), DOI:10.1002/eap.1458. Abstract
Populations of small pelagic fish are strongly influenced by climate. The inability of managers to anticipate environment-driven fluctuations in stock productivity or distribution can lead to overfishing and stock collapses, inflexible management regulations inducing shifts in the functional response to human predators, lost opportunities to harvest populations, bankruptcies in the fishing industry, and loss of resilience in the human food supply. Recent advances in dynamical global climate prediction systems allow for sea surface temperature (SST) anomaly predictions at a seasonal scale over many shelf ecosystems. Here we assess the utility of SST predictions at this “fishery relevant” scale to inform management, using Pacific sardine as a case study. The value of SST anomaly predictions to management was quantified under four harvest guidelines (HGs) differing in their level of integration of SST data and predictions. The HG that incorporated stock biomass forecasts informed by skillful SST predictions led to increases in stock biomass and yield, and reductions in the probability of yield and biomass falling below socioeconomic or ecologically acceptable levels. However, to mitigate the risk of collapse in the event of an erroneous forecast, it was important to combine such forecast-informed harvest controls with additional harvest restrictions at low biomass.
Decisions made by fishers and fisheries managers are informed by climate and fisheries observations that now often span more than 50 years. Multi-annual climate forecasts could further inform such decisions if they were skillful in predicting future conditions relative to the 50-year scope of past variability. We demonstrate that an existing multi-annual prediction system skillfully forecasts the probability of next year, the next 1–3 years, and the next 1–10 years being warmer or cooler than the 50-year average at the surface in coastal ecosystems. Probabilistic forecasts of upper and lower seas surface temperature (SST) terciles over the next 3 or 10 years from the GFDL CM 2.1 10-member ensemble global prediction system showed significant improvements in skill over the use of a 50-year climatology for most Large Marine Ecosystems (LMEs) in the North Atlantic, the western Pacific, and Indian oceans. Through a comparison of the forecast skill of initialized and uninitialized hindcasts, we demonstrate that this skill is largely due to the predictable signature of radiative forcing changes over the 50-year timescale rather than prediction of evolving modes of climate variability. North Atlantic LMEs stood out as the only coastal regions where initialization significantly contributed to SST prediction skill at the 1 to 10 year scale.
Barton, Andrew D., Andrew J Irwin, Zoe V Finkel, and Charles A Stock, March 2016: Anthropogenic climate change drives shift and shuffle in North Atlantic phytoplankton communities. Proceedings of the National Academy of Sciences, 113(11), DOI:10.1073/pnas.1519080113. Abstract
Anthropogenic climate change has shifted the biogeography and phenology of many terrestrial and marine species. Marine phytoplankton communities appear sensitive to climate change, yet understanding of how individual species may respond to anthropogenic climate change remains limited. Here, using historical environmental and phytoplankton observations, we characterize the realized ecological niches for 87 North Atlantic diatom and dinoflagellate taxa and project changes in species biogeography between mean historical (1951–2000) and future (2051–2100) ocean conditions. We find that the central positions of the core range of 74% of taxa shift poleward at a median rate of 12.9 km per decade (km⋅dec−1), and 90% of taxa shift eastward at a median rate of 42.7 km⋅dec−1. The poleward shift is faster than previously reported for marine taxa, and the predominance of longitudinal shifts is driven by dynamic changes in multiple environmental drivers, rather than a strictly poleward, temperature-driven redistribution of ocean habitats. A century of climate change significantly shuffles community composition by a basin-wide median value of 16%, compared with seasonal variations of 46%. The North Atlantic phytoplankton community appears poised for marked shift and shuffle, which may have broad effects on food webs and biogeochemical cycles.
Observations indicate that spring and fall phytoplankton blooms on the Eastern Bering Sea (EBS) continental shelf tend to co-vary on inter-annual scales – that is, a year with a strong spring bloom also tends to have a strong fall bloom. Similar co-variability of primary production is also seen in the multi-year (1987–2007) integration of a coupled physical–biological model. Moreover, the modeled seasonal amplitudes of 10-meter chlorophyll-a concentrations at the EBS middle shelf mooring locations, computed using the canonical Redfield ratio and a mean carbon-to-chlorophyll-a ratio, are generally consistent with the in situ mooring measurements. The coupled physical–biological model simulation is used to examine the relative contributions of wind mixing, local nutrient recycling/regeneration, horizontal nutrient advection, and water-column stability to this co-variability. There is no significant correlation between the spring and fall surface wind mixing. Although wind mixing is an important mechanism for bringing nutrients in the lower water column to the surface layers, it is not the mechanism tying the two seasons׳ productivity together. Local regeneration/recycling of the nutrients initially fueling spring production is an important mechanism for spring-to-fall nutrient accumulation in the bottom layers at the middle shelf. Horizontal advection does not appear to be the dominant factor for supplying nutrients to the middle shelf during the spring-to-fall period. Fall primary production in the model is strongly influenced by the lower water-column stability/stratification. Taken together, these results highlight the importance of local recycling/regeneration of nutrients assimilated by spring phytoplankton bloom in linking together the spring and fall primary productions on EBS middle shelf.
Cheung, William W., M C Jones, Gabriel Reygondeau, Charles A Stock, V W Y Lam, and Thomas L Frölicher, April 2016: Structural uncertainty in projecting global fisheries catches under climate change. Ecological Modelling, 325, DOI:10.1016/j.ecolmodel.2015.12.018. Abstract
The global ocean is projected to be warmer, less oxygenated and more acidic in the 21st century relative to the present day, resulting in changes in the biogeography and productivity of marine organisms and ecosystems. Previous studies using a Dynamic Bioclimate Envelope Model (DBEM) projected increases in potential catch in high latitude regions and decreases in tropical regions over the next few decades. A major structural uncertainty of the projected redistribution of species and fisheries catches can be attributed to the habitat suitability algorithms used. Here, we compare the DBEM projections of potential catches of 500 species of exploited marine fishes and invertebrates from 1971 to 2060 using three versions of DBEM that differ by the algorithm used to predict relative habitat suitability: DBEM-Basic, DBEM-Maxent and DBEM-Aquamaps. All the DBEM models have similar skill in predicting the occurrence of exploited species and distribution of observed fisheries production. Globally, the models project a decrease in catch potential of 3% to 13% by 2050 under a high emissions scenario (Representative Concentration Pathway 8.5). For the majority of the modelled species, projections by DBEM-Maxent are less sensitive to changes in ocean properties than those by DBEM-Aquamaps. The mean magnitude of projected changes relative to differences between projections differ between regions, being highest (>1 times the standard deviation) in the tropical regions and Arctic Ocean and lowest in three of the main Eastern Boundary Upwelling regions, the eastern Indian Ocean and the Southern Ocean. These results suggest that the qualitative patterns of changes in catch potential reported in previous studies are not affected by the structural uncertainty of DBEM, particularly in areas where catch potential was projected to be most sensitive to climate change. However, when making projections of fish stocks and their potential catches using DBEM in the future, multiple versions of DBEM should be used to quantify the uncertainty associated with structural uncertainty of the models. Overall, this study contributes to improving projection of future changes in living marine resources by exploring one aspect of the cascade of uncertainty associated with such projections.
Cheung, William W., Thomas L Frölicher, R G Asch, M C Jones, Malin L Pinsky, Gabriel Reygondeau, Keith B Rodgers, Ryan R Rykaczewski, Jorge L Sarmiento, Charles A Stock, and James R Watson, May 2016: Building confidence in projections of the responses of living marine resources to climate change. ICES Journal of Marine Science, 73(5), DOI:10.1093/icesjms/fsv250. Abstract
The Fifth Assessment Report of the Intergovernmental Panel on Climate Change highlights that climate change and ocean acidification are challenging the sustainable management of living marine resources (LMRs). Formal and systematic treatment of uncertainty in existing LMR projections, however, is lacking. We synthesize knowledge of how to address different sources of uncertainty by drawing from climate model intercomparison efforts. We suggest an ensemble of available models and projections, informed by observations, as a starting point to quantify uncertainties. Such an ensemble must be paired with analysis of the dominant uncertainties over different spatial scales, time horizons, and metrics. We use two examples: (i) global and regional projections of Sea Surface Temperature and (ii) projection of changes in potential catch of sablefish (Anoplopoma fimbria) in the 21st century, to illustrate this ensemble model approach to explore different types of uncertainties. Further effort should prioritize understanding dominant, undersampled dimensions of uncertainty, as well as the strategic collection of observations to quantify, and ultimately reduce, uncertainties. Our proposed framework will improve our understanding of future changes in LMR and the resulting risk of impacts to ecosystems and the societies under changing ocean conditions.
Frölicher, Thomas L., Keith B Rodgers, Charles A Stock, and William W L Cheung, August 2016: Sources of uncertainties in 21st century projections of potential ocean ecosystem stressors. Global Biogeochemical Cycles, 30(8), DOI:10.1002/2015GB005338. Abstract
Future projections of potential ocean ecosystem stressors, such as acidification, warming, deoxygenation and changes in ocean productivity, are uncertain due to incomplete understanding of fundamental processes, internal climate variability, and divergent carbon emissions scenarios. This complicates climate change impact assessments. We evaluate the relative importance of these uncertainty sources in projections of potential stressors as a function of projection lead-time and spatial scale. Internally generated climate variability is the dominant source of uncertainty in mid-to-low latitudes and in most coastal Large Marine Ecosystems over the next few decades, suggesting irreducible uncertainty inherent in these short projections. Uncertainty in projections of century-scale global sea surface temperature (SST), global thermocline oxygen, and regional surface pH is dominated by scenario uncertainty, highlighting the critical importance of policy decisions on carbon emissions. In contrast, uncertainty in century-scale projections of net primary productivity (NPP), low oxygen waters, and Southern Ocean SST is dominated by model uncertainty, underscoring the importance of overcoming deficiencies in scientific understanding and improved process representation in Earth system models are critical for making more robust projections of these potential stressors. We also show that changes in the combined potential stressors emerge from the noise in 39% (34 – 44%) of the ocean by 2016-2035 relative to the 1986-2005 reference period and in 54% (50 – 60%) of the ocean by 2076-2095 following a high carbon emissions scenario. Projected large changes in surface pH and SST can be reduced substantially and rapidly with aggressive carbon emission mitigation, but only marginally for oxygen. The regional importance of model uncertainty and internal variability underscores the need for expanded and improved multi-model and large initial condition ensemble projections with Earth system models for evaluating regional marine resource impacts.
Lee, Y J., P A Matrai, Marjorie A M Friedrichs, Vincent S Saba, Olivier Aumont, M Babin, Erik T Buitenhuis, M Chevallier, L de Mora, M Dessert, John P Dunne, I H Ellingsen, Daniel Feldman, R Frouin, Marion Gehlen, T Gorgues, Tatiana Ilyina, M Jin, Jasmin G John, J Lawrence, Manfredi Manizza, C Menkes, C Perruche, V Le Fouest, E E Popova, Anastasia Romanou, A Samuelsen, Jörg Schwinger, Roland Séférian, and Charles A Stock, et al., December 2016: Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models. Journal of Geophysical Research: Oceans, 121(12), DOI:10.1002/2016JC011993. Abstract
The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959–2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free versus ice-influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling.
Tagliabue, Alessandro, Olivier Aumont, R DeAth, John P Dunne, Stephanie Dutkiewicz, Eric D Galbraith, K Misumi, J Keith Moore, A Ridgwell, E Sherman, and Charles A Stock, et al., February 2016: How well do global ocean biogeochemistry models simulate dissolved iron distributions?Global Biogeochemical Cycles, 30(2), DOI:10.1002/2015GB005289. Abstract
Numerical models of ocean biogeochemistry are relied upon to make projections about the impact of climate change on marine resources and test hypotheses regarding the drivers of past changes in climate and ecosystems. In large areas of the ocean, iron availability regulates the functioning of marine ecosystems and hence the ocean carbon cycle. Accordingly, our ability to quantify the drivers and impacts of fluctuations in ocean ecosystems and carbon cycling in space and time relies on first achieving an appropriate representation of the modern marine iron cycle in models. When the iron distributions from thirteen global ocean biogeochemistry models are compared against the latest oceanic sections from the GEOTRACES programme we find that all models struggle to reproduce many aspects of the observed spatial patterns. Models that reflect the emerging evidence for multiple iron sources or subtleties of its internal cycling perform much better in capturing observed features than their simpler contemporaries, particularly in the ocean interior. We show that the substantial uncertainty in the input fluxes of iron results in a very wide range of residence times across models, which has implications for the response of ecosystems and global carbon cycling to perturbations. Given this large uncertainty, iron-fertilisation experiments based on any single current generation model should be interpreted with caution. Improvements to how such models represent iron scavenging and also biological cycling are needed to raise confidence in their projections of global biogeochemical change in the ocean.
Wigington, C H., D Sonderegger, C P D Brussaard, A Buchan, J F Finke, J A Fuhrman, Jay T Lennon, M Middelboe, C A Suttle, and Charles A Stock, et al., January 2016: Re-examination of the relationship between marine virus and microbial cell abundances. Nature Microbiology, 15024, DOI:10.1038/nmicrobiol.2015.24. Abstract
Marine viruses are critical drivers of ocean biogeochemistry, and their abundances vary spatiotemporally in the global oceans, with upper estimates exceeding 108 per ml. Over many years, a consensus has emerged that virus abundances are typically tenfold higher than microbial cell abundances. However, the true explanatory power of a linear relationship and its robustness across diverse ocean environments is unclear. Here, we compile 5,671 microbial cell and virus abundance estimates from 25 distinct marine surveys and find substantial variation in the virus-to-microbial cell ratio, in which a 10:1 model has either limited or no explanatory power. Instead, virus abundances are better described as nonlinear, power-law functions of microbial cell abundances. The fitted scaling exponents are typically less than 1, implying that the virus-to-microbial cell ratio decreases with microbial cell density, rather than remaining fixed. The observed scaling also implies that viral effect sizes derived from ‘representative’ abundances require substantial refinement to be extrapolated to regional or global scales.
Christensen, Villy, Marta Coll, J Buszowski, William W L Cheung, Thomas L Frölicher, Jeroen Steenbeek, Charles A Stock, Reg A Watson, and C J Walters, May 2015: The global ocean is an ecosystem: simulating marine life and fisheries. Global Ecology and Biogeography, 24(5), DOI:10.1111/geb.12281. Abstract
Aim
There has been considerable effort allocated to understanding the impact of climate change on our physical environment, but comparatively little to how life on Earth and ecosystem services will be affected. Therefore, we have developed a spatial–temporal food web model of the global ocean, spanning from primary producers through to top predators and fisheries. Through this, we aim to evaluate how alternative management actions may impact the supply of seafood for future generations.
Location
Global ocean.
Methods
We developed a modelling complex to initially predict the combined impact of environmental parameters and fisheries on global seafood production, and initially evaluated the model's performance through hindcasting. The modelling complex has a food web model as core, obtains environmental productivity from a biogeochemical model and assigns global fishing effort spatially. We tuned model parameters based on Markov chain random walk stock reduction analysis, fitting the model to historic catches. We evaluated the goodness-of-fit of the model to data for major functional groups, by spatial management units and globally.
Results
This model is the most detailed ever constructed of global fisheries, and it was able to replicate broad patterns of historic fisheries catches with best agreement for the total catches and good agreement for species groups, with more variation at the regional level.
Main conclusions
We have developed a modelling complex that can be used for evaluating the combined impact of fisheries and climate change on upper-trophic level organisms in the global ocean, including invertebrates, fish and other large vertebrates. The model provides an important step that will allow global-scale evaluation of how alternative fisheries management measures can be used for mitigation of climate change.
The world’s major Eastern Boundary Currents (EBC)
are critically important areas for global fisheries. Computational
limitations have divided past EBC modeling
into two types: high-resolution regional approaches
that resolve the strong mesoscale structures involved;
and coarse global approaches that represent the largescale
context for EBCs but crudely resolve only the
largest scales of their local manifestation. These latter
global studies have illustrated the complex mechanisms
involved in the climate change and acidification response
in these regions, with the EBC response dominated not
by local adjustments but large-scale reorganization of
ocean circulation through remote forcing of water mass
supply pathways. While qualitatively illustrating the limitations
of regional high-resolution studies in long-term
projections, these studies lack the ability to robustly
quantify change because of the inability of these models
to represent the baseline mesoscale structures of EBCs.
In the present work, we compare current generation
coarse resolution (1˚) and a prototype next generation
high-resolution (1/10˚) Earth System Models (ESMs)
from NOAA ’s Geophysical Fluid Dynamics Laboratory
in representing the four major EBCs. We review the
long-known temperature biases that the coarse models
suffer in being unable to represent the timing and intensity
of upwelling-favorable winds. In promising contrast,
we show that the high-resolution prototype is capable
of representing not only the overall mesoscale structure
in physical and biogeochemical fields, but also the
appropriate offshore extent of temperature anomalies
and other EBC characteristics. In terms of representation
of large-scale circulation, results were mixed, with the
high-resolution prototype addressing some, but not all,
of the biases in the coarse-resolution ESM. The ability
to simulate EBCs in the global context at high resolution
in global ESMs represents a fundamental milestone
towards both seasonal to interannual ecological forecasting
and long-term projection of climate, ecosystem, and
acidification baselines and sensitivity.
http://www.calcofi.org/publications/calcofireports/v56/Vol56-Dunne.web.72-75.pdf
Friedland, K D., R T Leaf, J Kane, Desiree Tommasi, R G Asch, N Rebuck, R Ji, S I Large, Charles A Stock, and Vincent S Saba, July 2015: Spring bloom dynamics and zooplankton biomass response on the US Northeast Continental Shelf. Continental Shelf Research, 102, DOI:10.1016/j.csr.2015.04.005. Abstract
The spring phytoplankton bloom on the US Northeast Continental Shelf is a feature of the ecosystem production cycle that varies annually in timing, spatial extent, and magnitude. To quantify this variability, we analyzed remotely-sensed ocean color data at two spatial scales, one based on ecologically defined sub-units of the ecosystem (production units) and the other on a regular grid (0.5°). Five units were defined: Gulf of Maine East and West, Georges Bank, and Middle Atlantic Bight North and South. The units averaged 47×103 km2 in size. The initiation and termination of the spring bloom were determined using change-point analysis with constraints on what was identified as a bloom based on climatological bloom patterns. A discrete spring bloom was detected in most years over much of the western Gulf of Maine production unit. However, bloom frequency declined in the eastern Gulf of Maine and transitioned to frequencies as low as 50% along the southern flank of the Georges Bank production unit. Detectable spring blooms were episodic in the Middle Atlantic Bight production units. In the western Gulf of Maine, bloom duration was inversely related to bloom start day; thus, early blooms tended to be longer lasting and larger magnitude blooms. We view this as a phenological mismatch between bloom timing and the “top-down” grazing pressure that terminates a bloom. Estimates of secondary production were available from plankton surveys that provided spring indices of zooplankton biovolume. Winter chlorophyll biomass had little effect on spring zooplankton biovolume, whereas spring chlorophyll biomass had mixed effects on biovolume. There was evidence of a “bottom up” response seen on Georges Bank where spring zooplankton biovolume was positively correlated with the concentration of chlorophyll. However, in the western Gulf of Maine, biovolume was uncorrelated with chlorophyll concentration, but was positively correlated with bloom start and negatively correlated with magnitude. This observation is consistent with both a “top-down” mechanism of control of the bloom and a “bottom-up” effect of bloom timing on zooplankton grazing. Our inability to form a consistent model of these relationships across adjacent systems underscores the need for further research.
Reversibility studies suggest a lagged recovery of global mean sea surface temperatures after mitigation, raising the question of whether a similar lag is likely for marine net primary production (NPP). Here we assess NPP reversibility with a mitigation scenario in which projected Representative Concentration Pathway (RCP8.5) forcings are applied out to 2100, and then reversed over the course of the following century in a fully coupled carbon-climate earth system model. In contrast to the temperature lag, we find a rapid increase in global mean NPP, including an overshoot to values above contemporary means. The enhanced NPP arises from a transient imbalance between the cooling surface ocean and continued warming in subsurface waters, which weakens upper ocean density gradients, resulting in deeper mixing and enhanced surface nitrate. We also find a marine ecosystem regime shift as persistent silicate depletion results in increased prevalence of large, non-diatom phytoplankton.
Kearney, Kelly A., Desiree Tommasi, and Charles A Stock, September 2015: Simulated ecosystem response to volcanic iron fertilization in the subarctic Pacific ocean. Fisheries Oceanography, 24(5), DOI:10.1111/fog.12118. Abstract
The eruption of the Kasatochi volcano in August 2008 stimulated an anomalously high phytoplankton bloom in the otherwise iron-limited subarctic Pacific ocean. It has been proposed that this increased production may have been responsible for record returns of some Pacific salmon stocks in the following years. Here, we investigate the potential effect of volcanic-induced iron fertilization on the entire ecosystem, from phytoplankton through to top predators, using a fully-coupled end-to-end ecosystem model. Our simulations indicate that the volcanic iron fertilization could only stimulate modest increases, at most 10%, in the standing stock biomass of upper trophic level species, including fisheries targets such as Pacific salmon. Propagation of energy to higher trophic levels depends on the timing of the eruption, with more efficient crustaceous zooplankton pathways being favored earlier in the growing season and less-efficient gelatinous zooplankton pathways dominating during later months. However, effects were of modest magnitude for all eruption timings, and the strong level of connectivity within the food web makes the preferential stimulation of a single salmon stock implausible. This adds additional support to evidence suggesting that the Kasatochi eruption did not play a large role in subsequent high salmon returns and questions the value of much smaller-scale artificial fertilization for fisheries. Indeed, the onset of macronutrient limitation coupled with the highly-connected nature of the food web exert strong controls on the fisheries response to even complete removal of iron limitation in the subarctic Pacific.
Lynch, P D., Janet A Nye, J A Hare, and Charles A Stock, et al., January 2015: Projected ocean warming creates a conservation challenge for river herring populations. ICES Journal of Marine Science, 72(2), DOI:10.1093/icesjms/fsu134. Abstract
The term river herring collectively refers to alewife (Alosa pseudoharengus) and blueback herring (A. aestivalis), two anadromous fishes distributed along the east coast of North America. Historically, river herring spawning migrations supported important fisheries, and their spawning runs continue to be of cultural significance to many coastal communities. Recently, substantial declines in spawning run size prompted a petition to consider river herring for listing under the Endangered Species Act (ESA). The ESA status review process requires an evaluation of a species' response to multiple stressors, including climate change. For anadromous species that utilize a range of habitats throughout their life cycle, the response to a changing global climate is inherently complex and likely varies regionally. River herring occupy marine habitat for most of their lives, and we demonstrate that their relative abundance in the ocean has been increasing in recent years. We project potential effects of ocean warming along the US Atlantic coast on river herring in two seasons (spring and fall), and two future periods (2020–2060 and 2060–2100) by linking species distribution models to projected temperature changes from global climate models. Our analyses indicate that climate change will likely result in reductions in total suitable habitat across the study region, which will alter the marine distribution of river herring. We also project that density will likely decrease for both species in fall, but may increase in spring. Finally, we demonstrate that river herring may have increased sensitivity to climate change under a low abundance scenario. This result could be an important consideration for resource managers when planning for climate change because establishing effective conservation efforts in the near term may improve population resiliency and provide lasting benefits to river herring populations.
Paulot, Fabien, D J Jacob, M T Johnson, T G Bell, A R Baker, W C Keene, Ivan D Lima, Scott C Doney, and Charles A Stock, August 2015: Global oceanic emission of ammonia: constraints from seawater and atmospheric observations. Global Biogeochemical Cycles, 29(8), DOI:10.1002/2015GB005106. Abstract
Current global inventories of ammonia emissions identify the ocean as the largest natural source. This source depends on seawater pH, temperature, and the concentration of total seawater ammonia (NHx(sw)), which reflects a balance between remineralization of organic matter, uptake by plankton, and nitrification. Here, we compare [NHx(sw)] from two global ocean biogeochemical models (BEC and COBALT) against extensive ocean observations. Simulated [NHx(sw)] are generally biased high. Improved simulation can be achieved in COBALT by increasing the plankton affinity for NHx within observed ranges. The resulting global ocean emissions is 2.5 TgN a−1, much lower than current literature values(7–23 TgN a−1), including the widely used GEIA inventory (8 TgN a−1). Such a weak ocean source implies that continental sources contribute more than half of atmospheric NHx over most of the ocean in the Northern hemisphere. Ammonia emitted from oceanic sources is insufficient to neutralize sulfate aerosol acidity, consistent with observations. There is evidence over the Equatorial Pacific for a missing source of atmospheric ammonia that could be due to photolysis of marine organic nitrogen at the ocean surface or in the atmosphere. Accommodating this possible missing source yields a global ocean emission of ammonia in the range 2–5 TgN a−1, comparable in magnitude to other natural sources from open fires and soils.
Saba, Vincent S., Charles A Stock, and John P Dunne, October 2015: Relation of Marine Primary Productivity to Leatherback Biology and Behavior In The Leatherback Turtle: Biology and Conservation, Baltimore, MD, John Hopkins University Press, 173-184.
Sea surface temperature (SST) anomalies are often both leading indicators and important drivers of marine resource fluctuations. Assessment of the skill of SST anomaly forecasts within coastal ecosystems accounting for the majority of global fish yields, however, has been minimal. This reflects coarse global forecast system resolution and past emphasis on the predictability of ocean basin-scale SST variations. This paper assesses monthly to inter-annual SST anomaly predictions in coastal “Large Marine Ecosystems” (LMEs). We begin with an analysis of 7 well-observed LMEs adjacent to the United States and then examine how mechanisms responsible for prediction skill in these systems are reflected in predictions for LMEs globally. Historical SST anomaly estimates from the 1/4o daily Optimal Interpolation Sea Surface Temperature reanalysis (OISST.v2) were first found to be highly consistent with in-situ measurements for 6 of the 7 U.S. LMEs. Thirty years of retrospective forecasts from climate forecast systems developed at NOAA’s Geophysical Fluid Dynamics Laboratory (CM2.5-FLOR) and the National Center for Environmental Prediction (CFSv2) were then assessed against OISST.v2. Forecast skill varied widely by LME, initialization month, and lead but there were many cases of high skill that also exceeded that of a persistence forecast, some at leads greater than 6 months. Mechanisms underlying skill above persistence included accurate simulation of a) seasonal transitions between less predictable locally generated and more predictable basin-scale SST variability; b) seasonal transitions between different basin-scale influences; c) propagation of SST anomalies across seasons through sea ice; and d) re-emergence of previous anomalies upon the breakdown of summer stratification. Globally, significant skill above persistence across many tropical systems arises via mechanisms a) and b). Combinations of all four mechanisms contribute to less prevalent but nonetheless significant skill in extratropical systems. While continued refinement of global climate forecast systems and observations are needed to improve coastal SST anomaly prediction and extend predictions to other ecosystem relevant variables (e.g., salinity), present skill warrants close examination of forecasts for marine resource applications.
Tommasi, Desiree, Janet A Nye, and Charles A Stock, et al., July 2015: Effect of Environmental Conditions on Juvenile Recruitment of Alewife (Alosa pseudoharengus) and Blueback Herring (A. aestivalis) in Freshwater: A Coastwide Perspective. Canadian Journal of Fisheries and Aquatic Sciences, 72(7), DOI:10.1139/cjfas-2014-0259. Abstract
The abundance of alewife (Alosa pseudoharengus) and blueback herring (Alosa aestivalis) has declined throughout their range, and there are increasing concerns about their conservation status. Because of their diadromous life history, variability in rates of survival in freshwater can affect overall recruitment. The objective of our study was to assess how river temperature and flow influence young of the year (YOY) river herring recruitment in the Northeast US. Observations of adult and juvenile fish in five rivers were used to construct spawner-YOY recruits models; these rivers were chosen because of the length of the time series (>15 years) and the paired observations of spawners and juveniles. An environmentally-explicit stock recruitment model explained a substantial fraction (41 to 80%) of the variance in YOY abundance, depending on river system. Our approach allowed for a preliminary discussion of potential mechanisms, which need to be further substantiated by focused field and laboratory studies. Early summer river flow and river temperature had the greatest influence indicating the importance of conditions in nursery habitats. In certain systems, spring or fall conditions were also important determinants of survival suggesting additional effects of the environment on spawning of adults and juvenile egress from freshwater nursery habitats.
Watson, James R., Charles A Stock, and Jorge L Sarmiento, November 2015: Exploring the role of movement in determining the global distribution of marine biomass using a coupled hydrodynamic – size-based ecosystem model. Progress in Oceanography, 138, Part B, DOI:10.1016/j.pocean.2014.09.001. Abstract
Modeling the dynamics of marine populations at a global scale - from phytoplankton to fish - is necessary if we are to quantify how climate change and other broad-scale anthropogenic actions affect the supply of marine-based food. Here, we estimate the abundance and distribution of fish biomass using a simple size-based food web model coupled to simulations of global ocean physics and biogeochemistry. We focus on the spatial distribution of biomass, identifying highly productive regions - shelf seas, western boundary currents and major upwelling zones. In the absence of fishing, we estimate the total ocean fish biomass to be View the MathML source∼2.84×109tonnes, similar to previous estimates. However, this value is sensitive to the choice of parameters, and further, allowing fish to move had a profound impact on the spatial distribution of fish biomass and the structure of marine communities. In particular, when movement is implemented the viable range of large predators is greatly increased, and stunted biomass spectra characterizing large ocean regions in simulations without movement, are replaced with expanded spectra that include large predators. These results highlight the importance of considering movement in global-scale ecological models.
Weitz, J S., and Charles A Stock, et al., June 2015: A multitrophic model to quantify the effects of marine viruses on microbial food webs and ecosystem processes. The ISME Journal, 9(6), DOI:10.1038/ismej.2014.220. Abstract
Viral lysis of microbial hosts releases organic matter that can then be assimilated by nontargeted microorganisms. Quantitative estimates of virus-mediated recycling of carbon in marine waters, first established in the late 1990s, were originally extrapolated from marine host and virus densities, host carbon content and inferred viral lysis rates. Yet, these estimates did not explicitly incorporate the cascade of complex feedbacks associated with virus-mediated lysis. To evaluate the role of viruses in shaping community structure and ecosystem functioning, we extend dynamic multitrophic ecosystem models to include a virus component, specifically parameterized for processes taking place in the ocean euphotic zone. Crucially, we are able to solve this model analytically, facilitating evaluation of model behavior under many alternative parameterizations. Analyses reveal that the addition of a virus component promotes the emergence of complex communities. In addition, biomass partitioning of the emergent multitrophic community is consistent with well-established empirical norms in the surface oceans. At steady state, ecosystem fluxes can be probed to characterize the effects that viruses have when compared with putative marine surface ecosystems without viruses. The model suggests that ecosystems with viruses will have (1) increased organic matter recycling, (2) reduced transfer to higher trophic levels and (3) increased net primary productivity. These model findings support hypotheses that viruses can have significant stimulatory effects across whole-ecosystem scales. We suggest that existing efforts to predict carbon and nutrient cycling without considering virus effects are likely to miss essential features of marine food webs that regulate global biogeochemical cycles.
Kristiansen, T, and Charles A Stock, et al., May 2014: Mechanistic insights into the effects of climate change on larval cod. Global Change Biology, 20(5), DOI:10.1111/gcb.12489. Abstract
Understanding the biophysical mechanisms that shape variability in fisheries recruitment is critical for estimating the effects of climate change on fisheries. In this study, we used an Earth System Model (ESM) and a mechanistic individual-based model (IBM) for larval fish to analyze how climate change may impact the growth and survival of larval cod in the North Atlantic. We focused our analysis on five regions that span the current geographical range of cod and are known to contain important spawning populations. Under the SRES A2 (high emissions) scenario, the ESM-projected surface ocean temperatures are expected to increase by >1 °C for 3 of the 5 regions, and stratification is expected to increase at all sites between 1950–1999 and 2050–2099. This enhanced stratification is projected to decrease large (>5 μm ESD) phytoplankton productivity and mesozooplankton biomass at all 5 sites. Higher temperatures are projected to increase larval metabolic costs, which combined with decreased food resources will reduce larval weight, increase the probability of larvae dying from starvation and increase larval exposure to visual and invertebrate predators at most sites. If current concentrations of piscivore and invertebrate predators are maintained, larval survival is projected to decrease at all five sites by 2050–2099. In contrast to past observed responses to climate variability in which warm anomalies led to better recruitment in cold-water stocks, our simulations indicated that reduced prey availability under climate change may cause a reduction in larval survival despite higher temperatures in these regions. In the lower prey environment projected under climate change, higher metabolic costs due to higher temperatures outweigh the advantages of higher growth potential, leading to negative effects on northern cod stocks. Our results provide an important first large-scale assessment of the impacts of climate change on larval cod in the North Atlantic.
Organic particles sinking from the sunlit surface are oases of food for heterotrophic bacteria living
in the deep ocean. Particle-attached bacteria need to solubilize particles, so they produce exoenzymes
that cleave bonds to make molecules small enough to be transported through bacterial cell walls.
Releasing exoenzymes, which have an energetic cost, to the external environment is risky because there
is no guarantee that products of exoenzyme activity, called hydrolysate, will diffuse to the particleattached
bacterium that produced the exoenzymes. Strategies used by particle-attached bacteria to
counteract diffusive losses of exoenzymes and hydrolysate are investigated in a water column model.
We find that production of exoenzymes by particle-attached bacteria is only energetically worthwhile
at high bacterial abundances. Quorum sensing provides the means to determine local abundances,
and thus the model results support lab and field studies which found that particle-attached bacteria
have the ability to use quorum sensing. Additional model results are that particle-attached bacterial
production is sensitive to diffusion of hydrolysate from the particle and is enhanced by as much as
15 times when diffusion of exoenzymes and hydrolysate from particles is reduced by barriers of
biofilms and particle-attached bacteria. Bacterial colonization rates and activities on particles in both
the euphotic and mesopelagic zones impact remineralization length scales. Shoaling or deepening of
the remineralization depth has been shown to exert significant influence on the residence time and
concentration of carbon in the atmosphere and ocean. By linking variability in remineralization depths
to mechanisms governing bacterial colonization of particles and group coordination of exoenzyme
production using a model, we quantitatively connect microscale bacteria-particle interactions to the
carbon cycle and provide new insights for future observations.
The Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) marine ecosystem model robustly captures large-scale observed patterns in the flow of carbon through the planktonic food web when embedded within a global ocean-ice simulation. The simulation offers holistic, quantitative, and self-consistent estimates of carbon and energy flows across ocean biomes. Results emphasize the importance of small phytoplankton to global productivity. This leads to widespread carnivorous feeding by mesozooplankton and muted cross-biome differences in annual mean mesozooplankton trophic level. Results also support highly distributed respiration across the planktonic food web. In oceanic upwelling regions, shortened food webs, elevated growth efficiencies, and tight consumer-phytoplankton coupling supports 47% of pelagic mesozooplankton production despite these areas accounting for only 21% of ocean area and 33% of net primary production (NPP). In seasonally stratified regions (40% of ocean area and 36% of NPP), weakened phytoplankton-consumer coupling reduces mesozooplankton production to 39% and enhances export such that it accounts for 55% of the global total. In oligotrophic systems (39% of ocean area and 27% of NPP), the dominance of small phytoplankton and low consumer growth efficiencies support only 15% of mesozooplankton production and 14% of export globally. Bacterial production, in contrast, is maintained in constant proportion to primary production across ecosystems. Further diagnosis of simulations elucidates the mechanisms underlying these cross biome contrasts and regularities. Results herein represent a baseline for further exploration of global-scale planktonic food web dynamics within an increasingly mechanistic dynamic global physical-biological framework.
Pronounced projected 21st century trends in regional oceanic net primary production (NPP) raise the prospect of significant redistributions of marine resources. Recent results further suggest that NPP changes may be amplified at higher trophic levels. Here, we elucidate the role of planktonic food web dynamics in driving projected changes in mesozooplankton production (MESOZP) found to be, on average, twice as large as projected changes in NPP by the latter half of the 21st century under a high emissions scenario. Globally, MESOZP was projected to decline by 7.9% but regional MESOZP changes sometimes exceeded 50%. Changes in three planktonic food web properties – zooplankton growth efficiency (ZGE), the trophic level of mesozooplankton (MESOTL), and the fraction of NPP consumed by zooplankton (zooplankton-phytoplankton coupling, ZPC), were demonstrated to be responsible for the projected amplification. Zooplankton growth efficiencies (ZGE) changed with NPP, amplifying both NPP increases and decreases. Negative amplification (i.e., exacerbation) of projected subtropical NPP declines via this mechanism was particularly strong since consumers in the subtropics already have limited surplus energy above basal metabolic costs. Increased mesozooplankton trophic level (MESOTL) resulted from projected declines in large phytoplankton production, the primary target of herbivorous mesozooplankton. This further amplified negative subtropical NPP declines but was secondary to ZGE and, at higher latitudes, was often offset by increased ZPC. Marked ZPC increases were projected for high latitude regions experiencing shoaling of deep winter mixing or decreased winter sea ice – both tending to increase winter zooplankton biomass and enhance grazer control of spring blooms. Increased ZPC amplified projected NPP increases associated with declining sea ice in the Artic and damped projected NPP declines associated with decreased mixing in the Northwest Atlantic and Southern Ocean. Improved understanding of the complex interactions governing these food web properties is essential to further refine estimates of climate-driven productivity changes across trophic levels.
Bianchi, Daniele, Charles A Stock, Eric D Galbraith, and Jorge L Sarmiento, May 2013: Diel vertical migration: ecological controls and impacts on the biological pump in a one-dimensional ocean model. Global Biogeochemical Cycles, 27, DOI:10.1002/gbc.20031. Abstract
Diel vertical migration (DVM) of zooplankton and micronekton is widespread in the ocean and forms a fundamental component of the biological pump, but is generally overlooked in global models of the Earth System. We develop a parameterization of DVM in the ocean and integrate it with a size-structured NPZD model. We assess the model's ability to recreate ecosystem and DVM patterns at three well observed Pacific sites, ALOHA, K2 and EQPAC, and use it to estimate the impact of DVM on marine ecosystems and biogeochemical dynamics. Our model includes: (1) a representation of migration dynamics in response to food availability and light intensity, (2) a representation of the digestive and metabolic processes that decouple zooplankton feeding from excretion, egestion and respiration, and (3) a light-dependent parameterization of visual predation on zooplankton. The model captures the first order patterns in plankton biomass and productivity across the biomes, including the biomass of migrating organisms. We estimate that realistic migratory populations sustain active fluxes to the mesopelagic zone equivalent to between 15 and 40 % the particle export, and contribute up to half of the total respiration within the layers affected by migration. The localized active transport has important consequences for the cycling of oxygen, nutrients and carbon. We highlight the importance of decoupling zooplankton feeding and respiration and excretion with depth for capturing the impact of migration on the redistribution of carbon and nutrients in the upper ocean.
Bianchi, Daniele, Eric D Galbraith, D A Carozza, K A S Mislan, and Charles A Stock, July 2013: Intensification of open-ocean oxygen depletion by vertically migrating animals. Nature Geoscience, 6(7), DOI:doi:10.1038/ngeo1837. Abstract
Throughout the ocean, countless small animals swim to depth in the daytime, presumably to seek refuge from large predators. These animals return to the surface at night to feed. This substantial diel vertical migration can result in the transfer of significant amounts of carbon and nutrients from the surface to depth. However, its consequences on ocean chemistry at the global scale have remained uncertain. Here, we determine the depths of these diel migrations in the global ocean using a global array of backscatter data from acoustic Doppler current profilers, collected between 1990 and 2011. We show that the depth of diel migration follows coherent large-scale patterns. We find that migration depth is greater where subsurface oxygen concentrations are high, such that seawater oxygen concentration is the best single predictor of migration depth at the global scale. In oxygen minimum zone areas, migratory animals generally descend as far as the upper margins of the low-oxygen waters. Using an ocean biogeochemical model coupled to a general circulation model, we show that by focusing oxygen consumption in poorly ventilated regions of the upper ocean, diel vertical migration intensifies oxygen depletion in the upper margin of oxygen minimum zones. We suggest that future changes in the extent of oxygen minimum zones could alter the migratory depths of marine organisms, with consequences for marine biogeochemistry, food webs and fisheries.
Considerable progress has been made in integrating carbon, nutrient, phytoplankton and zooplankton dynamics into global-scale physical climate models. Scientists are exploring ways to extend the resolution of the biosphere within these Earth system models (ESMs) to include impacts on global distribution and abundance of commercially exploited fish and shellfish. This paper compares different methods for modeling fish and shellfish responses to climate change on global and regional scales. Several different modeling approaches are considered including: direct applications of ESM’s, use of ESM output for estimation of shifts in bioclimatic windows, using ESM outputs to force single- and multi-species stock projection models, and using ESM and physical climate model outputs to force regional bio-physical models of varying complexity and mechanistic resolution. We evaluate the utility of each of these modeling approaches in addressing nine key questions relevant to climate change impacts on living marine resources. No single modeling approach was capable of fully addressing each question. A blend of highly mechanistic and less computationally intensive methods is recommended to gain mechanistic insights and to identify model uncertainties.
We used an end-to-end ecosystem
model that incorporates physics, biogeochemistry,
and predator−prey dynamics for the Eastern Subarctic
Pacific ecosystem to investigate the factors controlling
propagation of changes in primary production
to higher trophic levels. We found that lower
trophic levels respond to increased primary production
in unexpected ways due to complex predatory
interactions, with small phytoplankton increasing
more than large phytoplankton due to relief from
predation by microzooplankton, which are kept in
check by the more abundant mesozooplankton. We
also found that the propagation of production to
upper trophic levels depends critically on how nonpredatory
mortality is structured in the model, with
much greater propagation occurring with linear mortality
and much less with quadratic mortality, both of
which functional forms are in common use in eco -
system models. We used an ensemble simulation
approach to examine how uncertainties in model
parameters affect these results. When considering
the full range of potential responses to enhanced productivity,
the effect of uncertainties related to the
functional form of non-predatory mortality was often
masked by uncertainties in the food-web parameterization.
The predicted responses of several commercially
important species, however, were significantly
altered by non-predatory mortality assumptions.
The impact of climate warming on the upper layer of the Bering Sea is investigated by using a high-resolution coupled global climate model. The model is forced by increasing atmospheric CO2 at a rate of 1% per year until CO2 reaches double its initial value (after 70 years), after which it is held constant. In response to this forcing, the upper layer of the Bering Sea warms by about 2�C in the southeastern shelf and by a little more than 1�C in the western basin. The wintertime ventilation to the permanent thermocline weakens in the western Bering Sea. After CO2 doubling, the southeastern shelf of the Bering Sea becomes almost ice-free in March, and the stratification of the upper layer strengthens in May and June. Changes of physical condition due to the climate warming would impact the pre-condition of spring bio-productivity in the southeastern shelf.
The shift in marine resource management from a compartmentalized approach of dealing with resources on a species basis
to an approach based on management of spatially defined ecosystems requires an accurate accounting of energy flow. The
flow of energy from primary production through the food web will ultimately limit upper trophic-level fishery yields. In this
work, we examine the relationship between yield and several metrics including net primary production, chlorophyll
concentration, particle-export ratio, and the ratio of secondary to primary production. We also evaluate the relationship
between yield and two additional rate measures that describe the export of energy from the pelagic food web, particle
export flux and mesozooplankton productivity. We found primary production is a poor predictor of global fishery yields for
a sample of 52 large marine ecosystems. However, chlorophyll concentration, particle-export ratio, and the ratio of
secondary to primary production were positively associated with yields. The latter two measures provide greater
mechanistic insight into factors controlling fishery production than chlorophyll concentration alone. Particle export flux and
mesozooplankton productivity were also significantly related to yield on a global basis. Collectively, our analyses suggest
that factors related to the export of energy from pelagic food webs are critical to defining patterns of fishery yields. Such
trophic patterns are associated with temperature and latitude and hence greater yields are associated with colder, high
latitude ecosystems.
Hare, J A., and Charles A Stock, et al., December 2012: Cusk (Brosme brosme) and climate change: assessing the threat to a candidate marine fish species under the US Endangered Species Act. ICES Journal of Marine Science, 69(10), DOI:10.1093/icesjms/fss160. Abstract
In the Northwest Atlantic Ocean cusk (Brosme brosme) has declined dramatically, primarily as a result of fishing activities. These declines have led to concern about its status, which has prompted reviews under the US Endangered Species Act and the Canadian Species at Risk Act. Changes in distribution and abundance of a number of marine fish in the Northwest Atlantic have been linked to climate variability and change, suggesting that both fishing and climate may affect the status of cusk. Our goal was to evaluate potential effects of climate change on Northwest Atlantic cusk distribution. Coupling a species niche model with the output from an ensemble of climate models, we projected cusk distribution in the future. Our results indicate cusk habitat in the region will shrink and fragment, which is a result of a spatial mismatch between high complexity seafloor habitat and suitable temperature. The importance of habitat patch connectivity for cusk is poorly understood, so the population-level consequences of climate-related habitat fragmentation are uncertain. More broadly, climate change may reduce appropriate thermal habitat and increase habitat fragmentation for other cold-water species in the region; thereby, increasing the potential for regional overexploitation and extirpation.
Kearney, Kelly A., Charles A Stock, Kerim Y Aydin, and Jorge L Sarmiento, July 2012: Coupling planktonic ecosystem and fisheries food web models for a pelagic ecosystem: Description and validation for the subarctic Pacific. Ecological Modelling, 237-238, DOI:10.1016/j.ecolmodel.2012.04.006. Abstract
We provide a modeling framework that fully couples a one-dimensional physical mixed layer model, a biogeochemical model, and an upper trophic level fisheries model. For validation purposes, the model has been parameterized for the pelagic Eastern Pacific Subarctic Gyre ecosystem. This paper presents a thorough description of the model itself, as well as an ensemble-based parameterization process that allows the model to incorporate the high level of uncertainty associated with many upper trophic level predator-prey processes. Through a series of model architecture experiments, we demonstrate that the use of a consistent functional response for all predator-prey interactions, as well as the use of density-dependent mortality rates for planktonic functional groups, are important factors in reproducing annual and seasonal observations. We present the results of a 50-year climatological simulation, which demonstrates that under contemporary physical forcing, the model is capable of reproducing long-term seasonal dynamics in primary production and biogeochemical cycling, while maintaining steady-state coexistence of upper trophic level functional groups at levels consistent with observations.
Assessing the potential impacts of climate change on individual species and populations is essential for the stewardship of ecosystems and biodiversity. Critically endangered leatherback turtles in the eastern Pacific Ocean are excellent candidates for such an assessment because their sensitivity to contemporary climate variability has been substantially studied1, 2, 3, 4. If incidental fisheries mortality is eliminated, this population still faces the challenge of recovery in a rapidly changing climate. Here we combined an Earth system model5, climate model projections assessed by the Intergovernmental Panel on Climate Change6 and a population dynamics model to estimate a 7% per decade decline in the Costa Rica nesting population over the twenty-first century. Whereas changes in ocean conditions had a small effect on the population, the ~2.5 °C warming of the nesting beach was the primary driver of the decline through reduced hatching success and hatchling emergence rate. Hatchling sex ratio did not substantially change. Adjusting nesting phenology or changing nesting sites may not entirely prevent the decline, but could offset the decline rate. However, if future observations show a long-term decline in hatching success and emergence rate, anthropogenic climate mitigation of nests (for example, shading, irrigation)7, 8 may be able to preserve the nesting population.
Santidrián Tomillo, Pilar, Vincent S Saba, G S Blanco, Charles A Stock, F V Paladino, and J R Spotila, May 2012: Climate Driven Egg and Hatchling Mortality Threatens Survival of Eastern Pacific Leatherback Turtles. PLoS-ONE, 7(5), DOI:10.1371/journal.pone.0037602. Abstract
Egg-burying reptiles need relatively stable temperature and humidity in the substrate surrounding their eggs for successful
development and hatchling emergence. Here we show that egg and hatchling mortality of leatherback turtles (Dermochelys
coriacea) in northwest Costa Rica were affected by climatic variability (precipitation and air temperature) driven by the El
Nin˜o Southern Oscillation (ENSO). Drier and warmer conditions associated with El Nin˜o increased egg and hatchling
mortality. The fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC) projects a warming and
drying in Central America and other regions of the World, under the SRES A2 development scenario. Using projections from
an ensemble of global climate models contributed to the IPCC report, we project that egg and hatchling survival will rapidly
decline in the region over the next 100 years by ,50–60%, due to warming and drying in northwestern Costa Rica,
threatening the survival of leatherback turtles. Warming and drying trends may also threaten the survival of sea turtles in
other areas affected by similar climate changes.
Song, H, R Ji, Charles A Stock, Kelly A Kearney, and Z Wang, March 2011: Interannual variability in phytoplankton blooms and plankton productivity over the Nova Scotian Shelf and in the Gulf of Maine. Marine Ecology Progress Series, 426, DOI:10.3354/meps09002. Abstract
A 1D ecosystem model, driven by surface heat and wind forcing and relaxed toward observed salinity profiles, was applied to simulate the interannual and decadal scale variability of phytoplankton blooms and plankton production from 1984 to 2007 in the Nova Scotian Shelf (NSS) and Gulf of Maine (GoM) region. The model captured the mean observed timing and magnitude of the spring (SPB) and fall phytoplankton bloom (FPB) in both systems, as well as observed interannual variations in SPB peak timing. Model simulations for both the GoM and NSS exhibited marked interannual variability in SPB and FPB timing (±2 to 3 wk) and magnitude (up to ~1 mg chlorophyll m–3). Earlier SPBs and delayed FPBs are linked to enhanced water column stability generated by less saline surface water or sharper salinity gradients over the top 50 m of the water column. The modeled variation in annual primary productivity, mesozooplankton productivity, and particle export flux was modest (<10% of the mean). Years with high primary production were weakly associated with early SPBs (GoM: r = –0.205; NSS: r = –0.51), but there was no significant relationship with water column stability. This suggests that variation in annual productivity in the GoM and NSS reflects a combination of variation in light limitation (which is alleviated by increased water column stability) and nutrient limitation (which is exacerbated by increased water column stability) that offset and are of near equal importance when averaged over the year. Interannual variations in fisheries production due to changes in annual productivity are thus likely secondary to profound shifts in fisheries recruitment and production that have been linked to variations in SPB and FPB timing.
The study of climate impacts on Living Marine Resources (LMRs) has increased rapidly in recent years with the availability of climate model simulations contributed to the assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Collaboration between climate and LMR scientists and shared understanding of critical challenges for such applications are essential for developing robust projections of climate impacts on LMRs. This paper assesses present approaches for generating projections of climate impacts on LMRs using IPCC-class climate models, recommends practices that should be followed for these applications, and identifies priority developments that could improve current projections. Understanding of the climate system and its representation within climate models has progressed to a point where many climate model outputs can now be used effectively to make LMR projections. However, uncertainty in climate model projections (particularly biases and inter-model spread at regional to local scales), coarse climate model resolution, and the uncertainty and potential complexity of the mechanisms underlying the response of LMRs to climate limit the robustness and precision of LMR projections. A variety of techniques including the analysis of multi-model ensembles, bias corrections, and statistical and dynamical downscaling can ameliorate some limitations, though the assumptions underlying these approaches and the sensitivity of results to their application must be assessed for each application. Developments in LMR science that could improve current projections of climate impacts on LMRs include improved understanding of the multi-scale mechanisms that link climate and LMRs and better representations of these mechanisms within more holistic LMR models. These developments require a strong baseline of field and laboratory observations including long time-series and measurements over the broad range of spatial and temporal scales over which LMRs and climate interact. Priority developments for IPCC-class climate models include improved model accuracy (particularly at regional and local scales), inter-annual to decadal-scale predictions, and the continued development of earth system models capable of simulating the evolution of both the physical climate system and biosphere. Efforts to address these issues should occur in parallel and be informed by the continued application of existing climate and LMR models.
Song, H, R Ji, Charles A Stock, and Z Wang, November 2010: Phenology of phytoplankton blooms in the Nova Scotian Shelf–Gulf of Maine region: remote sensing and modeling analysis. Journal of Plankton Research, 32(11), DOI:10.1093/plankt/fbq086. Abstract
Remotely sensed ocean color data and numerical modeling have been used to
study the phenology of both spring and fall phytoplankton blooms (FPBs) in the
Nova Scotian Shelf (NSS)–Gulf of Maine (GoM) region. The ocean color data
reveal a general pattern of westward progression of the spring phytoplankton
bloom (SPB), and an eastward progression of the FPB in the NSS–GoM region.
The spatial pattern of mean chlorophyll concentration in spring is similar to that
in fall, with a lower concentration in the NSS and higher in the GoM.
Interannually, there is a weak but significant tendency for years with earlier
(delayed) SPBs to be followed by delayed (earlier) FPBs, but the mean chlorophyll
concentrations during SPBs are not correlated with those during FPBs. The interannual
variability of SPB timing is significantly correlated with sea surface salinity
(SSS), but the FPB timing is correlated with both SSS and sea surface temperature.
The process-oriented numerical modeling experiments suggest that (i) salinity
is the main factor influencing the bloom timing and magnitude in the NSS–GoM
region, especially for the timing of SPBs; (ii) compared to buoyancy forcing
induced by vertical salinity gradients, the impact of surface heating and surface
wind stress on the blooms variability is much weaker; and (iii) the nutrient level
controls the bloom magnitude, but only has a minor effect on bloom timing. This
study provides a quantitative estimation of relationship between changes in local/
remote environmental forcing and phytoplankton phenological shifts, thus improving
our understanding on the possible impact of climate change on coastal/shelf
ecosystems.
An ecosystem model was used to (1) determine the extent to which global trends in the ratio of mesozooplankton production to primary production (referred to herein as the “z-ratio”) can be explained by nutrient enrichment, temperature, and euphotic zone depth, and (2) quantitatively diagnose the mechanisms driving these trends. Equilibrium model solutions were calibrated to observed and empirically derived patterns in phytoplankton biomass and growth rates, mesozooplankton biomass and growth rates, and the fraction of phytoplankton that are large (>5 μm ESD). This constrained several otherwise highly uncertain model parameters. Most notably, half-saturation constants for zooplankton feeding were constrained by the biomass and growth rates of their prey populations, and low zooplankton basal metabolic rates were required to match observations from oligotrophic ecosystems. Calibrated model solutions had no major biases and produced median z-ratios and ranges consistent with estimates. However, much of the variability around the median values in the calibration dataset (72 points) could not be explained. Model results were then compared with an extended global compilation of z-ratio estimates (>10 000 points). This revealed a modest yet significant (r=0.40) increasing trend in z-ratios from values 0.01–0.04 to 0.1–0.2 with increasing primary productivity, with the transition from low to high z-ratios occurring at lower primary productivity in cold-water ecosystems. Two mechanisms, both linked to increasing phytoplankton biomass, were responsible: (1) zooplankton gross growth efficiencies increased as their ingestion rates became much greater than basal metabolic rates and (2) the trophic distance between primary producers and mesozooplankton shortened as primary production shifted toward large phytoplankton. Mechanism (1) was most important during the transition from low to moderate productivity ecosystems and mechanism (2) was responsible for a relatively abrupt transition to values >0.1 in high productivity ecosystems. Substantial z-ratio variations overlying these mean trends remained unexplained by these mechanisms. Potential sources of this variability include zooplankton patchiness, unresolved effects of advection and unsteady dynamics, unresolved shifts in mesozooplankton sizes and species, and unresolved aspects of zooplankton bioenergetics. Comparison of the modeled z-ratio patterns and mechanisms diagnosed herein with those obtained using models with expanded biological dynamics embedded in global circulation models will help further elucidate the causes of this variation.
McGillicuddy, Jr, Dennis J., and Charles A Stock, et al., 2008: Modeling blooms of Alexandrium fundyense in the Gulf of Maine In Real-time Observing Systems for Marine Ecosystems Dynamics and Harmful Algal Blooms, Paris, France, UNESCO Publishing, 599-626.
Stock, Charles A., T M Powell, and Simon A Levin, November 2008: Bottom-up and top-down forcing in a simple size-structured plankton dynamics model. Journal of Marine Systems, 74(1-2), DOI:10.1016/j.jmarsys.2007.12.004. Abstract
A size-structured plankton dynamics model is developed and used to explore the effects of variations in bottom-up and top-down forcing upon the biomass spectrum, size-structured patterns in primary production, and the flux of energy from primary producers to fish. Parameters and mechanisms controlling the steady-state model response to bottom-up forcing via nutrient enrichment and top-down forcing via fluctuations in planktivorous fish are first diagnosed. Results are then compared with mean observed biomass spectra from three ecosystems spanning a broad range of productivity. Solutions using parameters within empirical ranges can recreate trends in the biomass spectrum across these systems. The zooplankton gross growth efficiency is critical for matching the steady-state slopes of the spectra. Variability in export sources and zooplankton half-saturation constants both provide ways of matching the mean biomass. Results support the model's potential to provide mechanistic insights and testable quantitative hypotheses for the dynamics underlying observed biomass spectra.
Stock, Charles A., et al., November 2007: Blooms of the toxic dinoflagellate Alexandrium fundyense in the western Gulf of Maine in 1993 and 1994: A comparative modeling study. Continental Shelf Research, 27(19), DOI:10.1016/j.csr.2007.06.008. Abstract
Blooms of the toxic dinoflagellate Alexandrium fundyense commonly occur in the western Gulf of Maine but the amount of toxin observed in coastal shellfish is highly variable. In this study, a coupled physical–biological model is used to investigate the dynamics underlying the observed A. fundyense abundance and shellfish toxicity in 1993 (a high toxicity year) and 1994 (low toxicity year). The physical model simulates the spring circulation, while the biological model estimates the germination and population dynamics of A. fundyense based on laboratory and field data. The model captures the large-scale aspects of the initiation and development of A. fundyense blooms during both years, but small-scale patchiness and the dynamics of bloom termination remain problematic. In both cases, the germination of resting cysts accounts for the magnitude of A. fundyense populations early in the spring. Simulations with low net A. fundyense growth rates capture the mean observed concentration during the bloom peak, which is of similar magnitude during both years. There is little evidence that large-scale changes in biological dynamics between 1993 and 1994 were a primary driver of the differences in shellfish toxicity. Results instead suggest that the persistent southwesterly flow of the western Maine Coastal Current led to A. fundyense populations of similar alongshore extent by late May of both years. This period coincides with peak cell abundance in the region. Variations in wind forcing (downwelling favorable in 1993, upwelling favorable in 1994) and subsequent cell transport (inshore in 1993, offshore in 1994) in early June then provides a plausible explanation for the dramatic mid-June differences in shellfish toxicity throughout the western Gulf of Maine.
The flux of cells from germinated cysts is critical in the population dynamics of many dinoflagellates. Here, data from a large-scale cyst survey are combined with surveys in other years to yield an Alexandrium fundyense cyst distribution map for the Gulf of Maine that is massive in geographic extent and cyst abundance. The benthic cyst population extends nearly 500 km alongshore. Embedded within it are several distinct accumulation zones or “seedbeds,” each 3000–5000 km2 in area. Maximal cyst abundances range from 2–20×106 cysts m−2. Cysts are equally or more abundant in deeper sediment layers; nearshore, cysts are fewer by a factor of 10 or more. This cyst distribution reflects sedimentary dynamics and the location of blooms in overlying surface waters. The flux of germinated cells from sediments was estimated using a combination of laboratory measurements of cyst germination and autofluorescence and observations of cyst autofluorescence in the field. These measurements constrained a germination function that, when applied to the cyst distribution map, provided an estimate of the germination inoculum for a physical/biological numerical model. In the laboratory studies, virtually all cysts incubated at different temperatures and light regimes became autofluorescent, but the rate of development was slower at lower temperatures, with no difference between light and dark incubations. Germination rates were highest at elevated temperatures, and were 2-fold greater in the light than in the dark. Laboratory and field fluorescence measurements suggest that>70% of the cysts in the top cm of sediment would germinate over a 60–90 day period in offshore waters. The combination of laboratory germination experiments and numerical modeling predicts nearly 100% germination of cysts in the top cm of sediment and resulting early season cell concentrations that are comparable in magnitude to observed cell distributions. It cannot account for late-season peaks in cell abundance that are heavily influenced by vegetative growth. Cyst germination flux from deep-water (>50 m) cyst seedbeds is 14X the flux in shallow waters.
A conceptual model is proposed that is consistent with observed and modeled A. fundyense cyst and motile cell distributions and dynamics in the Gulf of Maine. Cysts germinate within the Bay of Fundy seedbed, causing localized, recurrent blooms that are self-seeding and “propagatory” in nature, supplying cells that populate the eastern segment of the Maine Coastal Current (MCC) and eventually deposit cysts offshore of Penobscot and Casco Bays. These cysts serve as a seed population for western Maine blooms that are transported to the west by the western segment of the MCC, where cells are removed either by mortality or advection from the region. Without the localized, “incubator” characteristic of the Bay of Fundy bloom zone, A. fundyense populations in the Gulf of Maine should diminish through time. Their persistence over many decades highlights the effectiveness of the mechanisms described here.
He, R, and Charles A Stock, et al., October 2005: Data assimilative hindcast of the Gulf of Maine coastal circulation. Journal of Geophysical Research, 110, C10011, DOI:10.1029/2004JC002807. Abstract
A data assimilative model hindcast of the Gulf of Maine (GOM) coastal circulation during an 11 day field survey in early summer 2003 is presented. In situ observations include surface winds, coastal sea levels, and shelf hydrography as well as moored and shipboard acoustic Doppler D current profiler (ADCP) currents. The hindcast system consists of both forward and inverse models. The forward model is a three-dimensional, nonlinear finite element ocean circulation model, and the inverse models are its linearized frequency domain and time domain counterparts. The model hindcast assimilates both coastal sea levels and ADCP current measurements via the inversion for the unknown sea level open boundary conditions. Model skill is evaluated by the divergence of the observed and modeled drifter trajectories. A mean drifter divergence rate (1.78 km d−1) is found, demonstrating the utility of the inverse data assimilation modeling system in the coastal ocean setting. Model hindcast also reveals complicated hydrodynamic structures and synoptic variability in the GOM coastal circulation and their influences on coastal water material property transport. The complex bottom bathymetric setting offshore of Penobscot and Casco bays is shown to be able to generate local upwelling and downwelling that may be important in local plankton dynamics.
Stock, Charles A., et al., September 2005: Evaluating hypotheses for the initiation and development of Alexandrium fundyense blooms in the western Gulf of Maine using a coupled physical–biological model. Deep-Sea Research, Part II, 52(19-21), DOI:10.1016/j.dsr2.2005.06.022. Abstract
A coupled physical/biological model and observations are used to investigate the factors governing the initiation and development of an Alexandrium fundyense bloom in the western Gulf of Maine (WGOM) during the spring of 1993 (March 19–June 6). The physical circulation is simulated using a 3D primitive equation model forced by climatological sea-surface elevation and observed winds, irradiance, and river outflow. This is coupled with a biological model constructed from laboratory and field data that estimates the germination and growth rates of A. fundyense as a function of environmental conditions. Four biological model structures of increasing complexity are considered, with each structure representing a hypothesis for factors controlling bloom initiation and development. The model/data fit is optimized over the uncertainty in the parameters to which the model is most sensitive. The significance of changes in the model/data fit between model structures is quantified using a maximum likelihood ratio test.
The baseline biological model, which parameterizes growth as only a function of temperature, salinity, and light, severely over-estimates observed A. fundyense abundance in the late spring. It is thus rejected with greater than 99% confidence in favor of biological models that include a mortality term or a dependence of growth on dissolved inorganic nitrogen (DIN). The overall best-fit simulation uses both nitrogen dependence and mortality. However, simulations using one or the other of these factors could not be differentiated from the best-fit case with greater than 90% confidence. The best-fit model captures the general timing and magnitude of the observed bloom and some of its secondary features. However, considerable misfits may exist in the point-to-point comparison, and some regional misfits remain.
Diagnosis of the cell budget suggests that germination from a large cyst bed offshore of Casco Bay provides the majority of cells comprising spring A. fundyense populations within the WGOM. The size of the modeled bloom is largely set by the size of this cyst-driven source. Transport of cells from the eastern Gulf of Maine becomes increasingly important later in the spring. Net growth of the modeled A. fundyense populations is first limited by low water temperatures and then by the combined influence of nitrogen limitation and mortality. This results in low domain-averaged net growth rates (<0.05 day−1) throughout much of the simulation. However, rates are sometimes elevated locally and therefore add notable spatial structure to the bloom. Primary uncertainties within the biological model include spatial and temporal variability in mortality, and the influence of sediment dynamics and inter-annual variability in the cyst abundance on the size and spatial character of the cyst driven source. As the dynamics governing these processes become better understood, the approach herein can be extended to accommodate additional dynamical model complexity. However, the ability of the model/data comparison to constrain and support the inclusion of additional biological processes is dependent on both the availability of A. fundyense observations and the physical model skill.
McGillicuddy, Jr, Dennis J., and Charles A Stock, et al., September 2003: A mechanism for offshore initiation of harmful algal blooms in the coastal Gulf of Maine. Journal of Plankton Research, 25(9), DOI:10.1093/plankt/25.9.1131. Abstract
A combination of observations and model results suggest a mechanism by which coastal blooms of the toxic dinoflagellate Alexandrium fundyense can be initiated from dormant cysts located in offshore sediments. The mechanism arises from the joint effects of organism behavior and the wind-driven response of a surface-trapped plume of fresh water originating from riverine sources. During upwelling-favorable winds, the plume thins vertically and extends offshore; downwelling winds thicken the plume and confine it to the nearshore region. In the western Gulf of Maine, the offshore extent of the river plume during upwelling conditions is sufficient to entrain upward-swimming A. fundyense cells germinated from offshore cyst beds. Subsequent downwelling conditions then transport those populations towards the coast.
