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Balancing blue growth with the conservation of wild species and habitats is a key challenge for global ocean management. This is exacerbated in Global South nations, such as Tanzania, where climate-driven ocean change requires delicate marine spatial planning (MSP) trade-offs to ensure climate resilience of marine resources relied upon by coastal communities. Here, we identified challenges and opportunities that climate change presents to the near-term spatial management of Tanzania's artisanal fishing sector, marine protected areas and seaweed farming. Specifically, spatial meta-analysis of climate modelling for the region was carried out to estimate the natural distribution of climate resilience in the marine resources that support these socially important sectors. We estimated changes within the next 20 and 40 years, using modelling projections forced under global emissions trajectories, as well as a wealth of GIS and habitat suitability data derived from globally distributed programmes. Multi-decadal analyses indicated that long-term climate change trends and extreme weather present important challenges to the activity of these sectors, locally and regionally. Only in few instances did we identify areas exhibiting climate resilience and opportunities for sectoral expansion. Including these climate change refugia and bright spots in effective ocean management strategies may serve as nature-based solutions: promoting adaptive capacity in some of Tanzania's most vulnerable economic sectors; creating wage-gaining opportunities that promote gender parity; and delivering some economic benefits of a thriving ocean where possible. Without curbs in global emissions, however, a bleak future may emerge for globally valuable biodiversity hosted in Tanzania, and for its coastal communities, despite the expansion of protected areas or curbs in other pressures. Growing a sustainable ocean economy in this part of the Global South remains a substantial challenge without global d

Marine spatial planning that addresses ocean climate-driven change ('climate-smart MSP') is a global aspiration to support economic growth, food security and ecosystem sustainability. Ocean climate change ('CC') modelling may become a key decision-support tool for MSP, but traditional modelling analysis and communication challenges prevent their broad uptake. We employed MSP-specific ocean climate modelling analyses to inform a real-life MSP process; addressing how nature conservation and fisheries could be adapted to CC. We found that the currently planned distribution of these activities may become unsustainable during the policy's implementation due to CC, leading to a shortfall in its sustainability and blue growth targets. Significant, climate-driven ecosystem-level shifts in ocean components underpinning designated sites and fishing activity were estimated, reflecting different magnitudes of shifts in benthic versus pelagic, and inshore versus offshore habitats. Supporting adaptation, we then identified: CC refugia (areas where the ecosystem remains within the boundaries of its present state); CC hotspots (where climate drives the ecosystem towards a new state, inconsistent with each sectors' present use distribution); and for the first time, identified bright spots (areas where oceanographic processes drive range expansion opportunities that may support sustainable growth in the medium term). We thus create the means to: identify where sector-relevant ecosystem change is attributable to CC; incorporate resilient delivery of conservation and sustainable ecosystem management aims into MSP; and to harness opportunities for blue growth where they exist. Capturing CC bright spots alongside refugia within protected areas may present important opportunities to meet sustainability targets while helping support the fishing sector in a changing climate. By capitalizing on the natural distribution of climate resilience within ocean ecosystems, such climate-adaptive spat

Marine spatial planning that addresses ocean climate-driven change ('climate-smart MSP') is a global aspiration to support economic growth, food security and ecosystem sustainability. Ocean climate change ('CC') modelling may become a key decision-support tool for MSP, but traditional modelling analysis and communication challenges prevent their broad uptake. We employed MSP-specific ocean climate modelling analyses to inform a real-life MSP process; addressing how nature conservation and fisheries could be adapted to CC. We found that the currently planned distribution of these activities may become unsustainable during the policy's implementation due to CC, leading to a shortfall in its sustainability and blue growth targets. Significant, climate-driven ecosystem-level shifts in ocean components underpinning designated sites and fishing activity were estimated, reflecting different magnitudes of shifts in benthic versus pelagic, and inshore versus offshore habitats. Supporting adaptation, we then identified: CC refugia (areas where the ecosystem remains within the boundaries of its present state); CC hotspots (where climate drives the ecosystem towards a new state, inconsistent with each sectors' present use distribution); and for the first time, identified bright spots (areas where oceanographic processes drive range expansion opportunities that may support sustainable growth in the medium term). We thus create the means to: identify where sector-relevant ecosystem change is attributable to CC; incorporate resilient delivery of conservation and sustainable ecosystem management aims into MSP; and to harness opportunities for blue growth where they exist. Capturing CC bright spots alongside refugia within protected areas may present important opportunities to meet sustainability targets while helping support the fishing sector in a changing climate. By capitalizing on the natural distribution of climate resilience within ocean ecosystems, such climate-adaptive spat

Marine spatial planning that addresses ocean climate-driven change ('climate-smart MSP') is a global aspiration to support economic growth, food security and ecosystem sustainability. Ocean climate change ('CC') modelling may become a key decision-support tool for MSP, but traditional modelling analysis and communication challenges prevent their broad uptake. We employed MSP-specific ocean climate modelling analyses to inform a real-life MSP process; addressing how nature conservation and fisheries could be adapted to CC. We found that the currently planned distribution of these activities may become unsustainable during the policy's implementation due to CC, leading to a shortfall in its sustainability and blue growth targets. Significant, climate-driven ecosystem-level shifts in ocean components underpinning designated sites and fishing activity were estimated, reflecting different magnitudes of shifts in benthic versus pelagic, and inshore versus offshore habitats. Supporting adaptation, we then identified: CC refugia (areas where the ecosystem remains within the boundaries of its present state); CC hotspots (where climate drives the ecosystem towards a new state, inconsistent with each sectors' present use distribution); and for the first time, identified bright spots (areas where oceanographic processes drive range expansion opportunities that may support sustainable growth in the medium term). We thus create the means to: identify where sector-relevant ecosystem change is attributable to CC; incorporate resilient delivery of conservation and sustainable ecosystem management aims into MSP; and to harness opportunities for blue growth where they exist. Capturing CC bright spots alongside refugia within protected areas may present important opportunities to meet sustainability targets while helping support the fishing sector in a changing climate. By capitalizing on the natural distribution of climate resilience within ocean ecosystems, such climate-adaptive spat

Climate change is anticipated to have long-term and widespread direct consequences for the European marine ecosystems and subsequently for the European fishery sector. Additionally, many socio-economic and political factors linked to climate change scenarios will impact the future development of fishing industries. Robust projection modeling of bioeconomic consequences of climate change on the European fishing sector must identify all these factors and their potential future interaction. In this study, four socio-political scenarios developed in the EU project CERES (Climate change and European aquatic RESources) were operationalized and used in model projections of marine wild capture fisheries. Four CERES scenarios (“World Markets,” “National Enterprise,” “Global Sustainability” and “Local Stewardship”) were based on the IPCC framework of Shared Socio-economic Pathways (SSPs). For each of these scenarios, a set of quantitative outputs was generated to allow projections of bio-economic impacts to mid-century (2050) on wild-capture fisheries operating in different European regions. Specifically, projections accounted for future changes in fisheries management targets, access regulations, international agreements, fish and fuel prices, technological developments and marine spatial planning. This study thoroughly describes the elements of these four fisheries scenarios and demonstrates an example of the “regionalization” of these scenarios by summarizing how they were applied to the North Sea flatfish fishery. Bioeconomic projections highlight the importance of future developments in fuel and fish price development to the viability of that and other fisheries. Adapting these scenarios for use in other models and regions outside the 10 European fisheries examined in CERES would be highly beneficial by allowing direct comparison of the bioeconomic risks and opportunities posed by climate change.

Climate change is anticipated to have long-term and widespread direct consequences for the European marine ecosystems and subsequently for the European fishery sector. Additionally, many socio-economic and political factors linked to climate change scenarios will impact the future development of fishing industries. Robust projection modeling of bioeconomic consequences of climate change on the European fishing sector must identify all these factors and their potential future interaction. In this study, four socio-political scenarios developed in the EU project CERES (Climate change and European aquatic RESources) were operationalized and used in model projections of marine wild capture fisheries. Four CERES scenarios (“World Markets,” “National Enterprise,” “Global Sustainability” and “Local Stewardship”) were based on the IPCC framework of Shared Socio-economic Pathways (SSPs). For each of these scenarios, a set of quantitative outputs was generated to allow projections of bio-economic impacts to mid-century (2050) on wild-capture fisheries operating in different European regions. Specifically, projections accounted for future changes in fisheries management targets, access regulations, international agreements, fish and fuel prices, technological developments and marine spatial planning. This study thoroughly describes the elements of these four fisheries scenarios and demonstrates an example of the “regionalization” of these scenarios by summarizing how they were applied to the North Sea flatfish fishery. Bioeconomic projections highlight the importance of future developments in fuel and fish price development to the viability of that and other fisheries. Adapting these scenarios for use in other models and regions outside the 10 European fisheries examined in CERES would be highly beneficial by allowing direct comparison of the bioeconomic risks and opportunities posed by climate change.

High-latitude ecosystems are among the fastest warming on the planet1. Polar species may be sensitive to warming and ice loss, but data are scarce and evidence is conflicting2,3,4. Here, we show that, within their main population centre in the southwest Atlantic sector, the distribution of Euphausia superba (hereafter, ‘krill’) has contracted southward over the past 90 years. Near their northern limit, numerical densities have declined sharply and the population has become more concentrated towards the Antarctic shelves. A concomitant increase in mean body length reflects reduced recruitment of juvenile krill. We found evidence for environmental controls on recruitment, including a reduced density of juveniles following positive anomalies of the Southern Annular Mode. Such anomalies are associated with warm, windy and cloudy weather and reduced sea ice, all of which may hinder egg production and the survival of larval krill5. However, the total post-larval density has declined less steeply than the density of recruits, suggesting that survival rates of older krill have increased. The changing distribution is already perturbing the krill-centred food web6 and may affect biogeochemical cycling7,8. Rapid climate change, with associated nonlinear adjustments in the roles of keystone species, poses challenges for the management of valuable polar ecosystems3.

High-latitude ecosystems are among the fastest warming on the planet1. Polar species may be sensitive to warming and ice loss, but data are scarce and evidence is conflicting2,3,4. Here, we show that, within their main population centre in the southwest Atlantic sector, the distribution of Euphausia superba (hereafter, ‘krill’) has contracted southward over the past 90 years. Near their northern limit, numerical densities have declined sharply and the population has become more concentrated towards the Antarctic shelves. A concomitant increase in mean body length reflects reduced recruitment of juvenile krill. We found evidence for environmental controls on recruitment, including a reduced density of juveniles following positive anomalies of the Southern Annular Mode. Such anomalies are associated with warm, windy and cloudy weather and reduced sea ice, all of which may hinder egg production and the survival of larval krill5. However, the total post-larval density has declined less steeply than the density of recruits, suggesting that survival rates of older krill have increased. The changing distribution is already perturbing the krill-centred food web6 and may affect biogeochemical cycling7,8. Rapid climate change, with associated nonlinear adjustments in the roles of keystone species, poses challenges for the management of valuable polar ecosystems3.

The Plymouth L4 time plankton series in the Western English Channel is a textbook example of a shallow, stratifying shelf sea system. Over its 30 yr of weekly sampling, this site has provided a diverse and contrasting suite of numerical and conceptual models of plankton bloom formation, phenology, and seasonal succession. The most recent of these papers, Kenitz et al. (2017) has initiated this comment, partly because we feel that it has presented a slightly misleading picture of the plankton composition at this site, and of a robust, recurring seasonal succession. We address this by illustrating the extent of inter-annual variability in phenology that occurs at the site, and which needs to be captured better within models. However our main aim is to foster a much better integration of the variety of top-down and bottom-up processes that have all been suggested to be key in driving seasonal succession. Some of these, particularly the multiple grazing and growth controls contributing to the so-called "loophole hypothesis" may be complementary, but others, such as the role of copepod feeding traits in driving species succession (Kenitz et al. 2017) offer testable competing hypotheses. The basic assumptions and outputs of all these models need to be validated more critically, both against time series data and process studies that include the finding of unselective feeding. We suggest that the variability in plankton phenology (and not just mean timing and amplitude) could be used to diagnose the performance of alternative models of plankton succession.

The present study describes the responses of summer phytoplankton biomass to changes in top-down forcing (expressed as zooplankton mortality) in three ecosystems (the North Sea, the Baltic Sea and the Nordic Seas) across different 3D ecosystem models. In each of the model set-ups, we applied the same changes in the magnitude of mortality (±20%) of the highest trophic zooplankton level (Z1). Model results showed overall dampened responses of phytoplankton relative to Z1 biomass. Phytoplankton responses varied depending on the food web structure and trophic coupling represented in the models. Hence, a priori model assumptions were found to influence cascades and pathways in model estimates and, thus, become highly relevant when examining ecosystem pressures such as fishing and climate change. Especially, the different roles and parameterizations of additional zooplankton groups grazed by Z1, and their importance for the outcome, emphasized the need for better calibration data. Spatial variability was high within each model indicating that physics (hydrodynamics and temperature) and nutrient dynamics also play vital roles for ecosystem responses to top-down effects. In conclusion, the model comparison indicated that changes in top-down forcing in combination with the modelled food-web structure affect summer phytoplankton biomass and, thereby, indirectly influence water quality of the systems.

Author Posting. © The Author(s), 2018. This is the author's version of the work. It is posted here under a nonexclusive, irrevocable, paid-up, worldwide license granted to WHOI. It is made available for personal use, not for redistribution. The definitive version was published in Ecological Modelling 376 (2018): 54-67, doi:10.1016/j.ecolmodel.2018.03.003., The present study describes the responses of summer phytoplankton biomass to changes in top-down forcing (expressed as zooplankton mortality) in three ecosystems (the North Sea, the Baltic Sea and the Nordic Seas) across different 3D ecosystem models. In each of the model set-ups, we applied the same changes in the magnitude of mortality (±20%) of the highest trophic zooplankton level (Z1). Model results showed overall dampened responses of phytoplankton relative to Z1 biomass. Phytoplankton responses varied depending on the food web structure and trophic coupling represented in the models. Hence, a priori model assumptions were found to influence cascades and pathways in model estimates and, thus, become highly relevant when examining ecosystem pressures such as fishing and climate change. Especially, the different roles and parameterizations of additional zooplankton groups grazed by Z1, and their importance for the outcome, emphasized the need for better calibration data. Spatial variability was high within each model indicating that physics (hydrodynamics and temperature) and nutrient dynamics also play vital roles for ecosystem responses to top-down effects. In conclusion, the model comparison indicated that changes in top-down forcing in combination with the modelled food-web structure affect summer phytoplankton biomass and, thereby, indirectly influence water quality of the systems., The work was supported by the EU grant “Vectors of Change in Oceans and Seas, Marine Life, Impact and Economic Sectors” (Vectors, FP7/2010-2013) and The Danish Council for Strategic Research to the project “Integrated Management of Agriculture, Fishery, Environment and Economy” (IMAGE, grant no. 09-067259).

Author Posting. © The Author(s), 2018. This is the author's version of the work. It is posted here under a nonexclusive, irrevocable, paid-up, worldwide license granted to WHOI. It is made available for personal use, not for redistribution. The definitive version was published in Ecological Modelling 376 (2018): 54-67, doi:10.1016/j.ecolmodel.2018.03.003., The present study describes the responses of summer phytoplankton biomass to changes in top-down forcing (expressed as zooplankton mortality) in three ecosystems (the North Sea, the Baltic Sea and the Nordic Seas) across different 3D ecosystem models. In each of the model set-ups, we applied the same changes in the magnitude of mortality (±20%) of the highest trophic zooplankton level (Z1). Model results showed overall dampened responses of phytoplankton relative to Z1 biomass. Phytoplankton responses varied depending on the food web structure and trophic coupling represented in the models. Hence, a priori model assumptions were found to influence cascades and pathways in model estimates and, thus, become highly relevant when examining ecosystem pressures such as fishing and climate change. Especially, the different roles and parameterizations of additional zooplankton groups grazed by Z1, and their importance for the outcome, emphasized the need for better calibration data. Spatial variability was high within each model indicating that physics (hydrodynamics and temperature) and nutrient dynamics also play vital roles for ecosystem responses to top-down effects. In conclusion, the model comparison indicated that changes in top-down forcing in combination with the modelled food-web structure affect summer phytoplankton biomass and, thereby, indirectly influence water quality of the systems., The work was supported by the EU grant “Vectors of Change in Oceans and Seas, Marine Life, Impact and Economic Sectors” (Vectors, FP7/2010-2013) and The Danish Council for Strategic Research to the project “Integrated Management of Agriculture, Fishery, Environment and Economy” (IMAGE, grant no. 09-067259).

The Plymouth L4 time plankton series in the Western English Channel is a textbook example of a shallow, stratifying shelf sea system. Over its 30 yr of weekly sampling, this site has provided a diverse and contrasting suite of numerical and conceptual models of plankton bloom formation, phenology, and seasonal succession. The most recent of these papers, Kenitz et al. (2017) has initiated this comment, partly because we feel that it has presented a slightly misleading picture of the plankton composition at this site, and of a robust, recurring seasonal succession. We address this by illustrating the extent of inter-annual variability in phenology that occurs at the site, and which needs to be captured better within models. However our main aim is to foster a much better integration of the variety of top-down and bottom-up processes that have all been suggested to be key in driving seasonal succession. Some of these, particularly the multiple grazing and growth controls contributing to the so-called "loophole hypothesis" may be complementary, but others, such as the role of copepod feeding traits in driving species succession (Kenitz et al. 2017) offer testable competing hypotheses. The basic assumptions and outputs of all these models need to be validated more critically, both against time series data and process studies that include the finding of unselective feeding. We suggest that the variability in plankton phenology (and not just mean timing and amplitude) could be used to diagnose the performance of alternative models of plankton succession.

The present study describes the responses of summer phytoplankton biomass to changes in top-down forcing (expressed as zooplankton mortality) in three ecosystems (the North Sea, the Baltic Sea and the Nordic Seas) across different 3D ecosystem models. In each of the model set-ups, we applied the same changes in the magnitude of mortality (±20%) of the highest trophic zooplankton level (Z1). Model results showed overall dampened responses of phytoplankton relative to Z1 biomass. Phytoplankton responses varied depending on the food web structure and trophic coupling represented in the models. Hence, a priori model assumptions were found to influence cascades and pathways in model estimates and, thus, become highly relevant when examining ecosystem pressures such as fishing and climate change. Especially, the different roles and parameterizations of additional zooplankton groups grazed by Z1, and their importance for the outcome, emphasized the need for better calibration data. Spatial variability was high within each model indicating that physics (hydrodynamics and temperature) and nutrient dynamics also play vital roles for ecosystem responses to top-down effects. In conclusion, the model comparison indicated that changes in top-down forcing in combination with the modelled food-web structure affect summer phytoplankton biomass and, thereby, indirectly influence water quality of the systems.

The Plymouth L4 time plankton series in the Western English Channel is a textbook example of a shallow, stratifying shelf sea system. Over its 30 yr of weekly sampling, this site has provided a diverse and contrasting suite of numerical and conceptual models of plankton bloom formation, phenology, and seasonal succession. The most recent of these papers, Kenitz et al. (2017) has initiated this comment, partly because we feel that it has presented a slightly misleading picture of the plankton composition at this site, and of a robust, recurring seasonal succession. We address this by illustrating the extent of inter-annual variability in phenology that occurs at the site, and which needs to be captured better within models. However our main aim is to foster a much better integration of the variety of top-down and bottom-up processes that have all been suggested to be key in driving seasonal succession. Some of these, particularly the multiple grazing and growth controls contributing to the so-called "loophole hypothesis" may be complementary, but others, such as the role of copepod feeding traits in driving species succession (Kenitz et al. 2017) offer testable competing hypotheses. The basic assumptions and outputs of all these models need to be validated more critically, both against time series data and process studies that include the finding of unselective feeding. We suggest that the variability in plankton phenology (and not just mean timing and amplitude) could be used to diagnose the performance of alternative models of plankton succession.

The present study describes the responses of summer phytoplankton biomass to changes in top-down forcing (expressed as zooplankton mortality) in three ecosystems (the North Sea, the Baltic Sea and the Nordic Seas) across different 3D ecosystem models. In each of the model set-ups, we applied the same changes in the magnitude of mortality (±20%) of the highest trophic zooplankton level (Z1). Model results showed overall dampened responses of phytoplankton relative to Z1 biomass. Phytoplankton responses varied depending on the food web structure and trophic coupling represented in the models. Hence, a priori model assumptions were found to influence cascades and pathways in model estimates and, thus, become highly relevant when examining ecosystem pressures such as fishing and climate change. Especially, the different roles and parameterizations of additional zooplankton groups grazed by Z1, and their importance for the outcome, emphasized the need for better calibration data. Spatial variability was high within each model indicating that physics (hydrodynamics and temperature) and nutrient dynamics also play vital roles for ecosystem responses to top-down effects. In conclusion, the model comparison indicated that changes in top-down forcing in combination with the modelled food-web structure affect summer phytoplankton biomass and, thereby, indirectly influence water quality of the systems.

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Modelling 261-262 (2013): 43–57, doi:10.1016/j.ecolmodel.2013.04.006., Dynamic Green Ocean Models (DGOMs) include different sets of Plankton Functional Types (PFTs) and equations, thus different interactions and food webs. Using four DGOMs (CCSM-BEC, PISCES, NEMURO and PlankTOM5) we explore how predator–prey interactions influence food web dynamics. Using each model's equations and biomass output, interaction strengths (direct and specific) were calculated and the role of zooplankton in modeled food webs examined. In CCSM-BEC the single size-class adaptive zooplankton preys on different phytoplankton groups according to prey availability and food preferences, resulting in a strong top-down control. In PISCES the micro- and meso-zooplankton groups compete for food resources, grazing phytoplankton depending on their availability in a mixture of bottom-up and top-down control. In NEMURO macrozooplankton controls the biomass of other zooplankton PFTs and defines the structure of the food web with a strong top-down control within the zooplankton. In PlankTOM5, competition and predation between micro- and meso-zooplankton along with strong preferences for nanophytoplankton and diatoms, respectively, leads to their mutual exclusion with a mixture of bottom-up and top-down control of the plankton community composition. In each model, the grazing pressure of the zooplankton PFTs and the way it is exerted on their preys may result in the food web dynamics and structure of the model to diverge from the one that was intended when designing the model. Our approach shows that the food web dynamics, in particular the strength of the predator–prey interactions, are driven by the choice of parameters and more specifically the food preferences. Consequently, our findings stress the importance of equation and parameter choice as they define interactions between PFTs and overall food web dynamics (competition, bottom-up or top-down effects). Also, the differences in the simulated food-webs between different models highlight the gap of knowledge for zoopla, This work was supported with funding from Palmer LTER (NSF OPP-0823101) and C-MORE (NSF EF-0424599).

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Modelling 261-262 (2013): 43–57, doi:10.1016/j.ecolmodel.2013.04.006., Dynamic Green Ocean Models (DGOMs) include different sets of Plankton Functional Types (PFTs) and equations, thus different interactions and food webs. Using four DGOMs (CCSM-BEC, PISCES, NEMURO and PlankTOM5) we explore how predator–prey interactions influence food web dynamics. Using each model's equations and biomass output, interaction strengths (direct and specific) were calculated and the role of zooplankton in modeled food webs examined. In CCSM-BEC the single size-class adaptive zooplankton preys on different phytoplankton groups according to prey availability and food preferences, resulting in a strong top-down control. In PISCES the micro- and meso-zooplankton groups compete for food resources, grazing phytoplankton depending on their availability in a mixture of bottom-up and top-down control. In NEMURO macrozooplankton controls the biomass of other zooplankton PFTs and defines the structure of the food web with a strong top-down control within the zooplankton. In PlankTOM5, competition and predation between micro- and meso-zooplankton along with strong preferences for nanophytoplankton and diatoms, respectively, leads to their mutual exclusion with a mixture of bottom-up and top-down control of the plankton community composition. In each model, the grazing pressure of the zooplankton PFTs and the way it is exerted on their preys may result in the food web dynamics and structure of the model to diverge from the one that was intended when designing the model. Our approach shows that the food web dynamics, in particular the strength of the predator–prey interactions, are driven by the choice of parameters and more specifically the food preferences. Consequently, our findings stress the importance of equation and parameter choice as they define interactions between PFTs and overall food web dynamics (competition, bottom-up or top-down effects). Also, the differences in the simulated food-webs between different models highlight the gap of knowledge for zoopla, This work was supported with funding from Palmer LTER (NSF OPP-0823101) and C-MORE (NSF EF-0424599).

Author Posting. © American Geophysical Union, 2014. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 28 (2014): 181-196, doi:10.1002/2013GB004743., The export of organic carbon from the surface ocean by sinking particles is an important, yet highly uncertain, component of the global carbon cycle. Here we introduce a mechanistic assessment of the global ocean carbon export using satellite observations, including determinations of net primary production and the slope of the particle size spectrum, to drive a food-web model that estimates the production of sinking zooplankton feces and algal aggregates comprising the sinking particle flux at the base of the euphotic zone. The synthesis of observations and models reveals fundamentally different and ecologically consistent regional-scale patterns in export and export efficiency not found in previous global carbon export assessments. The model reproduces regional-scale particle export field observations and predicts a climatological mean global carbon export from the euphotic zone of ~6 Pg C yr−1. Global export estimates show small variation (typically < 10%) to factor of 2 changes in model parameter values. The model is also robust to the choices of the satellite data products used and enables interannual changes to be quantified. The present synthesis of observations and models provides a path for quantifying the ocean's biological pump., D.A.S. and K.O.B. acknowledge support from the National Aeronautics and Space Administration (NNX11AF63G). S.C.D. and S.F.S. acknowledge support from the National Science Foundation through the Center for Microbial Oceanography: Research and Education (C-MORE) (NSF EF-0424599)., 2014-09-10

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 10 (2013); 6833-6850, doi:10.5194/bg-10-6833-2013., We investigated the mechanisms of phytoplankton competition during the spring bloom, one of the most dramatic seasonal events in lower-trophic-level ecosystems, in four state-of-the-art plankton functional type (PFT) models: PISCES, NEMURO, PlankTOM5 and CCSM-BEC. In particular, we investigated the relative importance of different ecophysiological processes on the determination of the community structure, focusing both on the bottom-up and the top-down controls. The models reasonably reproduced the observed global distribution and seasonal variation of phytoplankton biomass. The fraction of diatoms with respect to the total phytoplankton biomass increases with the magnitude of the spring bloom in all models. However, the governing mechanisms differ between models, despite the fact that current PFT models represent ecophysiological processes using the same types of parameterizations. The increasing trend in the percentage of diatoms with increasing bloom magnitude is mainly caused by a stronger nutrient dependence of diatom growth compared to nanophytoplankton (bottom-up control). The difference in the maximum growth rate plays an important role in NEMURO and PlankTOM5 and determines the absolute values of the percentage of diatoms during the bloom. In CCSM-BEC, the light dependency of growth plays an important role in the North Atlantic and the Southern Ocean. The grazing pressure by zooplankton (top-down control), however, strongly contributes to the dominance of diatoms in PISCES and CCSM-BEC. The regional differences in the percentage of diatoms in PlankTOM5 are mainly determined by top-down control. These differences in the mechanisms suggest that the response of marine ecosystems to climate change could significantly differ among models, even if the present-day ecosystem is reproduced to a similar degree of confidence. For further understanding of plankton competition and for the prediction of future change in marine ecosystems, it is important to understand th, T. Hashioka, Y. Yamanaka and T. Hirata, were supported by the Grant-in-Aid for the Global COE Program from MEXT, by the Global Environment Research Fund (S-5) from the Ministry of the Environment and by the Strategic Young Researcher Overseas Visits Program for Accelerating Brain Circulation from JSPS. S. Doney, I. Lima and S. Sailley acknowledge support from C-MORE (NSF EF-0424599).

Author Posting. © American Geophysical Union, 2014. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 28 (2014): 181-196, doi:10.1002/2013GB004743., The export of organic carbon from the surface ocean by sinking particles is an important, yet highly uncertain, component of the global carbon cycle. Here we introduce a mechanistic assessment of the global ocean carbon export using satellite observations, including determinations of net primary production and the slope of the particle size spectrum, to drive a food-web model that estimates the production of sinking zooplankton feces and algal aggregates comprising the sinking particle flux at the base of the euphotic zone. The synthesis of observations and models reveals fundamentally different and ecologically consistent regional-scale patterns in export and export efficiency not found in previous global carbon export assessments. The model reproduces regional-scale particle export field observations and predicts a climatological mean global carbon export from the euphotic zone of ~6 Pg C yr−1. Global export estimates show small variation (typically < 10%) to factor of 2 changes in model parameter values. The model is also robust to the choices of the satellite data products used and enables interannual changes to be quantified. The present synthesis of observations and models provides a path for quantifying the ocean's biological pump., D.A.S. and K.O.B. acknowledge support from the National Aeronautics and Space Administration (NNX11AF63G). S.C.D. and S.F.S. acknowledge support from the National Science Foundation through the Center for Microbial Oceanography: Research and Education (C-MORE) (NSF EF-0424599)., 2014-09-10

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biogeosciences 10 (2013); 6833-6850, doi:10.5194/bg-10-6833-2013., We investigated the mechanisms of phytoplankton competition during the spring bloom, one of the most dramatic seasonal events in lower-trophic-level ecosystems, in four state-of-the-art plankton functional type (PFT) models: PISCES, NEMURO, PlankTOM5 and CCSM-BEC. In particular, we investigated the relative importance of different ecophysiological processes on the determination of the community structure, focusing both on the bottom-up and the top-down controls. The models reasonably reproduced the observed global distribution and seasonal variation of phytoplankton biomass. The fraction of diatoms with respect to the total phytoplankton biomass increases with the magnitude of the spring bloom in all models. However, the governing mechanisms differ between models, despite the fact that current PFT models represent ecophysiological processes using the same types of parameterizations. The increasing trend in the percentage of diatoms with increasing bloom magnitude is mainly caused by a stronger nutrient dependence of diatom growth compared to nanophytoplankton (bottom-up control). The difference in the maximum growth rate plays an important role in NEMURO and PlankTOM5 and determines the absolute values of the percentage of diatoms during the bloom. In CCSM-BEC, the light dependency of growth plays an important role in the North Atlantic and the Southern Ocean. The grazing pressure by zooplankton (top-down control), however, strongly contributes to the dominance of diatoms in PISCES and CCSM-BEC. The regional differences in the percentage of diatoms in PlankTOM5 are mainly determined by top-down control. These differences in the mechanisms suggest that the response of marine ecosystems to climate change could significantly differ among models, even if the present-day ecosystem is reproduced to a similar degree of confidence. For further understanding of plankton competition and for the prediction of future change in marine ecosystems, it is important to understand th, T. Hashioka, Y. Yamanaka and T. Hirata, were supported by the Grant-in-Aid for the Global COE Program from MEXT, by the Global Environment Research Fund (S-5) from the Ministry of the Environment and by the Strategic Young Researcher Overseas Visits Program for Accelerating Brain Circulation from JSPS. S. Doney, I. Lima and S. Sailley acknowledge support from C-MORE (NSF EF-0424599).

Author Posting. © The Oceanography Society, 2013. This article is posted here by permission of The Oceanography Society] for personal use, not for redistribution. The definitive version was published in Oceanography 26, no. 3 (2013): 190–203, doi:10.5670/oceanog.2013.62., The extent, duration, and seasonality of sea ice and glacial discharge strongly influence Antarctic marine ecosystems. Most organisms' life cycles in this region are attuned to ice seasonality. The annual retreat and melting of sea ice in the austral spring stratifies the upper ocean, triggering large phytoplankton blooms. The magnitude of the blooms is proportional to the winter extent of ice cover, which can act as a barrier to wind mixing. Antarctic krill, one of the most abundant metazoan populations on Earth, consume phytoplankton blooms dominated by large diatoms. Krill, in turn, support a large biomass of predators, including penguins, seals, and whales. Human activity has altered even these remote ecosystems. The western Antarctic Peninsula region has warmed by 7°C over the past 50 years, and sea ice duration has declined by almost 100 days since 1978, causing a decrease in phytoplankton productivity in the northern peninsula region. Besides climate change, Antarctic marine systems have been greatly altered by harvesting of the great whales and now krill. It is unclear to what extent the ecosystems we observe today differ from the pristine state., Palmer LTER is supported by National Science Foundation grant ANT-0823101. Amsler was supported by NSF ANT- 0838773 and ANT-1041022. RaTS is a component of the Polar Oceans research program, funded by the British Antarctic Survey.

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Marine Ecology Progress Series 492 (2013): 253-272, doi:10.3354/meps10534., An inverse food-web model for the western Antarctic Peninsula (WAP) pelagic food web was constrained with data from Palmer Long Term Ecological Research (PAL-LTER) project annual austral summer sampling cruises. Model solutions were generated for 2 regions with Adélie penguin Pygoscelis adeliae colonies presenting different population trends (a northern and a southern colony) for a 12 yr period (1995-2006). Counter to the standard paradigm, comparisons of carbon flow through bacteria, microzooplankton, and krill showed that the diatom-krill-top predator food chain is not the dominant pathway for organic carbon exchanges. The food web is more complex, including significant contributions by microzooplankton and the microbial loop. Using both inverse model results and network indices, it appears that in the northern WAP the food web is dominated by the microbial food web, with a temporal trend toward its increasing importance. The dominant pathway for the southern WAP food web varies from year to year, with no detectable temporal trend toward dominance of microzooplankton versus krill. In addition, sensitivity analyses indicated that the northern colony of Adélie penguins, whose population size has been declining over the past 35 yr, appears to have sufficient krill during summer to sustain its basic metabolic needs and rear chicks, suggesting the importance of other processes in regulating the Adélie population decline., We acknowledge support from the National Science Foundation, Office of Polar Programs, Award 0823101 (Antarctic Organisms and Ecosystems Program) to Palmer LTER.

Author Posting. © The Author(s), 2013. This is the author's version of the work. It is posted here by permission of National Academy of Sciences for personal use, not for redistribution. The definitive version was published in Proceedings of the National Academy of Sciences of the United States of America 110 (2013): 2438–2439, doi:10.1073/pnas.1222736110., Populations of marine species wax and wane over time and space reflecting environmental forcing, biological dynamics, and in some cases human perturbations such as fishing, habitat destruction and climate change. The growing availability of multi‐decadal observational records opens new windows on how ocean ecosystems function, but the analysis and interpretation of such long time-­‐series also requires new mathematical tools and conceptual models. Population time-­‐ series often show strong variations at decadal time‐scales, and a central question is whether this arises from non‐linear biological processes or simply tracking of external physical variability. Borrowing from climate research, Di Lorenzo and Ohman develop a novel approach for deciphering links between physical forcing and biological response, using as a test case time‐series of marine zooplankton abundances off the coast of California., The authors gratefully acknowledge support from the U.S. National Science Foundation through the Palmer Long Term Ecological Research (LTER) project (http://pal.lternet.edu/) (NSF OPP-­‐0823101).

The extent, duration, and seasonality of sea ice and glacial discharge strongly influence Antarctic marine ecosystems. Most organisms' life cycles in this region are attuned to ice seasonality. The annual retreat and melting of sea ice in the austral spring stratifies the upper ocean, triggering large phytoplankton blooms. The magnitude of the blooms is proportional to the winter extent of ice cover, which can act as a barrier to wind mixing. Antarctic krill, one of the most abundant metazoan populations on Earth, consume phytoplankton blooms dominated by large diatoms. Krill, in turn, support a large biomass of predators, including penguins, seals, and whales. Human activity has altered even these remote ecosystems. The western Antarctic Peninsula region has warmed by 7°C over the past 50 years, and sea ice duration has declined by almost 100 days since 1978, causing a decrease in phytoplankton productivity in the northern peninsula region. Besides climate change, Antarctic marine systems have been greatly altered by harvesting of the great whales and now krill. It is unclear to what extent the ecosystems we observe today differ from the pristine state.

Author Posting. © The Author(s), 2013. This is the author's version of the work. It is posted here by permission of National Academy of Sciences for personal use, not for redistribution. The definitive version was published in Proceedings of the National Academy of Sciences of the United States of America 110 (2013): 2438–2439, doi:10.1073/pnas.1222736110., Populations of marine species wax and wane over time and space reflecting environmental forcing, biological dynamics, and in some cases human perturbations such as fishing, habitat destruction and climate change. The growing availability of multi‐decadal observational records opens new windows on how ocean ecosystems function, but the analysis and interpretation of such long time-­‐series also requires new mathematical tools and conceptual models. Population time-­‐ series often show strong variations at decadal time‐scales, and a central question is whether this arises from non‐linear biological processes or simply tracking of external physical variability. Borrowing from climate research, Di Lorenzo and Ohman develop a novel approach for deciphering links between physical forcing and biological response, using as a test case time‐series of marine zooplankton abundances off the coast of California., The authors gratefully acknowledge support from the U.S. National Science Foundation through the Palmer Long Term Ecological Research (LTER) project (http://pal.lternet.edu/) (NSF OPP-­‐0823101).

Author Posting. © The Oceanography Society, 2013. This article is posted here by permission of The Oceanography Society] for personal use, not for redistribution. The definitive version was published in Oceanography 26, no. 3 (2013): 190–203, doi:10.5670/oceanog.2013.62., The extent, duration, and seasonality of sea ice and glacial discharge strongly influence Antarctic marine ecosystems. Most organisms' life cycles in this region are attuned to ice seasonality. The annual retreat and melting of sea ice in the austral spring stratifies the upper ocean, triggering large phytoplankton blooms. The magnitude of the blooms is proportional to the winter extent of ice cover, which can act as a barrier to wind mixing. Antarctic krill, one of the most abundant metazoan populations on Earth, consume phytoplankton blooms dominated by large diatoms. Krill, in turn, support a large biomass of predators, including penguins, seals, and whales. Human activity has altered even these remote ecosystems. The western Antarctic Peninsula region has warmed by 7°C over the past 50 years, and sea ice duration has declined by almost 100 days since 1978, causing a decrease in phytoplankton productivity in the northern peninsula region. Besides climate change, Antarctic marine systems have been greatly altered by harvesting of the great whales and now krill. It is unclear to what extent the ecosystems we observe today differ from the pristine state., Palmer LTER is supported by National Science Foundation grant ANT-0823101. Amsler was supported by NSF ANT- 0838773 and ANT-1041022. RaTS is a component of the Polar Oceans research program, funded by the British Antarctic Survey.

© The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Marine Ecology Progress Series 492 (2013): 253-272, doi:10.3354/meps10534., An inverse food-web model for the western Antarctic Peninsula (WAP) pelagic food web was constrained with data from Palmer Long Term Ecological Research (PAL-LTER) project annual austral summer sampling cruises. Model solutions were generated for 2 regions with Adélie penguin Pygoscelis adeliae colonies presenting different population trends (a northern and a southern colony) for a 12 yr period (1995-2006). Counter to the standard paradigm, comparisons of carbon flow through bacteria, microzooplankton, and krill showed that the diatom-krill-top predator food chain is not the dominant pathway for organic carbon exchanges. The food web is more complex, including significant contributions by microzooplankton and the microbial loop. Using both inverse model results and network indices, it appears that in the northern WAP the food web is dominated by the microbial food web, with a temporal trend toward its increasing importance. The dominant pathway for the southern WAP food web varies from year to year, with no detectable temporal trend toward dominance of microzooplankton versus krill. In addition, sensitivity analyses indicated that the northern colony of Adélie penguins, whose population size has been declining over the past 35 yr, appears to have sufficient krill during summer to sustain its basic metabolic needs and rear chicks, suggesting the importance of other processes in regulating the Adélie population decline., We acknowledge support from the National Science Foundation, Office of Polar Programs, Award 0823101 (Antarctic Organisms and Ecosystems Program) to Palmer LTER.

The extent, duration, and seasonality of sea ice and glacial discharge strongly influence Antarctic marine ecosystems. Most organisms' life cycles in this region are attuned to ice seasonality. The annual retreat and melting of sea ice in the austral spring stratifies the upper ocean, triggering large phytoplankton blooms. The magnitude of the blooms is proportional to the winter extent of ice cover, which can act as a barrier to wind mixing. Antarctic krill, one of the most abundant metazoan populations on Earth, consume phytoplankton blooms dominated by large diatoms. Krill, in turn, support a large biomass of predators, including penguins, seals, and whales. Human activity has altered even these remote ecosystems. The western Antarctic Peninsula region has warmed by 7°C over the past 50 years, and sea ice duration has declined by almost 100 days since 1978, causing a decrease in phytoplankton productivity in the northern peninsula region. Besides climate change, Antarctic marine systems have been greatly altered by harvesting of the great whales and now krill. It is unclear to what extent the ecosystems we observe today differ from the pristine state.

In the context of global warming and climate change Biogeochemical Ocean General Circulation Models (BOGCM) are hard pressed to provide clear and realistic answers as to how ecosystems and the carbon cycle are affected. Ecosystem models have developed from the NPZ type (Nutrient-Plankton-Zooplankton) towards the use of several plankton functional types (PFTs) to enhance the prediction of ecosystem feedback on climate change. PFTs are selected on their impact on biogeochemical cycles. Zooplankton PFTs, for example, are mostly defined by size. Microzooplankton, one of these size classes, is a group of interest due to a high biomass and growth rates which allow these organisms to follow fluctuations in prey concentration. Furthermore, they are known to graze ~40-75% of particulate primary production in the surface ocean, against ~10-15% for the mesozooplankton. As a size class, microzooplankton includes several organisms pelagic ciliates, heterotrophic dinoflagellates, foraminifera, metazoans larva and copepods nauplii with different feeding modes, food preferences, grazing and growth rates. Ciliates and heterotrophic dinoflagellates are the main microzooplankton organisms. Although they are both protozoans, their feeding behaviour and preferred prey size have a substantial difference. In order to assess their differences, results from laboratory experiments were compiled from the literature a total of 342 for ciliates and 161 for dinoflagellates. It emerged that both organisms have a growth and a grazing threshold, also both grazing and growth rates depends on organism size and the size ratio with their prey (size expressed as diameter, volume or carbon content). Ciliates exhibit an increase of their maximal grazing rate past the optimal prey:ciliate ratio of 1:10. Dinoflagellates have a maximal grazing rate which increases to a prey:dinoflagellate ratio of 2:1, then continues to increase past this value, with a marked preference for diatoms over other possible prey t

In the context of global warming and climate change Biogeochemical Ocean General Circulation Models (BOGCM) are hard pressed to provide clear and realistic answers as to how ecosystems and the carbon cycle are affected. Ecosystem models have developed from the NPZ type (Nutrient-Plankton-Zooplankton) towards the use of several plankton functional types (PFTs) to enhance the prediction of ecosystem feedback on climate change. PFTs are selected on their impact on biogeochemical cycles. Zooplankton PFTs, for example, are mostly defined by size. Microzooplankton, one of these size classes, is a group of interest due to a high biomass and growth rates which allow these organisms to follow fluctuations in prey concentration. Furthermore, they are known to graze ~40-75% of particulate primary production in the surface ocean, against ~10-15% for the mesozooplankton. As a size class, microzooplankton includes several organisms pelagic ciliates, heterotrophic dinoflagellates, foraminifera, metazoans larva and copepods nauplii with different feeding modes, food preferences, grazing and growth rates. Ciliates and heterotrophic dinoflagellates are the main microzooplankton organisms. Although they are both protozoans, their feeding behaviour and preferred prey size have a substantial difference. In order to assess their differences, results from laboratory experiments were compiled from the literature a total of 342 for ciliates and 161 for dinoflagellates. It emerged that both organisms have a growth and a grazing threshold, also both grazing and growth rates depends on organism size and the size ratio with their prey (size expressed as diameter, volume or carbon content). Ciliates exhibit an increase of their maximal grazing rate past the optimal prey:ciliate ratio of 1:10. Dinoflagellates have a maximal grazing rate which increases to a prey:dinoflagellate ratio of 2:1, then continues to increase past this value, with a marked preference for diatoms over other possible prey t

In the context of global warming and climate change Biogeochemical Ocean General Circulation Models (BOGCM) are hard pressed to provide clear and realistic answers as to how ecosystems and the carbon cycle are affected. Ecosystem models have developed from the NPZ type (Nutrient-Plankton-Zooplankton) towards the use of several plankton functional types (PFTs) to enhance the prediction of ecosystem feedback on climate change. PFTs are selected on their impact on biogeochemical cycles. Zooplankton PFTs, for example, are mostly defined by size. Microzooplankton, one of these size classes, is a group of interest due to a high biomass and growth rates which allow these organisms to follow fluctuations in prey concentration. Furthermore, they are known to graze ~40-75% of particulate primary production in the surface ocean, against ~10-15% for the mesozooplankton. As a size class, microzooplankton includes several organisms pelagic ciliates, heterotrophic dinoflagellates, foraminifera, metazoans larva and copepods nauplii with different feeding modes, food preferences, grazing and growth rates. Ciliates and heterotrophic dinoflagellates are the main microzooplankton organisms. Although they are both protozoans, their feeding behaviour and preferred prey size have a substantial difference. In order to assess their differences, results from laboratory experiments were compiled from the literature a total of 342 for ciliates and 161 for dinoflagellates. It emerged that both organisms have a growth and a grazing threshold, also both grazing and growth rates depends on organism size and the size ratio with their prey (size expressed as diameter, volume or carbon content). Ciliates exhibit an increase of their maximal grazing rate past the optimal prey:ciliate ratio of 1:10. Dinoflagellates have a maximal grazing rate which increases to a prey:dinoflagellate ratio of 2:1, then continues to increase past this value, with a marked preference for diatoms over other possible prey t