AMEMR 2011
Overview of the third Advances in Marine Ecosystem Modelling Research (AMEMR) Symposium, 27–30 June 2011, Plymouth
The Advances in Marine Ecosystem Modelling Research (AMEMR) symposium series was originally convened to provide a forum for the presentation and discussion of diverse aspects of model based marine ecosystem research, encompassing numerical, conceptual, mathematical and statistical approaches. Our goal has always been focused more on the process (how to model a given issue?) and challenges (what can models aspire to?) than the results (what are the predicted impacts?). The hope was that this symposium series will contribute to the next generation of model based exploration by providing scientists and students an opportunity to discuss and contrast recent advances, outstanding problems and future requirements and since 2005 AMEMR has provided an opportunity to take a snapshot of the current state of progress in the field of marine ecosystem modelling.
The third Advances in Marine Ecosystem Modelling Research Symposium was held in Plymouth in June 2011. It attracted over 200 delegates from Europe, North America and Australia, who between them presented 90 oral and over 100 poster contributions;
Following the conference a Special Issue in the Journal of Marine Systems, Advances in Marine Ecosystem Modelling Research III
Volume 125 (2013) was produced which included a selection of the papers presented during the symposium which cover a wide range of topics. The key themes include foodwebs and diversity; grand challenges; next generation models and lessons learnt; progress towards end to end models and ecosystem responses to climate. Finally there is an emphasis on the practical applications of models in the context of operational forecast, policy development and environmental management.
The influence of the structure of a model on its behaviour is a crucial topic for model development. Cropp and Norbury (2013) demonstrate this point by constructing three plankton ecosystem models each designed to have specific properties and showing that the effect of change on plankton blooms and/or extinctions depends on the properties of the model chosen for the simulation. Similarly the fidelity of the processes descriptions used is also crucial. The next three papers explore the theme that many current parameterisations of key physiological processes in plankton are inadequate to capture our current knowledge of these processes. Glibert (2013) argues that dynamic regulatory concepts are relevant at all levels of ecosystem regulation, that elemental stoichiometry must be considered in physiological, trophodynamic and biogeochemical constructs, and therefore the advancement of models will require new emphasis on competing physiological processes and the feedback mechanisms between them. Ayata et al (2013) compared the qualitative behaviour of a suite of phytoplankton growth formulations with increasing complexity: 1) a Redfield formulation (constant C:N ratio) without photoacclimation (constant Chl:C ratio), 2) a Redfield formulation with diagnostic chlorophyll (variable and empirical Chl:C ratio), 3) a quota formulation (variable C:N ratio) with diagnostic chlorophyll, and 4) a quota formulation with prognostic chlorophyll (dynamic variable). Their results indicate that the most flexible models (i.e., with variable ratios) are necessary to reproduce observations. The role of trophic transfer formulations is examined by Anderson (2013) who assessed the performance of four contemporary formulations with strongly contrasting assumptions in two settings: a simple steady-state ecosystem model and a 3D biogeochemical general circulation model and found considerable variation in predictions for primary production, transfer to higher trophic levels and export to the ocean interior. All three papers highlight the need for modellers to revisit and appraise the equations and parameter values used to describe both physiological processes and trophic transfer in marine ecosystem models. Warne et al (2013) present a more specific example which focuses on modelling the life cycle processes of dinoflagellates including encystment, which is not fully understood. The development of a numerical model has led to the identification and formalisation of the functional dependence for growth, cyst formation, and environmental factors.
A major area of model development over the last few years has been the explicit two way coupling of biogeochemical and fish models. The work of Radtke et al (2013) applies an end to end nutrient-to-fish-model with explicit two-way interactions between the biogeochemical model of the lower food web and a fish model to the Baltic Sea. The dynamics of the fish model is driven by size (mass-class) dependent predator-prey interactions while the interaction between the biogeochemical and Fish model component is established through feeding of prey fish on zooplankton and recycling of fish biomass to nutrients and detritus.
The alternative approach to the dynamic modelling of fisheries is the statistical approach. Hossack et al (2013) use a Bayesian approach to explore potential mechanisms to explain the negative dependence between sardine and anchovy. In general, the sardine and anchovy landings suggest weak intraspecific density dependence and susceptibility to both environmental and anthropogenic perturbation. Results additionally suggest that the best fitting hypothesis depends on the choice of geographic scale, temporal scale, and stock definition of the recorded landings.
Coastal seas provide many beneficial goods and services to humankind, such as fisheries, recreation, climate regulation and coastal defences. However, these marine environments are being disrupted by climate change and human activities. It is important that the marine environment is observed and monitored to provide high quality environmental information and data, understand its role in our Earth system, track changes and predict the potential response of the ocean to stressors.
Operational ecology refers to the provision of operational services for biogeochemical and ecological parameters through a forecast system to project the future status of marine ecosystems by delivering a suite of error quantified indicators which describe changes in ecosystem function. The system should include an observational network along with models of the hydrodynamics, lower and higher trophic levels (plankton to fish) and biological data assimilation. Such systems are required to help assess and manage the risks posed by human activities on the marine environment.
The final set of papers all make a contribution to this aspiration. Data assimilation is required to combine models and data to obtain the best estimate of the current state of the system. A major challenge is robust assimilation during periods of large ecosystem variability; the paper by Triantafyllou et al (2013) demonstrates an assimilation scheme designed to cope with such changes. The response of ecosystems to external drivers is also an important consideration for Operational Ecology. There has been much emphasis put on impacts of riverine inputs and ocean shelf exchange, but much less consideration of atmospheric inputs. The paper by Troost et al (2013) quantifies the relative contribution of atmospheric deposition to total nitrogen in the southern North Sea, demonstrating the ecosystem may be highly sensitive to changes in atmospheric deposition.
The ultimate goal of Operational Ecology is to produce forecasts of the current state of the system. One such example is the Chesapeake Bay Ecological Prediction System (CBEPS), which automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as: sea-surface temperature and salinity; the concentrations of chlorophyll, nitrate, and dissolved oxygen; and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens. All of these variables are useful with respect to the monitoring the Bay's ecosystem, as described in the final paper (Brown et al 2013).
The Advances in Marine Ecosystem Modelling Research (AMEMR) symposium series was originally convened to provide a forum for the presentation and discussion of diverse aspects of model based marine ecosystem research, encompassing numerical, conceptual, mathematical and statistical approaches. Our goal has always been focused more on the process (how to model a given issue?) and challenges (what can models aspire to?) than the results (what are the predicted impacts?). The hope was that this symposium series will contribute to the next generation of model based exploration by providing scientists and students an opportunity to discuss and contrast recent advances, outstanding problems and future requirements and since 2005 AMEMR has provided an opportunity to take a snapshot of the current state of progress in the field of marine ecosystem modelling.
The third Advances in Marine Ecosystem Modelling Research Symposium was held in Plymouth in June 2011. It attracted over 200 delegates from Europe, North America and Australia, who between them presented 90 oral and over 100 poster contributions;
Following the conference a Special Issue in the Journal of Marine Systems, Advances in Marine Ecosystem Modelling Research III
Volume 125 (2013) was produced which included a selection of the papers presented during the symposium which cover a wide range of topics. The key themes include foodwebs and diversity; grand challenges; next generation models and lessons learnt; progress towards end to end models and ecosystem responses to climate. Finally there is an emphasis on the practical applications of models in the context of operational forecast, policy development and environmental management.
The influence of the structure of a model on its behaviour is a crucial topic for model development. Cropp and Norbury (2013) demonstrate this point by constructing three plankton ecosystem models each designed to have specific properties and showing that the effect of change on plankton blooms and/or extinctions depends on the properties of the model chosen for the simulation. Similarly the fidelity of the processes descriptions used is also crucial. The next three papers explore the theme that many current parameterisations of key physiological processes in plankton are inadequate to capture our current knowledge of these processes. Glibert (2013) argues that dynamic regulatory concepts are relevant at all levels of ecosystem regulation, that elemental stoichiometry must be considered in physiological, trophodynamic and biogeochemical constructs, and therefore the advancement of models will require new emphasis on competing physiological processes and the feedback mechanisms between them. Ayata et al (2013) compared the qualitative behaviour of a suite of phytoplankton growth formulations with increasing complexity: 1) a Redfield formulation (constant C:N ratio) without photoacclimation (constant Chl:C ratio), 2) a Redfield formulation with diagnostic chlorophyll (variable and empirical Chl:C ratio), 3) a quota formulation (variable C:N ratio) with diagnostic chlorophyll, and 4) a quota formulation with prognostic chlorophyll (dynamic variable). Their results indicate that the most flexible models (i.e., with variable ratios) are necessary to reproduce observations. The role of trophic transfer formulations is examined by Anderson (2013) who assessed the performance of four contemporary formulations with strongly contrasting assumptions in two settings: a simple steady-state ecosystem model and a 3D biogeochemical general circulation model and found considerable variation in predictions for primary production, transfer to higher trophic levels and export to the ocean interior. All three papers highlight the need for modellers to revisit and appraise the equations and parameter values used to describe both physiological processes and trophic transfer in marine ecosystem models. Warne et al (2013) present a more specific example which focuses on modelling the life cycle processes of dinoflagellates including encystment, which is not fully understood. The development of a numerical model has led to the identification and formalisation of the functional dependence for growth, cyst formation, and environmental factors.
A major area of model development over the last few years has been the explicit two way coupling of biogeochemical and fish models. The work of Radtke et al (2013) applies an end to end nutrient-to-fish-model with explicit two-way interactions between the biogeochemical model of the lower food web and a fish model to the Baltic Sea. The dynamics of the fish model is driven by size (mass-class) dependent predator-prey interactions while the interaction between the biogeochemical and Fish model component is established through feeding of prey fish on zooplankton and recycling of fish biomass to nutrients and detritus.
The alternative approach to the dynamic modelling of fisheries is the statistical approach. Hossack et al (2013) use a Bayesian approach to explore potential mechanisms to explain the negative dependence between sardine and anchovy. In general, the sardine and anchovy landings suggest weak intraspecific density dependence and susceptibility to both environmental and anthropogenic perturbation. Results additionally suggest that the best fitting hypothesis depends on the choice of geographic scale, temporal scale, and stock definition of the recorded landings.
Coastal seas provide many beneficial goods and services to humankind, such as fisheries, recreation, climate regulation and coastal defences. However, these marine environments are being disrupted by climate change and human activities. It is important that the marine environment is observed and monitored to provide high quality environmental information and data, understand its role in our Earth system, track changes and predict the potential response of the ocean to stressors.
Operational ecology refers to the provision of operational services for biogeochemical and ecological parameters through a forecast system to project the future status of marine ecosystems by delivering a suite of error quantified indicators which describe changes in ecosystem function. The system should include an observational network along with models of the hydrodynamics, lower and higher trophic levels (plankton to fish) and biological data assimilation. Such systems are required to help assess and manage the risks posed by human activities on the marine environment.
The final set of papers all make a contribution to this aspiration. Data assimilation is required to combine models and data to obtain the best estimate of the current state of the system. A major challenge is robust assimilation during periods of large ecosystem variability; the paper by Triantafyllou et al (2013) demonstrates an assimilation scheme designed to cope with such changes. The response of ecosystems to external drivers is also an important consideration for Operational Ecology. There has been much emphasis put on impacts of riverine inputs and ocean shelf exchange, but much less consideration of atmospheric inputs. The paper by Troost et al (2013) quantifies the relative contribution of atmospheric deposition to total nitrogen in the southern North Sea, demonstrating the ecosystem may be highly sensitive to changes in atmospheric deposition.
The ultimate goal of Operational Ecology is to produce forecasts of the current state of the system. One such example is the Chesapeake Bay Ecological Prediction System (CBEPS), which automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as: sea-surface temperature and salinity; the concentrations of chlorophyll, nitrate, and dissolved oxygen; and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens. All of these variables are useful with respect to the monitoring the Bay's ecosystem, as described in the final paper (Brown et al 2013).