Marine Ecosystem Model Research Articles

Building bridges between global information systems on marine organisms and ecosystem models

To facilitate the wider implementation of ecosystem modeling platforms and, thereby, to help advance ecosystem-based fisheries management (EBFM) worldwide, tools delivering a large quantity of inputs to ecosystem models are needed. We developed a web application providing OSMOSE ecosystem models with values for trophic, growth and reproduction parameters derived from data from two global information systems (FishBase and SeaLifeBase). Our web application guides the user through simple queries to extract information from FishBase and SeaLifeBase data archives, and it delivers all the configuration files necessary for running an OSMOSE model. Here, we present our web application and demonstrate it for the West Florida Shelf ecosystem. Our software architecture can serve as a basis for designing other advanced web applications using FishBase and SeaLifeBase data in support of EBFM.

Using stable isotope data to advance marine food web modelling

Marine ecosystem models that incorporate fisheries and climate change are essential for forecasting and guiding sustainable ecosystem management decisions. A key challenge in developing and applying ecosystem models that are able to provide robust predictions for management is to accurately represent the structure and dynamics of food webs. Ecosystem models vary in complexity and formulation and there is no set method routinely used to evaluate the skill of a model to correctly represent food web characteristics. One approach for evaluation is the comparison of modelled food web attributes with measures of stable isotope composition of taxa. While this approach has been used in some studies, its full potential has not been realised. Critically, directly modelling the assumed underlying processes that give rise to stable isotope signatures in ecosystem models has only just begun to be explored. Here, we examine the process of building ecosystem models and assess the potential for incorporating stable isotope results into this process, including the evaluation of model skill. We consider both size- and species- based ecosystem modelling approaches for their potential in this regard. We discuss that whilst conceptually achievable, in practice this is highly challenging through highlighting the advances and challenges in using stable isotope data, including the implications of precision associated with isotope-based measurements. We conclude with a proposed framework for explicitly integrating stable isotope data into both size- and species- based ecosystem models as an example of how signatures may be more powerfully used in the modelling process, and highlight key needs for future work.

Main factors favoring Mnemiopsis leidyi individuals growth and population outbreaks: A modelling approach

Abstract A population model of the marine invasive ctenophore species Mneniopsis leidyi (ML) including physiological and demographic processes has been included in the flexible-stoichiometry biogeochemical marine ecosystem model (Eco3M-MED). This model is used in order to define through several numerical simulations possible environmental windows favorable to ML adaptation and outbreaks in invaded habitats, such as the coastal areas of the Mediterranean Sea. One of the strengths of the ML model is that it delivers the functional response either expressed in terms of consumed individual prey or in prey biomass, however the prey are expressed, as individual abundance or biomass concentration. Numerical experiments were performed to test the functional response in various quantitative and qualitative diet conditions. Longer term experiments including starvation regimes were run to characterize the response of the ML population in terms of growth rate and dynamics. Our results firstly show that the required food conditions for ML outbursts, which involve combinations of food quality and quantity, should mainly be found in the most productive Mediterranean coastal areas, and more rarely in the open sea, and that variations in food concentrations may induce rapid outbursts or collapse of ML populations. Results also indicate that food concentrations directly impact reproduction, and that for a given fixed available prey biomass, ML abundance is maximum for the prey of richest nutritional value. As our model considers two levels of ecological integration, individual and population, it has been shown that the response to starvation or to recovery from starvation after food replenishment occurs at different time scales depending on the integration level. Then, different scenarios of global change have been simulated in order to analyze the inter-annual variability in ML population dynamics. Our model could reproduce typical 3 months ML blooms, which is also observed in nature, and it suggests that this is the result of a combination of species properties and environmental forcings. Our simulations also reveal that an increase in temperature promotes the occurrence of jellyfish outbreaks. Finally, the strongest forcing influence on ML dynamics is the reduction of fish competitors for food due to an increase in fishing pressure. This forcing significantly impacts not only the frequency of the outbreaks, but also ML accumulated population growth over a ten-year period. Finally, our simulations call for long-term (over at least a ten-year period) observations with a temporal resolution of one month or less.

Ecological ReGional Ocean Model with vertically resolved sediments (ERGOM SED 1.0): coupling benthic and pelagic biogeochemistry of the south-western Baltic Sea

Abstract. Sediments play an important role in organic matter mineralisation and nutrient recycling, especially in shallow marine systems. Marine ecosystem models, however, often only include a coarse representation of processes beneath the sea floor. While these parameterisations may give a reasonable description of the present ecosystem state, they lack predictive capacity for possible future changes, which can only be obtained from mechanistic modelling. This paper describes an integrated benthic–pelagic ecosystem model developed for the German Exclusive Economic Zone (EEZ) in the western Baltic Sea. The model is a hybrid of two existing models: the pelagic part of the marine ecosystem model ERGOM and an early diagenetic model by Reed et al. (2011). The latter one was extended to include the carbon cycle, a determination of precipitation and dissolution reactions which accounts for salinity differences, an explicit description of the adsorption of clay minerals, and an alternative pyrite formation pathway. We present a one-dimensional application of the model to seven sites with different sediment types. The model was calibrated with observed pore water profiles and validated with results of sediment composition, bioturbation rates and bentho-pelagic fluxes gathered by in situ incubations of sediments (benthic chambers). The model results generally give a reasonable fit to the observations, even if some deviations are observed, e.g. an overestimation of sulfide concentrations in the sandy sediments. We therefore consider it a good first step towards a three-dimensional representation of sedimentary processes in coupled pelagic–benthic ecosystem models of the Baltic Sea.

Enhanced global optimization methods applied to complex fisheries stock assessment models

Statistical fisheries models are frequently used by researchers and agencies to understand the behavior of marine ecosystems or to estimate the maximum acceptable catch of different species of commercial interest. The parameters of these models are usually adjusted through the use of optimization algorithms. Unfortunately, the choice of the best optimization method is far from trivial. This work proposes the use of population-based algorithms to improve the optimization process of the Globally applicable Area Disaggregated General Ecosystem Toolbox (Gadget), a flexible framework that allows the development of complex statistical marine ecosystem models. Specifically, parallel versions of the Differential Evolution (DE) and the Particle Swarm Optimization (PSO) methods are proposed. The proposals include an automatic selection of the internal parameters to reduce the complexity of their usage, and a restart mechanism to avoid local minima. The resulting optimization algorithms were called PMA (Parallel Multirestart Adaptive) DE and PMA PSO respectively. Experimental results prove that the new algorithms are faster and produce more accurate solutions than the other parallel optimization methods already included in Gadget. Although the new proposals have been evaluated on fisheries models, there is nothing specific to the tested models in them, and thus they can be also applied to other optimization problems. Moreover, the PMA scheme proposed can be seen as a template that can be easily applied to other population-based heuristics.

Energetically relevant predator-prey body mass ratios and their relationship with predator body size.

Food web structure and dynamics depend on relationships between body sizes of predators and their prey. Species‐based and community‐wide estimates of preferred and realized predator–prey mass ratios (PPMR) are required inputs to size‐based size spectrum models of marine communities, food webs, and ecosystems. Here, we clarify differences between PPMR definitions in different size spectrum models, in particular differences between PPMR measurements weighting prey abundance in individual predators by biomass (r bio) and numbers (r num). We argue that the former weighting generates PPMR as usually conceptualized in equilibrium (static) size spectrum models while the latter usually applies to dynamic models. We use diet information from 170,689 individuals of 34 species of fish in Alaskan marine ecosystems to calculate both PPMR metrics. Using hierarchical models, we examine how explained variance in these metrics changed with predator body size, predator taxonomic resolution, and spatial resolution. In the hierarchical analysis, variance in both metrics emerged primarily at the species level and substantially less variance was associated with other (higher) taxonomic levels or with spatial resolution. This suggests that changes in species composition are the main drivers of community‐wide mean PPMR. At all levels of analysis, relationships between weighted mean r bio or weighted mean r num and predator mass tended to be dome‐shaped. Weighted mean r num values, for species and community‐wide, were approximately an order of magnitude higher than weighted mean r bio, reflecting the consistent numeric dominance of small prey in predator diets. As well as increasing understanding of the drivers of variation in PPMR and providing estimates of PPMR in the north Pacific Ocean, our results demonstrate that that r bio or r num, as well as their corresponding weighted means for any defined group of predators, are not directly substitutable. When developing equilibrium size‐based models based on bulk energy flux or comparing PPMR estimates derived from the relationship between body mass and trophic level with those based on diet analysis, weighted mean r bio is a more appropriate measure of PPMR. When calibrating preference PPMR in dynamic size spectrum models then weighted mean r num will be a more appropriate measure of PPMR.

Twenty‐first‐century climate change impacts on marine animal biomass and ecosystem structure across ocean basins

Climate change effects on marine ecosystems include impacts on primary production, ocean temperature, species distributions, and abundance at local to global scales. These changes will significantly alter marine ecosystem structure and function with associated socio-economic impacts on ecosystem services, marine fisheries, and fishery-dependent societies. Yet how these changes may play out among ocean basins over the 21st century remains unclear, with most projections coming from single ecosystem models that do not adequately capture the range of model uncertainty. We address this by using six marine ecosystem models within the Fisheries and Marine Ecosystem Model Intercomparison Project (Fish-MIP) to analyze responses of marine animal biomass in all major ocean basins to contrasting climate change scenarios. Under a high emissions scenario (RCP8.5), total marine animal biomass declined by an ensemble mean of 15%-30% (±12%-17%) in the North and South Atlantic and Pacific, and the Indian Ocean by 2100, whereas polar ocean basins experienced a 20%-80% (±35%-200%) increase. Uncertainty and model disagreement were greatest in the Arctic and smallest in the South Pacific Ocean. Projected changes were reduced under a low (RCP2.6) emissions scenario. Under RCP2.6 and RCP8.5, biomass projections were highly correlated with changes in net primary production and negatively correlated with projected sea surface temperature increases across all ocean basins except the polar oceans. Ecosystem structure was projected to shift as animal biomass concentrated in different size-classes across ocean basins and emissions scenarios. We highlight that climate change mitigation measures could moderate the impacts on marine animal biomass by reducing biomass declines in the Pacific, Atlantic, and Indian Ocean basins. The range of individual model projections emphasizes the importance of using an ensemble approach in assessing uncertainty of future change.

Diet uncertainty analysis strengthens model-derived indicators of food web structure and function

Ecological Network Analysis (ENA) can inform marine management decisions by producing indicators that describe ecosystem health and function. Reporting ENA indicators with uncertainty boundaries lets end-users draw stronger inferences and can increase confidence in model results. However, few studies developing these indicators have estimated uncertainty due to data limitations and computational challenges. In this study, we used Linear Inverse Modelling with an Ecopath model of the Irish Sea to investigate how the incorporation of uncertainty in dietary data can strengthen inferences based on model-derived ENA indicators. A Monte Carlo approach was used to generate ten thousand data-bound parameterisations for the Irish Sea food web and provide plausible distribution estimates for functional group diets. ENA results captured the plausible range of state-indicators and provided robust estimates of the control exerted by components within the food web. Results suggest that, higher trophic components, such as mammals, birds, and elasmobranchs in the Irish Sea are controlled by mid-to-low trophic components, such as small pelagic fish, invertebrates, and plankton. Fisheries discards also played an important role in the flow of energy to groups such as Nephrops (Norway lobster), crabs and lobsters, and seabirds. These results bolster our understanding of food web dynamics in the Irish Sea and demonstrate how information derived from ENA indicators can have implications for effective and sustainable ecosystem based management. Finally, the methods established here represent an important step in the maturation of marine ecosystem modelling and ENA for management purposes.

A model for monitoring the evolution of the Black Sea ecosystem on the basis of remote sensing data assimilation

ABSTRACTThe study presents some results of the Black Sea ecosystem dynamics during about twenty years (1998–2016), based on numerical simulations with the assimilation of remote-sensing data. The 3D model of the lower trophic level marine ecosystem is a one-way, off-line coupled with circulation model. It describes processes in the layer from the sea surface to 200 m depth and includes 15 state variables. The ecosystem model assimilates the satellite measurements which are the maps of the surface chlorophyll concentration fields reconstructed based on the remote-sensing data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, satellite OrbView) and Moderate Resolution Imaging Spectroradiometer (MODIS, satellites Aqua and Terra) using the regional optical model of the Black Sea. The assimilation technique is based on optimal interpolation and nudging procedure. The results of the simulation were validated using the Black Sea Oceanographic Database, which contains the direct measurements of chlorophyll, nitrates, and dissolved oxygen concentrations in seawater. Comparison of the simulation data with measurements showed that the simulated fields satisfactorily reproduce seasonal variability and vertical distribution. In addition to in situ measurements, the obtained surface chlorophyll distributions were also compared with the satellite data. The simulation results allowed analysing the inter-annual and seasonal variability of the main parameters of the Black Sea pelagic ecosystem. Evolution of the plankton biomass in the upper 50 m layer shows a negative linear trend, which is followed by reduction of the nitrates content in this layer.

Marine birds and mammals as ecosystem sentinels in and near Distributed Biological Observatory regions: An abbreviated review of published accounts and recommendations for integration to ocean observatories

Marine birds and mammals can act as sentinels to shifts in ocean ecosystems, due to their (i) reliance on finding aggregated prey for efficient foraging, (ii) need to respond to biophysical signals in support of successful seasonal migrations, and (iii) capacity to reflect changes in marine food webs. Here we present an abbreviated review of recent published accounts of marine bird and mammal responses to biophysical features of the ocean ecosystem in and near sampling regions of the Distributed Biological Observatory (DBO). The review is meant to provide both context for seabird surveys and marine mammal watches conducted in conjunction with DBO sampling and support for the inclusion of marine bird and mammal research, either by direct sampling or collaboration, in the protocols of other ocean observatories. The review is framed by the ocean processes imbedded in the Arctic Marine Pulses conceptual model, with the overarching goal to promote the routine integration of data on marine birds and mammals during the development of marine ecosystem models for Arctic regions.

Coupling general ocean circulation models with the BFM marine ecosystem model

The coupling of numerical geophysical models of a sea with marine ecosystem models is considered. For the latter, BFM was chosen and coupled with three Russian models for three seas of different spatial scales: the White Sea (JASMINE), the Arctic Ocean (FEMAO), and the global ocean as a part of the Earth system (INMCM). We describe technical details of implementation and discuss important questions of the computing efficiency and sensitivity of the model to the sea-ice subsystem and boundary values. The ecology model can simultaneously embrace pelagic, benthic, and sympagic ecosystems.

Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific

Abstract. Ecosystem models are used to understand ecosystem dynamics and ocean biogeochemical cycles and require optimum physiological parameters to best represent biological behaviours. These physiological parameters are often tuned up empirically, while ecosystem models have evolved to increase the number of physiological parameters. We developed a three-dimensional (3-D) lower-trophic-level marine ecosystem model known as the Nitrogen, Silicon and Iron regulated Marine Ecosystem Model (NSI-MEM) and employed biological data assimilation using a micro-genetic algorithm to estimate 23 physiological parameters for two phytoplankton functional types in the western North Pacific. The estimation of the parameters was based on a one-dimensional simulation that referenced satellite data for constraining the physiological parameters. The 3-D NSI-MEM optimized by the data assimilation improved the timing of a modelled plankton bloom in the subarctic and subtropical regions compared to the model without data assimilation. Furthermore, the model was able to improve not only surface concentrations of phytoplankton but also their subsurface maximum concentrations. Our results showed that surface data assimilation of physiological parameters from two contrasting observatory stations benefits the representation of vertical plankton distribution in the western North Pacific.

A protocol for the intercomparison of marine fishery and ecosystem models: Fish-MIP v1.0

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.

Assimilation of Ocean‐Color Plankton Functional Types to Improve Marine Ecosystem Simulations

AbstractWe assimilated phytoplankton functional types (PFTs) derived from ocean color into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error‐characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton, and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical‐biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998–2003. The skill of the reference and reanalysis simulations in estimating ocean color and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean‐color PFTs (except nanoplankton), as well as the not‐assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not‐assimilated in situ data of PFTs, as well as of phosphate and pCO2, impacting the simulation of the air‐sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf‐sea ecosystems.

Do functional groups of planktonic copepods differ in their ecological niches?

AbstractAimTo assess the degree of overlap between the environmental niches of marine planktonic copepods and test if the distribution of copepod functional groups differs across environmental gradients.LocationThe Mediterranean Sea.MethodsFunctional groups were defined based on clustering of functional traits in 106 marine copepod species using a multivariate ordination analysis. Functional traits included maximum body length, feeding mode, spawning strategy and trophic group. Simultaneously, the global distribution of the species was used to model their environmental niches with six environmental variables. For each of these predictors, four niche parameters were derived from the univariate response curve of each species to summarise their environmental preferences and ordinate the species in niche space through a PCA. Finally, the differences in the position in niche space of functional groups were tested with variance analysis.ResultsWe identified seven copepod functional groups with different distributions along the environmental gradients covered by our study. While carnivorous functional groups were affiliated with oligotrophic and tropical conditions, large and small current‐feeding herbivores are associated with colder, more seasonally varying and productive conditions. Small cruising detritivores and other small current‐feeding herbivores were not affiliated with specific conditions as their constituting species were scattered in niche space.Main conclusionsSince copepod functional groups occupy distinct ecological niches, ecosystem processes related to these groups are expected to vary across environmental gradients. Conditions favouring large current‐feeding herbivores should allow for enhanced fluxes of energy and nutrients through Mediterranean Sea ecosystems, while such fluxes should be weakened where large carnivores and small passive ambush‐feeding copepods dominate. Our study supports the development of trait‐based zooplankton functional groups in marine ecosystem models.

Improving Marine Ecosystem Models with Biochemical Tracers.

Empirical data on food web dynamics and predator-prey interactions underpin ecosystem models, which are increasingly used to support strategic management of marine resources. These data have traditionally derived from stomach content analysis, but new and complementary forms of ecological data are increasingly available from biochemical tracer techniques. Extensive opportunities exist to improve the empirical robustness of ecosystem models through the incorporation of biochemical tracer data and derived indices, an area that is rapidly expanding because of advances in analytical developments and sophisticated statistical techniques. Here, we explore the trophic information required by ecosystem model frameworks (species, individual, and size based) and match them to the most commonly used biochemical tracers (bulk tissue and compound-specific stable isotopes, fatty acids, and trace elements). Key quantitative parameters derived from biochemical tracers include estimates of diet composition, niche width, and trophic position. Biochemical tracers also provide powerful insight into the spatial and temporal variability of food web structure and the characterization of dominant basal and microbial food web groups. A major challenge in incorporating biochemical tracer data into ecosystem models is scale and data type mismatches, which can be overcome with greater knowledge exchange and numerical approaches that transform, integrate, and visualize data.

Development of a marine ecosystem model to be embedded into an Earth system model

Development of a marine ecosystem model to be embedded into an Earth system model

Effects of incorporating age-specific traits of zooplankton into a marine ecosystem model

Morphological, physiological, behavioral, and life-history traits of zooplankton are vital when assessing their roles in marine ecosystem. A recent study has shown that certain traits of marine copepod change with life stage, where fast growing young nauplii have low N:P ratio, selecting for P rich-food and excreting at high N:P; while older, slow growing copepodites are characterized by higher N:P, selecting for N-rich food and excreting at low N:P. We developed a simple model for incorporating these age-specific traits within the European Regional Seas Ecosystem Model framework to test the importance of these traits in the marine ecosystem. Our results suggest that copepod’s community growth is limited by different factors in different life stages: nauplii population is limited by prey’s food quality; copepodites population is limited by food quality as well as aging-related reduction in assimilation rate. We also show that age-specific traits of zooplankton have impacts on nutrient cycling especially on the elemental stoichiometry of large particulate organic matter.

Climate induced human demographic and cultural change in northern Europe during the mid-Holocene

The transition from hunter-gatherer-fisher groups to agrarian societies is arguably the most significant change in human prehistory. In the European plain there is evidence for fully developed agrarian societies by 7,500 cal. yr BP, yet a well-established agrarian society does not appear in the north until 6,000 cal. yr BP for unknown reasons. Here we show a sudden increase in summer temperature at 6,000 cal. yr BP in northern Europe using a well-dated, high resolution record of sea surface temperature (SST) from the Baltic Sea. This temperature rise resulted in hypoxic conditions across the entire Baltic sea as revealed by multiple sedimentary records and supported by marine ecosystem modeling. Comparison with summed probability distributions of radiocarbon dates from archaeological sites indicate that this temperature rise coincided with both the introduction of farming, and a dramatic population increase. The evidence supports the hypothesis that the boundary of farming rapidly extended north at 6,000 cal. yr BP because terrestrial conditions in a previously marginal region improved.

Spatiotemporal patterns of sediment transport rate and beach–ocean profile for multi-hazard risk management

Many parameters, interacting differently in time and space, affect a long-shore hydrological and marine ecosystem model, and the water resource management advancement is highly affected by these interactions. Sediment transport in coastal regions is due to interactions between various land forms and different complicated physical processes. What determines coast to storm vulnerability, public/private land ownership legal boundaries, and beach extent that can be used for recreation/habitat is the shape of BOP (beach–ocean profile). This paper addresses an approach that requires a disorder power index (entropy power) for the analyses of spatiotemporal patterns and reports, on the basis of a beach area case study, the suitability of the index for the analyses of the hydrological/marine ecosystem components. The approach uses the 1970–2015 monthly data of six Makran ocean beach sections and investigates such variables as wave high, wind speed, and total beach sediment transport rates (TBSTR) spatiotemporal patterns each of which depends on time and plays an important part in terrestrial hydrological studies. Although these variables often show meaningful spatiotemporal variability, their combined performance is hard to explain. In the framework of this context, using entropy-power index exhibits important signals that help the assessment of water resources and provides a clear understanding of the interactions among hydrological parameters at such large scales as the beach area.