Biogeochemical marine ecosystem models I: IGBEM—a model of marine bay ecosystems

Forecasting ocean acidification impacts on kelp forest ecosystems

Ocean acidification is one the biggest threats to marine ecosystems worldwide, but its ecosystem wide responses are still poorly understood. This study integrates field and experimental data into a mass balance food web model of a temperate coastal ecosystem to determine the impacts of specific OA forcing mechanisms as well as how they interact with one another. Specifically, we forced a food web model of a kelp forest ecosystem near its southern distribution limit in the California large marine ecosystem to a 0.5 pH drop over the course of 50 years. This study utilizes a modeling approach to determine the impacts of specific OA forcing mechanisms as well as how they interact. Isolating OA impacts on growth (Production), mortality (Other Mortality), and predation interactions (Vulnerability) or combining all three mechanisms together leads to a variety of ecosystem responses, with some taxa increasing in abundance and other decreasing. Results suggest that carbonate mineralizing groups such as coralline algae, abalone, snails, and lobsters display the largest decreases in biomass while macroalgae, urchins, and some larger fish species display the largest increases. Low trophic level groups such as giant kelp and brown algae increase in biomass by 16% and 71%, respectively. Due to the diverse way in which OA stress manifests at both individual and population levels, ecosystem-level effects can vary and display nonlinear patterns. Combined OA forcing leads to initial increases in ecosystem and commercial biomasses followed by a decrease in commercial biomass below initial values over time, while ecosystem biomass remains high. Both biodiversity and average trophic level decrease over time. These projections indicate that the kelp forest community would maintain high productivity with a 0.5 drop in pH, but with a substantially different community structure characterized by lower biodiversity and relatively greater dominance by lower trophic level organisms.

Investigating cumulative effects across ecological scales

Species, habitats, and ecosystems are increasingly exposed to multiple anthropogenic stressors, fueling a rapidly expanding research program to understand the cumulative impacts of these environmental modifications. Since the 1970s, a growing set of methods has been developed through two parallel, sometimes connected, streams of research within the applied and academic realms to assess cumulative effects. Past reviews of cumulative effects assessment (CEA) methods focused on approaches used by practitioners. Academic research has developed several distinct and novel approaches to conducting CEA. Understanding the suite of methods that exist will help practitioners and academics better address various ecological foci (physiological responses, population impacts, ecosystem impacts) and ecological complexities (synergistic effects, impacts across space and time). We reviewed 6 categories of methods (experimental, meta-analysis, single-species modeling, mapping, qualitative modeling, and multispecies modeling) and examined the ability of those methods to address different levels of complexity. We focused on research gaps and emerging priorities. We found that no single method assessed impacts across the 4 ecological foci and 6 ecological complexities considered. We propose that methods can be used in combination to improve understanding such that multimodel inference can provide a suite of comparable outputs, mapping methods can help prioritize localized models or experimental gaps, and future experiments can be paired from the outset with models they will inform.

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.

An Introduction to Modelling Abundance and Life History Parameters in Shark Populations

Elasmobranchs play critically important ecological roles throughout the world's oceans, yet in many cases, their slow life histories and interactions with fisheries makes them particularly susceptible to exploitation. Management for these species requires robust scientific input, and mathematical models are the backbone of science-based management. In this chapter, we provide an introductory overview of the use of mathematical models to estimate shark abundance. First, we discuss life history models that are used to understand the basic biology of elasmobranchs. Second, we cover population dynamics models, which are used to make inferences regarding population trend, size, and risk of extinction. Finally, we provide examples of applied models used to assess the status of elasmobranchs in the Northeast Pacific Ocean to guide management for these species. This chapter is not a comprehensive review of quantitative methods, but rather introduces various mathematical tools in fisheries management, with a focus on shark management in the Northeast Pacific Ocean.

Emerging asymmetric interactions between forage and predator fisheries impose management trade-offs

A size and trait-based marine community model was used to investigate interactions, with potential implications for yields, when a fishery targeting forage fish species (whose main adult diet is zooplankton) co-occurs with a fishery targeting larger-sized predator species. Predicted effects on the size structure of the fish community, growth and recruitment of fishes, and yield from the fisheries were used to identify management trade-offs among the different fisheries. Results showed that moderate fishing on forage fishes imposed only small effects on predator fisheries, whereas predator fisheries could enhance yield from forage fisheries under some circumstances.

Indirect effects of conservation policies on the coupled human-natural ecosystem of the upper Gulf of California

High bycatch of non-target species and species of conservation concern often drives the implementation of fisheries policies. However, species- or fishery-specific policies may lead to indirect consequences, positive or negative, for other species or fisheries. We use an Atlantis ecosystem model of the Northern Gulf of California to evaluate the effects of fisheries policies directed at reducing bycatch of vaquita (Phocoena sinus) on other species of conservation concern, priority target species, and metrics of ecosystem function and structure. Vaquita, a Critically Endangered porpoise endemic to the Upper Gulf of California, are frequently entangled by finfish gillnets and shrimp driftnets. We tested five fishery management scenarios, projected over 30 years (2008 to 2038), directed at vaquita conservation. The scenarios consider progressively larger spatial restrictions for finfish gillnets and shrimp driftnets. The most restrictive scenario resulted in the highest biomass of species of conservation concern; the scenario without any conservation measures in place resulted in the lowest. Vaquita experienced the largest population increase of any functional group; their biomass increased 2.7 times relative to initial (2008) levels under the most restrictive spatial closure scenario. Bycatch of sea lions, sea turtles, and totoaba decreased > 80% in shrimp driftnets and at least 20% in finfish gillnet fleets under spatial management. We found indirect effects on species and ecosystem function and structure as a result of vaquita management actions. Biomass and catch of forage fish declined, which could affect lower-trophic level fisheries, while other species such as skates, rays, and sharks increased in both biomass and catch. When comparing across performance metrics, we found that scenarios that increased ecosystem function and structure resulted in lower economic performance indicators, underscoring the need for management actions that consider ecological and economic tradeoffs as part of the integrated management of the Upper Gulf of California.

A model for describing the eutrophication in a heavily regulated coastal lagoon. Application to the Albufera of Valencia (Spain)

A simplified two-dimensional eutrophication model was developed to simulate temporal and spatial variations of chlorophyll-a in heavily regulated coastal lagoons. This model considers the hydrodynamics of the whole study area, the regulated connexion of the lagoon with the sea, the variability of the input and output nutrient loads, the flux from the sediments to the water column, the phytoplankton growth and mortality kinetics, and the zooplankton grazing. The model was calibrated and validated by applying it to the Albufera of Valencia, a hypertrophic system whose connection to the sea is strongly regulated by a system of sluice-gates. The calibration and validation results presented a significant agreement between the model and the data obtained in several surveys. The accuracy was evaluated using a quantitative analysis, in which the average uncertainty of the model prediction was less than 6%. The results confirmed an expected phytoplankton bloom in April and October, achieving mean maximum values around 250 μg l(-1) of chlorophyll-a. A mass balance revealed that the eutrophication process is magnified by the input loads of nutrients, mainly from the sediments, as well as by the limited connection of the lagoon with the sea. This study has shown that the developed model is an efficient tool to manage the eutrophication problem in heavily regulated coastal lagoons.

Biodiversity and ecosystem function in the Gulf of Maine: pattern and role of zooplankton and pelagic nekton

This paper forms part of a broader overview of biodiversity of marine life in the Gulf of Maine area (GoMA), facilitated by the GoMA Census of Marine Life program. It synthesizes current data on species diversity of zooplankton and pelagic nekton, including compilation of observed species and descriptions of seasonal, regional and cross-shelf diversity patterns. Zooplankton diversity in the GoMA is characterized by spatial differences in community composition among the neritic environment, the coastal shelf, and deep offshore waters. Copepod diversity increased with depth on the Scotian Shelf. On the coastal shelf of the western Gulf of Maine, the number of higher-level taxonomic groups declined with distance from shore, reflecting more nearshore meroplankton. Copepod diversity increased in late summer, and interdecadal diversity shifts were observed, including a period of higher diversity in the 1990s. Changes in species diversity were greatest on interannual scales, intermediate on seasonal scales, and smallest across regions, in contrast to abundance patterns, suggesting that zooplankton diversity may be a more sensitive indicator of ecosystem response to inter annual climate variation than zoo plankton abundance. Local factors such as bathymetry, proximity of the coast, and advection probably drive zooplankton and pelagic nekton diversity patterns in the GoMA, while ocean-basin scale diversity patterns probably contribute to the increase in diversity at the Scotian Shelf break, a zone of mixing between the cold-temperate community of the shelf and the warm-water community offshore. Pressing research needs include establishment of a comprehensive system for observing change in zooplankton and pelagic nekton diversity, enhanced observations of "underknown" but important functional components of the ecosystem, population and metapopulation studies, and development of analytical modeling tools to enhance understanding of diversity patterns and drivers. Ultimately, sustained observations and modeling analysis of biodiversity must be effectively communicated to managers and incorporated into ecosystem approaches for management of GoMA living marine resources.