Employing ecosystem models and geographic information systems (GIS) to investigate the response of changing marsh edge on historical biomass of estuarine nekton in Barataria Bay, Louisiana, USA

The combined effects of predation, fishing, and ocean productivity on salmon species targeted by marine mammals in the northeast Pacific

Along the northeast Pacific coast, the salmon-eating southern resident killer whale population (SRKW, Orcinus orca) have been at very low levels since the 1970s. Previous research have suggested that reduction in food availability, especially of Chinook salmon (Oncorhynchus tshawytscha), could be the main limiting factor for the SRKW population. Using the ecosystem modelling platform Ecopath with Ecosim (EwE), this study evaluated if the decline of the Pacific salmon populations between 1979 and 2020 may have been impacted by a combination of factors, including marine mammal predation, fishing activities, and climatic patterns. We found that the total mortality of most Chinook salmon populations has been relatively stable for all mature returning fish despite strong reduction in fishing mortality since the 1990s. This mortality pattern was mainly driven by pinnipeds, with increases in predation between 1979 and 2020 mortality ranging by factors of 1.8 to 8.5 across the different Chinook salmon population groups. The predation mortality on fall-run Chinook salmon smolts originating from the Salish Sea increased 4.6 times from 1979 to 2020, whereas the predation mortality on coho salmon (Oncorhynchus kisutch) smolts increased by a factor of 7.3. The model also revealed that the north Pacific gyre oscillation (NPGO) was the most important large-scale climatic index affecting the stock productivity of Chinook salmon populations from California to northern British Columbia. Overall, the model provided evidence that multiple factors may have affected Chinook salmon populations between 1979 and 2020, and suggested that predation mortality by marine mammals could be an important driver of salmon population declines during that time.

Tropical estuarine ecosystem change under the interacting influences of future climate and ecosystem restoration

One of the largest restoration programs in the world, the Comprehensive Everglades Restoration Plan (CERP) aims to restore freshwater inputs to Everglades wetlands and the Florida Bay estuary. This study predicted how the Florida Bay ecosystem may respond to hydrological restoration from CERP within the context of contemporary projected impacts of sea-level rise (SLR) and increased future temperatures. A spatial-temporal dynamic model (Ecospace) was used to develop a spatiotemporal food web model incorporating environmental drivers of salinity, salinity variation, temperature, depth, distance to mangrove, and seagrass abundance and was used to predict responses of biomass, fisheries catch, and ecosystem resilience between current and future conditions. Changes in biomass between the current and future scenario suggest a suite of winners and losers, with many estuarine species increasing in both total biomass and spatial distribution. Notable biomass increases were predicted for important forage species, including bay anchovy (+32%), hardhead halfbeak (+19%), and pinfish (+31%), while decreases were predicted in mullet (-88%), clupeids (-55%), hardhead silverside (-15%), mojarras (-117%), and Portunid crabs (-16%). Increases in sportfish biomass included the angler-preferred spotted seatrout (+9%), red drum (+10%), and gray snapper (+8%), while decreases included sheepshead (-40%), Atlantic tarpon (-73%), and common snook (-507%). Ecosystem resilience and fisheries catch of angler-preferred species were predicted to improve in the future scenario in total, although a localized decline in resilience predicted for the Central Region may warrant further attention. Our results suggest the Florida Bay ecosystem is likely to achieve restoration benefits in spite of, and in some cases facilitated by, the projected future impacts from climate change due to the system's shallow depth and detrital dominance. The incorporation of climate impacts into long-term restoration planning using ecosystem modeling in similar systems facing unknown futures of SLR, warming seas, and shifting species distributions is recommended.

Exploring multiple stressor effects with Ecopath, Ecosim, and Ecospace: Research designs, modeling techniques, and future directions

Understanding the cumulative effects of multiple stressors is a research priority in environmental science. Ecological models are a key component of tackling this challenge because they can simulate interactions between the components of an ecosystem. Here, we ask, how has the popular modeling platform Ecopath with Ecosim (EwE) been used to model human impacts related to climate change, land and sea use, pollution, and invasive species? We conducted a literature review encompassing 166 studies covering stressors other than fishing mostly in aquatic ecosystems. The most modeled stressors were physical climate change (60 studies), species introductions (22), habitat loss (21), and eutrophication (20), using a range of modeling techniques. Despite this comprehensive coverage, we identified four gaps that must be filled to harness the potential of EwE for studying multiple stressor effects. First, only 12% of studies investigated three or more stressors, with most studies focusing on single stressors. Furthermore, many studies modeled only one of many pathways through which each stressor is known to affect ecosystems. Second, various methods have been applied to define environmental response functions representing the effects of single stressors on species groups. These functions can have a large effect on the simulated ecological changes, but best practices for deriving them are yet to emerge. Third, human dimensions of environmental change - except for fisheries - were rarely considered. Fourth, only 3% of studies used statistical research designs that allow attribution of simulated ecosystem changes to stressors' direct effects and interactions, such as factorial (computational) experiments. None made full use of the statistical possibilities that arise when simulations can be repeated many times with controlled changes to the inputs. We argue that all four gaps are feasibly filled by integrating ecological modeling with advances in other subfields of environmental science and in computational statistics.