Abstract
The marine ecosystem off British Columbia (BC), Canada, has experienced various changes in the last two decades, including reduced lipid-rich zooplankton biomass, increased marine mammals, and deteriorated commercial fisheries, particularly those targeting pelagic species such as Pacific Herring (Clupea pallasii). Understanding how stressors interactively and cumulatively affect commercially important fish species is key to moving toward ecosystem-based fisheries management. Because it is challenging to assess the cumulative effects of multiple stressors by using empirical data alone, a dynamic, individual-based spatially explicit ecosystem modeling platform such as Object-oriented Simulator of Marine Ecosystems (OSMOSE) represents a valuable tool to simulate ecological processes and comprehensively evaluate how stressors cumulatively impact modeled species. In this study, we employed OSMOSE to investigate the cumulative effects of fishing, plankton biomass change, and marine mammal consumption on the dynamics of some fish species and the BC marine ecosystem as a whole. We specifically simulated ecosystem dynamics during the last 20 years under two sets of scenarios: (1) unfavorable conditions from the perspective of commercial fish species (i.e., doubling fishing mortality rates, halving plankton biomass, and doubling marine mammal biomass, acting individually or collectively); and (2) favorable conditions with the three factors having opposite changes (i.e., halving fishing mortality rates, doubling plankton biomass, and halving marine mammal biomass, acting individually or collectively). Our results indicate that, under unfavorable conditions, the degree to which species biomass was reduced varied among species, and that negative synergistic and negative dampened effects were dominant under historical and doubled fishing mortality rates, respectively. Under favorable conditions, species biomasses did not increase as much as expected due to the existence of complex predator-prey interactions among fish species, and positive synergistic and positive dampened effects were prevailing under historical and halved fishing mortality rates, respectively. The ecosystem total biomass and the biomass to fisheries yield ratio were found to be good ecological indicators to represent ecosystem changes and track the impacts from the multiple drivers of change. Our research provides insights on how fisheries management should adapt to prepare for potential future impacts of climate change.
Highlights
IntroductionMarine ecosystems have been increasingly impacted by both climate- and human-induced drivers that have caused drastic changes in the ecosystems at multiple trophic levels and spatial scales, potentially resulting in species redistributions, altered biodiversity, ecosystem resilience and integrity, and affecting the reference points that are critical for effective resource management (e.g., Stenseth et al, 2002; Fulton, 2011; GarcíaReyes et al, 2013; Quetglas et al, 2013; Feld et al, 2016; Samhouri et al, 2017; Bonebrake et al, 2018; Le Bris et al, 2018; OrtegaCisneros et al, 2018; Ramírez et al, 2018; Guo et al, 2019)
During the first 10 years, the scenario BaseF_HalfPl_BaseMam resulted in larger biomass reductions than the scenario BaseF_BasePl_DoubMam for Pacific Herring, but not for Pacific Cod, Lingcod, and Walleye Pollock (Figure 3A), suggesting that Pacific Herring were more sensitive to plankton biomass halving, while Pacific Cod, Lingcod, and Walleye Pollock were more vulnerable to mammal biomass doubling
Using the individual-based ecosystem simulation model OSMOSE-BC, we were able to investigate how fish species biomass and ecological indicators would change relative to the historical scenario when the BC ecosystem was hypothetically subjected to changes in three drivers: fishing mortality rates, plankton biomass, and marine mammal biomass
Summary
Marine ecosystems have been increasingly impacted by both climate- and human-induced drivers that have caused drastic changes in the ecosystems at multiple trophic levels and spatial scales, potentially resulting in species redistributions, altered biodiversity, ecosystem resilience and integrity, and affecting the reference points that are critical for effective resource management (e.g., Stenseth et al, 2002; Fulton, 2011; GarcíaReyes et al, 2013; Quetglas et al, 2013; Feld et al, 2016; Samhouri et al, 2017; Bonebrake et al, 2018; Le Bris et al, 2018; OrtegaCisneros et al, 2018; Ramírez et al, 2018; Guo et al, 2019). Multiple drivers of change may interact and generate synergistic, dampened or antagonistic combined effects with respect to the sum of their individual effects (Crain et al, 2008; Griffith et al, 2011, 2012, 2019; TraversTrolet et al, 2014; Piggott et al, 2015; Fu et al, 2018) Addressing these interacting drivers of change jointly and understanding how they affect different ecosystem components and ecosystem functioning are important to natural resource managers (Planque et al, 2010; Hidalgo et al, 2011; Giakoumi et al, 2015; Halpern et al, 2015; Feld et al, 2016). B φ (eggs g−l) Amat (year) Amax (year) Arec (year) M (year−1) Euphausiids −0.20
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