Ensemble Projections of Future Climate Change Impacts on the Eastern Bering Sea Food Web Using a Multispecies Size Spectrum Model

Reum, Jonathan C. P.; Blanchard, Julia L.; Holsman, Kirstin K.; Aydin, Kerim; Hollowed, Anne B.; Hermann, Albert J.; Cheng, Wei; Faig, Amanda; Haynie, Alan C.; Punt, André E.

doi:10.3389/fmars.2020.00124

Cited by 40 publications

(49 citation statements)

References 78 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…That said, the three species in CEATTLE are known to strongly interact, account for a large proportion of total EBS fish biomass, and strongly drive TAC allocation. Future sensitivity analyses, possibly using more speciose food web models 32 , 68 would be useful to quantify this sensitivity.…”

Section: Methodsmentioning

confidence: 99%

“…Consequently, they provide limited utility in evaluating the performance of status quo EBFM policies under climate change (but see refs. 19 , 32 ). Here we use coupled climate-enhanced multispecies assessment and fishery management models to evaluate if EBFM reduces future risk of fishery declines, alters thermal tipping points for fisheries, and imparts increased stability and sustainability in harvest under climate change.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Ecosystem-based fisheries management forestalls climate-driven collapse

et al. 2020

View full text Add to dashboard Cite

Climate change is impacting fisheries worldwide with uncertain outcomes for food and nutritional security. Using management strategy evaluations for key US fisheries in the eastern Bering Sea we find that Ecosystem Based Fisheries Management (EBFM) measures forestall future declines under climate change over non-EBFM approaches. Yet, benefits are species-specific and decrease markedly after 2050. Under high-baseline carbon emission scenarios (RCP 8.5), end-of-century (2075–2100) pollock and Pacific cod fisheries collapse in >70% and >35% of all simulations, respectively. Our analysis suggests that 2.1–2.3 °C (modeled summer bottom temperature) is a tipping point of rapid decline in gadid biomass and catch. Multiyear stanzas above 2.1 °C become commonplace in projections from ~2030 onward, with higher agreement under RCP 8.5 than simulations with moderate carbon mitigation (i.e., RCP 4.5). We find that EBFM ameliorates climate change impacts on fisheries in the near-term, but long-term EBFM benefits are limited by the magnitude of anticipated change.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ecosystem-based fisheries management forestalls climate-driven collapse

et al. 2020

View full text Add to dashboard Cite

show abstract

“…A set of distinct, plausible models may permit multimodel inference and be treated as an ensemble. Model ensembles are used for analysis and operational forecasting in many fields including weather (Tracton and Kalnay, 1993;Zhou and Du, 2010) and long-term climate prediction (Tebaldi and Knutti, 2007;Semenov and Stratonovitch, 2010), and ecological applications of multispecies model ensembles (MMEs) include projection of impacts due to climate change (Gardmark et al, 2013;Cheung et al, 2016;Reum et al, 2020), fishing (Spence et al, 2018), and species eradications and invasions (Baker et al, 2017). Methods for combining quantitative ensemble projections are diverse: from unweighted methods (e.g., "democracy of models") to more complex approaches that weight models based on various criteria including level of data support, e.g., Bayesian posterior model probabilities (Burnham and Anderson, 2002;King et al, 2009;Ianelli et al, 2016;Spence et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…Doing so may foster an environment favorable to knowledge exchange and the cross-pollination of ideas. Moreover, qualitative syntheses, rigorous comparisons of model behavior, and evaluation of the role key assumptions have on predictions can yield deeper insight into a system and guide future data collection and modeling efforts (Gardmark et al, 2013;Cheung et al, 2016;Hollowed et al, 2020;Reum et al, 2020). These benefits are valuable in their own right and can be attainable even when quantitative, statistical treatment of ensemble outputs remains out of reach.…”

Section: Introductionmentioning

confidence: 99%

It’s Not the Destination, It’s the Journey: Multispecies Model Ensembles for Ecosystem Approaches to Fisheries Management

et al. 2021

Self Cite

View full text Add to dashboard Cite

As ecosystem-based fisheries management becomes more ingrained into the way fisheries agencies do business, a need for ecosystem and multispecies models arises. Yet ecosystems are complex, and model uncertainty can be large. Model ensembles have historically been used in other disciplines to address model uncertainty. To understand the benefits and limitations of multispecies model ensembles (MMEs), cases where they have been used in the United States to address fisheries management issues are reviewed. The cases include: (1) development of ecological reference points for Atlantic Menhaden, (2) the creation of time series to relate harmful algal blooms to grouper mortality in the Gulf of Mexico, and (3) fostering understanding of the role of forage fish in the California Current. Each case study briefly reviews the management issue, the models used and model synthesis approach taken, and the outcomes and lessons learned from the application of MMEs. Major conclusions drawn from these studies highlight how the act of developing an ensemble model suite can improve the credibility of multispecies models, how qualitative synthesis of projections can advance system understanding and build confidence in the absence of quantitative treatments, and how involving a diverse set of stakeholders early is useful for ensuring the utility of the models and ensemble. Procedures for review and uptake of information from single-species stock assessment models are well established, but the absence of well-defined procedures for MMEs in many fishery management decision-making bodies poses a major obstacle. The benefits and issues identified here should help accelerate the design, implementation, and utility of MMEs in applied fisheries contexts.

show abstract

“…Thus far FISH-MIP simulations have made simple assumptions about future levels of fishing activity (i.e., fished or unfished) (Lotze et al, 2018), likely because of the difficulty in specifying harvesting regimes for numerous stocks at the global scale. By focusing on a target stock (or subset of stocks), however, it should be possible to predict the effects of more detailed management scenarios alongside the effects of climate (e.g., Reum et al, 2020).…”

Section: Introductionmentioning

confidence: 99%