Diet composition uncertainty determines impacts on fisheries following an oil spill

Morzaria‐Luna, Hem Nalini; Ainsworth, Cameron H.; Tarnecki, Joseph H.; Grüss, Arnaud

doi:10.1016/j.ecoser.2018.05.002

Cited by 22 publications

(11 citation statements)

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“…However, sensitivity analysis in Atlantis is hampered by the model’s long run time and large number of parameters [ 16 , 17 ]. Morzaria et al [ 54 ] explore the error around the [K1000 β 363] simulation tested here using a new statistical methodology and parallel computing.…”

Section: Discussionmentioning

confidence: 99%

Impacts of the Deepwater Horizon oil spill evaluated using an end-to-end ecosystem model

et al. 2018

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We use a spatially explicit biogeochemical end-to-end ecosystem model, Atlantis, to simulate impacts from the Deepwater Horizon oil spill and subsequent recovery of fish guilds. Dose-response relationships with expected oil concentrations were utilized to estimate the impact on fish growth and mortality rates. We also examine the effects of fisheries closures and impacts on recruitment. We validate predictions of the model by comparing population trends and age structure before and after the oil spill with fisheries independent data. The model suggests that recruitment effects and fishery closures had little influence on biomass dynamics. However, at the assumed level of oil concentrations and toxicity, impacts on fish mortality and growth rates were large and commensurate with observations. Sensitivity analysis suggests the biomass of large reef fish decreased by 25% to 50% in areas most affected by the spill, and biomass of large demersal fish decreased even more, by 40% to 70%. Impacts on reef and demersal forage caused starvation mortality in predators and increased reliance on pelagic forage. Impacts on the food web translated effects of the spill far away from the oiled area. Effects on age structure suggest possible delayed impacts on fishery yields. Recovery of high-turnover populations generally is predicted to occur within 10 years, but some slower-growing populations may take 30+ years to fully recover.

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Section: Discussionmentioning

confidence: 99%

Impacts of the Deepwater Horizon oil spill evaluated using an end-to-end ecosystem model

et al. 2018

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“…how similar the predicted and observed datapoints should be for us to accept the model predictions? Physiologically structured models, especially more complex ones applied at community level, typically lack broadly accepted statistical uncertainty evaluation, and this is an important limitation to acknowledge when such models are applied to inform management and conservation decisions (Spence et al 2015, Morzaria-Luna et al 2018. Recent developments in computing power and statistical methods, are however increasing the feasibility of uncertainty evaluation of complex models, so we can expect and, in fact, demand, improvement in this field over the next decade.…”

Section: Modelling Challengesmentioning

confidence: 99%

A cross‐scale framework to support a mechanistic understanding and modelling of marine climate‐driven species redistribution, from individuals to communities

et al. 2020

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Climate‐driven species redistribution is pervasive and accelerating, yet the complex mechanisms at play remain poorly understood. The implications of large‐scale species redistribution for natural systems and human societies have resulted in a large number of studies exploring the effects on individual species and ecological communities worldwide. Whilst many studies have investigated discrete components of species redistribution, the integration required for a more complete mechanistic understanding is lacking. In this paper, we provide a framework for synthesising approaches to more robustly understand and predict marine species redistributions. We conceptualise the stages and processes involved in climate‐driven species redistribution at increasing levels of biological organisation, and synthesize the laboratory, field and modelling approaches used to study redistribution related processes at individual, population and community levels. We then summarise links between scales of biological organisation and methodological approaches in a hierarchical framework that represents an integrated mechanistic assessment of climate‐driven species redistributions. In a rapidly expanding field of research, this framework provides direction for: 1) guiding future research, 2) highlighting key knowledge gaps, 3) fostering data exchange and collaboration between disciplines and 4) improving shared capacity to predict and therefore, inform the proactive management of climate impacts on natural systems.

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“…Ainsworth method requires a minimum of 30 data points for each individual year (Morzaria-Luna et al, 2018). Therefore, in the datalimited case-study, we estimated diet proportions, as well as associated standard errors (except for the simple average method), for the entire period 2011-2015.…”

Section: Comparisons With Other Approaches To Estimating Diet Proportionsmentioning

confidence: 99%

“…The Ainsworth method has been employed and further developed in Masi et al (2014), Sagarese et al (2016), Tarnecki et al (2016), Morzaria-Luna, Ainsworth, Tarnecki, and Grüss (2018) and Reum et al (2019).…”

Section: Introductionmentioning

confidence: 99%

“…FishBase; Froese & Pauly, 2019); (b) bootstrapping the large diet composition dataset to produce likelihood profiles; (c) fitting the bootstrapped data to a Dirichlet distribution, which is a multivariate generalization of the Beta distribution (Douma & Weedon, 2019); and (d) employing the maximum likelihood estimates (MLEs) from the marginal Beta distributions of the Dirichlet model to define mean diet proportions for each predator of interest, and using the standard errors of these distributions to generate confidence intervals. The Ainsworth method has been employed and further developed in Masi et al (2014), Sagarese et al (2016), Tarnecki et al (2016), Morzaria‐Luna, Ainsworth, Tarnecki, and Grüss (2018) and Reum et al (2019).…”

Section: Introductionmentioning

confidence: 99%

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Spatio‐temporal analyses of marine predator diets from data‐rich and data‐limited systems

et al. 2020

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Accounting for variation in prey mortality and predator metabolic potential arising from spatial variation in consumption is an important task in ecology and resource management. However, there is no statistical method for processing stomach content data that accounts for fine-scale spatio-temporal structure while expanding individual stomach samples to population-level estimates of predation. Therefore, we developed an approach that fits a spatio-temporal model to both prey-biomass-perpredator-biomass data (i.e. the ratio of prey biomass in stomachs to predator weight) and predator biomass survey data, to predict "predator-expanded-stomach-contents" (PESCs). PESC estimates can be used to visualize either the annual landscape of PESCs (spatio-temporal variation), or can be aggregated across space to calculate annual variation in diet proportions (variation among prey items and among years).We demonstrated our approach in two contrasting scenarios: a data-rich situation involving eastern Bering Sea (EBS) large-size walleye pollock (Gadus chalcogrammus, Gadidae) for 1992-2015; and a data-limited situation involving West Florida Shelf red grouper (Epinephelus morio, Epinephelidae) for 2011-2015. Large walleye pollock PESC was predicted to be higher in very warm years on the Middle Shelf of the EBS, where food is abundant. Red grouper PESC was variable in north-western Florida waters, presumably due to spatio-temporal variation in harmful algal bloom severity.Our approach can be employed to parameterize or validate diverse ecosystem models, and can serve to address many fundamental ecological questions, such as providing an improved understanding of how climate-driven changes in spatial overlap between predator and prey distributions might influence predation pressure. K E Y W O R D S diet proportions, Poisson-link delta model, predation pressure, predator-expanded-stomachcontents, spatio-temporal model, stomach content data | 719 GRÜSS et al.1. INTRODUCTION 719 2. METHODS 721 2.1 Model overview 721 2.2 Model details 721 2.2.1 Poisson-link delta modelling framework 721 2.2.2 Parameter estimation 722 2.2.3 Estimation of predator-expanded-stomach-contents 722 2.2.4 Estimation of diet proportions and input sample sizes 723 2.3 Data-rich case-study 723 2.4 Data-limited case-study 725 2.5 Comparisons with other approaches to estimating diet proportions 726 3 RESULTS 727 3.1 Data-rich case-study 727 3.2 Data-limited case-study 729 3.3 Comparisons with other approaches to estimating diet proportions 730 4 DISCUSSION 731 ACKNOWLEDGMENTS 735

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Diet composition uncertainty determines impacts on fisheries following an oil spill

Cited by 22 publications

References 59 publications

Impacts of the Deepwater Horizon oil spill evaluated using an end-to-end ecosystem model

Impacts of the Deepwater Horizon oil spill evaluated using an end-to-end ecosystem model

A cross‐scale framework to support a mechanistic understanding and modelling of marine climate‐driven species redistribution, from individuals to communities

Spatio‐temporal analyses of marine predator diets from data‐rich and data‐limited systems

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