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Evaluation and management implications of uncertainty in a multispecies size-structured model of population and community responses to fishing.

Thorpe RB, Le Quesne WJ, Luxford F, Collie JS, Jennings S - Methods Ecol Evol (2014)

Bottom Line: This unfiltered ensemble was reduced to 188 plausible models, the filtered ensemble (FE), by screening outputs against fish abundance data and ecological principles such as requiring species' persistence.Effects of parameter uncertainty on estimates of single-species management reference points for fishing mortality (F MSY, fishing mortality rate providing MSY, the maximum sustainable yield) and biomass (B MSY, biomass at MSY) were evaluated by calculating probability distributions of estimated reference points with the FE.There was a 50% probability that multispecies F MSY could be estimated to within ±25% of its actual value, and a 50% probability that B MSY could be estimated to within ±40% of its actual value.Signal-to-noise ratio was assessed for four community indicators when mortality rates were reduced from current rates to F MSY.Further, the power of an ongoing international monitoring survey to detect predicted responses of size spectrum slope was higher than for other size-based metrics.Synthesis and applications: Application of the ensemble model approach allows explicit representation of parameter uncertainty and supports advice and management by (i) providing uncertainty intervals for management reference points, (ii) estimating working values of reference points that achieve a defined reduction in risk of not breaching the true reference point, (iii) estimating the responsiveness of population, community, food web and biodiversity indicators to changes in F, (iv) assessing the performance of indicators and monitoring programmes and (v) identifying priorities for data collection and changes to model structure to reduce uncertainty.

View Article: PubMed Central - PubMed

Affiliation: Centre for Environment, Fisheries and Aquaculture Science (CEFAS), Lowestoft Laboratory Lowestoft, NR33 0HT, UK.

ABSTRACT

Implementation of an ecosystem approach to fisheries requires advice on trade-offs among fished species and between fisheries yields and biodiversity or food web properties. However, the lack of explicit representation, analysis and consideration of uncertainty in most multispecies models has limited their application in analyses that could support management advice.We assessed the consequences of parameter uncertainty by developing 78 125 multispecies size-structured fish community models, with all combinations of parameters drawn from ranges that spanned parameter values estimated from data and literature. This unfiltered ensemble was reduced to 188 plausible models, the filtered ensemble (FE), by screening outputs against fish abundance data and ecological principles such as requiring species' persistence.Effects of parameter uncertainty on estimates of single-species management reference points for fishing mortality (F MSY, fishing mortality rate providing MSY, the maximum sustainable yield) and biomass (B MSY, biomass at MSY) were evaluated by calculating probability distributions of estimated reference points with the FE. There was a 50% probability that multispecies F MSY could be estimated to within ±25% of its actual value, and a 50% probability that B MSY could be estimated to within ±40% of its actual value.Signal-to-noise ratio was assessed for four community indicators when mortality rates were reduced from current rates to F MSY. The slope of the community size spectrum showed the greatest signal-to-noise ratio, indicating that it would be the most responsive indicator to the change in fishing mortality F. Further, the power of an ongoing international monitoring survey to detect predicted responses of size spectrum slope was higher than for other size-based metrics.Synthesis and applications: Application of the ensemble model approach allows explicit representation of parameter uncertainty and supports advice and management by (i) providing uncertainty intervals for management reference points, (ii) estimating working values of reference points that achieve a defined reduction in risk of not breaching the true reference point, (iii) estimating the responsiveness of population, community, food web and biodiversity indicators to changes in F, (iv) assessing the performance of indicators and monitoring programmes and (v) identifying priorities for data collection and changes to model structure to reduce uncertainty.

No MeSH data available.


Frequency distribution of estimated biomass of modelled species at FMSY. Grey histograms denote the frequency distribution of biomass estimates from models in the unfiltered ensemble (UE), black histograms the biomass estimates from models in the filtered ensemble (FE). The vertical shaded band represents the biomass range reported by ICES for assessed species for years 1990–2010.
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fig01: Frequency distribution of estimated biomass of modelled species at FMSY. Grey histograms denote the frequency distribution of biomass estimates from models in the unfiltered ensemble (UE), black histograms the biomass estimates from models in the filtered ensemble (FE). The vertical shaded band represents the biomass range reported by ICES for assessed species for years 1990–2010.

Mentions: Individual species' biomass predictions from the models in the unfiltered ensemble (UE), when fishing according to the FMSY scenario, tended to span 2 or more orders of magnitude (Fig. 1), indicating that initial spread of parameter choices provided little constraint on predictions. Uncertainty in predicted biomass is greatly reduced for the FE where uncertainty is reduced to between one-half and one order of magnitude (Fig. 1). Only 188 of 78 125 possible model variants passed the screening criteria. The default model did not pass the screening criteria. Changing the screening criteria for biomass at FHIST to allow a tolerance factor of 1·5× to 3× for the relationship between ICES single-species biomass estimates and model outputs increased the size of the FE (Fig. S5), but had a small effect on outputs and uncertainty and did not change qualitative behaviour and relative performance of species and community metrics (Figs S6 and S7).


Evaluation and management implications of uncertainty in a multispecies size-structured model of population and community responses to fishing.

Thorpe RB, Le Quesne WJ, Luxford F, Collie JS, Jennings S - Methods Ecol Evol (2014)

Frequency distribution of estimated biomass of modelled species at FMSY. Grey histograms denote the frequency distribution of biomass estimates from models in the unfiltered ensemble (UE), black histograms the biomass estimates from models in the filtered ensemble (FE). The vertical shaded band represents the biomass range reported by ICES for assessed species for years 1990–2010.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4390044&req=5

fig01: Frequency distribution of estimated biomass of modelled species at FMSY. Grey histograms denote the frequency distribution of biomass estimates from models in the unfiltered ensemble (UE), black histograms the biomass estimates from models in the filtered ensemble (FE). The vertical shaded band represents the biomass range reported by ICES for assessed species for years 1990–2010.
Mentions: Individual species' biomass predictions from the models in the unfiltered ensemble (UE), when fishing according to the FMSY scenario, tended to span 2 or more orders of magnitude (Fig. 1), indicating that initial spread of parameter choices provided little constraint on predictions. Uncertainty in predicted biomass is greatly reduced for the FE where uncertainty is reduced to between one-half and one order of magnitude (Fig. 1). Only 188 of 78 125 possible model variants passed the screening criteria. The default model did not pass the screening criteria. Changing the screening criteria for biomass at FHIST to allow a tolerance factor of 1·5× to 3× for the relationship between ICES single-species biomass estimates and model outputs increased the size of the FE (Fig. S5), but had a small effect on outputs and uncertainty and did not change qualitative behaviour and relative performance of species and community metrics (Figs S6 and S7).

Bottom Line: This unfiltered ensemble was reduced to 188 plausible models, the filtered ensemble (FE), by screening outputs against fish abundance data and ecological principles such as requiring species' persistence.Effects of parameter uncertainty on estimates of single-species management reference points for fishing mortality (F MSY, fishing mortality rate providing MSY, the maximum sustainable yield) and biomass (B MSY, biomass at MSY) were evaluated by calculating probability distributions of estimated reference points with the FE.There was a 50% probability that multispecies F MSY could be estimated to within ±25% of its actual value, and a 50% probability that B MSY could be estimated to within ±40% of its actual value.Signal-to-noise ratio was assessed for four community indicators when mortality rates were reduced from current rates to F MSY.Further, the power of an ongoing international monitoring survey to detect predicted responses of size spectrum slope was higher than for other size-based metrics.Synthesis and applications: Application of the ensemble model approach allows explicit representation of parameter uncertainty and supports advice and management by (i) providing uncertainty intervals for management reference points, (ii) estimating working values of reference points that achieve a defined reduction in risk of not breaching the true reference point, (iii) estimating the responsiveness of population, community, food web and biodiversity indicators to changes in F, (iv) assessing the performance of indicators and monitoring programmes and (v) identifying priorities for data collection and changes to model structure to reduce uncertainty.

View Article: PubMed Central - PubMed

Affiliation: Centre for Environment, Fisheries and Aquaculture Science (CEFAS), Lowestoft Laboratory Lowestoft, NR33 0HT, UK.

ABSTRACT

Implementation of an ecosystem approach to fisheries requires advice on trade-offs among fished species and between fisheries yields and biodiversity or food web properties. However, the lack of explicit representation, analysis and consideration of uncertainty in most multispecies models has limited their application in analyses that could support management advice.We assessed the consequences of parameter uncertainty by developing 78 125 multispecies size-structured fish community models, with all combinations of parameters drawn from ranges that spanned parameter values estimated from data and literature. This unfiltered ensemble was reduced to 188 plausible models, the filtered ensemble (FE), by screening outputs against fish abundance data and ecological principles such as requiring species' persistence.Effects of parameter uncertainty on estimates of single-species management reference points for fishing mortality (F MSY, fishing mortality rate providing MSY, the maximum sustainable yield) and biomass (B MSY, biomass at MSY) were evaluated by calculating probability distributions of estimated reference points with the FE. There was a 50% probability that multispecies F MSY could be estimated to within ±25% of its actual value, and a 50% probability that B MSY could be estimated to within ±40% of its actual value.Signal-to-noise ratio was assessed for four community indicators when mortality rates were reduced from current rates to F MSY. The slope of the community size spectrum showed the greatest signal-to-noise ratio, indicating that it would be the most responsive indicator to the change in fishing mortality F. Further, the power of an ongoing international monitoring survey to detect predicted responses of size spectrum slope was higher than for other size-based metrics.Synthesis and applications: Application of the ensemble model approach allows explicit representation of parameter uncertainty and supports advice and management by (i) providing uncertainty intervals for management reference points, (ii) estimating working values of reference points that achieve a defined reduction in risk of not breaching the true reference point, (iii) estimating the responsiveness of population, community, food web and biodiversity indicators to changes in F, (iv) assessing the performance of indicators and monitoring programmes and (v) identifying priorities for data collection and changes to model structure to reduce uncertainty.

No MeSH data available.