Dealing with uncertainty in ecosystem models: The paradox of use for living marine resource management

Link, Jason S.; Ihde, Thomas F.; Harvey, Chris J.; Gaichas, Sarah; Field, John C.; Brodziak, Jon K. T.; Townsend, Howard; Peterman, Randall M.

doi:10.1016/j.pocean.2012.03.008

Cited by 127 publications

(95 citation statements)

References 92 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This becomes increasingly relevant in situations where a relatively minor change in a factor's value results in a major change in model output (Link et al, 2012). For such complex ecological models it is therefore vitally important to focus on accurately representing those factors that are most influential for the model outputs (Arhonditsis and Brett, 2004).…”

Section: Introductionmentioning

confidence: 99%

Global sensitivity analysis of an end-to-end marine ecosystem model of the North Sea: Factors affecting the biomass of fish and benthos

Morris

Speirs

Cameron

et al. 2014

Ecological Modelling

View full text Add to dashboard Cite

This version is available at https://strathprints.strath.ac.uk/45100/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output.Global sensitivity analysis of an end-to-end marine ecosystem model of the North Sea: factors affecting the biomass of fish and benthos AbstractComprehensive analysis of parameter and driver sensitivity is key to establishing the credibility of models representing complex systems. This is especially so for models of natural systems where experimental manipulation of the real-world to provide controlled validation data is not possible.End-to-end ecosystem models (nutrients to birds and mammals) of marine ecosystems fall into this category with applications for evaluating the effects of climate change and fishing on nutrient fluxes and the abundances of flora and fauna. Here we present results of both 'one-at-a-time' (OAT) and variance based global sensitivity analyses (GSA) of the fish and fishery aspects of StrathE2E, an end-to-end ecosystem model of the North Sea. The sensitivity of the model was examined with respect to internal biological parameters, and external drivers related to climate and human activity.The OAT Morris method was first used to screen for factors most influential on model outputs. The Sobol GSA method was then used to calculate quantitative sensitivity indices. The results indicated that the fish and shellfish components of the model (demersal and pelagic fish, filter/deposit and scavenge/carnivore feeding benthos) were influenced by different sets of factors. Harvesting rates were directly influential on demersal and pelagic fish biomasses. Suspension/deposit feeding benthos were directly sensitive to changes in temperature, while the temperature acted indirectly on pelagic fish through the connectivity between model components of the food web. Biomass conversion efficiency was the most important factor for scavenge/carnivorous feeding benthos.

show abstract

Section: Introductionmentioning

confidence: 99%

Global sensitivity analysis of an end-to-end marine ecosystem model of the North Sea: Factors affecting the biomass of fish and benthos

Morris

Speirs

Cameron

et al. 2014

Ecological Modelling

View full text Add to dashboard Cite

show abstract

“…It implies a need for resilience objectives that acknowledge the differences between ecosystem components, and the practical constraints on assessing the characteristics of each relevant component. Secondly, the specific objectives of EBM are often uncertain (Link et al 2012). Consequently scientists may need to evaluate candidate management measures despite ambiguously specified objectives.…”

Section: S Hillmentioning

confidence: 99%

From strategic ambiguity to technical reference points in the Antarctic krill fishery: the worst journey in the world?

Hill

2013

Envir. Conserv.

View full text Add to dashboard Cite

SUMMARYThe goals of ecosystem based management (EBM) are strategically ambiguous, meaning that they require interpretation to identify objectives for ecosystem state. Ecosystem states that are useful for achieving such objectives are known as reference points. Soft reference points specify both a state and a probability of the ecosystem being in that state. They are used with simulation models to identify management measures for which the risk of the ecosystem entering an undesirable state is below a specified level. The Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) is responsible for the EBM of Antarctic krill fisheries. CCAMLR used soft reference points for the krill stock in the Scotia Sea and southern Drake Passage to set a regional catch limit. However, this catch limit needs spatial subdivision to protect predators from localized depletion. Modelbased evaluations of different options for subdividing the catch limit used illustrative reference points to assess the depletion risk to multiple predators. This study demonstrates that the apparent risk is sensitive to the choice of reference point and method for aggregating modelled predators. EBM practitioners and stakeholders need to be aware that these factors could therefore bias comparisons of management measures. Nonetheless, qualitative distinctions between different spatial subdivision options are relatively consistent except at high levels of aggregation and extreme reference points. This study also demonstrates a lack of generality in the relationship between current and future ecosystem state. Thus, the EBM goal of maintaining ecosystem resilience implies different reference points for the current state of different ecosystem components. Despite early progress in defining soft reference points for the krill stock, CCAMLR has not yet defined reference points for krill predators. Structured dialogue aimed at identifying collective objectives * Correspondence: Dr Simeon Hill e-mail: sih@bas.ac.uk The online version of this article is published within an Open Access environment subject to the conditions of the Creative Commons Attribution-NonCommercial-ShareAlike licence . The written permission of Cambridge University Press must be obtained for commercial re-use. might be necessary to achieve further progress in CCAMLR and other EBM organizations.

show abstract

“…Finally, there is often good reasons and pressure to include stochasticity in model predictions. Purely deterministic models do not capture the true variability observed in nature, and there has been much effort to incorporate stochasticity and uncertainty into fish population and food web models to match natural variation (e.g., Bjørkvoll et al, 2012;Magnusson et al, 2013;Link et al, 2012). However, it is quite tricky to make a stochastic model that correctly generates realistic variability that is comparable to the observational data (Saltelli et al, 2004).…”

Section: Concept 2: Variability Uncertainty and Stochasticitymentioning

confidence: 99%

Proposed best modeling practices for assessing the effects of ecosystem restoration on fish

Rose

Sable²,

Jiang

et al. 2015

Ecological Modelling

View full text Add to dashboard Cite

Dealing with uncertainty in ecosystem models: The paradox of use for living marine resource management

Cited by 127 publications

References 92 publications

Global sensitivity analysis of an end-to-end marine ecosystem model of the North Sea: Factors affecting the biomass of fish and benthos

Global sensitivity analysis of an end-to-end marine ecosystem model of the North Sea: Factors affecting the biomass of fish and benthos

From strategic ambiguity to technical reference points in the Antarctic krill fishery: the worst journey in the world?

Proposed best modeling practices for assessing the effects of ecosystem restoration on fish

Contact Info

Product

Resources

About