M. Potier , M. Robert , L. Pawlowski , D. Gascuel , M. Savina-Rolland
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引用次数: 0
Abstract
Integrating information on ecosystem dynamics into single-species stock assessment has been recommended for fisheries management to head towards Ecosystem-Approach to Fisheries Management (EAFM). This paper proposes a sensitivity analysis of single-species assessments in relation to the implementation of time-varying natural mortality (M). Time-varying estimates from a holistic ecosystem model were implemented in exploratory Celtic Sea gadoid stock assessments. Two species were selected to disclose different temporal patterns in M: whiting (Merlangius merlangus) displaying a trend and haddock (Melanogrammus aeglefinus) exhibiting high variability with no trend. Implementing overall higher M levels increases Spawning Stock Biomass (SSB) and decreases average fishing mortality at age (Fbar) in both cases. Here, time-varying values induce reference points modification. Introducing a trend in M improves the assessment quality for whiting, while shifting the stock status from fully exploited to overexploited for several years. Integrating high M variability for haddock induces minimal changes in assessment quality and stock status. In both cases, short term projected sustainable catch level was reduced by 14%. Despite uncertainty around estimates, results suggest that integrating M accounting for a varying predation is crucial, especially when M disclose a trend. Future research should focus on comparing M estimates across various sources, including ecosystem models, and benchmarking the single-species models’ sensitivity to time-varying values.
期刊介绍:
The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).