Interspecific relationships and environmentally driven catchabilities estimated from fisheries data

Author:

Hosack Geoffrey R.1,Peters Gareth W.2,Ludsin Stuart A.3

Affiliation:

1. CSIRO Marine Laboratories, Castray Esplanade, Hobart, Tasmania 7000, Australia.

2. Department of Statistical Science, University College London, Gower Street, London WC1E 6BT, UK.

3. Aquatic Ecology Laboratory, Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, 1314 Kinnear Road, 232 Research Center, Columbus, OH 43212, USA.

Abstract

A modelling framework is proposed to investigate possible interactions among fisheries, species, and shared environmental drivers. Two hypotheses that introduce temporal dependence among commercial and recreational catch and effort data from Lake Erie’s walleye (Sander vitreus) and yellow perch (Perca flavescens) stocks are evaluated using state space models. First, alternative forms of association between the mortality, recruitment, or migration of the two species are explored by modelling dependence in the interspecific process noise. Second, annual phosphorus inputs into Lake Erie, which are linked to the development of hypoxia, are tested for associations with the catchabilities of the fisheries. Interspecific process noise was positively associated, which suggests that mortality, recruitment, or migration is linked between walleye and yellow perch. Only for yellow perch, however, was annual phosphorus loading associated with catchability. The estimated probability that either stock fell below a common management benchmark was affected by the form of temporal dependence, which exemplifies the need to consider how interspecific interactions, shared environmental factors, and uncertainty in the process dynamics and observations affect stocks and their fisheries.

Publisher

Canadian Science Publishing

Subject

Aquatic Science,Ecology, Evolution, Behavior and Systematics

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Accounting for spatiotemporal sampling variation in joint species distribution models;Journal of Applied Ecology;2023-11-28

2. Fitting Time Series Models to Fisheries Data to Ascertain Age;Journal of Probability and Statistics;2023-10-07

3. Functional group based marine ecosystem assessment for the Bay of Biscay via elasticity analysis;PeerJ;2019-08-09

4. Review of State-Space Models for Fisheries Science;Annual Review of Statistics and Its Application;2018-03-07

5. Ecosystem Model in Data-Poor Situations;Fish Population Dynamics, Monitoring, and Management;2018

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