Scientific knowledge of biological processes that are potentially useful in fish stock predictions
In: Scientia Marina (Barcelona). Consejo Superior de Investigaciones Científicas. Institut de Ciènces del Mar: Barcelona. ISSN 0214-8358; e-ISSN 1886-8134, more Also appears in:Ulltang, Ø.; Blom, G. (2003). Fish stock assessments and predictions: integrating relevant knowledge. SAP Symposium held in Bergen, Norway 4-6 December 2000. Scientia Marina (Barcelona), 67(S1). Institut de Ciències de Mar: Barcelona. 374 pp. https://dx.doi.org/10.3989/scimar.2003.67s1, more |   |
| Keywords | Environmental effects
Environmental impact
Interactions
Prediction
Spawning
Stocks
Taxa > Species
Marine/Coastal |
| Authors | | Top | - Köster, F.W.
- Schnack, D.
- Möllmann, C.
| | |
| Abstract | Based on an extensive review of available knowledge, several sources of information have been identified as potentially useful in fish stock predictions. They refer to a variety of biological processes of importance for stock dynamics, e.g. growth, maturation and egg production as well as early and juvenile life stage survival and subsequent recruitment, for which examples are given. Environmental variables impacting these processes were derived, ranging from simple statistical exploratory analyses to complex process studies for various stocks in different sea areas. Causal relationships are understood to varying degrees and in several cases the identified variables may only be taken as proxies for processes not investigated in detail yet. Besides the explanatory power of relevant variables, their predictability and related predictive time frames are of major importance for a potential application in stock predictions. These criteria in particular may hamper implementation in the foreseeable future in several cases. However, the information may still be highly relevant for a) hindcasting stock developments that are so far not fully understood, b) defining stock projection scenarios for simulation of different fishery management strategies under varying environmental conditions and considering species interactions and c) elucidating areas of future research to further enhance our predictive capabilities. |
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