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RESEARCH ARTICLE

Evaluating the sensitivity of ecological indicators with a perspective of temporal scales

Chongliang Zhang A B , Yong Chen B , Yiping Ren A and Rong Wan A C
+ Author Affiliations
- Author Affiliations

A College of Fisheries, Ocean University of China, 5 Yushan Road, Qingdao, 266003, China.

B School of Marine Sciences, University of Maine, Orono, ME 04469, USA.

C Corresponding author. Email: rongwan@ouc.edu.cn

Marine and Freshwater Research 68(9) 1664-1676 https://doi.org/10.1071/MF16084
Submitted: 18 March 2016  Accepted: 22 November 2016   Published: 1 February 2017

Abstract

This simulation study tests the sensitivity of 12 candidate ecological indicators (EIs) that characterise fish abundance, body size and trophodynamics with respect to temporal scales. Size-spectrum models that explicitly account for trophic interactions are used to simulate community dynamics under different levels of fishing pressure, including a specific model of the fish community in Haizhou Bay, China, and trait-based models of generalised fishery systems. The sensitivity of EIs is characterised by (1) responsiveness, which refers to the dynamics of EI values with respect to the magnitude of changes in fishing effort, and (2) detectability, which measures the relative changes of EI with respect to reference baselines. The response of EIs is substantially non-linear over time. Most EIs are responsive to the reduction of fishing effort and have low detectability under high fishing pressure. Both characteristics of sensitivity tend to increase in the early years and level off in 2 decades, suggesting transient behaviours in EI dynamics. The results suggested the essential non-linear dynamics of EIs resulting from underlying trophic interactions and the potential misinterpretation of the temporal EIs dynamics. We highlight the necessity of considering temporal scales and fishing characteristics in applying EIs in fishery management.

Additional keywords: detectability, fishery management, responsiveness, size-spectrum model, trophic interaction.


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