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渔业诱导的营养级联的主要特征和背景依赖性。

Key features and context-dependence of fishery-induced trophic cascades.

机构信息

Marine Science Institute, University of California Santa Barbara, Santa Barbara, CA 93106-6150, USA.

出版信息

Conserv Biol. 2010 Apr;24(2):382-94. doi: 10.1111/j.1523-1739.2009.01436.x. Epub 2010 Feb 11.

Abstract

Trophic cascades triggered by fishing have profound implications for marine ecosystems and the socioeconomic systems that depend on them. With the number of reported cases quickly growing, key features and commonalities have emerged. Fishery-induced trophic cascades often display differential response times and nonlinear trajectories among trophic levels and can be accompanied by shifts in alternative states. Furthermore, their magnitude appears to be context dependent, varying as a function of species diversity, regional oceanography, local physical disturbance, habitat complexity, and the nature of the fishery itself. To conserve and manage exploited marine ecosystems, there is a pressing need for an improved understanding of the conditions that promote or inhibit the cascading consequences of fishing. Future research should investigate how the trophic effects of fishing interact with other human disturbances, identify strongly interacting species and ecosystem features that confer resilience to exploitation, determine ranges of predator depletion that elicit trophic cascades, pinpoint antecedents that signal ecosystem state shifts, and quantify variation in trophic rates across oceanographic conditions. This information will advance predictive models designed to forecast the trophic effects of fishing and will allow managers to better anticipate and avoid fishery-induced trophic cascades.

摘要

渔业引发的营养级联对海洋生态系统和依赖它们的社会经济系统有着深远的影响。随着报告案例数量的迅速增加,关键特征和共性已经显现出来。渔业引起的营养级联通常在营养级之间表现出不同的响应时间和非线性轨迹,并伴随着替代状态的转变。此外,它们的规模似乎取决于上下文,随着物种多样性、区域海洋学、当地物理干扰、栖息地复杂性和渔业本身的性质而变化。为了保护和管理受捕捞的海洋生态系统,迫切需要更好地了解促进或抑制捕捞级联后果的条件。未来的研究应该调查捕鱼的营养影响如何与其他人类干扰相互作用,确定赋予对开发具有弹性的强相互作用物种和生态系统特征,确定引发营养级联的捕食者消耗范围,确定指示生态系统状态转变的前兆,并量化跨海洋条件的营养率变化。这些信息将推进旨在预测渔业营养影响的预测模型,并使管理者能够更好地预测和避免渔业引发的营养级联。

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