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捕鱼驱动的生态进化动力学:从单物种模型到复杂食物网内的动态进化

Eco-evolutionary dynamics driven by fishing: From single species models to dynamic evolution within complex food webs.

作者信息

Perälä Tommi, Kuparinen Anna

机构信息

Department of Biological and Environmental Sciences University of Jyväskylä Jyväskylä Finland.

出版信息

Evol Appl. 2020 Aug 26;13(10):2507-2520. doi: 10.1111/eva.13058. eCollection 2020 Dec.

Abstract

Evidence of contemporary evolution across ecological time scales stimulated research on the eco-evolutionary dynamics of natural populations. Aquatic systems provide a good setting to study eco-evolutionary dynamics owing to a wealth of long-term monitoring data and the detected trends in fish life-history traits across intensively harvested marine and freshwater systems. In the present study, we focus on modelling approaches to simulate eco-evolutionary dynamics of fishes and their ecosystems. Firstly, we review the development of modelling from single species to multispecies approaches. Secondly, we advance the current state-of-the-art methodology by implementing evolution of life-history traits of a top predator into the context of complex food web dynamics as described by the allometric trophic network (ATN) framework. The functioning of our newly developed eco-evolutionary ATNE framework is illustrated using a well-studied lake food web. Our simulations show how both natural selection arising from feeding interactions and size-selective fishing cause evolutionary changes in the top predator and how those feed back to its prey species and further cascade down to lower trophic levels. Finally, we discuss future directions, particularly the need to integrate genomic discoveries into eco-evolutionary projections.

摘要

跨生态时间尺度的当代进化证据激发了对自然种群生态进化动态的研究。由于丰富的长期监测数据以及在过度捕捞的海洋和淡水系统中检测到的鱼类生活史特征趋势,水生系统为研究生态进化动态提供了一个良好的环境。在本研究中,我们专注于模拟鱼类及其生态系统生态进化动态的建模方法。首先,我们回顾了从单物种到多物种建模方法的发展。其次,我们通过将顶级捕食者生活史特征的进化纳入由异速生长营养网络(ATN)框架描述的复杂食物网动态背景中,推进了当前的先进方法。我们使用一个经过充分研究的湖泊食物网来说明新开发的生态进化ATNE框架的功能。我们的模拟展示了由摄食相互作用产生的自然选择和大小选择性捕捞如何导致顶级捕食者的进化变化,以及这些变化如何反馈到其猎物物种并进一步级联到更低的营养级。最后,我们讨论了未来的方向,特别是将基因组发现整合到生态进化预测中的必要性。

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