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一个基于多性状的通用框架,用于研究生物多样性对生态系统功能的影响。

A general multi-trait-based framework for studying the effects of biodiversity on ecosystem functioning.

作者信息

Savage Van M, Webb Colleen T, Norberg Jon

机构信息

Santa Fe Institute, Santa Fe, NM 87501, USA.

出版信息

J Theor Biol. 2007 Jul 21;247(2):213-29. doi: 10.1016/j.jtbi.2007.03.007. Epub 2007 Mar 14.

Abstract

Environmental change is as multifaceted as are the species and communities that respond to these changes. Current theoretical approaches to modeling ecosystem response to environmental change often deal only with single environmental drivers or single species traits, simple ecological interactions, and/or steady states, leading to concern about how accurately these approaches will capture future responses to environmental change in real biological systems. To begin addressing this issue, we generalize a previous trait-based framework to incorporate aspects of frequency dependence, functional complementarity, and the dynamics of systems composed of species that are defined by multiple traits that are tied to multiple environmental drivers. The framework is particularly well suited for analyzing the role of temporal environmental fluctuations in maintaining trait variability and the resultant effects on community response to environmental change. Using this framework, we construct simple models to investigate two ecological problems. First, we show how complementary resource use can significantly enhance the nutrient uptake of plant communities through two different mechanisms related to increased productivity (over-yielding) and larger trait variability. Over-yielding is a hallmark of complementarity and increases the total biomass of the community and, thus, the total rate at which nutrients are consumed. Trait variability also increases due to the lower levels of competition associated with complementarity, thus speeding up the rate at which more efficient species emerge as conditions change. Second, we study systems in which multiple environmental drivers act on species defined by multiple, correlated traits. We show that correlations in these systems can increase trait variability within the community and again lead to faster responses to environmental change. The methodological advances provided here will apply to almost any function that relates species traits and environmental drivers to growth, and should prove useful for studying the effects of climate change on the dynamics of biota.

摘要

环境变化与对这些变化做出反应的物种和群落一样具有多面性。当前用于模拟生态系统对环境变化反应的理论方法通常只涉及单一环境驱动因素或单一物种特征、简单的生态相互作用和/或稳态,这引发了人们对这些方法能否准确捕捉真实生物系统未来对环境变化反应的担忧。为了开始解决这个问题,我们对之前基于特征的框架进行了推广,以纳入频率依赖性、功能互补性以及由与多个环境驱动因素相关的多个特征所定义的物种组成的系统的动态方面。该框架特别适合分析时间环境波动在维持特征变异性方面的作用以及对群落对环境变化反应的后续影响。利用这个框架,我们构建了简单模型来研究两个生态问题。首先,我们展示了互补资源利用如何通过与提高生产力(超产)和更大特征变异性相关的两种不同机制,显著增强植物群落的养分吸收。超产是互补性的一个标志,它增加了群落的总生物量,从而提高了养分消耗的总速率。由于与互补性相关的竞争水平较低,特征变异性也会增加,因此随着条件变化,更高效的物种出现的速率会加快。其次,我们研究了多个环境驱动因素作用于由多个相关特征定义的物种的系统。我们表明,这些系统中的相关性可以增加群落内的特征变异性,并再次导致对环境变化的更快反应。这里提供的方法进展几乎适用于将物种特征和环境驱动因素与生长联系起来的任何函数,并且应该被证明对研究气候变化对生物群动态的影响是有用的。

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