Differences in trait–environment relationships: Implications for community weighted means tests

Author:

Lepš Jan12ORCID,de Bello Francesco13ORCID

Affiliation:

1. Department of Botany, Faculty of Science University of South Bohemia České Budějovice Czech Republic

2. Biology Research Centre, Czech Academy of Sciences Institute of Entomology České Budějovice Czech Republic

3. Centro de Investigaciones sobre Desertificación (CSIC‐UV‐GV) Valencia Spain

Abstract

Abstract One of J.P. Grime's greatest achievements was demonstrating the importance of the relationship between the environment and plant functional traits for understanding community assembly processes and the effects of biodiversity on ecosystem functioning. A popular approach assessing trait–environment relationships is the community weighted means (CWMs) method, which evaluates changes in communities' average trait values along gradients, with Grime being among its first practitioners. Today the CWM method is well‐established but some scholars have criticized it for inflated Type I errors. That is, in some scenarios of compositional turnover along a gradient, CWM tests can provide significant results even for randomly generated traits. Null models have been proposed to correct for such effects by randomizing trait values across species (CWM‐sp). We review different approaches relating traits to the environment within the framework of the accepted dichotomy between species‐level (observations are species) versus community‐level (observations are community parameters) analyses. Between these families of analyses and their combinations, a great variety of methods exist that test different trait–environment relationships, each with different null hypotheses and ecological questions. In classic CWM tests, the null hypothesis focuses on characteristics of trait distributions at the community level along gradients. The Type I error rate should not be a priori considered inflated when this test is used to identify changes in community trait structure affecting the functioning of communities. Trait changes observed with CWM tests may be accurate, but the interpretation that a specific trait drives turnover may be fallacious. Approaches like CWM‐sp may be more appropriate for testing other ecological hypotheses, such as whether trait–environment relationships are widespread across species. In effect, this moves the ecological focus towards species‐level analyses, that is on the adaptive value of traits and their relation to species niches. Synthesis. There is no single trait–environment relationship. Species‐level and community‐level analyses, including variants within them, test different relationships with different null hypotheses, such that the potential for inflated error rates can be misleading. Using a spectrum of methods provides a comprehensive picture of the diversity of trait–environment relationships.

Funder

Agencia Estatal de Investigación

Grantová Agentura České Republiky

Publisher

Wiley

Subject

Plant Science,Ecology,Ecology, Evolution, Behavior and Systematics

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3