Department of Botany, University of Wyoming, 1000 E. University Ave., Laramie, WY, 82071, USA.
Southern Oregon University, Biology and Environmental Science and Policy Programs, 1250 Siskiyou Boulevard, Ashland, OR, 97520, USA.
Ecol Lett. 2018 Mar;21(3):411-421. doi: 10.1111/ele.12914. Epub 2018 Jan 22.
Correlations between community-weighted mean (CWM) traits and environmental gradients are often assumed to quantify the adaptive value of traits. We tested this assumption by comparing these correlations with models of survival probability using 46 perennial species from long-term permanent plots in pine forests of Arizona. Survival was modelled as a function of trait × environment interactions, plant size, climatic variation and neighbourhood competition. The effect of traits on survival depended on the environmental conditions, but the two statistical approaches were inconsistent. For example, CWM-specific leaf area (SLA) and soil fertility were uncorrelated. However, survival was highest for species with low SLA in infertile soil, a result which agreed with expectations derived from the physiological trade-off underpinning leaf economic theory. CWM trait-environment relationships were unreliable estimates of how traits affected survival, and should only be used in predictive models when there is empirical support for an evolutionary trade-off that affects vital rates.
群落加权均值(CWM)特征与环境梯度之间的相关性通常被认为可以量化特征的适应值。我们通过使用来自亚利桑那州松林长期永久样地的 46 个多年生物种,将这些相关性与生存概率模型进行比较来检验这一假设。生存被建模为特征与环境相互作用、植物大小、气候变异和邻域竞争的函数。特征对生存的影响取决于环境条件,但这两种统计方法并不一致。例如,CWM 比叶面积(SLA)和土壤肥力之间没有相关性。然而,在贫瘠土壤中 SLA 较低的物种的存活率最高,这一结果与基于叶片经济理论的生理权衡的预期一致。CWM 特征-环境关系是对特征如何影响生存的不可靠估计,并且只有在有经验支持影响关键比率的进化权衡时,才应将其用于预测模型。