Edwards Kyle F
Department of Oceanography, University of Hawai'i, Honolulu, Hawai'i, USA.
Ecology. 2016 Dec;97(12):3441-3451. doi: 10.1002/ecy.1581.
The distribution of functional traits in communities, and how trait distributions shift over time and space, is critical information for understanding community structure, the maintenance of diversity, and community effects on ecosystem function. It is often the case that traits tightly linked to ecological performance, such as physiological capacities, are laborious to measure and largely unknown for speciose communities; however, these traits are particularly important for unraveling the mechanistic basis of community structure. Here I develop a method combining sparse trait data with a statistical niche model to infer trait distributions for phytoplankton communities and how they vary over 10 yr in the western English Channel. I find that community-average nitrate affinity, light-limited growth rate, and maximum growth rate all show major seasonal patterns, reflecting alternate limitation by light vs. nitrogen. Trait diversity exhibits a variety of patterns distinct from community trait means, which suggests complex regulation of functional diversity. Patterns such as these are important for predicting how ocean ecosystems will respond to global change, and for developing trait-based models of emergent community structure. The statistical approach used here could be applied to any kind of organism, if it exhibits strong relationships between traits and statistical niche estimates.
群落中功能性状的分布,以及性状分布如何随时间和空间变化,是理解群落结构、多样性维持以及群落对生态系统功能影响的关键信息。通常情况下,与生态表现紧密相关的性状,如生理能力,测量起来很费力,而且对于物种丰富的群落来说大多未知;然而,这些性状对于揭示群落结构的机制基础尤为重要。在此,我开发了一种方法,将稀疏的性状数据与统计生态位模型相结合,以推断浮游植物群落的性状分布及其在英吉利海峡西部10年中的变化情况。我发现群落平均硝酸盐亲和力、光限制生长率和最大生长率都呈现出主要的季节性模式,反映了光与氮的交替限制。性状多样性呈现出与群落性状均值不同的多种模式,这表明功能多样性受到复杂的调控。此类模式对于预测海洋生态系统如何应对全球变化,以及构建基于性状的新兴群落结构模型非常重要。如果某类生物的性状与统计生态位估计之间存在强关联,那么这里所使用的统计方法可应用于任何生物。