School of Environment, Environmental Futures Centre, Griffith University, Gold Coast, QLD 4222, Australia.
AoB Plants. 2014 Mar 26;6(0). doi: 10.1093/aobpla/plu008. Print 2014.
Classical approaches to investigating temporal and spatial changes in community composition offer only partial insight into the ecology that drives species distribution, community patterns and processes, whereas a functional approach can help to determine many of the underlying mechanisms that drive such patterns. Here, we aim to bring these two approaches together to understand such drivers, using an elevation gradient of sites, a repeat species survey and species functional traits. We used data from a repeat vegetation survey on five alpine summits and measured plant height, leaf area, leaf dry matter content and specific leaf area (SLA) for every species recorded in the surveys. We combined species abundances with trait values to produce a community trait-weighted mean (CTWM) for each trait, and then combined survey results with the CTWMs. Across the gradient of summits, more favourable conditions for plant growth (warmer, longer growing season) occurred at the lower elevations. Vegetation composition changes between 2004 and 2011 (according to non-metric multi-dimensional scaling ordination) were strongly affected by the high and increasing abundance of species with high SLA at high elevations. Species life-form categories strongly affected compositional changes and functional composition, with increasing dominance of tall shrubs and graminoids at the lower-elevation summits, and an overall increase in graminoids across the gradient. The CTWM for plant height and leaf dry matter content significantly decreased with elevation, whereas for leaf area and SLA it significantly increased. The significant relationships between CTWM and elevation may suggest specific ecological processes, namely plant competition and local productivity, influencing vegetation preferentially across the elevation gradient, with the dominance of shrubs and graminoids driving the patterns in the CTWMs.
经典的方法只能部分地揭示驱动物种分布、群落格局和过程的生态因素，而功能方法可以帮助确定许多驱动这些模式的潜在机制。在这里，我们旨在将这两种方法结合起来，以了解这些驱动因素，使用海拔梯度的地点、重复的物种调查和物种功能特征。我们使用了来自五个高山山顶的重复植被调查的数据，并测量了在调查中记录的每一种植物的株高、叶面积、叶干物质含量和比叶面积(SLA)。我们将物种丰度与特征值结合起来，为每个特征生成一个群落特征加权平均值(CTWM)，然后将调查结果与 CTWMs 结合起来。在山顶的梯度上，较高的海拔地区具有更有利于植物生长的条件(更温暖、更长的生长季节)。2004 年至 2011 年间(根据非度量多维标度排序)的植被组成变化受到高海拔地区高 SLA 物种高丰度的强烈影响。物种生活型分类强烈影响着组成变化和功能组成，随着低海拔山顶上高灌木和禾本科植物的优势地位增加，以及整个梯度上禾本科植物的总体增加。植物高度和叶干物质含量的 CTWM 随海拔显著降低，而叶面积和 SLA 的 CTWM 随海拔显著升高。CTWM 与海拔之间的显著关系可能表明，特定的生态过程，即植物竞争和局部生产力，优先影响整个海拔梯度上的植被，而灌木和禾本科植物的优势地位则驱动了 CTWM 中的模式。
