Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China.
Key Laboratory of Electronic and Information Engineering, State Ethnic Affairs Commission, Southwest Minzu University, Chengdu, China.
J Anim Ecol. 2024 Jul;93(7):932-942. doi: 10.1111/1365-2656.14114. Epub 2024 Jun 11.
The distribution of species is not random in space. At the finest-resolution spatial scale, that is, field sampling locations, distributional aggregation level of different species would be determined by various factors, for example spatial autocorrelation or environmental filtering. However, few studies have quantitatively measured the importance of these factors. In this study, inspired by the statistical properties of a Markov transition model, we propose a novel additive framework to partition local multispecies distributional aggregation levels for sequential sampling-derived field biodiversity data. The framework partitions the spatial distributional aggregation of different species into two independent components: regional abundance variability and the local spatial inertia effect. Empirical studies from field amphibian surveys through line-transect sampling in southwestern China (Minya Konka) and central-southern Vietnam showed that local spatial inertia was always the dominant mechanism structuring the local occurrence and distributional aggregation of amphibians in the two regions with a latitudinal gradient from 1200 to nearly 4000 m. However, regional abundance variability is still nonnegligible in highly diverse tropical regions (i.e. Vietnam) where the altitude is not higher than 2000 m. In summary, we propose a novel framework that shows that the multispecies distributional aggregation level can be structured by two additive components. The two partitioned components could be theoretically independent. These findings are expected to deepen our understanding of the local community structure from the perspective of both spatial distribution and regional diversity patterns. The partitioning framework might have potential applications in field ecology and macroecology research.
物种的分布在空间上并非随机的。在最精细的空间尺度上，即野外采样点，不同物种的分布聚集程度将由各种因素决定，例如空间自相关或环境过滤。然而，很少有研究定量测量这些因素的重要性。在这项研究中，受马尔可夫转移模型统计特性的启发，我们提出了一种新的加性框架，用于划分基于顺序采样的野外生物多样性数据的多物种局部分布聚集程度。该框架将不同物种的空间分布聚集分为两个独立的组成部分：区域丰度变异性和局部空间惯性效应。来自中国西南（岷山康卡）和越南中南部通过样线抽样进行的野外两栖动物调查的实证研究表明，在从 1200 米到近 4000 米的纬度梯度上，局部空间惯性始终是构造两个地区两栖动物局部出现和分布聚集的主导机制。然而，在高度多样化的热带地区（即越南），区域丰度变异性仍然不可忽视，那里的海拔不超过 2000 米。总之，我们提出了一个新的框架，表明多物种的分布聚集程度可以由两个加性成分来构造。这两个划分的组成部分在理论上可能是独立的。这些发现有望从空间分布和区域多样性模式的角度深化我们对局部群落结构的理解。分区框架可能在野外生态学和宏观生态学研究中有潜在的应用。
