关键词: autocorrelation biodiversity survey field ecology inertia regional effect sequential sampling spatial ecology

Mesh : Animals Vietnam Biodiversity Amphibians / physiology China Animal Distribution Models, Biological Markov Chains

来  源:   DOI:10.1111/1365-2656.14114

Abstract:
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.
摘要:
物种的分布在空间上不是随机的。在最高分辨率的空间尺度上,也就是说,现场采样位置,不同物种的分布聚集水平将由各种因素决定,例如空间自相关或环境过滤。然而,很少有研究定量衡量这些因素的重要性。在这项研究中,受马尔可夫转移模型的统计特性的启发,我们提出了一个新的加性框架来划分局部多物种分布聚集水平,以用于顺序采样得出的田间生物多样性数据。该框架将不同物种的空间分布聚集划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。通过中国西南部(MinyaKonka)和越南中南部的线横断面采样进行的野外两栖动物调查的实证研究表明,局部空间惯性始终是构成这两个地区两栖动物局部发生和分布聚集的主要机制,纬度梯度从1200到近4000m。但是,在海拔不高于2000米的高度多样化的热带地区(即越南),区域丰度变化仍然不可忽视。总之,我们提出了一个新的框架,表明多物种分布聚集水平可以由两个加性成分构成。这两个分配的组分在理论上可以是独立的。这些发现有望从空间分布和区域多样性格局的角度加深我们对当地社区结构的理解。该划分框架可能在田间生态学和宏观生态学研究中具有潜在的应用价值。
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