Determinants of palm species distributions across Africa: the relative roles of climate, non-climatic environmental factors, and spatial constraints
Determinants of palm species distributions across Africa: the relative roles of climate, non-climatic environmental factors, and spatial constraints
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DOI：
10.1111/j.1600-0587.2010.06273.x
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发表时间：
2010-04-01
期刊：
影响因子：
5.9
通讯作者：
Balslev, Henrik
中科院分区：
文献类型：
--
作者：
Blach-Overgaard, Anne;Svenning, Jens-Christian;Balslev, Henrik
地球上大部分的生物多样性都分布在热带地区。然而，仍然缺乏对哪些因素控制热带物种分布范围限制的全面了解。在大的空间尺度上，气候往往被认为是主要的范围决定机制。或者，物种的分布范围可能受土壤或其他环境因素的控制，或者受非环境因素的控制，如生物相互作用、扩散障碍、内在种群动态或从原产地或过去避难所的有限时间扩张。如何控制物种的分布范围对于预测它们对未来全球变化的反应至关重要。在这里，我们使用一种新的实现的物种分布模型（SDM），以评估非洲大陆规模的物种分布在一个关键的热带组，棕榈（槟榔科）的程度，由气候，非气候环境因素，或非环境的空间限制。利用SDM算法Maxent，结合气候和非气候环境预测因子（生境、人类影响）以及空间特征向量绘图（空间过滤器），收集和分析了关于非洲棕榈物种出现情况的综合数据集。表现最好的模型总是包括空间滤波器，这表明棕榈物种分布总是在一定程度上受到非环境约束的限制。包括气候的模型提供了比只包括非气候环境预测因子的模型更好的预测，后者在气候控制之外没有明显的影响。因此，在大陆尺度上，气候是非洲棕榈物种分布的唯一强有力的环境控制因素。关于非洲棕榈分布的最重要的气候预测因子，与水有关的因素对分析的29个物种中的25个最重要。棕榈树分布对气候的强烈反应以及非环境空间限制的重要性表明，非洲棕榈树对未来气候变化很敏感，但它们跟踪适当气候条件的能力将受到空间限制。
Most of the Earth's biodiversity resides in the tropics. However, a comprehensive understanding of which factors control range limits of tropical species is still lacking. Climate is often thought to be the predominant range-determining mechanism at large spatial scales. Alternatively, species' ranges may be controlled by soil or other environmental factors, or by non-environmental factors such as biotic interactions, dispersal barriers, intrinsic population dynamics, or time-limited expansion from place of origin or past refugia. How species ranges are controlled is of key importance for predicting their responses to future global change. Here, we use a novel implementation of species distribution modelling (SDM) to assess the degree to which African continental-scale species distributions in a keystone tropical group, the palms (Arecaceae), are controlled by climate, non-climatic environmental factors, or non-environmental spatial constraints. A comprehensive data set on African palm species occurrences was assembled and analysed using the SDM algorithm Maxent in combination with climatic and non-climatic environmental predictors (habitat, human impact), as well as spatial eigenvector mapping (spatial filters). The best performing models always included spatial filters, suggesting that palm species distributions are always to some extent limited by non-environmental constraints. Models which included climate provided significantly better predictions than models that included only non-climatic environmental predictors, the latter having no discernible effect beyond the climatic control. Hence, at the continental scale, climate constitutes the only strong environmental control of palm species distributions in Africa. With regard to the most important climatic predictors of African palm distributions, water-related factors were most important for 25 of the 29 species analysed. The strong response of palm distributions to climate in combination with the importance of non-environmental spatial constraints suggests that African palms will be sensitive to future climate changes, but that their ability to track suitable climatic conditions will be spatially constrained.