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专性互惠共生关系可能会限制开花植物的地理分布。

Specialized mutualisms may constrain the geographical distribution of flowering plants.

机构信息

School of Life Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg 3209, South Africa

School of Life Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg 3209, South Africa.

出版信息

Proc Biol Sci. 2017 Nov 15;284(1866). doi: 10.1098/rspb.2017.1841.

Abstract

It is commonly assumed that the geographical distributions of plants are governed mainly by abiotic variables. However, interactions with other organisms, such as pollinators, also have the potential to influence plant distributions. To investigate this, we developed niche models for 32 plant taxa that have specialized pollination systems and which are native to a biodiversity hotspot (South Africa). We found that the distributions of these taxa are best explained by a combination of biotic (pollinators) and abiotic factors, rather than by abiotic factors alone. For approximately 66% of these plant taxa, pollinator distributions were the factor that provided the best predictor of their niches. Furthermore, co-occurrence of these plants and their pollinators was generally not explained solely by shared abiotic niches, and thus probably reflects broad-scale positive ecological interactions. These results are consistent with the proposal that pollinator distributions may constrain plant distributions and highlight the general potential for species distributions to be shaped by positive interactions with other species. This has important consequences for predicting how distributions of species might change in the face of loss of their key mutualists.

摘要

人们通常认为植物的地理分布主要受非生物变量的控制。然而,与其他生物的相互作用,如传粉者,也有可能影响植物的分布。为了研究这一点,我们为 32 种具有专门传粉系统且原产于生物多样性热点地区(南非)的植物类群开发了生态位模型。我们发现,这些类群的分布最好由生物因素(传粉者)和非生物因素的组合来解释,而不是仅仅由非生物因素来解释。对于这些植物类群中的约 66%,传粉者的分布是预测其生态位的最佳因素。此外,这些植物与其传粉者的共存通常不仅仅是由共同的非生物生态位来解释的,因此可能反映了广泛的积极生态相互作用。这些结果与传粉者的分布可能限制植物分布的观点一致,并强调了物种分布可能受到与其他物种的积极相互作用的普遍影响。这对预测物种的分布在失去关键共生体的情况下可能会如何变化具有重要意义。

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