Phylogeny predicts future habitat shifts due to climate change.

Phylogeny predicts future habitat shifts due to climate change.
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DOI:
10.1371/journal.pone.0098907
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发表时间:
2014
期刊:
影响因子:
3.7
通讯作者:
Coddington JA
Coddington JA
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Kuntner M;Năpăruş M;Li D;Coddington JA

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分类群对气候变化的反应可能不同,这取决于系统发育或生态影响,但在这些替代方案中区分的研究很少。在这里,我们使用来自全球分布的蜘蛛分支的两个物种对,每对代表两种生活方式(多面手和专家),以测试系统发育和生态在预测对气候变化的反应中的相对重要性。我们利用最近的系统发育假说,从符合上述标准的两个属(NePhilingis和NePhilengys)中选择了四个种,它们完全异地分布,但组合在一起占据了所有的亚热带-热带地区。根据它们的记录,我们模拟了每个物种的生态位空间,并使用定制的地理信息系统工具和预测的气候变化预测了它们未来20、40、60和80年后的生态变化。与生活方式相比,系统发育学能更好地预测物种当前的生态偏好。到2080年,所有物种都面临适宜栖息地的急剧减少(54.8-77.1%),并通过向更高的海拔和纬度迁移来适应,尽管移动的节奏不同。系统发育和生活方式解释了模拟的栖息地在海拔上的变化,但系统发育是唯一最好的纬度变化预测因子。包含系统发育相关性的模型是准确预测对全球变化的生物反应的重要补充工具。
Taxa may respond differently to climatic changes, depending on phylogenetic or ecological effects, but studies that discern among these alternatives are scarce. Here, we use two species pairs from globally distributed spider clades, each pair representing two lifestyles (generalist, specialist) to test the relative importance of phylogeny versus ecology in predicted responses to climate change. We used a recent phylogenetic hypothesis for nephilid spiders to select four species from two genera (Nephilingis and Nephilengys) that match the above criteria, are fully allopatric but combined occupy all subtropical-tropical regions. Based on their records, we modeled each species niche spaces and predicted their ecological shifts 20, 40, 60, and 80 years into the future using customized GIS tools and projected climatic changes. Phylogeny better predicts the species current ecological preferences than do lifestyles. By 2080 all species face dramatic reductions in suitable habitat (54.8–77.1%) and adapt by moving towards higher altitudes and latitudes, although at different tempos. Phylogeny and life style explain simulated habitat shifts in altitude, but phylogeny is the sole best predictor of latitudinal shifts. Models incorporating phylogenetic relatedness are an important additional tool to predict accurately biotic responses to global change.
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