Body size trends in response to climate and urbanization in the widespread North American deer mouse, Peromyscus maniculatus
Body size trends in response to climate and urbanization in the widespread North American deer mouse, Peromyscus maniculatus
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DOI：
10.1038/s41598-020-65755-x
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发表时间：
2020-06-01
影响因子：
4.6
通讯作者：
McLean, Bryan S.
中科院分区：
文献类型：
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作者：
Guralnick, Robert;Hantak, Maggie M.;McLean, Bryan S.
体型下降被认为是对气候变暖的关键反应，包括由城市热岛引起的变暖。然而，城市化也可能通过栖息地破碎化产生较小恒温动物体型增加的选择性梯度。在这里，我们利用密集采样的多源数据集来研究气候和城市化如何影响马齿虎（Peromyscus maniculatus， PEMA）的体型，PEMA是一种遍布北美的大量啮齿动物。我们预测PEMA将符合伯格曼规则，例如，在空间和时间上，更大的个体在更冷的气候中。关于体型与城市化关系的假设不太清楚；然而，由于人类活动增加了食物资源，我们预计PEMA的规模会增加。空间混合模型表明，PEMA符合Bergmann规则，城市化程度越高的地区PEMA越短。在混合模型中加入十年后，我们发现无论气候或人口密度如何，PEMA的质量都随着时间的推移而减少，而不是长度。我们还意外地发现，随着时间的推移，体型较小的PEMA种群越来越大，而体型较大的种群越来越小。我们的工作强调了使用密集的时空数据集和考虑偏差的建模框架的重要性，以更好地解开大尺度气候和城市化对体型的影响。
Body size decline is hypothesized to be a key response to climate warming, including warming driven by urban heat islands. However, urbanization may also generate selective gradients for body size increases in smaller endotherms via habitat fragmentation. Here we utilize a densely sampled, multi-source dataset to examine how climate and urbanization affect body size of Peromyscus maniculatus (PEMA), an abundant rodent found across North America. We predicted PEMA would conform to Bergmann's Rule, e.g. larger individuals in colder climates, spatially and temporally. Hypotheses regarding body size in relation to urbanization are less clear; however, with increased food resources due to greater anthropogenic activity, we expected an increase in PEMA size. Spatial mixed-models showed that PEMA conform to Bergmann's Rule and that PEMA were shorter in more urbanized areas. With the inclusion of decade in mixed-models, we found PEMA mass, but not length, is decreasing over time irrespective of climate or population density. We also unexpectedly found that, over time, smaller-bodied populations of PEMA are getting larger, while larger-bodied populations are getting smaller. Our work highlights the importance of using dense spatiotemporal datasets, and modeling frameworks that account for bias, to better disentangle broad-scale climatic and urbanization effects on body size.