Florida Museum of Natural History, University of Florida, Gainesville, FL, 32611, USA.
Department of Biology, University of North Carolina Greensboro, Greensboro, NC, 27402, USA.
Sci Rep. 2020 Jun 1;10(1):8882. doi: 10.1038/s41598-020-65755-x.
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.
体型缩小被假设为对气候变暖的关键响应,包括由城市热岛引起的变暖。然而,城市化也可能通过生境破碎化,为较小的温血动物的体型增大产生选择性梯度。在这里,我们利用一个密集采样、多源数据集,来研究气候和城市化如何影响美洲旅鼠(Peromyscus maniculatus,PEMA)的体型,美洲旅鼠是一种在北美洲广泛存在的丰富啮齿动物。我们预测,PEMA 将符合伯格曼法则,即个体在更冷的气候中体型更大,在空间和时间上都是如此。与城市化有关的体型假设则不太明确;然而,由于人为活动增加带来了更多的食物资源,我们预计 PEMA 的体型会增大。空间混合模型显示,PEMA 符合伯格曼法则,在城市化程度较高的地区体型较短。在混合模型中加入十年的数据,我们发现,无论气候或种群密度如何,PEMA 的质量(而非长度)随着时间的推移而减少。我们还意外地发现,随着时间的推移,PEMA 的小体型种群变得更大,而大体型种群则变得更小。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,以更好地厘清气候和城市化对体型的广泛影响。