Context Dependence of Local Adaptation to Abiotic and Biotic Environments: A Quantitative and Qualitative Synthesis
Context Dependence of Local Adaptation to Abiotic and Biotic Environments: A Quantitative and Qualitative Synthesis
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DOI：
10.1086/707322
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发表时间：
2020-03-01
影响因子：
2.9
通讯作者：
Moeller, David A.
中科院分区：
文献类型：
--
作者：
Briscoe Runquist, Ryan D.;Gorton, Amanda J.;Moeller, David A.
理解空间变量选择如何塑造适应是进化生态学长期关注的一个领域。最近的荟萃分析已经量化了局部适应的程度，但对驱动种群差异的非生物和生物因素的相对重要性仍然知之甚少。为了解决这一差距，我们结合了定量荟萃分析和定性荟萃分析，以(1)量化对非生物和生物因素的局部适应程度，(2)表征影响寻求测试局部适应的实验动机和设计的主要主题。使用本地-外来对比作为本地适应（或不适应）的度量标准，我们发现存在生物相互作用时的本地适应比不存在生物相互作用时更大，尤其是对植物而言。我们还发现，当忽略这些环境是本地环境还是外来环境时，生物环境对适应性的影响比非生物环境更强。低纬度地区生物效应较强，高纬度地区非生物效应较强。我们的定性分析表明，通过该镜头，当地适应已经检查不同的非生物和生物因素。它还揭示了实验设计和实施中的偏差，这些偏差使定量结果难以解释，并为未来的研究提供了方向。
Understanding how spatially variable selection shapes adaptation is an area of long-standing interest in evolutionary ecology. Recent meta-analyses have quantified the extent of local adaptation, but the relative importance of abiotic and biotic factors in driving population divergence remains poorly understood. To address this gap, we combined a quantitative meta-analysis and a qualitative metasynthesis to (1) quantify the magnitude of local adaptation to abiotic and biotic factors and (2) characterize major themes that influence the motivation and design of experiments that seek to test for local adaptation. Using local-foreign contrasts as a metric of local adaptation (or maladaptation), we found that local adaptation was greater in the presence than in the absence of a biotic interactor, especially for plants. We also found that biotic environments had stronger effects on fitness than abiotic environments when ignoring whether those environments were local versus foreign. Finally, biotic effects were stronger at low latitudes, and abiotic effects were stronger at high latitudes. Our qualitative analysis revealed that the lens through which local adaptation has been examined differs for abiotic and biotic factors. It also revealed biases in the design and implementation of experiments that make quantitative results challenging to interpret and provided directions for future research.