Environmental Genetics & Genomics Facility, Department of Biological Sciences, Northern Arizona University, 617 South Beaver Street, PO Box 5640, Flagstaff, Arizona, 86011, USA.
Merriam-Powell Center for Environmental Research, Northern Arizona University, 800 South Beaver Street, PO Box 6077, Flagstaff, Arizona, 86011, USA.
Ecol Appl. 2021 Apr;31(3):e02254. doi: 10.1002/eap.2254. Epub 2021 Jan 20.
Ecological niche models (ENMs) have classically operated under the simplifying assumptions that there are no barriers to gene flow, species are genetically homogeneous (i.e., no population-specific local adaptation), and all individuals share the same niche. Yet, these assumptions are violated for most broadly distributed species. Here, we incorporate genetic data from the widespread riparian tree species narrowleaf cottonwood (Populus angustifolia) to examine whether including intraspecific genetic variation can alter model performance and predictions of climate change impacts. We found that (1) P. angustifolia is differentiated into six genetic groups across its range from México to Canada and (2) different populations occupy distinct climate niches representing unique ecotypes. Comparing model discriminatory power, (3) all genetically informed ecological niche models (gENMs) outperformed the standard species-level ENM (3-14% increase in AUC; 1-23% increase in pROC). Furthermore, (4) gENMs predicted large differences among ecotypes in both the direction and magnitude of responses to climate change and (5) revealed evidence of niche divergence, particularly for the Eastern Rocky Mountain ecotype. (6) Models also predicted progressively increasing fragmentation and decreasing overlap between ecotypes. Contact zones are often hotspots of diversity that are critical for supporting species' capacity to respond to present and future climate change, thus predicted reductions in connectivity among ecotypes is of conservation concern. We further examined the generality of our findings by comparing our model developed for a higher elevation Rocky Mountain species with a related desert riparian cottonwood, P. fremontii. Together our results suggest that incorporating intraspecific genetic information can improve model performance by addressing this important source of variance. gENMs bring an evolutionary perspective to niche modeling and provide a truly "adaptive management" approach to support conservation genetic management of species facing global change.
生态位模型 (ENMs) 经典地基于以下简化假设运作：不存在基因流动的障碍，物种在遗传上是同质的（即没有种群特异性的局部适应），并且所有个体都共享相同的生态位。然而，这些假设对于大多数广泛分布的物种都是不成立的。在这里，我们结合了广泛分布的河岸树种狭叶杨（Populus angustifolia）的遗传数据，以检验包含种内遗传变异是否可以改变模型性能和预测气候变化的影响。我们发现：(1) P. angustifolia 在其从墨西哥到加拿大的分布范围内分化为六个遗传群体；(2) 不同的种群占据不同的气候生态位，代表独特的生态型。比较模型区分能力，(3) 所有基于遗传的生态位模型 (gENMs) 都优于标准的物种水平 ENM（AUC 增加 3-14%，pROC 增加 1-23%）。此外，(4) gENMs 预测了不同生态型对气候变化的响应方向和幅度的巨大差异；(5) 揭示了生态位分歧的证据，特别是对于落矶山东部生态型。(6) 模型还预测了生态型之间的碎片化程度逐渐增加，重叠程度逐渐降低。接触区通常是多样性的热点，对于支持物种应对当前和未来气候变化的能力至关重要，因此，预测到生态型之间的连通性降低是令人关注的保护问题。我们通过比较我们为高海拔落矶山物种开发的模型与相关的沙漠河岸杨（P. fremontii），进一步检验了我们发现的普遍性。总的来说，我们的结果表明，通过解决这种重要的方差来源，纳入种内遗传信息可以提高模型性能。gENMs 为生态位建模带来了进化视角，并为支持面临全球变化的物种的保护遗传管理提供了一种真正的“适应性管理”方法。
