Predicting mammalian communities in Mesoamerican 'sky islands' using species traits and spatiotemporal patterns of environmental suitability

了解和预测物种地理分布（或范围）的变化对于就卫生、农业和自然资源管理中的一系列紧迫问题做出决策非常重要。许多人类活动增加了一个地区生境的斑块，从而影响物种的分布。然而，预测破碎化对特定物种的影响仍然很困难。为了预测哪些物种将留在每个斑块中，哪些将进入它们之间的区域，科学家不仅需要考虑它们的首选栖息地，还需要考虑该地区的环境历史和物种本身的其他特征（如体型，扩散能力和繁殖率）。在这里，研究人员将测试一种新的模型来预测破碎景观中的物种分布，并将其应用于与山林相关的哺乳动物。该研究将评估环境历史和物种特征在预测特定森林斑块中物种存在或不存在方面的作用。为该项目做出贡献的研究生和本科生将获得数据收集，使用地理信息系统（GIS）分析和计算机编码方面的培训。除了发表关于研究结果的科学论文外，该团队还将举办研讨会，并制作计算机代码，教程和网络研讨会。在一个自然分散的山地栖息地岛屿或天空岛屿系统中，研究人员将使用特征，异速生长比例（基于身体大小）以及现在和过去气候的空间模式来测试关于物种之间差异殖民和灭绝的假设。为了预测特定斑块中出现的特定物种，他们将实施新的基于约束的动态岛屿生物地理学模型（C-DIB）。该小组将研究与墨西哥（该系统的大陆）马德雷山脉东方目前孤立的梅西奇山地森林有关的小型非飞行哺乳动物。具体而言，研究人员将：1。搜集内地物种的出现纪录及性状资料; 2.使用体型、营养级、连通性和面积的测量，从应用于现在和过去条件的生态位模型中预测一个天空岛复合体内的每个物种和斑块; 3.通过实地调查确定斑块的物种组成;以及4.对物种之间的差异殖民和灭绝进行统计检验。该项目将促进对跨空间和时间影响物种范围的因素的了解，使研究人员能够改善生物多样性预测，并激发C-DIB在基础和应用科学中的进一步开发和使用。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Understanding and predicting shifts in species geographic distributions (or ranges) is important to inform decision-making on a range of pressing issues in health, agriculture, and natural-resource management. Many human activities increase the patchiness of habitats in an area, thus affecting species distributions. However, predicting the effects of fragmentation on particular species remains difficult. To forecast which species will remain in each patch and which will move into the areas between them, scientists need to consider not only their preferred habitats but also the environmental history of the region and other traits of the species themselves (like body size, dispersal ability, and reproductive rates). Here, the researchers will test a new model to forecast species distributions in fragmented landscapes, applying it to mammals associated with mountain forests. The research will evaluate the roles of environmental history and species traits in predicting a species' presence or absence in particular forest patches. Graduate and undergraduate students contributing to the project will gain training in data collection, analyses using Geographic Information Systems (GIS), and computer coding. In addition to publishing scientific papers on the findings, the team will conduct workshops and produce computer code, tutorials, and webinars. In a system of naturally fragmented, montane habitat islands or sky islands, the researchers will test hypotheses regarding differential colonization and extinction among species using traits, allometric scaling (based on body size), and spatial patterns of present and past climate. To predict the particular species occurring in given patches, they will implement the new Constraint-based model of Dynamic Island Biogeography (C-DIB). The team will do so studying small non-volant mammals associated with currently isolated mesic montane forests of the Sierra Madre Oriental in Mexico (the mainland of this system). Specifically, the researchers will: 1. obtain occurrence records and trait data for species of the mainland; 2. make predictions for each species and patch within one sky island complex using body size, trophic level, and measures of connectivity and area from ecological niche models applied to present and past conditions; 3. determine the species composition of the patches by conducting field inventories; and 4. perform statistical tests of differential colonization and extinction among species. This project will advance understanding of the factors that affect species ranges across space and over time, empowering researchers to improve biodiversity prediction and spark further development and use of the C-DIB in basic and applied science.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.