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）的变化对卫生、农业和自然资源管理等一系列紧迫问题的决策具有重要意义。许多人类活动增加了一个地区栖息地的斑块性，从而影响了物种分布。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上，哪些物种将进入它们之间的区域，科学家们不仅需要考虑它们喜欢的栖息地，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，研究人员将测试一个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有关的哺乳动物。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。参与该项目的研究生和本科生将获得数据收集、地理信息系统（GIS）分析和计算机编码方面的培训。除了发表有关研究结果的科学论文外，该团队还将举办研讨会，编写计算机代码、教程和网络研讨会。在一个由自然破碎的山地栖息地岛屿或天空岛屿组成的系统中，研究人员将利用物种特征、异速缩放（基于体型）以及现在和过去气候的空间模式来测试关于物种间差异定居和灭绝的假设。为了预测特定物种在给定斑块中发生，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东部马德雷山脉（该系统的大陆）目前孤立的mesic山地森林有关的小型非游动性哺乳动物。具体来说，研究人员将：1。获取大陆物种的发生记录和性状数据；2. 根据应用于现在和过去条件的生态位模型，利用体型、营养水平、连通性和面积对一个天空岛复合体内的每个物种和斑块进行预测；3. 通过实地调查确定斑块的物种组成；和4。进行物种间差异定殖和灭绝的统计检验。该项目将促进对跨空间和时间影响物种范围的因素的理解，使研究人员能够改进生物多样性预测，并促进C-DIB在基础科学和应用科学中的进一步发展和使用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识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.