Dimensions USBIOTA- Sao Paulo: Collaborative Proposal: Traits as predictors of adaptive diversification along the Brazilian Dry Diagonal

巴西干对角线（BDD）是一个广阔的地区，拥有多样化和独特的栖息地，夹在西部湿润的亚马逊盆地和东部潮湿的热带和亚热带大西洋森林之间。虽然从表面上看，BDD似乎是一片贫瘠的荒地，几乎没有什么物种，但实际上它拥有许多独特的物种，构成了巴西最濒危的栖息地，并且正在迅速失去农业和其他人类入侵。这项研究将首次综合物种特征、群落和遗传学信息，以了解生活在BDD中的生物的独特特征和群落是如何进化的。利用一系列不同的方法来详细研究今天栖息在巴西中部这片广阔的干燥栖息地的各种动物、植物和真菌，研究人员将评估：1)什么样的特征——比如体型、形状或特定行为——允许一群生物在一个新的环境中成功？2)新环境如何决定我们今天看到的生物群落？3)生物如何从遗传和形态上适应这种新环境？4)新的特征、群落和基因变化是如何相互作用，产生了今天在不同环境中看到的各种生物体的？这些问题的答案将提高科学家预测世界变化对生物多样性影响的能力。该项目将通过吸引来自美国和巴西的一个大型专家团队来促进新的国际研究合作，并将为本科生、研究生和博士后研究人员提供跨学科研究培训机会。为了实现上面列出的四个目标，该项目将首先使用一种机器学习方法，应用于BDD中的数百个特征和谱系，以确定哪些特征预示着进化的成功——适应干旱的物种经历进化多样化的趋势。然后，该项目将采用群落系统发育方法来了解BDD中功能性状变异的分布情况，并将确定目前居住在BDD的特定群落中观察到的性状值的进化模式和过度或不足分散，以及性状是如何在生境梯度中过滤的。最后，该项目使用各种基因组技术，包括全基因组测序和转录组学，以了解生物如何适应BDD更干燥的栖息地，而不是生活在邻近的mesic生物群系中的近亲。通过将性状、群落和基因的进化模式联系起来，该项目将综合BDD生物多样性的功能、系统发育和遗传维度，并全面描绘其起源和进化。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。

The Brazilian Dry Diagonal (BDD) is a broad region of diverse and unique habitats sandwiched in between the wetter Amazon basin to the west and the moist tropical and subtropical Atlantic Forest to the east. Although the BDD can appear superficially to be wasteland with little variety, in fact it harbors many unique species, comprise the most endangered set of habitats in Brazil, and is being rapidly being lost to agriculture and other human encroachment. This research will be the first to synthesize information from species' traits, communities, and genetics to understand how the unique traits and communities of organisms living in the BDD evolved. Using a diverse set of approaches to study in detail a variety of animals, plants and fungi that today inhabit this broad swath of dry habitats in central Brazil, the researchers will evaluate: 1) what sorts of traits - such as body size, shape or specific behaviors - allow a group of organisms to succeed in a novel environment? 2) how the novel environment determines the set of organisms - the community - that we see today? 3) how organisms adapt genetically and morphologically to that novel environment? and 4) how novel traits, communities, and genetic changes interact to produce the variety of organisms that are seen in different environments today? Answers to these questions will improve scientists' ability to predict the impacts of a changing world on biodiversity. The project will foster new international research collaborations by engaging a large team of experts from the United States and Brazil and will also provide interdisciplinary research training opportunities for undergraduate students, graduate students and post-doctoral researchers. To accomplish the four aims listed above, the project will first use a machine learning approach applied to hundreds of traits and lineages in the BDD to determine which traits predict evolutionary success - the tendency for xeric-adapted species to undergo evolutionary diversification. The project will then employ community phylogenetics approaches to understand how functional trait variation is distributed in the BDD, and will determine the evolutionary patterns and over- or under-dispersion of trait values observed in particular communities inhabiting the BDD today, as well as how traits are filtered across habitat gradients. Finally, the project uses a variety of genomic technologies, including whole genome sequencing and transcriptomics, to understand how organisms adapt to the more xeric habitats of the BDD as compared to close relatives living in adjacent mesic biomes. By linking evolutionary patterns in traits, communities and genes, the project will synthesize the functional, phylogenetic and genetic dimensions of biodiversity of the BDD and present a comprehensive portrait of its origins and evolution.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.