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，有着多样化和独特的栖息地，夹在西部较潮湿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。尽管BDD表面上看起来是一片物种稀少的荒地，但实际上它拥有许多独特的物种，构成了巴西最濒危的一组栖息地，正迅速消失在农业和其他人类入侵之下。这项研究将首次综合物种特征、群落和遗传学的信息，以了解生活在BDD中的有机体的独特特征和群落是如何进化的。研究人员将使用一套不同的方法来详细研究各种动物、植物和真菌，这些动物、植物和真菌今天生活在巴西中部这片广阔的干旱栖息地上。研究人员将评估：1)什么样的特征--如身体大小、形状或特定行为--允许一群生物在新环境中取得成功？2)新环境如何决定我们今天看到的有机体--群落？3)生物如何在基因和形态上适应这种新环境？以及4)新的特征、群落和基因变化如何相互作用，产生今天在不同环境中看到的各种有机体？对这些问题的回答将提高科学家预测不断变化的世界对生物多样性影响的能力。该项目将通过聘请来自美国和巴西的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中的数百个性状和谱系，以确定哪些性状预测进化成功-干旱适应物种经历进化多样化的趋势。然后，该项目将使用社区系统发育学方法来了解功能特征变异是如何在BDD中分布的，并将确定在今天BDD中观察到的特定社区中观察到的特征值的进化模式和过度或过度分散，以及特征是如何在栖息地梯度中过滤的。最后，该项目使用了各种基因组技术，包括全基因组测序和转录组学，以了解与生活在邻近中生代生物群中的近亲相比，生物如何适应BDD更干旱的生境。通过将特征、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，并呈现其起源和进化的全面肖像。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.