Dimensions US-BIOTA-Sao Paulo: Collaborative Proposal: Traits as predictors of adaptive diversification along the Brazilian Dry Diagonal
Dimensions US-BIOTA-Sao Paulo: Collaborative Proposal: Traits as predictors of adaptive diversification along the Brazilian Dry Diagonal
批准号:
1831322
负责人:
Kelly Zamudio
金额:
$40.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2022-07-31
中文摘要
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英文摘要
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.
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