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Understanding community assembly across altitudinal gradients in the tropics: can functional trait variation explain diversity-maintenance mechanisms?

Grant number: 16/00757-2
Support type:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): May 02, 2016
Effective date (End): August 01, 2016
Field of knowledge:Biological Sciences - Ecology - Theoretical Ecology
Principal researcher:Thiago Sanna Freire Silva
Grantee:Annia Susin Streher
Supervisor abroad: Brian McGill
Home Institution: Instituto de Geociências e Ciências Exatas (IGCE). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil
Research place: University of Maine, United States  
Associated to the scholarship:15/17534-3 - Abiotic and biotic drivers of species diversity across an elevation gradient: an optical trait-based approach for testing ecological theories, BP.DR


Recent functional trait studies have shown that trait differences may favor certain species (environmental filtering), while simultaneously preventing competitive exclusion (niche partitioning). In light of current ecological theories, we will seek to understand two central questions in community ecology: (i) Are assembly mechanisms similar across elevations, and/or between woody and herbaceous assemblages? (ii) Are trait variation patterns related to coexistence -competitive interactions at low altitudes and abiotic filtering at high altitudes? To answer these questions, we will look first at the similarity of mean trait variance across elevations, while also searching for the main environmental drivers related to the observed variations. The nature of assembly patterns will be tested based on the assumption that high functional similarity is a signature of abiotic filtering, while low functional similarity is a signature of biotic interactions. In the proposal "Abiotic and biotic drivers of species diversity across an elevation gradient: an optical trait-based approach for testing ecological theories" we propose a complete assessment of the applicability of hyperspectral data and drones to unravel the mechanisms underlying plant community assembly patterns across a tropical elevation gradient at Serra do Cipó, Brazil. To fully realize the potential of the technologies used in the proposed project, hyperspectral data must be combined with sound ecological theory, linking structural, physiological and phenological traits based on resource constraints. Therefore, proper and comprehensive understanding of the potential and limitations of trait-based approaches are essential for the formulation of strong testable hypotheses and for the experimental and analytical planning required to teste these hypotheses. Under the scientific framework of the proposed thesis project, this internship will allow us to test often-cited but rarely-tested modern theories on the origins and maintenance of diversity gradients in the tropics, in terms of variation in the functional diversity of community patterns. We expect to reach a better understanding on how community traits are distributed across gradients, in the light of niche theory, revealing mechanisms and patterns that can be used to predict the effects of environmental change on ecosystem structure and functioning. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
STREHER, ANNIA SUSIN; TORRES, RICARDO DA SILVA; CERDEIRA MORELLATO, LEONOR PATRICIA; FREIRE SILVA, THIAGO SANNA. Accuracy and limitations for spectroscopic prediction of leaf traits in seasonally dry tropical environments. REMOTE SENSING OF ENVIRONMENT, v. 244, JUL 2020. Web of Science Citations: 0.
STREHER, ANNIA SUSIN; FERREIRA SOBREIRO, JOAO FRANCISCO; CERDEIRA MORELLATO, LEONOR PATRICIA; FREIRE SILVA, THIAGO SANNA. Land Surface Phenology in the Tropics: The Role of Climate and Topography in a Snow-Free Mountain. ECOSYSTEMS, v. 20, n. 8, p. 1436-1453, DEC 2017. Web of Science Citations: 7.

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