When phylogeny and ecology meet: Modeling the occurrence of Trichoptera with environmental and phylogenetic data.

Autor: Godoy BS; Núcleo de Ciências Agrárias e Desenvolvimento Rural Univ Federal do Pará Belém Brazil., Camargos LM; Departament of Entomology Univ of Minnesota Saint Paul MN USA., Lodi S; Programa de Pós-Graduação em Ecologia e Evolução Univ Federal de Goiás Goiânia Brazil.
Jazyk: angličtina
Zdroj: Ecology and evolution [Ecol Evol] 2018 May 08; Vol. 8 (11), pp. 5313-5322. Date of Electronic Publication: 2018 May 08 (Print Publication: 2018).
DOI: 10.1002/ece3.4031
Abstrakt: Ecological studies are increasingly considering phylogenetic relationships among species. The phylogeny is used as a proxy or filter to improve statistical tests and retain evolutionary elements, such as niche conservation. We used the phylogenetic topology to improve the model for occurrence of Trichoptera genera in Cerrado (Brazilian Savanna) streams. We tested whether parameters generated by logistic models of occurrence, using phylogenetic signals, are better than models generated without phylogenetic information. We used a model with Bayesian updating to examine the influence of stream water pH and phylogenetic relationship among genera on the occurrence of Trichoptera genera. Then, we compared this model with the logistic model for each Trichoptera genus. The probability of occurrence of most genera increased with water pH, and the phylogeny-based explicit logistic model improved the parameters estimated for observed genera. The inferred relationship between genera occurrence and stream pH improved, indicating that phylogeny adds relevant information when estimating ecological responses of organisms. Water with elevated acidity (low pH values) may be restrictive for the occurrence of Trichoptera larvae, especially if the regional streams exhibit neutral to alkaline water, as is observed in the Cerrado region. Using phylogeny-based modeling to predict species occurrence is a prominent opportunity to extend our current statistical framework based on environmental conditions, as it enables a more precise estimation of ecological parameters.
Databáze: MEDLINE