Comparing taxon- and trait-environment relationships in stream communities

• Autor(a) principal: Saito, Victor Satoru
• Data de Publicação: 2020
• Outros Autores: Siqueira, Tadeu [UNESP], Bini, Luis Mauricio, Costa-Pereira, Raul, Santos, Edineusa Pereira [UNESP], Pavoine, Sandrine
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.ecolind.2020.106625; http://hdl.handle.net/11449/199012
• topic: Community weighted mean; Distance-based redundancy analysis; Mayflies; Species trait; Trait-environment relationship; Tropical streams

Traits define how organisms interact with their surrounding environment and with other organisms. Thus, trait composition of biological communities is expected to change predictably along environmental gradients. Because organisms’ traits, but not taxonomic identity, determine their fitness, trait-environment relationships should provide a better way to elucidate how biodiversity respond to environmental change. Here, we used data on tropical streams embedded in a landscape of intensive agriculture to investigate trait-environment and taxon-environment relationships in a set of 91 mayfly communities from southeastern Brazil. We expected that trait-environment relationships would be stronger than taxon-environment relationships and that the linkage between traits and environmental variables would provide mechanistic insights on environmental filtering. We found that variation in both species composition and traits were correlated to salinity, highlighting the influence of water salinization on mayfly communities due to agricultural practices. Surprisingly, using analogous statistical methods, in general, we found that the strengths of trait-environment relationships were lower than that of taxon-environment relationships. Further, (1) species responses to gradients were not correlated to similarity in their traits and (2) some species with different trait composition responded similarly to environmental variation, indicating that different suite of traits can cope with similar environmental contexts. Besides some cautionary results about trait-based approaches, results from taxon-based approaches indicated that variation in composition was more related to spatial variables, suggesting that dispersal limitation undermine its use for large scale assessments. Our results suggest that both taxon- and trait-based approaches have weakness and strengths and deciding between them for biomonitoring purposes will depend on spatial scales, trait interrelationships, and analytical methods.