Stream-dwelling anuran metacommunity structure and dynamics in the Atlantic Rainforest: a hierarchical approach that accounts for species imperfect detection

Abstract

The metacommunity approach has provided new insights about processes that drive community structure by considering that beyond local interactions like intraspecific, interspecific, and species-environment relations, processes that occur at broader scales (e.g., dispersal) also drive the assembly of local communities. However, until now metacommunity empirical studies surprisingly neglected detection error of species, which can generate biased patterns and reduce model explanatory power. Thus, the overall objective of this thesis proposal is to investigate community assembly of stream-dwelling anurans in the Atlantic Rainforest by using hierarchical multi-species occupancy models that account for imperfect detection. Two models are stated in the hierarchical modeling approach: one for parameters that are usually the main focus (e.g., beta diversity and species occurrence), but cannot be observed directly, and another model for directly observed data that is related with ecological parameters of interest, but is influenced and biased by methodology and sampling error. More specifically, we intend to: I) evaluate that amount of variation in local community composition that can be explained by environmental and spatial processes; II) evaluate that amount of variation in beta diversity that that can be explained by environmental and spatial processes; III) investigate which metacommunity pattern best fit the observed patterns; IV) model variation in species richness as a function of both environmental and spatial co-variables. Taking into account for detection error by hierarchical modeling, we will generate more accurate models to disentangle sampling noise from ecological parameters of interest. Thus, we expect to increase the amount of explained variation in our statistics models. (AU)