Stochastic species loss and dispersal limitation drive patterns of spatial and temporal beta diversity of fish assemblages in tropical agroecosystem streams

• Autor(a) principal: Zeni, Jaquelini O. [UNESP]
• Data de Publicação: 2020
• Outros Autores: Hoeinghaus, David J., Roa-Fuentes, Camilo A., Casatti, Lilian [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1007/s10750-020-04356-1; http://hdl.handle.net/11449/201982
• topic: Dispersal limitation; Historical environmental filters; Nestedness; Temporal dissimilarity; Turnover

Beta diversity quantifies changes in assemblages among sites and can identify how anthropogenic changes affect species distributions patterns. We investigated how spatial and temporal beta diversity of fish assemblages responded to recent environmental changes within an established agroecosystem and investigated whether the observed pattern of spatial and temporal beta diversity was different from null expectations. Fish assemblages in 38 streams were sampled in 2003 and 2013, and local and regional variables were quantified in both periods. Species were classified into functional groups based on 15 ecomorphological traits. We tested for relationships between spatial and temporal patterns of beta diversity and its components (turnover and nestedness) and environmental distances and degree of changes over time, and for differences with null expectations. Spatial beta diversity was mostly due to turnover and remained relatively unchanged between periods. Spatial beta diversity was not different from randomness. Temporal beta diversity was lower than expected by null models and not correlated with environmental changes. Past environmental filters related to a long history of agricultural development homogenized habitats and fish assemblages by selecting for habitat-generalist species. In this context, contemporary fish assemblage dynamics in these streams are driven primarily by stochastic processes, likely stochastic local species loss.