Abstract
Freshwater biodiversity is showing a global decline in relation to environmental change and there is an urgent need to quantify different facets of biodiversity to assess the conservation value of freshwater ecosystems. Identifying the ecological drivers of arid and semiarid Patagonian waterbodies is a critical requirement for planning action to conserve these still poorly understood habitats. We tested the responses of alpha and beta diversity of invertebrates (presence-absence, abundance, and biomass) to local, landscape, and climatic features, in 45 Patagonian freshwater bodies classified in three groups: isolated ponds, connected ponds, and lotic systems. We first compared the invertebrate community compositions of the different waterbodies. Secondly, using a co-inertia analysis we assessed the relative roles of local, landscape and climatic factors in driving variation in assemblage composition. Finally, we compared different facets of beta diversity and modelled their responses to environmental variables (predictors), by generalized dissimilarity modelling (GDM). Unexpectedly, lotic systems with a total of 109 taxa, were richer than lentic ones, but isolated ponds contributed most to beta diversity and supported more unique and proportionally more endemic species. Alpha and beta diversity were mainly driven by local features and secondly by climatic descriptors. However, these patterns shifted according to different community composition measures. Collectively, our results suggest that isolated ponds have a higher biodiversity value and would be more vulnerable than connected ponds and lotic systems to environmental changes. However, all waterbody types contributed to gamma biodiversity, reinforcing the importance of conserving a diversity of freshwater ecosystems in any landscape and particularly in arid and semiarid Patagonia. Our findings are a first step to resolving and quantifying the amount of changes occurring in Patagonian waterbodies, and are a prerequisite for predicting changes in species distributions in the face of global change.
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