RESUMO
Chlorophyll-a (Chl-a) has been widely used in the assessment and monitoring of aquatic environments. Local and regional factors can influence Chl-a concentrations; moreover, the connection between terrestrial and aquatic ecosystems is a major paradigm within aquatic ecology. Here, we investigate the spatial distribution of Chl-a concentrations in a tropical savannah floodplain in Central Brazil using a broad spatial data set (a 900-km north-south transect; 30 lakes). We determine the relative importance of local environmental variables (limnological and morphometric) and regional (land use) and spatial distances (spatial eigenvector) on Chl-a concentrations using partial linear regression. We evaluate the direct and indirect effects of local and regional variables on Chl-a with a path analysis. Our results indicate spatially autocorrelated patterns wherein lakes in closer proximity showed more similar levels of Chl-a than more distant lakes. Local environmental factors explained most variance in Chl-a (R 2adj = 0.28; P = 0.02); more specifically, both lake area and total nitrogen significantly (P < 0.05) explained Chl-a concentrations (direct effects). Meanwhile, regional factors neither directly nor indirectly predicted Chl-a. Thus, internal processes, such as the resuspension of sediment (which is frequent in tropical floodplains), rather than external influences, were the main factors that explained Chl-a concentrations in this study. The importance of local variables in structuring Chl-a concentration may be used to guide the conservation of the aquatic ecosystems in these tropical floodplain lakes.
Assuntos
Clorofila/análise , Lagos/química , Brasil , Clorofila A , Monitoramento AmbientalRESUMO
Geographic gradients in the species richness of non-human primates have traditionally been attributed to the variation in forest productivity (related to precipitation levels), although an all-inclusive, global-scale analysis has never been conducted. We perform a more comprehensive test on the role of precipitation and biomass production and propose an alternative hypothesis - the variation in vertical structure of forest habitats as measured by forest canopy height - in determining primate species richness on a global scale. Considering the potential causal relationships among precipitation, productivity and forest structure, we arranged these variables within a path framework to assess their direct and indirect associations with the pattern of primate species richness using structural equation modelling. The analysis also accounted for the influence of spatial autocorrelation in the relationships and assessed possible historical differences among biogeographical regions. The path coefficients indicate that forest canopy height (used as a proxy for vertical forest structure) is a better predictor of primate species richness than either precipitation or productivity on both global and continental scales. The only exception was Asia, where precipitation prevailed, albeit independently from productivity or forest structure. The influence of spatially structured processes varied markedly among biogeographical regions. Our results challenge the traditional rainfall-based viewpoint in favour of forest distribution and structure as primary drivers of primate species richness, which aggregate potential effects from both climatic factors and habitat complexity. These findings may support predictions of the impact of forest removal on primate species richness.