Análise cienciométrica e macroecologica de padrões de diversidade

Abstract

The amount of biodiversity information gathered by naturalists for centuries has motivated questions about species’ origin and distribution. In the 21th century, the rise of big data and new technologies have made possible to execute exhaustive statistical analyses on Macroecology. Recent efforts on gathering global data have not been sufficient to surpass biases and gaps. This incompleteness has serious consequences on conservation and ecological understanding, therefore it is of major importance to map, quantify and describe these flaws. The processes underlying the global biodiversity structure have been extensively investigated throughout the world and for decades. However, the biodiversity patterns are still not well understood. In the last few years some hypotheses explored different biological resolutions and tried to resume the processes that results in biodiversity patterns in some few or even only one variable. In this context, this work aimed to map and characterize the literature hotspots concerning biodiversity patterns, to assess inventory incompleteness for the Atlantic Rainforest – concerning amphibians, birds, mammals and reptiles –, and investigate if some environmental variables are correlated to biodiversity knowledge. Moreover, the richness patterns for terrestrial vertebrates of the Atlantic Forest were described and the influence of four environmental variables in their distribution were tested using Pearson’s correlation, linear models and Geographically Weighted Regression (GWR). The results suggest that there are a few gaps in the current literature about biodiversity patterns, once only a few countries and biomes have been largely explored and used as reference. Also, the Atlantic Forest fauna is not well known, with clusters of quality information near big conservation centres. Environmental variables commonly referred to as indicators of species richness were not correlated to inventory completeness. Richness patterns in this region are similarly arranged in space and the environmental variables were not correlated to species richness. GWR analyses showed that congruency between groups’ species richness are not uniform. We conclude that the latitudinal biodiversity pattern is not a multi-scale global tendency and that temperature, PET, NDVI and topography are not determinants of species richness or inventory completeness in this biome.