Spatial autocorrelation in a Mexican dung beetle ensemble: Implications for biodiversity assessment and monitoring

Abstract

Spatial autocorrelation is a general property of ecological variables. Since many of the statistical methods used in ecology often assume sample independence, spatial clustering is considered a source of noise in studies related to the estimation and monitoring of biological diversity. Spatial autocorrelation was assessed herein in a Mexican Scarabaeinae dung beetle ensemble. Dung beetles where sampled using 1,240 pitfall traps baited with human feces. Response variables such as Hill numbers and abundance (number of individuals by trap) were analyzed using the Moran’s I. A total of 3,198 dung beetles were collected, belonging to 67 species. Sample coverage suggested that the dung beetle survey was close to capture the true diversity of the ensemble, providing robust statistical inferences for subsequent analyses. All the ensemble level metrics (species richness, Shannon-Wiener diversity, Simpson diversity and abundance) were spatially autocorrelated. The species level analyses suggested that the number of individuals for 22 Scarabaeinae species was spatially clustered, while 33 dung beetle species were randomly distributed. Therefore, the patterns of spatial autocorrelation at ensemble level are suggested to mask the inherent patterns of autocorrelation of the individual species. Since spatial clustering in dung beetles is thought to be promoted by several dung beetle individuals co-occurring to exploit similar food resources, the bait type used to collect Scarabaeinae is proposed to have a considerable influence on the patterns of spatial autocorrelation. Consequently, trap spacing design could be irrelevant to ensure the avoidance of spatial autocorrelation in Scarabaeinae, while the use of methodologies that guarantee adequate representation of the different trophic guilds of Scarabaeinae could be of greater importance for biodiversity assessment and monitoring.