[Ecological indicators of habitat and biodiversity in a Neotropical landscape: multitaxonomic perspective]

Abstract

Ecological indicators of habitat and biodiversity in a Neotropical landscape: multitaxonomic perspective. The use of indicator species to characterize specific ecological areas is of high importance in conservation/restoration biology. The objective of this study was to identify indicator species of diverse taxa that characterize different landscape units, and to better understand how management alters species composition. We identified two ecomosaics, tropical rain forest and the agricultural matrix, each one comprised of four landscape units. The taxonomic groups studied included birds (highly mobile), butterflies (moderately mobile), terrestrial gastropods (less mobile) and trees (sessile). Sampling efficiency for both ecomosaics was > or = 86%. We found 50 mollusks, 74 butterflies, 218 birds and 172 tree species, for a total of 514 species. Using ordination and cluster analysis, we distinguished three habitat types in the landscape: tropical rainforest, secondary vegetation and pastures with scattered trees and live fences. The InVal (> or = 50%) method identified 107 indicator species, including 45 tree species, 38 birds, 14 butterflies and 10 gastropods. Of these, 35 trees, 10 birds, four butterflies and eight gastropods were forest indicators. Additionally, 10, 28, 10 and two species, respectively per group, were characteristic of the agricultural matrix. Our results revealed a pattern of diversity decrease of indicator species along the rainforest-secondary forest-pasture gradient. In the forest, the gastropods Carychium exiguum, Coelocentrum turris, Glyphyalinia aff. indentata y Helicina oweniana were significantly correlated (p < 0.05) with 90% of the other groups of flora and fauna indicator species. These findings suggest that gastropods may be good indicators of forest habitat quality and biodiversity. The secondary vegetation is an intermediate disturbance phase that fosters high diversity in the agricultural matrix. We exemplify a multitaxa approach, including mesofauna, for ecological monitoring of agricultural landscapes.