RESUMEN
In species-rich tropical forests, effective biodiversity management demands measures of progress, yet budgetary limitations typically constrain capacity of decision makers to assess response of biological communities to habitat change. One approach is to identify ecological-disturbance indicator species (EDIS) whose monitoring is also monetarily cost-effective. These species can be identified by determining individual species' responses to disturbance across a gradient; however, such responses may be confounded by factors other than disturbance. For example, in mountain environments the effects of anthropogenic habitat alteration are commonly confounded by elevation. EDIS have been identified with the indicator value (IndVal) metric, but there are weaknesses in the application of this approach in complex montane systems. We surveyed birds, small mammals, bats, and leaf-litter lizards in differentially disturbed cloud forest of the Ecuadorian Andes. We then incorporated elevation in generalized linear (mixed) models (GL(M)M) to screen for EDIS in the data set. Finally, we used rarefaction of species accumulation data to compare relative monetary costs of identifying and monitoring EDIS at equal sampling effort, based on species richness. Our GL(M)M generated greater numbers of EDIS but fewer characteristic species relative to IndVal. In absolute terms birds were the most cost-effective of the 4 taxa surveyed. We found one low-cost bird EDIS. In terms of the number of indicators generated as a proportion of species richness, EDIS of small mammals were the most cost-effective. Our approach has the potential to be a useful tool for facilitating more sustainable management of Andean forest systems.
