Cost-efficiency of Subsampling Protocols to Evaluate Oribatid-Mite Communities in an Amazonian Savanna

Sampling oribatid mites in large areas using conventional methods is expensive, time-consuming, and this constrains their use in environmental monitoring programs. We used samples collected in 38 plots of 3.75 ha spread over 30,000 ha in an Amazonian savanna to evaluate the reduction in costs and person-hours in sampling and sorting and to elaborate cost-effective protocols. Ten samples per plot were collected and extracted using a Berlese-Tullgren apparatus. In the laboratory, samples were reduced to 50, 25, 12.5, and 6.25 percent of the initial content. Field-effort reduction was estimated by reducing the number of subsamples per plot. Dissimilarity matrices were generated using Bray-Curtis, Sorensen, and Chao-Sorensen indices. Correlations between each reduced-effort dissimilarity matrix and 100 or 50 percent sorting were used as an index of how much information was retained in reduced-effort sampling, and could still be used in multivariate analyses. The effects of most predictor variables on mite composition were detected in data based on every level of sample reduction. The intensive sampling was insufficient to reveal the full oribatid-mite fauna in the savanna; as more plots were sampled, more species were recorded. Our data indicate subsampling protocols for biodiversity assessment of oribatid mites in savanna that increase field and laboratory efficiency, and optimize both taxonomic and ecological aspects of the investigation.