Soil macrofaunal biodiversity in Amazonian pastures: Matching sampling with patterns

Soil biodiversity varies through space as influenced by habitat features and land-use history. The performance of any sampling strategy highly depends on its relevance with regards to this pattern. We surveyed the soil macrofaunal species richness in the pastures of the Benfica Field Station (Eastern Amazonia, State of Pará, Brazil) and described its variability in 4 independent replicate plots. We designed a within-plot sampling scheme that accounted for the soil spatial variation (stratified sampling). Replicated pasture plots had different species richness (49–65) corresponding to a low proportion (40–53%) of the total number of species (123). Pairs of replicated plots showed an outstandingly low number of shared species (28–41% of the species pool). Likewise, different classes of soil thickness, corresponding to a Ferralsol–Cambisol sequence, had different species richness (12–44) and exhibited a very low proportion of shared species (15–29%). The proportion of rare species, i.e. singletons, ranged from 40–51% of the total species richness depending on the plot considered. We used the abundance-based coverage estimator of species richness (ACE) and the Chao shared species estimator that provides a correction based on the relative abundance of rare species. These indices also showed both a high between plots dissimilarity and a substantial within plot variability of species composition. Because of the high proportion of rare species, the rarefaction curves failed to reach any asymptote in all replicated plots. Bootstrap resampling showed that less than 5 samples per stratum (class of soil thickness) provided inconsistent species richness values. We simulated the efficiency of sampling strategies that included our 4 replicate plots and the 3 classes of soil thickness but with varying sampling effort within each stratum. The results indicated that a fairly large (74%) proportion of species would be recorded if strata were sampled using 5 sampling units (hence 15 samples per plot for a total of 4×15=60 samples). This study showed the need for adequate plot replication in soil macrofaunal biodiversity studies. Also, the main relevant factors of within-replicate plot spatial heterogeneity (e.g. soil, vegetation) should be accounted for through stratified sampling. The results showed that there is no way of reducing the local sampling effort below a certain level (here, 5 sampling units per stratum).