Untangling associations between chironomid taxa in Neotropical streams using local and landscape filters

1. Analyses of species association have major implications for selecting indicators for freshwater biomonitoring and conservation, because they allow for the elimination of redundant information and focus on taxa that can be easily handled and identified. These analyses are particularly relevant in the debate about using speciose groups (such as the Chironomidae) as indicators in the tropics, because they require difficult and time‐consuming analysis, and their responses to environmental gradients, including anthropogenic stressors, are poorly known. 2. Our objective was to show whether chironomid assemblages in Neotropical streams include clear associations of taxa and, if so, how well these associations could be explained by a set of models containing information from different spatial scales. For this, we formulated a priori models that allowed for the influence of local, landscape and spatial factors on chironomid taxon associations (CTA). These models represented biological hypotheses capable of explaining associations between chironomid taxa. For instance, CTA could be best explained by local variables (e.g. pH, conductivity and water temperature) or by processes acting at wider landscape scales (e.g. percentage of forest cover). 3. Biological data were taken from 61 streams in Southeastern Brazil, 47 of which were in well‐preserved regions, and 14 of which drained areas severely affected by anthropogenic activities. We adopted a model selection procedure using Akaike’s information criterion to determine the most parsimonious models for explaining CTA. 4. Applying Kendall’s coefficient of concordance, seven genera (Tanytarsus/Caladomyia, Ablabesmyia, Parametriocnemus, Pentaneura, Nanocladius, Polypedilum and Rheotanytarsus) were identified as associated taxa. The best‐supported model explained 42.6% of the total variance in the abundance of associated taxa. This model combined local and landscape environmental filters and spatial variables (which were derived from eigenfunction analysis). However, the model with local filters and spatial variables also had a good chance of being selected as the best model. 5. Standardised partial regression coefficients of local and landscape filters, including spatial variables, derived from model averaging allowed an estimation of which variables were best correlated with the abundance of associated taxa. In general, the abundance of the associated genera tended to be lower in streams characterised by a high percentage of forest cover (landscape scale), lower proportion of muddy substrata and high values of pH and conductivity (local scale). 6. Overall, our main result adds to the increasing number of studies that have indicated the importance of local and landscape variables, as well as the spatial relationships among sampling sites, for explaining aquatic insect community patterns in streams. Furthermore, our findings open new possibilities for the elimination of redundant data in the assessment of anthropogenic impacts on tropical streams.     

Biodiversity indicators in European ground waters: towards a predictive model of stygobiotic species richness

1. Estimates of species richness obtained from exhaustive field inventories over large spatial scales are expensive and time-consuming. For this reason, efficiency demands the use of indicators as 'surrogates' of species richness. Biodiversity indicators are defined herein as a limited suite of taxonomic groups the species richness of which is correlated with the species richness of all other taxonomic groups present in the survey area.
2. Species richness in ground water was assessed at different spatial scales using data collected from six regions in Europe. In total, 375 stygobiotic species were recorded across 1157 sites and 96 aquifers. The taxonomic groups collected from more than one site and with more than two species (Oligochaeta, Gastropoda, Cyclopoida, Harpacticoida, Ostracoda, Isopoda, Amphipoda, Bathynellacea and Acari) were used to develop nonparametric models to predict stygobiotic biodiversity at the aquifer scale.
3. Pair-wise correlations between taxonomic groups were low, i.e. variation in species richness of a single taxonomic group did not usually reflect variation of the other groups. In contrast, multiple regressions calculated between species richness of any combination of taxa and extra-group species richness along the six regions resulted in a number of significant relationships.
4. These results suggest that some taxonomic groups (mainly Copepoda and Amphipoda and, to a lesser extent, Oligochaeta and Gastropoda) combined in different ways across the regions, were good biodiversity indicators in European groundwater ecosystems. However, the uneven distribution of taxonomic groups prevented selection of a common set of indicators for all six regions. Faunal differences among regions are presumably related to both historical and ecological factors, including palaeogeography, palaeoecology, geology, aquifer fragmentation and isolation, and, less clearly, anthropogenic disturbance.