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

Abstract

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 847 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.

Concordance between macroinvertebrate communities and the typological classification of white and clear-water streams in Western Brazilian Amazonia

“…First, our findings agree with previous studies that found associations between the distribution patterns of aquatic insects and the geographical features through which streams flow, especially where marked differences in topography or water chemistry (e.g. conductivity and pH) are found (Hawkins & Norris 2000, Roque et al 2010. Second, Amazonian stream classification based on color may reflect fundamental discontinuities of nature (e.g.…”

The taxonomic distinctness of macroinvertebrate communities of Atlantic Forest streams cannot be predicted by landscape and climate variables, but traditional biodiversity indices can

“…Thus, although we estimated both pure environmental and spatial components in variation partitioning, our main intention was to use spatial variables as a way to control for inflated Type I error in assessing the environmental component. Together with previous studies about Atlantic Forest streams, these results indicate that by using local, landscape and spatial predictors (or a combination of them), we are usually able to explain around 40% or less of the of variation in macroinvertebrate abundance and distribution (Siqueira et al, 2009), taxa associations (Roque et al, 2010), diversity metrics ), common and rare taxa (Siqueira et al, 2012b) and functional diversity metrics (Colzani et al, 2013). Recent studies have tested the performance of taxonomic diversity and taxonomic distinctness in several systems and taxonomic groups.…”

“…Moreover, studies that have examined patterns of macroinvertebrates under a variety of measures of stream conditions in relation to land use at multiple scales report mixed influences (Allan, 2004). Thus, given the absence of specific information, we consider our exploratory approach an appropriate option for our purpose of estimating the effect of landscape processes on the structure of the macroinvertebrate community (see Roque et al, 2010;Siqueira et al, 2009Siqueira et al, , 2012b for a similar approach).…”

Influence of landscape on assemblages of Chironomidae in Neotropical streams

“…In general, chironomids respond efficiently to changes in aquatic ecosystems, and their occurrence and distribution are related to the biogeochemical aspects and heterogeneity of habitats (Rosin and Takeda, 2007;Campbell et al, 2009). Chironomid assemblage have proven to be structured by landscape-level factors, such as specific land uses (Lampert and Allan, 1999;Silver et al, 2004;Kleine and Trivinho-Strixino, 2005;Hepp and Santos, 2009;Roque et al, 2010;.…”