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Multimetric Indices (MMIs) have been widely applied for ecological assessment in freshwater ecosystems. Most MMIs face difficulties when scaling up from small spatial scales because larger scales usually encompass great environmental variability. Covariance of anthropogenic pressures with natural environmental gradients can be a confounding factor in assessing biologic responses to anthropogenic pressures. This study presents the development and validation of a predictive multimetric index to assess the ecological condition of Atlantic Forest wadeable streams using benthic macroinvertebrates. To do so, we sampled 158 sites for the index development. We adjusted each biological metric to natural variation through multiple regression analyses (stepwise-forward) and considered that the residual distribution describes the metric variation in the absence of natural environmental influence. For metric selection we considered normal distribution, variation explained by the models, redundancy between metrics and sensitivity to differentiate reference from impaired sites. We selected five metrics to the final index: total richness, %MOLD, %Coleoptera, EPT richness and Chironomidae abundance. The residuals were transformed into probabilities and the final index was obtained through the mean of these probabilities. This index performed well in discriminating the impairment gradient and it showed a high correlation (r = 0.85, p <0.001) with a specific index developed for a particular basin indicating a similar sensitivity. This index can be used to assess wadeable streams ecological condition in Atlantic Forest biome, so we believe that this type of approach represents an important step towards the application of biomonitoring tools in Brazil.

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Strongyloidiasis is an intestinal parasitic infection of the nematodeStrongyloides, 1 which is a parasite of animals in both free-living conditions and captivity. 2,3 The species S. fuelleborni and S. cebus are parasites of Old and New World primates, respectively. Human infections of S. stercolaris are frequent, but zoonotic or anthropozoonotic infections can also occur. 4 Among Old World primates, Erythrocebus patas have shown histopathological lesions caused by S. stercoralis manifesting as disseminated hyperinfection, severe necrotizing duodenitis, colitis, and pulmonary hemorrhage. 5 Among Neotropical primates, pot-bellied Lagothrix cana monkeys have shown severe Strongyloides infections manifesting as hemorrhage and lesions in the lung, duodenum, and jejunum with mucosal erosion, and presence of larvae. 6 This infection occurs by penetration of the filarioid larvae through feet or hands, reaching derma, and subsequently, lymphatic and blood circulation. It can also occur through ingestion of water and food contaminated with filarioid larvae.In Strongyloides infections, third-stage self-infecting larvae can promote severe hyperinfection resulting from the exacerbation of the autoinfection cycle, manifesting with diarrhea, malabsorption, and acute enteritis in primates. 6 This infection can accelerate pathological processes that are already established, such as wasting marmoset syndrome (WMS), and can lead to quick death, particularly in babies of non-human primates. The aim of this study was to describe the anatomopathological aspects of disseminated strongyloidiasis in three captive callitrichids.

Benthic macroinvertebrates Functional Feeding Group (FFG) have been used to determine aquatic assemblage dynamics and as a biomonitoring tool. The main goals of this study were to assess the effects of stream variables on the abundance and richness of FFGs and evaluate ecosystem attributes (FFG ratios) as a tool to assess ecological conditions of Atlantic Rainforest streams. We sampled 146 sites with different impairment conditions in Rio de Janeiro, Brazil. Richness was significantly different among impairment conditions for all FFGs. Mixed-effect models show that aquatic macroinvertebrate FFGs differed in their responses to abiotic variables for abundance and richness. Also, they were reduced in the impaired sites when compared to intermediate and reference sites. The FFG ratio indicated significant differences along the impairment gradient. The FFG ratio analysis was shown to be a fast and cheap tool that can be used for monitoring aquatic ecosystems in the Atlantic Forest biome. However, further studies are required to calibrate the method specifically for the Atlantic Forest region.

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Biological assessments that use the reference condition approach are based on the concept of comparing a site's observed biology to sites where disturbance is minimal or absent. However, in many regions of the world, such areas are scarce or nonexistent. In this study, an alternative approach proposed by Chessman and Royal for bioassessment without reference areas based on environmental filters was tested in Brazil. This approach assumes that key environmental features act in the selection of potential colonists, from a regional pool of taxa, based on the ecological traits (tolerances) possessed by each taxon. We developed the approach by: 1) determining the regional pool, based on a large Atlantic Forest biome database; 2) selecting environmental filters (elevation, original vegetation and soil type); and 3) including information on the tolerance and preferences of aquatic insects to these filters. With this information we were able to determine the expected taxon under natural conditions and compare with observed taxon, developing a predictive index (Observed/Expected). Although the model was intended to predict the fauna in regions without reference sites, we included reference areas to test the model responsiveness, precision and sensitivity. Our results indicated that the index was able to discriminate impairment classes (F=56.9; p<0,001), it has high precision due to low standard deviation across reference sites values (SD=0.098) and high sensitivity due the correlation with environmental variables that are sensitive to human alteration (r=0.74, p<0.01). Also, it was strongly correlated with multimetric indices developed for multiple watersheds in the state, showing agreement between the methods in relation to ecological quality classification. Even though the predictive index had performed well in our study, we make some considerations that may help to improve its sensitivity of similar methods that are being tested using the environmental filters approach.

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