Biodiversity conservation has faced many challenges, especially the conversion of natural areas that compete with use for agriculture, energy production and mineral extraction. This problem is further aggravated by lack of knowledge of the biodiversity that exists and the geographical distribution of different groups. The objectives of our study were to examine the distributional pattern of Gerromorpha diversity in Brazil, create a map of conservation priority areas, estimate the degree of protection that the current network of protected areas guarantees to this insect group, and identify the size thresholds in geographical distributions that would allow species to be protected. We used species occurrences from the Water Bugs Distributional Database, and we used 19 bioclimatic variables to build models of the potential distributions of species using the MaxEnt program. Using the potential model results, we calculated diversity metrics and overlapped them with the current state and federal “conservation units” (protected areas for biodiversity) in Brazil. Total beta diversity and turnover portions were separated into two faunistic groups, one in northern and the other in southern Brazil. The Amazon has higher beta diversity than what was predicted by the null models. We detected a positive relationship between species distribution area and occurrence in conservation units. Conservation units with less than 250 km²do not protect Gerromorpha species. Our results reinforce the necessity of formulating new conservation strategies for this group, contemplating species with both restricted and ample distributions, because rare and specialist species are the most harmed by habitat reduction, given that they are more sensitive to environmental disturbance.

An important aspect of conservation is to understand the founding elements and characteristics of metacommunities in natural environments, and the consequences of anthropogenic disturbance on these patterns. In natural Amazonian environments, the interfluves of the major rivers play an important role in the formation of areas of endemism through the historical isolation of species and the speciation process. We evaluated elements of metacommunity structure for Zygoptera (Insecta: Odonata) sampled in 93 Amazonian streams distributed in two distinct biogeographic regions (areas of endemism). Of sampled streams, 43 were considered to have experienced negligible anthropogenic impacts, and 50 were considered impacted by anthropogenic activities. Our hypothesis was that preserved (“negligible impact”) streams would present a Clementsian pattern, forming clusters of distinct species, reflecting the biogeographic pattern of the two regions, and that anthropogenic streams would present random patterns of metacommunity, due to the loss of more sensitive species and dominance of more tolerant species, which have higher dispersal ability and environmental tolerance. In negligible impact streams, the Clementsian pattern reflected a strong biogeographic pattern, which we discuss considering the areas of endemism of Amazonian rivers. As for communities in human‐impacted streams, a biotic homogenization was evident, in which rare species were suppressed and the most common species had become hyper‐dominant. Understanding the mechanisms that trigger changes in metacommunities is an important issue for conservation, because they can help create mitigation measures for the impacts of anthropogenic activities on biological communities, and so should be expanded to studies using other taxonomic groups in both tropical and temperate systems, and, wherever possible, at multiple spatial scales.

Substrate complexity is strongly related to biodiversity in aquatic habitats. We illustrate a novel framework, based on Structure-from-Motion photogrammetry (SfM) and Multi-View Stereo (MVS) photogrammetry, to quantify habitat complexity in freshwater ecosystems from Unmanned Aerial Vehicle (UAV) and underwater photography. We analysed sites in the Xingu river basin, Brazil, to reconstruct the 3D structure of the substrate and identify and map habitat classes important for maintaining fish assemblage biodiversity. From the digital models we calculated habitat complexity metrics including rugosity, slope and 3D fractal dimension. The UAV based SfM-MVS products were generated at a ground sampling distance (GSD) of 1.20–2.38 cm while the underwater photography produced a GSD of 1 mm. Our results show how these products provide spatially explicit complexity metrics, which are more comprehensive than conventional arbitrary cross sections. Shallow neural network classification of SfM-MVS products of substrate exposed in the dry season resulted in high accuracies across classes. UAV and underwater SfM-MVS is robust for quantifying freshwater habitat classes and complexity and should be chosen whenever possible over conventional methods (e.g., chain-and-tape) because of the repeatability, scalability and multi-dimensional nature of the products. The SfM-MVS products can be used to identify high priority freshwater sectors for conservation, species occurrences and diversity studies to provide a broader indication for overall fish species diversity and provide repeatability for monitoring change over time.

Riparian vegetation plays an important role in providing energy to small watercourses and maintaining ecological processes through organic matter input and together with hydrological and geomorphological watercourse characteristics influence on fish assemblages. The goal of this paper was partitioning and quantifying the influence of riparian zone (type of riverbank substrate, bank slope, type of riparian vegetation cover and percentage of riparian vegetation cover on the main channel), physical habitat (stream channel width and depth, type of substrate and aquatic habitat in channel, water velocity and organic matter), water quality (turbidity, temperature, conductivity, pH, dissolved oxygen and chlorophyll concentration) and spatial variables (linear distances between sampled points) on fish assemblages (richness and abundance per species) in headwater streams of the Upper Paraná River basin, Central Brazil. For this purpose, it was performed a variation partitioning analysis between riparian, physical habitat, water and spatial variables sets and a Redundancy Analysis to quantify the influence of variables on the fish assemblages. Only the physical habitat and water quality variables influenced the fish assemblages (richness and abundance per species).