Environmental changes are worrying in a scenario with large knowledge gaps on species diversity and distribution. Many species may become extinct before they are known to science. Considering this scenario, the present study aims to evaluate the known distribution of the species recorded for Maranhão state in Brazilian northeast region and discuss knowledge gaps about Odonata indicating the priority areas for faunistic inventories. Using primary and secondary data together, we present convex minimum polygons of the distribution of all the species registered for the state. In addition, we created maps with the richness of species and number of records of Odonata in the Maranhão state. In primary data sample 269 specimens, represented by 17 genera and 30 species were collected. Of the 30 species collected, 17 are new records for the state of Maranhão; of these, 35.29% are geographically widespread species, occurring in practically all regions of Brazil. Considering the records in the literature, there was a 68% increase in the number of Odonata species known for Maranhão. The most unexplored region is the Cerrado of the state of Maranhão. Furthermore, the transition regions between Cerrado and Amazônia and between Cerrado and Caatinga are also unknown. All these areas are a priority for faunistic inventories.

The odonates are insects that have a wide range of reproductive, ritualized territorial, and aggressive behaviors. Changes in behavior are the first response of most odonate species to environmental alterations. In this context, the primary objective of the present study was to assess the effects of environmental alterations resulting from shifts in land use on different aspects of the behavioral diversity of adult odonates. Fieldwork was conducted at 92 low-order streams in two different regions of the Brazilian Amazon. To address our main objective, we measured 29 abiotic variables at each stream, together with five morphological and five behavioral traits of the resident odonates. The results indicate a loss of behaviors at sites impacted by anthropogenic changes, as well as variation in some morphological/behavioral traits under specific environmental conditions. We highlight the importance of considering behavioral traits in the development of conservation strategies, given that species with a unique behavioral repertoire may suffer specific types of extinction pressure.

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In community ecology, it is important to understand the distribution of communities along environmental and spatial gradients. However, it is common for the residuals of models investigating those relationships to be very high (> 50%). It is believed that species’ intrinsic characteristics such as rarity can contribute to large residuals. The objective of this study is to test the relationship among communities and environmental and spatial predictors by evaluating the relative contribution of common and rare species to the explanatory power of models. Our hypothesis is that the residual of partition the variation of community matrix (varpart) models will decrease as rare species get removed. We used several environmental variables and spatial filters as varpart model predictors of fish and Zygoptera (Insecta: Odonata) communities in 109 and 141 Amazonian streams, respectively. We built a repetition structure, in which we gradually removed common and rare species independently. After the repetitions and removal of species, our hypothesis was not corroborated. In all scenarios, removing up to 50% of rare species did not reduce model residuals. Common species are important and rare species are irrelevant for understanding the relationships among communities and environmental and spatial gradients using varpart. Therefore, our findings suggest that studies using varpart with single sampling events that do not detect rare species can efficiently assess general distributional patterns of communities along environmental and spatial gradients. However, when the objectives concern conservation of biodiversity and functional diversity, rare species must be carefully assessed by other complementary methods, since they are not well represented in varpart models.