Biogeographic knowledge of Amazonian amphibians presents significant challenges in spatial and temporal coverage, as well as in the taxonomic refinement of their diversity. Despite recent advances, the spatial distribution of sampling and detailed taxonomic knowledge remain limited, potentially causing biases in our understanding of their diversity and distribution. In this study, we conducted a large-scale analysis using an extensive database with 951 species and 213,072 georeferenced occurrence records, distributed across 24,319 sampling points in the Amazon. This analysis aimed to elucidate potential drivers of sampling biases for Amazonian amphibians in the presence of infrastructure factors (cities, hydroelectric dams, and transmission lines) and accessibility (navigable rivers and roads). Among accessibility factors, we found that rivers were the main facilitators in amphibian sampling. On the other hand, roads did not exert a strong influence as expected, due to the late and limited development of land transportation in the region, which has historically been dominated by river transportation. Among the infrastructure factors, both cities and hydroelectric plants had a moderate influence on sampling. The reason for this is that most cities in the Amazon region were established a few decades ago and have limited infrastructure, especially considering the presence of consolidated research centers. Hydroelectric plants have generated extensive databases due to environmental legislation requirements for their installation, but restricted access to information from these reports limited their use in this study. We conclude that Amazonian amphibian sampling exhibits significant geographic bias, attributable to the uneven distribution of research efforts caused by logistical challenges, including accessibility and infrastructure limitations. Overcoming these obstacles requires coordinated efforts between researchers and decision-makers, as well as investment in research infrastructure and data dissemination initiatives, not only for amphibians, but for all biodiversity in the face of increasing deforestation and climate change.

In this study, we sought to understand how the Linnean shortfall (i.e., the lack of knowledge about species taxonomy) interacts with the Darwinian shortfall (i.e., the lack of knowledge about phylogenetic relationships among species), potentially jeopardizing geographical patterns in estimates of speciation rates, using New World coralsnakes as a case study. For this purpose, we created an index of taxonomic uncertainty that measures the likelihood of current species being split after undergoing future taxonomic revisions. Next, we conducted simulations in which branches of species with high taxonomic uncertainty are split in the phylogenetic trees to generate new hypothetical species along their geographic ranges. We found that a high number of coralsnake species display substantial taxonomic uncertainty, positively correlated with the latitude of the species’ geographical range centroid. The estimated speciation rates based on currently available data have a weak relationship with latitude. However, after incorporating taxonomic uncertainty into the phylogeny, we detect a higher positive correlation between speciation rate and latitude. This shift demonstrates that taxonomic uncertainty can undermine empirical evaluation of the geographical pattern estimates in speciation rates, revealing an interaction between the latitudinal taxonomic gradient and the latitudinal diversity gradient. Given that taxonomic changes can alter the number of species recognized as valid over time, our study highlights the need to incorporate taxonomic uncertainty into macroecological and macroevolutionary studies, enhancing the robustness of patterns inferred from these data.

Understanding how bird species from white sand ecosystems (WSEs) have managed to inhabit and specialize in insular environment in the middle of the Amazon Rainforest is fundamental to understand the evolutionary processes in birds restricted to one type of habitat. We sought to evaluate the diversification processes of the specialist bird species of the white sand ecosystems of the Rio Negro basin by comparing them with the pool of bird species of riparian environments. Many WSEs may be ancient riverbeds, which may favor current riparian species to be potential colonizers and settle within the WSEs. For this, we used an extension of biogeographic evolutionary models to verify state-dependent speciation and extinction models that specifically explain the presence of unmeasured factors that can affect the estimated diversification rates for the states of any observed trait. Thus, it was possible to evaluate the evolutionary processes that most acted in the formation of bird communities of WSEs. The results showed that WSEs specialist bird species have different functional diversity to what was expected on a random basis and evolutionary models have higher extinction and speciation rates in WSEs specialist bird communities. This evidences that source-sink processes maintain WSEs over time, and that they receive generalist and specialist species from riparian ecosystems. According to the models analyzed, once the species have the high degree of adaptation required by an ecosystem with severe conditions, they cannot colonize other ecosystems. Extinction is an important process for the dynamics of biodiversity in the Amazon since, as many species are lost, there is also speciation and high adaptation. This work is one of the first to use local evolutionary analyses in Amazonian ecosystems and was effective in showing that extinction is recurrent, which is a cause for concern due to the severe and rapid ecological changes currently occurring.