The Amazon is the primary source of Neotropical diversity and a nexus for discussions on processes that drive biotic diversification. Biogeographers have focused on the roles of rivers and Pleistocene climate change in explaining high rates of speciation. We combine phylogeographic and niche-based paleodistributional projections for 23 upland terra firme forest bird lineages from across the Amazon to derive a new model of regional biological diversification. We found that climate-driven refugial dynamics interact with dynamic riverine barriers to produce a dominant pattern: Older lineages in the wetter western and northern parts of the Amazon gave rise to lineages in the drier southern and eastern parts. This climate/drainage basin evolution interaction links landscape dynamics with biotic diversification and explains the east-west diversity gradients across the Amazon.

The ongoing decline in abundance and diversity of shark stocks, primarily due to uncontrolled fishery exploitation, is a worldwide problem. An additional problem for the development of conservation and management programmes is the identification of species diversity within a given area, given the morphological similarities among shark species, and the typical disembarkation of processed carcasses which are almost impossible to differentiate. The main aim of the present study was to identify those shark species being exploited off northern Brazil, by using the 12S-16S molecular marker. For this, DNA sequences were obtained from 122 specimens collected on the docks and the fish market in Bragança, in the Brazilian state of Pará. We identified at least 11 species. Three-quarters of the specimens collected were either Carcharhinus porosus or Rhizoprionodon sp, while a notable absence was the daggernose shark, Isogomphodon oxyrhyncus, previously one of the most common species in local catches. The study emphasises the value of molecular techniques for the identification of cryptic shark species, and the potential of the 12S-16S marker as a tool for phylogenetic inferences in a study of elasmobranchs.

Despite the widespread use of ecological niche models (ENMs) for predicting the responses of species to climate change, these models do not explicitly incorporate any population‐level mechanism. On the other hand, mechanistic models adding population processes (e.g. biotic interactions, dispersal and adaptive potential to abiotic conditions) are much more complex and difficult to parameterize, especially if the goal is to predict range shifts for many species simultaneously. In particular, the adaptive potential (based on genetic adaptations, phenotypic plasticity and behavioral adjustments for physiological responses) of local populations has been a less studied mechanism affecting species’ responses to climatic change so far. Here, we discuss and apply an alternative macroecological framework to evaluate the potential role of evolutionary rescue under climate change based on ENMs. We begin by reviewing eco‐evolutionary models that evaluate the maximum sustainable evolutionary rate under a scenario of environmental change, showing how they can be used to understand the impact of temperature change on a Neotropical anuran species, the Schneider's toad Rhinella diptycha. Then we show how to evaluate spatial patterns of species’ geographic range shift using such models, by estimating evolutionary rates at the trailing edge of species distribution estimated by ENMs and by recalculating the relative amount of total range loss under climate change. We show how different models can reduce the expected range loss predicted for the studied species by potential ecophysiological adaptations in some regions of the trailing edge predicted by ENMs. For general applications, we believe that parameters for large numbers of species and populations can be obtained from macroecological generalizations (e.g. allometric equations and ecogeographical rules), so our framework coupling ENMs with eco‐evolutionary models can be applied to achieve a more accurate picture of potential impacts from climate change and other threats to biodiversity.

The genus Xiphorhynchus is a species rich avian group widely distributed in Neotropical forests of Central and South America. Although recent molecular studies have improved our understanding of the spatial patterns of genetic diversity in some species of this genus, most are still poorly known, including their taxonomy. Here, we address the historical diversification and phylogenetic relationships of the X. guttatus/susurrans complex, using data from two mitochondrial (cyt b and ND2) and one nuclear (β-fibint7) genes. Phylogenetic relationships were inferred with both gene trees and a Bayesian-based species tree under a coalescent framework (∗BEAST). With exception of the nuclear β-fibint7 gene that produced an unresolved tree, both mtDNA and the species tree showed a similar topology and were congruent in recovering five main clades with high statistical support. These clades, however, are not fully concordant with traditional delimitation of some X. guttatus subspecies, since X. g. polystictus, X. g. guttatus, and X. g. connectens are not supported as distinct clades. Interestingly, these three taxa are more closely related to the mostly trans-Andean X. susurrans than the other southern and western Amazonian subspecies of X. guttatus, which constitutes a paraphyletic species. Timing estimates based on the species tree indicated that diversification in X. guttatus occurred between the end of the Pliocene and early Pleistocene, likely associated with the formation of the modern Amazon River and its main southern tributaries (Xingu, Tocantins, and Madeira), in addition to climate-induced changes in the distribution of rainforest biomes. Our study supports with an enlarged dataset a previous proposal for recognizing at least three species level taxa in the X. guttatus/susurrans complex: X. susurrans, X. guttatus, and X. guttatoides.

No abstract

Land-use land-cover (LULC) data are important predictors of species occurrence and biodiversity threat. Although there are LULC datasets available for ecologists under current conditions, there is a lack of such data under historical and future climatic conditions. This hinders, for example, projecting niche and distribution models under global change scenarios at different times. The Land Use Harmonization Project (LUH2) is a global terrestrial dataset at 0.25o spatial resolution that provides LULC data from 850 to 2300 for 12 LULC state classes. The dataset, however, is compressed in a file format (NetCDF) that is incompatible with most ecological analysis and intractable for most ecologists. Here we selected and transformed the LUH2 data in order to make it more useful for ecological studies. We provide LULC for every year from 850 to 2100, with data from 2015 on provided under two Shared Socioeconomic Pathways (SSP2 and SSP5). We provide two types of file for each year: separate files with continuous values for each of the 12 LULC state classes, and a single categorical file with all state classes combined. To create the categorical layer, we assigned the state with the highest value in a given pixel among the 12 continuous data. The final dataset provides LULC data for 1251 years that will be of interest for macroecology, ecological niche modeling, global change analysis, and other applications in ecology and conservation. We also provide a description of LUH2 prediction of future LULC change through time.

No abstract

Land-use land-cover (LULC) data are important predictors of species occurrence and biodiversity threat. Although there are LULC datasets available for ecologists under current conditions, there is a lack of such data under historical and future climatic conditions. This hinders, for example, projecting niche and distribution models under global change scenarios at different times. The Land Use Harmonization Project (LUH2) is a global terrestrial dataset at 0.25° spatial resolution that provides LULC data from 850 to 2300 for 12 LULC state classes. The dataset, however, is compressed in a file format (NetCDF) that is incompatible with most ecological analysis and intractable for most ecologists. Here we selected and transformed the LUH2 data in order to make it more useful for ecological studies. We provide LULC for every year from 850 to 2100, with data from 2015 on provided under two Shared Socioeconomic Pathways (SSP2 and SSP5). We provide two types of file for each year: separate files with continuous values for each of the 12 LULC state classes, and a single categorical file with all state classes combined. To create the categorical layer, we assigned the state with the highest value in a given pixel among the 12 continuous data. The final dataset provides LULC data for 1251 years that will be of interest for macroecology, ecological niche modeling, global change analysis, and other applications in ecology and conservation. We also provide a description of LUH2 prediction of future LULC change through time.