The dominant mesopredator and savanna formations shape the distribution of the rare northern tiger cat (Leopardus tigrinus) in the Amazon.

Understanding the distribution patterns of threatened species is central to conservation. The Amazonian distribution of the northern tiger cat (N-tiger cat, Leopardus tigrinus) and its interspecific relationship with the ocelot, its potential intraguild killer, are intriguing. Here, we combined presence/absence records with species distribution models (SDMs) to determine N-tiger cat occurrence in the Amazon. We also modeled ocelot density from 46 published estimates. The N-tiger cat's presence in the Amazon was negatively influenced by ocelot density and net primary productivity and positively influenced by savannas and precipitation in the driest month. The best-fitting model predicted highly patchy N-tiger cat occurrence over an area of 236,238.67 km2, almost exclusively in savanna enclaves. Additionally, 312,348 camera trap-days at 49 sites in the Amazon revealed no N-tiger cats. The ocelot densities were significantly higher in areas with denser vegetation cover and warmer habitats, with predicted densities ≥ 0.6 ind/km2 throughout most of the biome. The lowest ocelot densities (≤ 0.06 ind/km2) were observed along the predicted range of N-tiger cats. Our findings highlight that the N-tiger cat's presence in the Amazon is restricted to savannas and highly influenced by ocelot density, emphasizing the importance of including species interactions in SDMs.

Wild dogs at stake: deforestation threatens the only Amazon endemic canid, the short-eared dog (Atelocynus microtis).

The persistent high deforestation rate and fragmentation of the Amazon forests are the main threats to their biodiversity. To anticipate and mitigate these threats, it is important to understand and predict how species respond to the rapidly changing landscape. The short-eared dog Atelocynus microtis is the only Amazon-endemic canid and one of the most understudied wild dogs worldwide. We investigated short-eared dog habitat associations on two spatial scales. First, we used the largest record database ever compiled for short-eared dogs in combination with species distribution models to map species habitat suitability, estimate its distribution range and predict shifts in species distribution in response to predicted deforestation across the entire Amazon (regional scale). Second, we used systematic camera trap surveys and occupancy models to investigate how forest cover and forest fragmentation affect the space use of this species in the Southern Brazilian Amazon (local scale). Species distribution models suggested that the short-eared dog potentially occurs over an extensive and continuous area, through most of the Amazon region south of the Amazon River. However, approximately 30% of the short-eared dog's current distribution is expected to be lost or suffer sharp declines in habitat suitability by 2027 (within three generations) due to forest loss. This proportion might reach 40% of the species distribution in unprotected areas and exceed 60% in some interfluves (i.e. portions of land separated by large rivers) of the Amazon basin. Our local-scale analysis indicated that the presence of forest positively affected short-eared dog space use, while the density of forest edges had a negative effect. Beyond shedding light on the ecology of the short-eared dog and refining its distribution range, our results stress that forest loss poses a serious threat to the conservation of the species in a short time frame. Hence, we propose a re-assessment of the short-eared dog's current IUCN Red List status (Near Threatened) based on findings presented here. Our study exemplifies how data can be integrated across sources and modelling procedures to improve our knowledge of relatively understudied species.

ATLANTIC BIRD TRAITS: a data set of bird morphological traits from the Atlantic forests of South America.

Scientists have long been trying to understand why the Neotropical region holds the highest diversity of birds on Earth. Recently, there has been increased interest in morphological variation between and within species, and in how climate, topography, and anthropogenic pressures may explain and affect phenotypic variation. Because morphological data are not always available for many species at the local or regional scale, we are limited in our understanding of intra- and interspecies spatial morphological variation. Here, we present the ATLANTIC BIRD TRAITS, a data set that includes measurements of up to 44 morphological traits in 67,197 bird records from 2,790 populations distributed throughout the Atlantic forests of South America. This data set comprises information, compiled over two centuries (1820-2018), for 711 bird species, which represent 80% of all known bird diversity in the Atlantic Forest. Among the most commonly reported traits are sex (n = 65,717), age (n = 63,852), body mass (n = 58,768), flight molt presence (n = 44,941), molt presence (n = 44,847), body molt presence (n = 44,606), tail length (n = 43,005), reproductive stage (n = 42,588), bill length (n = 37,409), body length (n = 28,394), right wing length (n = 21,950), tarsus length (n = 20,342), and wing length (n = 18,071). The most frequently recorded species are Chiroxiphia caudata (n = 1,837), Turdus albicollis (n = 1,658), Trichothraupis melanops (n = 1,468), Turdus leucomelas (n = 1,436), and Basileuterus culicivorus (n = 1,384). The species recorded in the greatest number of sampling localities are Basileuterus culicivorus (n = 243), Trichothraupis melanops (n = 242), Chiroxiphia caudata (n = 210), Platyrinchus mystaceus (n = 208), and Turdus rufiventris (n = 191). ATLANTIC BIRD TRAITS (ABT) is the most comprehensive data set on measurements of bird morphological traits found in a biodiversity hotspot; it provides data for basic and applied research at multiple scales, from individual to community, and from the local to the macroecological perspectives. No copyright or proprietary restrictions are associated with the use of this data set. Please cite this data paper when the data are used in publications or teaching and educational activities.