In 2015, an emergency state was declared in Bolivia when Poopó Lake dried up. Climate variability and the increasing need for water are potential factors responsible for this situation. Because field data are missing over the region, no statements are possible about the influence of mentioned factors. This study is a preliminary step toward the understanding of Poopó Lake drought using remote sensing data. First, atmospheric corrections for Landsat (FLAASH and L8SR), seven satellite derived indexes for extracting water bodies, MOD16 evapotranspiration, PERSIANN-CDR and MSWEP rainfall products potentiality were assessed. Then, the fluctuations of Poopó Lake extent over the last 26 years are presented for the first time jointly, with the mean regional annual rainfall. Three main droughts are highlighted between 1990 and 2015: two are associated with negative annual rainfall anomalies in 1994 and 1995 and one associated with positive annual rainfall anomaly in 2015. This suggests that other factors than rainfall influenced the recent disappearance of the lake. The regional evapotranspiration increased by 12.8% between 2000 and 2014. Evapotranspiration increase is not homogeneous over the watershed but limited over the main agriculture regions. Agriculture activity is one of the major factors contributing to the regional desertification and recent disappearance of Poopó Lake.

We present an extensive investigation of a new erosion and weathering proxy derived from the ¹⁰Be(meteoric)/⁹Be(stable) ratio in the Amazon River basin. This new proxy combines a radioactive atmospheric flux tracer, meteoric cosmogenic ¹⁰Be, with ⁹Be, a trace metal released by weathering. Results show that meteoric ¹⁰Be concentrations ([¹⁰Be]) and ¹⁰Be/⁹Be ratios increase by >30% from the Andes to the lowlands. We can calculate floodplain transfer times of 2–30 kyr from this increase. Intriguingly however, the riverine exported flux of meteoric ¹⁰Be shows a deficit with respect to the atmospheric depositional ¹⁰Be flux. Most likely, the actual area from which the ¹⁰Be flux is being delivered into the mainstream is smaller than the basin‐wide one. Despite this imbalance, denudation rates calculated from ¹⁰Be/⁹Be ratios from bed load, suspended sediment, and water samples from Amazon Rivers agree within a factor of 2 with published in situ ¹⁰Be denudation rates. Erosion rates calculated from meteoric [¹⁰Be], measured from depth‐integrated suspended sediment samples, agree with denudation rates, suggesting that grain size‐induced variations in [¹⁰Be] are minimized when using such sampling material instead of bed load. In addition, the agreement between erosion and denudation rates implies minor chemical weathering intensity in most Amazon tributaries. Indeed, the Be‐specific weathering intensity, calculated from mobilized ⁹Be comprising reactive and dissolved fractions that are released during weathering, is constant at approximately 40% of the total denudation from the Andes across the lowlands to the Amazon mouth. Therefore, weathering in the Amazon floodplain is not detected.

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non‐detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non‐governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer‐reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non‐detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio‐temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large‐scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data.

This study assesses the performance of the new Global Precipitation Measurement (GPM)-based satellite precipitation estimates (SPEs) datasets in the Brazilian Central Plateau and compares it with the previous Tropical Rainfall Measurement Mission (TRMM)-era datasets. To do so, the Integrated Multi-satellitE Retrievals for GPM (IMERG)-v5 and the Global Satellite Mapping of Precipitation (GSMaP)-v7 were evaluated at their original 0.1° spatial resolution and for a 0.25° grid for comparison with TRMM Multi-satellite Precipitation Analysis (TMPA). The assessment was made on an annual, monthly, and daily basis for both wet and dry seasons. Overall, IMERG presents the best annual and monthly results. In both time steps, IMERG’s precipitation estimations present bias with lower magnitudes and smaller root-mean-square error. However, GSMaP performs slightly better for the daily time step based on categorical and quantitative statistical analysis. Both IMERG and GSMaP estimates are seasonally influenced, with the highest difficulty in estimating precipitation occurring during the dry season. Additionally, the study indicates that GPM-based SPEs products are capable of continuing TRMM-based precipitation monitoring with similar or even better accuracy than obtained previously with the widely used TMPA product.