Mind the gap: reconciling tropical forest carbon flux estimates from earth observation and national reporting requires transparency.

BACKGROUND: The application of different approaches calculating the anthropogenic carbon net flux from land, leads to estimates that vary considerably. One reason for these variations is the extent to which approaches consider forest land to be "managed" by humans, and thus contributing to the net anthropogenic flux. Global Earth Observation (EO) datasets characterising spatio-temporal changes in land cover and carbon stocks provide an independent and consistent approach to estimate forest carbon fluxes. These can be compared against results reported in National Greenhouse Gas Inventories (NGHGIs) to support accurate and timely measuring, reporting and verification (MRV). Using Brazil as a primary case study, with additional analysis in Indonesia and Malaysia, we compare a Global EO-based dataset of forest carbon fluxes to results reported in NGHGIs. RESULTS: Between 2001 and 2020, the EO-derived estimates of all forest-related emissions and removals indicate that Brazil was a net sink of carbon (- 0.2 GtCO2yr-1), while Brazil's NGHGI reported a net carbon source (+ 0.8 GtCO2yr-1). After adjusting the EO estimate to use the Brazilian NGHGI definition of managed forest and other assumptions used in the inventory's methodology, the EO net flux became a source of + 0.6 GtCO2yr-1, comparable to the NGHGI. Remaining discrepancies are due largely to differing carbon removal factors and forest types applied in the two datasets. In Indonesia, the EO and NGHGI net flux estimates were similar (+ 0.6 GtCO2 yr-1), but in Malaysia, they differed in both magnitude and sign (NGHGI: -0.2 GtCO2 yr-1; Global EO: + 0.2 GtCO2 yr-1). Spatially explicit datasets on forest types were not publicly available for analysis from either NGHGI, limiting the possibility of detailed adjustments. CONCLUSIONS: By adjusting the EO dataset to improve comparability with carbon fluxes estimated for managed forests in the Brazilian NGHGI, initially diverging estimates were largely reconciled and remaining differences can be explained. Despite limited spatial data available for Indonesia and Malaysia, our comparison indicated specific aspects where differing approaches may explain divergence, including uncertainties and inaccuracies. Our study highlights the importance of enhanced transparency, as set out by the Paris Agreement, to enable alignment between different approaches for independent measuring and verification.

Differences in Wildlife Roadkill Related to Landscape Fragmentation in Central Brazil.

The interaction between animal movement and roads is pervasive, but little is known of the effects of the land-use patterns in roadside landscapes on roadkill events. Here, we compared wildlife roadkill along two road stretches that cross landscapes with different land-use patterns, including the presence of protected areas in Central Brazil. Sampling was conducted in 2017 and 2018 in two seasons (dry and rainy). We expected roadkill events to be more frequent bordering the protected area. Roadkill occurred more frequently in the rainy season in the unprotected landscape. Birds were most frequently recorded in the unprotected (44%, n = 76) than in the protected landscape (37%, n = 48). The least recorded group in the unprotected landscape was Squamata (11%, n = 18), while mammals were less detected in the protected landscape (14%, n = 18). Classes 'agriculture' and 'savanna' were related to amphibian roadkill numbers. For Squamata, we observed the effect of the presence of forests in the protected landscape. Bird roadkill was affected by protection level, while the presence of pasture and the level of protection explained mammal roadkill. Differences in roadkill patterns reinforce the need for long-term management of this source of mortality for the Cerrado fauna.

Space Use and Movement of a Neotropical Top Predator: The Endangered Jaguar.

Accurately estimating home range and understanding movement behavior can provide important information on ecological processes. Advances in data collection and analysis have improved our ability to estimate home range and movement parameters, both of which have the potential to impact species conservation. Fitting continuous-time movement model to data and incorporating the autocorrelated kernel density estimator (AKDE), we investigated range residency of forty-four jaguars fit with GPS collars across five biomes in Brazil and Argentina. We assessed home range and movement parameters of range resident animals and compared AKDE estimates with kernel density estimates (KDE). We accounted for differential space use and movement among individuals, sex, region, and habitat quality. Thirty-three (80%) of collared jaguars were range resident. Home range estimates using AKDE were 1.02 to 4.80 times larger than KDE estimates that did not consider autocorrelation. Males exhibited larger home ranges, more directional movement paths, and a trend towards larger distances traveled per day. Jaguars with the largest home ranges occupied the Atlantic Forest, a biome with high levels of deforestation and high human population density. Our results fill a gap in the knowledge of the species' ecology with an aim towards better conservation of this endangered/critically endangered carnivore-the top predator in the Neotropics.