Spatial scenario of tropical deforestation and carbon emissions for the 21^stcentury

Abstract

Tropical forests are disappearing at an alarming rate due to human activities. Here, we provide spatial models of deforestation in 92 countries covering all the tropical moist forests in the world. Our models confirm the effectiveness of protected areas in displacing deforestation and the negative impact of roads and landscape fragmentation on forest conservation in the tropics. Using our models, we derive high-resolution pantropical maps of the deforestation risk and future forest cover for the 21st century under a ''business-as-usual'' scenario based on the deforestation rates observed in the 2010s. Although under this scenario, large areas of tropical moist forest should remain in the heart of the Amazon, in the Congo Basin, and in New Guinea in 2100, 48% (39–56%) of all forest cover is expected to disappear during the course of the 21st century, and many countries will have lost all their forests by 2100. The remaining forests will be highly fragmented and located in remote places. As future deforestation will concern forests with higher aboveground carbon stocks, annual carbon emissions associated with tropical deforestation are expected to increase by +0.161 Pg/yr (+35%) between the 2010s and the 2090s.

Estimation of land cover changes and biomass carbon stock in north-eastern hill forests of Bangladesh

“…According to Pearson et al (2017), land use change, including deforestation, emitted 1.3 ± 0.7 Gt(C)•yr -1 , with timber collection accounting for 53%, fuelwood harvesting accounting for 30%, and forest fires accounting for 17%. Tropical deforestation is expected to increase from 0.467 Pg•yr -1 in the 2010s to 0.628 Pg•yr -1 in the 2090s (+35%), making tropical forests a major carbon source in the 21 st century (Vieilledent et al 2022).…”

Fragmentation is the Main Driver of Residual Forest Aboveground Biomass in West African Low Forest-High Deforestation Landscapes

“…The terrain relief and topography were extracted from a 30-m resolution Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (Farr et al, 2007;Jarvis et al, 2008). From the DEM, we derived three primary variables: elevation, slope, aspect, and proximity to watercourses (Vieilledent et al, 2022).…”

“…This index is the ratio of the standard deviation of the monthly total precipitation to the mean monthly total precipitation (also known as the coefficient of variation) and is expressed as a percentage. CV therefore captures the dispersion in relative terms because standard deviation can produce two similar values while the means may be different (Vieilledent et al, 2022)…”

Deep Species Distribution Modeling From Sentinel-2 Image Time-Series: A Global Scale Analysis on the Orchid Family

“…Finally, including additional information that predicts the likely presence and extinction risk of species are other promising directions: species traits (Bourhis et al, 2023), ecosystem functional attributes (Arenas-Castro et al, 2018) and other threat/habitat rasters such as urban expansion forecasts, forest cover predictions or protected areas (Borgelt et al, 2022;Vieilledent et al, 2022). Indeed, the inclusion of climate change alone inevitably leads to an underestimation of future threats to biodiversity (Brook et al, 2009).…”