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Narrow-ranging species are usually omitted from Species distribution models (SDMs) due to statistical constraints, while they are predicted to be particularly vulnerable to climate change. The recently available high-resolution environmental predictors, along with recently developed methods enable to increase the eligibility of narrow-ranging species for SDMs, provided their distribution is well known. We fill a gap of knowledge on the effect of predicted climate change on narrow-ranging species. We modelled the distribution of the golden mantella frog Mantella aurantiaca and the Manapany day gecko Phelsuma inexpectata, for which the distribution of their occurrence records is well documented. Our modelling scheme included a range of processes susceptible to address statistical issues related to narrow-ranging species. We predict an alarming decline in climate suitability in the whole current distribution area of both species by 2070, potentially leading to a complete extinction in most scenarios. We identified the areas with the best climate suitability in the future, but these remain largely suboptimal regarding species climatic niche. The high level of habitat fragmentation suggests that both species likely need to be at least partly translocated. Climate change may not only drive range contractions or distribution shifts in narrow-ranging species, but may lead to the complete extirpation of suitable environments across their entire region. This study suggests that the level of threats of narrow-ranging species already identified as threatened may be underestimated, especially in heterogeneous tropical areas. We stress the need to develop sampling campaigns and implement proactive actions for narrow-ranging species in the tropics.

The fragmented and complex landscape in the Miombo landscape makes it a challenge to map and disentangle the various forest change drivers (FCD) associated with these changes and relate them to other underlying drivers. To overcome these challenges, we developed a method to spatially disentangle the drivers of deforestation (smallholder and commercial agriculture, mining, and clean-cutting charcoal), forest degradation (selective charcoal production, wildfires, logging), and forest growth (abandoned land, regrowth including plantations) in the Beira corridor, in central Mozambique. We identified ten potential FCD from the literature and created two land use and land cover (LULC) maps for 2000 and 2020 to identify areas of forest change. We used stratified random sampling based on the LULC change map, visually interpreted high-resolution satellite imagery, and NDVI time series to characterise and collected observation points of the FCD. We derived several potential underlying drivers as explanatory spatial variables. We used the random forest algorithm to evaluate their relative importance and generate a map of FCD. The forest loss due to deforestation and degradation accounts for 82.8 % (38,553.1 ha year−1) and 5.2 % (2,399.1 ha year−1), respectively, while the gain due to plantations accounts for 2.8 % (1,314.4 ha year−1) and regrowth for 9.2 % (4,297 ha year−1) of the total forest change area from 2000 to 2020. Smallholder agriculture (72.2 % of the total forest change), clear-cutting charcoal (9.1 %), abandoned land (5.4 %) and regrowth (5.7 %) were the main FCD in the study area. They are explained mainly by the intensity of change, altitude, population density and proximity to the main road. The results show a satisfactory accuracy for the LULC map (overall accuracy = 88 % and F1-score = 80 % for LULC 2000 and 90 % and 88 % for LULC 2020) and for the FCD map (overall accuracy = 79 % and F1-score = 73 %). This study provides a significant improvement in quantifying FCD by using spatially explicit data. The method could help decision-makers design land use policies better and monitor their impacts.

The phenology of tropical forests is tightly related to climate conditions. In the Amazon, the seasonal greening of forests is conditioned by solar radiation and rainfall. Yet, increasing anthropogenic pressures (e.g. logging and wildfires), raise concerns about the impacts of forest degradation on the functioning of forest ecosystems, especially in a climate change context. In this study, we relied on remote sensing data to assess the contribution of solar radiation and precipitation to forest greening in mature and fire degraded forests, with a focus on the 2015 drought event. Our results showed that forest greening is more dependent on water resources in degraded forests than in mature forests. As a consequence, the expected increase in drought episodes and associated fire occurrences under climate change could lead to a long-term drying of tropical forests.