No abstract

The effect of future climate change is poorly studied in the tropics, especially in mountainous areas, yet species living in these environments are predicted to be strongly affected. Newly available high‐resolution environmental data and statistical methods enable the development of forecasting models, but the uncertainty related to climate models can be strong, which can lead to ineffective conservation actions. Predictive studies aimed at providing conservation guidelines often account for a range of future climate predictions (climate scenarios and global circulation models). However, very few studies consider potential differences related to the source of climate data and/or do not account for spatial information (overlap) in uncertainty assessments. We modelled the environmental suitability for Phelsuma borbonica, an endangered reptile native to Reunion Island. Using two metrics of species range change (difference in overall suitability and spatial overlap), we quantified the uncertainty related to the modelling technique (n = 10), sample bias correction, climate change scenario, global circulation models (GCM) and data source (CHELSA vs. Worldclim). Uncertainty was mainly driven by GCMs when considering overall suitability, while for spatial overlap, the uncertainty related to data source became more important than that of GCMs. The uncertainty driven by sample bias correction and variable selection was much higher when assessed based on the spatial overlap. The modelling technique was a strong driver of uncertainty in both cases. We provide a consensus ensemble prediction map of the environmental suitability of P. borbonica to identify the areas predicted to be the most suitable in the future with the highest certainty. Predictive studies aimed at identifying priority areas for conservation in the face of climate change need to account for a wide panel of modelling techniques, GCMs and data sources. We recommend the use of multiple approaches, including spatial overlap when assessing uncertainty in species distribution models.

The effect of future climate change is poorly documented in the tropics, especially in mountainous areas. Yet, species living in these environments are predicted to be strongly affected. Newly available high-resolution environmental data and statistical methods enable the development of forecasting models. Nevertheless, the uncertainty related to climate models can be strong, which can lead to ineffective conservation actions. Predicted studies aimed at providing conservation guidelines often account for a range of future climate predictions (climate scenarios and global circulation models). However, very few studies considered potential differences related to baseline climate data and/or did not account for spatial information (overlap) in uncertainty assessments. We modelled the environmental suitability for Phelsuma borbonica, an endangered reptile native to Reunion Island. Using two metrics of species range change (difference in overall suitability and spatial overlap), we quantified the uncertainty related to the modelling technique (n = 10), sample bias correction, climate change scenario, global circulation models (GCM) and baseline climate (CHELSA versus Worldclim). Uncertainty was mainly driven by GCMs when considering overall suitability, while for spatial overlap the uncertainty related to baseline climate became more important than that of GCMs. The uncertainty driven by sample bias correction and variable selection was much higher when assessed based on spatial overlap. The modelling technique was a strong driver of uncertainty in both cases. We eventually provide a consensus ensemble prediction map of the environmental suitability of P. borbonica to identify the areas predicted to be the most suitable in the future with the highest certainty. Predictive studies aimed at identifying priority areas for conservation in the face of climate change need to account for a wide panel of modelling techniques, GCMs and baseline climate data. We recommend the use of multiple approaches, including spatial overlap, when assessing uncertainty in species distribution models.

First reports of envenoming by South American water snakes Helicops angulatus and Hydrops triangularis from Bolivian Amazon: a one-year prospective study of non-front-fanged colubroid snakebites. Toxicon. 2021;202:53-9. 8. da Silva AM, Mendes VKDG, Monteiro WM, Bernarde PS. Non-venomous snakebites in the Western Brazilian Amazon. Rev Soc Bras Med Trop. 2019;52:e20190120. 9. Ministry of Health of Brazil. How is Brazil taking care of tourists' health? Available at: https://bvsms.saude.gov.br/ bvs/publicacoes/como_cuidar_saude_brasil_ingles.pdf. Accessed July 20, 2021. 10. de Medeiros CR, Duarte MR, de Souza SN. Differential diagnosis between venomous (Bothrops jararaca, Serpentes, Viperidae) and "Nonvenomous" (Philodryas olfersii, Serpentes, Dipsadidae) snakebites: is it always possible?

Narrow-ranging species are usually omitted from Species distribution models (SDMs) due to statistical constraints, which may be problematic in conservation planning. The recently available high-resolution climate and land use data enable to increase the eligibility of narrow-ranging species for SDMs, provided their distribution is well known. We modelled the distribution of two narrow-ranging species for which the distribution of their occurrence records is assumed to be nearly comprehensive and unbiased (i.e., the Critically Endangered Manapany day gecko Phelsuma inexpectata and the Endangered golden Mantella frog Mantella aurantiaca). We predict a dramatic decline in climate suitability in the whole current distribution area of both species by 2070, potentially leading to a complete extinction even in the most optimistic scenario. 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. We propose to consider the use of spatially explicit guidelines for translocation and habitat restoration in order to leave the species a chance to adapt and persist. The effect of climate change remains understudied for the extreme majority of rare and highly threatened species. This study suggests that the level of threats of data-poor and narrow-ranging species already identified as threatened may be underestimated, especially in heterogeneous tropical environments. We stress the need to consider the option of implementing proactive actions for threatened narrow-ranging species.