Are narrow-ranging species doomed to extinction? Projected dramatic decline in future climate suitability of two highly threatened species

Abstract

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.

Here be dragons: important spatial uncertainty driven by climate data in forecasted distribution of an endangered insular reptile

“…This method is highly relevant for conservation purposes since it provides a spatially explicit map of the most consistently identified suitable areas but prevents from disentangling the sources of uncertainty. A possible approach to assess each source of uncertainty while accounting for spatial information is the use of overlap metrics such as Pearson's coefficient or similarity indices (Muscatello, Elith, & Kujala, 2020;Dubos, Montfort, et al, 2021). To date, no study has tested for potential differences in uncertainty assessments between these approaches.…”

“…Both gas emission scenarios and GCMs can produce highly heterogeneous results in terms of predicted future distributions (Buisson et al, 2010; Baker et al, 2016). Most predictive studies included a range of scenarios and GCMs, but very few have considered potential uncertainties related to baseline climate data (Baker et al, 2016; Morales-Barbero & Vega-Álvarez, 2019; Datta, Schweiger, & Kühn, 2020; Ocon, 2020; Dubos, et al, 2021). This can induce a risk of misidentification of suitable environments, which can affect conservation prioritisation (Kujala et al, 2013; Baker et al, 2016; Muscatello, Elith, & Kujala, 2020) and subsequently lead to ineffective conservation actions (Converse & Sipe, 2021).…”

“…To date, very few studies have focused on the potential effects of climate change on the future of Reunion Island’s biodiversity (but see Legrand et al, 2016). Dubos et al (2021) predicted the potential extinction of the endemic Reunion Island reptile, P. inexpectata , driven by climate change.…”