Abstract
Our limited understanding of the complexity of nature generates uncertainty in mathematical and cartographical models used to predict the effects of climate change on species’ distributions. We developed predictive models of distributional range shifts of threatened vertebrate species in mainland Spain, and in their accumulation in biodiversity hotspots due to climate change. We considered two relevant sources of climatological uncertainty that affect predictions of future climate: general circulation models and socio–economic scenarios. We also examined the relative importance of climate as a driver of species’ distribution and taxonomic uncertainty as additional biogeographical causes of uncertainty. Uncertainty was detected in all the forecasts derived from models in which climate was a significant explanatory factor, and in the species with taxonomic uncertainty. Uncertainty in forecasts was mainly located in areas not occupied by the species, and increased with time difference from the present. Mapping this uncertainty allowed us to assess the consistency of predictions regarding future changes in the distribution of hotspots of threatened vertebrates in Spain.
Highlights
Species distribution modelling (SDM) is useful to forecast the potential consequences of climate change on conservation of biodiversity (Dawson et al, 2011)
We considered four sources of uncertainty associated with future forecasts: (1) two alternative general circulation models (GCMs): CGCM2 (Canadian Climate Centre for Modeling and Analysis) and ECHAM4 (Max Planck Institut für Meteorologie) (IPCC, 2013), regionalized to Spain by the Spanish Meteorological Agency (AEMET) (Brunet et al, 2007); (2) two different Gas–Emission Scenarios or gas–emission scenarios (GESs) for the 21st century from IPCC, (Nakićenović et al, 2000): A2 and B2, representing intermediate positions in the range of projected temperature changes, being medium–high and medium–low respectively (Brunet et al, 2007); (3) the degree to which climate affects distribution models, as a consequence of correlations between climate and other factors
Climate had different degrees of influence depending on the species and the general circulation models (GCMs) and gas–emission scenarios (GES) analysed, but the relative contribution of climate was responsible for the largest differences between forecasts
Summary
Species distribution modelling (SDM) is useful to forecast the potential consequences of climate change on conservation of biodiversity (Dawson et al, 2011). Few studies have assessed the effects of taxonomic uncertainty (Lozier et al, 2009; Romero et al, 2013; McInerny and Purves, 2011; Tessarolo et al, 2017), diversity of sources for climate data (Fernández et al, 2013; García–López and Real, 2014), behavioural plasticity of species in their response to climate change (Muñoz et al, 2015), correlations between climate, and other environmental factors (Real et al, 2013) These causes of uncertainty can affect model accuracy more than the availability of GCMs and GESs
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