Abstract
The ability of ecological niche models (ENMs) to produce robust predictions for different time frames (i.e. temporal transferability) may be hindered by a lack of ecologically relevant predictors. Model performance may also be affected by species traits, which may reflect different responses to processes controlling species distribution. In this study, we tested four primary hypotheses involving the role of species traits and environmental predictors in ENM performance and transferability. We compared the predictive accuracy of ENMs based upon (1) climate, (2) land-use/cover (LULC) and (3) ecosystem functional attributes (EFAs), and (4) the combination of these factors for 27 bird species within and beyond the time frame of model calibration. The combination of these factors significantly increased both model performance and transferability, highlighting the need to integrate climate, LULC and EFAs to improve biodiversity projections. However, the overall model transferability was low (being only acceptable for less than 25% of species), even under a hierarchical modelling approach, which calls for great caution in the use of ENMs to predict bird distributions under global change scenarios. Our findings also indicate that positive effects of species traits on predictive accuracy within model calibration are not necessarily translated into higher temporal transferability.
Highlights
Ecological niche models (ENMs) based on correlative species-environment relationships are widely used to assess the impact of past and future global change on biodiversity[1,2]
The effects of species traits[35] on the predictive ability of ecological niche models (ENMs) were found to override any differences in modelling technique, as these traits may reflect the different responses of species to processes that control species distributions[36]
The gradual integration of information derived from ENMs based upon the different sets of predictors substantially increased model performance, both within (AUCmean up to 0.98; Fig. 3; ΣWPRED = 0.99; Table 3) and beyond (Fig. 3; ΣWPRED = 0.98; see ‘Internal TT’ in Table 3; ΣWPRED = 0.99; see ‘TT External’ in Table 3) the calibration time frame
Summary
Ecological niche models (ENMs) based on correlative species-environment relationships are widely used to assess the impact of past and future global change on biodiversity[1,2]. New research on how the integration of key environmental drivers affects the transferability of ENMs is urgently needed given the increasing consensus on the importance of addressing the combined impacts of future climate and land-use/cover changes on biodiversity[19,20,21]. In this regard, the incorporation of less common but important predictors is increasingly feasible, as remote sensing data are more readily available[22]. A recent study highlighted that the predictive ability of ENMs differs with regard to life history characteristics such as range, migration, habitat and rarity of a species[40]
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