2022
DOI: 10.1111/gcb.16072
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Spatial heterogeneity and temporal stability characterize future climatic refugia in Mediterranean Europe

Abstract: Identifying areas where species that are most exposed to climate change will occur in forthcoming decades has become a priority for conservation planning (Carroll et al., 2017;Heller et al., 2015;Wang et al., 2018). The dynamically shifting climate is a major parameter driving the global redistribution of biodiversity, and is expected to force many species out of current reserves, jeopardizing the efficiency of the present, static network of protected areas (PAs), which were established to halt biodiversity de… Show more

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Cited by 18 publications
(14 citation statements)
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“…Shabani et al (2016) showed how the type of SDM can considerably influence the projections of modelled habitat for Australian plants. Nevertheless, we found pockets of consensus in climatically suitable habitat around the Great Lakes for a number of species (areas in green and yellow in the consensus maps, Figure 3), indicating a potential for climate refugia (see also Doxa et al, 2022; Stralberg et al, 2018). Overall, using a variety of SDMs and RCPs can highlight areas of uncertainty and areas of consensus, information that is critical for conservation planning and forest management moving forward.…”
Section: Discussionmentioning
confidence: 77%
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“…Shabani et al (2016) showed how the type of SDM can considerably influence the projections of modelled habitat for Australian plants. Nevertheless, we found pockets of consensus in climatically suitable habitat around the Great Lakes for a number of species (areas in green and yellow in the consensus maps, Figure 3), indicating a potential for climate refugia (see also Doxa et al, 2022; Stralberg et al, 2018). Overall, using a variety of SDMs and RCPs can highlight areas of uncertainty and areas of consensus, information that is critical for conservation planning and forest management moving forward.…”
Section: Discussionmentioning
confidence: 77%
“…To identify areas of agreement in climatic suitability/unsuitability for a given RCP model, we mapped areas of consensus in climatically suitable habitat by RCP (RCP4.5, RCP8.5) to highlight how SDM choice influenced model outputs. Moreover, to identify possible climatic refugia (Doxa et al, 2022; Saraiva et al, 2021), we overlaid the outputs of the four simulations to highlight areas of consensus in climatic suitability/unsuitability across all SDM × RCP model combinations. From here, for each cell, we calculated the number of climatically suitable simulations (values ranging from 0—i.e.…”
Section: Methodsmentioning
confidence: 99%
“…Still, suggesting that the latter is climatically more stable could be an artifact, as biological, biochemical, and oceanographic processes could degrade at much higher rates than in the first case. Thus areas where both biological and climatic criteria predict climatic stability may be perceived as low regret priority areas, where the primary focus should be given when designing a climate‐smart network (Brito‐Morales et al, 2022; Doxa et al, 2022).…”
Section: Discussionmentioning
confidence: 99%
“…Based on previous studies that suggested using an observed variation measure (for ex. SD) as the climatic analog threshold (Doxa et al, 2022; García Molinos et al, 2017), we estimated cell‐specific analog thresholds based on historical local climate variability, as the means to define conditions that deviate from historical and current climate. These cell‐specific thresholds may mirror biological relevant information as species may not tolerate climatic extremes that exceed previously observed climatic variability at each site (García Molinos et al, 2017).…”
Section: Methodsmentioning
confidence: 99%
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