A Vanishing Imprint? Modeling the Present and Future Distribution of the Enigmatic Quercus crenata Lam., a Mediterranean Sporadic Tree Species

正在消失的印记?地中海零星分布树种——神秘的栎树(Quercus crenata Lam.)的当前和未来分布模型

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Abstract

Poorly known, rare species are important biodiversity elements; understanding the relationships between their effective numbers, geographical distribution, ecology, and adaptive potential is an unquestionable critical aspect to reverse biodiversity decline under climate change. Quercus crenata Lam. is a sporadic Mediterranean tree species with debated taxonomy and evolutionary history. Confusing identifications and a scattered distribution combine to create an incautious lack of comprehensive and reliable information on its spatial distribution, ecology, and genetic resources, thereby hindering correct management and conservation efforts. This work undertook a first decisive step to address these knowledge gaps, integrating all previous dispersive information and presenting a comprehensive map of Q. crenata occurrences, with 923 established records: 495 new field observations and 428 verified from all available literature and online databases. The taxon occurs with extremely low individual numbers across central and northern Italy, southern France, western Slovenia, and Croatia, mainly at altitudes between sea level and 1100 m a.s.l. A large part of the species records are outside current networks of protected areas. The MaxEnt-based distribution model highlights Q. crenata adaptation to mild Mediterranean climates with moderate temperature fluctuations, moderate-to-high water requirements, and diverse soil types. A broader present potential distribution than currently assessed is suggested, underlining the possibility of identifying new occurrences with accurate searches in targeted sites, thus refining the understanding of the species' actual present distribution. Future range projections under three carbon emission scenarios with increasing severity (SSP1, SSP3, and SSP5) predict substantial range losses by 2100, ranging from 32% to a drastic 99% reduction under the most severe scenario (SSP5). On these bases, our findings underline the urgent need to improve current conservation practices, which should be conveniently implemented by exhaustive genetic investigations.

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