Topography, climate, land cover, and biodiversity: Explaining endemic richness and management implications on a Mediterranean island
Aristides Moustakas, Ioannis N Vogiatzakis

TL;DR
This study uses machine learning to identify key environmental factors influencing endemic plant richness on Crete, highlighting the importance of topography and climate for conservation planning.
Contribution
It quantifies the relative importance of topography, climate, and land cover in shaping endemic richness using neural networks, providing a novel framework for island conservation strategies.
Findings
Elevation range and climatic variability are key predictors of endemic richness.
Endemic hotspots only partially overlap with total species richness areas.
Prioritizing mountainous, climatically variable regions benefits conservation and ecosystem services.
Abstract
Island endemism is shaped by complex interactions among environmental, ecological, and evolutionary factors, yet the relative contributions of topography, climate, and land cover remain incompletely quantified. We investigated the drivers of endemic plant richness across Crete, a Mediterranean biodiversity hotspot, using spatially explicit data on species distributions, topographic complexity, climatic variability, land cover, and soil characteristics. Artificial Neural Network models, a machine learning tool, were employed to assess the relative importance of these predictors and to identify hotspots of endemism. We found that total species richness, elevation range, and climatic variability were the strongest predictors of endemic richness, reflecting the role of biodiversity, topographic heterogeneity, and climatic gradients in generating diverse habitats and micro-refugia that…
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Taxonomy
TopicsSpecies Distribution and Climate Change · Ecology and Vegetation Dynamics Studies · Mediterranean and Iberian flora and fauna
