Topography, climate, land cover, and biodiversity: Explaining endemic richness and management implications on a Mediterranean island

• URL: http://arxiv.org/abs/2511.03242v1
• Date: Wed, 05 Nov 2025 07:09:18 GMT
• Title: Topography, climate, land cover, and biodiversity: Explaining endemic richness and management implications on a Mediterranean island
• Authors: Aristides Moustakas, Ioannis N Vogiatzakis,
• Abstract summary: Island endemism is shaped by complex interactions among environmental, ecological, and evolutionary factors.<n>We investigated the drivers of endemic plant richness across Crete, a Mediterranean biodiversity hotspot.<n>We found total species richness, elevation range, and climatic variability were the strongest predictors of endemic richness.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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 promote speciation and buffer extinction risk. Endemic hotspots only partially overlapped with areas of high total species richness, indicating that total species richness was the optimal from the ones examined, yet an imperfect surrogate. These environmentally heterogeneous areas also provide critical ecosystem services, including soil stabilization, pollination, and cultural value, which are increasingly threatened by tourism, renewable energy development, land-use change, and climate impacts. Our findings underscore the importance of prioritizing mountainous and climatically variable regions in conservation planning, integrating ecosystem service considerations, and accounting for within-island spatial heterogeneity. By explicitly linking the environmental drivers of endemism to both biodiversity patterns and ecosystem function, this study provides a framework for evidence-based conservation planning in Crete and other Mediterranean islands with similar geological and biogeographic contexts.

Related papers

• Utilizing Earth Foundation Models to Enhance the Simulation Performance of Hydrological Models with AlphaEarth Embeddings [48.54230513143053]
  This study examines whether AlphaEarth Foundation embeddings offer a more informative way to describe basin characteristics.<n>We find that models using them achieve higher accuracy when predicting flows in basins not used for training.
  arXiv  Detail & Related papers  (2026-01-04T15:14:16Z)
• EcoCast: A Spatio-Temporal Model for Continual Biodiversity and Climate Risk Forecasting [0.0]
  EcoCast bridges the gap between cutting-edge machine learning and biodiversity management.<n>Our pilot study in Africa shows promising improvements in forecasting targeted bird species.
  arXiv  Detail & Related papers  (2025-12-01T23:06:04Z)
• An Ecologically-Informed Deep Learning Framework for Interpretable and Validatable Habitat Mapping [1.4672361353012924]
  ECOSAIC is an Artificial Intelligence framework for automatic classification of benthic habitats.<n> ECOSAIC compresses n-dimensional feature space by optimizing specialization and orthogonality between domain-informed features.<n>We applied the model to the Colombian Pacific Ocean and the results revealed 16 benthic habitats, expanding from mangroves to deep rocky areas up to 1000 m depth.
  arXiv  Detail & Related papers  (2025-11-18T23:38:29Z)
• Continental-scale habitat distribution modelling with multimodal earth observation foundation models [0.0]
  Habitats integrate the abiotic conditions, vegetation composition and structure that support biodiversity and sustain nature's contributions to people.<n>Current habitat maps often fall short in thematic or spatial resolution.<n>We evaluated how high-resolution remote sensing (RS) data and Artificial Intelligence (AI) tools can improve habitat mapping.
  arXiv  Detail & Related papers  (2025-07-13T18:11:26Z)
• BioAnalyst: A Foundation Model for Biodiversity [0.565395466029518]
  We introduce BioAnalyst, the first Foundation Model tailored for biodiversity analysis and conservation planning.<n>BioAnalyst employs a transformer-based architecture, pretrained on extensive multi-modal datasets.<n>We evaluate the model's performance on two downstream use cases, demonstrating its generalisability compared to existing methods.
  arXiv  Detail & Related papers  (2025-07-11T23:56:08Z)
• Multi-scale species richness estimation with deep learning [0.0]
  We combine sampling theory and deep learning to predict local species richness within arbitrarily large sampling areas.<n>We show how our deep SAR model can provide fundamental insights on the multi-scale effects of key biodiversity processes.
  arXiv  Detail & Related papers  (2025-07-08T19:42:33Z)
• Combining Observational Data and Language for Species Range Estimation [63.65684199946094]
  We propose a novel approach combining millions of citizen science species observations with textual descriptions from Wikipedia.<n>Our framework maps locations, species, and text descriptions into a common space, enabling zero-shot range estimation from textual descriptions.<n>Our approach also acts as a strong prior when combined with observational data, resulting in more accurate range estimation with less data.
  arXiv  Detail & Related papers  (2024-10-14T17:22:55Z)
• Artificial Immune System of Secure Face Recognition Against Adversarial Attacks [67.31542713498627]
  optimisation is required for insect production to realise its full potential. This can be by targeted improvement of traits of interest through selective breeding. This review combines knowledge from diverse disciplines, bridging the gap between animal breeding, quantitative genetics, evolutionary biology, and entomology.
  arXiv  Detail & Related papers  (2024-06-26T07:50:58Z)
• Machine Learning Reveals Large-scale Impact of Posidonia Oceanica on Mediterranean Sea Water [0.0818489539741914]
  Posidonia oceanica is a protected endemic seagrass of Mediterranean sea that fosters biodiversity, stores carbon, releases oxygen, and provides habitat to numerous sea organisms. The study provides the evidence of the plant's ability to exert a global impact on the environment and underscores the crucial role of this plant in sea ecosystems.
  arXiv  Detail & Related papers  (2024-02-22T11:35:52Z)
• FREE: The Foundational Semantic Recognition for Modeling Environmental Ecosystems [56.0640340392818]
  We introduce a framework, FREE, that enables the use of varying features and available information to train a universal model.<n>The core idea is to map available environmental data into a text space and then convert the traditional predictive modeling task in environmental science to a semantic recognition problem.<n>Our evaluation on two societally important real-world applications, stream water temperature prediction and crop yield prediction, demonstrates the superiority of FREE over multiple baselines.
  arXiv  Detail & Related papers  (2023-11-17T00:53:09Z)
• SatBird: Bird Species Distribution Modeling with Remote Sensing and Citizen Science Data [68.2366021016172]
  We present SatBird, a satellite dataset of locations in the USA with labels derived from presence-absence observation data from the citizen science database eBird. We also provide a dataset in Kenya representing low-data regimes. We benchmark a set of baselines on our dataset, including SOTA models for remote sensing tasks.
  arXiv  Detail & Related papers  (2023-11-02T02:00:27Z)
• Dynamical Landscape and Multistability of a Climate Model [64.467612647225]
  We find a third intermediate stable state in one of the two climate models we consider. The combination of our approaches allows to identify how the negative feedback of ocean heat transport and entropy production drastically change the topography of Earth's climate.
  arXiv  Detail & Related papers  (2020-10-20T15:31:38Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.