A comprehensive trait dataset for Terrestrial Arthropods of the Azores: insights for conservation, island ecology and species invasion

亚速尔群岛陆生节肢动物综合性状数据集:对保护、岛屿生态和物种入侵的启示

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Abstract

BACKGROUND: Species functional traits provide critical insights into how organisms interact with and respond to their environment. Key characteristics, such as body size, dispersal ability and trophic specialisation influence species' survival, reproduction and adaptability. Island ecosystems, particularly oceanic archipelagos like the Azores, serve as ideal natural laboratories for studying these traits due to their unique biogeographic history and high endemism. Arthropods, as dominant colonisers and ecosystem engineers, exhibit rapid adaptation and trait diversification in these isolated settings. However, island arthropods face escalating threats from habitat loss, climate change and invasive species, which disrupt ecological functions and increase extinction risks. Under the scope of BALA (Biodiversity of Arthropods from the Laurisilva of Azores) project (1999-2021) and SLAM (Long Term Ecological Study of the Impacts of Climate Change in the natural forest of Azores) project (2012-2025), we obtained a comprehensive and standardised dataset of arthropods functional traits currently known to occur in the Azores Archipelago. NEW INFORMATION: We present a standardised functional trait database for Azorean arthropods, building on 25 years of research on 602 species and subspecies across seven classes and 27 orders. The dataset includes endemic, native non-endemic and exotic species, with traits selected for their relevance to disturbance responses (e.g. body size, dispersal, verticality) and ecological interactions (e.g. trophic level, feeding behaviour). By synthesising these data, we aim to support predictive modelling of biodiversity responses to environmental change and provide information for conservation strategies. This resource provides a foundation for global comparisons and advances in trait-based ecology in island systems.

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