Integrating plot-based methods for monitoring biodiversity in island habitats under the scope of BIODIVERSA+ project BioMonI: Beetle monitoring in Pico and Terceira Islands
Oceanic island native forests have become highly fragmented and yet host a disproportionate share of endemic arthropod diversity. Long-term monitoring and conservation planning are often limited by the scarcity of standardised, plot-based datasets for key indicator taxonomic groups, such as the megadiverse beetles (Coleoptera). Under the scope of the projects EU-NETBIOME grant 0003/2011, FCT MACDIV – FCT-PTDC/BIABIC/0054/2014 and BIODIVERSA+ funded BioMonI, we compile and mobilise a baseline dataset of forest beetles from the Azores using a network of 16 permanent 50 m × 50 m native-forest plots (Pico: 6 plots; Terceira: 10 plots). Beetles were sampled with an optimised COBRA (Conservation Oriented Biodiversity Rapid Assessment) protocol complemented by beetle-targeted sampling techiques (under-bark/epiphyte and coarse woody debris/ground refugia searches), enabling repeatable and comparable monitoring across islands and through time.We provide the first Darwin Core–compliant, plot-based inventory of beetles from native forests of Pico and Terceira Islands (Azores, Portugal), delivered as a sample-event dataset with 308 event records and an associated occurrence table (539 records). Across both islands, we recorded 43 beetle morphospecies (39 taxa were identified at species or subspecies levels) from 16 families, totalling 1,787 individuals. The plots in Pico yielded 25 taxa (13 families; 620 individuals; 23 identified species and subspecies) and those in Terceira 30 taxa (10 families; 1,167 individuals; 28 identified species and subspecies). The assemblage is dominated by endemic taxa in both richness and abundance, providing a robust benchmark for detecting compositional change, supporting biogeographical analyses and informing conservation assessments and management of native forest remnants, including evaluations of recovery status for threatened endemics.
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