Borges, P.A.V., Lhoumeau, S. & Vounatsi, M. (2026). Long-term monitoring of Azorean forest arthropods: Graciosa Island. Version 1.0. Universidade dos Açores. Samplingevent dataset.
Since 2012, the SLAM (Sea, Land and Air Malaise) long-term monitoring programme has generated standardised, seasonally comparable time series to track changes in Azorean arthropod distributions, abundances and community composition under multiple biodiversity-erosion drivers, with particular relevance for detecting compositional turnover and the rise of introduced species in island systems. This dataset mobilises the Graciosa component of SLAM monitoring for the period 2015–2021, providing a baseline for an island where native vegetation is extremely reduced and where introduced species are expected to dominate many assemblages. Sampling relies on continuously operating passive flight-interception SLAM traps, enabling repeatable seasonal and interannual comparisons and supporting the use of arthropod assemblages as practical indicators of habitat condition in applied conservation contexts. Across the 2015–2021 samples, we sorted 17,064 specimens, identifying 16,491 (96.6%) to species/subspecies level, and summarising the assemblage as 17 orders, 82 families, 156 genera, 165 species and 8 subspecies, with 14 endemic, 49 native non-endemic, 86 introduced and 24 indeterminate-status taxa. We report 26 species recorded for the first time on Graciosa (none new to the Azores), including two Azorean endemic spiders newly recorded for the island — Neon acoreensis (Salticidae) and Savigniorrhipis acoreensis (Linyphiidae)— alongside additional new island records spanning Araneae, Coleoptera, Diplopoda, Hemiptera, Hymenoptera, Psocodea, Thysanoptera and Orthoptera. Among the collected material, a Cixiidae planthopper (Cixius sp.) is suspected to represent a species new to science and potentially a single-island endemic of Graciosa, pending confirmatory morphological and/or molecular work. By making these standardised records openly available, the dataset directly supports biosecurity-oriented early detection and provides the kind of long-term evidence needed to interpret island biodiversity change, where dynamics are often better captured by turnover and shifts in introduced subsets than by immediate declines in total richness. The resulting time series can be used to (i) characterise local diversity and colonisation-status structure, (ii) flag invasion signals and new occurrences, and (iii) serve as a robust baseline for future reassessments and conservation monitoring aligned with best-practice calls for sustained, standardised biodiversity observation.
