The data we present are part of the long-term project SLAM (Long Term Ecological Study of the Impacts of Climate Change in the natural forest of Azores) that aims to understand the impact of biodiversity erosion drivers on Azorean native forests. Passive flight interception SLAM traps (Sea, Land and Air Malaise trap) were used to sample forest plots in both islands, with one trap being setup at each plot. A total of twenty 50m x 50m plots were sampled in two of the islands from the archipelago, 13 in Terceira and 7 in Pico. This publication contributes not only to a better knowledge of the arachnofauna present in native forests of Terceira and Pico, but also contributes to understand the patterns of abundance and diversity both seasonally and between years.

This dataset is based on a National Report on the progress and implementation of the Habitats Directive in Portugal, concerning the 2007-2012 period. It originates from a project performed periodically (every 6 years) that aims to permit an adequate assessment of the progress, via the Natura 2000 Network, towards the goals of the Habitats Directive. This national reports describes conservation status for flora and fauna species in three biogeographic regions (Atlantic, Macaronesian and Mediterranean) and two marine regions (Atlantic and Macaronesian). It contains occurrence data for fauna and flora belonging to 3 kingdoms, 7 phyla, 16 classes, 52 orders, 104 families, 188 genera and 271 species.

This dataset is based on a National Report on the progress and implementation of the Habitats Directive in Portugal, concerning the 2013-2018 period. It originates from a project performed periodically (every 6 years) that aims to permit an adequate assessment of the progress, via the Natura 2000 Network, towards the goals of the Habitats Directive. This national reports describes conservation status for flora and fauna species in three biogeographic regions (Atlantic, Macaronesian and Mediterranean) and two marine regions (Atlantic and Macaronesian). It contains occurrence data for fauna and flora belonging to 3 kingdoms, 7 phyla, 16 classes, 52 orders, 105 families, 192 genera and 277 species.