Olive cultivation is a key agricultural activity in Spain, primarily for producing oil. The extraction process of olive oil from the drupe yields a by-product known as 'alperujo', which can be composted and utilized as fertilizer. This research examines the impact of composted 'alperujo' on arthropod assemblages in the tree canopy, comparing it to mineral fertilization over the years 2021 and 2022. The study was conducted in two olive groves with different management systems (superintensive and traditional). Two types of sampling methods were used for the canopy: visual survey and sweep net. Under superintensive management, the presence and damage of Eriophyidae (Acari; Trombidiformes) in the shoots was significantly lower in the compost treatment in 2022 (20% of the shoots were occupied/damaged) compared to the mineral treatment (60% of the shoots were occupied/damaged). Araneae abundance was significantly higher (p = 0.033) in the compost treatment compared to the mineral treatment. However, under traditional management, no clear effect on arthropod assemblage was observed. In conclusion, the addition of compost to the superintensive grove helped to limit the presence of some arthropod pests compared to mineral treatment, contributing to a more sustainable crop. Grove type management appeared to play a significant role in the arthropod assemblages and effect of compost addition, but future research utilizing a greater number of groves (replicates) and an extended observation period should be performed to confirm these results.

Assessing biodiversity in arctic-alpine ecosystems is a costly task. We test in the current study whether we can map the spatial patterns of spider alpha and beta diversity using remotely-sensed surface reflectance and topography in a heterogeneous alpine environment in Central Norway. This proof-of-concept study may provide a tool for an assessment of arthropod communities in remote study areas. Data on arthropod species distribution and richness were collected through pitfall trapping and subjected to a detrended correspondence analysis (DCA) to extract the main species composition gradients. The DCA axis scores as indicators of species composition as well as trap species richness were regressed against a combined data set of surface reflectance as measured by the Sentinel-2 satellite and topographical parameters extracted from a digital elevation model. The models were subsequently applied to the spatial data set to achieve a pixel-wise prediction of both species richness and position in the DCA space. The spatial variation in the modelled DCA scores was used to draw conclusions regarding spider beta-diversity. The species composition was described with two DCA axes that were characterized by post hoc-defined indicator species, which showed a typical annidation in the arctic-alpine environment under study. The fits of the regression models for the DCA axes and species richness ranged from R-2 = 0.25 up to R-2 = 0.62. The resulting maps show strong gradients in alpha and beta diversity across the study area. Our results indicate that the diversity patterns of spiders can at least partially be explained by means of remotely sensed data. Our approach would likely benefit from the additional use of high resolution aerial photography and LiDAR data and may help to improve conservation strategies in arctic-alpine ecosystems.

Arthropods form a major part of the terrestrial species diversity in the Arctic, and are particularly sensitive to temporal changes in the abiotic environment. It is assumed that most Arctic arthropods are habitat generalists and that their diversity patterns exhibit low spatial variation. The empirical basis for this assumption, however, is weak. We examine the degree of spatial variation in species diversity and assemblage structure among five habitat types at two sites of similar abiotic conditions and plant species composition in southwest Greenland, using standardized field collection methods for spiders, beetles and butterflies. We employed non-metric multidimensional scaling, species richness estimation, community dissimilarity and indicator species analysis to test for local (within site)- and regional (between site)-scale differences in arthropod communities. To identify specific drivers of local arthropod assemblages, we used a combination of ordination techniques and linear regression. Species richness and the species pool differed between sites, with the latter indicating high species turnover. Local-scale assemblage patterns were related to soil moisture and temperature. We conclude that Arctic arthropod species assemblages vary substantially over short distances due to local soil characteristics, while regional variation in the species pool is likely influenced by geographic barriers, i.e., inland ice sheet, glaciers, mountains and large water bodies. In order to predict future changes to Arctic arthropod diversity, further efforts are needed to disentangle contemporary drivers of diversity at multiple spatial scales.