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Positive plant-plant interactions are thought to drive vegetation patterns in harsh environments, such as semi-arid areas. According to the stress-gradient hypothesis (SGH), the role of positive interactions between species (facilitation) is expected to increase with harshness, predicting associated variation in species composition along environmental gradients. However, the relation between stress and facilitation along environmental gradients is debated. Furthermore, differentiating facilitative interactions from other underlying mechanisms, such as microtopographic heterogeneity, is not trivial. We analysed the spatial cooccurrence relationships of vascular plant species that form patchy vegetation in arid lapilli fields (tephra) from recent volcanic eruptions on La Palma, Canary Islands. We assume a harshness gradient negatively correlated with elevation because of more arid conditions at lower elevations where water availability is considered the most limiting resource. Based on the SGH we expect a greater degree of co-occurrence at lower elevations, as an outcome of facilitation is plants co-occurring in the same patch. We tested this at both the species and the individual plant level. We analysed the species composition of 1277 shrubby vegetation patches at 64 different sampling points, ranging from the coast to around 700 m a.s.l. Patch morphology and microtopographic heterogeneity variables were also measured, to account for their potential effects on the species composition of patches. We used generalized linear models and generalized mixed-effects models to analyse species richness, number of individuals in patches and percentage of patches with positive co-occurrences, and a pairwise co-occurrence analysis combined with a graphical network analysis to reveal positive links between 13 of the species. We found that the percentage of patches with positive co-occurrences increased at higher elevations, in contrast to the predictions of the SGH, but in accordance with a refined stress-gradient hypothesis for arid sites, in which characteristics of the interacting species are incorporated.

Biological invasions are a major global threat to biodiversity and often affect ecosystem services negatively. They are particularly problematic on oceanic islands where there are many narrow-ranged endemic species, and the biota may be very susceptible to invasion. Quantifying and mapping invasion processes are important steps for management and control but are challenging with the limited resources typically available and particularly difficult to implement on oceanic islands with very steep terrain. Remote sensing may provide an excellent solution in circumstances where the invading species can be reliably detected from imagery. We here develop a method to map the distribution of the alien chestnut (Castanea sativa Mill.) on the island of La Palma (Canary Islands, Spain), using freely available satellite images. On La Palma, the chestnut invasion threatens the iconic laurel forest, which has survived since the Tertiary period in the favourable climatic conditions of mountainous islands in the trade wind zone. We detect chestnut presence by taking advantage of the distinctive phenology of this alien tree, which retains its deciduousness while the native vegetation is evergreen. Using both Landsat 8 and Sentinel-2 (parallel analyses), we obtained images in two seasons (chestnuts leafless and in-leaf, respectively) and performed image regression to detect pixels changing from leafless to in-leaf chestnuts. We then applied supervised classification using Random Forest to map the present-day occurrence of the chestnut. Finally, we performed species distribution modelling to map the habitat suitability for chestnut on La Palma, to estimate which areas are prone to further invasion. Our results indicate that chestnuts occupy 1.2% of the total area of natural ecosystems on La Palma, with a further 12–17% representing suitable habitat that is not yet occupied. This enables targeted control measures with potential to successfully manage the invasion, given the relatively long generation time of the chestnut. Our method also enables research on the spread of the species since the earliest Landsat images.