The current loss of biodiversity requires long-term monitoring of the distribution of living organisms, particularly in regions, such as mountains, which are highly sensitive to climatic and environmental changes. In 2007, three alpine parks in N-W Italy started a field program to determine the factors which influence animal biodiversity and identify the most appropriate methods for periodically repeatable monitoring. Twelve altitudinal transects (from montane to alpine belt) were chosen, each composed of 4–7 sampling units, for a total of 69 monitored plots. In each station, five taxonomic groups (carabids, butterflies, spiders, staphylinids, birds) were systematically sampled and topographic, environmental and micro-climatic variables were recorded. The aim was to assess the distribution of different taxa along altitudinal gradients and the relative influence of geographical, environmental and climatic factors. The data showed that species richness and community composition of invertebrates are mainly determined by altitude and microclimatic conditions, whereas birds are more sensitive to habitat structure. For invertebrates, the strong relationship with temperature suggests their potential sensitivity to climatic variations. The analysis of biodiversity patterns across vegetation belts indicated that the alpine belt hosts few species but a high percentage of endemic and vulnerable species, highlighting its importance for conservation purposes. This work offers a representative sample of the northwestern Italian Alps and it is a first step of a monitoring effort that will be repeated every five years to highlight the response of alpine biodiversity to climate and land-use changes

Mountain biodiversity is associated with rare and fragile biota that are highly sensitive to climate change. To estimate the vulnerability of biodiversity to temperature rise, long-term field data are crucial. Species distribution models are an essential tool, in particular for invertebrates, for which detailed information on spatial and temporal distributions is largely missing. We applied presence-only distribution models to field data obtained from a systematic survey of 5 taxa (birds, butterflies, carabids, spiders, staphylinids), monitored in the northwestern Italian Alps. We estimated the effects of a moderate temperature increase on the multi-taxa distributions. Only small changes in the overall biodiversity patterns emerged, but we observed significant differences between groups of species and along the altitudinal gradient. The effects of temperature increase could be more pronounced for spiders and butterflies, and particularly detrimental for high-altitude species. We observed significant changes in community composition and species richness, especially in the alpine belt, but a clear separation between vegetation levels was retained also in the warming scenarios. Our conservative approach suggests that even a moderate temperature increase (about 1 °C) could influence animal biodiversity in mountain ecosystems: only long-term field data can provide the information to improve quantitative predictions, allowing us to readily identify the most informative signals of forthcoming changes.

Mountain ecosystems are biodiversity hotspots that are increasingly threatened by climate and land use/land cover changes. Long-term biodiversity monitoring programs provide unique insights into resulting adverse impacts on plant and animal species distribution. Species distribution models (SDMs) in combination with satellite remote sensing (SRS) data offer the opportunity to analyze shifts of species distributions in response to these changes in a spatially explicit way. Here, we predicted the presence probability of three different rove beetles in a mountainous protected area (Gran Paradiso National Park, GPNP) using environmental variables derived from Landsat and Aster Global Digital Elevation Model data and an ensemble modelling approach based on five different model algorithms (maximum entropy, random forest, generalized boosting models, generalized additive models, and generalized linear models). The objectives of the study were (1) to evaluate the potential of SRS data for predicting the presence of species dependent on local-scale environmental parameters at two different time periods, (2) to analyze shifts in species distributions between the years, and (3) to identify the most important species-specific SRS predictor variables. All ensemble models showed area under curve (AUC) of the receiver operating characteristics values above 0.7 and true skills statistics (TSS) values above 0.4, highlighting the great potential of SRS data. While only a small proportion of the total area was predicted as highly suitable for each species, our results suggest an increase of suitable habitat over time for the species Platydracus stercorarius and Ocypus ophthalmicus, and an opposite trend for Dinothenarus fossor. Vegetation cover was the most important predictor variable in the majority of the SDMs across all three study species. To better account for intra- and inter-annual variability of population dynamics as well as environmental conditions, a continuation of the monitoring program in GPNP as well as the employment of SRS with higher spatial and temporal resolution is recommended.

Cacyreus marshalli is the only alien butterfly in Europe. It has recently spread in the Gran Paradiso National Park (GPNP), where it could potentially compete with native geranium-consuming butterflies. Our study aimed to (1) assess the main drivers of its distribution, (2) evaluate the potential species distribution in GPNP and (3) predict different scenarios to understand the impact of climate warming and the effect of possible mitigations. Considering different sampling designs (opportunistic and standardised) and different statistical approaches (MaxEnt and N-mixture models), we built up models predicting habitat suitability and egg abundance for the alien species, testing covariates as bioclimatic variables, food plant (Pelargonium spp.) distribution and land cover. A standardised approach resulted in more informative data collection due to the survey design adopted. Opportunistic data could be potentially informative but a major investment in citizen science projects would be needed. Both approaches showed that C. marshalli is associated with its host plant distribution and therefore confined in urban areas. Its expansion is controlled by cold temperatures which, even if the host plant is abundant, constrain the number of eggs. Rising temperatures could lead to an increase in the number of eggs laid, but the halving of Pelargonium spp. populations would mostly mitigate the trend, with a slight countertrend at high elevations.