Ethnomedicinal and Ethnobotanical Survey in the Aosta Valley Side of the Gran Paradiso National Park (Western Alps, Italy)

Most of traditional knowledge about plants and their uses is fast disappearing because of socio-economic and land use changes. This trend is also occurring in bio-cultural refugia, such as mountain areas. New data on Traditional Ethnobotanical Knowledge (TEK) of Italian alpine regions were collected relating to three valleys (Cogne, Valsavarenche, Rhêmes) of the Gran Paradiso National Park. Extensive dialogues and semi-structured interviews with 68 native informants (30 men, 38 women; mean age 70) were carried out between 2017 and 2019. A total of 3918 reports were collected, concerning 217 taxa (including 10 mushrooms, 1 lichen) mainly used for medicinal (42%) and food (33%) purposes. Minor uses were related to liquor making (7%), domestic (7%), veterinary (5%), forage (4%), cosmetic (1%) and other (2%). Medicinal plants were used to treat 14 ailment categories, of which the most important were respiratory (22%), digestive (19%), skin (13%), musculoskeletal (10%) and genitourinary (10%) diseases. Data were also evaluated by quantitative ethnobotanical indexes. The results show a rich and alive traditional knowledge concerning plants uses in the Gran Paradiso National Park. Plants resources may provide new opportunities from the scientific point of view, for the valorization of local products for health community and for sustainable land management.

A Revised Snow Cover Algorithm to Improve Discrimination between Snow and Clouds: A Case Study in Gran Paradiso National Park

Snow cover plays an important role in biotic and abiotic environmental processes, as well as human activities, on both regional and global scales. Due to the difficulty of in situ data collection in vast and inaccessible areas, the use of optical satellite imagery represents a useful support for snow cover mapping. At present, several operational snow cover algorithms and products are available. Even though most of them offer an up-to-daily time scale, they do not provide sufficient spatial resolution for studies requiring high spatial detail. By contrast, the Let-It-Snow (LIS) algorithm can produce high-resolution snow cover maps, based on the use of both the normalized-difference snow index (NDSI) and a digital elevation model. The latter is introduced to define a threshold value on the altitude, below which the presence of snow is excluded. In this study, we revised the LIS algorithm by introducing a new parameter, based on a threshold in the shortwave infrared (SWIR) band, and by modifying the overall algorithm workflow, such that the cloud mask selection can be used as an input. The revised algorithm has been applied to a case study in Gran Paradiso National Park. Unlike previous studies, we also compared the performance of both the original and the modified algorithms in the presence of cloud cover, in order to evaluate their effectiveness in discriminating between snow and clouds. Ground data collected by meteorological stations equipped with both snow gauges and solarimeters were used for validation purposes. The changes introduced in the revised algorithm can improve upon the overall classification accuracy obtained by the original LIS algorithm (i.e., up to 89.17 from 80.88%). The producer’s and user’s accuracy values obtained by the modified algorithm (89.12 and 95.03%, respectively) were larger than those obtained by the original algorithm (76.68 and 93.67%, respectively), thus providing a more accurate snow cover map.

Bronchopulmonary Nematodes in Alpine Ibex: Shedding of First Stage Larvae Analyzed at the Individual Host Level

Pneumonia is the most frequent cause of death for Alpine ibex (Capra ibex) in Gran Paradiso National Park, (Italy). The etiology of this form of pneumonia is currently unknown and the identification of the primary etiological agent remains difficult due to biological and logistic constraints. Uncovering individual differences in Protostrongylid prevalence and intensity is important to further investigate the epidemiology of respiratory diseases and their relationship to heterozygosity and inbreeding in a once almost extinct population like C. ibex. In a group of 21 individually recognizable adult male we monitored monthly prevalence and intensity of Protostrongylid first-stage larvae using Baerman's technique from June to September 2019. First-stage larvae of 5 genera were detected. Muellerius (P = 100%, CI95% = 84–100) and Protostrongylus (P = 86%, CI95%:71–100) were two dominant genera according to Bush's importance index. Neostrongylus (P = 38%,CI95%: 17–59), Cystocaulus (P = 33%,CI95% = 13–53) were classified as co-dominant genera while Dictyocaulus filaria (P = 0.05%, CI95% = 0.04–0.13) was detected, for the first time in Alpine ibex, in one subject. Protostrongylidae larval excretion varied significantly over time, with minimum L1 excretion in July. Individual median larval intensity ranged from 4.4 lpg to 82.2 lpg with Poulin's discrepancy index showing highly aggregated distribution patterns for Muellerius spp. (D = 0.283, CI95% = 0.760–0.895) and Protostrongylus spp. (D = 0.635, CI95% = 0.580–0.705). Presented data provide the necessary base point to further investigate how lungworm infection account for the different rates of progression of pneumonia in C. ibex. Individual aggregation of larval intensity must be further evaluated to determine whether these differences mirror different levels of parasitic infection related to individual differences in immune response, hormonal-states or genetic fitness.

Snow Cover Evolution in the Gran Paradiso National Park, Italian Alps, Using the Earth Observation Data Cube

Mountainous regions are particularly vulnerable to climate change, and the impacts are already extensive and observable, the implications of which go far beyond mountain boundaries and the environmental sectors. Monitoring and understanding climate and environmental changes in mountain regions is, therefore, needed. One of the key variables to study is snow cover, since it represents an essential driver of many ecological, hydrological and socioeconomic processes in mountains. As remotely sensed data can contribute to filling the gap of sparse in-situ stations in high-altitude environments, a methodology for snow cover detection through time series analyses using Landsat satellite observations stored in an Open Data Cube is described in this paper, and applied to a case study on the Gran Paradiso National Park, in the western Italian Alps. In particular, this study presents a proof of concept of the preliminary version of the snow observation from space algorithm applied to Landsat data stored in the Swiss Data Cube. Implemented in an Earth Observation Data Cube environment, the algorithm can process a large amount of remote sensing data ready for analysis and can compile all Landsat series since 1984 into one single multi-sensor dataset. Temporal filtering methodology and multi-sensors analysis allows one to considerably reduce the uncertainty in the estimation of snow cover area using high-resolution sensors. The study highlights that, despite this methodology, the lack of available cloud-free images still represents a big issue for snow cover mapping from satellite data. Though accurate mapping of snow extent below cloud cover with optical sensors still represents a challenge, spatial and temporal filtering techniques and radar imagery for future time series analyses will likely allow one to reduce the current cloud cover issue.

Graphical factorial surveys reveal the acceptability of wildlife observation at protected areas

ABSTRACTApproaching large ungulates at protected areas is dangerous both for visitors and the animals. Nudging interventions can mitigate this issue, but conservationists need to be sure about which factors influence the acceptability of human-wildlife encounters, to design them.In summer 2018, we recruited a sample of visitors (n = 205) at the Gran Paradiso National Park (Italy). They evaluated the acceptability of 9 digitally modified pictures, depicting a group of visitors observing an alpine ibex (Capra ibex) close to a trail. Pictures were characterized in terms of group size and distance from the ibex.Observing ibexes was deemed to be acceptable if visitors were further than 25 meters from animals and when groups included less than 3 people. Approaching ibexes at 5 meters was always deemed to be unacceptable. Potential for Conflict Index (PCI) was constant across distance classes and it was generally low.Our findings indicate that visitors share normative beliefs about the optimal distance and group size, that should characterize encounters with large ungulates, when visiting the park. These normative beliefs are crystallized, because previous encounters with ibexes did not affect the evaluation of each scenario and because the PCI was constant and low. We believe that behavioral interventions aimed at promoting respectful and safe human-ibex interactions can be enforced in areas where this interaction is critical, mostly in form of panels on hiking trails introducing normative pressures on visitors and motivating them to comply with rules.

Evidences of zooplankton vertical migration in stocked and never-stocked alpine lakes in Gran Paradiso National Park (Italy)

Zooplankton vertical migration was described in four high altitude lakes in Gran Paradiso National Park (Northern Italy) during 2008 summertime. The authors succeeded in describing the vertical distribution of 6 species: diel vertical migrations were observed in the case of adult crustacean species (Cyclops gr. abyssorum, Arctodiaptomus alpinus and Daphnia gr. longispina), whereas the remaining rotifer species (Keratella quadrata, Polyarthra gr. dolichoptera and Synchaeta gr. stylata-pectinata) and naupliar stages of copepods did not undergo migrations. Migratory behavior of Daphnia gr. longispina and Cyclops gr. abyssorum was influenced by the size of individuals, especially larger individuals use to migrate deeper during the day compared to the smaller conspecific. This study provides new evidences of zooplankton vertical migration in never-stocked lakes and highlights the need to consider the zooplankton migration as result of multiple causal factors.