Aims Mires are important habitats that provide fundamental ecosystem services. Although they have traditionally been considered stable ecosystems, exhibiting little to no change in floristic composition over several decades to millennia, the effect of contemporary climate change is largely unknown. This study aimed to assess (i) how the vegetation of Sphagnum-dominated mires changed over the last two decades in the Western Alps, where mires are fragmented and at the southern edge of their European distribution, and (ii) whether climate change was a primary driver of these changes.Location Western Alps, Italy.Methods We resurveyed 139 plots across 14 sites, comparing historical vegetation data from 1998 and 2011 with new surveys conducted in 2023, including vascular plants and bryophytes. We analysed the shifts in species composition and the changes in community diversity and ecological indicators. We also evaluated climate trends over the past three decades and their relationship with vegetation dynamics.Results Climate data analyses confirmed increasing air temperatures, decreasing precipitation and increasing evaporation across the study sites. Both short-term and long-term resurveys showed an increase in species diversity, in particular woody and non-specialist vascular plants, and a decrease in or local extinction of mire specialists, including Sphagnum species. These results suggest a lowering of the water table and a consequent drying. Longer term resurveys revealed signs of acidification and eutrophication, likely due to increased mineralisation. Attribution to climate change was supported by the higher increase in species richness in mires with a stronger decrease in precipitation.Conclusion Our results revealed significant vegetation changes under the pressure of climate change, with mires at the southern edge of their European distribution exhibiting more rapid and pronounced vegetation dynamics than previous studies conducted at higher latitudes. Urgent conservation measures, including rewetting, are essential to preserve these mires and their ecosystem services.

Fertilization strictly depends on the availability of viable and germinable pollen. Pollen viability can vary depending on the cultivar and the time of the dispersal, but the physiological basis of this pattern is still poorly understood. Carbohydrates play a pivotal role in regulating the osmotic equilibrium, as well as representing the main substrate for the cellular respiration necessary for pollen maintenance and germination. Pollen grains from four Corylus avellana L. cultivars (Camponica, Tonda di Giffoni, Tonda Gentile sin. ‘Tonda Gentile delle Langhe’ e Barcelona) were analyzed to verify whether viability and germinability are related to the carbohydrate concentration (glucose, fructose, sucrose and starch) during dispersal. Samples were collected from two different hazelnut collection fields located in Piacenza and Chieri, and compared with each other. In both fields, all genotypes were characterized by the absence or very low concentrations of glucose and fructose, while starch showed stable values. Sucrose had a fluctuating trend, largely reflecting that of viability and germinability. Pollen viability was positively correlated with sucrose content, regardless of the genotype or field considered. Pollen germinability was also positively correlated with viability in some cultivars but not in all locations tested. These results suggest that viability and germinability could be good predictor parameters of the pollen suitability at different stages of the pollination and fertilization process. On the other hand, no significant correlation emerged between pollen germinability and sucrose content. The intervention of a third factor, such as the climatic variations between the two areas, could further explain the data obtained. The findings of this research confirm the role of sucrose in supporting hazelnut pollen viability.

Assessing pollen viability and anomalies is essential to optimize resources and improve hazelnut productivity. However, knowledge of pollen viability dynamics across cultivars and environments remains limited. This study applied impedance flow cytometry to (i) monitor pollen hydration and define optimal rehydration time, (ii) quantify pollen viability over three flowering seasons, and (iii) evaluate genetic, environmental, and agronomic influences on viable and anomalous pollen formation. Viable pollen showed an adaptive response, restoring high viability (~85%) after four hours of hydration following dehydration stress. Viability displayed cultivar-specific patterns, stable across years but variable among sites. In Viterbo (central Italy, Mediterranean climate), flowering occurred 2–4 weeks earlier than in northern orchards (Piedmont, continental climate). Wild-type accessions exhibited higher viability and minimal anomalous pollen (<3%), whereas cultivated genotypes maintained abundant anomalous pollen (30–50%) across sites and seasons. Multifactorial analysis revealed that both genotype and environment affected viable pollen, while anomalous pollen depended mainly on genotype. Overall, pollen viability results from the interaction between genetic predisposition and local conditions, whereas anomalous pollen reflects stable, genotype-linked traits. These findings highlight the dominant role of cultivar-specific genetics in hazelnut pollen quality, providing a framework for breeding and orchard management strategies.

Woody species encroachment of grasslands is occurring worldwide with contrasting consequences for ecosystem processes. This work aims to describe the changes in soil and litter decomposition following the early stages of colonization in a subalpine grassland located in the Alps. We investigated soil properties onto O and A horizons, and carried out a 1-year decomposition experiment to quantify the decomposition rate and describe the qualitative features of the process through Fourier-transform infrared spectroscopy methodology. All the analyses were carried out in an encroached area and the adjacent grassland. Shrubland soil showed higher temperature and moisture compared to grassland, whereas no significant differences were found for pH, ammonium, nitrate, available P, total organic carbon, and total nitrogen, neither in the O nor in the A soil horizon. A significantly higher dissolved organic carbon content was observed in the shrubland A horizon, as well as a higher content of microbial C and N. The decomposition rate was significantly higher in the shrubland soil with no relevant differences about the qualitative aspects of the process. Our results showed that, even in the early stage of the process, when soil chemistry has not changed yet, woody encroachment caused an increase of soil moisture and microbial biomass, which favoured decomposition rate.

Habitat loss is the main threat to biodiversity at a global level, making habitat mapping an essential tool for the management of protected areas and for the conservation and monitoring, in line with Directive 92/43/EEC. Traditional mapping methods are resource-intensive, while remote sensing approaches depend on the availability of ground truth datasets. In this context, this study presents a novel framework for time series habitat classification. The approach leverages a single pre-existing habitat cartography and a limited set of ancillary data to derive a retrospective training dataset. The method was applied to analyse 39 years (1985–2023) of habitat and land cover changes in Gran Paradiso National Park (NW Italy). Annual seasonal composite images were generated for the growing and senescence seasons using an enhanced Best Available Pixel approach. Annually derived training datasets were used to classify hierarchically land cover and habitats via ensemble random forest models. Validation against high-resolution maps demonstrated the robustness of the approach. The method allows for long-term habitat monitoring even in data-sparse environments. The results reveal high stability of land cover (88

Lowland meadows represent aboveground and belowground biodiversity reservoirs in intensive agricultural areas, improving water retention and filtration, ensuring forage production, contrasting erosion and contributing to soil fertility and carbon sequestration. Besides such major ecosystem services, the presence of functionally different plant species improves forage quality, nutritional value and productivity, also limiting the establishment of weeds and alien species. Here, we tested the effectiveness of a commercial seed mixture in restoring a lowland mixed meadow in the presence or absence of inoculation with arbuscular mycorrhizal (AM) fungi and biostimulation of symbiosis development with the addition of short chain chito-oligosaccharides (CO). Plant community composition, phenology and productivity were regularly monitored alongside AM colonization in control, inoculated and CO-treated inoculated plots. Our analyses revealed that the CO treatment accelerated symbiosis development significantly increasing root colonization by AM fungi. Moreover, the combination of AM fungal inoculation and CO treatment improved plant species evenness and productivity with more balanced composition in forage species. Altogether, our study presented a successful and scalable strategy for the reintroduction of mixed meadows as valuable sources of forage biomass; demonstrated the positive impact of CO treatment on AM development in an agronomic context, extending previous observations developed under controlled laboratory conditions and leading the way to the application in sustainable agricultural practices.

Anthropogenic threats are responsible for habitat degradation and biodiversity decline. The mapping of the distribution and intensity of threats to biodiversity can be useful for informing efficient planning in protected areas. In this study, we propose a cumulative spatial and temporal analysis of anthropogenic impacts insisting on an alpine protected area, the Gran Paradiso National Park. The applied methodology starts with the construction of a spatial and temporal dataset of anthropogenic impacts and normalization based on relative intensity. The impacts analyzed include overgrazing, helicopter flights, road networks, built-up areas, worksites, derivations and discharges, sports activities, and dams and hydroelectric power plants. Each impact was assigned a weight based on its temporal persistence. Threats maps obtained from the collected, normalized, and weighted geodata are thus obtained. Finally, the risk map is calculated by combining the impact map with the vulnerability map, estimated through the methodology outlined in the Green Guidelines of the Metropolitan City of Turin. The risk map obtained was cross-referenced with the Park's cartography to highlight any critical issues to specific habitats. Results show that most of the territory falls in low-risk (63%) or no-risk (35%) areas. However, there are some habitats that are totally or nearly totally affected by some degree of risk, although different to zero, such as the "Lentic waters with aquatic vegetation [incl. cod. 3130]", the "Lentic waters partially buried", the "Mountain pine forests (Pinus uncinata) [cod. 9430]", and the "Mixed hygrophilous woods of broad-leaved trees [incl. cod. 91E0]". This study highlights both the potential of these analyses, which enable informed management and planning of the fruition of protected areas, and the limitations of such approaches, which require in-depth knowledge of the territory and ecosystems and how they respond to threats in order to refine the model and obtain realistic maps.

Preterm birth (PTB) identifies infants prematurely born <37 weeks/gestation and is one of the main causes of infant mortality. PTB has been linked to air pollution exposure, but its timing is still unclear and neglects the acute nature of delivery and its association with short-term effects. We analyzed 3 years of birth data (2015–2017) in Turin (Italy) and the relationships with proinflammatory chemicals (PM2.5, O3, and NO2) and biological (aeroallergens) pollutants on PTB vs. at-term birth, in the narrow window of a week before delivery. A tailored non-stationary Poisson model correcting for seasonality and possible confounding variables was applied. Relative risk associated with each pollutant was assessed at any time lag between 0 and 7 days prior to delivery. PTB risk was significantly associated with increased levels of both chemical (PM2.5, RR = 1.023 (1.003–1.043), O3, 1.025 (1.001–1.048)) and biological (aeroallergens, RR ~ 1.01 (1.0002–1.016)) pollutants in the week prior to delivery. None of these, except for NO2 (RR = 1.01 (1.002–1.021)), appeared to play any role on at-term delivery. Pollutant-induced acute inflammation eliciting delivery in at-risk pregnancies may represent the pathophysiological link between air pollution and PTB, as testified by the different effects played on PTB revealed. Further studies are needed to better elucidate a possible exposure threshold to prevent PTB.

Invasive alien species are among the main global drivers of biodiversity loss posing major challenges to nature conservation and to managers of protected areas. The present study applied a methodological framework that combined invasive Species Distribution Models, based on propagule pressure, abiotic and biotic factors for 14 invasive alien plants of Union concern in Italy, with the local interpretable model-agnostic explanation analysis aiming to map, evaluate and analyse the risk of plant invasions across the country, inside and outside the network of protected areas. Using a hierarchical invasive Species Distribution Model, we explored the combined effect of propagule pressure, abiotic and biotic factors on shaping invasive alien plant occurrence across three biogeographic regions (Alpine, Continental, and Mediterranean) and realms (terrestrial and aquatic) in Italy. We disentangled the role of propagule pressure, abiotic and biotic factors on invasive alien plant distribution and projected invasion risk maps. We compared the risk posed by invasive alien plants inside and outside protected areas. Invasive alien plant distribution varied across biogeographic regions and realms and unevenly threatens protected areas. As an alien's occurrence and risk on a national scale are linked with abiotic factors followed by propagule pressure, their local distribution in protected areas is shaped by propagule pressure and biotic filters. The proposed modelling framework for the assessment of the risk posed by invasive alien plants across spatial scales and under different protection regimes represents an attempt to fill the gap between theory and practice in conservation planning helping to identify scale, site, and species-specific priorities of management, monitoring and control actions. Based on solid theory and on free geographic information, it has great potential for application to wider networks of protected areas in the world and to any invasive alien plant, aiding improved management strategies claimed by the environmental legislation and national and global strategies.

In the Alpine environment, snow plays a key role in many processes involving ecosystems, biogeochemical cycles, and human wellbeing. Due to the inaccessibility of mountain areas and the high spatial and temporal heterogeneity of the snowpack, satellite spatio-temporal data without gaps offer a unique opportunity to monitor snow on a fine scale. In this study, we present a random forest approach within three different workflows to combine MODIS and Sentinel-2 snow products to retrieve daily gap-free snow cover maps at 20 m resolution. The three workflows differ in terms of the type of ingested snow products and, consequently, in the type of random forest used. The required inputs are the MODIS/Terra Snow Cover Daily L3 Global dataset at 500 m and the Sentinel-2 snow dataset at 20 m, automatically retrieved through the recently developed revised-Let It Snow workflow, from which the selected inputs are, alternatively, the Snow Cover Extent (SCE) map or the Normalized Difference Snow Index (NDSI) map, and a Digital Elevation Model (DEM) of consistent resolution with Sentinel-2 imagery. The algorithm is based on two steps, the first to fill the gaps of the MODIS snow dataset and the second to downscale the data and obtain the high resolution daily snow time series. The workflow is applied to a case study in Gran Paradiso National Park. The proposed study represents a first attempt to use the revised-Let It Snow with the purpose of extracting temporal parameters of snow. The validation was achieved by comparison with both an independent dataset of Sentinel-2 to assess the spatial accuracy, including the snowline elevation prediction, and the algorithm’s performance through the different topographic conditions, and with in-situ data collected by meteorological stations, to assess temporal accuracy, with a focus on seasonal snow phenology parameters. Results show that all of the approaches provide robust time series (overall accuracies of A1 = 93.4%, and A2 and A3 = 92.6% against Sentinel-2, and A1 = 93.1%, A2 = 93.7%, and A3 = 93.6% against weather stations), but the first approach requires about one fifth of the computational resources needed for the other two. The proposed workflow is fully automatic and requires input data that are readily and globally available, and promises to be easily reproducible in other study areas to obtain high-resolution daily time series, which is crucial for understanding snow-driven processes at a fine scale, such as vegetation dynamics after snowmelt.

Plant phenology reveals important information about the physiological status of plants, especially in relation to water availability. In many seasonally dry regions, such as the Mediterranean region, low water availability not only affects

Since climate change impacts are already occurring, urgent adaptive actions are necessary to avoid the worst damages. Regional authorities play an important role in adaptation, but they have few binding guidelines to carry out strategies and plans. Sectoral impacts and adaptive measures strongly differ between regions; therefore, specific results for each territory are needed. Impacts are often not exhaustively reported by literature, dataset and models, thus making it impossible to objectively identify specific adaptive measures. Usual expert elicitation helps to fill this gap but shows some issues. For the Piedmont Strategy, an innovative approach has been proposed, involving experts of private and public bodies (regional authorities, academia, research institutes, parks, associations, NGOs, etc.). They collaborated in two work group, first to identify current and future impacts on biodiversity and ecosystems, and secondly to elaborate and prioritize measures. Involving 143 experts of 46 affiliations, it was possible to quickly edit a cross-validated list of impacts (110) and measures (92) with limited costs. Lastly, a public return of results took place. This approach proved to be effective, efficient and influenced the policymakers, overcoming the tendency to enact long-term actions to face climate change. It could be used internationally by subnational authorities also in other sectors.

Projections of future climate change indicate that extreme events will be larger in frequency and intensity, with an increased risk of ecosystem transition from carbon sinks to carbon sources. In particular, warming is occurring at a higher rate in the Alps, with important impacts for tree species acclimated to a strong climate seasonality and a short growing season. In this study, we investigated the ecosystem responses to heatwave and drought at a high-altitude Larix decidua (Mill.) forest in the western Italian Alps (IT-Trf, 2050 m asl), by coupling direct measurements of ecosystem-scale surface-atmosphere fluxes and tree-based observations. Ecosystem fluxes were monitored by means of the eddy covariance technique, measuring water and carbon fluxes (i.e., gross primary production, net ecosystem exchange, and evapotranspiration). From 2015 to 2017 additional observations were carried out at tree level, including stem growth and its duration, direct phenological observations, sap flow, and tree water deficit. Results showed that the warm spells observed in 2015 and 2017, caused the advance of the larch phenological development and, thus, of the seasonal trajectories of many processes. However, we did not observe significant quantitative changes in the C sequestration at the ecosystem level, whereas in 2017 we found a reduction of 18% in larch stem growth and a contraction of 45% of the stem growth period. The growing season in 2017 was indeed characterized by different drought events and by the highest water deficit during the study years. By combining tree- and ecosystem-based observations, we demonstrated that larch growth decrease was not driven by a reduction of the photosynthetic activity. We formulate two contrasting hypotheses to explain our results: i) a shift in C allocation within the plants towards the prioritization of NSC storage within leaves and roots over growth processes, which question the C-source limitation hypothesis, usually applied in vegetation modeling; ii) the ‘Insurance Hypothesis’, which can be used to explain the stability of the whole ecosystem gas exchanges, where the negative effects of climatic fluctuations on larch growth might have been buffered by the asynchrony responses of the understory species that can benefit from the higher temperatures.

Climate change is expected to increase both the frequency and the intensity of climate extremes, consequently increasing the risk of forest role transition from carbon sequestration to carbon emission. These changes are occurring more rapidly in the Alps, with important consequences for tree species adapted to strong climate seasonality and short growing season. In this study, we aimed at investigating the responses of a high-altitude Larix decidua Mill. forest to heat and drought, by coupling ecosystem- and tree-level measurements. From 2012 to 2018, ecosystem carbon and water fluxes (i.e. gross primary production, net ecosystem exchange, and evapotranspiration) were measured by means of the eddy covariance technique, together with the monitoring of canopy development (i.e. larch phenology and normalized difference vegetation index). From 2015 to 2017 we carried out additional observations at the tree level, including stem growth and its duration, direct phenological observations, sap flow, and tree water deficit. Results showed that the warm spells in 2015 and 2017 caused an advance of the phenological development and, thus, of the seasonal trajectories of many processes, at both tree and ecosystem level. However, we did not observe any significant quantitative changes regarding ecosystem gas exchanges during extreme years. In contrast, in 2017 we found a reduction of 17% in larch stem growth and a contraction of 45% of the stem growth period. The growing season in 2017 was indeed characterized by different drought events and by the highest water deficit during the study years. Due to its multi-level approach, our study provided evidence of the independence between C-source (i.e. photosynthesis) and C-sink (i.e. tree stem growth) processes in a subalpine larch forest.

Abstract Background Italy was the first western country severely affected by the Covid-19 pandemic attesting more than 16 million cases since the outbreak began. Po Valley regions have been most afflicted, with Piedmont ranking sixth at 25,899 cases/100,000 inhabitants. Within this area, air dispersion is hampered making Po Valley a recognised air pollution hotspot. We aimed to explore the potential association between the environment and Covid-19 incidence. Methods Daily key air pollutants (NO2, NO, CO, O3, PM10, and PM2.5), meteorological parameters (temperature, %humidity, wind speed and solar radiation), pollens and Covid-19 cases were collected from 01/01 to 31/12/2021 in Turin, Italy. This ecological study preliminarily tested correlations (Spearman) between air pollutants and Covid-19 cases. Results The Covid-19 pandemic followed a seasonal trend with the highest number of cases (/100,000 inhabitants) in winter and spring (3.1) followed by autumn (1.3) and summer (0.5) (KW test p < 0.0001). Likewise, all air pollutants showed peaks in winter and autumn and sensibly decreased during spring and summer apart from pollens and O3. O3 follows the photochemical processes reaching its peak in the sunniest periods, while pollens undergo their natural vegetative process. Daily Covid-19 cases were positively correlated with daily-averaged NO2 (0.50, p < 0.0001), NO (0.48, p < 0.0001), CO (0.81, p < 0.0001), PM10 (0.36, p < 0.0001), PM2.5 (0.39, p < 0.0001), pollens (0.15, p = 0.073) and inversely with O3 (-0.44, p < 0.0001). We plan future analyses to test the hypothesized association by enhanced models with lagged air pollution variables, with demographic characteristics and meteorological data as potential confounders. Conclusions Results from ecological studies may support researchers’ preliminary understanding of the interplay between environment and Public Health issues, including pandemics. A multidisciplinary approach is mandatory to deepen the complexity of this topic across European regions Key messages • The Covid-19 pandemic may be associated with environmental conditions and air pollution but further research is needed. • Atmospheric particulate matter, including aeroallergens, can favour many airborne-related diseases by acting as immune suppressor and/or carrier, but these hypotheses deserve future research.

The results of the 4th National Report for the Italian flora under the 92/43/EEC 'Habitats' Directive are presented. The outcomes showed a general negative conservation status for plant species, with the worst situation being in the Mediterranean bioregion. At the National level, significant monitoring and conservation activities are required.

This report summarises the Pollen Grain Classification Challenge 2020, and the related findings. It serves as an introduction to the technical reports that were submitted to the competition section at the 25th International Conference on Pattern Recognition (ICPR 2020), related to the Pollen Grain Classification Challenge. The challenge is meant to develop automatic pollen grain classification systems, by leveraging on the first large scale annotated dataset of microscope pollen grain images.

Climate change and the global economy impose new challenges in the management of food-producing trees and require studying how to model plant physiological responses, namely growth dynamics and phenology. Hazelnut (Corylus avellana L.) is a multi-stemmed forest species domesticated for nut production and now widely spread across different continents. However, information on stem growth and its synchronization with leaf and reproductive phenology is extremely limited. This study aimed at (i) defining the sequencing of radial growth phases in hazelnut (onset, maximum growth and cessation) and the specific temperature triggering stem growth; and (ii) combining the stem growth phases with leaf and fruit phenology. Point dendrometers were installed on 20 hazelnut trees across eight orchards distributed in the Northern and Southern hemisphere during a period of three growing seasons between 2015 and 2018. The radial growth variations and climatic parameters were averaged and recorded every 15 min. Leaf and reproductive phenology were collected weekly at each site. Results showed that stem radial growth started from day of year 84 to 134 in relation to site and year but within a relatively narrow range of temperature (from 13 to 16.5 degrees C). However, we observed a temperature-related acclimation in the cultivar Tonda di Giffoni. Maximum growth always occurred well before the summer solstice (on average 35 days) and before the maximum annual air temperatures. Xylogenesis developed rapidly since the time interval between onset and maximum growth rate was about 3 weeks. Importantly, the species showed an evident delay of stem growth onset with respect to leaf emergence (on average 4-6 weeks) rarely observed in tree species. These findings represent the first global analysis of radial growth dynamics in hazelnut, which is an essential step for developing models on orchard functioning and management on different continents.