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Abstract We introduce a georeferenced dataset of Net Ecosystem Exchange (NEE), Ecosystem Respiration (ER) and meteo-climatic variables (air and soil temperature, air relative humidity, soil volumetric water content, pressure, and solar irradiance) collected at the Nivolet Plain in Gran Paradiso National Park (GPNP), western Italian Alps, from 2017 to 2023. NEE and ER are derived by measuring the temporal variation of CO2 concentration obtained by the enclosed chamber method. We used a customised portable non-steady-state dynamic flux chamber, paired with an InfraRed Gas Analyser (IRGA) and a portable weather station, measuring CO2 fluxes at a number of points (around 20 per site and per day) within five different sites during the snow-free season (June to October). Sites are located within the same hydrological basin and have different geological substrates: carbonate rocks (site CARB), gneiss (GNE), glacial deposits (GLA, EC), alluvial sediments (AL). This dataset provides relevant and often missing information on high-altitude mountain ecosystems and enables new comparisons with other similar sites, modelling developments and validation of remote sensing data.

Abstract We assembled the first gridded burned area (BA) database of national wildfire data (ONFIRE), a comprehensive and integrated resource for researchers, non-government organisations, and government agencies analysing wildfires in various regions of the Earth. We extracted and harmonised records from different regions and sources using open and reproducible methods, providing data in a common framework for the whole period available (starting from 1950 in Australia, 1959 in Canada, 1985 in Chile, 1980 in Europe, and 1984 in the United States) up to 2021 on a common 1° × 1° grid. The data originate from national agencies (often, ground mapping), thus representing the best local expert knowledge. Key opportunities and limits in using this dataset are discussed as well as possible future expansions of this open-source approach that should be explored. This dataset complements existing gridded BA data based on remote sensing and offers a valuable opportunity to better understand and assess fire regime changes, and their drivers, in these regions. The ONFIRE database can be freely accessed at https://zenodo.org/record/8289245 .

Abstract Better understanding how fires respond to climate variability is an issue of current interest in light of ongoing climate change. However, evaluating the global‐scale temporal variability of fires in response to climate presents a challenge due to the intricate processes at play and the limitation of fire data. Here, we investigate the links between year‐to‐year variability of burned area (BA) and climate using BA data, the Fire Weather Index (FWI), and the Standardized Precipitation Evapotranspiration Index (SPEI) from 2001 to 2021 at ecoregion scales. Our results reveal complex spatial patterns in the dependence of BA variability on antecedent and concurrent weather conditions, highlighting where BA is mostly influenced by either FWI or SPEI and where the combined effect of both indicators must be considered. Our findings indicate that same‐season weather conditions have a more pronounced relationship with BA across various ecoregions, particularly in climatologically wetter areas. Additionally, we note that BA is also significantly associated with periods of antecedent wetness and coolness, with this association being especially evident in more arid ecoregions. About 60% of the interannual variations in BA can be explained by climatic variability in a large fraction (∼77%) of the world's burnable regions.

Abstract Landscapes nearby glaciers are disproportionally affected by climate change, but we lack detailed information on microclimate variations that can modulate the impacts of global warming on proglacial ecosystems and their biodiversity. Here, we use near-subsurface soil temperatures in 175 stations from polar, equatorial and alpine glacier forelands to generate high-resolution temperature reconstructions, assess spatial variability in microclimate change from 2001 to 2020, and estimate whether microclimate heterogeneity might buffer the severity of warming trends. Temporal changes in microclimate are tightly linked to broad-scale conditions, but the rate of local warming shows great spatial heterogeneity, with faster warming nearby glaciers and during the warm season, and an extension of the snow-free season. Still, most of the fine-scale spatial variability of microclimate is one-to-ten times larger than the temporal change experienced during the past 20 years, indicating the potential for microclimate to buffer climate change, possibly allowing organisms to withstand, at least temporarily, the effects of warming.

Abstract The detection of cause-effect relationships from the analysis of paleoclimatic records is a crucial step to disentangle the main mechanisms at work in the climate system. Here, we show that the approach based on the generalized Fluctuation–Dissipation Relation, complemented by the analysis of the Transfer Entropy, allows the causal links to be identified between temperature, CO $$_2$$ 2 concentration and astronomical forcing during the glacial cycles of the last 800 kyr based on Antarctic ice core records. When considering the whole spectrum of time scales, the results of the analysis suggest that temperature drives CO $$_2$$ 2 concentration, or that are both driven by the common astronomical forcing. However, considering only millennial-scale fluctuations, the results reveal the presence of more complex causal links, indicating that CO $$_2$$ 2 variations contribute to driving the changes of temperature on such time scales. The results also evidence a slow temporal variability in the strength of the millennial-scale causal links between temperature and CO $$_2$$ 2 concentration.

Abstract High-Arctic ecosystems are strongly affected by climate change, and it is still unclear whether they will become a carbon source or sink in the next few decades. In turn, such knowledge gaps on the drivers and the processes controlling CO2 fluxes and storage make future projections of the Arctic carbon budget a challenging goal. During summer 2019, we extensively measured CO2 fluxes at the soil–vegetation–atmosphere interface, together with basic meteoclimatic variables and ecological characteristics in the Bayelva river basin near Ny Ålesund, Spitzbergen, Svalbard (NO). By means of multi-regression models, we identified the main small-scale drivers of CO2 emission (Ecosystem Respiration, ER), and uptake (Gross Primary Production, GPP) in this tundra biome, showing that (i) at point scale, the temporal variability of fluxes is controlled by the classical drivers, i.e. air temperature and solar irradiance respectively for ER and GPP, (ii) at site scale, the heterogeneity of fractional vegetation cover, soil moisture and vegetation type acted as additional source of variability for both CO2 emissions and uptake. The assessment of the relative importance of such drivers in the multi-regression model contributes to a better understanding of the terrestrial carbon dioxide exchanges and of Critical Zone processes in the Arctic tundra.

Non-steady-state closed dynamic accumulation chambers are widely used to measure the respiration of terrestrial ecosystems, thanks to their low cost, low energy consumption and simple transportability, that allow measurements even in hostile and remote environments. However, the assessment of the accuracy and precision associated with the measurement system (independently of possible disturbances due to chamber-soil interactions) is rarely reported. This information is instead necessary for basic quality control, to compare data obtained by different devices and regression models and to provide Confidence Intervals (CIs) on the carbon flux values. This study quantifies the uncertainty associated with emission flux measurements, with a focus on very low fluxes. Calibration tests using different accumulation chambers and CO2 sensors were performed, and fluxes were calculated by means of different models (parametric, non-parametric and flux models). The results of this work show that the linear regression model has the best reproducibility when compared to the other tested models, regardless of the sensor used and the chamber volumes, while the second order polynomial regression has the best accuracy. We remark the importance of building a calibration curve in the range of the expected flux values, with an interval between the lowest and highest imposed flux that should not exceed two orders of magnitude. To evaluate the reproducibility of the measurement, performing replicates for each imposed flux value is essential. We also show that it is necessary to carefully identify the best time interval for interpolating the CO2 concentration curve in order to guarantee reproducibility and accuracy in flux estimates.

The dynamics of carbon dioxide fluxes in the high-altitude Alpine Critical Zone is only partially understood. The complex geomorphology induces significant spatial heterogeneity, and a strong interannual variability is present in the often-extreme climatic and environmental conditions of Alpine ecosystems. To explore the relative importance of the spatial and temporal variability of CO2 fluxes, we analysed a set of in-situ measurements obtained during the summers from 2018 to 2021 in four sampling plots, characterised by soils with different underlying bedrock within the same watershed in the Nivolet plain, in the Gran Paradiso National Park, western Italian Alps. Multi-regression models of CO2 emission and uptake were built using measured meteo-climatic and environmental variables considering either individual years (aggregating over plots) or individual plots (aggregating over years). We observed a significant variability of the model parameters across the different years, while such variability was much smaller across different plots. Significant changes between the different years mainly concerned the temperature dependence of respiration (CO2 emission) and the light dependence of photosynthesis (CO2 uptake). These results suggest that spatial upscaling can be obtained from site measurements, but long-term flux monitoring is required to properly capture the temporal variability at interannual scales.

Assessing the environmental status of Protected Areas (PAs) is a challenging issue. To indicate that status, the identification of a common set of variables that are scientifically sound, and easy to assess and monitor by the PA practitioners, is particularly important. In this study, a set of 27 Essential Variables (EVs) for PA management was selected in a bottom-up process from 67 harmonised variables that describe the status of Ecosystem Functions and Structures, Ecosystem Services, and Threats in PAs. This bottom-up process involved 27 internationally recognised PAs, mostly European, with different level of protection, different extent, and a wide range of human-nature interactions. The EVs were selected by more than 120 practitioners, i.e. PA managers and rangers, as well as scientists, working in terrestrial and aquatic PAs. Across both terrestrial and aquatic PAs, scientists and practitioners largely identified the same variables as important. Data availability for these 27 EVs varied between PAs and averaged 67% across all studied PAs. As this set of EVs for PAs is defined through a bottom-up approach considering variables already in use both in management and research, it is more than for previous EVs likely to be adopted, applied and developed to record the status and changes in the ecological and socio-economic conditions of PAs and to forecast future changes. Thereby, the EVs for PAs present a common vocabulary and tool to enhance in a uniform way the (inter)national communication, exchange and comparison of information on the status of PAs between policy makers, scientists and PA managers. The perceived status of the EVs, on an average 3.6 on a scale to a maximum of 5, indicates the surveyed PAs are in a moderate to good environmental condition. Moreover, the EVs for PAs form a cost- and time-efficient tool for PA managers to monitor developments in essential elements of their PAs, including the potential for Societal Goods and Benefits (SG&B), and to (pro-)actively tackle the potential threats that may arise in their area. Likewise, for policy makers EVs for PAs may support decision making on ecosystem management, spatial planning, and predictive modelling on the future status and requirements of PAs in their country or region.

Mountain ecosystems are particularly sensitive to changes in climate and land cover, but at the same time, they can offer important refuges for species on the opposite of the more altered lowlands. To explore the potential role of mountain ecosystems in butterfly conservation and to assess the vulnerability of the alpine species, we analyzed the short-term changes (2006–2008 vs. 2012–2013) of butterflies’ distribution along altitudinal gradients in the NW Italian Alps. We sampled butterfly communities once a month (62 sampling stations, 3 seasonal replicates per year, from June to August) by semi-quantitative sampling techniques. The monitored gradient ranges from the montane to the alpine belt (600–2700 m a.s.l.) within three protected areas: Gran Paradiso National Park (LTER, Sitecode: LTER_EU_IT_109), Orsiera Rocciavrè Natural Park and Veglia Devero Natural Park. We investigated butterflies’ temporal changes in accordance with a hierarchical approach to assess potential relationships between species and community level. As a first step, we characterized each species in terms of habitat requirements, elevational range and temperature preferences and we compared plot occupancy and altitudinal range changes between time periods (2006–2008 vs. 2012–2013). Secondly, we focused on community level, analyzing species richness and community composition temporal changes. The species level analysis highlighted a general increase in mean occupancy level and significant changes at both altitudinal boundaries. Looking at the ecological groups, we observed an increase of generalist and highly mobile species at the expense of the specialist and less mobile ones. For the community level, we noticed a significant increase in species richness, in the community temperature index and a tendency towards homogenization within communities. Besides the short time period considered, butterflies species distribution and communities changed considerably. In light of these results, it is fundamental to continue monitoring activities to understand if we are facing transient changes or first signals of an imminent trend.

A warmer and drier climate will affect wildfire activity but the climate-fire relationship could change under warming. Here the authors use models with a non-stationary climate-fire relationship to show that to avoid doubling the burned area in the coming decades we must stay below 1.5 °C Paris target.

Societal exposure to large fires has been increasing in recent years and fire forecasting is required for fire management strategies. Here the authors use seasonal climate models to provide skilful predictions of global fire activity.

Our work aims to assess how butterfly communities in the Italian Maritime Alps changed over the past 40 years, in parallel with altitudinal shifts occurring in plant communities. In 2019, we sampled butterflies at 7 grassland sites, between 1300–1900 m, previously investigated in 2009 and 1978, by semi-quantitative linear transects. Fine-scale temperature and precipitation data elaborated by optimal interpolation techniques were used to quantify climate changes. The changes in the vegetation cover and main habitat alterations were assessed by inspection of aerial photographs (1978–2018/1978–2006–2015). The vegetation structure showed a marked decrease of grassland habitats and an increase of woods (1978–2009). Plant physiognomy has remained stable in recent years (2009–2019) with some local exceptions due to geomorphic disturbance. We observed butterfly ‘species substitution’ indicating a general loss in the more specialised and a general gain in more tolerant elements. We did not observe any decrease in species richness, but rather a change in guild compositions, with (i) an overall increased abundance in some widespread and common lowland species and (ii) the disappearance (or strong decrease) of some alpine (high elevation) species, so that ‘resilience’ could be just delusive. Changes in butterfly community composition were consistent with predicted impacts of local warming.

Abstract Summer fires frequently rage across Mediterranean Europe, often intensified by high temperatures and droughts. According to the state-of-the-art regional fire risk projections, in forthcoming decades climate effects are expected to become stronger and possibly overcome fire prevention efforts. However, significant uncertainties exist and the direct effect of climate change in regulating fuel moisture (e.g. warmer conditions increasing fuel dryness) could be counterbalanced by the indirect effects on fuel structure (e.g. warmer conditions limiting fuel amount), affecting the transition between climate-driven and fuel-limited fire regimes as temperatures increase. Here we analyse and model the impact of coincident drought and antecedent wet conditions (proxy for the climatic factor influencing total fuel and fine fuel structure) on the summer Burned Area (BA) across all eco-regions in Mediterranean Europe. This approach allows BA to be linked to the key drivers of fire in the region. We show a statistically significant relationship between fire and same-summer droughts in most regions, while antecedent climate conditions play a relatively minor role, except in few specific eco-regions. The presented models for individual eco-regions provide insights on the impacts of climate variability on BA, and appear to be promising for developing a seasonal forecast system supporting fire management strategies.

The environment affects population dynamics through multiple drivers. Here we explore a simplified version of such influence in a three-species food chain, making use of the Hastings–Powell model. This represents an idealized resource–consumer–predator chain, or equivalently, a vegetation–host–parasitoid system. By stochastically perturbing the value of some parameters in this dynamical system, we observe dramatic modifications in the system behavior. In particular, we show the emergence of on–off intermittency, i.e., an irregular alternation between stable phases and sudden bursts in population size, which hints towards a possible conceptual description of population outbursts grounded into an environment-driven mechanism.

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.

Water and energy are recognized as the most influential climatic vegetation growth-limiting factors. These factors are usually measured from ground meteorological stations. However, since both vary in space, time, and scale, they can be assessed by satellite-derived biophysical indicators. Energy, represented by land surface temperature (LST), is assumed to resemble air temperature; and water availability, related to precipitation, is represented by the normalized difference vegetation index (NDVI). It is hypothesized that positive correlations between LST and NDVI indicate energy-limited conditions, while negative correlations indicate water-limited conditions. The current project aimed to quantify the spatial and seasonal (spring and summer) distributions of LST−NDVI relations over Europe, using long-term (2000−2017) MODIS images. Overlaying the LST−NDVI relations on the European biome map revealed that relations between LST and NDVI were highly diverse among the various biomes and throughout the entire study period (March−August). During the spring season (March−May), 80% of the European domain, across all biomes, showed the dominance of significant positive relations. However, during the summer season (June−August), most of the biomes—except the northern ones—turned to negative correlation. This study demonstrates that the drought/vegetation/stress spectral indices, based on the prevalent hypothesis of an inverse LST−NDVI correlation, are spatially and temporally dependent. These negative correlations are not valid in regions where energy is the limiting factor (e.g., in the drier regions in the southern and eastern extents of the domain) or during specific periods of the year (e.g., the spring season). Consequently, it is essential to re-examine this assumption and restrict applications of such an approach only to areas and periods in which negative correlations are observed. Predicted climate change will lead to an increase in temperature in the coming decades (i.e., increased LST), as well as a complex pattern of precipitation changes (i.e., changes of NDVI). Thus shifts in plant species locations are expected to cause a redistribution of biomes.

Protected Areas are a key component of nature conservation. They can play an important role in counterbalancing the impacts of ecosystem degradation. For an optimal protection of a Protected Area it is essential to account for the variables underlying the major Ecosystem Services an area delivers, and the threats upon them. Here we show that the perception of these important variables differs markedly between scientists and managers of Protected Areas in mountains and transitional waters. Scientists emphasise variables of abiotic and biotic nature, whereas managers highlight socio-economic, cultural and anthropogenic variables. This indicates fundamental differences in perception. To be able to better protect an area it would be advisable to bring the perception of scientists and managers closer together. Intensified and harmonised communication across disciplinary and professional boundaries will be needed to implement and improve Ecosystem Service oriented management strategies in current and future Protected Areas.

We study the interaction between climate and vegetation on an ideal water-limited planet, focussing on the influence of vegetation on the global water cycle. We introduce a simple mechanistic box model consisting in a two-layer representation of the atmosphere and a two-layer soil scheme. The model includes the dynamics of vegetation cover, and the main physical processes of energy and water exchange among the different components. With a realistic choice of parameters, this model displays three stable equilibria, depending on the initial conditions of soil water and vegetation cover. The system reaches a hot and dry state for low values of initial water content and/or vegetation cover, while we observe a wet, vegetated state with mild surface temperature when the system starts from larger initial values of both variables. The third state is a cold desert, where plants transfer enough water to the atmosphere to start a weaker, evaporation-dominated water cycle before they wilt. These results indicate that in this system vegetation plays a central role in transferring water from the soil to the atmosphere and trigger a hydrologic cycle. The model adopted here can also be used to conceptually illustrate processes and feedbacks affecting the water cycle in water-limited continental areas on Earth.

Forest fires are a serious environmental hazard in southern Europe. Quantitative assessment of recent trends in fire statistics is important for assessing the possible shifts induced by climate and other environmental/socioeconomic changes in this area. Here we analyse recent fire trends in Portugal, Spain, southern France, Italy and Greece, building on a homogenized fire database integrating official fire statistics provided by several national/EU agencies. During the period 1985-2011, the total annual burned area (BA) displayed a general decreasing trend, with the exception of Portugal, where a heterogeneous signal was found. Considering all countries globally, we found that BA decreased by about 3020 km2 over the 27-year-long study period (i.e. about -66% of the mean historical value). These results are consistent with those obtained on longer time scales when data were available, also yielding predominantly negative trends in Spain and France (1974-2011) and a mixed trend in Portugal (1980-2011). Similar overall results were found for the annual number of fires (NF), which globally decreased by about 12600 in the study period (about -59%), except for Spain where, excluding the provinces along the Mediterranean coast, an upward trend was found for the longer period. We argue that the negative trends can be explained, at least in part, by an increased effort in fire management and prevention after the big fires of the 1980's, while positive trends may be related to recent socioeconomic transformations leading to more hazardous landscape configurations, as well as to the observed warming of recent decades. We stress the importance of fire data homogenization prior to analysis, in order to alleviate spurious effects associated with non-stationarities in the data due to temporal variations in fire detection efforts.

We studied hydrochemistry and plankton dynamics in two remote alpine lakes: lake Nivolet superiore (2530 m asl) and lake Trebecchi superiore (2729 m asl) in the Gran Paradiso National Park (Western Italian Alps) in summer 2009. The aim of this study was to enhance the understanding of natural ecological dynamics in the pelagic habitat of alpine lakes by enlarging the number of biotic and abiotic variables usually considered to this end and by increasing the frequency of samplings, generally low in remote lakes. During the eight samplings performed in 2009, chemical and physical variables were measured both in situ and in the laboratory. We also followed the dynamics of all the compartments of the naturally simplified trophic chain of the two lakes from pico-prokaryotes to phytoplankton and zooplankton. Our results confirm the oligotrophic, close-to-pristine state of lake Nivolet and lake Trebecchi as they are not affected by hydromorphological alterations, they are naturally fishless and are not sensitive to acidification risk and acidity pulses. On the other hand, the two lakes have distinct abiotic conditions due to their glacial origin and to the lithological composition of their watersheds. We found some differences in the spatial variation of pico-prokaryotes, phytoplankton and zooplankton due to the different mixing regimes and maximum depth of the two lakes. Conversely, temporal patterns were similar in both lakes, related to ecological interactions and to changes in the abiotic conditions. The rapid succession of events in extreme ecosystems, such as the alpine lakes studied here, confirm the predominant role of external environmental factors (e.g. the duration of the ice-free season) and of ecological interactions among different trophic compartments. This research underlines the importance of seasonal niche partitioning among organisms with different size.

Alpine grouses are particularly vulnerable to climate change due to their adaptation to extreme conditions and to their relict distributions in the Alps where global warming has been particularly marked in the last half century. Grouses are also currently threatened by habitat modification and human disturbance, and an assessment of the impact of multiple stressors is needed to predict the fate of Alpine populations of these birds in the next decades. We estimated the effect of climate change and human disturbance on a rock ptarmigan population living in the western Italian Alps by combining an empirical population modelling approach and stochastic simulations of the population dynamics under the a1B climate scenario and two different disturbance scenarios, represented by the development of a ski resort, through 2050.The early appearance of snow-free ground in the previous spring had a favorable effect on the rock ptarmigan population, probably through a higher reproductive success. On the contrary, delayed snowfall in autumn had a negative effect possibly due to a mismatch in time to molt to white winter plumage which increases predation risk. The regional climate model PROTHEUS does not foresee any significant change in snowmelt date in the study area, while the start date of continuous snow cover is expected to be significantly delayed. The net effect in the stochastic projections is a more or less pronounced (depending on the model used) decline in the studied population. The addition of extra-mortality due to collision with ski-lift wires led the population to fatal consequences in most projections. Should these results be confirmed by larger studies the conservation of Alpine populations would deserve more attention. To counterbalance the effects of climate change, the reduction of all causes of death should be pursued, through a strict preservation of the habitats in the present area of occurrence.