Fire Responses Shape Plant Communities in a Minimal Model for Fire Ecosystems across the World.

AbstractAcross plant communities worldwide, fire regimes reflect a combination of climatic factors and plant characteristics. To shed new light on the complex relationships between plant characteristics and fire regimes, we developed a new conceptual mechanistic model that includes plant competition, stochastic fires, and fire-vegetation feedback. Considering a single standing plant functional type, we observed that highly flammable and slowly colonizing plants can persist only when they have a strong fire response, while fast colonizing and less flammable plants can display a larger range of fire responses. At the community level, the fire response of the strongest competitor determines the existence of alternative ecological states (i.e., different plant communities) under the same environmental conditions. Specifically, when the strongest competitor had a very strong fire response, such as in Mediterranean forests, only one ecological state could be achieved. Conversely, when the strongest competitor was poorly fire adapted, alternative ecological states emerged-for example, between tropical humid savannas and forests or between different types of boreal forests. These findings underline the importance of including the plant fire response when modeling fire ecosystems, for example, to predict the vegetation response to invasive species or to climate change.

On-off intermittency and irruptions in host-parasitoid dynamics.

Environmental stochasticity affects population dynamics in a variety of ways, including the possibility of drastic modifications in the stability properties of the ecosystem. In this work, we investigate a case of coupled host-parasitoid dynamics adopting Beddington's conceptual two-dimensional map. We stochastically perturb some of the parameters controlling either the host dynamics or the host-parasitoid interaction, observing a dramatic change in the system dynamics with the emergence of on-off intermittency, a behavior characterized by the irregular alternation between quiescent phases and sudden population bursts. This phenomenon is herein offered as a qualitative, environmental-based description of population outbreaks.

Carbon dioxide fluxes in Alpine grasslands at the Nivolet Plain, Gran Paradiso National Park, Italy 2017-2023.

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.

A monthly gridded burned area database of national wildland fire data.

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 .

Spatial and temporal variability of carbon dioxide fluxes in the Alpine Critical Zone: The case of the Nivolet Plain, Gran Paradiso National Park, Italy.

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.

Heterogeneous changes of soil microclimate in high mountains and glacier forelands.

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.

Extracting causation from millennial-scale climate fluctuations in the last 800 kyr.

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[Formula: see text] 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[Formula: see text] 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[Formula: see text] 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[Formula: see text] concentration.

Microscale drivers of summer CO2 fluxes in the Svalbard High Arctic tundra.

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.

Climate warming, ecological mismatch at arrival and population decline in migratory birds.

Climate is changing at a fast pace, causing widespread, profound consequences for living organisms. Failure to adjust the timing of life-cycle events to climate may jeopardize populations by causing ecological mismatches to the life cycle of other species and abiotic factors. Population declines of some migratory birds breeding in Europe have been suggested to depend on their inability to adjust migration phenology so as to keep track of advancement of spring events at their breeding grounds. In fact, several migrants have advanced their spring arrival date, but whether such advancement has been sufficient to compensate for temporal shift in spring phenophases or, conversely, birds have become ecologically mismatched, is still an unanswered question, with very few exceptions. We used a novel approach based on accumulated winter and spring temperatures (degree-days) as a proxy for timing of spring biological events to test if the progress of spring at arrival to the breeding areas by 117 European migratory bird species has changed over the past five decades. Migrants, and particularly those wintering in sub-Saharan Africa, now arrive at higher degree-days and may have therefore accumulated a 'thermal delay', thus possibly becoming increasingly mismatched to spring phenology. Species with greater 'thermal delay' have shown larger population decline, and this evidence was not confounded by concomitant ecological factors or by phylogenetic effects. These findings provide general support to the largely untested hypotheses that migratory birds are becoming ecologically mismatched and that failure to respond to climate change can have severe negative impacts on their populations. The novel approach we adopted can be extended to the analysis of ecological consequences of phenological response to climate change by other taxa.

Scale of plume clustering in large-Prandtl-number convection.

Clustering of plumes in turbulent Rayleigh-Bénard convection has been numerically observed in low-Prandtl-number fluids. In this framework, turbulent plumes undergo a phase-separation process leading to large-scale clusters and circulations, sometimes called plume superstructures and reminiscent of solar granulation and supergranulation. On the other hand, the possible presence of large-scale plume aggregates has not been explored in the case of large values of the Prandtl number, Pr, relevant to geological settings such as convection in planetary interiors. Here we address this problem and numerically explore the behavior of plume ensembles in turbulent convection at very high Prandtl number values, including the case Pr→∞. The results indicate the presence of plume clustering, albeit at smaller scale, also for large Pr number fluids, suggesting interesting consequences for mantle convection processes.

Climate and land-use changes drive biodiversity turnover in arthropod assemblages over 150 years.

Long-term studies are essential to understand the impacts of global changes on the multiple facets of biological diversity. Here, we use distribution data for over 600 species of arthropods collected over 150 years from locations across Italy and test how multiple environmental stressors (climate, land use and human population density) influenced assemblage composition and functionality. By carefully reconstructing the temporal changes in these stressors, we explicitly tested how environmental changes can determine the observed changes in taxonomic and functional diversity. We found that rapid changes in precipitation destabilize the assemblages and maximize colonization and extinction rates, especially when coupled with changes in human population density (for taxonomy) or temperature (for functionality). Higher microclimatic heterogeneity increases the stability of biodiversity by reducing taxonomic and functional loss. Finally, changes in natural habitats increased colonization, influencing taxonomic nestedness and functional replacement. The integration of long-term datasets combining distributions, climate and traits may deepen our understanding of the processes underlying biodiversity responses to global-scale drivers.

Changes in Alpine Butterfly Communities during the Last 40 Years.

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.

Drivers of carbon fluxes in Alpine tundra: a comparison of three empirical model approaches.

In high mountains, the effects of climate change are manifesting most rapidly. This is especially critical for the high-altitude carbon cycle, for which new feedbacks could be triggered. However, mountain carbon dynamics is only partially known. In particular, models of the processes driving carbon fluxes in high-altitude grasslands and Alpine tundra need to be improved. Here, we propose a comparison of three empirical approaches using systematic statistical analysis, to identify the environmental variables controlling CO2 fluxes. The methods were applied to a complete dataset of simultaneous in situ measurements of the net CO2 exchange, ecosystem respiration and basic environmental variables in three sampling sites in the same catchment. Large year-to-year variations in the Gross Primary Production (GPP) and Ecosystem Respiration (ER) dependences on solar irradiance and temperature were observed. We thus implemented a multi regression model in which additional variables were introduced as perturbations of the standard exponential and rectangular hyperbolic functions for ER and GPP, respectively. A comparison of this model with other common modelling strategies showed the benefits of this approach, resulting in large explained variances (83% to 94%). The optimum ensemble of variables explaining the inter- and intra-annual flux variability included solar irradiance, soil moisture and day of the year for GPP, and air temperature, soil moisture, air pressure and day of the year for ER, in agreement with other studies. The modelling approach discussed here provides a basis for selecting drivers of carbon fluxes and understanding their role in high-altitude Alpine ecosystems, also allowing for future short-range assessments of local trends.

ClimCKmap, a spatially, temporally and climatically explicit distribution database for the Italian fauna.

Understanding and counteracting biodiversity losses requires quantitative knowledge on species distribution and abundance across space and time, as well as integrated and interoperable information on climate conditions and climatic changes. In this paper we developed a new biodiversity-climate database for Italy, ClimCKmap, based on the critical analysis, quality estimation and subsequent integration of the CKmap database with several high-resolution climate datasets. The original database was quality-checked for errors in toponym, species name and dating; the retained records were georeferenced and their distribution polygonised via Voronoi tessellation. We then integrated the species distribution information with several high-resolution climatic datasets: average monthly minimum and maximum temperature and total monthly precipitation were reconstructed for each Voronoi cell and year. The resulting database contains 268,977 occurrence records from 8,445 binomials and 16,332 localities, dating between 1680 and 2006 CE. This dataset, fully available at https://doi.org/10.6084/m9.figshare.7906739.v4 and http://hdl.handle.net/21.11125/a91f85cb-befd-4e14-8e83-24f17c4a0491 , represents the largest, fully quality-checked, spatially, temporally and climatically explicit distribution database ever assembled for the Italian fauna, now ready for scientific exploitation.

Uniqueness of Protected Areas for Conservation Strategies in the European Union.

Protected areas (PAs) constitute major tools in nature conservation. In the European Union (EU), the Birds and Habitats Directives are the most important policies for conservation strategy, legally preserving Europe's characteristic, rare, endemic and threatened biota. We used occurrence data for species listed in the directives' Annexes to assess the uniqueness of major PAs in the EU (National Parks, Biosphere Reserves); this is important for preserving the EU's focal species. We developed a novel, multifunctional approach to calculate different metrics of conservation value that represent different components of species diversity within the PAs, involving inventory diversity, deviation from the species-area relationship, species rarity and differentiation diversity. Applying it, we found that individual PAs frequently vary considerably in their scores on different components, which are often disconnected from PA size. PAs around the EU periphery, often containing few species, are key to conserving species that are rare in the EU. Because our analysis focuses on EU priority species and includes different components of diversity, it allows more appropriate estimation of conservation value inside PAs in context of the EU than recent, high-profile, global-level research. We offer tools to evaluate, and information to regulate, the representativeness, persistence and efficiency of PAs.

Skilful forecasting of global fire activity using seasonal climate predictions.

Societal exposure to large fires has been increasing in recent years. Estimating the expected fire activity a few months in advance would allow reducing environmental and socio-economic impacts through short-term adaptation and response to climate variability and change. However, seasonal prediction of climate-driven fires is still in its infancy. Here, we discuss a strategy for seasonally forecasting burned area anomalies linking seasonal climate predictions with parsimonious empirical climate-fire models using the standardized precipitation index as the climate predictor for burned area. Assuming near-perfect climate predictions, we obtained skilful predictions of fire activity over a substantial portion of the global burnable area (~60%). Using currently available operational seasonal climate predictions, the skill of fire seasonal forecasts remains high and significant in a large fraction of the burnable area (~40%). These findings reveal an untapped and useful burned area predictive ability using seasonal climate forecasts, which can play a crucial role in fire management strategies and minimise the impact of adverse climate conditions.

Exacerbated fires in Mediterranean Europe due to anthropogenic warming projected with non-stationary climate-fire models.

The observed trend towards warmer and drier conditions in southern Europe is projected to continue in the next decades, possibly leading to increased risk of large fires. However, an assessment of climate change impacts on fires at and above the 1.5 °C Paris target is still missing. Here, we estimate future summer burned area in Mediterranean Europe under 1.5, 2, and 3 °C global warming scenarios, accounting for possible modifications of climate-fire relationships under changed climatic conditions owing to productivity alterations. We found that such modifications could be beneficial, roughly halving the fire-intensifying signals. In any case, the burned area is robustly projected to increase. The higher the warming level is, the larger is the increase of burned area, ranging from ~40% to ~100% across the scenarios. Our results indicate that significant benefits would be obtained if warming were limited to well below 2 °C.

On the key role of droughts in the dynamics of summer fires in Mediterranean Europe.

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.

Ecosystem services in European protected areas: Ambiguity in the views of scientists and managers?

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.

On the dynamics of a generalized predator-prey system with Z-type control.

We apply the Z-control approach to a generalized predator-prey system and consider the specific case of indirect control of the prey population. We derive the associated Z-controlled model and investigate its properties from the point of view of the dynamical systems theory. The key role of the design parameter λ for the successful application of the method is stressed and related to specific dynamical properties of the Z-controlled model. Critical values of the design parameter are also found, delimiting the λ-range for the effectiveness of the Z-method. Analytical results are then numerically validated by the means of two ecological models: the classical Lotka-Volterra model and a model related to a case study of the wolf-wild boar dynamics in the Alta Murgia National Park. Investigations on these models also highlight how the Z-control method acts in respect to different dynamical regimes of the uncontrolled model.