Biology subjects

Collalti, A.

Publications and source records attributed to Collalti, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Reconciling intrinsic and ecosystem water-use efficiency reveals physiological mechanisms underlying carbon-water coupling across biological scales

Understanding how carbon-water coupling scales from leaves to ecosystems remains a major challenge because water-use efficiency (WUE) metrics integrate physiological, hydrological, and ecological processes. We integrated tree-ring width, triple stable isotopes ({delta}13C, {delta}18O and {delta}2H), eddy covariance (EC) observations, and a process-based model to investigate the drivers of intrinsic (iWUE) and ecosystem water-use efficiency (WUEeco) across biological scales in a mature Fagus sylvatica forest between 2004 and 2023. Modelled and isotope-derived iWUE were strongly correlated (r = 0.61, p < 0.05) and both indicated an approximately 20% long-term increase, consistent with increasing gross primary productivity. In contrast, WUEeco derived from EC was lower than model estimates and exhibited a positive trend not reproduced by the model. This divergence primarily reflected differences in biological representation and hydrological integration, as the single-species model underestimated ecosystem evapotranspiration by excluding co-occurring deciduous and evergreen species together with understory vegetation. Triple-isotope analyses showed that the long-term increase in iWUE was driven by enhanced photosynthetic assimilation rather than sustained stomatal closure, whereas {delta}18O and {delta}2H variability was mainly controlled by source-water dynamics. These findings provide a mechanistic framework for reconciling leaf- and ecosystem-scale WUE and improving predictions of forest carbon-water coupling under climate change.

ecology↗

bioRxiv2026

Climate change threatens the productivity stability of Italian forests

Mediterranean forests are emerging as one of the clearest hotspots of climate-change impacts, where rapid warming and increasingly severe droughts and heatwaves are pushing forest ecosystems toward their physiological and functional limits. These pressures threaten productivity, carbon dynamics, ecosystem stability, and the services forests provide. In this context, a process-based forest ecosystem model was used to assess climate-driven changes in carbon dynamics and productivity stability across Italian forests within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) framework. 5135 plots were simulated, corresponding to ~80% of the field plots included in the second Italian National Forest Inventory (INFI). Model simulations were first evaluated against independent observations of gross primary production (GPP) from satellite-based products and forest carbon variables from the third INFI. Forest dynamics from 2015 to 2100 were simulated under three CMIP6-based emission scenarios (SSP1-2.6, SSP3-7.0, and SSP5-8.5) using two climate forcings (GFDL-ESM4 and UKESM1-0-LL). Future responses were assessed for GPP, aboveground biomass, growing stock volume, and carbon stocks, while variability in GPP was quantified using the coefficient of variation as an indicator of forest stability. Results show that the model reproduced the main spatial and temporal patterns of forest productivity and carbon stocks. Future projections revealed strong spatial heterogeneity and increasing divergence among scenarios after mid-century. GPP showed the earliest and strongest response to climate change, with mountain forests generally maintaining or increasing productivity and exhibiting greater stability, whereas coastal forests showed pronounced productivity declines and increasing variability, particularly under higher-emission scenarios and more extreme climate forcing. In contrast, carbon stocks generally continued to increase throughout the century, although carbon accumulation progressively slowed toward the end of the century, particularly under higher-emission scenarios.

ecology↗

bioRxiv2026

Natural and planted forests differ in the mechanisms regulating productivity and stability

Forest productivity and stability underpin ecosystem functioning and services, yet whether the drivers and mechanisms regulating these properties differ between natural and planted forests at large spatial scales remains unclear. Using data from 2,389 forest plots across China and a novel analytical framework, we systematically compared productivity and stability between natural and planted forests and identified their dominant drivers and underlying mechanisms across 38 biotic, structural, climatic, and edaphic variables. We found that natural forests were 14% more productive and 34% more stable than planted forests, although these differences varied across ecoregions and stand development stages. Productivity in natural forests was primarily driven by functional diversity and functional traits, supporting the niche complementarity and mass-ratio hypotheses, whereas nitrogen availability emerged as the dominant regulator of productivity in planted forests. Likewise, stability shifted from diversity-related regulation in natural forests to stronger abiotic control in planted forests, while functional diversity remained a key stabilizing mechanism in both forest types, supporting the insurance hypothesis. We also found that planted forests were more sensitive to hydroclimatic variability, indicating greater vulnerability to drought. Our findings reveal a fundamental shift in the mechanisms regulating forest productivity and stability from diversity-mediated control in natural forests to stronger abiotic regulation in planted forests, highlighting the importance of integrating biodiversity conservation and nitrogen management to sustain forest productivity and stability under future climate change.

ecology↗

bioRxiv2026

Decadal climate-driven decoupling between gross primary productivity and tree growth in Mediterranean forests

Mediterranean forests are becoming increasingly vulnerable under climate change, as the growing frequency and intensity of droughts and heatwaves amplify physiological stress, reduce productivity, and heighten the risk of large-scale disturbances. Yet vegetation activity trends, as revealed by remote sensing, may obscure divergent responses between photosynthetic activity and growth, a critical early warning of forest vulnerability. Therefore, the long-term relationship between photosynthesis and tree growth remains poorly understood at regional scales, especially in Mediterranean areas. To address this challenge, we applied a mechanistic, process-based forest ecosystem model across approximately 2,400 km{superscript 2} of Mediterranean forests in southern Italy, encompassing a heterogeneous landscape characterized by diverse stand structures and species dominance. This framework enabled us to explicitly trace carbon fluxes from gross primary productivity (GPP) through allocation processes to average tree growth. By mean of a factorial approach, we identify over extended areas an emergent spatial pattern of divergence of summer GPP and radial tree growth amplified in space and time by the climate variability of the last two decades and shaped by forest legacy. Our findings reveal also that canopy-level greening can mask structural vulnerability and previsual decline across Mediterranean forests. Data show as an apparent long-term trend in photosynthesis decline during summer, not necessarily translates to tree growth decline. Improving our ability to determine if, where and when a key change in forest behaviour will occurs, remains essential for designing effective restoration measure and anticipating tipping points in forest resilience under accelerating climate change.

ecology↗

bioRxiv2026

Investigating climate-phenology relationships among the most common Italian forest species using Sentinel-2-derived vegetation phenology and productivity products

Climate change is profoundly altering forest phenology and productivity across Europe, with particularly strong impacts in Mediterranean regions characterized by high climatic heterogeneity. Understanding how climatic and site-specific drivers regulate the start, end, and length of the growing season, and how these phenological shifts translate into productivity responses, remains a key challenge for predicting forest carbon dynamics. In this study, we investigate phenological timing and total seasonal productivity across multiple Italian forest species spanning Mediterranean, temperate, and mountain environments, leveraging the new High-Resolution Vegetation Productivity and Phenology product from the Copernicus Land Monitoring Service, machine learning (random forests) modeling, and explainable artificial intelligence analysis (SHAP). Our results confirm a general lengthening of the growing season driven mainly by chilling accumulation and spring temperatures. Warmer conditions advance the start of the season by 1-10 days across species, while the combined effects of temperature, radiation, and moisture can extend the growing season by up to 20-30 days. End-of-season dynamics and season length are more strongly controlled by light and water availability than by temperature alone. In several Mediterranean species, the end of the season can advance by up to 40 days due to summer drought, high vapor pressure deficit, and site exposure. Mediterranean species often show compensatory shifts between season onset and senescence, maintaining a relatively stable length of the season, whereas mountain species exhibit a tighter coupling between delayed onset and shortened season length. Phenological shifts are frequently decoupled from productivity, which is mainly regulated by energy and water availability, highlighting species- and site-specific responses to climate change. The findings of this study highlight the substantial advantage of remote sensing data, coupled with machine learning approaches, for advancing the understanding of forest phenology and productivity across broad spatial and climatic gradients.

ecology↗

bioRxiv2026

Loss of competitive strength in European conifer species under climate change

Climate change is expected to alter species assemblages by affecting the outcome of competition between species. Investigating processes of competition remains challenging particularly in tree communities, as they unfold over extensive spatio-temporal scales. Here, we developed a deep-learning approach to leverage a novel database of 135 million simulated local-scale tree responses to climate across continental Europe to investigate changes in the competitiveness of nine major tree species under different scenarios of climate change. Specifically, we trained a Deep Neural Network on local process model projections to investigate climate change effects on indicators of competitive strength and species dominance. We found decreasing competitive strength for all investigated evergreen coniferous species across their distribution, while major deciduous broadleaved species such as Quercus robur and Fagus sylvatica increased in competitiveness. Changes in tree species competition with climate differed locally, but most investigated species lost competitive strength at their warm range edges. As a consequence of these changes, up to 19% of Europes forests could experience a change in the dominant tree species until the end of the 21st century. Our results suggest a profound climate-induced reassembly of Europes forests and identify areas that may require specific attention in forest policy and management.

ecology↗

bioRxiv2025

Long-term forest-sector mitigation and radiative forcing under contrasting management, climate, and substitution pathways

Forests are central to the EUs climate neutrality strategy, currently offsetting [~]9% of total greenhouse gas emissions and offering further mitigation potential through harvested wood products and the substitution effect. However, the climate benefit of the forest sector is influenced by multiple interacting factors, including forest management, climate change, wood-use strategies, and assumptions about substitution benefits, as well as the timing and fate of carbon across the forest ecosystem and technosphere. To evaluate these drivers, we used a coupled forest growth and a wood products model to simulate five different silvicultural strategies under three climate change scenarios, four wood use schemes, and five displacement factor decay pathways over a 285-year period (2015-2300), applied to a Pinus nigra forest in Italy, questioning the impact of these factors on climate mitigation potential of the forest sector. We assessed forest sector balance (FSB, net carbon exchange between forest system and atmosphere), radiative forcing from biogenic CO2 (RFbio), and mitigation efficiency (ME) - the proportion of sequestered carbon contributing to net climate benefit. Results showed that FSB and RFbio were "broadly" aligned, but ME varied with the magnitude and duration of biogenic emissions. The scenarios BIOE (bioenergy) and TM (modular cutting) achieved high FSB but showed lower ME due to concentrated or sustained emissions. WOOD (promotion of long-lived wood) and ADAPT (adaptation management) yielded higher ME under SSP1-2.6, while several strategies (WOOD, ADAPT, TRANS) became net sources under SSP5-8.5 after 2200. Substitution benefits declined under degressive assumptions, reducing mitigation by up to 53% especially for high-harvest scenarios. FSB was primarily shaped by climate and management, secondly by substitution, however; wood-use strategies had no significant long-term effect provided they did not impact resource availability. Together, these findings underscore that effective forest-sector mitigation requires not only maximizing cumulative carbon stocks, but also minimizing the magnitude, timing, and atmospheric residence time of emissions while carefully considering the role of substitution benefits. HighlightsO_LIThe long-term forest sector carbon balance is mainly governed by active management, climate conditions, and wood substitution pathways. C_LIO_LIForest Sector Balance as a metric is "broadly" aligned with the radiative forcing from biogenic emissions C_LIO_LIThe mitigation efficiency of forest sector options depends on emissions timing, duration, and amplitude C_LIO_LISubstitution factors also known as displacement factors need to be considered with greater caution C_LI

ecology↗

bioRxiv2025

Enhancing ecosystem service provision through the silvicultural management of European black pine stands from afforestation and reforestation

Afforestation and reforestation are integral components of the wider field of land management. When these initiatives integrate the diverse eco-biological, landscape, cultural, and socioeconomic characteristics of the intervention area they can achieve substantial environmental improvements also by improving ecosystem functions, commonly referred to as ecosystem services (ES). European black pines are some of most frequently used tree species for afforestation and reforestation in Mediterranean regions, thanks to their ability to grow in poor soil conditions and their resistance to environmental stressors. In this study, we adopted a validated process-based modeling approach to explore the effects of thinning intensity and frequency on the provision of some ES from European black pine stands, which have been established through afforestation and reforestation in Italy. We found a net financial gain when basal area removal reaches 25% with a 25-year thinning interval, highlighting the higher financial efficiency of more intensive interventions. Non-provisioning ES (erosion protection, carbon sequestration, and aesthetic/recreational value) tend to decrease with increased basal area removal and benefit from longer intervals between thinning. Remarkably, the economic values of aesthetic appeal and carbon sequestration far exceed those of timber production and erosion protection, regardless of thinning regime. Based on our results, we claim that strategic, long-term planning of thinning operations is essential to ensure a balanced trade-off between wood production and other ES while maintaining the cost-effectiveness of operations. Ultimately, our approach can provide guidelines for forest managers to ensure the provision of multiple ES.

ecology↗

bioRxiv2024

R3DFEM: an R package for running the 3D-CMCC-FEM model

Forest ecosystems account for about one-third of the Earths land area, and monitoring their structure and dynamics is essential for understanding the lands carbon cycle and their role in the greenhouse gas balance. In this framework, process-based forest models (PBFMs) allow studying, monitoring and predicting forest growth and dynamics, capturing spatial and temporal patterns of carbon fluxes and stocks. The Three Dimensional-Coupled Model Carbon Cycle - Forest Ecosystem Module (3D-CMCC-FEM) is a well-known eco-physiological, biogeochemical, biophysical process-based model, able to simulate energy, carbon, water and nitrogen fluxes and their allocation in homogeneous and heterogenous forest ecosystem. The model is specifically designed to represent forest stands, from simple ones to those with complex structures, involving several cohorts competing for light and other resources in a prognostic way. Currently, the model is implemented in C-language, which can be challenging for the broad public to use, and thus limiting its applications. In this paper, we present the open-source R package R3DFEM which introduces efficient methods for: i) generating and handling input data needed for the model initialization; ii) running model simulations with different set up and exploring input; and iii) plotting output data. The functions in the R-package are designed to be user-friendly and intended for all R users with little to advanced coding skills, who aim to perform simulations using the 3D-CMCC-FEM. Here we present the package and its functionalities using some real case study and model applications.

bioinformatics↗

bioRxiv2024

Assessing the combined effects of forest management and climate change on carbon and water fluxes in European beech forests

The consequences of climate change continue to threaten European forests, particularly for species located at the edges of their latitudinal and altitudinal ranges. While extensively studied in Central Europe, European beech forests require further investigation to understand how climate change will affect these ecosystems in Mediterranean areas. Proposed silvicultural options increasingly aim at sustainable management to reduce biotic and abiotic stresses and enhance these forest ecosystems resistance and resilience mechanisms. Process-based models (PBMs) can help us to simulate such phenomena and capture early stress signals while considering the effect of different management approaches. In this study, we focus on estimating sensitivity of two state-of-the-art PBMs forest models by simulating carbon and water fluxes at the stand level to assess productivity changes and feedback resulting from different climatic forcings as well as different management regimes. We applied the 3D-CMCC-FEM and MEDFATE forest models for carbon (C) and water (H2O) fluxes in in two sites of the Italian peninsula, Cansiglio in the north and Mongiana in the south, under managed vs. unmanaged scenarios and under current climate and different climatic scenarios (RCP4.5 and RCP8.5). To ensure confidence in the models results, we preliminary evaluated their performance in simulating C and H2O flux in three additional beech forests of the FLUXNET network along a latitudinal gradient spanning from Denmark to central Italy. The 3D-CMCC-FEM model achieved R{superscript 2} values of 0.83 and 0.86 with RMSEs of 2.53 and 2.05 for C and H2O fluxes, respectively. MEDFATE showed R{superscript 2} values of 0.76 and 0.69 with RMSEs of 2.54 and 3.01. At the Cansiglio site in northern Italy, both models simulated a general increase in C and H2O fluxes under the RCP8.5 climate scenario compared to the current climate. Still, no benefit in managed plots compared to unmanaged ones, as the site does not have water availability limitations, and thus, competition for water is low. At the Mongiana site in southern Italy, both models predict a decrease in C and H2O fluxes and sensitivity to the different climatic forcing compared to the current climate; and an increase in C and H2O fluxes when considering specific management regimes compared to unmanaged scenarios. Conversely, under unmanaged scenarios plots are simulated to experience first signals of mortality prematurely due to water stress (MEDFATE) and carbon starvation (3D-CMCC-FEM) scenarios. In conclusion, while management interventions may be considered a viable solution for the conservation of beech forests under future climate conditions at moister sites like Cansiglio, in drier sites like Mongiana conservation may not lie in management interventions alone.

ecology↗

bioRxiv2024

Emissions of climate-altering species from open vegetation fires in the Mediterranean region

The climate change over the Mediterranean region poses serious concerns about the role of open vegetation fires in the emissions of climate-altering species. The aim of this work is to review the current methodologies for quantifying the emissions of greenhouse gases and black carbon from open vegetation fires, as well as the data provided by four state-of-the-art inventories of emissions of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O) and black carbon (BC) in the Mediterranean region for the period 2003 - 2020. A limited number of studies specifically addressed the quantification of emissions from open fires in the Mediterranean region. Our data review of fire emissions in the Mediterranean region, where "top-down" methods have not yet implemented, reveals discrepancies across the four inventories examined (GFED v4.1s, GFAS v1.2, FINN v2.5, and EDGAR v8.0). Among these, FINN v2.5 consistently reported the highest emissions, while GFED v4.1s reported the lowest. We observed that the relative ranking of total emissions between the inventories varied for the species considered (e.g. CO2 vs. CH4) and that different proportions of emissions were attributed to the individual countries included in the Mediterranean domain. We argued that these differences were related to the different spatial resolutions of the input data used to detect the occurrence of fires, the different approaches to calculating the amount of fuel available, and the emission factors used. The three inventories reporting wildfire emissions were consistent in identifying the occurrence of peaks in the emissions for the years 2007, 2012 and 2017. We hypothesized that La Nina events could partially contribute to triggering the occurrence of these emission peaks. To increase the accuracy and consistency of climate-altering emission data related to open vegetation fires in the Mediterranean region, we recommend to integrate bottom-up approaches with top-down inversion methods based on satellite and in-situ atmospheric observations.

ecology↗

bioRxiv2024

Stand Age and Climate Change Effects on Carbon Increments and Stock Dynamics

Carbon assimilation and wood production are influenced by environmental conditions and endogenous factors, such as species auto-ecology, age, and hierarchical position within the forest structure. Disentangling the intricate relationships between those factors is more pressing than ever due to climate changes pressure. We employed the 3D-CMCC-FEM model to simulate undisturbed forests of different ages under four climate change scenarios (plus one no climate change) from five Earth System Models. In this context, carbon stocks and increment were simulated via total car-bon woody stocks and mean annual increment, which depends mainly on climate trends. We find greater differences among different age cohorts under the same scenario than in different climate scenarios under the same age class. Increasing temperature and changes in precipitation patterns led to a decline in above-ground biomass in spruce stands, espe-cially in the older age classes. On the contrary, the results show that beech forests at DK-Sor will maintain and even increase C-storage rates under most RCP scenarios. Scots pine forests show an intermediate behavior with a stable stock capacity over time and in different scenarios but with decreasing mean volume annual increment. These results confirm current observations worldwide that indicate a stronger climate-related decline in conifers forests than in broadleaves.

ecology↗

bioRxiv2024

Changes in Mean Seasonal Carbon Cycle Due to Climate Change

Through photosynthesis, forests absorb annually large amounts of atmospheric CO2. However, they also release CO2 back through respiration. These two, opposite in sign, large fluxes determine, much of the carbon that is stored or released back to the atmosphere. The mean seasonal cycle (MSC) is an interesting metric that associates phenology and carbon (C) partitioning-allocation analysis within forest stands. Here we applied the 3D-CMCC-FEM model and analyzed its capability to represent the main C-fluxes, by validating the model against observed data, questioning if the sink/source mean seasonality is influenced under two scenarios of climate change, in five contrasting European forest sites. We found the model has, under current climate conditions, robust predictive abilities in estimating NEE. Model results also predict a consistent reduction of the forests capabilities to act as a C-sink under climate change and stand-ageing at all sites. Such a reduction is predicted despite the number of annual days of C-sink in evergreen forests increasing over the years, indicating a consistent downward trend. Similarly, deciduous forests, despite maintaining a relatively stable number of C-sink days throughout the year and over the century, show a reduction in their overall annual C-sink capacity. Overall, both types of forests at all sites show a consistent reduction in their future mitigating potential.

ecology↗

bioRxiv2024

Impacts Of Deforestation And Land Use/Land Cover Change On Carbon Stock And Dynamics In The Jomoro District, Ghana

Tropical deforestation in the African continent plays a key role in the global carbon cycle and bears significant implications in terms of climate change and sustainable development. Especially in Sub-Saharan Africa, where more than two-thirds of the population rely on forest and woodland resources for their livelihoods, deforestation and land use changes for crop production lead to a substantial loss of ecosystem-level carbon stock. Unfortunately, the impacts of deforestation and land use change can be more critical than in any other region, but these are poorly quantified. We analyse changes in the main carbon pools (above- and below-ground, soil and litter, respectively) after deforestation and land use/land cover change, for the Jomoro District (Ghana), by assessing the initial reference level of carbon stock for primary forest and the subsequent stock changes and dynamics as a consequence of conversion to the secondary forest and to six different tree plantations (rubber, coconut, cocoa, oil palm, and mixed plantations). Results indicate overall a statistically significant carbon loss across all the land uses/covers and for all the carbon pools compared to the primary forest with the total carbon stock loss ranging between 85% and 35% but with no statistically significant differences observed in the comparison between primary forest and mixed plantations and secondary forest. Results also suggest that above-ground carbon and soil organic carbon are the primary pools contributing to the total carbon stocks but with opposite trends of carbon loss and accumulation. Strategies for sustainable development, policies to reduce emissions from deforestation and forest degradation, carbon stock enhancement (REDD+), and planning for sustainable land use management should carefully consider the type of conversion and carbon stock dynamics behind land use change for a win-win strategy while preserving carbon stocks potential in tropical ecosystems.

ecology↗

bioRxiv2024

TimberTracer: A Comprehensive Framework for the Evaluation of Carbon Sequestration by Forest Management and Substitution of Harvested Wood Products.

BackgroundHarvested wood products (HWPs) have a pivotal role in climate change mitigation, a recognition solidified in many Nationally Determined Contributions (NDCs) under the Paris Agreement. Integrating HWPs greenhouse gas (GHG) emissions and removals into accounting requirements relies on typical decision-oriented tools known as wood product models (WPMs). The study introduces the TimberTracer (TT) framework, designed to simulate HWP carbon stock, substitution effects, and emissions from wood decay and bioenergy. ResultsCoupled with the 3D-CMCC-FEM forest growth model, TimberTracer was applied to Laricio Pine (Pinus nigra subsp. laricio) in Italys Bonis watershed, evaluating three forest management practices (clearcut, selective thinning, and shelterwood) and four wood-use scenarios (business as usual, increased recycling rate, extended average lifespan, and a simultaneous increase in both the recycling rate and the average lifespan) over a 140-year planning horizon, to assess the overall carbon balance of HWPs. Furthermore, this study evaluates the consequences of disregarding landfill methane emissions and relying on static substitution factors, assessing their impact on the mitigation potential of various options. This investigation, covering HWPs stock, carbon (C) emissions, and the substitution effect, revealed that selective thinning emerged as the optimal forest management scenario. In addition, a simultaneous 10% increase in both the recycling rate and half-life, under the so-called "sustainability" scenario, proved to be the optimal wood-use strategy. Finally, the analysis shows that failing to account for landfill methane emissions and the use of dynamic substitution can significantly overestimate the mitigation potential of various forest management and wood-use options, which underscores the critical importance of a comprehensive accounting in climate mitigation strategies involving HWPs. ConclusionsOur study highlights the critical role of harvested wood products (HWPs) in climate change mitigation, as endorsed by multiple Nationally Determined Contributions (NDCs) under the Paris Agreement. Utilizing the TimberTracer framework coupled with the 3D-CMCC-FEM forest growth model, we identified selective thinning as the optimal forest management practice. Additionally, enhancing recycling rates and extending product lifespan effectively bolstered the carbon balance. Moreover, this study emphasizes the necessity of accounting for landfill methane emissions and dynamic product substitution, as failing to do so may significantly overestimate the mitigation potential of implemented projects. These findings offer actionable insights to optimize forest management strategies and advance climate change mitigation efforts.

ecology↗

bioRxiv2023

Integrating annual radial growth analyses and carbon isotope discrimination to forecast early warning of beech forest dieback across the Italian Peninsula

Tree mortality and forest dieback episodes are increasing due to drought and heat stress. Nevertheless, a comprehensive understanding of mechanisms enabling trees to withstand and survive droughts remains lacking. Our study investigated basal area increment (BAI), and {delta}13C- derived intrinsic water-use-efficiency (iWUE), to elucidate beech resilience across four healthy stands in Italy with varying climates and water availability. Additionally, fist-order autocorrelation (AR1) analysis was performed to detect early warning signals for potential tree dieback risks during extreme drought events. Results reveal a negative link between BAI and vapour pressure deficit (VPD), especially in southern latitudes. After the 2003 drought, BAI decreased at the northern site, with an increase in {delta}13C and iWUE, indicating conservative water-use. Conversely, the southern sites showed increased BAI and iWUE, likely influenced by rising CO2 and improved water availability. In contrast, the central site sustained higher transpiration rates due to higher soil water holding capacity (SWHC). Despite varied responses, most sites exhibited reduced resilience to future extreme events, indicated by increased AR1. Temperature significantly affected beech iWUE and BAI in northern Italy, while VPD strongly influenced the southern latitudes. The observed increase in BAI and iWUE in southern regions might be attributed to an acclimation response.

plant biology↗

bioRxiv2023

Stand age diversity dampens forests sensitivity to climate change

Stand age significantly influences the functioning of forest ecosystems by shaping structural and physiological plant traits, affecting water and carbon budgets. Forest age distribution is determined by the interplay of tree mortality and regeneration, influenced by both natural and anthropogenic disturbances. Thus, human-driven alteration of tree age distribution presents an underexplored avenue for enhancing forest stability and resilience. In our study, we investigated how age distribution impacts the stability and resilience of the forest carbon budget under both current and future climate conditions. We employed a biogeochemical model on three historically managed forest stands, projecting their future as undisturbed systems, i.e., left at their natural evolution with no management interventions. The model, driven by climate data from five Earth System Models under four representative climate scenarios and one baseline scenario, spanned 11 age classes for each stand. Our findings indicate that Net Primary Production (NPP) peaks in the young and middle-aged classes (16- to 50-year-old), aligning with ecological theories, regardless of the climate scenario. Under climate change, the beech forest exhibited an increase in NPP and maintained stability across all age classes, while resilience remained constant with rising atmospheric CO2 and temperatures. However, NPP declined under climate change scenarios for the Norway spruce and Scots pine sites. In these coniferous forests, stability and resilience were more influenced. These results underscore the necessity of accounting for age classes and species-specific reactions in evaluating the impacts of climate change on forest stability and resilience. We, therefore, advocate for customized management strategies that enhance the adaptability of forests to changing climatic conditions, taking into account the diverse responses of different species and age groups to climate.

plant biology↗

bioRxiv2023

Regional estimates of gross primary production applying the process-based model 3D-CMCC-FEM vs. multiple datasets

Process-based Forest Models (PBFMs) offer the possibility to capture important spatial and temporal patterns of both carbon fluxes and stocks in forests, accounting for ecophysiological, climate and geographical variability. Yet, their predictive capacity should be demonstrated not only at the stand-level but also in the context of large spatial and temporal heterogeneity. For the first time, we apply a stand scale process-based model (3D-CMCC-FEM) in a spatially explicit manner at 1 km spatial resolution in a Mediterranean region in southern Italy. Specifically, we developed a methodology to initialize the model that comprehends the use of spatial information derived from the integration of remote sensing (RS) data, the national forest inventory data and regional forest maps to characterize structural features of the main forest species. Gross primary production (GPP) is simulated over the period 2005-2019 and the multiyear predictive capability of the model in simulating GPP is evaluated both aggregated as at species-level by means of independent multiple data sources based on different RS-based products. We show that the model is able to reproduce most of the spatial ([~]2800 km2) and temporal (32 years in total) patterns of the observed GPP at both seasonal, annual and interannual time scales, even at the species-level. These new very promising results open the possibility of applying the 3D-CMCC- FEM confidently and robustly to investigate the forests behavior under climate and environmental variability over large areas across the highly variable ecological and bio- geographical heterogeneity of the Mediterranean region. Key PointsO_LIWe apply a process-based forest model on a regular grid at 1 km spatial resolution in a Mediterranean region. C_LIO_LIInitial forest state is estimated using spatially explicit input data derived from remote sensing and national forest inventory data. C_LIO_LIThe 3D-CMCC-FEM shows comparably estimates in simulating both spatial and temporally the gross primary production, when compared to independent satellite-based products. C_LI

ecology↗