Agroforestry is increasingly promoted in Mediterranean regions as a strategy to enhance system resilience and multifunctionality, although evidence remains limited for modern alley cropping systems. We report findings from a 14-year alley-cropping experiment conducted in Sagàs (northeastern Spain) combining hybrid walnut (Juglans × intermedia Mj209 x Ra) with sage (Salvia officinalis, years 1–7) and lemon balm (Melissa officinalis, years 8–14), compared with respective monoculture systems. Linear mixed-effects models, accounting for repeated measurements, were used to assess crop and tree performance and micro-site modifications over time. During the first crop phase, sage productivity was driven primarily by interannual climate variability, with no significant treatment differences. In contrast, progressive tree canopy development during the second phase reduced understory light availability (up to 50

Forest management is crucial for climate change mitigation, particularly in Mediterranean forests, which serve as significant carbon pools but face increasing climate threats. This study assesses the impact of different forest management strategies on the carbon balance of Mediterranean forests in Catalonia (NE Spain) under two climate scenarios (RCP 4.5 and RCP 8.5). We simulate forest dynamics over 100 years and apply a Life Cycle Assessment approach to quantify carbon fluxes associated with four contrasting management strategies: (i) Business-as-usual, (ii) Promotion of wood energy, (iii) Carbon storage, and (iv) Ecohydrological-based management. Our results indicate that management strongly influences the carbon balance, often outweighing the effect of climate change. The carbon storage scenario exhibited the highest net sequestration due to extended rotations and the production of long-lived wood products, while the Promotion of wood energy scenario led to higher emissions, resulting in carbon losses in low-productivity Pinus nigra forests. Manufacturing dominated emissions (50–75%), while forest growth accounted for most uptake (77%). Our findings indicate that climate-smart forestry in Mediterranean landscapes should prioritize strategies that balance productivity, resilience, and carbon storage. Ecohydrological management stands out as a scalable pathway for the fragmented private forests typical of the region, while carbon-storage practices may be selectively applied in productive and well-protected stands.

In Mediterranean forests, the increasing frequency of high severity fires poses a challenge to current landscape management. In addition, these areas are experiencing a generalized process of landscape homogenization leading to a major risk of large fires. In this context, it is important to understand how wildfires (e.g. fire severity) influence changes in landscape heterogeneity. Our objectives were (1) to evaluate how pre-fire landscape conditions influence the post-fire dynamics of landscape heterogeneity both in terms of composition and configuration and (2) to understand how variability in fire severity affects changes in the structural heterogeneity of landscapes. We analyzed 225 landscapes within 45 fire perimeters that occurred between 2002 and 2004 in Spain. We used a novel land cover database and fire severity data to assess post-fire landscape heterogeneity dynamics. Landscapes with higher pre-fire diversity values were more stable (in both composition and configuration) than more homogeneous landscapes. Additionally, we identified a significant interaction between fire severity and pre-fire landscape configuration. This interaction showed that high variations in fire severity decreased the size of small and medium pre-fire patches but increased the size of larger pre-fire patches. This work provides valuable insights into the effects of fire on mid-term (11–13 years after fire) landscape configuration and composition. The results highlight the importance of fire severity variability. They emphasize the need to consider the role of fire in landscape management, as this could help reduce the vulnerability of Mediterranean forests.

Aims Rapid revegetation of burnt forest is essential for recovering ecosystem functioning, especially in the context of climate change-driven shifts in fire regime. This study aimed to provide a comprehensive understanding of how abiotic factors (topography, fire behaviour) and biotic factors (pre-fire forest characteristics, plant reproductive strategies, land-use trajectories) influence the recovery of Pinus halepensis forests, identifying regeneration vulnerabilities that could inform management practices.Location A P. halepensis forest burnt in 2019 (4000 ha) in NE Iberian Peninsula.Methods We established 72 sampling sites within the burnt forest, covering gradients of pre-fire canopy cover (PCC), topography, fire severity and land-use history. At each site, we recorded the abundance of P. halepensis seedlings within a 100-m2 plot. We also conducted a floristic inventory of all associated woody species along two parallel 20-m transects to assess woody species cover, richness and distribution. Woody species were classified based on their post-fire reproductive strategies (obligate seeding, facultative resprouting and resprouting) to explore the relationship between functional characteristics and plant distribution along the studied gradients.Results Northern exposures enhanced the abundance of P. halepensis, whereas coexisting woody species cover was higher on southern ones, probably due to the contribution of obligate seeders, as fire-responsive reproductive traits vary along the north-south gradient. PCC boosted pine regeneration and species richness, while high fire severity reduced both cover and richness of woody species, likely due to damage to reproductive structures.Conclusions We show that the drivers of post-fire regeneration influence in different and even divergent ways the vegetation components considered (canopy and shrub layer), as in the case of aspect. From a management perspective, post-fire forest interventions should be tailored to restoration objectives and to the post-fire vegetation communities that better respond to them.

In this work we showcase the in-progress results from the FirePATHS project (PID2020-116556RA-I00). The project aims to assess the evolution of fire danger under different emission and forest management scenarios through the explicit interaction of the climate-vegetation-fire system. For this purpose, a methodological framework combining different simulation models of the elements of this system is proposed. The core of the process lies in the modeling of vegetation dynamics at stand scale according to different trajectories of climatic evolution to characterize the state and typology of fuels and the subsequent simulation of potential fire behavior during the 21st century.We analyzed a set of 114 Pinus halepensis plots, surveyed in the field during 2017; 68 plots burned during the summer of 1994 and 46 unburned control stands. We used the medfate model to simulate forest functioning and dynamics, which provides the necessary fuel model parameters to be entered into fire behavior models (Fuel Characteristics Classification System, implemented in medfate as well). The combination of these two approaches provides time-varying estimates of fire behavior metrics (e.g., flame length or rate of spread). The simulation was conducted under SSP climate scenarios (SSP 126, 245, 370 and 585) depicting different levels of climate warming, vegetation dynamics and, hence, fire danger. Likewise, we devised a set of forest management prescriptions aimed at reducing climate vulnerability of tree communities and reducing extreme wildfire potentials. A baseline scenario with no management was also assessed.We observed very contrasting trajectories between burned and control stands, with the first leading to increasing fuel loads, except in SSP 585. Fire potentials depicted a significant increase in surface fire behavior, with adaptive and mitigation management being able to mitigate it to some extent.

In recent years, multiple remote sensing technologies have been used to quantify aboveground biomass (AGB) at different scales, from regionally trained models to global maps. The former are capable of providing higher resolution and accurate estimations albeit for smaller regions. Tailoring model weights and inputs to a specific biome or region have proved to be effective to obtain better results. Global maps, on the other hand, provide an attempt to standardizing AGB mapping at slightly to moderately lower resolutions and tend to have differences between them. A similar standardization with the benefits of regional mapping, applied across biomes, has yet to be available. For that, the first step would be comprehensively comparing state-of-the-art regional and local studies. However, existing inconsistencies in the different models and inputs used, which are often region-specific, make it impracticable. This study addresses the need for a comparison of a single methodology consistent across different biomes in order to understand the nuances that drive the estimation of AGB. We present a data fusion approach to mapping aboveground biomass at a 20m resolution using regionally trained, regression-enhanced Random Forests in 4 different biomes: semi-arid savannas in the Sahel region, dense tropical forests in Brazil, Mediterranean forests in coastal and pre-coastal areas of Catalonia, and temperate/boreal forests in Minnesota. GEDI L4A AGB data (25-m discrete footprints) is used to train a regression model in each study area. We derived predictors from Sentinel-1 SAR, Sentinel-2 multi-spectral and Digital Elevation Model (DEM) datasets, which are common for all locations. Additionally, auxiliary data such as proximity to coastlines, human-made structures or bio-climatic variables are used to enhance predictions in saturation-prone areas. Additional to the goodness of adjustment to the training data from GEDI, we carried out a thorough validation of the results using in-situ data from Forest Inventory plots gathered in all 4 study regions. This enables a comprehensive comparison of the capabilities of Machine Learning modelling to adapt to the particular characteristics of each ecosystem. An in-depth analysis is carried out to find the most important predictor variables in each biome, as well as to assess the accuracy that can be expected across a wide range of AGB values.

Recent shifts in fire regimes challenge recovery of forest ecosystems. In Catalonia, Spain, the capacity of Pinus nigra to persist has been affected by recent high severity fires. To understand the biophysical conditions that support P. nigra recovery after high severity fire, we investigate the main biophysical drivers—seed availability, community interactions, water, and nutritional constraints—affecting post-fire regeneration patterns in Catalonia. We identified fire refugia and calculated the distance-weighted refugia density (DWD) across four fire footprints to represent the seed source abundance. We surveyed abundance of regeneration and shrub cover on 270 sites. We tested identical statistical models for “inside” and “outside” fire refugia, to assess the role of fire refugia and main biophysical drivers on post-fire regeneration. The DWD had a positive effect on post-fire P. nigra recovery, with a stronger effect outside refugia than inside. Inside fire refugia, canopy trees had a sheltering effect on post-fire regeneration, reducing negative effects of heat load, particularly at higher aridity plots. Presence of Rubus spp. broadleaf shrubs enhanced the abundance of regeneration both inside and outside refugia. Total shrubs cover negatively impacted regeneration inside refugia and sites with greater aridity outside refugia but exerted a facilitative effect on P. nigra regeneration outside of fire refugia at sites with lower heat load. Seed source abundance is an integral driver of post-fire regeneration however, biophysical site conditions are important filters that amplify or diminish regeneration. This ecological information can be used to tailor post-fire management goals for forest recovery.

Regional mapping of Above Ground Biomass Density (AGBD) using Remote Sensing data has shown high accuracy but lacks replicability at a global scale. In contrast, global models capture AGBD variability across biomes but struggle with biome-specific accuracy. To address this gap, we develop and assess the performance of a Deep Learning model for mapping AGBD at 10-m resolution using multi-source satellite data (Sentinel-1, Sentinel-2, ALOS PALSAR-2, and GEDI) across four biomes: Mediterranean, taiga (boreal forests), tropical rainforests, and semi-arid savannas. The model is trained and validated separately for each biome, yielding four regional models with normalized RMSEs of 0.43–0.67 and correlation coefficients (r) of 0.61–0.77 against forest inventories. We compare predictions from these models to a benchmark dataset and to a model trained on all four biomes combined. The regional models consistently outperform both, achieving better metrics than the benchmark. Additionally, an analysis of prediction drivers reveals biome-specific differences, reinforcing the importance of per-biome mapping approaches. This study highlights the advantages and limitations of regional against global modeling, creating the basis for biome-specific, replicable, scalable and multi-temporal AGBD mapping.

En los últimos años la gestión forestal está evolucionando frente a las consecuencias futuras y actuales del cambio climático. Para prepararse mejor se están ejecutando diferentes proyectos como, el LIFE ADAPT-ALEPPO tiene como objetivo el desarrollo de herramientas de adaptación de los bosques de pino carrasco frente al cambio climático. Esta nota se centra en la gestión adaptativa post-incendio para mejorar la resiliencia de bosques incendiados hace 20 o 30 años. Los tratamientos consisten en una reducción del 95% de la densidad en rodales situados en Castilla-La Mancha, Comunidad Valenciana, Cataluña y Aragón, siguiendo un gradiente climático. Se medirán parámetros de calidad del suelo, biodiversidad, crecimiento y producción de semillas y viabilidad. Los futuros resultados se quieren transmitir al mundo de la investigación y de la gestión forestal en todas las escalas para mejorar las herramientas frente al cambio climático en bosques ibéricos de pino carrasco y otros ecosistemas con similitudes.

Assisted population migration in new forest plantations can enhance future success by using seed sources that are more adapted to future climate than the local seed source. It is particularly interesting in the Spanish Mediterranean, where the number of protective plantations with Pinus halepensis has increased. However, there is a lack of operational information on these practices. The aim of this work is to improve this gap and provide information to forest managers on how to accomplish this new practice. To this end, the response of six plantations in terms of growth and survival has been evaluated. These six sites are heterogeneous regarding: the seed source planted (between 7 and 11 different ones), the bioclimate (aridity gradient), and the period analysed (from one to 13 years). Twelve seed source selection approaches have been proposed and tested using these sites. The local-use approach performed well overall (54 % reliability) but showed 25 % less medium-term survival than the average. The genetic improvement approach achieved the highest growth (+13 %), although survival gains were limited (+2 %). The drought-duration approach showed the highest reliability (58 %) and favourable outcomes where differences appeared. In contrast, the use of population distribution models as an approach to select the suitable seed source, showed poor average reliability under climate change scenarios, but not for except the historical climate, and did not correlated to plantation performance. In conclusion, to improve the future performance of P. halepensis plantations, it is recommended to review traditional silvicultural practices and consider the use of seed sources from genetic improvement or from areas with longer drought periods than the target area.

Quantifying tree resources is essential for effectively implementing climate adaptation strategies and supporting local communities. In the Sahel, where tree presence is scattered, measuring carbon becomes challenging. We present an approach to estimating aboveground carbon (AGC) at the individual tree level using a combination of very high-resolution imagery, field-collected data, and machine learning algorithms. We populated an AGC database from in situ measurements using allometric equations and carbon conversion factors. We extracted satellite spectral information and tree crown area upon segmenting each tree crown. We then trained and validated an artificial neural network to predict AGC from these variables. The validation at the tree level resulted in an R2 of 0.66, a root mean square error (RMSE) of 373.85 kg, a relative RMSE of 78.6%, and an overestimation bias of 47 kg. When aggregating results at coarser spatial resolutions, the relative RMSE decreased for all areas, with the median value at the plot level being under 30% in all cases. Within our areas of study, we obtained a total of 3,900 Mg, with an average carbon content per tree of 330 kg. A benchmarking analysis against published carbon maps showed that 9 out of 10 underestimate AGC stocks, in comparison to our results, in the areas of study. An additional comparison against a method using only crown area to determine AGC showed an improved performance, including spectral signature. This study improves crown-based biomass estimations for areas where unmanned aerial vehicle or height data are not available and validates at the individual tree level using solely satellite imagery.

Aim Growing evidence suggests that impacts of biodiversity loss on ecosystem functioning and nature’s contributions to people are usually negative, yet the magnitude and direction of these impacts can be variable across naturally-assembled ecosystems. A potential driver of variation in diversity-productivity relationships is the biogeographical context, which may alter these relationships via processes acting on the size and composition of the species pool like dispersal limitation, environmental filtering, speciation, and invasibility. However, the extent to which the relationships between biodiversity facets and forest productivity are shaped by the biogeographic context remains uncertain. Here, we examine the effects of taxonomic, phylogenetic, and functional tree diversity on aboveground productivity in climatically similar forests on islands and mainland. Location Continental and insular Spain. Time period 1997-2018. Major taxa studied Trees. Methods Using plot data from a national forest inventory, we assessed the influence of taxonomic, phylogenetic, and functional diversity on aboveground productivity using linear models and structural equation models, while accounting for environmental conditions, non-native species, and the number of trees. Results We find that drier environmental conditions lead to a decrease in productivity and in the number of trees in both island and mainland forests. In island forests, non-native species increased productivity directly and via their effects on phylogenetic diversity. Main conclusions Our results suggest that multifaceted diversity, by capturing the diversity of evolutionary history, contributes to elucidating diversity-productivity relationships in island forests that could not be detected otherwise by taxonomic diversity alone. By filling empty niches in island forests, we find that non-native species are fundamentally altering ecosystem functioning on islands.

Mountain forests face important threats from global change and spatio-temporal variation in tree height can help to monitor these effects. In this study, we used the Global Ecosystem Dynamics Investigation space-borne laser sensor to examine the relationship between maximum tree height and elevation, and the role of climate, in the main European mountain ranges. We found a piecewise relationship between elevation and maximum tree height in all mountain ranges, supporting the existence of a common breakpoint that marks the beginning of tree development limitations. Temperature and precipitation were identified as the most important drivers of tree height variation. Additionally, we predicted significant upward displacement of the breakpoint for the period 2080-2100 under climate change scenarios, potentially increasing the area without growth limitations for trees. These findings contribute to understanding the impacts of global warming on mountain forest ecosystems and provide insights for their monitoring and management.

Competition can intensify the struggle for resources among plants, affecting forest growth and dynamics. The intensity and mode of competition - asymmetric vs. symmetric - can change along environmental gradients and with time, impacting the response of plants to their environment, but this is seldom explicitly considered in management plans. In this study, we aim to (i) disentangle the main environmental and tree-related factors that affect post-fire Pinus halepensis sapling growth; (ii) determine which mode of competition characterizes the species post-fire regeneration; and (iii) elucidate if the mode of competition changes with time, and along climatic gradients. We sampled 148 P. halepensis saplings located in 15 sites affected by wildfires between 1987 and 2013 in Catalonia (NE Spain). We measured their radial growth at the base, and we identified their competitive environment by locating and measuring all the trees in a 3-meter-radius from our target saplings. We modelled the effect of tree size, age, climate, and competitive environment on the post-fire regeneration growth following the neighborhood theory of forest dynamics and using model comparison and information criteria to address our research questions. We used a modification from the Hegyi index to determine the prevalence of symmetric vs. asymmetric competition, and we assessed the support for models in which competition was allowed to vary with age and precipitation. The best model showed that competition, precipitation, age, and target size influenced the radial growth of P. halepensis post-fire regeneration (Akaike weight 0.66, R2 = 0.52). We found evidence that P. halepensis mode of competition is generally asymmetric but can change along a precipitation gradient: it shifts from asymmetric in drier sites to almost fully symmetrical as precipitation increases. Our findings have implications for the management of post-fire P. halepensis stands, enabling the adaptation of silvicultural prescriptions to the climatic environment. In a context of increasing water scarcity, adaptive silviculture is fundamental to foster the resilience of pinewoods to future climatic and disturbance regimes.

Spatial and temporal variation in functional traits allows trees to adjust to shifting environmental conditions such as water stress. However, the change of traits, both mean and variances, along water availability gradients and across growing seasons, as well as their covariation with tree performance, have been rarely assessed. We examined intraspecific trait variation in coexisting evergreen (Quercus ilex ssp. ilex and Q. ilex ssp. ballota) and deciduous (Quercus faginea and Quercus humilis) Mediterranean oaks along a wide water availability gradient in northeastern Spain during six years. We measured leaf area (LA), shoot twig mass (Sm), leaf mass per area (LMA) and the ratio of shoot twig to leaf biomass (Sm:Lm). We characterized tree performance through basal area increment (BAI) and drought resilience indices. Higher variation was found within individuals than between individuals across populations and years. Within species, we found trait adjustments toward more conservative water -use (low LA and Sm and high LMA) with increasing drier conditions. Intraspecific trait variation was constrained by water availability, particularly on the deciduous species. In Q. ilex, trait variance of LMA positively covaried with annual BAI, whereas variance of LA, Sm and Sm:Lm was positively related to resistance and resilience against the severe 2012 drought in deciduous oaks. Our results support a tradeoff between the ability to tolerate drought and the capacity to cope with unpredictable changes in the environment through increased intraspecific trait variation, which may have implications on tree performance in the face of increased extreme events.

In the climate-vulnerable Mediterranean basin, the severity and frequency of disturbances such as windthrows, droughts and fires are intensifying. Forests are generally resilient, but struggle to adapt to abrupt changes, which can impact their functionality and service provision. Various forest management alternatives aim to reduce forest vulnerability to disturbances, but few studies have evaluated the impact of management alternatives on multiple disturbances and service provision simultaneously. We aimed at filling this gap by conducting simulations of forest dynamics between 2020 and 2100 for 261 pine-dominated forest plots in Catalonia (NE Spain), under two emissions scenarios (RCP4.5 and RCP8.5) and four management scenarios (business-as-usual, promotion of bioenergy, maximum carbon storage, and ecohydrological forest management). We used the annual simulated output of forest structure and composition and future climatic projections to produce annual estimates of six ecosystem services, and we determined the annual potential impact on forests of the three main abiotic disturbances in the Mediterranean region: fire, droughts, and windstorms. We also evaluated trade-offs and synergies between disturbance impact and the provision of ecosystem services. Our simulations predicted a greater influence of management over climate scenario on the potential impact caused by all disturbances. The business-as-usual scenario consistently predicted higher impacts than the other three management scenarios, regardless of the disturbance considered or the climate scenario (fire impact 175% higher, drought impact 300%; wind impact 130%). The other three management scenarios showed similar patterns in predicted impact, but differences among them increased under more severe climate conditions. In general, there was a positive correlation between the impact by the three disturbance agents, particularly drought and fire (Pearson's r = 0.69). We observed that the provision of some services is highly correlated to disturbance impacts, suggesting that, under certain management schemes, service provision may be compromised due to abiotic disturbance impacts. Our work supports the need for an "adaptation-first" model in which the promotion of forest adaptation is placed at the core of forest management as the only way to ensure forest persistence and the delivery of services.

Background: Understanding the role of species identity in interactions among individuals is crucial for assessing the productivity and stability of mixed forests over time. However, there is limited knowledge concerning the variation in competitive effect and response of different species along climatic gradients. In this study, we investigated the importance of climate, tree size, and competition on the growth of three tree species: spruce (Picea abies), fir (Abies alba), and beech (Fagus sylvatica), and examined their competitive response and effect along a climatic gradient. Methods: We selected 39 plots distributed across the European mountains with records of the position and growth of 5,759 individuals. For each target species, models relating tree growth to tree size, climate and competition were proposed. Competition was modelled using a neighbourhood competition index that considered the effects of inter- and intraspecific competition on target trees. Competitive responses and effects were related to climate. Likelihood methods and information theory were used to select the best model. Results: Our findings revealed that competition had a greater impact on target species growth than tree size or climate. Climate did influence the competitive effects of neighbouring species, but it did not affect the target species' response to competition. The strength of competitive effects varied along the gradient, contingent on the identity of the interacting species. When the target species exhibited an intermediate competitive effect relative to neighbouring species, both higher inter- than intraspecific competitive effects and competition reduction occurred along the gradient. Notably, species competitive effects were most pronounced when the target species’ growth was at its peak and weakest when growing conditions were far from their maximum. Conclusions: Climate modulates the effects of competition from neighbouring trees on the target tree and not the susceptibility of the target tree to competition. The modelling approach should be useful in future research to expand our knowledge of how competition modulates forest communities across environmental gradients.

Tree growth is a key uncertainty in projections of forest productivity and the global carbon cycle. While global vegetation models commonly represent tree growth as a carbon assimilation (source)-driven process, accumulating evidence points toward widespread non-photosynthetic (sink) limitations. Notably, growth biophysical potential, defined as the upper-limit to tree growth imposed by temperature and turgor constraints on cell division, has been suggested to be a potent driver of observed decoupling between tree growth and photosynthesis. Understanding the interplay between biophysical potential and photosynthesis and how to accommodate it parsimoniously in models remains a challenge. Here, we use a soil-plant-atmosphere continuum model together with a regional network of forest structure and annual, radial tree growth observations extending over three decades to simulate tree photosynthesis and biophysical potential along an aridity gradient and across five tree species in NE Spain. We then apply a linear modelling framework to quantify the relative importance of photosynthesis, biophysical potential and their interactions to predict annual tree growth along the aridity gradient. Overall similar relative importance of photosynthesis and biophysical potential was underlain by strong variations with climate, photosynthesis being more relevant at wet sites and biophysical potential at dry sites. Observed spatial and temporal trends further suggested that tree growth is primarily limited by biophysical potential under dry conditions and that disregarding it could lead to underestimating tree growth decline with increased aridity under climate change. Our results support the idea that biophysical potential is an important component of sink limitations to tree radial growth. Its representation in vegetation models could accommodate spatially and temporally dynamic source-sink limitations on tree growth.

The dataset associated with this paper comprises GEDI 2A data collected from 2019/05/01 to 2020/09/03, along with ancillary data (NASADEM & WorldClim) at the footprint level. Additionally, footprints are filtered by elevation ranging from 800 meters above sea level to the maximum elevation calculated for each mountain range (please see Methods / GEDI Dataset subsection). Each file encompasses the described data for a specific mountain range (specified in the filename) and is presented as a *.RData file. Data ready for modelling and plotting.