The increasing integration of ecosystem services (ES) into environmental and agricultural policies creates the need for operational approaches linking ecosystem service assessment with territorial planning and incentive design. This study develops a functional–territorial typology of ES provision for mainland Portugal based on the assessment of 26 ecosystem services derived from the Common International Classification of Ecosystem Services (CICES v5.2) across 278 municipalities. Territorial clusters were identified using provisioning and regulating ES, while cultural ES were subsequently incorporated into functional bundles and territorial–functional analyses. The analysis identified three functional ES bundles and six territorial socio-ecological regimes representing distinct patterns of ES provision. Functional bundle identification proved highly robust, with 92.3% of ES retaining the same bundle assignment across alternative correlation thresholds. A sensitivity analysis including cultural ES confirmed the stability of the main territorial regimes. Between 70% and 86% of municipalities remained within the same territorial group, while most reclassifications occurred near the boundaries between neighbouring regimes, indicating local refinements rather than changes in the overall territorial organization. Cross-analysis showed that territorial regimes differ systematically in ES configurations, baseline conditions, and patterns of synergies and trade-offs, indicating that additionality is inherently territorial and cannot be adequately interpreted using uniform baselines. Building on these findings, we propose a framework of territorially differentiated Ecosystem Service Provision Units (UPSE) incorporating variations in ES configurations and additionality potential across socio-ecological contexts. The framework provides a methodological basis for more context-sensitive ES incentives, restoration strategies, and environmental policy instruments.

This study provides new equations to estimate crown width and percent crown cover of cork oak (Quercus suber L.), helping forest managers understand forest structure and making informed decisions on understory management and thinning operations. These equations can either be used as standalone solutions or help adapt existing tools, such as the Physiological Processes Predicting Growth (3PG) model, thereby supporting better decisions to protect Mediterranean woodlands facing environmental changes. Tree crown width and canopy cover are key variables that influence forest productivity, regeneration, and ecosystem functioning. In cork oak stands, low regeneration and sparse canopy cover are common challenges. There is no established consensus on the optimal stand density, and research on this topic remains limited. This study aims to develop robust models to estimate tree crown width and canopy cover at the stand level, designed for both standalone application and integration with the outputs of the widely used 3PG model. In addition, the proposed models can be used to evaluate alternative methods for estimating light interception in the 3PG model. The first step involved the development of a crown width model based on stand variables, computed with all trees in the stand, including trees with DBH < 7.5 cm, which is really important in young even-aged stands and in close-to-nature management. This model was then used to calculate missing crown widths, followed by the development of new models to estimate canopy cover based on stand variables and some biomass component(s). Several formulations of allometric and monomolecular functions were tested to produce alternatives both for general use as a decision-support tool and use within the 3PG model. The monomolecular function was preferred for its broad applicability across stand ages. Three final formulations, one using basal area and the other two using leaf biomass as the main predictor, showed strong predictive performance (EFpred. = 0.88, 0.91 and 0.91, respectively) and maintained biological relevance. The model based on leaf biomass and tree density enables canopy cover estimation independent of stand age and uses variables directly provided by the 3PG model. Improved estimates of crown width and canopy cover allow for more accurate assessments of the relationship between the tree canopy and the understory vegetation, which enables the use of canopy cover as thinning criteria. Therefore, the equations developed in this study are valuable tools for supporting sustainable forest management. Furthermore, one of the canopy cover models was specifically designed for direct integration into the 3PG model, and the set of equations developed open new avenues to test alternative methods for estimating light interception within this framework.

Stand-level canopy base height (Cbh) is a key variable controlling crown fire initiation, yet it is commonly computed as the mean of tree height to the base of the crown (hbc), which does not reflect the lower portion of the hbc distribution governing the transition from surface to crown fire. This study investigates the relationship between physically based Cbh definitions and the hbc distribution. We develop a general multi-percentile modeling framework to estimate hbc percentiles at the stand level. Using a dataset of Pinus pinaster Aiton trials in Portugal, percentile-specific models (5th to 50th) were fitted and synthesized into a nonlinear multi-percentile formulation. Results show that the height at which canopy bulk density exceeds the critical threshold does not match mean hbc, but instead corresponds to lower percentiles, typically around the 10th percentile, varying with stand structure and age. Mean-based Cbh tends to overestimate the lower canopy boundary, reflecting its inability to capture structural variability. The final model predicts hbc at any percentile and incorporates effects of stand height, basal area, tree density, and age, ensuring positive predictions and high predictive accuracy (adjusted R2 = 0.9770; RSE = 0.4073 m; PRESS R2 = 0.9769). The framework provides a consistent representation of canopy base height for fire behavior modelling.

This paper provides individual tree models to estimate crown variables in maritime pine (Pinus pinaster Aiton.). The estimation of crown variables, especially height to the base of the crown and crown length, is essential for forest fire simulators that require the calculation of canopy bulk density, a measure that relates leaf weight and canopy volume. The numerous forest fires that have occurred in the Portuguese forest ecosystems over the past decades justify, by themselves, the importance of estimating crown variables such as crown ratio, crown length and height to the base of the crown, which are also frequently used as predictors in individual tree models’ components. A compatible system of equations to predict crown variables was developed for maritime pine (Pinus pinaster Aiton.) in Portugal. A database with a long time-series of measurements covering a wide variety of situations was used to fit models to estimate crown ratio, crown length and height to the base of the crown. To guarantee accuracy and compatibility among crown variables the models were developed as a compatible system of equations fit using seemingly unrelated regression. The parameters of the functions were expressed as a function of tree, site and stand variables and inter-tree competition. The system of equations for height to the base of crown and crown length, both accurate and consistent, is based on a set of parameters describing tree age, height and slenderness, basal area, dominant height and a distance-independent competition index, the ratio tree size/average tree size. The equations developed in this study describe how the tree and stand variables control height to the base of the crown, crown ratio and crown length. These variables depend on tree age and dominant height, with crown ratio decreasing as trees and stands get older. Tree slenderness has a positive effect, with shorter crowns in trees that are closer to a cylinder (lower d/h ratio). Stand density implies shorter crowns and, within a stand, trees under lower competition (higher values of d/dg) have longer crowns.

The whole-plant preferential allocation patterns of recently assimilated carbon by the source leaves of six-year-old cork oaks (Quercus suber L.) were assessed 7 days after a 14CO2 pulse-labelling in late spring (end of May). The 14CO2 assimilation was separately induced on attached leaves on branches located at the top-down 30% of the crown height, in the middle 40% and at the bottom-up 30% of the crown height of twelve plants. Our results showed that the top source leaves retained the highest amount (64%) of their own current produced carbohydrates compared to either lower (49%) or middle (42%) source leaves. The top source leaves preferentially export current carbohydrates to their most proximal sinks, namely, other leaves or their branches. However, lower source leaves exported the highest amount of current carbon, about 37%, preferentially to the root system. Roots displayed the greatest sink strength for the available current carbohydrates, due to their largest biomass (between 69% and 75% of the whole plant biomass), when other strong sinks, such as the annual leaves, were fully expanded. Taken together, our data revealed that carbon supply by leaves and delivery to roots are critical for maintaining root growth in cork oak under Mediterranean seasonal drought conditions.

Edaphoclimatic variables and inter-tree competition effects may be observed in adult cork stands. Expressing parameters of tree growth models as a function of these drivers seems therefore appropriate. This work aimed to study the impact of this procedure in the model prediction capacity of cork oak tree diameter growth models. The used dataset consisted of individual adult tree measurements obtained between 1995 and 2019 from seventy-five plots installed across most of the cork oak distribution in Portugal. Tree diameter growth was modelled with the Richards growth function, formulated as an age-independent difference equation. Edaphoclimatic variables and stand metrics were added to one or both model parameters. Then, the best performing four edaphoclimatic models were refitted while testing for significance of adding both distance-dependent and -independent competition indices to model parameters. Finally, a mixed-effects modelling approach was used, by including in the best performing models plot-level random effects to account for the hierarchical structure of the data. Precipitation and Lang index combined with Schists class (Lithology variable) originated the best performing edaphoclimatic models (highest modelling efficiency = 0.98077). Of the nine competition indices that originated suitable models and improved the predictive capacity of their respective edaphoclimatic model, eight were distance-dependent and one was distance-independent (highest modelling efficiency = 0.98082). Adding plot-level random effects did not improve the models. Edaphoclimatic variables showed a higher model improvement than the competition indices, which still improved their respective edaphoclimatic models. Most of the suitable competition indices were spatially explicit, but their performance was equalled by a distance-independent one. The proposed models will be incorporated in existing growth and yield models becoming important tools for forest managers, as they consider climate, soil and competition in cork oak diameter growth prediction in Montado stands.

Forest certification is a voluntary conservation tool that aims to promote sustainable forest management. While research on forest certification has increased recently, there remains a significant gap in understanding how and to what extent certification can promote forest conservation. Mediterranean cork oak open woodlands are ecosystems of high conservation and socio-economic value. However, these ecosystems are threatened by increased adult oak mortality and regeneration failure, often due to inadequate management and the rise of pests and diseases, aggravated by climate change. Forest certification prescribes management practices intended to enhance tree regeneration and maintain stand health conditions. Therefore, it is anticipated that forest certification could mitigate the observed decline of oak trees in Mediterranean regions. Here, we investigate whether forest certification contributes to the ecological sustainability of Mediterranean cork oak open woodlands in Portugal. We compare the stand biometrics of noncertified and certified cork oak stands before and after certification implementation, using both National Forest Inventory data and field sampling from 2005 and 2020. Our findings indicate that the density of adult oak trees decreased by 16% in certified estates and 28 % in noncertified estates between 2005 and 2020. Similarly, cork oak cover declined by 6 % tree cover in certified plots and 19 % in non-certified plots during the same period. Consequently, by 2020, tree density was 20 % higher in certified stands than in the non-certified ones, and tree cover was 36 % higher in certified stands. Tree diameter and height increased at similar rates in both certified and non-certified stands from 2005 to 2020.The age structure of the stands also remained consistent, showing a bell-shaped distribution of tree diameters in both years. However, results on oak regeneration were inconclusive. Our results suggest that cork oak decline, measured by the changes in density and cover of adult trees from 2005 to 2020, is slower in certified cork oak woodlands. Nonetheless, the increase in tree diameter and the age structure shape indicate potential regeneration issues in both certified and non-certified stands, needing further measures to address the aging of cork oak open woodlands.

Ecosystems are likely to be severely affected by climate change. While the literature on this subject focuses primarily on climate variable means, increasing evidence has been gathered on the importance of changes in climate variability in determining ecosystem impacts. In this context, forests play a significant role. While, on the one hand, forests have often been identified to be a key element in mitigating greenhouse gas emissions, on the other, forests are also affected by changes in climate. However, the number of studies on optimal forest management under climate change remains limited and has overlooked the role of climate variability. This paper adds to that literature by developing a coupled ecological-economic forest stand model in which forest dynamics are a function of monthly climate variables. We show that accounting for changes in climate variability substantially changes earlier findings. In particular, ignoring climate variability may fail to adequately account for changes in optimal harvest age and lead to erroneous conclusions regarding the effects of climate change on forested land value.

Local terrain or microsite conditions influence the development of trees, particularly at early ages. These conditions might be described by edaphic or topographic variables. We mapped soil and topographic variables from four even-aged and even-spaced cork oak plantations located in two climatically distinct Portuguese regions. The major goal of this research was to understand the relation between soil and topographic fine-scale conditions and tree growth expressed by diameter without cork annual growth (idu). The methodology consisted in (1) analysing the spatial variability and autocorrelation of idu; (2) modelling idu with ordinary least squares (OLS) regressions; (3) comparing with spatial modelling of idu, incorporating spatial autocorrelation. The driest stands A and B, exhibited weaker spatial autocorrelation, distributed in smaller clusters (R-2 < 0.03, OLS models), while stands C (R-2 = 0.18, OLS models) and D (R-2 = 0.11, OLS models) showed higher predictive capacity. Spatial models increased R-2 scores, keeping most variables from OLS models and accounting for spatial autocorrelation. A + B + C + D OLS model obtained an R-2 = 0.34 and respective spatial model R-2 = 0.58. Apparent electrical conductivity at 0.5 (ECa0.5) and 1 m of soil depth, slope, elevation and topography position index were included as predictors (OLS), but only ECa0.5, slope and elevation were selected in the spatial model. Models were fitted using average to high productivity stands and should be used cautiously outside this range. Local terrain conditions determine the growth of young cork oak trees. Mapping soil and topographic variables before establishing new plantations may identify limiting microsite conditions where using cork oak species is not suitable due to low growth rates expectations.

In recent years, there has been an increasing demand for forest certification and certified forest products in Europe. This trend is related to major worldwide challenges, such as the need to decarbonize the economy and mitigate climate change but also social and consumer demands for wider fair trade. However, whether forest certification influences economic valorization in forestry remains a question. The aim of this study is to analyze forest certification levels across Europe and identify potential relationships between the level of certification in forest areas and relevant economic indicators at country level. This study collected openly available data on total and certified forest areas, economic indicators, and environmental indicators for 28 European countries and explored the correlation between certified forest areas and economic performance in the forestry sector. Findings show that forest certification can significantly improve the economic performance of European forests. It has a more pronounced positive effect on economic incomes than on costs’ reduction. While certification costs do rise with the extent of forest area, they tend to stabilize at larger scales, suggesting that the certification process is economically sustainable and scale is relevant. Czechia and the Netherlands stand out for having the highest net values added related to forest certification, reflecting an effective economic exploration of forest resources. This study offers new perspectives to natural and social scientists, as well as to industry and policy makers, by proving contextualized data to support decision making. Additionally, it provides hints for further studies and policy guidelines on sustainable development and the impact of forest certification schemes.

Characterizing Management Units (MUs) with tree-level data is instrumental for a comprehensive understanding of forest structure and for providing information needed to support forest management decision-making. Airborne Laser Scanning (ALS) data may enhance this characterization. While some studies rely on Individual Tree Detection (ITD) methods using ALS data to estimate tree diameters within stands, these methods often face challenges when the goal is to characterize MUs in dense forests. This study proposes a methodology that simulates diameter distributions from LiDAR data using an Area-Based Approach (ABA) to overcome these limitations. Focusing on maritime pine (Pinus pinaster Ait.) MUs within a forest intervention zone in northern Portugal, the research initially assesses the suitability of two highly flexible Probability Density Functions (PDFs), Johnson’s SB and Weibull, for simulating diameter distribution in maritime pine stands in Portugal using the PINASTER database. The selected PDF is then used in conjunction with ABA to derive the variables needed for parameter recovery, enabling the simulation of diameter distributions within each MU. Monte Carlo Simulation (MCS) is applied to generate a sample list of tree diameters from the simulated distributions. The results indicate that this methodology is appropriate to estimate diameter distributions within maritime pine MUs by using ABA combined with Johnson’s SB and Weibull PDFs.

Climatic factors drive the annual growth of cork and the subsequent increase in its thickness, which, in addition to porosity, determines the price of cork. Therefore, the simulation of cork thickness is a crucial module of forest growth simulators for cork oak stands. As the existing cork growth models are independent of climatic factors, cork thickness under different climate change scenarios could not be simulated using these models. The primary objective of this study was to develop a climate-dependent tree model to predict annual cork growth. We also verified the hypothesis that the effects of climate change on cork annual growth are nonlinear, and vary with the cork age and thickness. Due to the limited amount of work developed around this topic, we evaluated three candidate models and selected the one that presented best prediction performance as the base model. A set of climate variables that characterized annual climatic conditions were tested in the base model parameters. The resulting climate-dependent model was referred to as the fixed-effects model, and used to initialize a mixed-effect model which accounted for the nested structure of the data. We considered two random effects-the plot and the trees inside the plot. Annual precipitation and the Lang index (ratio between annual precipitation and mean annual temperature) were the variables that showed best results when included in the model parameters. Using a ratio of the variable to cork thickness recorded during the previous year, in both cases, suggested a decline of the positive effect of annual precipitation and the Lang index for increasing cork thickness. The models developed in this study predicted the cork thickness of individual trees based on the cork age and under different climate change scenarios. Therefore, they can be used in forest growth simulators for forest management and research purposes.

The necessity for accurate biomass estimates is greater than ever for the sustainable management of forest resources, which is an increasingly pressing matter due to climate change. The most used method to estimate biomass for operational purposes is through allometric equations. Typically, each country develops their own models to be applied at the local scale because it is more convenient. But, for Quercus suber, a joint regional model can be more beneficial, since the species is distributed across the Mediterranean and is challenging to account for due to felling limitations and the nature of mature cork biomass itself. We found that these characteristics are reflected in the biomass datasets and compatibility was, perhaps, the largest impediment to such a model. The use of dummy variables to differentiate between countries, as well as compromises in the limits of biomass compartments, allowed us to develop two joint models to estimate aboveground biomass in Portugal, Spain and Tunisia. One model as a function of diameter and another as a function of diameter and total tree height. In addition, we developed a separate model for roots (modelling efficiency of fitting = 0.89), since it was not possible to assure additivity of the whole tree. All coefficients were estimated using Seemingly Unrelated Regressions (SUR) and model fitting assured additivity in the aboveground compartments—leaves and woody biomass (modelling efficiency of fitting = 0.89 and 0.93, respectively). This work proves that it is possible to have a biologically sound and efficient model for the three countries, despite differences in the observed allometric patterns.

Around 1.5 million ha of the Iberian Peninsula is currently occupied by Eucalyptus globulus, the preferred species for commercial plantations due to its fast growth and wood technological properties. However, these econom-ically important plantations are being heavily damaged by Gonipterus platensis (Col: Curculionidae), an invasive species native to Australia which was established in the Peninsula, in the nineties. A classical biological control with the release of the egg parasitoid Anaphes nitens (Hym: Mymaridae) was launched in the Peninsula. Yet, in the colder regions, in the North of the Peninsula, the parasitoid is not efficient enough to control the weevil population. The resulting damage overcomes more than 200 million euros every year.Current control strategies rely on the application of insecticide (acetamiprid) or augmentative biological control (ABC) with yearly releases of A. nitens in spring. However, uncertainties about the best option persist. In this study, chemical and ABC treatments were submitted to a cost-benefit analysis with the aim of determining their viability against the weevil, based on a treatment efficacy and stand productivity trade-off analysis.A simulation tool (3-PG.d) was used to simulate the growth of E. globulus stands, under four defoliation in-tensity scenarios mimicking the removal of 25, 50, 75 and 100% of the spring new leaves biomass. Each defo-liation scenario was combined with three treatments: (i) chemical (acetamiprid), (ii) ABC+ (optimistic approach), and (iii) ABC- (pessimistic approach). For each treatment, several plans of yearly treatments were tested. The Net Present Value (NPV) and the harvested volume were used to compare all treatment alternatives.The best treatment decision, based on a cost-benefit analysis comparing economic results and harvested volume, varied with the intensity of defoliation. Treating was always better than doing nothing, except for the 25% defoliation scenario. ABC+ offered the best economic results, relative to other treatments, for 25, 50 and 75% defoliation scenarios. ABC- was only as good as the chemical treatment for the 25 and 50% defoliations. Under the heaviest weevil attack (100%), applying insecticide was the best alternative, overcoming both ABC treatments. These results show that augmentative biological control was a strategy to consider for this study, and thus, may be a strategy to be considered in the future. The 3-PG.d simulator showed that it can be an asset for forest managers aiming at integrating chemical and/or biological treatments against forest pests in stand management decisions.

Keywords: Forest management; sustainability; FSC; PEFC; research; market share

Density-dependent mortality occurs in the evolution of even-aged populations when these approach crown closure age. This density-dependent mortality is regulated by the so-called “3/2 power law of self-thinning” that assumes a constant slope for the line relating the log of stand density with the log of the average tree size, the self-thinning line or maximum size–density relationship, MSDR. A good estimate of the self-thinning line is therefore an essential component to any forest growth model. Two concepts for the MSDR have emerged: (1) a static upper limit for the species; and (2) a dynamic self-thinning line influenced by several factors (e.g., management techniques, site quality and/or genetics). The objective of this study was to estimate a new static self-thinning line based on the quadratic mean diameter at breast height (Reineke’s self-thinning line) for the generalized use in maritime pine growth models in Portugal. Data from 41 observations obtained in nine long-term permanent experimental trials of maritime pine species were carefully selected from a data set of 186 plots as being under self-thinning. Two methods were used: OLS and mixed linear models. An exploratory analysis on the impact of each environmental variable on the slope and intercept of the self-thinning line led to the selection of a subset of environmental variables later used in an all possible regressions algorithm to find the subsets leading to the lowest values of Akaike information criterion (AIC). The OLS procedure showed that the differences between the plots could be explained by site index, by climate variables (e.g., evaporation or climatic indices) and the use of more than one covariable slightly improved the fit. Nevertheless, the best MSDR line fitted with mixed linear models (ln N = 12.97158 − 1.83926 ln dg) having the plot random effect in the intercept, largely outperformed the best OLS model and is therefore recommended for generalized use in forest growth models.

Competition indices may improve tree growth modelling in high-density stands, found often in new cork oak plantations. Distance-dependent competition indices have hardly been considered for juvenile cork oak plantations since existing models were developed for low-density mature stands. This study aims at inspecting the potential of including distance-dependent competition indices into diameter at breast height (d) and total height (h) growth models for Quercus suber L., comparing several distance-dependent and distance-independent competition indices. Annual d and h growth were modelled with linear and non-linear growth functions, formulated as difference equations. Base models were initially fitted considering parameter estimates depending only on site index (S) and/or stand density (N). They were refitted, testing the significance of adding each competition index to the model parameters. Selected models included the best-performing distance-dependent or -independent competition indices as additional predictors. Best base d and h growth models showed a modelling efficiency (ef) of ef = 0.9833 and ef = 0.9900, respectively. Adding a distance-dependent competition index slightly improved growth models, to an ef = 0.9851 for d and ef = 0.9902 for h. Best distance-dependent competition indices slightly overperformed distance-independent ones in diameter growth models. Neither S nor N were included on best fitted models. If inter-tree competition is present in juvenile undebarked cork oak plantations, it does not yet strongly impact individual tree growth, which may diminish the importance of using, at this stage, more complex spatially explicit competition indices on predicting individual tree growth.

: In this paper, we estimated the methane emissions by the disposal of sanitary and domestic-use paper consumed throughout Brazil from 1901 to 2016. The apparent consumption of this type of paper from 1961 to 2016, calculated from the data of the FAOSTAT system, was used to estimate the amount of waste disposed of annually in three site categories: sanitary landfill, controlled dump, and open-air, uncontrolled dump. The 2006 IPCC Guide methodology was used to calculate CH 4 emissions and long-term carbon storage. Nine scenarios based upon the law that establishes the National Solid Waste Policy (NSWP) were examined, considering 100% waste disposal and treatment in landfills or incineration from 2014. The total emission was estimated at 1.967 MtCH 4 , corresponding to 55.080 MtCO 2eq by GWP-AR5, and the stored carbon at 3.724 Mt, corresponding to 13.655 MtCO 2eq . CH4emission increased beyond the population growth rate due to an increase in the per capita paper consumption in the country, from 0.02 kgCH 4 .year -1 in 1961 to 0.30 kg CH 4 .year -1 in 2016. The NSWP has not yet been accomplished, and the scenarios outlined indicate that, from the point of view of CH 4 emissions, it would be more advantageous to carry out incineration instead of applying other waste treatment technologies.