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Although native to Australia, Eucalyptus species are found throughout Europe. At present, they are located mainly in the Iberian Peninsula and Eucalyptus globulus is the most commonly planted species. Climate forecasts anticipate an expansion of Eucalyptus to other regions of Europe. The fast growth of E. globulus, together with its resprouting ability and wood properties, has promoted the use of this species in the Iberian Peninsula. The total volume of E. globulus harvested there was close to 14 million m3 in 2019. Eucalyptus species represent the main source of raw material for the pulp and paper industries and provide an important source of income to non-industrial owners. Being exotic fast-growing trees, their expansion has also been associated with negative environmental impacts. The species therefore poses a series of challenges, while also generating opportunities. The objectives of this review paper are: (1) to summarize the importance of Eucalyptus plantations in Europe; (2) to analyse the opportunities and challenges of this genus in present and future plantations in Europe; (3) to assess to what extent forest management, at both stand and landscape levels, can reduce negative impacts; (4) to make policy and management recommendations that may support the use of this genus in other European regions. These aims are accomplished based on a thorough literature review, particularly focused on research developed in the Iberian Peninsula. [ABSTRACT FROM AUTHOR]

How relevant is the role of CO2 from harvested wood products (HWPs) for the Brazilian GHG emission balance? The C stocks and CO2 emissions and removals from the HWPs in Brazil during 1900–2016 were evaluated using three methodological approaches: stock-change approach (SCA), production approach (PA), and stock-change of domestic origin (SCDOA). Data from the FAO's FAOSTAT system on production, import and export of semi-finished products (sawnwood, wood-based panels and paper/paperboard) were analyzed, considering distinct land-use activities: deforestation (D), forest management (FM) and afforestation/reforestation (A/R). Two scenarios to evaluate the effect of HWPs from D were evaluated. The C stock in HWPs in 2016 reached 252 Mt C, by SCA. Contributions to C storage historically were higher from sawnwood, but wood-based panels and paper/paperboard have recently outperformed it. A/R is the major activity responsible for C storage in HWPs. The CO2 removal by HWPs was 521 Mt during 1990–2016, which corresponds to 1.1% of the country's emissions in the same period. It was concluded that Brazil has become a major producer and wood consumer and that HWPs are allies for a positive C balance and fulfillment of the commitments assumed by the country regarding climate change. AFOLU Agriculture, forestry and other land uses A/R Afforestation/reforestation D Deforestation FAO United Nations Food and Agriculture Organization FM Forest management HWPs Harvested wood products IBGE Brazilian Institute of Geography and Statistics PA Production approach PEVS Plant extraction and forestry SCA Stock-change approach SCDOA Stock-change of domestic origin approach [ABSTRACT FROM AUTHOR]

Two systems of equations for predicting stand level aboveground biomass and biomass per tree component (wood, bark, branches and leaves) were developed taking into consideration the specific characteristics of the stands. The two systems differ by considering or not stand age as one of the regressors. Data from permanent plot, trials and continuous forestry inventory was used. It included data from first rotation and coppiced stands that represent the existing range of ages, stand densities, sites and management options in Portugal. The models have a good predictive capacity (adjusted R 2 > 0.97) using only stand variables easily accessible in forest inventories; stand age, stand density, dominant height, basal area and cultural regime. The proposed equations where used on National Forestry Inventory plot data and the results obtained where compared to the inventory results and estimates obtained using tree level allometric equations and Biomass Expansion Factors (BEF's). The comparison of the four approaches showed that the use of stand level methods gives as accurate results as the use of tree level methods. The use of BEF's resulted in the least accurate method for estimating biomass, with an average mean error of 17%. In contrast, the proposed equations estimate biomass values with a mean error of 9% and are the best option for biomass estimates in short rotation forestry, where the objective is to obtain biomass estimates for short rotation stands (2–5 years). They also allow tree component biomass estimates, something that is not possible using the existing BEF's for Eucalyptus globulus . [ABSTRACT FROM AUTHOR]

Simple, operational tools are required for forest managers to quantify the effects of soil fertility on tree growth and ecosystem sustainability leading to precise, sustainable forest management. The simplified process-based 3-PG model (Landsberg, J.J., and Waring, R.H., For. Ecol. Manage. 95: 209-228, 1997) provides a useful framework for operational prediction of forest growth. However, no simple objective method for relating the effects of available soil nutrients to the model fertility parameter fertility rating (FR) is yet available. The present study aimed to compare several general modeling approaches for the estimation of FR values from soil relative nutrient contents (RNCs) to maximum nonlimiting values, measured in the whole soil profile, at continuous inventory plots of Eucalyptus globulus Labill. in several locations under different parent materials in northwestern Spain. The modeling approaches tested provided good predictions of FR values from RNCs. In particular, using the minimum value of the most significant RNCs showed considerable potential for modeling FR values and plantation growth responses to them. This modeling approach showed promise to be further tested as a generally applicable strategy for estimating the effect of soil nutrients on forest plantations growth. [ABSTRACT FROM AUTHOR]

In the scope of energy diversification and profitable forest resource exploitation, increasing the use of biomass residues for energy can play an important role by using local sources of energy, reducing carbon emissions and fossil-energy use, providing additional revenue for the forest sector, and also reducing the risk of forest wildfires. Regional simulators can help forecast available wood and biomass and allow evaluation of possible future conflicts of interest and their consequences for society. This paper focuses on improving an existing regional forest simulator (SIMPLOT) so that it can be applied to study research questions related to increasing the use of eucalyptus biomass for bioenergy and the related consequences for wood available for pulp. Biomass modules were integrated into SIMPLOT so that different sources of biomass used for energy could be accounted for. The updated version of the simulator was used to assess the impact of different biomass demands for bioenergy, combined with different afforestation alternatives on the wood available for the pulp and paper industry in Portugal. SIMPLOT's forecasts indicated that the eucalyptus forest is unable to satisfy wood demand even when pulp afforestation areas are doubled, regardless of the biomass demand considered. Also, the simulation results showed that, with the tested afforestation rates, eucalyptus forest cannot meet high increases in demand for wood. [ABSTRACT FROM AUTHOR]

Abstract: SIMPLOT is a forest simulator for eucalyptus mainly driven by wood demand. It was developed to predict the evolution of the eucalyptus plantations in Portugal by combining forest inventory data with growth models taking into account the effect of different drivers such as wood demand, hazards occurrence and percentage of land use changes. The use of simulators for scenario analysis can be a powerful tool to explore policy options and to illustrate the consequences of different management alternatives. In the past years Portugal has been marked by extremely severe forest fires of great environmental impact. This paper shows simulation runs for two main scenario lines: the wood demand line and the wildfires line. In the first one, the simulator is used to identify a reasonable wood demand out of three different wood demands combined with a low/medium intensity fire scenario. The selected wood demand combined with three fire scenarios of increasing severity and a fourth one disregarding the existence of recent severe wildfires builds the second scenario line. The purpose of this study is to evaluate the impact of different magnitudes of forest fires occurrence on the sustainability of eucalyptus plantations starting with NFI data gathered in 1997 during a horizon of 28 years. The simulations reflect a constant level of afforestation and deforestation and assume that no changes took place between different management alternatives. These simulations provide some insight on the impact of different wood demand and different magnitudes/frequency of severe wildfires: it is not only the number and magnitude of severe wildfires that make a difference, but it is also the number and magnitude of medium wildfires that follow an extremely severe one. Furthermore, the inter-annual variability of wildfire occurrence affects carbon stock and carbon sequestration in a different way. The occurrence of severe wildfires has an immediate effect on carbon sequestration. The lower values are registered in the same year in which the most severe wildfires occur. On the other hand, the occurrence of severe wildfires has more permanent consequences on carbon stocks than on carbon sequestration. The more severe and numerous are the wildfires the more difficult and at long-term will be to recover the carbon stocks in the forest. Results have also shown that if a higher wood demand compatible with the expected increase of pulp industry capacity would have been considered this would have had drastic impacts on eucalyptus forest sustainability due to overharvesting in order to meet the desired wood demand. [Copyright &y& Elsevier]

We present a new dynamic dominant height growth model based on Cieszewski’s generalized algebraic difference approach (GADA) advanced dynamic site equation strengthened by the use of explicit climate and soil variables (i.e., H = f(H0,T0, T, site conditions)). The results suggest that the inclusion of climatic variables would improve the applicability of the inter-regional model in regions in which climate and soil type lead to intra-regional variability. The new model reduces the bias present in a previous dynamic model that did not include climatic attributes and improves the model efficiency across the different age classes. Climate has a multiplicative effect on dominant tree growth in the early development stages (<20 years) and an additive effect in older stands. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop a system of compatible equations to estimate eucalyptus (Eucalyptus globulus Labill.) tree aboveground biomass and biomass of tree components for forest biomass prediction across regional boundaries. Data came from 441 trees sampled on several sites (99 and 14 plots in planted and coppice regenerated stands, respectively) representative of the eucalyptus expansion area in Portugal. The system of equations, simultaneously fitted using seemingly unrelated regression, was based on the allometric model for the biomass of stem wood, stem bark, leaves, and branches. Total aboveground biomass was expressed as the sum of the biomass of the respective tree components. The study allowed the following conclusions: (i) there is a significant increase in the predictive ability of the models that include height (stem components) or crown length (crown components) as an additional predictor to diameter at 1.30 m; (ii) there is a clear effect of the stage of development of the stand on tree allometry, with a decreasing pattern of the allometric constants; (iii) no effect of stand density, site index or climate on tree allometry was found; and (iv) for practical purposes, the same system of equations can be used for planted and coppice regenerated stands. [ABSTRACT FROM AUTHOR]

Modelling growth of trees or stands when age is not available is often necessary. This is the case in national forest inventories or when age is not a main determinant of growth (e.g., trees growing in uneven-aged stands). Even if age is not known, functions used to model growth should follow the required pattern, with a maximum and a slow decline after the maximum is attained. There are some empirical functions with these properties; however, direct modelling with difference equations derived from the so-called theoretical growth functions has not been used for this purpose, as they are age dependent. This paper presents a methodology to formulate growth functions as age-independent difference equations. These can be used when age is not available or is not relevant. The proposed equations have the advantage of allowing the direct modelling of yield instead of growth. If the parameters are expressed as a function of site variables, the equations are invariant for projection length and therefore can be used when data is not equally spaced in time, as is the case of most data sets. The methodology is applied to the Lundqvist and Richards growth functions, the most commonly used in growth and yield modelling. The use of the age-independent growth functions is illustrated by using two case studies in Portugal: dominant height growth of eucalyptus (Eucalyptus globulus Labill.) plantations and individual tree growth in diameter at breast height in sparse cork oak (Quercus suber L.) stands. [ABSTRACT FROM AUTHOR]

The cork oak (Quercus suber L.) is an evergreen oak that has the ability to produce a continuous layer of cork tissue which regenerates after being removed. Cork oak stands can be diverse in structure. Young stands are often regularly spaced, whereas older stands usually show clustering and can be mixed with other species. Farmers assessing cork value use a zigzag sampling procedure within a stand. In this study we compare zigzag sampling with two other sampling methods, fixed-radius plot sampling and n-tree distance sampling, using a model for the costs of sampling. We used data from two cork oak stands in Portugal as well as data from six types of simulated stands. We found that zigzag is the poorest sampling method, as in most situations it produces estimators with larger bias and larger standard errors than that produced by the other two procedures. Fixed-radius plot sampling and n-tree distance sampling produce comparable results; however, fixed-radius plot sampling is preferred because it produces unbiased estimators. [ABSTRACT FROM AUTHOR]

Continuous cover practices are likely to better respond to the increasing demand for social, aesthetic and environmental values provided by forest ecosystems than even-aged forest plantations. Also, uneven-aged forestry may be especially attractive for non-industrial private forest owners, as it provides more regular revenues and, by taking advantage of natural regeneration, reduce installation costs. Knowledge on alternative regimes to even-aged forestry is therefore in high demand. We first add to the literature by proposing a new maritime pine forest growth model that can be readily used in optimization studies. Second, we are the first to analyze optimal uneven aged forest management for this species. Highlighting the contribution of this study, a comparison of our results with currently suggested silvicultural management scenarios is provided. We show that the economic profitability of this species significantly increases under optimal forest management and may thus present a viable alternative to rotation forests. In particular, we show that optimal forest management may entail harvesting cycles. [ABSTRACT FROM AUTHOR]

The article focuses on effects of numbers of observations and predictors for various model types on the performance of forest inventory with airborne laser scanning.

Knowledge of factors that trigger human response to climate change is crucial for effective climate change policy communication. Climate change has been claimed to have low salience as a risk issue because it cannot be directly experienced. Still, personal factors such as strength of belief in local effects of climate change have been shown to correlate strongly with responses to climate change and there is a growing literature on the hypothesis that personal experience of climate change (and/or its effects) explains responses to climate change. Here we provide, using survey data from 845 private forest owners operating in a wide range of bio-climatic as well as economic-social-political structures in a latitudinal gradient across Europe, the first evidence that the personal strength of belief and perception of local effects of climate change, highly significantly explain human responses to climate change. A logistic regression model was fitted to the two variables, estimating expected probabilities ranging from 0.07 (SD ±0.01) to 0.81 (SD ±0.03) for self-reported adaptive measures taken. Adding socio-demographic variables improved the fit, estimating expected probabilities ranging from 0.022 (SD ±0.008) to 0.91 (SD ±0.02). We conclude that to explain and predict adaptation to climate change, the combination of personal experience and belief must be considered. [ABSTRACT FROM AUTHOR]

A system of equations for compatible prediction of total and merchantable volumes that allows for different definitions of tree volume was developed in this study. The use of the developed system will allow the conversion and subsequent comparison of results from forest inventories using different definitions of tree volume (e.g., including or not the top material of the tree and (or) the stump, inside or outside bark). The compatibility between taper, total volume, and volume ratio equations is ensured by properly integrating the taper equation. The diameter under the bark at any height is modeled with the Demaerschalk taper equation, and the corresponding diameter over the bark is obtained by assuming that bark thickness is also modeled with Demaerschalk’s function. The set of equations that has contemporaneous cross-equation error correlation (known as nonlinear seemingly unrelated regression equations) was fit using nonlinear joint generalized least squares regression. The predictive ability was evaluated using an independent data set. The system is consistent and performs well when applied to maritime pine (Pinus pinaster Ait.) trees in Portugal, showing better performance than do other total volume equations for maritime pine used in the latest Portuguese national forest inventories. Un système d’équations capable de prédire de façon compatible le volume total et le volume marchand et qui peut accepter différentes définitions du volume de l’arbre a été développé dans cette étude. L’utilisation du système proposé permettra de convertir et de comparer les résultats des inventaires forestiers en utilisant différentes définitions du volume de l’arbre (p. ex. en incluant ou non la partie supérieure de l’arbre ou la souche, avec ou sans écorce). La compatibilité entre les équations du défilement, du volume total et du rapport de volume est assurée en intégrant correctement l’équation du défilement. Le diamètre sans écorce à n’importe quelle hauteur est modélisé avec l’équation du défilement de Demaerschalk et le diamètre correspondant avec écorce est obtenu en supposant que l’épaisseur de l’écorce est également modélisée avec la fonction de Demaerschalk. L’ensemble des équations dont les termes d’erreur sont corrélés (connu sous le nom de régression sans corrélation apparente) a été ajusté à l’aide de la régression non-linéaire par la méthode des moindres carrés généralisés. La valeur prédictive a été évaluée en utilisant un ensemble indépendant de données. Le système est cohérent et fonctionne bien lorsqu’il est appliqué au pin maritime (Pinus pinaster Ait.) au Portugal. Il a une meilleure performance que les autres équations du volume total pour le pin maritime utilisées dans les derniers inventaires forestiers nationaux au Portugal. [ABSTRACT FROM AUTHOR]

The annual growth and the thickness of cork are known to be highly variable between trees located in the same geographical location. Researching how climate variables affect different trees within the same site is a step forward for the management of cork production since current knowledge focusses only on the average tree response. Quantile regression methodology was applied for the first time to a large data set containing measurements of cork growth, sampled in 35 stands across the cork oak distribution area in Portugal. This methodology proved to be useful for testing the hypothesis raised: does climate affect differently the annual cork growth, and ultimately cork thickness of individual trees located in the same stand? Estimating the amount of cork produced by one stand that has the required thickness for the production of natural cork stoppers is essential to support cork oak management. However, no model, before this work, had been developed to provide managers with this information. A downward parabolic relationship between annual cork growth and annual precipitation was determined for all quantiles, with optimum annual average precipitation value ranging from 1103 to 1007 mm. April to August monthly temperatures, spring average temperature or summer average temperature, showed a negative relationship with annual cork growth, in particular for lower quantiles. Maximum annual temperature was shown to negatively affect annual cork thickness, in particular for the trees under the 6th quantile. The ratio between annual precipitation and average temperature, that define the Lang index (LI), showed a downward parabolic relationship with annual cork growth. Best cork growth conditions are found for Lang index values around 60, corresponding for the transition between semi-arid climate and humid climate. The application of the final model developed for estimating cork thickness of an eight years' cork growth period allowed the prediction and mapping of the percentage of cork suitable for natural cork stopper production. It showed that higher values are expected in the Southern and Central coastal regions and along the Tagus River basin. The Northern coastal and mountain regions, characterised by Lang index values higher to 60 (humid climates), present lower estimated values for the percentage of cork suitable for natural cork stopper production. The estimated values are expected to be reduced under climate change scenarios in the Southern and Central coastal regions. [ABSTRACT FROM AUTHOR]

Food security, climate change mitigation, and land use challenges are interlinked and need to be considered simultaneously. One possible solution is sustainable intensification, which is the practice of increasing food production per area of land whilst also reducing the environmental impacts associated with this. Agroforestry has been stated to be a practice that meets this definition. In this study, a new methodology is presented to assess the potential of different management options as sustainable intensification practices. The methodology is based on comparing the carbon emissions associated with the production of food and the carbon sequestered for that same activity for a particular quantity of food produced over a specific area and over a specific time. The resulting indicator, the "carbon balance" is the difference between the greenhouse gasses emitted (considered as negative values) and carbon sequestered (positive values) estimated in Mg CO2eq per Mg of food produced on one hectare of land for one year. The carbon balance quantifies the global warming potential associated with sustainable intensification by integrating a process-based model with life cycle analysis and is able to estimate above- and below-ground biomass and soil carbon content. This methodology is tested in Portugal for wheat production under crop monoculture and agroforestry systems. The results show agroforestry to be a suitable practice for sustainable intensification compared to a crop monoculture as it just slightly decreased wheat yields whilst providing a positive carbon balance from year 50 onwards of approximately 1 Mg of CO2eq sequestered per Mg of wheat produced. [ABSTRACT FROM AUTHOR]

The aim of this study was to develop stem taper equations for trees of Pinus taeda L. inside and outside bark with extensive applicability to several age classes. Data were obtained from 631 trees of P. taeda, ranging from 4 to 31 years of age, in different stands distributed in several counties of the Midwest region of the state of Santa Catarina, Brazil. The taper models of Biging (1984), Schöpfer (1966), and Kozak et al. (1969) were tested. These models were fitted in their simplest formulation as well as by varying their coefficient linear functions of stand age with the procedure PROC NLIN in the software SAS® University Edition. There were no significant differences in accuracy and precision in the estimates between the simplest formulation of the Schöpfer (1966) model and the variation of its coefficient b linear function of age, and thus, the simplest formulation was chosen. Among all taper models tested, the Schöpfer (1966) model presented greater accuracy and precision to estimate diameters inside and outside bark, throughout the stem of Pinus taeda, in the Midwest region of the state of Santa Catarina, Brazil. [ABSTRACT FROM AUTHOR]

Highly accurate, rapid forest inventory techniques are needed to enable forest managers to address the increasing demand for sustainable forestry. In the last two decades, Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning have become internationally established as forest mapping and monitoring methods. However, recent advances in sensors and in image processing - particularly Structure from Motion (SfM) technology - have also enabled the extraction of dense point clouds from images obtained by Digital Aerial Photography (DAP). DAP is cheaper than ALS, especially when the systems are mounted on small unmanned aerial vehicles (UAVs), and the density of the point cloud can easily reach the levels yielded by ALS devices. The main objective of this study was to evaluate and compare the usefulness of ALS-derived and UAV(SfM)-derived highdensity point clouds for detecting and measuring individual tree height in Eucalyptus spp. plantations established on complex terrain. A total of 325 reference trees were measured and located in 6 square plots (400 m2). The individual tree crown (ITC) delineation algorithm detected 311 from the ALS-derived data and 259 trees from the UAV (SfM)-derived data, representing accuracy levels of, respectively, 96% and 80%. The results suggest that at plot level, UAV(SfM)-generated point clouds are as good as ALS-derived point clouds for estimating individual tree height. Furthermore, analysis of the differences in digital elevation models at landscape level showed that the elevations of the UAV(SfM)-derived terrain surfaces were slightly higher than the ALS-derived surfaces (mean difference, 1.14mand standard deviation, 1.93 m). Finally, we discuss how non-optimal UAV-image-acquisition conditions and slope terrain affect the ITC delineation process. [ABSTRACT FROM AUTHOR]

An accurate and objective estimate on the extent of agroforestry in Europe is critical for the development of supporting policies. For this reason, a more harmonised and uniform Pan-European estimate is needed. The aim of this study was to quantify and map the distribution of agroforestry in the European Union. We classified agroforestry into three main types of agroforestry systems: arable agroforestry, livestock agroforestry and high value tree agroforestry. These three classes are partly overlapping as high value tree agroforestry can be part of either arable or livestock agroforestry. Agroforestry areas were mapped using LUCAS Land Use and Land Cover data (Eurostat, 2015). By identifying certain combinations of primary and secondary land cover and/or land management it was possible to identify agroforestry points and stratify them in the three different systems. According to our estimate using the LUCAS database the total area under agroforestry in the EU 27 is about 15.4 million ha which is equivalent to about 3.6% of the territorial area and 8.8% of the utilised agricultural area. Of our three studied systems, livestock agroforestry covers about 15.1 million ha which is by far the largest area. High value tree agroforestry and arable agroforestry cover 1.1 and 0.3 million ha respectively. Spain (5.6 million ha), France (1.6 million ha), Greece (1.6 million ha), Italy (1.4 million ha), Portugal (1.2 million ha), Romania (0.9 million ha) and Bulgaria (0.9 million ha) have the largest absolute area of agroforestry. However the extent of agroforestry, expressed as a proportion of the utilised agricultural area (UAA), is greatest in countries like Cyprus (40% of UAA), Portugal (32% of UAA) and Greece (31% of UAA). A cluster analysis revealed that a high abundance of agroforestry areas can be found in the south-west quadrat of the Iberian Peninsula, the south of France, Sardinia, south and central Italy, central and north-east Greece, south and central Bulgaria, and central Romania. Since the data were collected and analysed in a uniform manner it is now possible to make comparisons between countries and identify regions in Europe where agroforestry is already widely practiced and areas where there are opportunities for practicing agroforestry on a larger area and introducing novel practices. In addition, with this method it is possible to make more precise estimates on the extent of agroforestry in Europe and changes over time. Because agroforestry covers a considerable part of the agricultural land in the EU, it is crucial that it gets a more prominent and clearer place in EU statistical reporting in order to provide decision makers with more reliable information on the extent and nature of agroforestry. Reliable information, in turn, should help to guide policy development and implementation, and the evaluation of the impact of agricultural and other policies on agroforestry. [ABSTRACT FROM AUTHOR]

The scientific community involved in the UN-REDD program is still reporting large uncertainties about the amount and spatial variability of CO2 stored in forests. The main limitation has been the lack of field samplings over space and time needed to calibrate and convert remote sensing measurements into aboveground biomass (AGB). As an alternative to costly field inventories, we examine the reliability of state-of-the-art lidar methods to provide direct retrieval of many forest metrics that are commonly collected through field sampling techniques (e.g., tree density, individual tree height, crown cover). AGB is estimated using existing allometric equations that are fed by lidar-derived metrics at either the individual tree- or forest layer-level (for the overstory or underneath layers, respectively). Results over 40 plots of a multilayered forest located in northwest Portugal show that the lidar method provides AGB estimates with a relatively small random error (RMSE = of 17.1%) and bias (of 4.6%). It provides local AGB baselines that meet the requirements in terms of accuracy to calibrate satellite remote sensing measurements (e.g., the upcoming lidar GEDI (Global Ecosystem Dynamics Investigation), and the Synthetic Aperture Radar (SAR) missions NISAR (National Aeronautics and Space Administration and Indian Space Research Organization SAR) and BIOMASS from the European Space Agency, ESA) for AGB mapping purposes. The development of similar techniques over a variety of forest types would be a significant improvement in quantifying CO2 stocks and changes to comply with the UN-REDD policies. [ABSTRACT FROM AUTHOR]

A generalized non-linear tree crown diameter model was developed with the aim of allowing the computation of tree crown diameter over a large range of tree dimensions, and allowing its inclusion in forest growth and yield models. The model was formulated to provide biological meaning to the predicted values. Due to the nested structure of the data analyzed (trees within stands), both mixed- and fixed-effect models were developed. Since tree crown diameter is not frequently measured in forest inventories, the validation of the mixed model was carried out by considering the population specific response. The results demonstrate that when the measurements required for the mixed model calibration are not available, the use of the fixed effect model results in less biased and more accurate estimates. The fixed model was applied to the data from the two last Portuguese National Forest Inventories (NFI) to analyze the change in stand crown cover and assess the stocking evolution of cork oak stands in Portugal between 1996 and 2006. Results showed an increase in the frequency of stands with crown cover lower than 20%, as well as a decrease in the frequency of stands with crown cover between 20 and 40%. Average crown cover values were significantly different in the two NFI, with a decrease from 28.0 to 26.5% over the considered period. [ABSTRACT FROM AUTHOR]

The growth and yield of mixed-species stands has become an important topic of research since there are certain advantages of this type of forest as regards functions and services. However, the concepts and methods used to characterize mixed stands need to be understood, as well as harmonized and standardized. In this review we have compiled a set of measures, indices, and methods at stand level to characterize the structure, dynamics, and productivity of mixed stands, and we discuss the pros and cons of their application in growth and yield studies. Parameters for the characterization of mixed stand structure such as stand density, species composition, horizontal (intermingling) and vertical tree distribution pattern, tree size distribution, and age composition are described, detailing the potential as well as the constraints of these parameters for understanding resource capture, use, and efficiency in mixed stands. Furthermore, a set of stand-level parameters was evaluated to characterize the dynamics of mixed stands, e.g. height growth and space partitioning, self- and alien-thinning, and growth partitioning among trees. The deviations and changes in the behaviour of the analysed parameters in comparison with pure stand conditions due to inter-specific interactions are of particular interest. As regards stand productivity, we reviewed site productivity indices, the growth-density relationship in mixed stands as well as methods to compare productivity in mixed versus monospecific stands. Finally, we discuss the main problems associated with the methodology such as up-scaling from tree to stand level as well as the relevance of standardized measures and methods for improving forest growth and yield research in mixed stands. The main challenges are also outlined, especially the need for qualitatively sound data. [ABSTRACT FROM AUTHOR]

Assessment of forest fuel loading is a prerequisite for most fire management activities. However, the inclusion of shrub biomass in forest planning has been hindered by the inability to predict its growth and accumulation. The main objective of this study was to model shrub biomass over time under a tree canopy with the aim of including shrub management in fire risk mitigation plans. To this purpose, data was obtained from the 4th and 5th Portuguese National Forest Inventories. Five biologically realistic models were built to describe shrub biomass accumulation in Portuguese forests. The selected model indicates that maximum biomass is affected by stand basal area and the percentage of resprouting shrub species in the stand. Biomass growth rate was clearly affected by the regeneration strategies of shrubs in combination with climatic conditions (mean annual temperature). The model can be used in the accumulation form for initialization purposes or in one of the two alternative difference forms to project observed shrub biomass. The model proposed in this study facilitates the inclusion of shrub biomass in forest growth simulations, and will contribute to more accurate estimates of fire behavior characteristics and stored carbon. This is essential to improve decision-making in forest management plans that integrate fire risk, namely to schedule understory fuel treatments. [ABSTRACT FROM AUTHOR]

Dans le cadre des politiques de lutte contre le réchauffement climatique (programme UN-REDD des Nations Unies), les techniques de télédétection sont désormais utilisées pour extrapoler des estimations de la biomasse aérienne à l'échelle locale (dérivées à partir des mesures terrain obtenues via des inventaires forestiers) sur des grandes surfaces où aucune donnée de référence n'est disponible. Néanmoins, la communauté scientifique signale encore une grande incertitude concernant la quantification du CO2 stocké dans les forêts. Cela est dû au nombre insuffisant d'échantillons terrains surdes grandes zones de forêt de la planète, notamment dans des pays qui n'ont pas de pratiques régulières d'inventaires forestiers. Dans cet article, nous investiguons la fiabilité de la technologie lidar aéroporté (airborne laser scanning, ALS) pour estimer la biomasse aérienne des forêts sans nécessiter d'importantes mesures terrain. D'abord, des métriques forestières clés qui sont couramment obtenues via les inventaires forestiers traditionnels sont dérivées par analyse des donnés lidar. Il s'agit notamment de la densité d'arbres, leur hauteur individuelle, l'épaisseur de la couronne, la hauteur moyenne de chaque strate, et le taux de couverture de canopée de chacune de celles-ci. Puis, des équations allométriques sont utilisées pour estimer la biomasse à partir des mesures terrain ainsi que des mesures lidar. Enfin, les résultats sont évalués pour chaque strate de végétation sur 40 parcelles d'une forêt portugaise à plusieurs strates de végétation. La biomasse aérienne est dérivée à l'échelle de la placette forestière avec une erreur de 0,4% comparée aux estimations terrain, ce qui prouve que notre approche est un outil efficace pour estimer la biomasse aérienne avec précision. Le développement de techniques similaires fondées sur le lidar aéroporté, capables de traiter forêts de différents biomes, avec l'utilisation conjointe de mesures obtenues par télédétection satellitaire, serait une avancée significative pour l'estimation de la biomasse sur de vastes régions à l'échelle mondiale. [ABSTRACT FROM AUTHOR]

This paper presents a model to predict annual wildfire risk in pure and evenaged eucalypt stands in Portugal. Emphasis was in developing a management- oriented model, i.e., a model that might both: (a) help assess wildfire occurrence probability as a function of readily available forest inventory data; and (b) help predict the effects of management options (e.g., silvicultural treatments) on the risk of fire in eucalypt stands. Data from both the 1995/1998 and the 2005/2006 Portuguese National Forest Inventories as well as wildfire perimeters' data were used for modeling purposes. Specifically, this research considered 1122 inventory plots with approximately 1.2 million trees and 85 wildfire perimeters. The model to predict the probability of wildfire occurrence is a logistic function of measurable and controllable biometric and environmental variables. Results showed that wildfire occurrence probability in a stand increases with the ratio basal area/quadratic mean diameter and with the shrubs biomass load, while it decreases with stand dominant height. They further showed that the probability of wildfire occurrence is higher in stands that are over 1 Km distant from roads. These results are instrumental for assessing the impact of forest management options on wildfire risk levels thus helping forest managers develop plans that may mitigate wildfire impacts. [ABSTRACT FROM AUTHOR]

Abstract: This study presents a robust approach for characterization of multi-layered forests using airborne laser scanning (ALS) data. Fuel mapping or biomass estimation requires knowing the diversity and boundaries of the forest patches, as well as their spatial pattern. This includes the thickness of the main vegetation layers, but also the spatial arrangement and size of the individual plants that compose each stratum. In order to decompose the ALS point cloud into genuine 3-D segments corresponding to individual vegetation features, such as shrubs or tree crowns, we apply a statistical approach based on the mean shift algorithm. The segments are progressively assigned to a forest layer: ground vegetation, understory or overstory. Our method relies on a single biophysically meaningful parameter, the kernel bandwidth, which is related to the local forest structure. It is validated on 44 plots of a Portuguese forest, composed mainly of eucalyptus (Eucalyptus globulus Labill.) and maritime pine (Pinus pinaster Ait.) trees. The number of detected trees varies with the dominance position: from 98.6% for the dominant trees to 12.8% for the suppressed trees. Linear regression models explain up to 70% of the variability associated with ground vegetation and understory height. [Copyright &y& Elsevier]

Modelling masting habit, i.e. the spatial synchronized annual variability in fruit production, is a huge task due to two main circumstances: (1) the identification of main ecological factors controlling fruiting processes, and (2) the common departure of fruit data series from the main basic statistical assumptions of normality and independence. Stone pine (Pinus pinea L.) is one of the main species in the Mediterranean basin that is able to grow under hard limiting conditions (sandy soils and extreme continental climate), and typically defined as a masting species. Considering the high economical value associated with edible nut production, the masting habit of stone pine has been a main concern for the forest management of the species. In the present work we have used annual fruit data series from 740 stone pine trees measured during a 13 years period (1996–2008) in order: (a) to verify our main hypothesis pointing out to the existence of a weather control of the fruiting process in limiting environments, rather than resource depletion or endogenous inherent cycles; (b) to identify those site factors, stand attributes and climate events affecting specific traits involved in fruiting process; and (c) to construct a model for predicting spatial and temporal patterns of variability in stone pine cone production at different spatial extents as region, stand and tree. Given the nature of the data, the model has been formulated as zero-inflated log-normal, incorporating random components to carry out with the observed lack of independence. This model attains efficiencies close to 70–80% in predicting temporal and spatial variability at regional scale. Though efficiencies are reduced according to the spatial extent of the model, it leads to unbiased estimates and efficiencies over 35–50% when predicting annual yields at tree or stand scale, respectively. In this sense, the proposed model is a main tool for facilitating decision making in some management aspects such as the quantification of total amount of cones annually supplied to nut industry, design of cone harvest programs or the optimal application of seedling felling. [Copyright &y& Elsevier]

The work described in this paper aimed to establish a single set of parameter values for a process-based model (3-PG), applicable to Eucalyptus globulus Labill. in Portugal. Initial testing was done with parameter values from Australia using climate, biometric, and soils data from an irrigation and fertilization trial and a spacing trial. The model provided good estimates for stem mass and basal area, poor estimates for leaf mass, and reasonable estimates for volume. The fit between simulated and observed values was then improved by tuning parameter values to produce a final set. The calibrated model was tested, and performed well, against data from permanent sample plots (PSPs) at different locations across Portugal. Volume and basal area predictions made by 3-PG for PSPs were then compared with predictions made by the empirical model in use for E. globulus plantations in Portugal. Differences were negligible. Model outputs with the Australian parameter set and the optimum set for Portugal indicated that partitioning of carbohydrates (net primary productivity) was very different in E. globulus grown in Portugal and Australia. The study has confirmed the potential of this process-based model as a practical tool to support forest management decision-making. [ABSTRACT FROM AUTHOR]

Ground point filtering of the airborne laser scanning (ALS) returns is crucial to derive digital terrain models (DTMs) and to perform ALS-based forest inventories. However, the filtering calibration requires considerable knowledge from users, who normally perform it by trial and error without knowing the impacts of the calibration on the produced DTM and the forest attribute estimation. Therefore, this work aims at calibrating four popular filtering algorithms and assessing their impact on the quality of the DTM and the estimation of forest attributes through the area-based approach. The analyzed filters were the progressive triangulated irregular network (PTIN), weighted linear least-squares interpolation (WLS) multiscale curvature classification (MCC), and the progressive morphological filter (PMF). The calibration was established by the vertical DTM accuracy, the root mean squared error (RMSE) using 3240 high-accuracy ground control points. The calibrated parameter sets were compared to the default ones regarding the quality of the estimation of the plot growing stock volume and the dominant height through multiple linear regression. The calibrated parameters allowed for producing DTM with RMSE varying from 0.25 to 0.26 m, against a variation from 0.26 to 0.30 m for the default parameters. The PTIN was the least affected by the calibration, while the WLS was the most affected. Compared to the default parameter sets, the calibrated sets resulted in dominant height equations with comparable accuracies for the PTIN, while WLS, MCC, and PFM reduced the models' RMSE by 6.5% to 10.6%. The calibration of PTIN and MCC did not affect the volume estimation accuracy, whereas calibrated WLS and PMF reduced the RMSE by 3.4% to 7.9%. The filter calibration improved the DTM quality for all filters and, excepting PTIN, the filters increased the quality of forest attribute estimation, especially in the case of dominant height. [ABSTRACT FROM AUTHOR]

The analysis of the diameter distribution is important for forest management since the knowledge of tree density and growing stock by diameter classes is essential to define management plans and to support operational decisions. The modeling of diameter distributions from airborne laser scanning (ALS) data has been performed through the two-parameter Weibull probability density function (PDF), but the more flexible PDF Johnson's SB has never been tested for this purpose until now. This study evaluated the performance of the Johnson's SB to predict the diameter distributions based on ALS data from two of the most common forest plantations in the northwest of the Iberian Peninsula (Eucalyptus globulus Labill. and Pinus radiata D. Don). The Weibull PDF was taken as a benchmark for the diameter distributions prediction and both PDFs were fitted with ALS data. The results show that the SB presented a comparable performance to the Weibull for both forest types. The SB presented a slightly better performance for the E. globulus, while the Weibull PDF had a small advantage when applied to the P. radiata data. The Johnson's SB PDF is more flexible but also more sensitive to possible errors arising from the higher number of stand variables needed for the estimation of the PDF parameters. [ABSTRACT FROM AUTHOR]

Background: We analyzed the dynamics of carbon (C) stocks and CO2 removals by Brazilian forest plantations over the period 1990-2016. Data on the extent of forests compiled from various sources were used in the calculations. Productivities were simulated using species-specific growth and yield simulators for the main trees species planted in the country. Biomass expansion factors, root-to-shoot ratios, wood densities, and carbon fractions compiled from literature were applied. C stocks in necromass (deadwood and litter) and harvested wood products (HWP) were also included in the calculations.Results: Plantation forests stocked 231 Mt C in 1990 increasing to 612 Mt C in 2016 due to an increase in plantation area and higher productivity of the stands during the 26-year period. Eucalyptus contributed 58% of the C stock in 1990 and 71% in 2016 due to a remarkable increase in plantation area and productivity. Pinus reduced its proportion of the carbon storage due to its low growth in area, while the other species shared less than 6% of the C stocks during the period of study. Aboveground biomass, belowground biomass and necromass shared 71, 12, and 5% of the total C stocked in plantations in 2016, respectively. HWP stocked 76 Mt C in the period, which represents 12% of the total C stocked. Carbon dioxide removals by Brazilian forest plantations during the 26-year period totaled 1669 Gt CO2-e.Conclusions: The carbon dioxide removed by Brazilian forest plantations over the 26 years represent almost the totality of the country´s emissions from the waste sector within the same period, or from the agriculture, forestry and other land use sector in 2016. We concluded that forest plantations play an important role in mitigating GHG (greenhouse gases) emissions in Brazil. This study is helpful to improve national reporting on plantation forests and their GHG sequestration potential, and to achieve Brazil’s Nationally Determined Contribution and the Paris Agreement. [ABSTRACT FROM AUTHOR]