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ABSTRACT. Forest transitions (FT) occur when socioeconomic development leads to a shift from net deforestation to reforestation; these dynamics have been observed in multiple countries across the globe, including the island of Puerto Rico in the Caribbean. Starting in the 1950s, Puerto Rico transitioned from an agrarian to a manufacturing and service economy reliant on food imports, leading to extensive reforestation. In recent years, however, net reforestation has leveled off. Here we examine the drivers of forest transition in Puerto Rico from 1977 to 2000 at two subnational, nested spatial scales (municipality and barrio) and over two time periods (1977-1991 and 1991-2000). This study builds on previous work by considering the social and biophysical factors that influence both reforestation and deforestation at multiple spatial and temporal scales. By doing so within one analysis, this study offers a comprehensive understanding of the relative importance of various social and biophysical factors for forest transitions and the scales at which they are manifest. Biophysical factors considered in these analyses included slope, soil quality, and land-cover in the surrounding landscape. We also considered per capita income, population density, and the extent of protected areas as potential factors associated with forest change. Our results show that, in the 1977-1991 period, biophysical factors that exhibit variation at municipality scales (~100 km²) were more important predictors of forest change than socioeconomic factors. In this period, forest dynamics were driven primarily by abandonment of less productive, steep agricultural land in the western, central part of the island. These factors had less predictive power at the smaller barrio scale (~10 km²) relative to the larger municipality scale during this time period. The relative importance of socioeconomic variables for deforestation, however, increased over time as development pressures on available land increased. From 1991-2000, changes in forest cover reflected influences from multiple factors, including increasing population densities, land development pressure from suburbanization, and the presence of protected areas. In contrast to the 1977-1991 period, drivers of deforestation and reforestation over this second interval were similar for the two spatial scales of analyses. Generally, our results suggest that although broader socioeconomic changes in a given region may drive the demand for land, biophysical factors ultimately mediate where development occurs. Although economic development may initially result in reforestation due to rural to urban migration and the abandonment of agricultural lands, increased economic development may lead to deforestation through increased suburbanization pressures.

In this paper, a two stage ingrowth model is presented for predicting periodic, 10 years ingrowth for pyrenean oak (Quercus pyrenaica Willd.) grown in medium to fully stocked coppice stands in north-western Spain. Data from the Spanish National Forest Inventory was used to develop the model, extracting the information from two inventories taken in 222 permanent plots. The first stage of the model predicts the probability of ingrowth occurrence, and in the second stage, the number of recruits is predicted using a conditional model. Both models were biologically realistic and presented logical behaviour. The ingrowth occurrence probability model was dependent on quadratic mean diameter and average height. The recruitment quantification model included stand density and average diameter as explanatory variables. Although the occurrence probability of ingrowth was predicted correctly in 71.7% of cases, the predictions of the number of recruitment are poorer, yielding a coefficient of determination of 0.358. The evaluation criteria included qualitative and quantitative examinations and a testing with independent data from another region. The proposed ingrowth model is the first to be developed for mediterranean oak species in Spain and is an essential feature in any stand growth system.

-A dominant height growth model and a site index model were developed for rebollo oak (Quercus pyrenaica Willd.) in northwest Spain. Data from 147 stem analysis in 90 permanent plots, where rebollo oak was the main species, were used for modelling. The plots were selected from the National Forest Inventory at random in proportion to four biogeoclimatic stratums. Different traditional and generalized algebraic difference equations were tested. The evaluation criteria included qualitative and quantitative examinations and a testing with independent data from another region. The generalized algebraic difference equation of Cieszewski based on Bailey equation showed the best results for the four stratums. An analysis of the height growth patterns among ecological stratums was made in order to study the necessity of different site index curves. Results indicated the validity of a common height growth model for the four stratums. In spite of the irregular height growth pattern observed in rebollo oak, probably due to past management, the model obtained allows us to classify and compare correctly rebollo oak stands growing at different sites.growth model / site index / rebollo oak / coppices / algebraic difference equations Résumé -Modèle de croissance en hauteur et qualité de station de chêne tauzin (Quercus pyrenaica Willd.). Les auteurs ont développé un modèle de croissance pour estimer la hauteur dominante et la qualité de station des peuplements de chêne tauzin (Quercus pyrenaica Willd.) dans le NordOuest de l'Espagne. Les données pour établir ce modèle proviennent d'analyse de tiges de 147 arbres dominants de 24 placettes permanentes où l'espèce est la plus représentée. Ces placettes de l'Inventaire Forestier Espagnol ont été proportionnellement réparties dans quatre régions biogéoclimatiques. Huit équations en différences algébriques et huit équations en différences algébriques généralisées ont été essayées pour développer des courbes de croissance. Des analyses numériques, des analyses graphiques et une validation sur un échantillonnage indépendant ont été utilisées pour comparer les différents modèles existants. La fonction de Cieszewski fondée sur l'équation de Bailey avec la méthode des différences algébriques généralisées a donné les meilleurs résultats dans les quatre régions biogéoclimatiques. Les différences des modèles entre écorégions ont été étudiées afin de déterminer si la construction de quatre modèles régionaux différents était nécessaire. Les résultats indiquent qu'un seul modèle commun est utilisable pour toutes les régions étudiées. Malgré une croissance irrégulière en hauteur dominante du chêne tauzin, probablement à cause des gestions antérieures, le modèle recommandé permet de classer et comparer correctement les peuplements de chêne tauzin qui poussent dans différentes régions. modèle de croissance en hauteur / qualité de station / chêne tauzin / taillis / différences algébriques généralisées

Keywords:individual-tree mortality model / logistic regression / mixed model / rebollo oak / Mediteranean oak Abstract • Tree mortality is an important process in forest ecosystem dynamics and is one of the least understood phenomena, because of the complex interactions between different environmental stresses, minimal understanding of whole-plant mortality processes, and a chronic shortage of data.• A multilevel logistic regression model was developed for predicting the probability of mortality in individual trees with the objective of improving long-term planning in Spanish pyrenean oak forests. The data came from one 10-year re-measurement of the permanent plot network belonging to the Spanish National Forest Inventory distributed throughout north-west Spain.• The probability of mortality decreased with increasing individual diameter at breast height and increasing ratio of the height of subject tree to the dominant height of the sample plot. The resulting mortality model was evaluated using an independent data set from a region close to the study area.• The regeneration of pyrenean oak generally takes place through stump and/or root sprouting; so stand dynamics differ from those of others species. The model developed is expected to improve the accuracy of stand forecasts in northwest Spain.

• Key message A dataset of forest resource projections in 23 European countries to 2040 has been prepared for forestrelated policy analysis and decision-making. Due to applying harmonised definitions, while maintaining country-specific forestry practices, the projections should be usable from national to international levels. The dataset can be accessed at https://doi.org/10.5061/dryad.4t880qh. The associated metadata are available at https://metadata-afs.nancy.inra.fr/ geonetwork/srv/eng/catalog.search#/metadata/8f93e0d6-b524-43bd-bdb8-621ad5ae6fa9.

Aim of study: Understanding the factors that control tree growth in successional stands is particularly important for quantifying the carbon sequestration potential and timber yield of secondary tropical forests. Understanding the factors that control tree growth in successional stands is particularly important for quantifying the carbon sequestration potential and timber yield of secondary tropical forests. Yet, the high species diversity of mixed tropical forests, including many uncommon species, hinders the development of species-specific diameter growth models.Area of study: In these analyses, we grouped 82 species from secondary forests distributed across 93 permanent plots on the island of Puerto Rico.Material and Methods: Species were classified according to regeneration strategy and adult height into six functional groups. This classification allowed us to develop a robust diameter growth model using growth data collected from 1980-1990. We used mixed linear model regression to analyze tree diameter growth as a function of individual tree characteristics, stand structure, functional group and site factors.Main results: The proportion of variance in diameter growth explained by the model was 15.1%, ranging from 7.9 to 21.7%. Diameter at breast height, stem density and functional group were the most important predictors of tree growth in Puerto Rican secondary forest. Site factors such as soil and topography failed to predict diameter growth.