Tree height is a key variable for assessing forest functioning and resources (e.g. volume, carbon stocks) at both tree and stand levels. However, direct field measurements are costly and time-consuming. Developing accurate and unbiased height-diameter allometries applicable over large spatial scales is therefore crucial for forest research and management. Based on the French National Forest Inventory, with 269,460 tree-height observations on 49,120 plots measured, we developed generalized, species-specific height-diameter allometries that integrate stand dendrometrical characteristics and stand structure. The models cover 41 European tree species and the four main stand structures: even-aged, uneven-aged, coppice-with-standards and coppice. We provide a recalibration method that practitioners can optionally use, directly on the field, to enhance local accuracy. This method, used at plot level, assesses how many additional trees should be measured and which ones to select to maximize the improvement of the model, by keeping the method easily usable on the field. By integrating basal area as stand density and quadratic mean diameter as an indicator of stand development stage, our models enable us to assess the influence stand dendrometrical characteristics on these allometries and evaluate how different species responded to competition. Results indicate that with increasing competition, tree height tends to be higher for a given diameter, and that stand structure significantly influences 28 out of the 41 species. Local recalibration showed that measuring just one to six trees (among the largest and thinnest diameter) per plot reduced prediction error by 10–70

The influence of environmental factors on the dynamics of tree species can imply non-linear relationships. Some of them exhibit threshold effects. Hyperbolic functions effectively represent ecological processes that display threshold behaviours. However, the mathematical formulation of the hyperbola is complex, which makes its use challenging and its parameters difficult to interpret. In this article, we propose an efficient mathematical formulation for the hyperbola, one in which all the parameters are independent and easily interpretable. We also provide an R script and a Python script to facilitate the implementation of this hyperbolic formulation in modelling studies. We then modelled the influence of edaphic and climatic factors on the growth of 18 forest tree species widely distributed across Europe based on a dataset of 8,330 plots from the French National Forest Inventory. Our hyperbolic function allowed us to identify the threshold effects of summer climatic constraints on forest growth for several species. In particular, we found negative effects for soil water deficit and maximum summer temperature, although for several species these effects only appear beyond a certain level of constraint. Accounting for such threshold effects is crucial to improve our ability to understand and predict forest ecosystem responses in the context of climate change.

Tree height is a key variable for assessing forest functioning and resources (e.g volume, carbon stocks) at both tree and stand levels. However, direct field measurements are costly and time-consuming. Developing accurate and unbiased height-diameter allometries applicable over large spatial scales is therefore crucial for forest research and management. Based on the French National Forest Inventory, with 269,976 tree-height observations on 49,234 plots measured, we developed generalized, species-specific height-diameter allometries that integrate stand dendrometrical characteristics and stand structure. The models cover 42 European tree species and the four main stand structures: even-aged, uneven-aged, coppice-with-standards and coppice. To enhance local accuracy, we developed an optional recalibration method at the plot level, assessing how many additional trees should be measured and which ones to select to maximize the improvement of the model. By integrating basal area as stand density and quadratic mean diameter as an indicator of stand development stage, our models enable us to assess the influence stand dendrometrical characteristics on these allometries and evaluate how different species responded to competition. Results indicate that with increasing competition, tree height tends to be higher for a given diameter, and that stand structure significantly influences 30 out of the 42 species. Local recalibration showed that measuring just one to six of the largest trees per plot reduced prediction error by 20 to 70%, depending on species. This study provides a useful, robust and scalable tool for forest research and management, for the most widespread species in Europe, while offering precision for local applications. ### Competing Interest Statement The authors have declared no competing interest. Office National des forêts, https://ror.org/01yekza56, Régénération, croissance et production des forêts de plaine, 2022-2024

Forests provide many ecosystem services that strongly depend on species diversity, as illustrated by the repeatedly observed diversity-productivity relationships (DPRs). These forest DPRs are assumed to result mostly from complementarity between species at the tree level whilst emerging community-level processes remain poorly explored. In this study, we propose that the 'tree packing effect' (TPE), where species diversity promotes productivity by positively impacting maximum stand density, is an important determinant of DPRs. We tested the two components of TPE: (i) whether maximum stand density increases with species richness and (ii) whether this higher stand density allowed by species richness promotes forest productivity. First, relying on national forest inventories of six European countries (NFIs, totaling 2,367,776 trees), we fitted self-thinning lines to examine whether these lines were influenced by plot species richness. We showed that maximum stand density increases with tree species richness in Europe, in all but one country. This trend was notably stronger in extreme climates. Second, we ran a large simulation-based experiment (including 7,024,815 simulations) with an individual-based forest dynamics model able to control for stand-density effects, to quantify DPRs for more than 1000 sites in Europe. Relying on an original method to quantify DPRs at the site level, we compared the strength of DPRs simulated with and without control for stand density. We found positive DPRs up to 10-times stronger when TPE is at play than when stand density is controlled. This positive effect of diversity on forest productivity through tree packing is also stronger in extreme climates, especially in warm and dry conditions. Synthesis. Highlighting the generality of the TPE in European forests, our results reveal that the effect of diversity on forest functioning is partly mediated by diversity-driven changes in stand density. This mechanism has been long overlooked in biodiversity-ecosystem functioning studies, but our findings strongly call for its reconsideration, especially in natural forests. It also opens key perspectives for management and climate change mitigation programmes. Les forê ts fournissent de nombreux services é cosysté miques aux populations, et ceux-ci dé pendent fortement de la diversité en espè ces, comme cela a é té fré quemment montré. Ces relations diversité-fonctionnement sont supposé es ré sulter principalement de la complé mentarité entre espè ces d'arbres au niveau individuel, alors que les processus é mergents à l'é chelle des communauté s restent peu é tudié s. Dans cette é tude, nous proposons qu'un effet de << densification des arbres >> (<< Tree packing effect >>, TPE), selon lequel la diversité des espè ces favourise la productivité en ayant un effet positif sur la densité maximale du peuplement, soit un dé terminant important des relations entre diversité et productivité forestiè re. Nous avons ici testé les deux composantes du << TPE >>: (i) si la densité maximale du peuplement augmente avec la richesse en espè ces, et (ii) si cette densité de peuplement plus é levé e grâ ce à la richesse en espè ces favourise la productivité forestiè re. Tout d'abord, en nous appuyant sur les inventaires forestiers nationaux de six pays europé ens (totalisant 2,367,776 arbres), nous avons estimé les lignes d'auto-é claircie afin d'examiner si ces lignes é taient influencé es par la richesse en espè ces. Nous avons ainsi montré que la densité maximale des peuplements augmente avec la richesse en espè ces d'arbres en Europe, dans tous les pays sauf un. Cette tendance é tait notamment plus forte dans les climats plus extrê mes. Deuxiè mement, nous avons mené une vaste expé rience virtuelle (comprenant 7,024,815 simulations indé pendantes) avec un modè le de dynamique forestiè re individu-centré capable de contrô ler les effets de la densité des peuplements, afin de quantifier les relations diversité-productivité pour plus de 1000 sites en Europe. En nous appuyant sur une mé thode originale pour quantifier ces relations au niveau du site, nous avons comparé la force des effets diversité simulé s avec et sans contrô le de la densité des peuplements. Synthè se. Soulignant le caractè re gé né ral du << TPE >> dans les forê ts europé ennes, nos ré sultats montrent que l'effet de la diversité sur le fonctionnement forestier est. en partie contrô lé par les changements de densité de peuplement induits par la diversité. Ce mé canisme a longtemps é té né gligé dans les é tudes liant biodiversité et fonctionnement des é cosystè mes, mais nos ré sultats invitent fortement à le reconsidé rer, en particulier dans les forê ts naturelles. Cette é tude ouvre é galement des perspectives importantes pour les programmes de gestion et d'atté nuation du changement climatique.

Cette étude explore la résilience de la productivité des peuplements forestiers mélangés en France dans un contexte de changements climatiques, à partir des données de l’inventaire forestier national. 21 mélanges d’essences et leurs monocultures associées ont été analysés par modélisation en deux étapes contrôlant les biais observationnels. Cinq indicateurs de résilience ont été établis. Les résultats montrent une plus grande stabilité moyenne des mélanges, mais sans supériorité systématique par rapport aux monocultures associées. Deux dimensions de la résilience par étude de corrélation sont identifiées. L’étude souligne le potentiel d’un suivi national par l’inventaire pour évaluer la résilience des forêts mélangées. Messages clés : - Les peuplements mélangés affichent une stabilité de productivité supérieure à celle des monocultures, en raison d'une fréquence moindre d’années à productivité exceptionnellement élevée. - Aucun avantage généralisé des mélanges par rapport aux monocultures associées n’est observé. - L’inventaire forestier national est un outil pertinent pour le suivi de la résilience des forêts face aux changements climatiques.

Analyzing how climate change has affected forest growth is crucial for predicting future dynamics and adapting forest management to future climate change. In this paper, we investigate how climate change has modified stand dominant height dynamics and site index of 20 European tree species. We used an innovative method based on an annual height increment equation to model stand dominant height as a function of climate back to 1872 and of other stand environmental conditions. We used these models to simulate stand dominant height dynamics and site index under two different climates (prior to climate change and actual recent climate) to analyze the impact of climate change over the past century. To build our models, we combined the recently published FYRE long-term climate database, which provides daily data since 1871, with data from more than 17,000 forest stands of the French National Forest Inventory network. Higher temperature, precipitation and climatic water balance generally favor stand dominant height dynamics when the variables are considered separately. However, the positive effects often saturate at the higher end of the variable distribution. Over the past century, the effect of climate change on the site index has varied widely among species, ranging from a decrease of less than 3% to an increase of more than 5%. The effect of climate change has also varied within species, with more positive effects on initially temperature-limited stands for some species. For the species and environmental conditions considered, our results highlight a positive response of site index to past climate change for most species, albeit with between- and within-species differences. Our results also suggest that this positive response could become negative under continued climate change. These conclusions, as well as the quantitative relationships we provide between climate and stand dominant height dynamics or site index, will help design management strategies to adapt forests to climate change.

Recent observations of tree regeneration failures following large and severe disturbances, particularly under warm and dry conditions, have raised concerns about the resilience of forest ecosystems and their recovery dynamics in the face of climate change. We investigated the recovery of temperate forests in Europe after large and severe disturbance events (i.e., resulting in more than 70% canopy loss in patches larger than 1 ha), with a range of one to five decades since the disturbance occurred. The study included 143 sites of different forest types and management practices that had experienced 28 disturbance events, including windthrow (132 sites), fire (six sites), and bark beetle outbreaks (five sites). We focused on assessing post-disturbance tree density, structure, and composition as key indicators of forest resilience. We compared post-disturbance height-weighted densities with site-specific pre-disturbance densities to qualitatively assess the potential for structural and compositional recovery, overall and for dominant tree species, respectively. Additionally, we analyzed the ecological drivers of post-windthrow tree density, such as forest management, topography, and post-disturbance aridity, using a series of generalized additive models. The descriptive results show that European temperate forests have been resilient to past large and severe disturbances and concurrent climate conditions, albeit with lower resilience to high-severity fire compared with other disturbance agents. Across sites and disturbance agents, the potential for structural recovery was greater than that of compositional recovery, with a large proportion of plots becoming dominated by early-successional species after disturbance. The models showed that increasing elevation and salvage logging negatively affect post-windthrow regeneration, particularly for late-successional species, while pioneer species are negatively affected by increasing summer aridity. These findings provide a key baseline for assessing future recovery and resilience following the recent occurrence of widespread disturbance in the region and in anticipation of future conditions characterized by increasing heat and drought stress. As a result of global change, forest disturbances are becoming larger and more severe, which may put forest recovery at risk, especially under a warm and dry climate. Our study shows that European temperate forests have been able to recover after large and severe disturbances and concurrent climate conditions, although with more difficulty after fires compared with other disturbance agents. The main factors negatively influencing tree regeneration after wind disturbances were increasing elevation and the removal of damaged trees from the disturbed forests.image

Adapting forests to climate change is a major challenge for forest ecology and forestry. Among the management options available, encouraging the use of mixtures is a promising way forward. However, this practice requires a thorough understanding of how species respond to mixing. In this article, we analyzed species dominant height responds to mixing and how species ontogeny and traits drive this response. We compared species observed dominant height in mixed even-aged stands with the expected dominant height of the same species in a monospecific stand under the same environmental conditions. We then related this dominant height variation due to mixing to between-species dominant height difference and to species traits linked to competition (shade tolerance, wood density, specific leaf area). We focused our analyses on 76 pairs of forest tree species. We used data from the French National Forest Inventory to calculate species dominant height in 1368 mixed stands. We then used previously developed models to estimate the expected dominant height in virtual monospecific stands with the same environmental conditions. We found that mixture had a significant impact on species dominant height for 15 out of 50 species-combination considered. Dominant height of a given species was higher in mixture than in pure stands when this species had a lower dominant height in pure stands, a lower shade tolerance, a lower specific leaf area or a higher wood density than its companion species. Our results suggest that species dominant height response to mixing depends on how mixture influences the competition for light. Our results will help inform strategies aiming to diversify species in forests, and will be especially useful in anticipating a given species' behavior in response to competition for light when it is mixed with other species.

Ecology and forestry sciences are using an increasing amount of data to address a wide variety of technical and research questions at the local, continental and global scales. However, one type of data remains rare: fine-grain descriptions of large landscapes. Yet, this type of data could help address the scaling issues in ecology and could prove useful for testing forest management strategies and accurately predicting the dynamics of ecosystem services. Here we present three datasets describing three large European landscapes in France, Poland and Slovenia down to the tree level. Tree diameter, height and species data were generated combining field data, vegetation maps and airborne laser scanning (ALS) data following an area-based approach. Together, these landscapes cover more than 100 000 ha and consist of more than 42 million trees of 51 different species. Alongside the data, we provide here a simple method to produce high-resolution descriptions of large landscapes using increasingly available data: inventory and ALS data. We carried out an in-depth evaluation of our workflow including, among other analyses, a leave-one-out cross validation. Overall, the landscapes we generated are in good agreement with the landscapes they aim to reproduce. In the most favourable conditions, the root mean square error (RMSE) of stand basal area (BA) and mean quadratic diameter (Dg) predictions were respectively 5.4 m2.ha-1 and 3.9 cm, and the generated main species corresponded to the observed main species in 76.2% of cases.

Ecology and forestry sciences are using an increasing amount of data to address a wide variety of technical and research questions at the local, continental and global scales. However, one type of data remains rare: fine-grain descriptions of large landscapes. Yet, this type of data could help address the scaling issues in ecology and could prove useful for testing forest management strategies and accurately predicting the dynamics of ecosystem services. Here we present three datasets describing three large European landscapes in France, Poland and Slovenia down to the tree level. Tree diameter, height and species data were generated combining field data, vegetation maps and airborne laser scanning (ALS) data following an area-based approach. Together, these landscapes cover more than 100 000 ha and consist of more than 42 million trees of 51 different species. Alongside the data, we provide here a simple method to produce high-resolution descriptions of large landscapes using increasingly available data: inventory and ALS data. We carried out an in-depth evaluation of our workflow including, among other analyses, a leave-one-out cross validation. Overall, the landscapes we generated are in good agreement with the landscapes they aim to reproduce. In the most favourable conditions, the root mean square error (RMSE) of stand basal area (BA) and mean quadratic diameter (Dg) predictions were respectively 5.4 m2.ha-1 and 3.9 cm, and the generated main species corresponded to the observed main species in 76.2% of cases.

Aim The distribution of overmature forests in metropolitan France is poorly known, with only a few well-studied prominent sites, and has never been evaluated countrywide. Here, we modelled French forest reserves’ time since the last harvesting operation - a proxy for forest maturity - then inferred the current statistical distribution of overmature forests (i.e. forests over 50 years without harvesting) in France. Location Metropolitan France Methods We used inventories from forest reserves and managed forests to calibrate a generalised linear mixed model explaining the time since the last harvesting with selected structural attributes and environmental variables. We then projected this model on the independent National Forest Inventory dataset. We thus obtained an updated estimation of the proportion and a rough distribution of overmature forest stands in metropolitan France. Results We found that high basal area of very large trees, high volumes of standing and downed deadwood, high diversity of tree-related microhabitats and more marginally diversity of decay stages best characterized the time since the last harvesting. Volumes of stumps and high density of coppices translating legacy of past forest management also distinguished more overmature plots. Our projection yielded an estimated 3% of French forests over 50 years without harvesting mostly located in more inaccessible areas (i.e. mountainous areas) and a promising proportion of future overmature forests if left unharvested. Main conclusions Our study showed that the time since the last harvesting is a good proxy for a combination of stand structure attributes key in characterising overmature temperate forests. It gives the first robust statistical estimate of the proportion of overmature forests and may serve to report on their status in metropolitan France. Our method could be implemented at a larger spatial scale, notably in countries with accessible National Forest Inventory and calibration data, to produce indicators at international level.

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.

A growing body of research suggests mixed-species stands are generally more productive than pure stands as well as less sensitive to disturbances. However, these effects of mixture depend on species assemblages and environmental conditions. Here, we present the Salem simulator, a tool that can help forest managers assess the potential benefit of shifting from pure to mixed stands from a productivity perspective. Salem predicts the dynamics of pure and mixed even-aged stands and makes it possible to simulate management operations. Its purpose is to be a decision support tool for forest managers and stakeholders as well as for policy makers. It is also designed to conduct virtual experiments and help answer research questions. In Salem, we parameterised the growth in pure stand of 12 common tree species of Europe and we assessed the effect of mixture on species growth for 24 species pairs (made up of the 12 species mentioned above). Thus, Salem makes it possible to compare the productivity of 36 different pure and mixed stands depending on environmental conditions and user-defined management strategies. Salem is essentially based on the analysis of National Forest Inventory data. A major outcome of this analysis is that we found species mixture most often increases species growth, in particular at the poorest sites. Independently from the simulator, foresters and researchers can also consider using the species-specific models that constitute Salem: the growth models including or excluding mixture effect, the bark models, the diameter distribution models, the circumference-height relationship models, as well as the volume equations for the 12 parameterised species. Salem runs on Windows, Linux, or Mac. Its user-friendly graphical user interface makes it easy to use for non-modellers. Finally, it is distributed under a LGPL license and is therefore free and open source.

Increasing atmospheric nitrogen deposition and climate change are considered the main factors accelerating the long-term growth of forests. Quantification of changes in growth rate can be extremely useful in monitoring and assessing the impact of climate change on site productivity. In this study, we carried out a country-wide analysis of long-term (100 years) dynamics and changes in the height growth rate and site index (SI) of Scots pine in Poland. To ensure representativeness we used a large sample of stem analysis trees collected on 312 plots selected using stratified sampling. To control the effect of site fertility and thus avoid the over-representation of older stands on infertile sites, we measured a range of soil properties that, together with environmental indicators characterising climatic conditions and topography, were used in growth trend modelling as explanatory variables. We found that trees planted in successive years have grown faster. The SI calculated for individual trees is linearly dependent on the year of germination and with increasing age of germination, the SI at the base age of 100 years has increased by 8.4 cm per year. Despite the differences in the growth dynamics of pines planted in different germination years, tree growth follows the same growth pattern. The observed continuous changes in site productivity correspond to an increase in the SI by over 29% between 1900 and 2000. A consequence of continuous changes in site conditions and height growth rate is ambiguity in derived SI values. Under changing site conditions, SI values calculated based on stand height and age depend not only on site productivity but also the year of germination. As a consequence, stands growing under identical site conditions show different SIs, which should be acknowledged if the SI is to be used in forest management. Therefore, determining the SI of newly established stands based on the SI of older generations requires the application of an amendment to account for stand age. Continuously improving our understanding of potential climate change impacts on forest ecosystems is essential and provide information to support forest managers seeking to develop effective adaptation measures and determine sustainable forestry production. As such, our results provide valuable support when making long-term decisions and developing effective adaptation strategies in forest management.