Model Of Forest Dynamics Research Articles

Deriving forest stand information from small sample plots: An evaluation of statistical methods

Most strategic and operational forest management decisions are taken based on stand-level information, and quantitative models of forest dynamics are key for developing sustainable management strategies. However, data on forest stands for the initialisation of such models that are representative at large spatial scales, e.g., countries or ecoregions, are often lacking. National Forest Inventories (NFIs) provide forest data from small sample plots at large spatial scales, yet deriving full stand information based on such data is challenging. Here, we evaluate seven methods of varying complexity for deriving quantitative stand descriptions based on sample data as provided by the Swiss NFI. We selected 271 extensively measured Swiss forests stands with unimodal diameter distributions, classified them as beech- vs. spruce-dominated in five development stages and randomly placed a small sized sample plot in each stand using the Swiss NFI sampling design (i.e., a circular plot of 500 m2). Seven modelling approaches were used to derive diameter distributions and species-specific stem numbers (i.e., tree species composition) from the sample data that are representative for a particular stand (local scale) and for stand types in general (generalised scale). The prediction performance of the modelling approaches was evaluated using 100 random samples per stand to calculate prediction errors. Generalised even-aged diameter distributions were best predicted by the simultaneous parameter prediction method (PPM), i.e. a combined three-step regression approach, with on average 1.3 to 2.5 times lower prediction errors compared to the simple pooling of diameter samples. However, uneven-aged diameter distributions were best predicted by pooling. At the local scale, the simultaneous PPM performed best for data from sample plots with fewer than 17 to 19 trees across all development stages. Prediction performance of the PPMs increased for structurally and spatially diverse local stands with positively skewed diameter distributions. A Random Forest approach was most suitable for predicting species composition at both the generalised and the local scale. Our study evaluates the strengths and weaknesses of methods to model stands based on data from small sample plots. We emphasise terminological pitfalls by consequently distinguishing local accuracy and generalised representativity of the stand descriptions. We demonstrate the feasibility of deriving locally accurate stands using data from small forest sample plots and evaluate the derivation of generalised stands representative at large regions. At both scales, our developments contribute to an improved initialisation of forest models and thus to a more realistic modelling of forest development under future boundary conditions.

Sensitivity of forest composition and productivity to climate change in mixed broadleaved-Korean pine forest of Northeastern China

Temperate forest is one of the largest forest biomes and is undergoing remarkable shifts in forest composition and ecosystem productivity under warming climates. However, there are considerable uncertainties when predicting future dynamics of temperate forest ecosystems partly because of the uncertainties in future climate predictions. Sensitivity analysis provides an effective mean to evaluate the uncertainties in the predicted forest responses to climate change. Here we evaluated the sensitivity of forest composition and productivity to climate change in the mixed broadleaved-Korean pine forest, a keystone temperate forest type in northeast China. In this study, we used a process-based forest dynamic model, FORMIND, to simulate and predict the response of the mixed broadleaved-Korean pine forest under climate change based on plant functional types (PFTs), and we performed model calibration using forest investigation. We then designed a factorial experiment to quantify the sensitivity to temperature and precipitation of forest composition and ecosystem productivity. Results showed that the uncertainty in future climate predictions could result in divergent responses of forest composition and ecosystem productivity to climate change over the 21st century. The response of PFTs to climate (temperature and precipitation) varied in terms of aboveground biomass. Both shade-tolerant and shade-intolerant PFTs exhibited higher sensitivity (>80% for most of the PFTs) to temperature than precipitation, yet they responded oppositely to climate warming with shade-tolerant PFTs generally increasing but shade-tolerant PFTs decreasing. Moderate shade-tolerant PFTs showed higher precipitation sensitiveness (>50%). Such differences in response and sensitivity of PFTs to climate change are related to PFTs’ competitiveness. Ecosystem productivity exhibited a higher sensitivity (≥50%) to temperature than to precipitation. There was more increase in ecosystem respiration than gross primary productivity (GPP) under warming climate, leading to a decrease in carbon sequestration and net ecosystem exchange (NEE). Our study addresses the importance of evaluating the sensitivity of a forest ecosystem model to climate change, which is relatively less studied. The insight from the study may help design effective forest management strategies to cope with future climate change.

Multi-stemming enhances tree survival and growth in Borneo’s logged forests

Multi-stemmed architecture is a common but overlooked tree growth form in tropical rainforests. Although multi-stemming is thought to be a key trait for tree persistence after disturbance, the role of multi-stemmed trees in post-disturbance demographic processes has been largely unexplored in logged rainforests. Here, we used decade-long measurements on nearly 14,000 tree stems to study post-logging growth and survival along a logging disturbance gradient in Malaysian Borneo. We found that multi-stemming enhanced tree persistence after logging. Along the entire disturbance gradient, multi-stemmed trees suffered significantly lower mortality than single-stemmed trees, and survival strongly increased with the number of stems. Small to medium-sized trees with multiple stems showed greater growth than similar-sized single-stemmed trees, with the difference increasing as the disturbance increased. Our findings demonstrate the significance of multi-stemmed architecture after logging in Borneo’s rainforests and highlight the need to consider the multi-stemmed growth form in forest inventories and models of post-disturbance forest dynamics.

MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales

Abstract. Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity, which requires moving away from broadly defined functional types. Different approaches have been adopted in the last years to incorporate a trait-based perspective into modeling exercises. A common parametrization strategy involves using trait data to represent functional variation between individuals while discarding taxonomic identity. However, this strategy ignores the phylogenetic signal of trait variation and cannot be employed when predictions for specific taxa are needed, such as in applications to inform forest management planning. An alternative strategy involves adapting the taxonomic resolution of model entities to that of the data source employed for large-scale initialization and estimating functional parameters from available plant trait databases, adopting diverse solutions for missing data and non-observable parameters. Here we report the advantages and limitations of this second strategy according to our experience in the development of MEDFATE (version 2.9.3), a novel cohort-based and trait-enabled model of forest dynamics, for its application over a region in the western Mediterranean Basin. First, 217 taxonomic entities were defined according to woody species codes of the Spanish National Forest Inventory. While forest inventory records were used to obtain some empirical parameter estimates, a large proportion of physiological, morphological, and anatomical parameters were matched to measured plant traits, with estimates extracted from multiple databases and averaged at the required taxonomic level. Estimates for non-observable key parameters were obtained using meta-modeling and calibration exercises. Missing values were addressed using imputation procedures based on trait covariation, taxonomic averages or both. The model properly simulated observed historical changes in basal area, with a performance similar to an empirical model trained for the same region. While strong efforts are still required to parameterize trait-enabled models for multiple taxa, and to incorporate intra-specific trait variability, estimation procedures such as those presented here can be progressively refined, transferred to other regions or models and iterated following data source changes by employing automated workflows. We advocate for the adoption of trait-enabled and population-structured models for regional-level projections of forest function and dynamics.

Machine Learning Forest Simulator (MLFS): R package for data-driven assessment of the future state of forests

The Machine Learning Forest Simulator (MLFS) is the first completely data-driven model of forest dynamics organised as an R package. It is a single-tree, easy to use and freely available tool that is applicable to all forest ecosystems, from even-aged monocultures to mixed forests with diverse vertical structures. This article presents the newly developed model system and gives detailed instructions on how to use it, from data preparation to description of key arguments and algorithms and to evaluation and interpretation of simulation outputs. The sample simulations are based on the most recent national forest inventory data from Slovenia and include different mortality, harvesting and climate scenarios. We show a wide range of potential applications and input settings, which result in different growing stock, yield and forest structures. The MLFS showed reasonable accuracy and can therefore become a standard tool for decision-making in forest ecosystem management.

Impacts on water quality in the peatland dominated catchment due to foreseen changes in Nordic Bioeconomy Pathways

The Nordic Bioeconomy Pathways (NBPs), conceptualized subsets of Shared Socioeconomic Pathways varying from environmentally friendly to open-market competition scenarios, can lead to plausible stressors in future for using bioresources. This study analysed the impacts of NBPs on hydrology and water quality based on two different land system management attributes: management strategy and a combination of reduced stand management and biomass removal at a catchment-scale projection. To understand the potential impacts of NBPs, the Simojoki catchment in northern Finland was chosen, as the catchment mainly covered peatland forestry. The analysis integrated a stakeholder-driven questionnaire, the Finnish Forest dynamics model, and Soil and Water Assessment Tool to build NBP scenarios, including Greenhouse gas emission pathways, for multiple management attributes to simulate flows, nutrients, and suspended solids (SS). For the catchment management strategy, an annual decrease in nutrients was observed for sustainability and business-as-usual scenarios. Reduced stand management and biomass removal also led to decreased export of nutrients and SS for the same scenarios, whereas, in other NBPs, the export of nutrients and SS increased with decreased evapotranspiration. Although the study was investigated at a local scale, based on the current political and socioeconomic situation, the approach used in this study can be outscaled to assess the use of forest and other bioresources in similar catchments.

Tree growth is correlated with hydraulic efficiency and safety across 22 tree species in a subtropical karst forest.

Karst forests are habitats in which access to soil water can be challenging for plants. Therefore, safe and efficient xylem water transport and large internal water storage may benefit tree growth. In this study, we selected 22 tree species from a primary subtropical karst forest in southern China and measured their xylem anatomical traits, saturated water content (SWC), hydraulic conductivity (Ks) and embolism resistance (P50). Additionally, we monitored growth of diameter at breast height (DBH) in 440 individual trees of various sizes over three consecutive years. Our objective was to analyze the relationships between xylem structure, hydraulic efficiency, safety, water storage and growth of karst tree species. The results showed significant differences in structure but not in hydraulic traits between deciduous and evergreen species. Larger vessel diameter, paratracheal parenchyma and higher SWC were correlated with higher Ks. Embolism resistance was not correlated with the studied anatomical traits, and no tradeoff with Ks was observed. In small trees (5-15cm DBH), diameter growth rate (DGR) was independent of hydraulic traits. In large trees (>15cm DBH), higher Ks and more negative P50 accounted for higher DGR. From lower to greater embolism resistance, the size-growth relationship shifted from growth deceleration to acceleration with increasing tree size in eight of the 22 species. Our study highlights the vital contributions of xylem hydraulic efficiency and safety to growth rate and dynamics in karst tree species; therefore, we strongly recommend their integration into trait-based forest dynamic models.

Forest Resources Projection Tools: Comparison of Available Tools and Their Adaptation to Polish Conditions

Over the years, various methods for estimating and projecting forest resources have been developed and are used by countries where the forest sector is important. Therefore, the obligation to report and account for forest resources, including changes in carbon stocks in a forest area, has gained attention. The latest regulations (Land Use, Land Use Change and Forestry—LULUCF) requires European Union (EU) members to annually report and publish national accounting plans estimating emissions and removals from managed forest areas (Regulation EU 2018/841). The major challenge is to choose and adapt a unique tool for this accounting. At the same time, they need to provide reliable estimates that are recognized by regulators and control authorities. This study focuses on comparing the adaptation of two accounting frameworks: the Operational-Scale Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) and the European Forest Dynamics Model (EFDM). Both tools are based on National Forest Inventory (NFI) data. It is assumed that the EFDM can provide similar results to the CBM-CFS3, which is already used in Poland. Implementing the EFDM and adapting it to Polish conditions could facilitate forest management decision-making and the preparation of forest policies. The main objective of this study was to compare and validate the accuracy of the results obtained with the EFDM framework. Metrics compared using both tools included growing stock volume, biomass of growing stock expressed in carbon units and age–class distribution over area. The comparison was based on the agreement of EFDM with CBM-CFS3 results. The volume of logging was taken from the EFDM and compared with the values obtained by Statistics Poland. This study also provides a guide for framework parameterization directly from the Polish National Forest Inventory data from the 2010–2015 cycle. Our main findings are that the results of the two models are reasonably comparable (the extent of deviation is acceptable). Moreover, the first implementation of the EFDM showed that it is an easy-to-use open-source program that allows forest managers to implement their own settings according to their needs. This document elucidates the concept of using both frameworks under Polish conditions and provides an impression of their performance for future modelers, students and researchers.

Some fundamental elements for studying social-ecological co-existence in forest common pool resources.

For millennia, societies have tried to find ways to sustain people's livelihoods by setting rules to equitably and sustainably access, harvest and manage common pools of resources (CPR) that are productive and rich in species. But what are the elements that explain historical successes and failures? Elinor Ostrom suggested that it depends on at least eight axiomatic principles of good governance, whereas empirical results suggest that these principles are not sufficient to describe them, especially when applied to CPRs that possess great social and ecological diversity. The aim of this article is to explore the behavior of a mathematical model of multi-species forest dynamics that respects the foundations of ecology and Ostrom's governance theory, in order to detect possible constraints inherent to the functioning of these complex systems. The model reveals that fundamental structural laws of compatibilities between species life-history traits are indeed constraining the level of co-existence (average and variance) between a diversity of co-vulnerable timber resource users (RU) and of competing tree species. These structural constraints can also lead to unexpected outcomes. For instance in wetter forest commons, opening up the access to as many diverse RUs as there are competing tree species, produces a diversity of independently-controlled disturbances on species, collectively improving the chances of coexistence between species with different life-history traits. Similar benefits are observed on forest carbon and on profits from timber harvesting. However in drier forest commons, the same benefits cannot be observed, as predicted on the basis of the constraining laws. The results show that the successes and failures of certain management strategies can be reasonably explained by simple mechanistic theories from ecology and the social-ecological sciences, which are themselves constrained by fundamental ecological invariants. If corroborated, the results could be used, in conjunction with Ostrom's CPR theory, to understand and solve various human-nature coexistence dilemmas in complex social-ecological systems.

ProForM: A simulation model for the management of mountain protection forests

Protection from gravitational natural hazards such as snow avalanches and rockfall is among the most important ecosystem services provided by forests in steep mountain terrain such as the European Alps. These so-called “protection forests” often have to be actively managed to ensure a sustainable ecosystem service provision in time and space. For studying these slowly developing ecosystems, dynamic forest models are important tools to assess the effect of management on the protective function. However, existing models focus on the current protective effect and in many cases neglect aspects of stand resistance and resilience to large disturbances, which are important factors for maintaining the long-term protective function. Therefore, we developed ProForM, a new dynamic forest model aimed at (1) reproducing stand dynamics of managed temperate mountain forests and (2) assessing their protective function in detail. ProForM is a structurally simple model that contains mechanistic formulations of basic demographic processes but was developed mainly with empirical data. It is spatially explicit and was developed with a focus on regeneration dynamics. The model is parameterized for four tree species (Picea abies, Abies alba, Fagus sylvatica, and Acer pseudoplatanus) and four elevational zones, ranging from mixed species submontane to spruce-dominated subalpine forests. ProForM was calibrated with and validated against independent data from long-term forest inventories from Switzerland. It exhibited a satisfactory performance in reproducing measured basal area, stem number, diameter distribution and mean crown ratio at the stand level, comparable to the performance of other, typically more complex models. Illustrative example simulations demonstrate the assessment of the protective function of a stand against gravitational hazards according to multiple criteria used in forestry practice in Alpine countries. ProForM is a valuable new tool to study the impacts of management on the protective effect of mountain forests, and to inform forest managers.

Modelling the influence of thinning intensity and frequency on the future provision of ecosystem services in Mediterranean mountain pine forests

Thinnings are silvicultural operations that repetitively reduce tree density to improve the vigour of the remaining trees and the economic benefits of the stands. Thinning can also enhance the provision of various ecosystem services throughout the rotation period. In this study, we use a modelling approach to evaluate stand dynamics and the provision of ecosystem services (mushroom production, wood for timber, carbon storage, blue water, and habitat for biodiversity) in Mediterranean mountain pine forests. We simulated thirteen thinning regimes—defined by intensity and frequency—under two different climate change scenarios. We implemented the thinning regimes using SORTIE-ND, an individual-based model of forest dynamics, and then we used models developed for the study area to calculate the provision of services. We used as a case study Pinus sylvestris and Pinus nigra stands, and we evaluated the effect of the thinning regime, climate change, and forest type over 100 years. Our simulations suggest that the production of timber and carbon decreased with increasing intensity and shortening frequency of thinnings, while the provision of mushrooms and blue water generally increased under those conditions. Large timber was better supported by a thinning regime with heavy intensity and shorter frequencies, which also favoured the rapid presence of large dead trees (dbh > 30 cm) in the stand. We found synergies between the production of timber and carbon, while the provision of mushrooms and particularly blue water were in a trade-off relationship with these services. Our simulations show that climate change will lower the production of ecosystem services under the most severe climate predictions and alter the effect of different regimes on the provision of services. We conclude that our modelling approach is a useful and efficient tool for answering questions that would otherwise require long-term studies, and that it can provide useful information to guide management efforts to adapt forest management to the challenges of climate change.

FORCCHN V2.0: an individual-based model for predicting multiscale forest carbon dynamics

Abstract. Process-based ecological models are essential tools to quantify and predict forest growth and carbon cycles under the background of climate change. The accurate description of phenology and tree growth processes enables an improved understanding and predictive modeling of forest dynamics. An individual tree-based carbon model, FORCCHN2 (Forest Ecosystem Carbon Budget Model for China version 2.0), used non-structural carbohydrate (NSC) pools to couple tree growth and phenology. This model performed well in reducing uncertainty when predicting forest carbon fluxes. Here, we describe the framework in detail and provide the source code of FORCCHN2. We also present a dynamic-link library (DLL) package containing the latest version of FORCCHN2. This package has the advantage of using Fortran as an interface to make the model run fast on a daily step, and the package also allows users to call it with their preferred computer tools (e.g., MATLAB, R, Python). FORCCHN2 can be used directly to predict spring and autumn phenological dates, daily carbon fluxes (including photosynthesis, aboveground and belowground autotrophic respiration, and soil heterotrophic respiration), and biomass on plot, regional, and hemispheric scales. As case studies, we provide an example of FORCCHN2 running model validations in 78 forest sites and an example model application for the carbon dynamics of Northern Hemisphere forests. We demonstrate that FORCCHN2 can produce a reasonable agreement with flux observations. Given the potential importance of the application of this ecological model in many studies, there is substantial scope for using FORCCHN2 in fields as diverse as forest ecology, climate change, and carbon estimations.

The evolution, complexity and diversity of models of long-term forest dynamics.

To assess the impacts of climate change on vegetation from stand to global scales, models of forest dynamics that include tree demography are needed. Such models are now available for 50 years, but the currently existing diversity of model formulations and its evolution over time are poorly documented. This hampers systematic assessments of structural uncertainties in model-based studies.We conducted a meta-analysis of 28 models, focusing on models that were used in the past five years for climate change studies. We defined 52 model attributes in five groups (basic assumptions, growth, regeneration, mortality and soil moisture) and characterized each model according to these attributes. Analyses of model complexity and diversity included hierarchical cluster analysis and redundancy analysis.Model complexity evolved considerably over the past 50 years. Increases in complexity were largest for growth processes, while complexity of modelled establishment processes increased only moderately. Model diversity was lowest at the global scale, and highest at the landscape scale. We identified five distinct clusters of models, ranging from very simple models to models where specific attribute groups are rendered in a complex manner and models that feature high complexity across all attributes.Most models in use today are not balanced in the level of complexity with which they represent different processes. This is the result of different model purposes, but also reflects legacies in model code, modelers' preferences, and the 'prevailing spirit of the epoch'. The lack of firm theories, laws and 'first principles' in ecology provides high degrees of freedom in model development, but also results in high responsibilities for model developers and the need for rigorous model evaluation. Synthesis. The currently available model diversity is beneficial: convergence in simulations of structurally different models indicates robust projections, while convergence of similar models may convey a false sense of certainty. The existing model diversity-with the exception of global models-can be exploited for improved projections based on multiple models. We strongly recommend balanced further developments of forest models that should particularly focus on establishment and mortality processes, in order to provide robust information for decisions in ecosystem management and policymaking.

Trajectories of wildfire behavior under climate change. Can forest management mitigate the increasing hazard?

Mediterranean forests and fire regimes are closely intertwined. Global change is likely to alter both forest dynamics and wildfire activity, ultimately threatening the provision of ecosystem services and posing greater risks to society. In this paper we evaluate future wildfire behavior by coupling climate projections with simulation models of forest dynamics and wildfire hazard. To do so, we explore different forest management scenarios reflecting different narratives related to EU forestry (promotion of carbon stocks, reduction of water vulnerability, biomass production and business-as-usual) under the RCP 4.5 and RCP 8.5 climate pathways in the period 2020–2100. We used as a study model pure submediterranean Pinus nigra forests of central Catalonia (NE Spain). Forest dynamics were simulated from the 3rd National Forest Inventory (143 stands) using SORTIE-nd software based on climate projections under RCPs 4.5 and 8.5. The climate products were also used to estimate fuel moisture conditions (both live and dead) and wind speed. Fuel parameters and fire behavior were then simulated, selecting crown fire initiation potential and rate of spread as key indicators. The results revealed consistent trade-offs between forest dynamics, climate and wildfire. Despite the clear influence exerted by climate, forest management modulates fire behavior, resulting in different trends depending on the climatic pathway. In general, the maintenance of current practices would result in the highest rates of crown fire activity, while management for water vulnerability reduction is postulated as the best alternative to surmount the increasingly hazardous conditions envisaged in RCP 8.5.

The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0

Abstract. Hurricanes commonly disturb and damage tropical forests. Hurricane frequency and intensity are predicted to change under the changing climate. The short-term impacts of hurricane disturbances to tropical forests have been widely studied, but the long-term impacts are rarely investigated. Modeling is critical to investigate the potential response of forests to future disturbances, particularly if the nature of the disturbances is changing with climate. Unfortunately, existing models of forest dynamics are not presently able to account for hurricane disturbances. Therefore, we implement the Hurricane Disturbance in the Ecosystem Demography model (ED2) (ED2-HuDi). The hurricane disturbance includes hurricane-induced immediate mortality and subsequent recovery modules. The parameterizations are based on observations at the Bisley Experimental Watersheds (BEW) in the Luquillo Experimental Forest in Puerto Rico. We add one new plant functional type (PFT) to the model – Palm, as palms cannot be categorized into one of the current existing PFTs and are known to be an abundant component of tropical forests worldwide. The model is calibrated with observations at BEW using the generalized likelihood uncertainty estimation (GLUE) approach. The optimal simulation obtained from GLUE has a mean relative error of −21 %, −12 %, and −15 % for stem density, basal area, and aboveground biomass, respectively. The optimal simulation also agrees well with the observation in terms of PFT composition (+1 %, −8 %, −2 %, and +9 % differences in the percentages of “Early”, “Mid”, “Late”, and “Palm” PFTs, respectively) and size structure of the forest (+0.8 % differences in the percentage of large stems). Lastly, using the optimal parameter set, we study the impact of forest initial condition on the recovery of the forest from a single hurricane disturbance. The results indicate that, compared to a no-hurricane scenario, a single hurricane disturbance has little impact on forest structure (+1 % change in the percentage of large stems) and composition (<1 % change in the percentage of each of the four PFTs) but leads to 5 % higher aboveground biomass after 80 years of succession. The assumption of a less severe hurricane disturbance leads to a 4 % increase in aboveground biomass.

Wind Speed Controls Forest Structure in a Subtropical Forest Exposed to Cyclones: A Case Study Using an Individual-Based Model

Extreme wind blowdown events can significantly modify the structure and composition of forests, and the predicted shift in tropical cyclone regimes due to climate change could strongly impact forests across the tropics. In this study, we coupled an individual-based and spatially-explicit forest dynamics model (TROLL) with a mechanistic model estimating wind damage as a function of tree size, traits, and allometry (ForestGALES). We assimilated floristic trait data and climate data from a subtropical forest site in Taiwan to explore the effect of wind regimes on forest properties. We found that the average canopy height and biomass stocks decreased as wind disturbance strength increased, but biomass stocks showed a nonlinear response. Above a wind intensity threshold, both canopy height and biomass drastically decreased to near-zero, exhibiting a transition to a non-forest state. Wind intensity strongly regulated wind impact, but varying wind frequency did not cause discernible effects. The implementation of within-stand topographic heterogeneity led to weak effects on within-stand forest structure heterogeneity at the study site. In conclusion, the intensity of wind disturbances can potentially greatly impact forest structure by modifying mortality. Individual-based modeling provides a framework in which to investigate the impact of wind regimes on mortality, other factors influencing wind-induced tree mortality, as well as interaction between wind and other forms of forest disturbance and human land use legacy.

Importance of the forest state in estimating biomass losses from tropical forests: combining dynamic forest models and remote sensing

Abstract. Disturbances, such as extreme weather events, fires, floods, and biotic agents, can have strong impacts on the dynamics and structures of tropical forests. In the future, the intensity of disturbances will likely further increase, which may have more serious consequences for tropical forests than those we have already observed. Thus, quantifying aboveground biomass loss of forest stands due to stem mortality (hereafter biomass loss rate) is important for the estimation of the role of tropical forests in the global carbon cycle. So far, the long-term impacts of altered stem mortality on rates of biomass loss have not been adequately described. This study aims to analyse the consequences of long-term elevated stem mortality rates on forest dynamics and biomass loss rate. We applied an individual-based forest model and investigated the impacts of permanently increased stem mortality rates on the growth dynamics of humid, terra firme forests in French Guiana. Here, we focused on biomass, leaf area index (LAI), forest height, productivity, forest age, quadratic mean stem diameter, and biomass loss rate. Based on the simulation data, we developed a multiple linear regression model to estimate biomass loss rates of forests in different successional states from the various forest attributes. The findings of our simulation study indicated that increased stem mortality altered the succession patterns of forests in favour of fast-growing species, which increased the old-growth forests' gross primary production, though net primary production remained stable. The stem mortality rate had a strong influence on the functional species composition and tree size distribution, which led to lower values in LAI, biomass, and forest height at the ecosystem level. We observed a strong influence of a change in stem mortality on biomass loss rate. Assuming a doubling of stem mortality rate, the biomass loss rate increased from 3.2 % yr−1 to 4.5 % yr−1 at equilibrium. We also obtained a multidimensional relationship that allowed for the estimation of biomass loss rates from forest height and LAI. Via an example, we applied this relationship to remote sensing data on LAI and forest height to map biomass loss rates for French Guiana. We estimated a countrywide mean biomass loss rate of 3.0 % yr−1. The approach described here provides a novel methodology for quantifying biomass loss rates, taking the successional state of tropical forests into account. Quantifying biomass loss rates may help to reduce uncertainties in the analysis of the global carbon cycle.

Assessment of the effect of stand density on the height growth of Scots pine using repeated ALS data

• Repeated ALS allows detecting the height increment variation influenced by stand density. • Higher stand density stimulate height growth, particularly on most productive sites. • Repeated ALS data allows developing density-dependent top height growth models. The spread of remote sensing technologies allows for continuous and precise mapping of forest ecosystem attributes over large areas. One of the most important attributes of a forest ecosystem is site productivity, an essential determinant of resource availability. Knowledge of site productivity is crucial for sustainable forest management because it is the basis for predictions of future forest growth and is fundamental to long-term planning in forestry. Models of forest dynamics allow us to better understand the functioning of forest ecosystems and to assess the provision of ecosystem services. However, discussions on the factors affecting forest growth are ongoing. Previous research has not clarified the influence of stand density on the height increment of trees. Consequently, this uncertainty leads to inconsistent predictions for stand growth and nonoptimal forest-management decisions. We aimed to analyse the effect of stand density on top height (TH) growth and the development of the TH growth model for Scots pine based on bitemporal ALS measurements. We applied repeated ALS observations from two acquisitions (2011, 2019) to fit a density-sensitive TH growth model. We found that stand density affected the TH growth of Scots pine. A higher stand density stimulated TH growth, particularly in productive sites showing a TH increment of about 10%. We demonstrated the usefulness of bitemporal ALS measurements for developing a TH growth model for Scots pine considering stand density. We found that the predictive accuracy of the TH increment increased when stand density was considered.

Forest Dynamics Models for Conservation, Restoration, and Management of Small Forests

Globally, there are myriad situations in which people aim to conserve, restore, or manage forest ecosystems at small spatial scales of 50 ha or less. To inform management, forest dynamics models provide an increasingly diverse and valuable portfolio of tools for projecting forest change under different management and environmental conditions. Yet, many models may not be appropriate or feasible to use in small forest management because of their design for larger-scale applications, the information needed to initialize models, or discrepancies between model outputs and information relevant for small forest management objectives. This review explores the suitability of 54 existing forest dynamics models to inform the management of small forests. We evaluated the characteristics of each model using five criteria with implications for small forest management: spatial resolution, number of species the model can simulate, inclusion of spatial structure, modeling approach, and mechanistic detail. While numerous models can be suitable under certain conditions, the review criteria led us to conclude that two models offered the broadest versatility and usability for small forest contexts, SORTIE and FORMIND. This review can help orient and guide small forest managers who wish to add modeling to their forest management efforts.

Large fires or small fires, will they differ in affecting shifts in species composition and distributions under climate change?

Climate change is expected to increase fire activity, which has the potential to accelerate climate-induced shifts in species composition and distribution in the boreal-temperate ecotone. Wildfire can kill resident trees, and thus provide establishment opportunities for migrating tree species. However, the role of fire size and its interactions with tree species with varied life-history attributes in driving climate-induced shifts is not understood. Future fire regimes could be characterized by many small fires or a few large fires. Large and small fires create and regulate distinct burn patterns, which may influence tree-species responses and post-fire successional trajectories. Here we investigated the effects of future fire-regime variability on the boreal-temperate ecotone of northeastern China under climate change using a coupled forest dynamic model (LANDIS PRO) and ecosystem process model (LINKAGES). We simulated fire regimes using the LANDIS PRO fire module. We designed two fire scenarios (frequent, small fires and infrequent, large fires) to represent different fire regimes in terms of fire size. Results showed fire-catalyzed, climate-induced transitions from boreal to pioneer and temperate forest communities. Frequent, small fires resulted in 13% and 23% higher increases in pioneer and temperate species respectively, relative to infrequent, large fires. Therefore, species composition shifts were faster following frequent, small fires than infrequent, large fires. The results can help policymakers and forest managers determine tradeoffs among strategies to mitigate or adapt to climate change under altered fire regimes.