Determinants of carbon sequestration in thinned forests.

Given global climate change and the projected increases in the greenhouse effect, enhancing the carbon storage capacity of forest ecosystems is especially critical. To fully realize the potential carbon sequestration, it is imperative to understand the drivers affecting carbon storage in forest ecosystems, particularly with disturbances that disrupt existing balance. In this study, we explored the effects of stem-only harvest at various thinning intensities on forest structure and carbon density in middle-aged natural secondary forests, located in the northern temperate zone. Carbon density included aboveground carbon density (ACD), soil organic carbon stocks (SOCD), and total carbon density (TCD), which was the sum of ACD and SOCD. We employed the random forest analysis method to identify significant variables influencing changes in carbon density. Structural equation modelling (SEM) was then used to determine the drivers of changes in forest carbon density. The results showed that moderate thinning (20 %-35 % trees removed), is an effective management practice for increasing the TCD in forests. Although heavy thinning (35.1 %-59.9 % trees removed) accelerated individual growth, it did not fully offset the carbon removed due to thinning. It is noteworthy that light thinning (0-19.9 % trees removed) not only reduced the species richness but also caused a significant number of tree deaths. Large live trees were an important direct determining factor of ACD, but not the only one. In addition, thinning indirectly influenced ACD by reducing canopy density and deformed tree density. The increase in dead tree density had an adverse impact on SOCD, and this phenomenon increased with the passage of recovery time. Conversely, greater thinning intensity enhanced SOCD. Moreover, TCD was directly influenced by tree height, large live trees, and stand density. Furthermore, thinning altered the conifer ratio, thereby influencing tree growth and indirectly controlling the TCD. We believe that this knowledge will be highly beneficial for successful forest management and enhancing the carbon sequestration capacity of forest ecosystems.

Determinants of tree population temporal stability in a temperate mixed forest over a gradient of nitrogen addition.

Nitrogen (N) deposition is a significant threat to the functioning of forests and negatively impacts the delivery of forest goods and services. Contemporary management approaches seek to adapt forests to such N-deposition stressors, but to date how plant populations in natural forests respond to N deposition and what factors determine the contrasting responses among populations are still unclear. Here, we investigated the impact of N-addition (control: 0 kg ha-1 yr-1; low: 25 kg ha-1 yr-1; medium: 50 kg ha-1 yr-1; high: 75 kg ha-1 ha yr-1) on tree population temporal stability and how initial tree size, mycorrhizal type, and leaf N content (LNC; as a surrogate for functional trait composition) mediate tree population responses to N-addition in a Korean pine and mixed broadleaved dominated temperate forest in northern China. We quantified tree species population temporal stability as the ratio of mean to standard deviation of the year-by-year stem increments recorded in individual trees from 2015 to 2022 experimental period. The results showed different temporal stabilities of tree species among four N-addition levels, with the highest population stability observed within the high N-addition plots. Furthermore, initial tree size had significantly (p < 0.001) positive effects on population temporal stability. The effect of LNC and initial tree size were also contingent on the level of N applied. Specifically, increase in tree population LNC reduced population temporal stability in all plots where N was added. Our results imply that retention of large-sized trees and species with resource-conservative strategies (e.g., low LNC) could enhance forest stability under N deposition.

An Entropy-Balanced Orthogonal Learning Bamboo Forest Growth Optimization Algorithm with Quasi-Affine Transformation Evolutionary and Its Application in Capacitated Vehicle Routing Problem.

The bamboo forest growth optimization (BFGO) algorithm combines the characteristics of the bamboo forest growth process with the optimization course of the algorithm. The algorithm performs well in dealing with optimization problems, but its exploitation ability is not outstanding. Therefore, a new heuristic algorithm named orthogonal learning quasi-affine transformation evolutionary bamboo forest growth optimization (OQBFGO) algorithm is proposed in this work. This algorithm combines the quasi-affine transformation evolution algorithm to expand the particle distribution range, a process of entropy increase that can significantly improve particle searchability. The algorithm also uses an orthogonal learning strategy to accurately aggregate particles from a chaotic state, which can be an entropy reduction process that can more accurately perform global development. OQBFGO algorithm, BFGO algorithm, quasi-affine transformation evolutionary bamboo growth optimization (QBFGO) algorithm, orthogonal learning bamboo growth optimization (OBFGO) algorithm, and three other mature algorithms are tested on the CEC2017 benchmark function. The experimental results show that the OQBFGO algorithm is superior to the above algorithms. Then, OQBFGO is used to solve the capacitated vehicle routing problem. The results show that OQBFGO can obtain better results than other algorithms.

Role of data uncertainty when identifying important areas for biodiversity and carbon in boreal forests.

Forest conservation plays a central role in meeting national and international biodiversity and climate targets. Biodiversity and carbon values within forests are often estimated with models, introducing uncertainty to decision making on which forest stands to protect. Here, we explore how uncertainties in forest variable estimates affect modelled biodiversity and carbon patterns, and how this in turn introduces variability in the selection of new protected areas. We find that both biodiversity and carbon patterns were sensitive to alterations in forest attributes. Uncertainty in features that were rare and/or had dissimilar distributions with other features introduced most variation to conservation plans. The most critical data uncertainty also depended on what fraction of the landscape was being protected. Forests of highest conservation value were more robust to data uncertainties than forests of lesser conservation value. Identifying critical sources of model uncertainty helps to effectively reduce errors in conservation decisions.

Determinants of growth and carbon accumulation of common plantation tree species in the three northern regions, China: Responses to climate and management strategies.

The Three-North (Northwest, North and Northeast) Shelter Forests Program (TNSFP) in China has effectively promoted vegetation growth and carbon sink in the temperate semi-humid and semi-arid regions. To compare the afforestation benefits of commonly used tree species in the area and explore the effect of environment on growth and carbon accumulation in plantations, backpack LiDAR was used to acquire 3 dimensional lidar point clouds of forests from a total of 480 pure plantation patches consisting of Pinus sylvestris (P.s.), Pinus tabuliformis (P.t.), Populus spp. (Pop.), and Robinia pseudoacacia (R.p.). Then, diameter at breast height (DBH), forest height, canopy coverage, and aboveground carbon accumulation were calculated for each plantation patches, which ranged from 7.0 to 37.3 cm, 1.5-14.5 m, 10-99 % and 4.2-205.9 Mg/ha, respectively. Generalized linear mixed-effect models and ANOVA were applied to account for the environmental constraints on the variations of forest parameters. Results showed that precipitation had a stronger effect on all the above parameters of plantations than temperature, and P.t. was more sensitive to climate than other three species. With regard to forest management in Pop. plantations, thinning could improve afforestation efficiency because carbon accumulation would reduce after the age exceeds 30 years. In contrast, P.s. populations maintained a continuous increase in carbon accumulation at least before 40 years old, while the radial growth of canopy became saturated after 12 years of age. The optimal planting density for P.s. and Pop. are about 1000 trees/ha, beyond which the increase in carbon accumulation will slow down or change rate of canopy coverage will be insignificant. Within the TNSFP area, P.t. and R.p. plantations would be more suitable in southern regions, while P.s. and Pop. plantations grow better in the northeastern regions. Meanwhile, mountains along the "Hu Line" showed high potential for growth and carbon accumulation for all tree species examined.

Collective property rights lead to secondary forest growth in the Brazilian Amazon.

Forests serve a crucial role in our fight against climate change. Secondary forests provide important potential for conservation of biodiversity and climate change mitigation. In this paper, we explore whether collective property rights in the form of indigenous territories (ITs) lead to higher rates of secondary forest growth in previously deforested areas. We exploit the timing of granting of property rights, the geographic boundaries of ITs and two different methods, regression discontinuity design and difference-in-difference, to recover causal estimates. We find strong evidence that indigenous territories with secure tenure not only reduce deforestation inside their lands but also lead to higher secondary forest growth on previously deforested areas. After receiving full property rights, land inside ITs displayed higher secondary forest growth than land outside ITs, with an estimated effect of 5% using our main RDD specification, and 2.21% using our difference-in-difference research design. Furthermore, we estimate that the average age of secondary forests was 2.2 y older inside ITs with secure tenure using our main RDD specification, and 2.8 y older when using our difference-in-difference research design. Together, these findings provide evidence for the role that collective property rights can play in the push to restore forest ecosystems.

How biotic, abiotic, and functional variables drive belowground soil carbon stocks along stress gradient in the Sundarbans Mangrove Forest?

Mangrove forests, some of the most carbon-dense ecosystems on Earth, play an important role in climate change mitigation through storing carbon in the soil. However, increasing anthropogenic pressures and sea level rise are likely to alter mangrove forest structure and functions, including the major source of carbon in mangrove ecosystems - below-ground soil carbon stocks (BSCS). Although estimating soil carbon stocks has been a popular practice in the mangroves, but poorly understood the (I) the linkage between BSCS and key ecosystem drivers (i.e., biotic, abiotic, and functional) and in (II) determining the pathways of how BSCS and multiple forest variables interact along stress gradients. This lack of understanding limits our ability to predict ecosystem carbon dynamics under future changes in climate. Here, we aimed to understand how abiotic factors (such as salinity, canopy gap fraction, nutrients, and soil pH), biotic factors (e.g., structural parameters, canopy packing, and leaf area index, LAI), and forest functional variables (e.g., growth and aboveground biomass stocks, AGB) affect BSCS (i.e., soil organic carbon, SOC, and root carbon, RC) using spatiotemporal data collected from the Sundarbans Mangrove Forest (SMF) in Bangladesh. We observed that BSCS decreased significantly with increasing salinity (e.g., from 70.6 Mg C ha-1 in the low-saline zone to 44.6 Mg C ha-1 in the high-saline zone). In contrast, the availability of several macronutrients (such as nitrogen, phosphorous, and potassium), LAI, species diversity, AGB, and growth showed a significant positive effect on SOC and RC. Stand properties, including tree height, basal area, density, canopy packing, and structural diversity, had a non-significant but positive impact on RC, while tree height and basal area significantly influenced SOC. Pathway analysis showed that salinity affects BSCS variability directly and indirectly by regulating stand structure and restricting nutrients and forest functions, although basal area, nutrients, and LAI directly enhance RC stocks. Our results indicate that an increase in nutrient content, canopy density, species diversity, and leaf area index can enhance BSCS, as they improve forest functions and contribute to a better understanding of the underlying mechanisms.

Binary Bamboo Forest Growth Optimization Algorithm for Feature Selection Problem.

Inspired by the bamboo growth process, Chu et al. proposed the Bamboo Forest Growth Optimization (BFGO) algorithm. It incorporates bamboo whip extension and bamboo shoot growth into the optimization process. It can be applied very well to classical engineering problems. However, binary values can only take 0 or 1, and for some binary optimization problems, the standard BFGO is not applicable. This paper firstly proposes a binary version of BFGO, called BBFGO. By analyzing the search space of BFGO under binary conditions, the new curve V-shaped and Taper-shaped transfer function for converting continuous values into binary BFGO is proposed for the first time. A long-mutation strategy with a new mutation approach is presented to solve the algorithmic stagnation problem. Binary BFGO and the long-mutation strategy with a new mutation are tested on 23 benchmark test functions. The experimental results show that binary BFGO achieves better results in solving the optimal values and convergence speed, and the variation strategy can significantly enhance the algorithm's performance. In terms of application, 12 data sets derived from the UCI machine learning repository are selected for feature-selection implementation and compared with the transfer functions used by BGWO-a, BPSO-TVMS and BQUATRE, which demonstrates binary BFGO algorithm's potential to explore the attribute space and choose the most significant features for classification issues.

Future supply of boreal forest ecosystem services is driven by management rather than by climate change.

Forests provide a wide variety of ecosystem services (ES) to society. The boreal biome is experiencing the highest rates of warming on the planet and increasing demand for forest products. To foresee how to maximize the adaptation of boreal forests to future warmer conditions and growing demands of forest products, we need a better understanding of the relative importance of forest management and climate change on the supply of ecosystem services. Here, using Finland as a boreal forest case study, we assessed the potential supply of a wide range of ES (timber, bilberry, cowberry, mushrooms, carbon storage, scenic beauty, species habitat availability and deadwood) given seven management regimes and four climate change scenarios. We used the forest simulator SIMO to project forest dynamics for 100 years into the future (2016-2116) and estimate the potential supply of each service using published models. Then, we tested the relative importance of management and climate change as drivers of the future supply of these services using generalized linear mixed models. Our results show that the effects of management on the future supply of these ES were, on average, 11 times higher than the effects of climate change across all services, but greatly differed among them (from 0.53 to 24 times higher for timber and cowberry, respectively). Notably, the importance of these drivers substantially differed among biogeographical zones within the boreal biome. The effects of climate change were 1.6 times higher in northern Finland than in southern Finland, whereas the effects of management were the opposite-they were three times higher in the south compared to the north. We conclude that new guidelines for adapting forests to global change should account for regional differences and the variation in the effects of climate change and management on different forest ES.

Energy-Efficient Clustering Mechanism of Routing Protocol for Heterogeneous Wireless Sensor Network Based on Bamboo Forest Growth Optimizer.

In wireless sensor networks (WSN), most sensor nodes are powered by batteries with limited power, meaning the quality of the network may deteriorate at any time. Therefore, to reduce the energy consumption of sensor nodes and extend the lifetime of the network, this study proposes a novel energy-efficient clustering mechanism of a routing protocol. First, a novel metaheuristic algorithm is proposed, based on differential equations of bamboo growth and the Gaussian mixture model, called the bamboo growth optimizer (BFGO). Second, based on the BFGO algorithm, a clustering mechanism of a routing protocol (BFGO-C) is proposed, in which the encoding method and fitness function are redesigned. It can maximize the energy efficiency and minimize the transmission distance. In addition, heterogeneous nodes are added to the WSN to distinguish tasks among nodes and extend the lifetime of the network. Finally, this paper compares the proposed BFGO-C with three classic clustering protocols. The results show that the protocol based on the BFGO-C can be successfully applied to the clustering routing protocol and can effectively reduce energy consumption and enhance network performance.

Application of integrated Korean forest growth dynamics model to meet NDC target by considering forest management scenarios and budget.

BACKGROUND: Forests are atmospheric carbon sinks, whose natural growth can contribute to climate change mitigation. However, they are also affected by climate change and various other phenomena, for example, the low growth of coniferous forests currently reported globally, including in the Republic of Korea. In response to the implementation of the Paris Agreement, the Korean government has proposed 2030 greenhouse gas roadmap to achieve a Nationally Determined Contribution (NDC), and the forest sector set a sequestration target of 26 million tons by 2030. In this study, the Korean forest growth model (KO-G-Dynamic model) was used to analyze various climate change and forest management scenarios and their capacity to address the NDC targets. A 2050 climate change adaptation strategy is suggested based on forest growth and CO2 sequestration. RESULTS: Forest growth was predicted to gradually decline, and CO2 sequestration was predicted to reach 23 million tons per year in 2050 if current climate and conditions are maintained. According to the model, sequestrations of 33 million tCO2 year-1 in 2030 and 27 million tCO2 year-1 in 2050 can be achieved if ideal forest management is implemented. It was also estimated that the current forest management budget of 317 billion KRW (264 million USD) should be twice as large at 722 billion KRW (602 million USD) in the 2030s and 618 billion KRW (516 million USD) in the 2050s to achieve NDC targets. CONCLUSIONS: The growth trend in Korea's forests transitions from young-matured stands to over-mature forests. The presented model-based forest management plans are an appropriate response and can increase the capacity of Korea to achieve its NDC targets. Such a modeling can help the forestry sector develop plans and policies for climate change adaptation.

Predicting crown width using nonlinear mixed-effects models accounting for competition in multi-species secondary forests.

Crown width (CW) is an important tree variable and is often used as a covariate predictor in forest growth models. The precise measurement and prediction of CW is therefore critical for forest management. In this study, we introduced tree species as a random effect to develop nonlinear mixed-effects CW models for individual trees in multi-species secondary forests, accounting for the effects of competition. We identified a simple power function for the basic CW model. In addition to diameter at breast height (DBH), other significant predictor variables including height to crown base (HCB), tree height (TH), and competition indices (CI) were selected for the mixed-effects CW model. The sum of relative DBH (SRD) was identified the optimal distance-independent CI and as a covariate predictor for spatially non-explicit CW models, whereas the sum of the Hegyi index for fixed number competitors (SHGN) was the optimal distance-dependent CI for spatially explicit CW models, with significant linear correlation (R 2 = 0.943, P < 0.001). Both spatially non-explicit and spatially explicit mixed-effects CW models were developed for studied secondary forests. We found that these models can describe more than 50% of the variation in CW without significant residual trends. Spatially explicit models exhibited a significantly larger effect on CW than spatially non-explicit ones; however, spatially explicit models are computationally complex and difficult and can be replaced by corresponding spatially non-explicit models due to the small differences in the fit statistics. The models we present may be useful for forestry inventory practices and have the potential to aid the evaluation and management of secondary forests in the region.

Diffuse sunlight and cosmic rays: Missing pieces of the forest growth change attribution puzzle?

Forest growth changes have been a matter of intense research efforts since the 1980s. Owing to the variety of their environmental causes - mainly atmospheric CO2 increase, atmospheric N deposition, changes in temperature and water availability, and their interactions - their interpretation has remained challenging. Recent isolated researches suggest further effects of neglected environmental factors, namely changes in the diffuse fraction of light, more efficient to photosynthesis, and galactic cosmic rays (GCR), both emphasized in this Discussion paper. With growing awareness of GCR influence on global cloudiness (the cosmoclimatologic theory by H. Svensmark), GCR may thus cause trends in diffuse-light, and distinguishing between their direct/indirect influences on forest growth remains uncertain. This link between cosmic rays and diffuse sunlight also forms an alternative explanation to the geological evidence of a negative correlation between GCR and atmospheric CO2 concentration over the past 500 Myr. After a careful scrutiny of this literature and of key contributions in the field, we draw research options to progress further in this attribution. These include i) observational strategies intending to build on differences in the spatio-temporal dynamics of environmental growth factors, ranging from quasi-experiments to meta-analyses, ii) simulation strategies intending to quantify environmental factor's effects based on process-based ecosystem modelling, in a context where progresses for accounting for diffuse-light fraction are ongoing. Also, the hunt for tree-ring based proxies of GCR may offer the perspective of testing the GCR hypothesis on fully coupled forest growth samples.

The Impact of Globalization on Forest Growth: Evidence from Multinational Panel Data.

Even though some existing literature has studied the impact of globalization on forest growth, this research remains inconclusive; moreover, little clarification has emerged as to whether the influence of globalization on forest growth is consistent among different countries. To fill this research gap, we investigated the impact of globalization on forest growth and considered what factors could change the influence of the former upon the latter. To empirically investigate these essential issues, we utilized cross-country data covering 108 countries during the period 1991-2018 to conduct a system generalized method of moment (GMM) estimation. The baseline results confirm the positive impact of globalization on forest growth, which is also supported by several robustness tests, such as changing the measurements and setting new samples. Furthermore, an increase in globalization would bring about higher forest growth. Aside from this, two specific dimensions of globalization, namely economics and trade, can also protect forest growth. Additionally, a higher FDI strengthens the positive impact of globalization on forest growth, while aging, industrial share, and CO2 emissions weaken it. Finally, the impact of globalization on forests is weaker in democracies, emerging markets, and countries with higher fiscal freedoms, while it is stronger in countries with higher political stability. Our study provides substantial policy implications for governments participating in international treaties related to forest growth. The structure of this paper is organized as follows.

Nighttime warming alleviates the incidence of juniper forest growth decline on the Tibetan Plateau.

Recent warming over the Tibetan Plateau (TP) is approximately twice the global-mean surface temperature increase and poses a threat to the healthy growth of forests. Although many studies have focused on whether recent climate warming has caused forest growth decline on the TP, it remains unclear how asymmetric warming, that is faster increasing nighttime temperature than daytime, impacts forest growth decline. We explored this question by using a ring-width index series from 1489 juniper trees (Juniperus prezwalskii and J. tibetica) at 50 sites on the TP. We calculated the percentage of trees with growth decline (PTD) to reconstruct historical forest growth decline and employed a piecewise structural equation meta-model (pSEM) and linear mixed model (LMM) to explore influencing factors. We found that the PTD has decreased since the late 19th century, with an abrupt decreasing trend since the 1980s. Results of the pSEM show that winter minimum temperature has a stronger indirect negative effect on the variation in PTD (ß = -0.24, p < 0.05) compared to that of the weak indirect positive effect of summer maximum temperature (ß = 0.16, p < 0.05). The results of LMM show that the variation in PTD is directly negatively (p < 0.001) affected by both winter minimum temperature and summer total precipitation, but the former has a greater independent contribution than the latter (with 17.7% vs 2.5% of variances independently explained, respectively). These results suggest that increased winter minimum temperature substantially mitigates the growth decline in juniper forests on the TP. As the minimum temperature generally occurs at night, we conclude that the asymmetric increase in nighttime temperature has decreased the incidence of juniper forest growth decline on the TP under climate warming. This alleviating effect of nighttime warming is likely due to reduced low-temperature constraints and reduced damage to tree growth.

Forest density intensifies the importance of snowpack to growth in water-limited pine forests.

Warming climate and resulting declines in seasonal snowpack have been associated with drought stress and tree mortality in seasonally snow-covered watersheds worldwide. Meanwhile, increasing forest density has further exacerbated drought stress due to intensified tree-tree competition. Using a uniquely detailed data set of population-level forest growth (n = 2,495 sampled trees), we examined how inter-annual variability in growth relates to snow volume across a range of forest densities (e.g., competitive environments) in sites spanning a broad aridity gradient across the United States. Forest growth was positively related to snowpack in water-limited forests located at low latitude, and this relationship was intensified by forest density. However, forest growth was negatively related to snowpack in a higher latitude more energy-limited forest, and this relationship did not interact with forest density. Future reductions in snowpack may have contrasting consequences, as growth may respond positively in energy-limited forests and negatively in water-limited forests; however, these declines may be mitigated by reducing stand density through forest thinning.

It is not just a 'trade-off': indications for sink- and source-limitation to vegetative and regenerative growth in an old-growth beech forest.

Controls on tree growth are key issues in plant physiology. The hypothesis of our study was that the interannual variability of wood and fruit production are primarily controlled directly by weather conditions (sink limitation), while carbon assimilation (source limitation) plays a secondary role. We analyzed the interannual variability of weather conditions, gross primary productivity (GPP) and net primary productivity (NPP) of wood and fruits of an old-growth, unmanaged Fagus sylvatica forest over 14 yr, including six mast years. In a multiple linear regression model, c. 71% of the annual variation in wood-NPP could be explained by mean air temperature in May, precipitation from April to May (positive influence) and fruit-NPP (negative influence). GPP of June to July solely explained c. 42% of the variation in wood-NPP. Fruit-NPP was positively related to summer precipitation 2 yr before (R2  = 0.85), and negatively to precipitation in May (R2  = 0.83) in the fruit years. GPP had no influence on fruit-NPP. Our results suggest a complex system of sink and source limitations to tree growth driven by weather conditions and going beyond a simple carbon-mediated 'trade-off' between regenerative and vegetative growth.

Forest Productivity Enhancement and Compensatory Growth: A Review and Synthesis.

This review and synthesis article attempts to integrate observations from forestry to contemporary development in related biological research fields to explore the issue of forest productivity enhancement and its contributions in mitigating the wood supply shortage now facing the forest sector. Compensatory growth has been clearly demonstrated in the long-term precommercial thinning and fertilization trial near the Shawnigan Lake, British Columbia, Canada. This phenomenon appears similar to many observations from other biological fields. The concept of compensatory growth can be applied to forest productivity enhancement through overcompensation, by taking advantage of theories and methods developed in other compensatory growth research. Modeling technology provides an alternative approach in elucidating the mechanisms of overcompensation, which could reveal whether the Shawnigan Lake case could be generalized to other tree species and regions. A new mitigation strategy for dealing with issues related to wood supply shortage could be formed through searching for and creating conditions promoting overcompensation. A forest growth model that is state dependent could provide a way of investigating the effect of partial harvest on forest growth trajectories and stand dynamics. Results from such a study could provide cost-effective decision support tools to practitioners.

How can forest management increase biomass accumulation and CO2 sequestration? A case study on beech forests in Hesse, Germany.

BACKGROUND: While the capability of forests to sequester carbon dioxide (CO2) is acknowledged as an important component in fighting climate change, a closer look reveals the difficulties in determining the actual contribution by forest management when indirect and natural impacts are to be factored out. The goal of this study is to determine the direct human-induced impacts on forest growth by cumulative biomass growth and resulting structural changes, exemplified for a dominating forest species Fagus sylvatica L. in central Europe. In 1988, forest reserves with directly adjacent forest management areas (under business as usual management) were established in the federal state of Hesse, Germany. Thereof, 212 ha of forest reserve and 224 ha of management area were selected for this study. Biomass changes were recorded for a time span of 19 to 24 years by methods used in the National Inventory Report (NIR) and structural changes by standard approaches, as well as by a growth-dominance model. RESULTS: The results indicate a higher rate of cumulative biomass production in the investigated management areas and age classes. The cumulative biomass growth reveals a superior periodic biomass accumulation of about 16%. For beech alone, it is noted to be about 19% higher in management areas than in forest reserves. When harvests are not included, forest reserves provide about 40% more biomass than management areas. The analysis of growth-dominance structures indicates that forest management led to a situation where trees of all sizes contributed to biomass increment more proportionally; a related increase in productivity may be explained by potentially improved resource-use efficiency. CONCLUSIONS: The results allow a conclusion on management-induced structural changes and their impact on carbon sequestration for Fagus sylvatica L., the dominating forest species in central Germany. This affirms a potential superiority of managed forests to forests where the management was abandoned in terms of biomass accumulation and reveal the impact and effect of the respective interventions. Especially the analysis of growth-dominance structures indicates that forest management resulted in more balanced dominance structures, and these in higher individual biomass increment. Forest management obviously led to a situation where trees of all sizes contributed to biomass increment more proportionally.