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China is reported as the leading country in the Earth's greening. However, it is a challenge to capture the gradual recovery in forest cover and distinguish the contribution of trees from herbaceous vegetation using remote sensing data. We developed a new fractional tree cover product (GLOBMAP FTC China) from MODIS time series data to investigate change patterns of China's forests during 2000–2022. This annual product showed high consistency with China's National Forest Inventory. We found a significant increase (∼4 Mha/year) in the annual forest area in China from ∼154.47 Mha in 2000 to ∼236.01 Mha in 2015. This rate then slowed by 50% in 2015–2022 (∼2 Mha/year). The forest recovery primarily started in 2000–2004, and reached saturation in 2015. It was primarily contributed by the tree cover gain (92%) from forest conservation and restoration programs. Our findings can support forest management and carbon neutrality achievement for the country. Plain Language Summary: As the largest carbon reservoir in terrestrial ecosystems, forests are an indispensable part of China's carbon sink. Explicitly monitoring when, where, and how the forest recovery happening in China is crucial. In this work, a fractional tree cover product (named GLOBMAP FTC China) is generated, providing the coverage of trees within pixels. Compared to other remote sensing products, this product is proved to have the best consistency with China's National Forest Inventory (NFI). Applying the product for analysis, we found that China's forests have been recovering since 2000, and the increasing rate then slowed by 50% after 2015. Forest area in southwestern China shows the fastest increasing rate during 2000–2022, which is more than 0.2 Mha per year. The changes primarily show a stepwise transition from forests with a low fractional tree cover to forests with a higher fractional tree cover, which mainly thanks to the forest conservation and restoration programs. This study underscores that trees' growth dominates the greening in China's forests, highlighting the importance of the new fractional tree cover product for future accurate forest change studies and implications for forest management. Our findings are crucial for climate change mitigation as proposed by the Paris Agreement. Key Points: This work generates a fractional tree cover product GLOBMAP to separate the mixed effect of herbaceous vegetation from woody coverUsing GLOBMAP, we can obtain detailed and nuanced forest recovery in China, which is consistent with China's National Forest InventoryDuring 2000–2022, China's forests primarily presented as a stepwise transition from low tree cover forests to higher ones [ABSTRACT FROM AUTHOR]

Estimating forest growing stock volume (GSV) is crucial for forest growth and resource management, as it reflects forest productivity. National measurements are laborious and costly; however, integrating satellite data such as optical, Synthetic Aperture Radar (SAR), and airborne laser scanning (ALS) with National Forest Inventory (NFI) data and machine learning (ML) methods has transformed forest management. In this study, random forest (RF), support vector regression (SVR), and Extreme Gradient Boosting (XGBoost) were used to predict GSV using Estonian NFI data, Sentinel-2 imagery, and ALS point cloud data. Four variable combinations were tested: CO1 (vegetation indices and LiDAR), CO2 (vegetation indices and individual band reflectance), CO3 (LiDAR and individual band reflectance), and CO4 (a combination of vegetation indices, individual band reflectance, and LiDAR). Across Estonia's geographical regions, RF consistently delivered the best performance. In the northwest (NW), the RF model achieved the best performance with the CO3 combination, having an R2 of 0.63 and an RMSE of 125.39 m3/plot. In the southwest (SW), the RF model also performed exceptionally well, achieving an R2 of 0.73 and an RMSE of 128.86 m3/plot with the CO4 variable combination. In the northeast (NE), the RF model outperformed other ML models, achieving an R2 of 0.64 and an RMSE of 133.77 m3/plot under the CO4 combination. Finally, in the southeast (SE) region, the best performance was achieved with the CO4 combination, yielding an R2 of 0.70 and an RMSE of 21,120.72 m3/plot. These results underscore RF's precision in predicting GSV across diverse environments, though refining variable selection and improving tree species data could further enhance accuracy. [ABSTRACT FROM AUTHOR]

In 2019–2023 the 13th Finnish National Forest Inventory (NFI) was implemented by measuring a total of 62 266 sample plots across the country. The methodology of the sampling and measurements was similar as in the previous inventory, but the proportion and number of remeasured permanent plots was increased to improve the monitoring of annual increment and other changes in the forests. Only 6.2 M ha (14%) of Finland’s total land area (30.4 M ha) is other land than forestry land. Productive and poorly productive forests cover 22.9 M ha (75%) of the total land area. The forest area has remained stable in recent decades but the forest area available for wood supply (FAWS) has decreased due to increased forest protection – 23% of the forestry land and 10% of the productive forest are not available for wood supply. Compared to the previous inventory, forest resources have continued to increase but the average annual increment has declined from 107.8 M m3 to 103.0 M m3. The quality of forests from the timber production point of view has remained relatively good or improved slightly. The area of observed forest damage on FAWS is 8.4 M ha (46% of FAWS area), half of these minor damages with no impact on stand quality. Although the area of forest damage has not increased, the amount of mortality has continued to increase, and is now 8.8 M m3 year–1. The amount of dead wood has continued to increase in South Finland, while in North Finland the declining trend has turned into a slight increase. Since the 1920s, the area of forestry land has remained stable, but the area of productive forest has increased due to the drainage of poorly productive or treeless peatlands. The total volume of growing stock has increased by 84% and annual increment has more than doubled.

Classifications of forest vegetation types and characterization of related species assemblages are important analytical tools for mapping and diversity monitoring of forest communities. The discrimination of forest communities is often based on β‐diversity, which can be quantified via numerous indices to derive compositional dissimilarity between samples. This study aims to evaluate the applicability of unsupervised classification for National Forest Inventory data from Georgia by comparing two cluster hierarchies. We calculated the mean basal area per hectare for each woody species across 1059 plot observations and quantified interspecies distances for all 87 species. Following an unspuervised cluster analysis, we compared the results derived from the species‐neutral dissimilarity (Bray‐Curtis) with those based on the Discriminating Avalanche dissimilarity, which incorporates interspecies phylogenetic variation. Incorporating genetic variation in the dissimilarity quantification resulted in a more nuanced discrimination of woody species assemblages and increased cluster coherence. Favorable statistics include the total number of clusters (23 vs. 20), mean distance within clusters (0.773 vs. 0.343), and within sum of squares (344.13 vs. 112.92). Clusters derived from dissimilarities that account for genetic variation showed a more robust alignment with biogeographical units, such as elevation and known habitats. We demonstrate that the applicability of unsupervised classification of species assemblages to large‐scale forest inventory data strongly depends on the underlying quantification of dissimilarity. Our results indicate that by incorporating phylogenetic variation, a more precise classification aligned with biogeographic units is attained. This supports the concept that the genetic signal of species assemblages reflects biogeographical patterns and facilitates more precise analyses for mapping, monitoring, and management of forest diversity. [ABSTRACT FROM AUTHOR]

In forests, the amount and diversity of structural features with high value for biodiversity, such as large trees and dead wood, are affected by productivity, stand age, and forest management. For efficient conservation of forest biodiversity, it is essential to understand the combined effects of these drivers. We used data from the Swedish National Forest Inventory to study the combined effects of productivity, stand age, and management for wood production on structures with high value for biodiversity: tree species richness, large living trees, dead wood volume, and specific dead wood types. Forest management changed the relationship between productivity and amount or diversity of some of the structures. Most structures increased with productivity and stand age, but decreased due to management. The negative effect of management was greatest for structures occurring mainly in high-productivity forests, such as deciduous dead wood. Thus, biodiversity conservation should target high-productivity forests to preserve these structures. [ABSTRACT FROM AUTHOR]

Winter storms pose a major threat to forest management in Central Europe. They affect forests at a large spatial scale and produce large losses in standing and merchantable timber within few hours. The assessment of winter storm vulnerability by statistical modelling serves as an important tool to tackle uncertainities about the damage risk and to inform management decision processes. This study made use of an extensive forest inventory data set from South-West Germany before and after winter storm Lothar in 1999, one of the most severe storm events in Germany over the last decades. Hierarchical logistic models were fitted to relate storm damage probability on individual tree level to features of dendrometry, site, orography, and storm-specific high resolution data of maximum gust speed. We developed two different approaches to implement gust speed as a predictor and compared them to a baseline model with a structured spatial effect function with no gust speed information. Regional and local variability which could not be described by the predictors was modelled by multi-level group effects. Generalisation performance was tested with a spatially and temporally independent data set on storm separation between explicit spatial gust speeds and unknown variability achieved with the parametric multi-level approach led to a higher degree of transparency and utilisability. [ABSTRACT FROM AUTHOR]

The link between biodiversity and ecosystem function can depend on environmental conditions. This contingency can impede our ability to predict how biodiversity‐ecosystem function (BEF) relationships will respond to future environmental change, causing a clear need to explore the processes underlying shifts in BEF relationships across large spatial scales and broad environmental gradients. We compiled a dataset on five functional traits (maximum height, wood density, specific leaf area [SLA], seed size, and xylem vulnerability to embolism [P50]), covering 78%–90% of the tree species in the National Forest Inventory from Italy, to test (i) how a water limitation gradient shapes the functional composition and diversity of forests, (ii) how functional composition and diversity of trees relate to forest annual increment via mass ratio and complementarity effects, and (iii) how the relationship between functional diversity and annual increment varies between Mediterranean and temperate climate regions. Functional composition varied with water limitation; tree communities tended to have more conservative traits in sites with higher levels of water limitation. The response of functional diversity differed among traits and climatic regions but among temperate forest plots, we found a consistent increase of functional diversity with water limitation. Tree diversity was positively associated with annual increment of Italian forests through a combination of mass ratio and niche complementarity effects, but the relative importance of these effects depended on the trait and range of climate considered. Specifically, niche complementarity effects were more strongly associated with annual increment in the Mediterranean compared to temperate forests. Synthesis: Overall, our results suggest that biodiversity mediates forest annual increment under water‐limited conditions by promoting beneficial interactions between species and complementarity in resource use. Our work highlights the importance of conserving functional diversity for future forest management to maintain forest annual increment under the expected increase in intensity and frequency of drought. [ABSTRACT FROM AUTHOR]

Key message: This paper proposes a methodology that could be considered as a base for a harmonized protocol for stem-quality reporting in Europe while conducting National Forest Inventories, in order to cost-efficiently obtain a visual wood quality proxy. The importance of the variables selected, the limitations identified, and some improvements to the methodology are suggested. Forest areas with better wood quality, which in turn it would be useful for breeding programs, can be easily detected. Context: The establishment of harmonized standards or indicators that allow us to determine the quality of the wood present in a forest prior to its exploitation has long been demanded by the European forestry sector, although agreed methodologies for the evaluation of wood quality in standing trees, which is one of the sector's most urgent requirements, have not, as yet, been implemented. Aims: To develop a protocol that visually characterizes wood quality on standing trees in a cost-effective way for the National Forest Inventory (NFI). After some improvements, it can be considered as a base for a European harmonized protocol. Methods: In this article, we analyze the implementation, in the NFI, of a visual wood-quality assessment methodology in forests of Central Spain based on the different European standards as well as on research papers addressing this issue. Results: The silvicultural practices employed are of the utmost importance to obtain the best wood quality, regardless of the species. Several areas with higher wood quality were identified as well as areas most affected by specific pests in the studied region. The impact of the variables measured (e.g., branchiness, crookedness, maximum branch diameter) is discussed. Conclusion: It is feasible to estimate a proxy for wood quality on standing trees in the NFI. Furthermore, after studying the inventory data provided, several enhancements are proposed, not only to improve wood-quality estimates but also to optimize fieldwork costs. Harmonizing NFIs to assess and map European standing wood quality can be achieved. [ABSTRACT FROM AUTHOR]

Standing deadwood is an important structural component of forest ecosystems. Its occurrence and dynamics influence both carbon fluxes and the availability of habitats for many species. However, deadwood is greatly reduced in managed, and even in many currently unmanaged temperate forests in Europe. To date, few studies have examined how environmental factors, forest management and changing climate affect the availability of standing deadwood and its dynamics.Data from five periods of the Austrian National Forest Inventory (1981–2009) were used to (I) analyse standing deadwood volume in relation to living volume stock, elevation, eco‐region, forest type, ownership and management intensity, (II) investigate the influence of forest ownership and management intensity on snag persistence and (III) define drivers of standing deadwood volume loss for seven tree genera (Abies, Alnus, Fagus, Larix, Picea, Pinus and Quercus) using tree‐related, site‐related and climate‐related variables, and predict volume loss under two climate change scenarios.Standing deadwood volume was mainly determined by living volume stock and elevation, resulting in different distributions between eco‐regions. While forest type and management intensity influenced standing deadwood volume only slightly, the latter exhibited a significant effect on persistence. Snag persistence was shorter in intensively managed forests than in extensively managed forests and shorter in private than in public forests.Standing deadwood volume loss was driven by a combination of diameter at breast height, elevation, as well as temperature, precipitation and relative humidity. Volume loss under climate change predictions revealed constant rates for moderate climate change (RCP2.6) by the end of the 21st century. Under severe climate change conditions (RCP8.5), volume loss increased for most tree genera, with Quercus, Alnus and Picea showing different predictions depending on the model used as the baseline scenario. We observed trends towards faster volume loss at higher temperatures and lower elevations and slower volume loss at high precipitation levels. The tree genera most susceptible to climate change were Pinus and Fagus, while Abies was least susceptible.Synthesis and applications. We recommend to protect standing dead trees from regular harvesting to ensure the full decomposition process. The consequences for decomposition‐dependent species must be taken into account to evaluate the influences of management and climate change on standing deadwood dynamics. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Models based on national forest inventory (NFI) data intend to project forests under management and policy scenarios. This study aimed at quantifying the influence of NFI sampling uncertainty on parameters and simulations of the demographic model MARGOT. Parameter variance–covariance structure was estimated from bootstrap sampling of NFI field plots. Parameter variances and distributions were further modeled to serve as a plug‐in option to any inventory‐based initial condition. Forty‐year time series of observed forest growing stock were compared with model simulations to balance model uncertainty and bias. Variance models showed high accuracies. The Gamma distribution best fitted the distributions of transition, mortality and felling rates, while the Gaussian distribution best fitted tree recruitment fluxes. Simulation uncertainty amounted to 12% of the model bias at the country scale. Parameter covariance structure increased simulation uncertainty by 5.5% in this 12%. This uncertainty appraisal allows targeting model bias as a modeling priority. Recommendations for Resource Managers: •Uncovering the potential and limitations of large‐scale forest models are needed when deducing recommendations from forest resource projections under forest management and policy scenarios at regional, national, or continental scales.•Estimating simulation uncertainty in these models is crucial to assess their accuracy. The present study offers a generic methodological strategy for assessing parameter uncertainty in large‐scale forest models.•Users of the MARGOT model should consider that simulation uncertainties proved to be low at a national scale, but decennial wood stock increases as observed in the French forests over the period 1970–2016 were underestimated.•Assessing simulation uncertainty is also major for model bias appraisal. Better accounting for the controls of forest demographic processes (growth, regeneration and mortality) appears to be a priority for the development of MARGOT, and for other large‐scale models. [ABSTRACT FROM AUTHOR]

Various tree species contribute differently to total biomass stock, making the development of species-specific stand-level equations critical for better estimation of forest biomass and quantification of carbon stocks. Previously derived dry weight biomass models did not assess the effect of dominant species composition according to stand growing stock. Growing stock definitions and forest species composition differ by country, justifying the need for national stand-level biomass equations. We explored the relationship between growing stock volume and stand biomass density of above- and below-ground components in six common forest categories in Latvia using plot-level data from the National Forest Inventory from 2016 to 2020. Additionally, we explored model dependence on region, forest type, and species composition index. Models that considered growing stock and dominant species composition index performed better than models with growing stock as the only variable, especially for heterogeneous deciduous forests with greater species diversity. The elaborated models are a useful alternative to individual-level assessment for estimating forest biomass stocks in circumstances where individual tree data are not available. [ABSTRACT FROM AUTHOR]

National Forest Inventories (NFIs) perform systematic forest surveys across space and time. They are hence powerful tools to understand climate controls on forest growth at wide geographical scales and account for the effects of local abiotic and biotic interactions. To investigate the effects of climate change upon growth dynamics of four major European conifer species along elevation and continentality gradients, we herein provide an original harmonization of the French and Austrian NFI datasets. The growth of Norway spruce, Scots pine, silver fir and European larch over the 1996–2016 period was studied in pure and even-aged plots across different ecological regions. We derived climate-driven growth trends from > 65, 000 radial increment series filtered out from major biotic and abiotic influences using statistical modeling. We further identified primary environmental drivers of conifer growth by regressing growth trends against regionally aggregated biotic and abiotic forest attributes. Negative growth trends were observed in continental regions undergoing the most rapid warming and thermal amplitude contraction over the study period. Negative trends were also associated with lower forest structural heterogeneity and, surprisingly, with greater available water capacity. Remarkably, we observed these associations both at the inter- and intra-species levels, suggesting the universality of these primary growth determinants. Our study shows that harmonized NFI data at the transnational level provide reliable information on climate–growth interactions. Here, greater forest structural complexity and greater water resource limitation were highlighted as drivers of greater forest resilience to climate change at large-scale. This result forms crucial bases to implementing climate-smart forest management. [ABSTRACT FROM AUTHOR]

In Europe, some non-native tree species (NNT) are classified as invasive because they have spread into semi-natural habitats. Yet, available risk assessment protocols are often based on a few limited case studies with unknown representativeness and uncertain data quality. This is particularly problematic when negative impacts of NNT are confined to particular ecosystems or processes, whilst providing valuable ecosystem services elsewhere. Here, we filled this knowledge gap and assessed invasion risks of two controversially discussed NNT in Germany (Quercus rubra L., Pseudotsuga menziesii (Mirb.) Franco) for broad forest types using large scale inventory data. For this purpose, establishment success of natural regeneration was quantified in terms of cover and height classes. The current extent of spread into protected forest habitats was investigated in south-west Germany using regional data. Establishment was most successful at sites where the NNT are abundant in the canopy and where sufficient light is available in the understory. Natural regeneration of both NNT was observed in 0.3% of the total area of protected habitats. In forest habitats with sufficient light in the understory and competitively inferior tree species, there is a risk that Douglas fir and red oak cause changes in species composition in the absence of management interventions. The installation of buffer zones and regular removal of unwanted regeneration could minimize such risks for protected areas. Our study showed that forest inventories can provide valuable data for comparing the establishment risk of NNT amongst ecosystem types, regions or jurisdictions. This information can be improved by recording the abundance and developmental stage of widespread NNT, particularly in semi-natural ecosystems. [ABSTRACT FROM AUTHOR]

Abstract Background Forest management aims at obtaining a sustainable production of wood to be harvested to generate products or energy. However, the quantitative influence of forest management and of removals by harvest on biomass stocks has rarely been analysed on a large scale based on measurements. Two hypotheses prevail: management induces a reduction of wood stocks due to cuttings, versus no impact because of increased growth of the remaining trees. Using data collected for 2840 permanent plots across Romania from the National Forest Inventory representing ~ 2.5 Mha, we have tested to what extent different management types and treatments can influence the biomass stock and productivity of beech forests, and attempt to quantify these effects both on the short and long terms. Three main types of beech forest management are implemented in Romania with specific objectives: intensive wood production in production forests, protection of ecosystem services (e.g. watersheds, avalanche protection) in protection forests, and protection of the forest and its biodiversity in protected forests. Production forests encompass two treatments differing according to the stand regeneration method: the age class rotation management and the group shelterwood management. Results We show that forest management had little influence on the biomass stocks at a given stand age. The highest stocks at stand age 100 were observed in production forests (the most intensively managed forests). Consequences of early cuttings were very short-termed because the increase in tree growth rapidly compensated for tree cuttings. The cumulated biomass of production forests exceeded that of protected and protection forests. Regarding the treatment, the group shelterwood forests had a markedly higher production over a full rotation period. The total amount of deadwood was primarily driven by the amount of standing deadwood, and no management effect was detected. Conclusions Given the relatively low-intensity management in Romania, forest management had no negative impact on wood stocks in beech forests biomass stocks at large scale. Stand productivity was very similar among management types or treatments. However cumulated biomass in production forests was higher than in protection or protected forests, and differed markedly according to treatments with a higher cumulated biomass in shelterwood forests.

Interactions between soil, topography, and climatic site factors can exacerbate and/ or alleviate the vulnerability of oak woodland to climate change. Reducing climaterelated impacts on oak woodland habitats and ecosystems through adaptation management requires knowledge of different site interactions in relation to species tolerance. In Britain, the required thematic detail of woodland type is unavailable from digital maps. A species distribution model (SDM) ensemble, using biomod2 algorithms, was used to predict oak woodland. The model was cross-validated (50%:50% - training:testing) 30 times, with each of 15 random sets of absence data, matching the size of presence data, to maximize environmental variation while maintaining data prevalence. Four biomod2 algorithms provided stable and consistent TSS-weighted ensemble mean results predicting oak woodland as a probability raster. Biophysical data from the Ecological Site Classification (forest site classification) for Britain were used to characterize oak woodland sites. Several forest datasets were used, each with merits and weaknesses: public forest estate subcompartment database map (PFE map) for oak-stand locations as a training dataset; the national forest inventory (NFI) "published regional reports" of oak woodland area; and an "NFI map" of indicative forest type broad habitat. Broadleaved woodland polygons of the NFI map were filled with the biomod2 oak woodland probability raster. Ranked pixels were selected up to the published NFI regional area estimate of oak woodland and matched to the elevation distribution of oak woodland stands, from "NFI survey" sample squares. Validation using separate oak woodland data showed that the elevation filter significantly improved the accuracy of predictions from 55% (p = .53) to 83% coincidence success rate (p < .0001). The biomod2 ensemble, with masking and filtering, produced a predicted oak woodland map, from which site characteristics will be used in climate change interaction studies, supporting adaptation management recommendations for forest policy and practice. [ABSTRACT FROM AUTHOR]

Forests and forest industries can contribute to climate change mitigation by sequestering carbon from the atmosphere, by storing it in biomass, and by fabricating products that substitute more greenhouse gas emission intensive materials and energy. The objectives of the study are to specify alternative scenarios for the diversification of wood product markets and to determine how an increasingly diversified market structure could impact the net carbon emissions (NCEs) of forestry in Finland. The NCEs of the Finnish forest sector were modelled for the period 2016–2056 by using a forest management simulation and optimization model for the standing forests and soil and separate models for product carbon storage and substitution impacts. The annual harvest was fixed at approximately 70 Mm3, which was close to the level of roundwood removals for industry and energy in 2016. The results show that the substitution benefits for a reference scenario with the 2016 market structure account for 9.6 Mt C (35.2 Mt CO2 equivalent [CO2 eq]) in 2056, which could be further increased by 7.1 Mt C (26 Mt CO2 eq) by altering the market structure. As a key outcome, increasing the use of by‐products for textiles and wood–plastic composites in place of kraft pulp and biofuel implies greater overall substitution credits compared to increasing the level of log harvest for construction. [ABSTRACT FROM AUTHOR]

Key message: Forest owners who maximize profitability with a low discount rate or whose management goals are related to conservation and recreation, rarely sell timber. These owners make it difficult to achieve the high harvesting targets of the growing bioeconomy sector of Finland. To increase timber supply, these landowners should be informed about alternative silvicultural methods. Context: The round wood harvests from Finnish forests are increasing and approaching to the level of maximum sustainable cut. Cutting budget calculations assume that forests are harvested in an optimal way for national timber supply. The calculations ignore the variability of landowners' forest management preferences. Aims: This study analyzed the effect of variation in the management objectives and silvicultural preferences of forest landowners on the forecasted timber supply from Finnish forests. Methods: Forest owners were divided into savers (net present value maximized with a 1% discount rate), average owners (3% discount rate), and investors (5% discount rate). The owners of each group were further divided into three groups: those who allow only continuous cover management (12%), owners who use only rotation forest management (10%), and indifferent landowners who may use both silvicultural systems (78%). Scenarios were composed of management prescriptions that were optimized separately for the different groups of forest landowners. Results: Compared to the even-flow timber drain scenario for rotation forest management (calculated without acknowledging the varying preferences of landowners), the scenario where the owners' preferences varied decreased harvested volume by 15–19% during a 100-year calculation period. The main reason for the difference was the saver type of landowners who rarely sell timber. Conclusion: It was concluded that variation of the preferences of forest landowners may make it challenging to meet the increasing harvesting targets of the growing bioeconomy of Finland. [ABSTRACT FROM AUTHOR]

The forest in India have a long history of human induced modifications through intensive forest management that began in the colonial period but continued afterwards to meet the wood-based demand until the forestry goals shifted towards conservation efforts. All this greatly influenced the plant community structure. We attempt to describe the abundance and distribution pattern of trees in recorded forestland of Western Himalaya using the National Forest Inventory database. A total of 3549 sample plots laid across different forest types were analyzed to reveal the abundance, frequency and distribution pattern of 226 tree species/genus using various indices i.e. abundance by frequency ratio, Morisita index and variance mean ratio. Twelve tree species and Eucalyptus genus were found to be most abundantly found tree species in recorded forest area of Western Himalaya. Ten tree species were found to have regular distribution pattern, one hundred ninety-two were contagiously distributed while twenty-five were randomly distributed. Results derived from huge datasets helps in establishing firm statements with quoted significance value. Myrica esculenta and Aegle marmelos were found among the most abundantly occurring tree species whereas Myrica esculenta, Syzygium cumini and Pyrus pashia, were among the most relatively frequently occurring wild fruit yielding tree species. These species (apart from fodder tree species) can be considered in social forest and joint forest management programs in forest fringe villages/areas to enhance and sustain the provisional ecosystem services in Western Himalaya. [ABSTRACT FROM AUTHOR]

Forest site quality assessment refers to the judgment and prediction of the appropriate forestry or potential productivity of the site. It is an extremely important basic work in the forest management. Taking Zhejiang province as a research area, based on the four consecutive National Forest Inventory (NFI) data from 1994 to 2009, the maximum DBH growth rate as a site quality evaluation indicator on Chinese fir plantation is proposed. The quantification theory model I was used to establish a regression model of the relationship between the maximum growth rate of the DBH and the site factors. The results show that the model's multiple correlation coefficient is 0.3167, and the F test reaches a significant level at the F0.01 (7,190). The model's RMSE and RRMSE are 3.4160, 30.3165%, respectively. The RMSE and RRMSE of the test data are, respectively, 3.249% and 29.1397% and the fitting accuracy is acceptable. The impact of the site quality factor on DBH growth rate of Chinese fir plantation in descending order is followed by aspect, soil, topography, slope, slope position, altitude, latitude. As an indicator on-site quality evaluation, maximum DBH growth rate is easy to be extracted from NFI data, and forest age as the traditional key dependence will no longer be essential. The method with effective use of NFI historical data is applicable to the even-aged forest and uneven-aged forest. Constructing a site quality evaluation model with the maximum growth rate of the DBH can effectively evaluate the site quality of the study area and is of great significance in forestry production. [ABSTRACT FROM AUTHOR]

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. • We modeled stand dominant height as a function of annual climate for 20 species. • On average, site index increased over the past century for most species. • Site index varied widely between and within species with climate change. • Site index increased mainly on temperature-limited sites. [ABSTRACT FROM AUTHOR]

The main objective of this study was to estimate past and future dynamics of forest carbon pools in South Korea, as classified by the Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance (GPG) and to test the Carbon Budget Model of the Canadian Forest Sector 3 (CBM-CFS3). Inventory data required in CBM-CFS3 were extracted from Korea’s 3rd Forest Type Map. The site index in the inventory data was estimated through regression models developed using 5th National Forest Inventory (NFI) data with 4000 plots. Necessary yield tables to a stand age of over 100 years, stratified by species, were prepared through the estimation of volume per ha with tree species, site index and stand age. We considered thinning and cutting regulations for sustainable forest management announced by the Korean Forest Service and that the forest area was constant over from 1992 to 2092. We estimated the carbon stocks and their changes of aboveground (AGB) and belowground (BGB) biomass, litter (L), dead wood (DW), and soil organic matter (SOM). Validation was conducted based on the 5th NFI and statistical data. Our results showed that the carbon content of the total forest area increased from 509.7 Tg C to 1007.3 Tg C at a rate of 11.8 Tg C yr-1 during 1992-2034. Results also showed that AGB, BGB, DW, L and SOM changed from 54.6, 30.2, 15.9, 43.6, and 373.9 Tg C in 1992 to 455.6, 100.77, 32.89, 65.46, and 369.2 Tg C in 2034, respectively. However, the amount of forest carbon was projected to decrease due to large increases in harvest rates as most of the forest reaches the legislated cutting age during 2035-2045. Our simulation estimated that by 2045 AGB, BGB, and SOM decreased to 347.8, 78.2, and 368.9 Tg C, respectively, while DW and L increased to 46.8 and 89.1 Tg C, respectively. The carbon content of the total forested area starts to stabilize after 2045 as the annual stand growth gradually decreases. Finally in 2092, the carbon content of AGB, BGB, DW, L, and SOM was estimated as 422.3, 93.9, 31.2, 63.0, and 365.1 Tg C, respectively. Through harvesting, over the 100 year period more than 200 Tg C were transferred from South Korea’s forests to meet demands for timber, fiber and energy. Good agreement between model results, NFI data and independent studies, demonstrates the applicability of CBM-CFS3 for estimating past and future forest carbon budgets in South Korean forests and for exploring forest management activity impacts in managed forests.

The future dynamics of forest species and ecosystems depend on the effects of climate change and are related to forest management strategies. The expected impacts of climate change are linked to forest growth and productivity. An increase in the length of the growing season and greater productivity are likely as well as shifts in average climatic values and more variable frequencies, intensities, durations and timings of extreme events. The main aim of this work is to assess and describe the climatic requirements for Italian forest tree species. We used 7,272 field observations from Italian National Forest Inventory plots and average annual temperatures and precipitation as interpolated from raster maps with 1 km spatial resolution. On this basis we evaluated the current observed distributions of the 19 most important tree species in Italy with respect to potential climatic limits based on expert knowledge and the available literature. We found that only 46% of the observations fall within the potential joint temperature and precipitation limits as defined by expert knowledge. For precipitation alone, 70% of observations were within the potential limits, and for temperature alone, 80% of observations were within the potential limits. Similarity between current observed and potential limits differ from species-to-species with broadleaves in general more frequently distributed within the potential climatic limits than conifers. We found that ecological requirements and potential information should be revised for some species, particularly for the Pinus genus and more frequently for precipitation. The results of the study are particularly relevant given the threat of climate change effects for Italian forests which are broadly acknowledged to be a biodiversity hotspot. Further investigations should be aimed at modelling the effects of climate changes on Italian forests as a basis for development of mitigation and adaptation forest management strategies. [ABSTRACT FROM AUTHOR]

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Aims: Plant responses to disturbances and environmental variation can manifest in communities as compositional nestedness (i.e., one community is a subset of another) and/or turnover (two communities represent different compositional gradient spaces). Yet, different sampling designs can artificially give an illusion of such compositional differences among two datasets, making it problematic to harmonize them in multi‐species analysis. We test the prediction that sampling differences which increase beta‐diversity components (nestedness and turnover) among two vegetation datasets will decrease their exchangeability. Location: Boreal forests of Tanana River region, interior Alaska, USA. Methods: We develop novel methods for comparing compositional variation among two datasets in nonmetric multidimensional scaling (NMDS) ordination. Resampled NMDS establishes internal sampling variability for each dataset independently, and reciprocal NMDS determines external exchangeability when the two are mutually exchanged. We first compare simulated data with specified beta‐diversity differences, then evaluate two forest inventories based on local vs regional sampling designs in Alaska's boreal forests. Results: As simulated species turnover and nestedness increased, internal sampling variability remained essentially constant, but external exchangeability progressively declined. Species turnover (not nestedness) had the larger negative effect on exchangeability. Among the boreal forest inventories, internal sampling variability was relatively similar, and exchangeability was weakly moderate, but the regional inventory exhibited much better fit to broad‐scale environment. Species turnover (not nestedness) contributed the majority of beta‐diversity differences among the two forest inventories, suggesting that strong environmental gradients were unequally represented. Conclusions: Species turnover alters multivariate outcomes more drastically than species nestedness. Therefore, combining two vegetation datasets may be inadvisable when turnover prevails. Instead, a multi‐scale perspective, with separate but complementary forest inventory analyses, can portray local and regional variation at appropriate scales. Our method is tractable for assessing exchangeability of potentially inconsistent sampling designs, like those that are common in synthesis studies and long‐term ecological monitoring. Combining two community datasets in one ordination can be risky if sampling designs differ. We present "reciprocal NMDS" methods and software to estimate multivariate data exchangeability. From simulations and real vegetation communities of boreal Alaska, poor exchangeability arises when species turnover prevails over nestedness. Long‐term monitoring programs can benefit from evaluating exchangeability when sampling designs change over time. [ABSTRACT FROM AUTHOR]

Abstract: Mixed species forests can often be more productive and deliver higher levels of ecosystem services and functions than monocultures. However, complementarity effects for any given tree species are difficult to generalize because they can vary greatly along gradients of climatic conditions and resource availability. Identifying the conditions where species diversity can positively influence productivity is crucial. To date, few studies have examined how growth complementarity across species and mixture types is modulated by stand and environmental factors, and fewer have considered more than one or two factors. We investigated how complementarity effects for several major Central European tree species change with climatic and edaphic conditions, and with stand structural characteristics, including species composition. We used data from the Swiss National Forest Inventory, which is based on 3,231 plots of pure and mixed stands (19 mixture types) across a broad environmental gradient, to test (i) how mixing effects change depending on the identity of the admixed species and (ii) if complementarity consistently increases when environmental conditions become harsher. The magnitude, whether positive or negative, of complementarity increased with increasing stand density and stand developmental stage, but no general pattern could be identified across mixture types. Complementarity for many species increased as drought intensity and temperature increased, but not for all species and mixture types. While soil conditions, nitrogen and site topography influenced complementarity for many species, there was no general pattern (increases and decreases were observed). Synthesis. Our study indicates that complementarity varies strongly with stand density and stand development as well as with topographic, climatic and soil conditions. This emphasizes the need to account for site‐dependent conditions when exploring mixture effects in relation to forest productivity. We found that under certain conditions (i.e. increasing drought, higher temperature), mixed forests can promote individual tree growth in Central European temperate forests. However, careful assessments depending on the species composing the stands are required under changing resource availability as well as under different levels of stand density and development. [ABSTRACT FROM AUTHOR]

Spatially explicit wall-to-wall forest-attributes information is critically important for designing management strategies resilient to climate-induced uncertainties. Multivariate estimation methods that link forest attributes and auxiliary variables at full-information locations can be used to estimate the forest attributes for locations with only auxiliary variables information. However, trade-offs between estimation accuracies versus logical consistency among estimated attributes may occur. This is particularly likely for macroscales (i.e., ≥1 Mha) with large forest-attributes variances and wide spacing between full-information locations. We examined these trade-offs for ∼390 Mha of Canada's boreal zone using variable-space nearest-neighbours imputation versus two modelling methods (i.e., a system of simultaneous nonlinear models and kriging with external drift). We found logical consistency among estimated forest attributes (i.e., crown closure, average height and age, volume per hectare, species percentages) using ( i) k ≤ 2 nearest neighbours or ( ii) careful model selection for the modelling methods. Of these logically consistent methods, kriging with external drift was the most accurate, but implementing this for a macroscale is computationally more difficult. This extra cost is justified given the importance of assessing strategies under expected climate changes in Canada's boreal forest and in other forest regions. [ABSTRACT FROM AUTHOR]

We used data from representatively sampled trees to identify key drivers of tree growth for central European tree species. Nonlinear mixed models were fitted to individual-tree basal area increments (BAI) from the Swiss national forest inventory. Data from 1983 to 2006 were used for model fitting and data from 2009 to 2013 for model evaluation. We considered 23 potential explanatory variables specifying individual-tree characteristics, site and stand conditions, management, climate, and nitrogen deposition. Model selection was processed separately for Picea abies, Abies alba, Pinus sp., Larix sp., other conifers, Fagus sylvatica, Quercus sp., Fraxinus sp./Acer sp., and other broadleaves. The selected models explained 56-70% of the BAI variance in the model fitting dataset and 21-64% in the evaluation dataset. While some variables were relevant for all species, the combination of further variables differed among the species, reflecting their physiological properties. In general, BAI was positively related to DBH and temperature and negatively related to basal area of larger trees, stand density, mean DBH of the 100 thickest trees per ha, slope, and soil pH. For most species, harvesting had a positive effect on BAI. In general, nitrogen deposition was positively related to BAI, except for spruce and fir, for which the inverse effect was found. Increasing drought reduced BAI for most species, except for pine and oak. These BAI models incorporate many influencing factors while representing large spatial extents, making them useful for both nationwide scenario analyses and deepening the understanding of the main drivers modulating tree growth throughout central Europe. [ABSTRACT FROM AUTHOR]

Aims Forest vegetation variability may be explained by the complex interplay among several spatial structuring factors, including climate and topography. We modelled the spatial variability of forest vegetation assemblages and significant environmental variables along a complex environmental gradient or coenocline to produce a detailed cartographic database portraying the distribution of forests along it. Methods We combined an analysis of ordination coenoclines with kriging over 772 field data plots from the third Spanish National Forest Inventory in an Atlantic--Mediterranean transitional area (northern Spain). Important Findings The best fitted empirical semivariogram revealed a strong spatial structure of forest species composition along the complex environmental gradient considered (the climatic--topographic gradient from north to south). The steady and gradual increase of semivariance with a marked lag distance indicates a gradual turnover of forest assemblages according to the climatic--topographic variations (regional or local). Two changes in the slope of the semivariogram suggest the existence of two different scales of spatial variation. The interpolation map by Kriging of forest vegetation assemblages along the main coenocline shows a clear spatial distribution pattern of trees and shrubs in accordance with the spatial variation of significant environmental variables. We concluded that the multivariate geostatistical approach is a suitable technique for spatial analysis of forest systems employing data from national forest inventories based on a regular network of field plots. The development of an assortment of maps describing changes in vegetation assemblages and variation in environmental variables is expected to be a suitable tool for an integrated forest management and planning. [ABSTRACT FROM AUTHOR]

• Evaluating methods to derive stand descriptions from large-scale sampling data. • Multi-scale approach to improve initialisation of dynamic forest models. • Simultaneous parameter prediction method best to predict tree diameter distributions. • Random Forest approach best to predict tree species composition. 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. [ABSTRACT FROM AUTHOR]

The National Mapping Agency in Sweden has conducted an airborne laser scanning (ALS) campaign covering almost the entire country for the purpose of creating a new national Digital Elevation Model (DEM). The ALS data were collected between 2009 and 2015 using Leica, Optech, Riegl, and Trimble scanners and have a point density of 0.5–1.0 pulses/m 2 . A high resolution national raster database (12.5 m × 12.5 m cell size) with forest variables was produced by combining the ALS data with field data from the Swedish National Forest Inventory (NFI). Approximately 11500 NFI plots (10 meter radius) located on productive forest land, inventoried between 2009 and 2013, were used to create linear regression models relating selected forest variables, or transformations of the variables, to metrics derived from the ALS data. The resulting stand level relative RMSEs for predictions of stem volume, basal area, basal-area weighted mean tree height, and basal-area weighted mean stem diameter were in the ranges of 17.2–22.0%, 13.9–18.2%, 5.4–9.5%, and 8.7–13.1%, respectively. It was concluded that the predictions had an accuracy that were at least as good as data typically used in forest management planning. Above ground tree biomass was also included in the national raster database but not validated on a stand-level. An important part of the project was to make the raster database available to private forest owners, forest associations, forest companies, authorities, researchers, and the general public. Thus, all predicted forest variables can be viewed and downloaded free of charge at the Swedish Forest Agency's homepage ( http://www.skogsstyrelsen.se/skogligagrunddata ). [ABSTRACT FROM AUTHOR]

Carbon sequestration has become an important issue in forest management in the light of concerns about global warming. The two methods proposed by IPCC to quantify the net carbon sequestered by trees are based either on the estimation of annual gains and losses of carbon due to the growth of trees and their removals (default method), or on the difference in carbon stocks between two consecutive inventories (stock-change method). The objectives of this study are to compare the net carbon sequestered by the tree layer of forest ecosystems in Andalusia estimated by the two methods, and to identify what measured variables contribute the most to the differences in the estimations. Multivariate analysis was performed in order to identify the causes of these variations. The results revealed differences of up to 200% in the estimated net carbon sequestration depending on the methodology employed, and changes in the direction of the capture/emission in some areas. The net carbon sequestration ranged between 0.08 ± 0.01 and 1.93 ± 0.52 Mg C ha−1year−1depending on the method used and on the tree species analyzed. In global terms, net carbon sequestration at the regional level reaches 2,101,715 ± 560,906 Mg C according to thedefault methodand 1,693,412 ± 272,529 Mg C using thestock-change method. [ABSTRACT FROM PUBLISHER]

Mortality is a key process in forest stand dynamics. However, tree mortality is not well understood, particularly in relation to climatic factors. The objectives of this study were to: ( i ) determine the patterns of maximum stem number per ha (MSN) over dominant tree height from 5-year remeasurements of the permanent sample plots for temperate forests [Red pine ( Pinus densiflora ), Japanese larch ( Larix kaempferi ), Korean pine ( Pinus koraiensis ), Chinese cork oak ( Quercus variabilis ), and Mongolian oak ( Quercus mongolica )] using Sterba’s theory and Korean National Forest Inventory (NFI) data, ( ii ) develop a stand-level mortality (self-thinning) model using the MSN curve, and ( iii ) assess the impact of temperature on tree mortality in semi-variogram and linear regression models. The MSN curve represents the upper boundary of observed stem numbers per ha. The developed mortality model with our results showed a high degree of reliability (R 2 = 0.55–0.81) and no obvious dependencies or patterns in residuals. However, spatial autocorrelation was detected from residuals of coniferous species (Red pine, Japanese larch and Korean pine), but not for oak species (Chinese cork oak and Mongolian oak). Based on the linear regression analysis of residuals, we found that the mortality of coniferous forests tended to increase with the rising seasonal temperature. This is more evident during winter and spring months. Conversely, oak mortality did not significantly vary with increasing temperature. These findings indicate that enhanced tree mortality due to rising temperatures in response to climate change is possible, especially in coniferous forests, and is expected to contribute to forest management decisions. [ABSTRACT FROM AUTHOR]

The main objective of this study was to estimate past and future dynamics of forest carbon pools in South Korea, as classified by the Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance (GPG) and to test the Carbon Budget Model of the Canadian Forest Sector 3 (CBM-CFS3). Inventory data required in CBM-CFS3 were extracted from Korea's 3rd Forest Type Map. The site index in the inventory data was estimated through regression models developed using 5th National Forest Inventory (NFI) data with 4000 plots. Necessary yield tables to a stand age of over 100 years, stratified by species, were prepared through the estimation of volume per ha with tree species, site index and stand age. We considered thinning and cutting regulations for sustainable forest management announced by the Korean Forest Service and that the forest area was constant over from 1992 to 2092. We estimated the carbon stocks and their changes of aboveground (AGB) and belowground (BGB) biomass, litter (L), dead wood (DW), and soil organic matter (SOM). Validation was conducted based on the 5th NFI and statistical data. Our results showed that the carbon content of the total forest area increased from 509.7 Tg C to 1007.3 Tg C at a rate of 11.8 Tg C yr-1 during 1992-2034. Results also showed that AGB, BGB, DW, L and SOM changed from 54.6, 30.2, 15.9, 43.6, and 373.9 Tg C in 1992 to 455.6, 100.77, 32.89, 65.46, and 369.2 Tg C in 2034, respectively. However, the amount of forest carbon was projected to decrease due to large increases in harvest rates as most of the forest reaches the legislated cutting age during 2035-2045. Our simulation estimated that by 2045 AGB, BGB, and SOM decreased to 347.8, 78.2, and 368.9 Tg C, respectively, while DW and L increased to 46.8 and 89.1 Tg C, respectively. The carbon content of the total forested area starts to stabilize after 2045 as the annual stand growth gradually decreases. Finally in 2092, the carbon content of AGB, BGB, DW, L, and SOM was estimated as 422.3, 93.9, 31.2, 63.0, and 365.1 Tg C, respectively. Through harvesting, over the 100 year period more than 200 Tg C were transferred from South Korea's forests to meet demands for timber, fiber and energy. Good agreement between model results, NFI data and independent studies, demonstrates the applicability of CBM-CFS3 for estimating past and future forest carbon budgets in South Korean forests and for exploring forest management activity impacts in managed forests. [ABSTRACT FROM AUTHOR]

• Modern aspen forest management guides are based on data from nearly a century ago. • Current atmospheric CO2, climate, and management objectives changed over a century. • Mismatched data for guides and forest conditions reduces forest health and management. • Aspen stocking tables recalculated with modern data show that guides are outdated. • New management guides should be dynamic to empower adaptive management. Since the development of contemporary stocking techniques a century ago, the combination of climatic, atmospheric, financial, and social factors that determine forest management strategies have changed, altering aspen stand dynamics in the western Great Lakes, USA. Despite this, aspen management is still informed by 1970s management guides that are based on 1920s inventories; hence, a century exists between the data that underlie current management guidelines and current stand conditions. We hypothesized that current aspen stands may support higher stocking and height growth than nearly a century ago at relatively similar age and site indices, due to increased atmospheric CO 2 concentrations and fertilization, intensive coppice harvests, and other factors. To explore this question, we compared historic aspen observations with comparable contemporary data from the USDA Forest Service's Forest Inventory and Analysis program. The results show increased stand stocking levels as well as increased height growth of aspen throughout the region over the historic inventory data. Although other controlled experimental studies support the hypothesis of increased carbon fertilization altering aspen size-density relationships, our study is the first to examine an empirical application to forest management guides. Our results suggest a comprehensive reevaluation of aspen growth dynamics under contemporary environmental conditions is warranted. We highlight the need to assess the value of current stocking standards in an era of increasingly variable environmental conditions and to reimagine a more dynamic, responsive, and predictive approach to guide forest management for future application as global change may accelerate. [ABSTRACT FROM AUTHOR]

For forest ecosystems, studies dealing with diversity-productivity relationships are often based on diameter increment observations. Studying how height growth is affected by species interactions can provide new insights on this issue. We studied the mixture effect on dominant height growth in order to answer two questions. Do species interactions in mixed forest modify the dominant height growth of species? Does the diversity effect on diameter found in previous studies correspond to actual overyielding, or rather to an effect on allocation of growth between diameter and height? We used the French National Forest Inventory (NFI) data to model the mixture effect on dominant height. We included biophysical factors in the models to compare the dominant height of mixed and monospecific stands, all other parameters being equal. We studied five target species – Quercus petraea (Matt.) Liebl., Fagus sylvatica L., Picea abies (L.) Karst., Abies alba Mill., and Pinus sylvestris L. – in association with sixteen other species. Mixture effects on dominant height were weak, though often significant. They were either positive or negative according to species association. We showed that mixture effect on dominant height corresponds to a leveling process between species: the taller one limits its growth while the smaller one’s growth increases. Furthermore, most of the time, mixture effects on dominant height are in the same direction as those found on diameter, though with a lower magnitude. Our results confirm that tree diversity results in overyielding rather than in a different allocation of volume between the parts of the tree. [ABSTRACT FROM AUTHOR]

While a large sum of timber stock in private forests, especially broadleaved forests, has been ignored by their owners, a rising global concern about climate change and ecosystems has led to a renewed interest in natural broadleaved forest management strategies. This study establishes the forest growth model for the natural broadleaved forest of Gangwon-do based on the matrix model developed by Buongiorno and Michie. The matrix model by Buongiorno and Michie has been widely applied to study forest population dynamics, especially for uneven-aged forests. To develop an existing matrix model, our approach applies transitional probabilities of forest stands which are calibrated using National Forest Inventory data. Both long and short-term predicted simulation results show that the predicted average tree density and diameter distribution from our model are very close to the stand density and diameter distribution from observed data. Although the model simplifies reality, the results from our study confirm that our models are valid enough to predict the average stand status of the broadleaved forests in Gangwon-do. [ABSTRACT FROM AUTHOR]

Dead wood is a critical resource for forest biodiversity and widely used as an indicator for sustainable forest management. Based on data from the Swedish National Forest Inventory we provide baseline information and analyze trends in volume and distribution of dead wood in Swedish managed forests during 15 years. The data are based on ≈30,000 sample plots inventoried during three periods (1994–1998; 2003–2007 and 2008–2012). The forest policy has since 1994 emphasized the need to increase the amount of dead wood in Swedish forests. The average volume of dead wood in Sweden has increased by 25% (from 6.1 to 7.6 m 3 ha −1 ) since the mid-1990s, but patterns differed among regions and tree species. The volume of conifer dead wood (mainly from Picea abies ) has increased in the southern part of the country, but remained stable or decreased in the northern part. Heterogeneity of dead wood types was low in terms of species, diameter and decay classes, potentially negatively impacting on biodiversity. Overall, we found only minor effects of the current forest policy since most of the increase can be attributed to storm events creating a pulse of hard dead wood. Therefore, the implementation of established policy instruments (e.g. legislation and voluntary certification schemes) need to be revisited. In addition to the retention of dead trees during forestry operations, policy makers should consider calling for more large-scale targeted creation of dead trees and management methods with longer rotation cycles. [ABSTRACT FROM AUTHOR]

The aim of this study was to quantitatively assess and analyze the dynamic changes and current problems of Chinese forest resources based on the National Forest Inventory (NFI). In this study, a hierarchical model was established using the analytic hierarchy process to assess forest resources quality (FRQ) at the provincial level. Four criteria were used, including forest quantity, forest productivity, forest structure, and forest health and each criterion was further composed of multiple factors. Among these assessment factors, stock volume per unit area was the most important, while canopy structure was the least important. The ranges of FRQ Indies across China during the 6th NFI (1999–2003), 7th NFI (2004–2008), and 8th NFI (2009–2013) were 0.3031–0.6366, 0.3499–0.7186, and 0.3534–0.7555, respectively. From the 6th to 8th NFI, forest quality improved by different degrees for all provinces, whereas the other three criteria presented an increasing or decreasing trend. In general, the implementation of ecological projects has significantly improved the FRQ at provincial and national levels. During the 8th NFI, the FRQ levels were excellent for 3 provinces, good for 15 provinces, medium for 12 provinces, and only one province exhibited an inferior level of FRQ. Based on cluster analysis, Chinese forest resources during the 8th NFI could be grouped into four clusters according to the provincial administrative region, and each cluster had its own advantages and disadvantages. Stock volume increment and forest calamity were in a very good state, while canopy structure was the key factor limiting the FQR for all the clusters. Some relevant measures were proposed to improve the existing conditions of Chinese forest resources. The results of this study are significant in that they can provide theoretical and technical references for future adjustment and sustainable management of forest resources in China. [ABSTRACT FROM AUTHOR]