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The objective of this article is to evaluate the adequacy of different probabilistic distribution models in the characterization of the diameter structure of a secondary native forest of Araucaria angustifolia in Campo Belo do Sul and Capão Alto, Santa Catarina. The fixed area method was used with cluster sampling, measuring trees with Diameter at Breast Height (DBH) = 10 cm. The diameter classes were grouped into amplitudes of 10 cm. The density and probability functions Gamma, Normal, Log-normal, Exponential, Weibull 2p and Weibull 3p were tested. The following statistics were evaluated: Kolmogorov-Smirnov test, adjusted and corrected standard error of estimation, adjusted coefficient of determination, Akaike information criterion and Bayesian criterion. The forest presented an inverted J-diameter distribution and only the Weibull 3p model was adjusted to all diameter classes. The Log-normal and Weibull 3p models were the most suitable, with Weibull 3p showing the best overall performance. [ABSTRACT FROM AUTHOR]

There is a growing demand for wood products from forests located in dry regions, which includes the Caatinga, a biome in Northeast Brazil. This study evaluates the relationship between volumetric production, energy potential, and the rotation cycle. Information was collected from forest stands in different stages of regeneration located in an arid region of Brazil. Based on the forest management plan, four fields were selected with post-logging ages of 9, 11, 13, and 16 years. This inventory recorded circumference at chest height, circumference at base height, total height, volume, stored energy, technical cutting age, and rainfall index. The results showed that the species that presented the most significant quantity of stems did not always correspond to those that obtained the most significant amount of biomass. The technical cutting age was determined at 16 years, aiming to maximize wood utilization. Regarding energy density, the 9-year-old field reached 7,281 kcal ha-1, the 11-yearold field obtained 14,448 kcal ha-1, the 13-year-old field recorded 41,526 kcal ha-1, and the 16-year-old field reached 98,190 kcal ha-1. The species that contributed most to energy accumulation included Mimosa tenuiflora with 3,740 kcal m-³, Piptadenia stipulacea with 3,271 kcal m-3, and Cenostigma pyramidale with 3,101 kcal m-3. [ABSTRACT FROM AUTHOR]

In nutrient poor and dry forest sites common to northern Scandinavia, Scots pine (Pinus sylvestris L.) is the most common species both in managed and natural forests. However, Scots pine is sensitive to competition during establishment. Harvesting of all trees within a given area, i.e., clear-cutting, liberates regenerating seedlings from competition with mature trees. However, recently, clear-cut-free or continuous cover forestry has been the subject of substantial debate. When choosing a management method, it is important to recognize how competitive interactions direct the success of Scots pine regeneration. We studied Scots pine regeneration at three environments: beneath the canopy of mature trees, at the canopy edge in full sunlight, and distant from the canopy with no influence of mature trees. We imposed three treatments in each of these environments: root isolation (i.e., trenching), nitrogen (N) fertilization, and control plots. Root isolation enhanced seedling performance under the canopy of mature trees. Nitrogen fertilization enhanced seedling performance to a greater extent in the clear-cut than at the forest edge. However, N fertilization had no effect under the canopy. In the N-fertilized plots, we measured higher N content in the soil under the canopy than in the open environments, indicating that not all excess N was obtained by the mature trees. N-uptake might have been limited by competition for water in the N-fertilized plots. Our results suggest that belowground competition limits the success of regeneration of Scots pine. However, N fertilization presents a tool to compensate for underground competition along canopy edges. [ABSTRACT FROM AUTHOR]

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Aims: Ecological stoichiometry plays an important role in biogeochemical cycles and ecosystem functions. However, we know little of fine-root stoichiometry responses to nitrogen (N) addition and whether the responses are similar to those of leaves. Methods: We conducted a field experiment to explore the effects of N addition on carbon: N: phosphorus (C:N:P) stoichiometric ratios and homeostasis in green leaves, fine roots and soil as well as the regulatory effects of plant and soil stoichiometric ratios on forest growth in poplar plantations on the eastern Chinese coast. Results: We found that N addition increased soil organic C (SOC), soil available N and P, and soil N:P and decreased soil C:N. We also found that N addition increased leaf C and N, N:P and C:P of green leaves and fine roots, while it decreased fine root C and P as well as green leaf and fine root C:N. The consistent responses of green leaf and fine root stoichiometry to N addition were attributed to stoichiometric homeostasis. That diameter at breast height (DBH) and fine root biomass (FRB) growth contradicted C:N:P stoichiometry appeared to be because of their different nutrient uptake and utilization efficiencies. Conclusions: The C:N:P stoichiometry of green leaves and fine roots was generally consistent in response to N addition. These findings contribute to our understanding of the biogeochemical cycles of plantation ecosystems and provide basic data for plantation cultivation and management. [ABSTRACT FROM AUTHOR]

This paper analyses the trends, patterns and determinants of biodiversity conservation in the Buxa Tiger Reserve (BTR), India. Temporal remote sensing data from 1990 to 2020 shows a loss of 27.69 km2. The results show that the total forest area has seen a significant decline from 1990 to 2020, whereas non-forest and degraded forest areas have been on the rise. The decline of forest area is observed more in fringe and lower altitude areas where accessibility is easy for humans to extract forest resources. The secondary data shows a decline in the wildlife population including the flagship species, the Bengal tiger. The decline in natural resources due to human activities in the BTR is likely to continue unless a participatory biodiversity conservation programme is established. The establishment of the Joint Forest Management Committee (JFMC), a formal local institution where local communities and forest departments (FDs) jointly share the rights and responsibility towards the use and management of the forest, seems to be effective in reducing negative forest activities. The sustainability of the BTR is possible if the local people abandon the 'tragedy of the commons' activities and work together, with government guidance for the promotion of livelihoods and biodiversity conservation. [ABSTRACT FROM AUTHOR]

Despite the potential of secondary tropical forests to store and sequester substantial amounts of carbon, little is known about their above-ground carbon (AGC) stocks and the factors affecting them, especially in West Africa. This information is of key importance if the countries in this region want to achieve their forest restoration and climate mitigation commitments. To fill in this gap, we investigated how environmental and local management (e.g. remnant trees) factors influenced AGC and tree species richness in secondary forests at seven sites across Guinea, Sierra Leone and Liberia. We established 140 plots (20 x 50 m) in fallows <15 years (20 plots per site) and sampled all trees ≥10 cm diameter following standardised protocols. We found that AGC stocks and tree species richness increased with fallow age, but were highly variable across sites driven by both climatic and local management practices. While drought stress negatively affected AGC, remnant trees had a positive effect. AGC recovery rates ranged between 0.72 Mg C ha−1 y−1 (second driest site) and 13.76 Mg C ha−1 y−1 (wettest site). Given its low cost, our findings highlight the potential of passive restoration in secondary forests for carbon sequestration, particularly in wetter landscapes and areas with remnant trees from prior land use. • Above-ground carbon and tree species diversity increased with fallow age. • Above-ground carbon recovered slower in drier compared to wetter sites. • Remnant trees had a positive effect on above-ground carbon and species recovery. • Previous estimates from Ivory Coast are not applicable to the countries we studied. [ABSTRACT FROM AUTHOR]

Overcoming the climate crisis and achieving the 1.5 °C target requires the exploration of climate-resilient development pathways (CRDPs), as emphasized in the intergovernmental panel on climate change (IPCC) AR6 report. Republic of Korea has aligned itself with the international context by setting nationally determined contributions (NDC) and long-term low greenhouse gas emission development strategies (LEDS) goals. In addition, the country has announced plans to enhance carbon sink in the forestry sector. This study explored the CRDP in the forestry sector using an advanced Korean forest dynamic growth model (AKO-G-Dynamic model) with refined management algorithms. We utilized this model and applied various options for forest management based on the available detailed data, including climate change scenarios and policies reflecting possible CRDPs in the Republic of Korea. As a result, CO 2 sequestration in the 2050s was predicted to be 23.08 million tCO 2 year−1 if climate change SSP 5–8.5 and the current forest management level are maintained and 28.49 million tCO 2 year−1 if climate change SSP 1–2.6 and resilient level of forest management are applied. Furthermore, from the perspective of the age class of the forest, the proportion of over-matured forests decreased, leading to an improvement in the imbalance of age classes as climate change mitigation and sustainable forest management were implemented. Therefore, this study demonstrated realizable CRDPs and their implementation in decision-making concerning the NDC and LEDS. This comprehensive analysis of climate change and forest management, exploring the CRDP from various perspectives, can contribute to the development of forest management policies for climate adaptation strategies and carbon sink enhancement, thereby influencing the allocation of the carbon budget. • Explored climate-resilient development pathways in South Korea's forestry sector using the AKO-G-Dynamic model. • Predicted CO 2 sequestration for the 2050s to be 23.08 million tCO 2 year−1 under SSP5–85 and 28.49 million tCO 2 year−1 under SSP1–26 with resilient management. • Reduced over-matured forests and improved age class balance through sustainable forest management. • Provided insights for developing forest management policies to enhance climate adaptation and carbon sinks [ABSTRACT FROM AUTHOR]

Phenolic compounds (PC) are important secondary metabolites in plants, playing a crucial role in plant defense mechanisms against pathogens and other plants. Monitoring PC levels is important for understanding tree stress and implementing effective breeding programs. However, traditional methods for monitoring PC are time-consuming, prone to altering the phenolic composition, and mostly applicable only on a small scale. In this study, we evaluated the performance of Unoccupied Aerial Vehicles (UAV) multispectral imaging in estimating the canopy phenolic content in slash pine over an 11-month period in 2021 and a seven-month period in 2022. Three machine learning models including Partial least squares regression (PLSR), Random forest (RF) and Support Vector Machine (SVM) were compared to determine the optimal predictive model for canopy PC. The RF model provided the best predictive results, with R2 values of 0.82 for the validation set and 0.94 for the calibration set. Additionally, the study assesses the heritable variation in canopy PC over time, with the monthly heritability (h 2 ) of PC ranging from 0 to 0.26 in 2021 and from 0 to 0.35 in 2022; The highest h 2 levels were observed in July and September 2021and July 2022. The findings demonstrate significant genetic control over the variation of PC. Furthermore, we observed higher breeding values and genetic gains in July and November, which further supports the strong correlation between PC and environmental factors such as temperature and light intensity. To the best of our knowledge, this is the first study to employ time-series UAV multispectral imaging to predict secondary metabolites in pine trees and estimate their genetic variation over time. As a proof of concept, these findings provide more reliable information for tree breeding programs, ultimately enhancing their overall performance. • UAV Innovation: First-time use of UAV multispectral imaging for phenolics in slash pine. • ML Models: Random Forest model showed highest accuracy in predicting canopy phenolics. • Genetic Insights: Detailed analysis of heritable variation in canopy phenolics over time. • Seasonal Analysis: Conducted comprehensive statistical analysis of phenolic content variations. [ABSTRACT FROM AUTHOR]

Geum River basin is currently suffering from stream drying which is caused by various reasons. Among many reasons, the expansion of groundwater use and forest growth which are known to pose an influence on stream drying have significantly developed over the past 40 years in Geum River basin. Therefore, the periodic change of two factors were reflected to SWAT to figure out their influences on watershed hydrology and stream drying. The periodic change was considered by using 10-year period data from the 1980s (1976 ~ 1985) to the 2010s (2006 ~ 2015), and applying the condition to SWAT. The model was calibrated based on observed data of streamflow, evapotranspiration, at monitoring points including dam, weir, flux tower, and soil moisture sensor. The calibration result showed satisfactory result evaluated by coefficient of determination (R2), Nash–Sutcliffe Efficiency (NSE), scatter index (SI), and percent bias (PBIAS). The impact of groundwater use and forest growth was evaluated by hydrologic responses obtained by differentiating and comparing their conditions by period while settling weather conditions. As a result, the increase of groundwater use lowered groundwater recharge and groundwater flow while forest growth led to the rise of evapotranspiration which lessened surface runoff and the infiltration to soil layer. These two series of processes reduced total runoff showing decreased value of 2.7%, 6.3%, and 8.9% in 1990s, 2000s, and 2010s compared to 1980s. [ABSTRACT FROM AUTHOR]

Forest structure and composition have changed rapidly worldwide, presenting tendencies towards an increasing proportion of younger trees. From chronologies of tree-ring indices (TRI) and the reconstruction of the basal area increment (BAI), a dendroecological study was conducted from the perspective of the radial growth of twelve contemporary conifer species in a highly diverse region of the planet. From an elevational perspective, the TRI were associated with climate and the NDVI, while the BAI was also modeled as a potential proxy for forest productivity. Climate affects the species differently according to elevation: at 1900 m asl, Pinus caribaea, P. oocarpa and P. jeffreyi presented the lowest sensitivities to climate and drought. For their part, species occupying the intermediate part of the gradient (1901–3000 m asl), such as P. engelmannii, P. patula, P. johannis and P. maximartinezii, were very sensitive to maximum temperature (TMax), precipitation (PP) and drought during the winter–spring period. Finally, of the species distributed on the upper part of the gradient (>3000 m asl), only Abies religiosa was associated with TMax and drought; Juniperus deppeana, A. hickelii and P. hartwegii did not seem to be vulnerable to drought. Complementarily, we found significant differences in the BAI as a function of elevation, with the sites at 1001–1500 m asl presenting higher BAI. The results suggest that the growth in these forests is impacted by droughts and follows a distinct spatial pattern, with greater restriction found in mid-elevation forests. Consistent implications are also observed in BAI trends. For its part, the NDVI demonstrated a decreasing tendency in greenness from south to north, although no elevation pattern was evident. The combined proxies utilized here produced parameters that improve our understanding of forest growth and should be considered in vegetation dynamics models in order to reduce their uncertainty in the face of climate vulnerability. These forests must be sustainably managed, and it is therefore crucial to determine the influence of ecological variables on their growth. [ABSTRACT FROM AUTHOR]

• The spatial and temporal patterns of China's carbon changes at the pixel scale were provided. • China's aboveground biomass carbon (AGC) stock showed an increase in recent years. • The carbon sink rate of China's forests peaked in middle-aged forests and then decreased with increasing forest age. • The Grain for Green Program contributed most to the increase of aboveground carbon sinks in China. China's terrestrial ecosystems are pivotal in upholding the global carbon balance, with their recognized capacity for carbon sequestration holding significant importance on a global scale, but there are still challenges in accurately monitoring its spatial-temporal patterns. SMOSMAP-IB L - VOD, a recently developed low-frequency L - band Vegetation Optical Depth (L-VOD) product, was employed to monitor the fluctuations in aboveground vegetation carbon stock over China between 2015 and 2021, and to investigate the influence of forest age and ecological restoration projects on China's carbon sink capacity. The carbon sink of above-ground vegetation in China was + 169. 98 + 135.59 + 179.44 Tg C yr-1 during 2015–2021. Southwest and northeast China's forests exhibit higher carbon sink capacity, contrasting with lower values per unit area are mainly found in northwestern China. The forest served as the foremost contributor to the carbon sink of above-ground vegetation in China, although their carbon density peaked in the middle-aged forests and then gradually decreased as the age of the forest grew. Furthermore, carbon sink areas were observed in most regions where ecological restoration projects were implemented, indicating that the execution of afforestation and ecological restoration initiatives has proven effective in carbon sequestration, creating a sink in these areas. Our results provide an improved foundation for formulating new afforestation policies in the future. [ABSTRACT FROM AUTHOR]

The out-of-phase rainfall and temperature and deep root system make the sequential connection between past rainfall events, soil water storage, and forest growth response complicated and temporally extended in asynchronous climates with Mediterranean-type settings. Unfortunately, these location-specific deep-soil water stores are rarely measured due to logistic and financial constraints, especially in the forest. Therefore, at a large spatio-temporal scale, forest growth relationship to growth drivers is still unknown in these ecosystems, limiting our knowledge to understand the functioning of these forests and their links with hydrological processes. Although process-based water balance models can analyze vegetation growth response to the input climate forcing, they rely upon some significant assumptions regarding plants access to deep soil water storage. Thus, this study aims to understand how the out-of-phase rainfall events affect the current ecosystem growth response, represented by the observed Normalized Difference Vegetation Index (NDVI), across the landscape. We have used an empirical approach on long term observed data without any assumption on access to deep-soil water stores. We estimated time lags between forest growth and rainfall events using a lagged correlation analysis applied to monthly anomalies of NDVI and rainfall against their climatological averages over 2002–2018. The study found that the forests in asynchronous climates exhibit unexpectedly long (10–25 months) memory to rain, and this memory has a systematic pattern across the landscape, which we contend has highlighted three things: 1) the forest in the middle aridity (∼3–4.5) range are relatively more sensitive to changes in the short-term rainfall than the forest in lower (5) aridity regions, could be due to rapid depletion of relatively small soil water storage in between the storms, 2) the variable memory of forest to rain across the landscape can be an indicator of soil depth/rooting depth, and 3) the variable sized location specific antecedent rainfall windows can explain significant variability in forest growth status in asynchronous climates, thus these rainfall windows can be employed to forecast forest growth with a lead time (>4 months).

Until now, top-down estimation using the areal weighting interpolation method was applied to estimate the woody biomass energy potential for each of the 1741 municipalities in Japan. However, it was difficult to utilize the uncertain results in policy making. In contrast, bottom-up estimation can reflect the regional characteristics and provide novel benefits to policymakers. In this study, bottom-up estimation using the method of aggregation approach was carried out from the geospatial data for artificial forests, excluding protected forest, and considering forest growth. The data was collected from both national and each prefecture government. The forest growth of each forest division was adjusted by curve fitting and compared with statistical values to verify the estimation results. The woody biomass energy potential was defined as the amount of unused wood generated from harvesting to produce materials. In Japan, the total potential was 0.26–0.74 [EJ/year]. Comparing with the top-down estimation, these results were 34 % overestimated for the maximum value and 54 % underestimated for the minimum value. The detail results of geospatial distribution were statistically analyzed. Moran's I statistic was 0.68, and a hierarchical clustering with proportion resulted in the largest distribution with the majority of Japanese Ceder. [ABSTRACT FROM AUTHOR]

While there is consensus that fertilization with nitrogen (N) is a cost-effective way of increasing both forest biomass yield and timber harvest profitability, the strength and longevity of legacy effects are debated. To quantify legacy effects of past fertilization, we analysed 21 mixed Pinus sylvesteris and Picea abies stands. The stands, on average 23 years old at the time of this study, were either unfertilized (n=7), fertilized with 150 kg N ha−1 once 36 years ago (n=7), or twice, 45 and 36 years ago, respectively (n=7), during the previous stand rotation. We performed measurements on soil N mineralisation and N availability, forest growth, ground vegetation community composition, soil and vegetation C/N ratios and soil C and N stocks, many of which responded to legacy N fertilization earlier in stand development. Our results show that the legacy effects of fertilization during the previous stand rotation have diminished through time, indicating an eventual convergence of stand properties. Specifically, all significant effects present in the previous measurement period (over a decade ago), were weaker or completely absent in the current study (i.e. 36 years after fertilization and 23 years after initiation of the new stands). None-the-less, this indicates a longer legacy effect of N fertilization than what is normally considered and suggests that care should be taken to mitigate unwanted, long-term effects when utilizing N addition to promote tree growth in boreal forests. • Legacy effects of N applied during the previous stand rotation were analyzed. • No significant effects were present in soil, vegetation composition or forest growth. • The absence of responses contrasts previous analysis that occurred 10 years ago. • Diminishing effects indicates a convergence of stand properties after ca. 45 years. [ABSTRACT FROM AUTHOR]

Consistent knowledge about the increment in European forests gained amplified importance in European policies and decision processes related to forest-based bioeconomy, carbon sequestration, sustainable forest management and environmental changes. Until now, large-area increment information from European countries was lacking international comparability. In this study we present a harmonisation framework in accordance with the principles and the approach established for the harmonisation of National Forest Inventories (NFIs) in Europe. 11 European NFIs, representing a broad range of increment measurement and estimation methods, developed unified reference definitions and methods that were subsequently implemented to provide harmonised increment estimates by NUTS regions (Nomenclature of territorial units for statistics of the European Union), main forest types and tree species groups, and to rate the impact of harmonisation measures. The main emphasis was on gross annual increment (GAI), however, also annual natural losses (ANL) and net annual increment (NAI) were estimated. The data from the latest available NFI cycles were processed. The participating countries represent a forest area of about 130 million ha, and 82% of the European Unions' (EU) forest area, respectively. The increments were estimated in terms of volume (m³ year−1, m³ ha−1 year−1) and above-ground biomass (t year−1, t ha−1 year−1). The harmonised GAI volume estimates deviate in a range of +12.3% to −26.5% from the estimates according to the national definitions and estimation methods. Within the study area, the harmonised estimates show a considerable range over the NUTS regions for GAI, from 0.6 to 12.3 m³ ha−1 year−1, and 0.8–6.4 t ha−1 year−1, of volume and above-ground biomass, respectively. The largest increment estimates are found in Central Europe and gradually decrease towards the North, South, West and East. In most countries coniferous forests show larger increment estimates per hectare than broadleaved forests while mixed forests are at an intermediate level. However, in some instances, the differences were small or mixed forests revealed the largest increment estimates. The most important tree species groups in the study area are Pinus spp. and Picea spp., contributing 29% and 26% of the estimated total GAI volume, respectively. The shares of the prevalent broadleaved species are smaller with contributions of 9%, 7% and 6% by Quercus spp., Fagus sylvatica and Betula spp. The results underline the importance of harmonisation in international forest statistics. Looking ahead, harmonised large-area increment estimation is pivotal for accurate monitoring and evidence-based policy decisions in the changing context of future forest ecosystems dynamics, management strategies and wood availability. [Display omitted] • Increment estimation approaches differ among European NFIs. • Harmonisation framework developed for gross and net annual increment. • Common increment estimation method implemented by 10 European countries. • Harmonised increments estimated for NUTS regions, forest types and tree species. • Harmonised increments improve the comparability of international forest statistics. [ABSTRACT FROM AUTHOR]

The Full Carbon Accounting Model (FullCAM) is used by the Australian Government for international reporting of greenhouse gas emissions and to predict carbon stock changes for carbon abatement projects. It is also used by landowners, companies and researchers, and is therefore regularly applied at local to continental scales. FullCAM is a stand level model with daily, monthly or annual temporal resolutions, depending on the users' preference. FullCAM has been developed over the past 20 years, however, no studies have reviewed and described the current structure, parameters, calibration, and uses of FullCAM, which was the objective of this study. We also discuss the potential for further developments that could improve FullCAM's ability to model responses to disturbances and climate, while also increasing its local accuracy. • FullCAM simulates carbon follows between live biomass, standing dead, debris and soil. • FullCAM is used at local, regional and continental scales, and daily, monthly or annual steps. • FullCAM is used for native forests, woodlands and savannas, as well as plantations. [ABSTRACT FROM AUTHOR]

Continuous cover forestry (CCF) is forest management based on ecological principles and this management type is currently re-visited in many countries. CCF woodlands are known for their structural diversity in terms of tree size and species and forest planning in CCF needs to make room for multiple forest development pathways as opposed to only one management target. As forest management diversifies and management types such as CCF become more common, models used for projecting forest development need to have a generic and flexible bottom-up design. They also need to be able to handle uncertainty to a larger extent and more comprehensively than is necessary with single, traditional forest management types. In this study, a spatial tree model was designed for analyzing a data set involving 18 plots from CCF stands in Southern Finland. The tree model has specific ingrowth, growth and mortality model components, each including a spatially explicit competition effect involving neighboring trees. Approximations were presented that allow inference of the model components operating in annual steps based on time-series measurements from several years. We employed Bayesian methodology and posterior predictive distributions to simulate forest development for short- and long-term projections. The Bayesian approach allowed us to incorporate uncertainties related to model parameters in the projections, and we analyzed these uncertainties based on three scenarios: (1) known plot and tree level random effects, (2) known plot level random effects but unknown tree level random effects, and (3) unknown random effects. Our simulations revealed that uncertainties related to plot effects can be rather high, particularly when accumulated across many years whilst the length of the simulation step only had a minor effect. As the plot and tree effects are not known when tree models are applied in practice, in such cases, it may be possible to significantly improve model projections for a single plot by taking one-off individual-tree growth measurements from the plot and using them for calibrating the model. Random plot effects as used in our tree model are also a way of describing environmental conditions in CCF stands where other traditional descriptors based on stand height and stand age fail to be suitable any more. [Display omitted] • Spatially-explicit tree models can be used to project continuous cover forestry (CCF). • Bayesian methodology was employed to model uncertainties associated with projections. • Uncertainties were high if plot or stand effects were unknown. • Random plot effects can describe environmental conditions in CCF stands. • The length of simulation steps had a minor effect on the simulation results. [ABSTRACT FROM AUTHOR]

• A comprehensive sensitivity analysis was completed for the FullCAM model. • Carbon stock outputs were most sensitive to background mortality rates, age, site conditions, decomposition/turnover parameters and stand structure. • Model applications showed the importance of background mortality in relation to fire and harvesting. • Sensitivity of FullCAM outputs is very context dependent in relation to age and site conditions. • Implications for further developing FullCAM are discussed. In Australia, the Full Carbon Accounting Model (FullCAM) is used by the Australian Government for international reporting of greenhouse gas emissions and to predict carbon stock changes for carbon abatement projects. Consequently, over the last 20 years, it has been routinely applied at continental, regional and local scales, and has been subject to on-going development to improve its accuracy and representativeness. Given its importance, a sensitivity analysis could facilitate our understanding of model behaviour and aid the planning of future work and data collection. In particular, the sensitivity of a given model parameter is often context dependent such that it depends on the level of other parameters or variables. Key FullCAM parameters have generally been calibrated using data from empirical studies, with differing levels of confidence based on the sample size and data quality. The objective of this study was to apply a sensitivity analysis to examine (i) the sensitivity of FullCAM carbon stock outputs to its parameters and inputs, and how the sensitivity indices compare with the sample sizes used to calculate the respective parameters, (ii) the context dependency in terms of how the sensitivity varies with age, potential maximum biomass (a key FullCAM parameter), and disturbance severity or type, and (iii) to identify the implications for further development of FullCAM for woody vegetation systems. Of the 67 parameters tested, FullCAM carbon stock outputs were most sensitive to background mortality rates, age, potential maximum biomass, climate variability, age of maximum growth, decomposition or turnover parameters, and stand structure (regenerating or mature). The context dependency of the sensitivity analysis followed a consistent pattern depending on two main conditions, such that the sensitivity was higher when (i) the carbon stock was large and (ii) the parameter had a strong influence on that carbon stock. Several strong context dependencies occurred because the size of carbon stocks often vary through space and time within an ecosystem, and different processes (i.e. parameters) are more important at different times and locations. There was a strong context dependency in relation to age and potential maximum biomass, and FullCAM simulations indicated an interaction between fire disturbances and vegetation types. Lastly, background mortality was one of the least available inputs, but one to which FullCAM outputs were very sensitive. FullCAM was applied to show that the long-term contributions of low rates of background mortality to standing dead and debris C stocks were often as large as those from frequent (every 30 years) and intense harvesting and fire events because of the regular (annual) contribution of mortality and its accumulating influence of C stocks. [ABSTRACT FROM AUTHOR]

Secondary forests recovering after disturbances currently comprise about half of the world′s tropical forests. A better understanding of the recovery of species composition, stand structure, and biomass stocks of these secondary forests is critical for the sustainable management of these ecosystems. The main objective of this research was to develop the successional trends in forest biomass, tree diversity, and species composition recovery. We monitored the changes in tree species composition, stand structural characteristics, and biomass growth in a chronosequence of tropical secondary forests in the Yucatan Peninsula of Southeastern Mexico. We used both linear and non-linear regressions to develop biomass growth models during forest succession. We calculated tree species diversity and similitude indices between forest successional groups (young, medium-aged, and old-growth forests). The aboveground biomass stocks ranged from 5.2 to 121 Mg C ha-1, which increased gradually with forest age. We observed a divergent trend of biomass accumulation between soft- and densewood species during succession. The contribution of densewood species on tree biomass stock increased (from 32 % to 81 %) with the increasing forest ages. However, the tree diversity indices did not change significantly with forest age and were a poor predictor of aboveground biomass growth during succession. Secondary forests (SFs) of advanced age were more similar to old-growth forests (OF) in their species composition compared to young ones, as evidenced by the Chao-Jaccard index. However, it may take more than a century for these secondary forests to recover to OF-level species composition. Furthermore, the structural equation model allowed us to infer the relative importance of forest age, tree diversity, soil properties, and stand structural attributes, including wood density on biomass growth along the forest chronosequence. Forest age-mediated effect of species composition shift and stand structural changes was a better predictor of biomass accumulation than the changes in tree diversity or soil properties during succession. However, the soil properties as a construct (latent variable), had a significant positive covariance with stand structure, indirectly influencing biomass growth. These biomass and species composition recovery models could be useful in forest management for biodiversity conservation, landscape restoration, and ecosystem services, including carbon sequestration. • Divergent trends of biomass accumulation between soft- and densewood species during succession. • Secondary forests take more than 100 years to restore their original species composition and biomass stocks. • The tree diversity index was a poor predictor of aboveground biomass storage during succession. • Wood traits and stand structural properties predicted the change in biomass stocks. • Soil properties covaried positively with forest structure and composition, indirectly influencing biomass change. [ABSTRACT FROM AUTHOR]

• Long-term increase in forest growth in Finland mainly due to improved forest structure. • Environmental factors induced a significant share (20 – 31 %) of the growth increase. • The recent growth reduction mainly caused by environmental factors. After a rising trend for 1971 – 2013, during which the annual volume growth of the forests of Finland increased by more than 70 %, a recent reduction has been observed. We analyzed the development of annual growth in the forest of Finland, focusing on the component not explainable by changes in growing stock. The data originate from nine consecutive Finnish National Forest Inventories. In the data, diameter increments were measured from increment cores and tree height increments from standing sample trees in the field. We developed models predicting periodic (5 years) annual volume increment per hectare with properties of the trees and stands as predictor variables. Deviations from model-predicted values were interpreted to be induced by environmental variation. The development was analyzed for all tree species combined and separately for three species groups: Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.) and broadleaves. We observed a rising growth trend not solely explainable by increased growing stock. The species groups produced rather a similar pattern in different parts of Finland: from the 1960s to the mid-1990s, the observed volume increment was mainly below the model-predicted level, thereafter above it. During the current century, the difference between observed and predicted annual volume increment has shown a downward trend for Scots pine. For Norway spruce, the difference has continued to increase in southern Finland, but shows little change in the north. For broadleaved species, the difference between measured and predicted increment shows a recent increase as well, though not as large as for Norway spruce. The geographical pattern of the environment-induced increment component was described in more detail via maps using a 75 km × 75 km grid. The changing environment has enhanced forest productivity in Finland over a period of nearly six decades, but recent years have not been favorable for Scots pine, which represents 50 % of the growing stock volume of the forests of Finland. [ABSTRACT FROM AUTHOR]

• We fitted growth models suitable for both continuous cover and rotation forestry stands. • Sensitivity to climate was restricted by using only temperature sum. • Species-specific symmetric and asymmetric competition affected tree growth. Forest growth models employed in Fennoscandia have been generally targeted at rotation forestry (RF) stands, relying on age as a key predictor. Uneven aged, irregular stands, such as the ones managed with continuous cover forestry, are becoming of increasingly common. New models suited for all kind of management approaches (i.e., age-independent) have been developed in Fennoscandia. Although the ongoing climate change is projected to strongly affect tree growth in boreal regions, climatic variables included in current models are usually restricted to temperature sum averages with simple links. The objectives of our research were: 1) fitting a new age independent empirical tree basal area increment model (B2023) with inclusion of additional climatic variables for the main Nordic tree species (Norway spruce, Scots pine, and birches); 2) using independent data to validate both the new model and other two age-independent published empirical models (P2013, P2021); and 3) investigating the sensitivity of growth predictions of all the empirical models to climate change. Our results showed that the new model B2023 was as accurate as P2013 when independently validated. Both models performed well in different forest structures and management alternatives (namely rotation forestry, continuous cover forestry, two-storied stands, and old-growth natural forests), although with few differences, and on average slightly better than P2021. At plot level, the new model B2023 showed slight underprediction for the overstorey pine layer in continuous cover forestry and two-storied stands. The predicted climate change scenarios increased simulated growth in all models, although P2021 showed very high values for spruce. We failed to include additional climatic variables than temperature sum in B2023, thus not improving much its accuracy under historical data, nor its sensitivity to future climate. Concluding, the individual tree models here presented can be applied to a wide range of forest structures and managements in Fennoscandia. For long-term simulation scenarios, different approaches to improve the climate sensitivity of empirical, individual tree model should be explored. [ABSTRACT FROM AUTHOR]

• Soil organic carbon distribution in forests responded to external environmental factors. • Forest soil organic carbon distribution exhibited surface aggregation at multiple scales. • Forest growth and soil enzyme activity were important factors affecting soil organic carbon distribution. • The interaction of various environmental factors on soil organic carbon distribution showed a weakening trend. To investigate the effects of stand age and soil layer on the temporal and spatial distribution of soil organic carbon (SOC) in Cunninghamia lanceolata plantations, five experimental plots and 15 soil sampling sites were established in five stands of different ages (3, 6, 9, 15, and 25 years) in Huitong, Hunan Province. Tree diameter at breast height, tree height, canopy density and elevation in sample plots, and soil organic carbon concentrations (SOCC), soil enzyme activity, soil pH, and soil bulk density at 0–15, 15–30, 30–45 cm soil layers were measured during stand development. The change in SOC distribution with stand age and soil layer, and soil enzyme activity were investigated using ANOVA, LSD test, and inter-subject effect test and simulation analysis. The results showed that the SOC distribution in Cunninghamia lanceolata plantations had spatiotemporal heterogeneity and surface aggregation. The SOC increased with increasing stand age and decreased with increasing soil depth. Furthermore, SOCC and SOC density (SOCD) were strongly correlated with environmental factors; however, the interaction between forest growth and soil layer reduced the variation of SOC distribution. Forest growth and soil enzyme activity were important factors that affect the temporal and spatial distribution of SOC. Therefore, the management measures to promote the growth of the plantation and improve soil enzyme activity can enhance the SOC storage capacity from the angle of balancing ecological and economic benefits, and contribute to the achievement of the goal of "carbon neutrality". [ABSTRACT FROM AUTHOR]

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. [Display omitted] • Belowground carbon stocks (BSCs) have been revealed to be driven by biotic, abiotic, and functional variables. • Increasing salinity, gap fraction, and high saline zones negatively affect BSCs. • Nutrients, basal area, leaf area index, functional variables positively affect BSCs. • Structural diversity and canopy packing may indirectly benefit BSCs. [ABSTRACT FROM AUTHOR]

Climate change is an important factor affecting forest growth. Therefore, approaching the impacts of climate change on forest growth is of great significance to ameliorate this degraded land and push up forestry development. This paper initially probes the impacts of climate change on tree growth in Yellow River Delta region and responds of different tree species on the change. In this study, five species of 22-year-old trees were selected, and the tree biomass was measured by standard site methods and tree ring sampling to pursue the impacts of climate change on forest growth. Besides, growth models of the different tree species were established and verified using Robinia pseudoacacia as an example. The results showed: (1) In the Yellow River Delta, the most adapted tree species are Fraxinus chinensis and R. pseudoacacia. (2) Precipitation is the main meteorological factor affecting tree growth, while temperature and air pressure are also significantly correlated with tree growth. (3) Linear and power function models can simulate tree growth well. From the verification results, the modified R. pseudoacacia biomass is 294.54 t/ha, and the simulated biomass of the linear function model is close to the value. It is expected that the research not only provides a theoretical basis for forestry development in saline lands, but also helps to rehabilitate saline-alkali lands and cope with climate change. [ABSTRACT FROM AUTHOR]