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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]

Whether and how the timing of extreme events affects the direction and magnitude of legacy effects on tree growth is poorly understood. In this study, we use a global database of Ring-Width Index (RWI) from 2,500 sites to examine the impact and legacy effects (the departure of observed RWI from expected RWI) of extreme drought events during 1948-2008, with a particular focus on the influence of drought timing. We assessed the recovery of stem radial growth in the years following severe drought events with separate groupings designed to characterize the timing of the drought. We found that legacies from extreme droughts during the dry season (DS droughts) lasted longer and had larger impacts in each of the 3 years post drought than those from extreme droughts during the wet season (WS droughts). At the global scale, the average integrated legacy from DS droughts (0.18) was about nine times that from WS droughts (0.02). Site-level comparisons also suggest stronger negative impacts or weaker positive impacts of DS droughts on tree growth than WS droughts. Our results, therefore, highlight that the timing of drought is a crucial factor determining drought impacts on tree recovery. Further increases in baseline aridity could therefore exacerbate the impact of punctuated droughts on terrestrial ecosystems.

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).

As climate change makes many traditional empirical growth approaches not functional for forest dynamics modelling, new climate-sensitive models are needed. However, using these newly developed models for extrapolation, such as predicting forest productivity for new areas or future scenarios is still a difficult task. In this study, we proposed a method for delimiting the uncertainty of climate-sensitive extrapolations of forest productivity (site index, SI) using the regularisation approach implicit in distance-based Support Vector Regression. As a case study, we predicted forest productivity with a dataset of 165 permanent research plots of radiata pine forests in Galicia (NW of Spain) as a function of bioclimatic variables from the Worldclim 2 raster datasets. The developed model was based on the radial basis kernel and, after calibrating it using cross-validation, produced adequate performance metrics, explaining up to 56% of the site index’ variability. Then, we predicted forest productivity for the Galician territory basing on climate raster maps for current conditions and six future scenarios (using different Global Climate Models) and evaluated the resulting maps by delimiting the surfaces with predictions strongly regressed to the mean. This analysis revealed that the extrapolations for unseen climatic conditions were extremely regularised, even for current climate, being 60–99% of the territory regressed to the observational site index mean. In other words, the validity area delimited for the fitted model was narrow in comparison with the prediction extent. These results imply that the climatic conditions in these areas/scenarios were too different from the training datastet for making reliable predictions, at least under the optimum model setup defined by cross-validation. However, when we reduced the σ parameter, responsible for controlling distance-based regularisation, we observed a noticeable increase in validity area of the model, together with a drop in performance. This fact revealed the existence of a trade–off between highly specific models, with high performance and a small applicability area, and more generalisable models, with a broad validity area but lower performance. We concluded that the tested methodology could be a useful starting point for assessing the spatio-temporal uncertainty of forest productivity predictions in the future.

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]

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

Abstract To facilitate forest research, simulations of the whole forest growth process can be employed to analyze forest dynamics and predict forest yields. Different forest growth models can be integrated for comprehensive process simulation and thus can assist forest growth research. With the development of network technologies, a web environment can provide cross‐platform capability and wide availability for distributed researchers. In order to serve the simulation of complex forest growth processes and help online forest growth research, this article proposes a web‐based integrated modeling and simulation method for forest growth research. The proposed method includes three steps, namely, model preparation, model integration, and forest growth simulation. The corresponding implementation strategies are designed to prepare forest growth models, integrate different models, preprocess model data, and implement forest growth simulations for integrated modeling and simulations via the web. Two applications in the comprehensive prediction of forest growth and comparison of different forest management decisions are introduced to verify the feasibility and capability of the proposed method. The results show that the proposed web‐based integrated modeling and simulation method can be used conveniently for comprehensive simulations of forest growth research.

Abstract Background There is a serious lack of experience regarding the productive potential of the natural forests in northeastern China, which severely limits the development of sustainable forest management strategies for this most important forest region in China. Accordingly, the objective of this study is to develop a first comprehensive system for estimating the wood production for the five dominant forest types. Methods Based on a network of 384 field plots and using the state-space approach, we develop a system of dynamic stand models, for each of the five main forest types. Four models were developed and evaluated, including a base model and three extended models which include the effects of dominant height and climate variables. The four models were fitted, and their predictive strengths were tested, using the “seemingly unrelated regression” (SUR) technique. Results All three of the extended models increased the accuracy of the predictions at varying degrees for the five major natural forest types of northeastern China. The inclusion of dominant height and two climate factors (precipitation and temperature) in the base model resulted in the best performance for all the forest types. On average, the root mean square values were reduced by 13.0% when compared with the base model. Conclusion Both dominant height and climate factors were important variables in estimating forest production. This study not only presents a new method for estimating forest production for a large region, but also explains regional differences in the effect of site productivity and climate.

Forests in the Philippines, and many other developing countries in the tropics, have been extensively cleared over recent decades. There have been increasing efforts to reforest these cleared lands to achieve both socio-economic and environmental objectives. To date, planted forests have been dominated by monocultures. There has however been increasing calls to use mixtures of species, although there is limited evidence to support mixed-species plantations being a better or win-win approach to reforestation. To address this, we compared the tree growth, forest structure, and tree species diversity performance of monoculture and mixed-species tree plantations across 168 sites (251 survey plots) on Leyte Island, the Philippines. Our results indicate that mixtures of fast-growing exotics species had better growth performance compared to monocultures of fast-growing exotics species, and also better tree species diversity performance at both the plot and landscape scale. Our results suggest that mixtures of exotic or native species can provide benefits over monoculture plantations. Mixtures of productive exotic species are most suited to situations where the production function of the forest is most important, while mixtures of native species are most suited to situations where the biodiversity function of the forest is most important. [ABSTRACT FROM AUTHOR]

Models to predict the emissions of biogenic volatile organic compounds (BVOCs) from terrestrial vegetation largely use standardised emission potentials derived from shoot enclosure measurements of mature foliage. In these models, the potential of new foliage to emit BVOCs is assumed to be similar, or up to twice as high, as that of mature foliage, and thus new conifers foliage is predicted to have a negligible to minor contribution to canopy BVOC emissions during spring time due to the small foliage mass of emerging and growing needles. Extensive observations have, however, recently demonstrated that the potential of new Scots pine needles to emit several different BVOCs can be up to about 500 times higher than that of the corresponding mature foliage. Thus, we build on these discoveries and investigate the potential impact of considering these enhanced emissions from new Scots pine foliage on estimates of monoterpene emissions and new atmospheric aerosol particle formation and their subsequent growth. We show that the importance of taking the enhanced monoterpene emission potential of new Scots pine foliage into account decreases as a function of season, tree age and latitude, and that new foliage could be responsible for the majority of the whole tree's foliage emissions of monoterpenes during spring time, independently of tree age and location. Our results suggest that annual monoterpene emission estimates from Finland would increase with up to ~25% if the enhanced emissions from new Scots pine foliage were also considered, with the majority being emitted during spring time where also new particle formation has been observed to occur most frequently. We estimate that our findings can lead to increases in predictions of the formation rates of 2 nm particles during spring time by ~75–280% in northern Finland and by ~130–870% in southern Finland. Likewise, simulated growth rates of 2–3 nm particles would increase by ~65–180% in northern Finland and by ~110–520% in southern Finland if the enhanced emissions of monoterpenes from new Scots pine foliage were explicitly considered. Since only one measurement study (Aalto et al., 2014), on which our work builds, has so far found highly pronounced emissions of monoterpenes from new Scots pine foliage compared to those of mature, we conclude that more spring time measurements of new conifers foliage are required for improving emission algorithms in biogenic emission models.

Abstract Background Forest management decisions are based on expectations of future developments. For sound decisions it is essential to accurately predict the expected values in future developments and to account for their inherent uncertainty, for example the impact of climate change on forests. Changing climatic conditions affect forest productivity and alter the risk profile of forests and forest enterprises. Intensifying drought stress is seen as one major risk factor threatening forest management in the north German lowlands. Drought stress reduces tree growth and vitality and might even trigger mortality. But so far, it is not possible to quantify effects of a persistent dryer climate on forest productivity at a level suitable for forest management. Methods We apply a well-established single-tree forest growth simulator to quantify the effect of persistent dryer climates on future forest productivity. We analyse the growth of Scots pine (Pinus sylvestris L.), European beech (Fagus sylvatica L.) and oak (Quercus robur L. and Quercus petraea (Matt.) Liebl.) in two forest regions in the north German lowlands for a time interval of 60 years until 2070. The growth response under three different climate projections is compared to a baseline scenario. Results The results show clear differences in volume increment to persistent dryer climates between tree species. The findings exhibit regional differences and temporal trends. While mean annual increment at biological rotation age of Scots pine and oak predominantly benefits from the projected climate conditions until 2070, beech might suffer losses of up to 3 m3·ha–1·yr–1 depending on climate scenario and region. However, in the projection period 2051 to 2070 the uncertainty ranges comprise positive as well as negative climatic effects for all species. Conclusions The projected changes in forest growth serve as quantitative contributions to provide decision support in the evaluation of, for example, species future site suitability and timber supply assessments. The analysis of productivity changes under persistent dryer climate complements the drought vulnerability assessment which is applied in practical forestry in northwestern Germany today. The projected species’ productivity has strong implications for forest management and the inherent uncertainty needs to be accounted for.

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

Taking the "One Million-Mu (666 km2)" Plain Afforestation (Phase I) Project (Phase I afforestation) in Beijing city as an example, we monitored the growth status of planted forest using long-term remote sensing images, and evaluated the impacts of afforestation on land use change and vegetation growth. We found there is a large space for improvement regarding the ecological benefits of the project. Moreover, we found forest patches with decreasing greenness after the afforestation were mainly converted from farmland with high greenness and low heterogeneity in terms of the normalized difference vegetation index (NDVI). This implies that those farmland patches are inappropriate for afforestation. According to the results from Phase I afforestation and the impact of urbanization on green space, we constructed a series of spatial variables and generated a suitability map for the next "New Round of One Million-Mu (666 km2) Afforestation project" (Phase II afforestation). We then modeled the spatial distribution of Phase II afforestation based on the derived suitability map. This study is crucial for the scientific evaluation of afforestation projects for space planning (e.g., urban green space planning). The evaluation and modeling framework built in this study can be used to support the decision making and policy implementation of afforestation projects in China. [ABSTRACT FROM AUTHOR]

Keywords: climate change; forest vulnerability; forest dynamics; forest growth; drought mortality EN climate change forest vulnerability forest dynamics forest growth drought mortality 1 4 4 06/10/20 20200605 NES 200605 In recent decades, forest, vulnerability to climate change is rapidly increasing worldwide; forest dieback episodes have been recorded in all biomes (Allen et al., [2]; Adams et al., [1]). Networking also across disciplines and communities would be highly welcome to achieve an in-depth understanding of forest functioning through the whole soil-plant-atmosphere pathway allowing for predictions on forest destiny and ES under various climate change scenarios. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. Climate change, forest vulnerability, forest dynamics, forest growth, drought mortality. [Extracted from the article]

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

Forests play a critical role in mitigating climate change, and, at the same time, are predicted to experience large-scale impacts of climate change that will affect the efficiency of forests in mitigation efforts. Projections of future carbon sequestration potential typically do not account for the changing economic costs of timber and agricultural production and land use change. We integrated a dynamic forward-looking economic optimization model of global land use with results from a dynamic global vegetation model and meta-analysis of climate impacts on crop yields to project future carbon sequestration in forests. We find that the direct impacts of climate change on forests, represented by changes in dieback and forest growth, and indirect effects due to lost crop productivity, together result in a net gain of 17 Gt C in aboveground forest carbon storage from 2000 to 2100. Increases in climate-driven forest growth rates will result in an 81%–99% reduction in costs of reaching a range of global forest carbon stock targets in 2100, while the increases in dieback rates are projected to raise the costs by 57%–132%. When combined, these two direct impacts are expected to reduce the global costs of climate change mitigation in forests by more than 70%. Inclusion of the third, indirect impact of climate change on forests through reduction in crop yields, and the resulting expansion of cropland, raises the costs by 11%–38% and widens the uncertainty range. While we cannot rule out the possibility of climate change increasing mitigation costs, the central outcomes of the simultaneous impacts of climate change on forests and agriculture are 64%–86% reductions in the mitigation costs. Overall, the results suggest that concerns about climate driven dieback in forests should not inhibit the ambitions of policy makers in expanding forest-based climate solutions.

We used a 10-year record of the CO2 flux by an old growth boreal forest in central Manitoba (the Northern Old Black Spruce Site (NOBS)), a ∼150-year-old Picea mariana [Mill.] stand) to determine whether and how whole-forest CO2 flux is related to tree ring width. We compared a 37-year ring width chronology collected at NOBS to a second chronology that was collected at a nearby Black Spruce stand with a different disturbance history, and also to three measures of annual whole-forest photosynthesis [gross ecosystem production (GEP)], two measures of annual respiration (R), and one measure of annual carbon balance [net ecosystem production (NEP)]. The year-to-year ring width fluctuations were well correlated between the two sites; increasing our confidence in the NOBS chronology and implying that ring width variation is driven and synchronized by the physical environment. Both chronologies exhibited serial correlation, with a fluctuation in ring width that had an apparent periodicity of ∼7 years. Neither chronology was correlated with variation in annual precipitation or temperature. Ring width and NEP increased, while R decreased from 1995 to 2004. GEP either remained constant or decreased from 1995 to 2004, depending on which measure was considered. The lack of relationship between ring width and GEP may indicate that ring growth is controlled almost entirely by something other than carbon uptake. Alternative explanations for the ring width chronologies include the possibility that wood production varies as a result of shifts in respiration, or that an unidentified aspect of the environment, rather than the balance between GEP and respiration, controls wood production. The serial correlation in ring width may be related to increases and decreases in carbohydrate pools, or to gradual changes in nutrient availability, pathogens, herbivores, soil frost or soil water table. The cause or causes of serial correlation, and the controls on the allocation of photosynthate to wood production, emerge as critical uncertainties for efforts in predicting the carbon balance of boreal ecosystems and inferring past climate from tree rings. © 2006 Blackwell Publishing Ltd.