Tree Size Diversity Research Articles

Tree size variation induced by stand age mainly regulates aboveground biomass across three major stands of temperate forests in South Korea

Forest biomass and biodiversity are the most important elements of forest functions and ecosystem services. In this study, we explore the possibilities and ways to enhance ecosystem functions and services related to biomass and biodiversity. Biotic drivers (i.e., species, phylogenetic and functional diversity, stand structural attributes, and community-weighted mean of trait values), abiotic drivers (i.e., topography and climate), and stand age were extracted as independent variables to explain aboveground biomass (AGB). Using South Korea’s 7th National Forest Inventory data, we analyzed 2,070 plots belonging to the natural forests consisting of 394 plots (19.0%) of coniferous stands, 829 plots (40.0%) of broadleaved stands, and 847 plots (40.9%) of mixed stands. Multimodel inference test and model-averaging approaches were conducted to determine the most significant control variables on AGB in each stand type, and piecewise structural equation modeling was conducted to quantify the relationships and directions between the variables. Abiotic drivers, including stand age and climate moisture index, control tree size variation in all stand types, but biotic drivers control AGB through different mechanisms depending on the stand type. Our results show that there were differences in the composition of variables for controlling AGB among stand types. Across all forest types and total stands, we found that increasing the tree size variation is the key driver of increasing AGB as stand age increases. Our study suggests that forest carbon accumulation by stand type can be enhanced if the key drivers of each stand type are properly managed across forest succession, and different forest management plans that consider different regulation factors among stand types are required. Moreover, it is important to adapt resource use patterns for each stand type with considering environmental conditions to maintain healthy and sustainable forests.

Climate and soil effects on tree species diversity and aboveground carbon patterns in semi-arid tree savannas

Climatic and edaphic effects are increasingly being discussed in the context of biodiversity-ecosystem functioning. Here we use data from West African semi-arid tree savannas and contrasting climatic conditions (lower vs. higher mean annual precipitation-MAP and mean annual temperature-MAT) to (1) determine how climate modulates the effects of species richness on aboveground carbon (AGC); (2) explore how species richness and AGC relate with soil variables in these contrasting climatic conditions; and (3) assess how climate and soil influence directly, and/or indirectly AGC through species richness and stand structural attributes such as tree density and size variation. We find that greater species richness is generally associated with higher AGC, but more strongly in areas with higher MAP, which also have greater stem density. There is a climate-related influence of soils on AGC, which decreases from lower to higher MAP conditions. Variance partitioning analyses and structural equation modelling show that, across all sites, MAP, relative to soils, has smaller effect on AGC, mediated by stand structural attributes whereas soil texture and fertility explain 14% of variations in AGC and influence AGC directly and indirectly via species richness and stand structural attributes. Our results highlight coordinated effects of climate and soils on AGC, which operated primarily via the mediation role of species diversity and stand structures.

Tree Species and Size Diversity of Akure Strict Nature Reserve, Nigeria

Tree Species and Size Diversity of Akure Strict Nature Reserve, Nigeria

Effects of forest structural and compositional change on forest microclimates across a gradient of disturbance severity

Forest structural diversity and community composition are key in regulating forest microclimates. When disturbance affects structural diversity or composition, forest microclimates may be altered due to changes in soil temperature, soil water content, and light availability. It is unclear however which structural or compositional components, when changed or to what extent, result in microclimatic change. To address this question, we used data from a large scale, manipulative stem-girdling experiment in northern, lower Michigan—the Forest Resilience and Threshold Experiment (FoRTE). FoRTE follows a factorial design with multiple levels of disturbance severity (0, 45, 65, 85%) based on targeted reductions in gross leaf area index via stem-girdling induced mortality. These disturbance severity treatments are applied in two ways: either as top-down (largest trees are killed) or bottom-up (small to medium trees killed) treatments. We examined how multiple components of structural diversity and community composition changed as a product of disturbance severity and type, and then tested for resulting effects on forest microclimates (light availability, soil temperature, and soil water), using a multivariate, Random Forest framework. We found that measures of community composition (species richness, species evenness, and Shannon-Wiener Diversity Index) and stand structure (basal area, standard deviation of DBH, tree size diversity) declined more following disturbance than did measures of canopy cover, heterogeneity, arrangement, or height. However, when changes in each variable from pre- to post-disturbance, measured as log change, were employed in a multivariate, Random Forest regression framework, structural diversity measures of heterogeneity (rugosity, top rugosity), cover (canopy cover), and arrangement (porosity) were the most influential variables, but with differences among bottom-up and top-down treatments We found that the death of large trees from disturbance impacts soil temperature, water, and light environments more substantially and uniformly across disturbance gradients than does the death of smaller trees. Our results have implications for both statistical and process-based modeling of forest disturbance.

Forest fragmentation and its associated edge-effects reduce tree species diversity, size, and structural diversity in Madagascar’s transitional forests

AbstractTropical forests are being cleared at an accelerating rate, despite being one of the most important habitats for global biodiversity. Many remaining tropical forest tracts are now highly degraded and fragmented, which presents a major problem for sensitive and threatened forest-dwelling species that depend on this habitat for survival. In this study, we assessed the impacts of forest fragmentation, and its associated edge-effects, on tree species diversity, tree size, and structural diversity within the transitional forests of north west Madagascar. Using data collected from 9,619 trees within 200 vegetation plots, we calculated species diversity indices, a range of dendrometry measurements, and Shannon-Weaver diversity indices of structure, which we compared among core and edge areas of a continuous forest and a fragmented forest. We found that species diversity, tree size, and structural diversity was significantly reduced in fragmented forest, and within forest edge areas in comparison to core, continuous forest. We also observed species diversity and structural diversity to be strongly influenced by the total size, core area size, and shape of forest fragments. Whilst we found fragmentation and edge-effects to individually impact tree species diversity, size and structural diversity, fragmentation and edge-effects are strongly correlated and affect natural forest synergistically. Our results provide evidence that forest fragmentation seriously degrades habitat quality and integrity of transitional forests, which is of great concern for the threatened species that inhabit them. Urgent conservation efforts are needed to halt ongoing forest fragmentation throughout the tropics, and reforestation and restoration efforts are required to reconnect isolated forest patches and to reduce forest edge area.

The influence of vegetation structure on sleeping site selection by chimpanzees (Pan troglodytes troglodytes).

Sleep is an important aspect of great ape life; these animals build sleeping platforms every night. In a community of chimpanzees, each subgroup selects a sleeping site where each individual builds a sleeping platform, mostly on a tree. Previous studies have measured the heights of sleeping platforms and sleeping trees to test the predation avoidance and thermoregulation hypotheses of sleeping site selection. However, it remains unclear how components of vegetation structure (vertical and horizontal) together determine the selection of sleeping sites by chimpanzees. Using botanical inventories around sleeping sites in a tropical rainforest of Cameroon, we found that chimpanzees preferentially sleep in trees measuring 40-50 cm in diameter. Regarding height, on average, sleeping trees measured 26 m and sleeping platforms were built at 16 m. To build sleeping platforms, chimpanzees preferred four tree species, which represent less than 3% of tree species in the study area. We demonstrate that the variation in abundance of tree species and the vertical and horizontal structure of the vegetation drive chimpanzee sleeping site selection. It was previously thought that preference for vegetation types was the driver of sleeping site selection in chimpanzees. However, results from this study indicate that the importance of vegetation types in sleeping site selection depends on their botanical characteristics including the variation in tree size, the abundance of all trees, the abundance of sleeping trees, and the occurrence of preferred sleeping tree species, which predict sleeping site selection. The height and diameter of trees are considered by chimpanzees when selecting a particular tree for sleeping and when selecting a site with a specific vertical structure. In addition to tree height, the abundance of smaller neighboring trees may also play a role in the chimpanzee antipredation strategy. Our results demonstrate that chimpanzees consider several vegetation parameters to establish sleeping sites.

Clustered tree size analysis of bio-productivity of Dinghushan National Nature Reserve in China

Over various terrain types, natural forests exhibit tree size and biomass variation. We started long- term research that consists of forest vegetation surveys in the Dinghushan National Nature Reserve to comprehensively investigate productivity based on the structure and species composition of China’s forest communities. We grouped the trees into three categories, i.e., as large or mature (DBH > 30 cm), medium-sized or growing (DBH 10–30 cm), and small-sized or regenerating seedlings (DBH < 10 cm). Forest data observations, i.e., species DBH, height, and biomass components (trunk, leaves, branches, above-ground dry weight, and below-ground dry weight) were recorded by use of standard protocols. All recorded observations were statistically analyzed by use of SPSS version 25. To comprehend the connections between the many elements of forest bio-productivity, linear regression analysis was utilized. Total above-ground biomass was 34.19 ± 5.75Kg/tree, but varied results were obtained when the forest was clustered based on DBH. Large-sized trees contributed an average of 2400.54 ± 510.4 kg/tree (93.24%), while medium-sized trees contributed 171.61 ± 25.06 kg/tree, and the least was regenerating seedlings which contributed 3.013 ± 0.07 kg/tree. There were positive linear relationships for all life forms between biomass and DHB, as well as DBH and height. The evergreen broadleaved shrubs were shorter in height (3.06 ± 0.99 m) than palm-leaved life forms (19.29 ± 5.39 m). Height influenced biomass accumulation and hence C gain, where life forms with tall stands had higher biomass. Generalized biomass estimation without clustering based on life forms or size class underestimates biomass components and hence lower C stocks for most forests worldwide. It’s also crucial to remember that trees with big DBH have tall, broad, well-lit crowns, which raise the primary productivity of forests and increase carbon storage. Besides natural disturbance (Typhoon) and climate change, it could be interesting to understand the relationship between soil resources such as nutrient and soil moisture content. These are factors that have direct impact on growth and biomass accumulation.

Two new methods applied to crown width additive models: a case study for three tree species in Northeastern China

Key messageThe non-linear seemingly unrelated regression mixed-effects model (NSURMEM) and generalized additive model (GAM) were applied for the first time in crown width (CW) additive models of larch (Larix gmelinii Rupr.), birch (Betula platyphylla Suk.), and poplar (Populus davidiana Dode). The crown radii in four directions (CR) exhibited different growth trends and responded differently to tree size and competition variables. In the absence of calibration, GAM was more accurate than NSURMEM for CR and CW predictions.ContextCrown radii in four directions (CR) and crown width (CW) are fundamental indicators used to describe tree crowns. The complexity of the CR growth in four directions of different tree species in natural forests is often ignored. There is logical additivity among CR and CW that is also often overlooked. Furthermore, the existing methods applied to CW additive models have some drawbacks.AimsWe aim to: (i) evaluate the utility of two new methods in developing CW additive models for larch (Larix gmelinii Rupr.), birch (Betula platyphylla Suk.), and poplar (Populus davidiana Dode) in natural secondary forests of Northeastern China; and (ii) explore the growth patterns of CR in four directions to gain important ecological insights.MethodsThe non-linear seemingly unrelated regression mixed-effects model (NSURMEM) and generalized additive model (GAM) were used to develop CW additive models and to explore crown growth patterns. The predictive ability of the additive models was evaluated using leave-one-plot-out cross-validation (LOOCV).ResultsAt a fair level without calibration, GAM provided slightly better results than NSURMEM. The response of the four CR to tree size and competition variables is different and may be non-uniform due to complex stand conditions and tree growth strategies.ConclusionThe newly provided methods applied to additive models are available for external datasets. GAM is recommended in the absence of calibration. This study has important implications for the understanding of natural forest dynamics and decision-making for critical stand management.

Basal area growth response of Scots pine to drainage: An analysis using a mixed-effects modelling approach

Wood production in peatland forests is often associated with management of site hydrology that aims to improve soil moisture status and stand growth. Silvicultural outcomes of ditching activities vary greatly among drained sites, therefore new data and modelling approaches are necessary for better understanding of forest growth dynamics on a tree-level and a long-term scale. A mixed-effects model estimating growth response to initial ditching performed 40 years ago in Ongassaare region (northeast Estonia) was developed using basal area increment data derived from ring-width series of 287 Scots pine trees from 39 stands. The model indicated that ditching response was up to around 800 mm2 year−1 on average; this level of drainage-induced additional increment was reached 16 years after treatment. Pre-drainage tree diameter, mean stand diameter and radial growth rate were among the significant predictors, therefore the results suggest that tree size, stand growing stock and site quality or microsite conditions before the ditching are affecting post-drainage tree growth. Smaller trees experienced greater growth response; however larger trees responded to the treatment faster than smaller ones. Ditching therefore induced changes in stand structure by decreasing tree size variation. Ditching response was more pronounced in stands with smaller pre-drainage diameter, faster growing trees reached the maximum response values quicker. Trees closer to the drainage ditch responded slightly more intensively to changing site conditions, however, this relationship was significant in the case of a reference ditch (one of the ditches surrounding a forest stand, selected according to the topography of the landscape) but not the nearest one. Drained peatlands are very diverse in terms of pre-treatment site conditions, stand history and ditch network design, therefore additional data from extended network of sample plots would be necessary for updating the developed model to make it more applicable for further use (e.g., predicting forest growth and yield).

Acacia canopy structure and carbon stock in Ba Vi, Vietnam

Forest structure is a key component of its management and assessment in every forest ecosystem. In the study, 23 plots were established to obtain data on the acacia forest community based on tree size. Results from the study indicated that the acacia community could be broadly divided into two groups based on tree-size variables. The diameter and height frequency distributions of Group 1 were right-skewed, while those of Group 2 were more complicated. In both groups, there were positive correlations between tree-size variables, nonetheless the relationship between diameter at breast height and total height was best described using the cubic equation. Further, the Weibull and Sinh-Arcsinh (SHASH) best simulated the diameter and height frequency distribution. High-quality trees were found in a large diameter (> 30 cm) and height groups (> 22 m). In contrast, low-quality plants often concentrated on the smallest sizes. Therefore, trees with a diameter of 2–10 cm and a height lower than 8 m should receive attention to tend. Carbon stock in the two groups was 61.48 Mg·ha–1 and 64.21 Mg·ha–1, respectively. Tending solutions and measurements should be carried out regularly to promptly propose silvicultural measures and improve forest quality in future.

Environmental, structural, and taxonomic diversity factors drive aboveground carbon stocks in semi‐deciduous tropical rainforest strata in Cameroon

AbstractForest stratification plays a crucial role in the interception of light and plants' photosynthetic activities. However, there is still a lack of information on the contribution of tropical forest stratification to its functioning, despite the increasing number of studies. Here, we analysed from a perspective of the whole tree community (WTC) and forest strata (i.e., large trees, understory trees, and small stems), the relationship between abiotic, biotic factors and aboveground Carbon (AGC). The abiotic factors‐AGC relationships were positive for all strata and WTC. However, soil factors‐AGC relationship was stronger for small stems and understorey, while topography factor‐AGC relationship was stronger for large trees and WTC. Tree size inequality‐AGC relationship was positive and much stronger for WTC, large trees and small stems. In addition, a species diversity‐AGC relationship was found positive only for large trees and WTC. These results highlight the niche complementarity effect for driving positive relationships of species diversity and individual tree size variation with aboveground biomass at large tree strata and WTC. The lack of positive effect of species diversity on AGC for understorey and small stems strata might be attributable to the selection effect or resource complementarity among species.

Developing and Comparing Individual Tree Growth Models of Major Coniferous Species in South Korea Based on Stem Analysis Data

Tree growth in Korean red pine (Pinus densiflora, hereafter Pd), Korean white pine (Pinus koraiensis, hereafter Pk), and Japanese larch (Larix kaempferi, hereafter Lk) was modeled using Logistic, Korf, Gompertz, Chapman-Richards, and Weibull equations and stem analysis data from sample trees: 38 trees for Pd, 46 trees for Pk, and 45 trees for Lk. The models were fitted to the total increment of tree size variables, diameter at breast height (DBH), height, basal area, and stem volume, as a function of age. After selecting the best-fit growth function, the current annual increment (CAI) and mean annual increment (MAI) were compared for each variable by species. The optimal growth functions were Chapman-Richards for DBH and stem volume, Korf for height, and Gompertz for basal area. The parameter estimates in the final models were all significant (p < 0.01) with best-fit statistics and unbiased residual plots. When plotted with observed values, the growth patterns of each variable were represented properly. The predicted growth curves over age were concave with respect to the Y-axis in DBH and height but lightly convex in basal area, and explicitly convex in stem volume, whereas an asymptote of sigmoid curve in stem volume was not apparent until 100 years. Age with the maximum MAI among variables was arranged similarly to CAI; the age with maximum MAI was earliest for DBH and latest for volume. The maximum growth was achieved earliest in Lk, followed by Pk and Pd. The developed models were able to predict tree size variables and serve as a reference to understand growth characteristics by species.

Allometric relationships among tree-size variables under tropical forest stages in Gia Lai, Vietnam

Allometric models play an undeniable role for estimating hard-to-measure quantities such as volume, biomass and carbon stock in forests. However, so far there has been limited model development for native forests in Vietnam. Therefore, this study was conducted to build and analyze the effectiveness of nonlinear and mixed models for secondary and old-growth forests in Gia Lai, Vietnam. The study measured diameter at breast height, total height, commercial height and crown width of forest trees in 20 plots (10 plots for each forest stage). The results showed that diameter had the strongest relationship with height. In the secondary forest, the Power, Korf and Ratskowky models were the best for pairs of variables, while Prodan, Weibull and Power models were the best fit in the old-growth forest. The nonlinear mixed-effect models were better than classic nonlinear models in both forest stages. Fixed and mixed models developed in this study are very valuable for estimating difficult-to-measure quantities and contribute to effective forest management in the study region.

Age-independent diameter increment models for mixed mountain forests

Mixed mountain forests with an uneven-aged structure are characterized by a high tree-growth variability making traditional age-dependent growth models inapplicable. Estimating site productivity is yet another impediment for modelling tree growth in such forests. Uneven-aged mixed-stand forests are known for their high resilience, resistance and productivity, and are being promoted as a suitable alternative to even-aged, pure plantations for climate change adaptation and mitigation. However, their growth must be accurately measured and predicted, but diameter at the breast height (dbh) increment models specifically designed for uneven-aged mixed mountain forests are still rare. Using permanent sampling network data and 465 increment cores, we built two age-independent dbh increment ({i}_{d}) models for the main species of the study area, namely Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.) and European beech (Fagus sylvatica L.). Mixed effects models and the algebraic difference approach were employed to develop {i}_{d} models based on empirical and commonly used theoretical growth functions. A past growth index was further developed and introduced in the model in order to explain the {i}_{d} variability. Several mixed effects calibration strategies were assessed in order to obtain the most accurate localized curve for new plots. Tree size, competition and biogeoclimatic variables were found to explain the {i}_{d} through the empirical growth function, while the growth index significantly improved the theoretical growth function for Norway spruce. The optimization of the calibration strategy for the mixed effects modelling framework enables the growth index implementation in forest practice as an accurate method for estimating site productivity. The accuracy of the two {i}_{d} models was similar: the root mean squared error of the empirical growth function varied between 0.940 and 1.042 cm for spruce, beech and fir, while the root mean squared error obtained through the theoretical growth function for spruce only was 1.105 cm. The basal area increment prediction at the plot level based on the theoretical growth function reached a root mean squared error of 0.043 m2 while using the empirical growth function the root mean squared error is 0.047 m2. The high accuracy obtained using age-independent models underlines their suitability for predicting growth in mixed uneven-aged forests. The developed models can be easily integrated into forest practice to accurately obtain {i}_{d} estimates.

Size‐dependent intraspecific variation in wood traits has little impact on aboveground carbon estimates in a tropical forest landscape

Abstract There is increasing evidence that intraspecific trait variation plays a role in governing rates of ecosystem functioning. While wood traits such as wood specific gravity (WSG) and wood carbon concentration (WCC) are key drivers of forest aboveground carbon (AGC) stocks, the sources of intraspecific variation in these wood traits and the consequences of this variation on AGC are poorly known, especially in the tropics. Here, we investigated intraspecific variation in wood specific gravity (WSG) and wood carbon concentration (WCC) from 556 individual trees belonging to 15 species that well characterize different successional stages of seasonal evergreen forests in Southeast Asia. Specifically, we tested the contribution of individual or species characteristics (tree size, growth rate and regeneration guilds) and local environmental conditions (topographic wetness index and successional stages) to intraspecific variation in WSG and WCC, and assessed the consequences of intraspecific variation in these wood traits on AGC estimates in 14 permanent forest plots established along a successional gradient in Khao Yai National park, Thailand. We found that tree size was the main driver of intraspecific variation in WSG and WCC as tree sizes increased from 10–100 cm in diameter, WSG increased by 7.3%, while WCC increased by 2.4% in heartwood, 1.6% and 2.7% in sapwood without and with volatile carbon included. There was no effect of the topographic wetness and other local environment condition in wood traits led to a slight overestimation of AGC in young secondary forests (+0.09% to +1.29%) and a small underestimation in older forests (−0.86% to −2.87%), but overall AGC estimates (13 of 14 forest plots) remained within error margins (the 95% interval). Our study provides evidence that tree size variation translates into intraspecific variability in wood traits, whereas local environmental conditions related to topography successional stages had no effect on wood trait variability. While size‐dependent variation in WSG and WCC have largely been undocumented and thus ignored in forest carbon assessment approaches, we highlight that it has a limited impact on AGC estimates, indicating that it does not invalidate current forest carbon stock estimation approaches. Read the free Plain Language Summary for this article on the Journal blog.

The effect of plant–plant interactions as a key biotic process mediating the spatial variation of phenotypes in a Pinus sylvestris forest

Key messageIn this work, we highlighted the importance of the phenotypic structure of forest in regulating inter-tree competition with scattered individuals showing larger growth than close neighbours, with lower growth rates.Plant interactions are among the fundamental processes shaping the structure and functioning of ecosystems as they modulate competitive dynamics. However, the connection between the response of individual growth to neighbours and to environmental conditions and the mechanisms determining interactions in monospecific stands remain poorly understood. Here, we followed a phenotypic-based approach to disentangle the effect of plant size, neighbourhood interactions and microhabitat effects on Pinus sylvestris growth and traits, as well as their spatial variation of growth. We mapped all adult trees (1002 pines) in a 2 ha stand and measured their height, DBH and crown projection. For each individual, we assessed its growth and a competition index in relation to the closest neighbours. Soil chemical and physical properties and ground cover were also measured in a grid within the stand. We analysed the effects of tree size, neighbour competition and microhabitat variation on tree growth with a linear model. We also used spatial mark-correlation functions to explore the spatial dependence of tree age, secondary growth and phenotypic traits. Our results showed that trees with close neighbours displayed lower growth rates, whilst individuals with larger growths appeared scattered throughout the stand. Moreover, we found that growth depended on competition, tree height and crown area while tree growth poorly correlated with age or microhabitat conditions. Our findings highlight the importance of forest structure, in regulating inter-tree competition and growth in a Mediterranean pure stand and they provide insight into the causes and consequences of intraspecific variation in this system.

Development of Mixed-Effects Individual-Tree Diameter Increment Model for Casuarina Equisetifolia Considering the Effects of Tree-Size Diversity, Tree Density Reduction, and Climate

ABSTRACT Based on the data provided by the 6th (1998), 7th (2003), and 8th (2008) National Forest Inventory (NFI) in Hainan Province, southern China, we developed an individual-tree diameter increment model considering tree-size diversity, tree density reduction, and climate for Casuarina equisetifolia. Since the data was longitudinal and had a nested structure, we used a linear mixed-effects approach to construct the mixed-effects model based on sample plot effects. And we applied the method of 10-fold cross-validation to test the basic model without random effects and final mixed-effects model. The results indicate that natural logarithm of initial DBH (logDBH), sum of basal area of trees larger than objective tree (BAL), soil thickness (ST), Gini coefficient of DBH diversity for residual trees (GCres), and mean coolest month temperature (MCMT) had significant impact on the individual-tree diameter increment for Casuarina equisetifolia. Comparing with basic model, the final mixed-effects model performance was greatly improved. In the model validation, the mixed-effects model also showed a better fitting goodness. The individual-tree diameter increment models of Casuarina equisetifolia developed in this study will provide a good basis for estimating and predicting growth of Casuarina equisetifolia forests over larger areas.

Topography, Diversity, and Forest Structure Attributes Drive Aboveground Carbon Storage in Different Forest Types in Northeast China

Forests regulate air quality and respond to climate change by storing carbon. Assessing the driving factors of forest aboveground carbon (AGC) storage is of great importance for forest management. We assumed that different forest types would affect the relationship between species richness, stand density, individual tree size variation, and AGC. In order to test and verify it, we analyzed the inventory data of 206 fixed plots (20 m × 20 m) of Jingouling Forest Farm, taking advantage of the piecewise structural equation model (pSEM) to explore the effects of species diversity, stand structure attributes, and topography on the AGC storage in the Wangqing Forest in Jilin Province. In addition, in this study, we aimed to investigate whether the fixed factors (species diversity, stand structure attributes, and topography) influenced AGC storage more significantly than the random factor (forest type). According to the results of pSEM, the selected factors jointly explain the impact on 33% of AGC storage. The relationship between stand density and AGC is positive, and the impact of individual tree size variation on AGC storage is negative. Species richness has direct and indirect impacts on AGC storage, and the indirect impact is more significant through individual tree size variation. Both elevation and slope are significantly negatively associated with AGC storage. Forest type explains the impact on 12% of AGC storage, which means the relationship between AGC and predictors varies across forest types. The results provide a scientific basis for the protection and management decision of natural forests in northeastern China.

Tree spatial pattern and mortality prediction in burned patches of Dahurian larch (

Background Fire-caused tree mortality and spatial pattern are crucial for evaluating forest dynamics and developing management prescriptions. Aims We investigated direct fire effects on spatial distribution and mortality of Dahurian larch (Larix gmelinii Rupr.) and assessed the Ryan and Amman (R–A) model performance and the importance of immediate mortality predictors. Methods We analysed spatial patterns of fire-killed and surviving trees of three size classes in plots that burned at low- to high-severity using pair-correlation functions and tree mortality with the R–A model and generalised linear mixed models. Key results The mixed-severity fire caused strong density-dependent mortality and more aggregated surviving tree patterns at short distances. The R–A model generally performed acceptably, and crown scorch and bole char height were critical predictors determining post-fire tree mortality. Conclusions Fire-caused tree mortality and spatial patterns are controlled primarily by spatial variation in tree size and biological and structural characteristics. The prediction biases of the R–A model arose primarily from the intrinsic traits of Dahurian larch and the imbalanced dataset. Fine-scale neighbourhood density might be a fundamental priority for fire management and restoration. Implications This study could possibly improve mechanistic understanding of spatial pattern development and tree mortality in similar fire-prone conifer forests.

Two-level optimization approach to tree-level forest planning

Laser scanning and individual-tree detection are used increasingly in forest inventories. As a consequence, methods that optimize forest management at the level of individual trees will be gradually developed and adopted. The current study proposed a hierarchical two-level optimization method for tree-level planning where the cutting years are optimized at the higher level. The lower-level optimization allocates the trees to the cutting events in an optimal way. The higher-level optimization employed differential evolution whereas the lower-level problem was solved with the simulated annealing metaheuristic. The method was demonstrated with a 30 ​m ​× ​30 ​m sample plot of planted Larix olgensis . The baseline case maximized the net present value as the only management objective. The solution suggested heavy thinning from above and a rotation length of 62 years. The baseline problem was enhanced to mixed stands where species diversity was used as another management objective. The method was also demonstrated in a problem that considered the complexity of stand structure, in addition to net present value. The objective variables that were used to measure complexity were the Shannon index (species diversity), Gini index (tree size diversity), and the index of Clark and Evans, which was used to describe the spatial distribution of trees. The article also presents a method to include natural advance regeneration in the optimization problem and optimize the parameters of simulated annealing simultaneously with the cutting years. The study showed that optimization approaches developed for forest-level planning can be adapted to problems where treatment prescriptions are required for individual trees.