Tree Species Groups Research Articles

Research Note: Multi-Algorithm-Based urban tree information extraction and Its applications in urban planning

Urban trees provide several vital social and environmental services. Within the field of urban planning, tree information is currently usually obtained through expensive and time-consuming fieldwork. This research presents a multi-algorithm methodology that extracts urban tree information, including tree location, absolute height, crown perimeter, and species (group) from airborne laser scanning (ALS) datasets and high-resolution aerial images. We first determine the location of trees from the ALS dataset. After a filtration step removing the erroneous tree locations, we simulate each location’s canopy based on aerial imagery. Finally, we utilize the extracted canopy images to perform tree species classification with deep learning. The validation assessment showed overall good credibility (>70 %) in urban areas and better performance (90 %) in street areas. Compared to other methods that require additional information collection, our methodology uses common data in city databases, enabling cities to collect and update large-scale tree information in a fast manner and supporting decision-makers with important information on understanding the value of urban green under the context of ecosystem services, urban heat islands, and CO2 mitigations.

Japanese Oak Wilt Disease decreased survival probability and mean lifetime of tree populations in a secondary natural forest

ABSTRACT The purpose of this study was to assess the effects of Japanese Oak Wilt Disease on mortality in a tree population. The study site was the permanent plot of 0.26 ha established in the secondary forest dominated by Abies firma, Tsuga sieboldii and Quercus serrata at the University of Tokyo Chiba Forest in the southeastern part of the Boso peninsula, Japan. We set the two observation periods of 1999–2008 and 2009–2021, and Japanese Oak Wilt Disease invaded the study site in the middle of the second period. We collected tree age data for both alive and dead trees in the two periods based on semi-nondestructive drilling measurements for trees using a RESISTOGRAPH. Survival analyses were conducted on the second-period data, and the demographic metrics such as mortality ratios and mean lifetimes were compared between the two periods. The results showed that: the mortality ratio of the tree population at old ages, where oaks (Quercus serrata) concentrated in their age distribution, significantly increased; the effect of the oak group was significant on mortality in the tree population; the hazard for the oak group was 24 times the hazard for the other tree species group; the survival curve reflected the mass mortality in oaks at old ages, which led to the decrease of mean lifetime less than half. Consequently, it was implied that the effects of Japanese Oak Wilt Disease impacted the demographic metrics of oak trees.

Preparatory study for carbon sequestration modelling of agroforestry systems in Hungary: The assessment of the yield class distribution of windbreaks

The escalating carbon dioxide emissions leading to global climate change are acknowledged as a paramount environmental challenge in the twenty-first century. The significance of land use systems in stabilising carbon dioxide levels and enhancing carbon sink potential has gained noteworthy attention from both the scientific and political communities. The Intergovernmental Panel on Climate Change emphasises that agroforestry systems present vital prospects for synergising climate change adaptation and mitigation efforts, offering substantial technical mitigation potential. Windbreaks are well-known agroforestry systems in Hungary and form an important part of agricultural landscapes. The improved agroforestry subsidy system in our country makes it relevant to model the carbon sequestration potential of windbreaks. In the framework of the ForestLab project we plan to develop a carbon sequestration model specific for Hungarian agroforestry systems. In this study, as a preparatory step of the model development, we assessed the yield class distribution of Hungarian windbreaks by tree species group and identified variables that had significant effect on yield class based on the data of the National Forestry Database. Our results show that among the examined effects the most important predictor of the yield class of windbreaks was the tree species group, followed by the thickness of the productive soil layer and the hydrology of the site.

Evolutionary history shapes variation of wood density of tree species across the world

The effect of evolutionary history on wood density variation may play an important role in shaping variation in wood density, but this has largely not been tested. Using a comprehensive global dataset including 27,297 measurements of wood density from 2621 tree species worldwide, we test the hypothesis that the legacy of evolutionary history plays an important role in driving the variation of wood density among tree species. We assessed phylogenetic signal in different taxonomic (e.g., angiosperms and gymnosperms) and ecological (e.g., tropical, temperate, and boreal) groups of tree species, explored the biogeographical and phylogenetic patterns of wood density, and quantified the relative importance of current environmental factors (e.g., climatic and soil variables) and evolutionary history (i.e., phylogenetic relatedness among species and lineages) in driving global wood density variation. We found that wood density displayed a significant phylogenetic signal. Wood density differed among different biomes and climatic zones, with higher mean values of wood density in relatively drier regions (highest in subtropical desert). Our study revealed that at a global scale, for angiosperms and gymnosperms combined, phylogeny and species (representing the variance explained by taxonomy and not direct explained by long-term evolution process) explained 84.3% and 7.7% of total wood density variation, respectively, whereas current environment explained 2.7% of total wood density variation when phylogeny and species were taken into account. When angiosperms and gymnosperms were considered separately, the three proportions of explained variation are, respectively, 84.2%, 7.5% and 6.7% for angiosperms, and 45.7%, 21.3% and 18.6% for gymnosperms. Our study shows that evolutionary history outpaced current environmental factors in shaping global variation in wood density.

Height-diameter model of broad-leaved mixed forest based on species classification in Maoershan, Northeast China.

The complex stand structure and high species diversity of natural forests pose great challenges for analyzing stand growth and formulating reasonable plans for forest management. The height-diameter relationship is of great significance for predicting stand growth and formulating forest management measures. Based on survey data of 48 broad-leaved mixed forest plots in Maoershan, we classified 23 tree species into four groups based on species structure, growth characteristics and bionomics. We established a generalized model including stand, tree competition, species mixing and species diversity variables by reparameterization method, and a two-level mixed effect model of plot and tree species group. We tested the prediction ability of the model by leave-one-out cross-validation method. The results showed that the Ratkowsky (1990) model was the optimal basic model. The introduction of dominant height, basal area of trees larger than the object tree, basal area proportion of each species, and Shannon index could better explain the height-diameter relationship of broad-leaved mixed forest in Maoershan. The introduction of the mixed effect model of plot and tree species group could significantly improve the prediction accuracy of the model, with a Ra2 of 0.83. Under the same gradient of environmental factors, intolerant tree species exhibited higher tree heights than shade-tolerant tree species. In this study, we used the constructed tree height-diameter model to analyze the effects of species mixing and tree functional traits on tree height, which provided a theoretical basis for accurately predicting height of different tree species and analyzing the growth relationships in broadleaved mixed forests.

The Range Potential of North American Tree Species in Europe

European forest ecosystems are projected to change severely under climate change especially due to an anticipated decline in the distribution of major tree species in Europe. Therefore, the adaptation of European forests appears necessary and urgent. While spontaneous adaptation mechanisms bear a large self-guided potential, we focus on quantifying the potential of management-guided mechanisms. Besides other possible tree species groups for adaptation, non-native tree species from North America have a long tradition in Europe, yet their full distribution potential is not completely revealed. We applied an ensemble species distribution model approach to six North American species, using combined occurrence data from the native and naturalized ranges to gain more insights into the species suitability in the introduced area in 2070 (2061–2080) under the emission scenarios RCP 4.5 and 8.5. Our findings support the assumption that there is unreported species potential in the introduced area beyond their current distribution. Next to northeastern range shifts projected for all species, we identified Abies grandis, Liriodendron tulipifera, Quercus rubra, and Robinia pseudoacacia with increasing range potentials in the future. P. ponderosa and P. menziesii var. menziesii are projected to show a steady and decreased range potential under RCP 4.5 and 8.5, respectively.

Reference sites of threatened riverine Atlantic forest in upper Rio Doce watershed

The most important condition of ecological restoration is the identification of reference ecosystems, which function as a guide for assertive practice with which biological integrity and ecosystem structure and function can be compared. For restoration and conservation projects to be effective in the current scenario of biodiversity and ecosystem services decay worldwide, it is fundamental to understand the soil-plant interactions in each environment. In this study, we evaluated the structure and composition of the flora in 45 plots, equally distributed in three preserved areas (reference ecosystems) of Atlantic Forest in the upper Rio Doce watershed, Southeast Brazil. We also tested whether differences in species composition were influenced by edaphic factors, both in the adult tree and sapling strata. In both tree and sapling strata, Fabaceae was the species-richest family, followed by Myrtaceae, and Lauraceae. The Fabaceae family also showed the highest importance value for both strata. The soils of the riparian forests were highly heterogeneous among the studied sites. Co-inertia analyses indicated a clear edaphic-floristic gradient in both tree (RV = 0.467; p < 0.001) and sapling (RV = 0.478; p < 0.001) strata, with a connection of 46.7% and 47.8% between the edaphic and floristic matrices for trees and saplings, respectively. We identified the groups of tree and sapling strata species that were strongly associated with either nutritionally richer or poorer soils on each studied site. Understanding how ecological and life-history traits of plant species relate with edaphic factors is an important step to provide scientific-based knowledge to support policies for ecosystem recovery and restoration in the stretches of the Rio Doce watershed.

Integration of Unmanned Aerial Vehicle Imagery and Machine Learning Technology to Map the Distribution of Conifer and Broadleaf Canopy Cover in Uneven-Aged Mixed Forests

Uneven-aged mixed forests have been recognized as important contributors to biodiversity conservation, ecological stability, carbon sequestration, the provisioning of ecosystem services, and sustainable timber production. Recently, numerous studies have demonstrated the applicability of integrating remote sensing datasets with machine learning for forest management purposes, such as forest type classification and the identification of individual trees. However, studies focusing on the integration of unmanned aerial vehicle (UAV) datasets with machine learning for mapping of tree species groups in uneven-aged mixed forests remain limited. Thus, this study explored the feasibility of integrating UAV imagery with semantic segmentation-based machine learning classification algorithms to describe conifer and broadleaf species canopies in uneven-aged mixed forests. The study was conducted in two sub-compartments of the University of Tokyo Hokkaido Forest in northern Japan. We analyzed UAV images using the semantic-segmentation based U-Net and random forest (RF) classification models. The results indicate that the integration of UAV imagery with the U-Net model generated reliable conifer and broadleaf canopy cover classification maps in both sub-compartments, while the RF model often failed to distinguish conifer crowns. Moreover, our findings demonstrate the potential of this method to detect dominant tree species groups in uneven-aged mixed forests.

Simulation and prediction of changes in tree species composition in subtropical forests of China using a nonlinear difference equation system model.

Changes in tree species composition are one of the key aspects of forest succession. In recent decades, significant changes have occurred in the tree species composition of subtropical forests in China, with a decrease in coniferous trees and an increase in broad-leaved trees. This study focuses on Zhejiang Province, located in the subtropical region of China, and utilizes seven inventories from the National Continuous Forest Inventory (NCFI) System spanning 30 years (1989-2019) for modeling and analysis. We categorized tree species into three groups: pine, fir, and broadleaf. We used the proportion of biomass in a sample plot as a measure of the relative abundance of each tree species group. A novel nonlinear difference equation system (NDES) model was proposed. A NDES model was established based on two consecutive survey datasets. A total of six models were established in this study. The results indicated that during the first two re-examination periods (1989-1994, 1994-1999), there was significant fluctuation in the trend of tree species abundance, with no consistent pattern of change. During the latter four re-examination periods (1999-2004, 2004-2009, 2009-2014, 2014-2019), a consistent trend was observed, whereby the abundance of the pine group and the fir group decreased while the abundance of the broad-leaved group increased. Moreover, over time, this pattern became increasingly stable. Although the abundances of the pine group and the fir group have been steadily declining, neither group is expected to become extinct. The NDES model not only facilitates short-term, medium-term, and even long-term predictions but also employs limit analysis to reveal currently obscure changing trends in tree species composition.

Dead wood volume-to-carbon conversion factors by decay class for ten tree species in Croatia and eight tree genera globally

Dead wood (DW) is an important forest carbon (C) pool for which the reporting of C stock changes within the National Greenhouse Gas Inventory Report (NIR) is mandatory. The use of DW volume-to-carbon conversion factors by decay classes, i.e. DW basic density (DWBD) and C fraction (CF), or C density (CD) as their product, facilitates more accurate estimates of DW C stocks and C stock changes.We present DW conversion factors, namely DWBD, CF, and CD, by decay classes for six broadleaf (Quercus robur L., Carpinus betulus L., Alnus glutinosa Garnet., Fraxinus angustifolia Vahl., Fagus sylvatica L., and Quercus ilex L.) and four conifer (Abies alba Mill., Picea abies (L.) Karst., Pinus nigra Arnold and Pinus pinaster Aiton) tree species from Continental, Alpine and Mediterranean biogeographical regions of Croatia. For each tree species DW logs (diameter from 5 to 30 cm) were visually categorized into four decay classes and nine discs per decay class were sampled. In addition, three healthy trees of each species were felled down at the same location for estimating the basic density of fresh wood (BWD, decay class 0) and calculation of species-specific relative density reduction patterns. In total, 390 discs were sampled and analysed in the laboratory.Our results show that broadleaves, on average, have higher DWBD than conifers (p < 0.05) for decay classes 0–3, but for decay class 4 no difference (p < 0.05) was observed between these two tree species groups. Unlike for DWBD, CF showed no trend with decay class, but a difference (p < 0.05) in the average CF was found between broadleaves and conifers with the mean (s.e.) of 47.65% (0.12%) and 50.67% (0.23%), respectively. The application of decay class-specific CD by forest land use strata used in the Croatian NIR yielded 11.1% − 26.6% lower DW C pool estimates, compared to the current ones calculated using BWDs and default CF.DWBD data from our study was compared with DWBD data from the literature. We observed good agreement between national species-specific DWBD and global genus-specific DWBD for the great majority of investigated tree genera and decay classes. Therefore, we combined our results with the published data to provide a global DWBD meta-means with confidence intervals by decay classes for eight tree genera. Our results suggest that in the absence of local or national DWBD data, the use of genus-specific DWBD meta-means is justified.

Prospects for the Preservation of the Main Pinus sylvestris L. Ecotypes in Poland in the Context of the Habitat Conditions of Their Occurrence

This study investigates the prospects for preserving the main Pinus sylvestris L. (Scots pine) ecotypes in Poland, considering the habitat conditions of their occurrence. Scots pine is known for its wide distribution and natural adaptability to various habitats. However, there is an increasing vulnerability of pine forests to damage from biotic factors and a decrease in natural regeneration, particularly in areas under legal protection. Additionally, projected climate change has raised concerns about the future of Pinus sylvestris, placing it in the “losing” group of tree species. The aim of the study was to analyze the habitat conditions of the seven main selected Pinus sylvestris L. ecotypes to assess the sustainability of pine stands in their natural habitat conditions. Out of the seven populations of studied pine ecotypes, only one grows under conditions representing a typical form of pine forest (Leucobryo–Pinetum plant association). Two populations grow under conditions corresponding to potential deciduous forests (Galio sylvatici–Carpinetum and Calamagrostio arundinaceae–Quercetum petraeae). The remaining populations represent potentially mixed oak–pine forests. Such a distribution of plant communities, except for Leucobryo–Pinetum, does not guarantee the continuity of the studied pine stands as a result of their natural regeneration. Therefore, it is necessary to preserve the offspring of the studied populations outside their occurrence sites, but the studied pine stands should be preserved until their natural death in their natural habitats. In the conducted research, the NDVI turned out to be very useful, showing a high correlation with the trophicity of habitat expressed in the diversity of plant communities, as well as with the height and diameter of the studied stands.

An evaluation of the antimicrobial activity of some commonly used wood species

Aims: Antibiotic resistance mechanisms in pathogenic bacteria constitute an important obstacle in the fight against infection. Controlling the spread of resistant pathogens by utilizing antimicrobial activity on their surfaces may help us in this fight. There are many plant and wood species that have been previously tested for their antibacterial and antiviral properties. In this study, walnut (Juglans regia), white mulberry (Morus alba), white oak (Quercus alba), yellow pine (Pinus sylvestris), and beech (Fagus sylvetica), which are among the wood species used in the production of products that are in constant contact with humans in daily life, such as furniture, doors, and beads, were examined in terms of an antistaphylococcal effect. Methods: Five groups of tree species and glass samples selected as a positive control were cut into 1 cm3, contaminated with Staphylococcus aureus solution with a concentration of 1*106 CFU/ml, and monitored for five days. Each day, five randomly selected samples from each group were sonicated with phosphate buffered saline. Samples taken from the sonicated solution were cultured on tryptic soy agar, and the number of bacteria per sample was calculated. One sample selected from the uncontaminated samples was incubated with 0.5 McFarland standard bacterial solution on Müller Hinton agar, and the diameter of inhibition was evaluated. The study was repeated twice. The significance level was set at 0.05. Results: The agar diffusion method showed inhibition zone only in Q. alba and M. alba. In samples contaminated with bacteria, the highest antistaphylococcal effect was found in Q. alba. This was followed by M. alba, P. sylvestris, F. sylvetica. There was no significant difference between J. regia and the positive control. Conclusion: In this study in which we wanted to emphasize the importance of the antimicrobial activity of surfaces for pathogens known to live on the surface environment, all trees except J. regia showed antistaphylococcal activity. It is thought that the procyanidins?phenethyl, benzyl, and benzyl?in the bark of the trees are effective. In previous studies, Q. alba in particular is recommended for anti-infective use due to its high inhibition effect. Antibacterial activity was also found in F. sylvetica, which is known to have antiviral activity. Antibacterial activity was not demonstrated for J. regia. In order to prevent the spread of infection in collective living areas, it is recommended that trees be selected that contain antimicrobial raw materials such as M. alba, Q. alba, P. Sylvestris, and F. sylvetica and to evaluate the use of extracts from these trees as natural and edible products to combat bacteria.

Formulating Equations for Estimating Forest Stand Carbon Stock for Various Tree Species Groups in Northern Thailand

Through this study, we established equations for estimating the standing tree carbon stock based on 24 tree species in multiple size classes in a case study at the Ngao Demonstration Forest (NDF) in northern Thailand. Four hundred thirty-nine wood samples from trees in mixed deciduous forest (MDF), dry dipterocarp forest (DDF), and dry evergreen forest (DEF) were collected using non-destructive methods to estimate aboveground carbon equations through statistical regression. The equations were established based on four criteria: (1) the coefficient of determination (R2), (2) standard error of estimate (SE), (3) F-value, and (4) significant value (p-value, α ≤ 0.05). The aboveground carbon stock (C) equations for standing trees in the MDF was C = 0.0199DBH2.1887H0.5825, for DDF was C = 0.0145DBH2.1435H0.748, for DEF was C = 0.0167DBH2.1423H0.7070, and the general equation for all species/wood density groups was C = 0.017543DBH2.1625H0.6614, where DBH is tree diameter at breast height, and H is tree total height. The aboveground carbon stock in the DDF, MDF, and DEF was 142, 53.02, and 12 tons/ha, respectively, and the estimated aboveground carbon stock in the Mae Huad sector at the NDF was 61 tons/ha.

Spatial Analysis of Dense LiDAR Point Clouds for Tree Species Group Classification Using Individual Tree Metrics

This study presents a method of tree species classification using individual tree metrics derived from a three-dimensional point cloud from unmanned aerial vehicle laser scanning (ULS). In this novel approach, we evaluated the metrics of 1045 trees using generalized linear model (GLM) and random forest (RF) techniques to automatically assign individual trees into either a coniferous or broadleaf group. We evaluated several statistical descriptors, including a novel approach using the Clark–Evans spatial aggregation index (CE), which indicates the level of clustering in point clouds. A comparison of classifiers that included and excluded the CE indicator values demonstrated their importance for improved classification of the individual tree point clouds. The overall accuracy when including the CE index was 94.8% using a GLM approach and 95.1% using an RF approach. With the RF approach, the inclusion of CE yielded a significant improvement in overall classification accuracy, and for the GLM approach, the CE index was always selected as a significant variable for correct tree class prediction. Compared to other studies, the above-mentioned accuracies prove the benefits of CE for tree species classification, as do the worse results of excluding the CE, where the derived GLM achieved an accuracy of 92.6% and RF an accuracy of 93.8%.

Developing Growth and Harvest Prediction Models for Mixed Coniferous and Broad-Leaved Forests at Different Ages

In order to clarify the combined impact of tree species composition, site quality, and stand age on the growth and harvest of mixed forests, the prediction models of average DBH and stand volume for mixed forests were established, respectively. The interval period and tree species composition coefficient (TSCC) were considered as independent variables. These models were then optimized by using the particle swarm optimization algorithm for reparameterization and evaluating their applicability. It was found that after introducing the site quality grade and TSCC, the average stand height prediction model showed a better fitting result. The fit accuracy of the average DBH prediction model and the stand volume prediction model were both improved with the help of the TSCC, mainly because the tree species composition affects the growth rate of the average stand height and average DBH and the maximum growth rate of the stand volume. The degree of the impact can be sorted as Cunninghamia lanceolata &gt; Pinus massoniana &gt; hard broad-leaved tree species (group). Overall, the established growth and harvest prediction models for mixed forests with the interval period and TSCC as independent variables have high fit accuracy and applicability.

Mapping temperate forest stands using mobile terrestrial LiDAR shows the influence of forest management regimes on tree mortality

With global change, forest trees will be exposed to increasing stress in the coming decades with various studies demonstrating that stress-related mortality will increase in forests. While tree death can be triggered by a single factor, it is often caused by the accumulation and the complex interaction of various stressors. Several silvicultural strategies have been developed to cope with global change but very few studies have addressed the ways in which silvicultural regimes interact with various stressors to influence tree mortality. This lack of research on the effects of forest management regimes on tree mortality may be due to the challenge of acquiring large (or long-term) datasets to assess tree mortality in forests. Within this context and using a mobile terrestrial LiDAR approach for rapid 3D-mapping of forest stands, we aimed to (i) compare recent tree mortality patterns in temperate forests among contrasting forest management regimes (even-aged silviculture, uneven-aged silviculture and unmanaged forests), and (ii) evaluate the relative influence of regeneration harvest severity on tree mortality compared to other spatially explicit factors (i.e., localized competition and slope position) and non-spatially explicit factors (i.e. tree DBH -diameter at breast height- and tree species group). In a permanent sample plot network, we mapped 15 508 dead and living trees (>9.1 cm DBH) within 37 sugar maple-dominated stands: 14 even-aged, 16 uneven-aged and 7 unmanaged stands. We separated the relative role of forest management on individual tree mortality from other factors such as size, species, slope position, and localized competition by modeling the probability of mortality for each tree. Localized competition or slope position were not significant factors describing tree mortality. Results showed that tree mortality was influenced by tree species, DBH and forest management regime. Models indicated that forest management regime, by itself, had a strong effect on tree mortality proportion. Results also indicated that trees in uneven-aged stands had a higher probability of dying than the those in even-aged or unmanaged stands. However, we do not advocate for the replacement of uneven-aged regimes in favour of even-aged ones. Instead, we believe that, in the context of global change, adjustments should be made to uneven-aged regimes to reduce risk of mortality. Moreover, our study reinforces the idea that silviculture can be applied in such a way as to enhance stand resistance and resilience to cope with global change; for example, by influencing size structure and species composition, which greatly influence tree mortality.

The ecosystem disservices of trees on sidewalks: A study based on a municipality urban tree inventory in Central Italy

Urban green infrastructure, including street trees, plays a key role in providing ecosystem services to urban residents. However, to fully understand the effective role of trees in the urban context, it is also necessary to evaluate the disservices that they can produce in the development of their functions if not managed in an adequate and integrated way. This contribution aims to demonstrate an approach to assess three disservices (pavement damage, aesthetic damage, likelihood of tree failure) of street trees at the municipal level, starting from the existing municipal tree inventory. In this case study, from the street tree population, a sample of approximately 5% of the trees was drawn by stratified random sampling, where the strata were composed of groups of tree species. In particular, a sampling scheme is adapted in which the probability to select a tree in the sample is greater for bigger trees, under the assumption that the bigger the trees the greater are the disservices caused. In this way, a greater precision of the estimates of the considered disservices for the population of urban trees is expected. The results show a high variability of disservices provision among species groups. The results also confirmed a positive correlation between the considered disservices and tree diameter at breast height, while other tree attributes such as total height and crown diameter were found to be positively related only to pavement damages. Finally, severe pruning can lead to a high level of the aesthetic and functional disservices even for shorter and younger street trees.

Functional diversity affects tree vigor, growth, and mortality in mixed-conifer/hardwood forests in California, U.S.A, in the absence of fire

Mixed tree-species forest management can increase forest resilience by reducing the impacts of disturbances that disproportionately affect a single tree species or closely related groups of tree species. Beyond disturbance-risk reduction, tree-species diversification may foster functional-diversity effects (e.g., complementarity or facilitation) that alter the performance of a given tree species in mixed versus pure stands, potentially benefitting carbon sequestration and wildlife habitat. Tree species-mixture effects have been explored to only a limited degree in western US forests and, particularly, in California. Establishing whether vigor, growth, and mortality of common tree species vary with stand composition would help inform restoration and modeling of these forests under climate change. Using data from USDA Forest Service Forest Inventory and Analysis (FIA) plots from California, we examined how individual-tree vigor, as indicated by live crown ratio (LCR), periodic basal area increment (BAI), and mortality odds varied with functional dissimilarity (FDis). We quantified FDis using an index based on 11 traits related to resource acquisition, competition, environmental tolerances, and fire ecology. We classified major tree species into ponderosa pine (Pinus ponderosa), Jeffrey pine (Pinus jeffreyi), incense-cedar (Calocedrus decurrens), true firs (Abies spp.), Douglas-fir (Pseudotsuga menziesii), live oaks (Quercus spp.), and deciduous oaks (Quercus spp.) response groups. We tested for the main effects of FDis on tree responses, as well as for interactions with tree, site, stand, and climate factors. We found that initial tree height modulated the effects of FDis on ponderosa pine, Jeffrey pine, incense-cedar, and true fir LCR, whereas FDis interacted with climate to alter live oak and deciduous oak LCR. FDis decreased BAI in ponderosa pine and increased BAI in live oaks. FDis interacted with tree size to influence BAI for Jeffrey pine, Douglas-fir, and true firs. We found no evidence that climate or site quality modulated FDis effects on BAI for any species group. Tree mortality was not responsive to FDis, except for the true firs, where both initial tree height and competition interacted with FDis to increase and decrease mortality odds, respectively. FDis effects commonly shifted from positive to negative along gradients of stand structure and site quality, indicating that these effects vary with site and stand conditions. Our results have implications for balancing the ecosystem benefits of mixed stands, such as disturbance risk, carbon sequestration, and habitat during forest restoration projects in the region, as well as for more accurate modeling of complex stands.

Forest Area and Structural Variable Estimation in Boreal Forest Using Suomi NPP VIIRS Data and a Sample from VHR Imagery

Our objective was to develop a method for the assessment of forest area and structural variables for cases in which the availability of representative ground reference data is poor and these data are not collected from the whole area of interest. We implemented two independent approaches to the estimation of the forest variables of a European boreal forest: (i) the computation of wall-to-wall estimates using moderate- to low-resolution VIIRS imagery from the Suomi NPP mission; and (ii) the visual interpretation of plots of samples from very high resolution (VHR) satellite data obtained via a two-stage design. Our focus was on the statistical comparison of forest resources at a country or larger level. The study area was boreal forest ranging from Norway to the Ural Mountains in Russia. We computed a seamless mosaic from 111 VIIRS images. From the mosaic, we computed predictions for the forest area, growing stock volume, height of the dominating tree layer, proportion of conifers and broadleaved trees, site fertility class, and leaf area index. The reference data for the VIIRS imagery were national forest inventory (NFI)-based raster maps from Finland. The first stage sample of VHR data included 42 images; of these, a second stage sample of 2690 plots was visually interpreted for the same variables. The forest area prediction from VIIRS for the whole study area was 1.2% higher than the VHR-based result. All other structural variable predictions using VIIRS fitted within the 95% confidence intervals computed from the VHR sample except for estimates of the main tree species groups, which were outside the limits. A comparison of VIIRS-based forest area estimates using Finnish and Swedish NFI data indicated overestimations of 10.0% points and 4.6% points, whereas the total growing stock volumes were overestimated by 8% and underestimated by 3.4%, respectively. The correlation coefficients between the VIIRS and VHR image predictions at the 42 VHR image locations varied from 0.70 to 0.85. The VIIRS maps strongly averaged the local predictions due to their coarse spatial resolutions. Based on our findings, the approach using two independent estimations yielded similar figures for the central forest variables for the European boreal forest. A model computed using reference data from a small part of the area of interest can provide satisfactory predictions for a much larger area with a similar biome. Therefore, our concept is applicable to the estimation and overall mapping of a forest area and central structural variables at regional to national levels.

Disentangling regeneration by vertical stratification: A 17-year gap-filling process in a temperate secondary forest

Forest gaps are widely spread in the forest ecosystems and play important roles in driving forest dynamics. However, long-term regeneration during the gap-filling process was less understood, especially species composition and dynamics along vertical gradients over time. We monitored tree regeneration in artificial gaps of a temperate secondary forest for 17 years and analyzed the gap-filling process both as a whole and by stratification (lower layer: 0∼3 m, middle layer: 3∼6 m, and upper layer: >6 m) for three shade-tolerance groups of tree species. We found that the interaction effects of gap size and shade tolerance could result in a growth difference of five to ten years among different regeneration groups, with the most significant effects in the large gaps for the light-demanding species such as Juglans mandshurica and Phellodendron amurense. Regeneration density in the large and small gaps eventually converged, but there were great differences in density dynamics. The regeneration density in the large gaps decreased gradually over time, while it decreased sharply in the small gaps after just one growing season of gap formation and consistently remained at low levels regardless of shade tolerance. Species richness decreased smoothly during the 17-year monitoring, but the richness in the large gaps was consistently higher than that in the small gaps, with all shade-tolerance groups existing, which underlined the importance of gap size in maintaining tree species diversity. Differences in the density, richness, and composition among regeneration layers reduced over time. However, vertical regeneration patterns diverged among shade-tolerance groups during the gap-filling process. Light-demanding species were likely to have only one chance for successful regeneration because almost no new recruitments appeared in the lower or middle layer as dominant stems reached the upper layer. Intermediate and shade-tolerant species, by contrast, were well-distributed in different regeneration layers, indicating a stronger capacity for resistance and resilience during uncertain disturbance events in the long run. Our results revealed the gap-filling strategies of tree species with different shade-tolerance groups, which explained why light-demanding species could not completely occupy a forest gap and highlighted the necessity of repeated gap disturbance for intermediate and shade-tolerant species regeneration.