Mean Diameter At Breast Height Research Articles

Woody Species Composition, Stand Structure and Regeneration Status of Londiani Forest in Kenya

Tropical forests provide habitats for diverse flora and fauna, in addition to playing a crucial role in climate regulation. They are being recognized for their roles as nature-based solutions to many sustainable development challenges, as shown by increased political commitment and global promises to reduce the rates of deforestation and boost the restoration of degraded forest ecosystems. Understanding tropical forest dynamics and their conservation status is therefore important. This study analysed the forest stand structure, the tree species composition and the regeneration status of Londiani Forest. In the three blocks of Londiani Forest, which are Kedowa, Chebewor and Londiani, belt transects that were 25 m wide and 1 km long were established. At every 200 m along the transects, 25 m × 25 m quadrats were set up in which an inventory of all the tree species was determined. Diameter tape was used to measure the diameter at breast height (DBH) 1.3 m above the ground. With the use of a Suunto angular clinometer, the tree height was measured. A nested 5 m × 5 m quadrat within the 25 m × 25 m quadrat was used to sample the saplings, while a 1m × 1 m quadrat was used to sample the seedlings. The quantities of seedlings and saplings were used to determine the state of regeneration. The data were entered into Microsoft Excel. The total stem density, species density, basal area, species basal area, relative density and species diversity were determined and extrapolated per hectare. A total of 1308 distinct trees from 34 different species and 24 families were counted. Kedowa recorded the highest (27) species richness, followed by Chebewor (19) and then Londiani (14). There was a statistically significant difference in the species richness among the three forest blocks (p < 0.05). Within the three forest blocks, there were no statistically significant variations in the basal area distribution (p > 0.005) or in the mean DBH (F = 0.560; p = 0.729) or height class distribution (F = 0.821; p = 0.558). There was a statistically significant difference in the stem density (F = 12.22; p = 0.005) and woody species diversity (F = 0.32; p = 0.001) within the three forests blocks. The similarity index ranged from 0.34–0.47. The presence of substantial numbers of seedlings and saplings in all forest blocks was an indication that there was regeneration.

Sampling Protocol for Measuring Mean Diameter at Breast Height of Forked Urban Trees

The sustainable management of urban green areas requires clear and efficient protocols for measuring the biometric properties of tree vegetation. Specifically, operational in situ sampling solutions are essential to inventory forked (multi-stemmed) trees. This study aimed to assess the efficiency of two different sampling protocols for mean tree diameter at breast height (DBH) measurement of forked urban trees. The protocols were tested on a dataset of 76 forked trees, each having more than three stems and sampled in urban areas of Kyiv, Ukraine. First, we tested the efficiency of mean tree DBH estimations using measurements of randomly selected one, two, or three stems (random sampling, or RSM). Second, we examined different combinations of the thinnest, thickest, and average stems (identified visually) for each tree to estimate mean tree DBH (targeted sampling, or TSM). The distributions of mean tree DBH and root mean square errors (RMSE) were utilized to compare the utility of the two approaches. The TSM of three stems (the thinnest, thickest, and average) provided the highest accuracy of mean tree DBH estimation (RMSE% = 6.3% of the mean), compared to the RSM (RMSE% = 12.1%). The TSM of the four thickest stems demonstrated the overestimation of mean tree DBH for forked trees with five or more stems. Accurate mean tree DBH estimates can be derived with negligible systematic errors applying the RSM over a large number of measured trees. However, these estimates will not likely match the measurements from previous inventories due to random stem selection. We recommend using the TSM with measuring three specific stems as a balanced solution in terms of estimation accuracy, bias, and time costs.

Neighborhood Tree Position and Size Had Hierarchical Effects on Korean Pine Growth at Different Opening Degree Levels

Certain fluctuations were found when using the opening degree index to evaluate the effects of the adjacent broadleaved trees on the under-canopy target Korean pine (Pinus koraiensis Sieb. et Zucc.) trees in a mixed forest of planted Korean trees and natural broadleaved trees. The fluctuations were probably caused by the different positions and sizes of the adjacent broadleaved trees over the target Korean pine trees. For the purpose of clarifying this issue, the effect of the position and size (marked by height and diameter) of the neighborhood broadleaved trees on the height and diameter growth of Korean pine trees under the canopy in a secondary forest at different opening degree levels was studied. Generally, the mean DBH (diameter at breast height) and mean height of P. koraiensis trees under the canopy were higher when the adjacent broadleaved trees were located on the north or east sides of the target P. koraiensis trees than when they were located on the south or west sides. This was the case at all opening degree levels except the 0.5 opening degree level, where no significant difference was observed among the growth indexes of Korean pine trees based on the different positions of neighborhood trees. The mean DBH and height of P. koraiensis trees under the canopy decreased with the increase in the DBH and height of the adjacent broadleaved trees at all orientations and at all opening degree levels, but only those of the Korean pine trees with adjacent broadleaved trees on the south side in the 12.6–13.5 m height range and those with adjacent broadleaved trees on most sides in the 18.6–21.0 cm and 13.6–14.5 m height ranges at opening degree levels of K = 2.0, 1.5, and 1.0 reached a significant level of difference; whereas those of most Korean pine trees with adjacent broadleaved trees on the south and west sides in the height range of 11.6–12.5 m and DBH ranges of 13.6–16 cm and 16.1–18.5 cm, as well as the ones with adjacent broadleaved trees on most sides in the DBH range of 18.6–21.0 cm and the height range of 13.6–14.5 m at the opening degree level of K = 0.5, reached a significant level of difference, with a few exceptions. In conclusion, the broadleaved trees with a large diameter, great height, and a south or west orientation of the target P. koraiensis trees had a negative impact on their growth, but influence intensities changed at different opening degree levels.

Effect of Improved Planting Stock on Tree Growth, Wood Properties, and Soil Fertility of Teak Plantations 10 Years After Planting

Teak (Tectona grandis Linn. f.) is one of the most economically valuable types of tropical forest because teak wood has high durability, resilience and good aesthetic qualities. Teak tree improvement in Indonesia was initiated in 1983 producing planting stock for reforestation, i.e. clonal seed orchards (CSO) to produce seedling as sexual reproduction (referred to seedling), and hedge orchards to produce shoot cuttings as asexual (vegetative) reproductive (referred to shoot cuttings). Teak plantations established using seedling and shoot cuttings should improve forest productivity. The objectives of this study were to compare the growth rate, wood properties, and soil fertility of teak plantations propagated using seedling and shoot cuttings. Three square plots of 100 trees (10 × 10 trees; 1,000 m2) were established on both types of plantation and tree growth characteristics, wood properties, and soil fertility were monitored. The tree growth characteristics were diameter at breast height (DBH), tree height (H), clear bole height (CB), and volume of standing stock (Vss), and the wood properties included pilodyn penetration (PP) and stress wave velocity (SWV). Soil fertility was assessed from soil samples collected from three soil depths, with three replicates in each plot: 0–5 cm (top layer), 6–30 cm (middle layer), and 31–60 cm (bottom layer). Soil samples were analysed for total nitrogen, total phosphorus, total potassium, total calcium, and total magnesium. The results showed that the mean DBH, H, CB, and Vss differed significantly between the type of planting stock. The DBH, H, CB, and Vss values were 28.4%, 46.8%, 49.1%, and 130.1% higher, respectively, in teak plantations from shoot cuttings than from seedling. Moreover, the SWV of shoot cuttings planting stock plantation was 3.6% higher than from seedling. The mean PP did not differ significantly between teak plantations from shoot cuttings (22.00 mm) and seedling (21.80 mm). Furthermore, the planting stock did not affect soil fertility, which was highest in the top layer in all treatments. Our results suggest that teak plantations from shoot cuttings would increase growth, forest productivity, maintaining wood quality and soil fertility. Thus, it can maintain sustainable teak forest plantations.

Modeling stand biomass for Moso bamboo forests in Eastern China.

Stand biomass models can be used as basic decision-making tools in forest management planning. The Moso bamboo (Phyllostachys pubescens) forest, a major forest system in tropical and subtropical regions, represents a substantial carbon sink, slowing down the rise of greenhouse gas concentrations in the earth's atmosphere. Bamboo stand biomass models are important for the assessment of the contribution of carbon to the terrestrial ecosystem. We constructed a stand biomass model for Moso bamboo using destructively sampled data from 45 sample plots that were located across the Yixing state-owned farm in Jiangsu Province, China. Among several bamboo stand variables used as predictors in the stand biomass models, mean diameter at breast height (MDBH), mean height (MH), and canopy density (CD) of bamboo contributed significantly to the model. To increase the model's accuracy, we introduced the effects of bamboo forest block as a random effect into the model through mixed-effects modeling. The mixed-effects model described a large part of stand biomass variation (R2=0.6987), significantly higher than that of the ordinary least squares regression model (R2=0.5748). Our results show an increased bamboo stand biomass with increasing MH and CD, confirming our model's biological logic. The proposed stand biomass model may have important management implications; for example, it can be combined with other bamboo models to estimate bamboo canopy biomass, carbon sequestration, and bamboo biomass at different growth stages.

Structural changes and carbon reduction due to habitat loss in Atlantic Forest

Habitat loss is a significant threat to biodiversity in tropical forests, leading to changes in composition, structure, and function. In this study, we aimed to evaluate the influence of the forest amount at the landscape scale on the structure and the stored carbon of tree communities. Eleven landscape samples of 36 km2 (6 × 6 km), with different amounts of forest cover at the landscape scale (between 5 and 60%), were randomly selected within a wide latitudinal range of Atlantic Forests in Brazil. We also used a sample design to control and avoid some biases in landscape-scale studies during the landscape selection, such as the rescue effect from the surrounding landscapes, differences in matrix permeability in each landscape, and the control for the same vegetation type or successional stage. In each selected landscape, we surveyed all woody individuals with a diameter at breast height (DBH) ≥ 2.5 cm in eight plots of 250 m2, randomly placed in the landscape’s forested areas. The structural variables evaluated were: total abundance, the abundance of prominent families, the abundance of large trees (DBH ≥ 30 cm), mean DBH, and average height, besides carbon storage. From the set of 8,179 individuals, we observed a positive correlation between forest amount and the total abundance, the abundance of large trees, and carbon stock. The abundance of the prominent hardwood tree families were positively correlated with forest amount. When comparing the two landscapes with the lowest proportion of habitats (5–15%) and the highest proportion (55−60%), almost one thousand trees and more than 150 T of carbon per hectare are lost. This reduction in the overall abundance and carbon indicates no compensatory effects on the tree community due to a turnover in composition or substitution of large trees for smaller ones. The Atlantic Forest is undergoing a process of homogenization and functional collapse, derived directly or indirectly from habitat loss, leading to a possible regime shift.

Synergistic use of Sentinel-1, Sentinel-2, and Landsat 8 in predicting forest variables

Forest variables measurement is indispensable to supervising the dynamic of forest carbon storage. As commonly quantified forest variables, canopy cover (CC), diameter at breast height (DBH), and tree height (TH) were the predicted objects in our study. Recently, remote sensing technology, with high efficiency and wide temporal and spatial coverage, has been extensively used in practice. However, integrating open access satellite resources Sentinel-1 (S1), Sentinel-2 (S2), and Landsat 8 (L8) to quantify forest CC, DBH, and TH has not been extensively examined in the literature. In this study, we explored the potential of individual satellite bands/indices and the integration of different sensors in predicting mean CC, mean DBH, and mean TH in the plots dominated by four tree species (total area 102,887.6 ha). We acquired the satellite patterns of S1, S2, and L8 covered our research plots in 2017, and extracted the mean pixel values of the spectral images for every plot we detected. Specifically, seven sets of features derived from the satellite images of S1, S2, and L8 were used to predict CC, DBH, and TH for the survey plots. The results mainly indicated that group S2 + L8 (RMSEr (the relative root mean square error) = 17.9%, 21.0%, 23.0%) or S2 + L8 + S1 (RMSEr = 17. 8%, 21.0%, 23.1%) achieved the best accuracy for CC, DBH, and TH of all plots. Additionally, group S2 + L8 outperformed the other groups within two sensors and was superior to the individual sensors. Adding S1 synthetic aperture radar (SAR, the sensor carried by S1) had no evident improvement or deviation for most models, nevertheless, numerous bands/indices of SAR occupied important positions in variable importance and were been selected by stepwise regression, which denoted that it is available and valuable for forest parameters of some dominant tree species. Moreover, shortwave infrared (SWIR) bands played a crucial role in the three forest parameters prediction during the rainy season. SWIR bands (RMSEr = 20.5%), NIR bands (RMSEr = 24.1%), and red-edge bands (RMSEr = 27.1%) exerted the most significant implication for predicting CC, DBH, and TH apiece as univariate models. Green bands and NIR also occupied more positions of higher variable importance in multivariate models for estimating DBH and TH, while SWIR took up more for CC in all dominant species. Furthermore, non-parametric models outperformed the parametric model on the whole. In the meanwhile, the best models also were influenced by the data analysis methods.In a nutshell, a combination of multiple satellite sensors was proposed for forest variable selection, especially different optical sensors. SAR data were also inspired to be pitched in related forest measurement work, but it requires some data processing before applying to the research in many cases.

Natural regeneration potential and dynamics in boreal lichen woodlands of eastern Canada following soil scarification

Boreal lichen woodlands (LWs) are stable low tree-density zones of the Canadian boreal forest whose afforestation has been proposed as a way to create new C sinks and thus mitigate climate change. Planting operations in these remote areas are however costly and time-consuming, and may not be necessary when soil scarification is followed by dense natural regeneration. In the present study, we assessed the natural regeneration potential and dynamics in six boreal LWs of Québec, Canada, 11 years after soil scarification. The number, size (height and stem diameter) and age of seedlings were measured in 2-4 sampling plots per site (18 plots in total). Our data show that scarification operations produced on average 1,400 m2 ha–1 of exposed mineral soil (scarification intensity of 14%) with, however, a large within-site variability. The natural regeneration was mainly composed of black spruce seedlings (> 95%), averaged ∼12,000 seedlings ha–1 across the six sites and significantly varied among sites, mostly due to the variation in scarification intensity. Seedling density averaged ∼9 seedlings m–2 of exposed mineral soil and increased with seed tree mean diameter at breast height (DBH) (R2 = 0.51; P < 0.05) but not with the density of seed trees, revealing the importance of old and large seed trees in natural regeneration success. Together, scarification intensity and the DBH of remaining seed trees explained ∼60% of the variation in natural regeneration density across the 18 sampled plots. The rate of establishment of seedlings was generally high – with on average 60% of the carrying capacity of the substrate being reached within three years following scarification – and increased with seed tree mean DBH (R2 = 0.77; P < 0.05). However, the growth rate of seedlings was very low. Eleven years after scarification, 60% of the seedlings were < 15 cm and the height of 10-yr-old seedlings averaged 27.5 cm. Thus, even though seedling establishment was successful, the biomass accumulated by the natural regeneration was negligible in the span of a decade. Therefore, the implementation of afforestation following scarification appears to be necessary to create significant C sinks in the midterm.

Constructing two-level nonlinear mixed-effects crown width models for Moso bamboo in China.

Bamboo crown width (CW) is a reliable index for evaluating growth, yield, health and vitality of bamboo, and light capture ability and carbon fixation efficiency of bamboo forests. Based on statistical results produced from fitting the eight basic growth functions using data from 1374 Phyllostachys pubescens in Yixing, Jiangsu Province, China, this study identified the most suitable function (logistic function) to construct a two-level mixed effects (NLME) CW model with the forest block and sample plot-level effects included as random effects in the model. Four methods for selecting sample bamboos per sample plot (largest bamboo, medium-sized bamboo, smallest bamboo, and randomly selected bamboos) and eight sample sizes (1-8 selected bamboos per sample plot) were evaluated to calibrate our NLME CW model. Using diameter at breast height (DBH), height to crown base (HCB), arithmetic mean diameter at breast height (MDBH), and height (H) as predictor variables, the model produced the best fit statistics (Max R2, min RMSE, and TRE). This model was further improved by introducing random effects at two levels. The results showed a positive correlation of CW with HCB and DBH and a negative correlation with H. The smallest two bamboo poles per sample plot used to estimate the random effects of the NLME model provided a satisfactory compromise regarding measurement cost, model efficiency, and prediction accuracy. The presented NLME CW model may guide effective management and carbon estimation of bamboo forests.

An improved area-based approach for estimating plot-level tree DBH from airborne LiDAR data

The diameter at breast height (DBH) of trees and stands is not only a widely used plant functional trait in ecology and biodiversity but also one of the most fundamental measurements in managing forests. However, systematically measuring the DBH of individual trees over large areas using conventional ground-based approaches is labour-intensive and costly. Here, we present an improved area-based approach to estimate plot-level tree DBH from airborne LiDAR data using the relationship between tree height and DBH, which is widely available for most forest types and many individual tree species. We first determined optimal functional forms for modelling height-DBH relationships using field-measured tree height and DBH. Then we estimated plot-level mean DBH by inverting the height-DBH relationships using the tree height predicted by LiDAR. Finally, we compared the predictive performance of our approach with a classical area-based method of DBH. The results showed that our approach significantly improved the prediction accuracy of tree DBH (R2 ​= ​0.85–0.90, rRMSE ​= ​9.57%–11.26%) compared to the classical area-based approach (R2 ​= ​0.80–0.83, rRMSE ​= ​11.98%–14.97%). Our study demonstrates the potential of using height-DBH relationships to improve the estimation of the plot-level DBH from airborne LiDAR data.

Combining Weibull distribution and k-nearest neighbor imputation method to predict wall-to-wall tree lists for the entire forest region of Northeast China

Key messageWe propose a coupled framework to combine the strengths of the Weibull function in modeling diameter distributions and the ability of the k-nearest neighbor (kNN) method to impute spatially continuous forest stand attributes for the prediction of wall-to-wall tree lists (lists of stems per hectare by species and diameter at breast height (DBH)) at regional scales. The tree lists of entire Northeast China’s forests predicted by the above framework reasonably reflect the species-specific tree density and diameter distributions.ContextDetailed tree lists provide information about forest stocks disaggregated by species and size classes, which are crucial for forest managers to accurately characterize the current forest stand state to formulate targeted forest management strategies. However, regional tree list information is still lacking due to limited forest inventory.AimsWe aimed to develop a coupled framework to enable the prediction of wall-to-wall tree lists for the entire forest region of Northeast China, then analyze the species-specific diameter distributions and reveal the spatial patterns of tree density by species.MethodsA two-parameter Weibull function was used to model the species-specific diameter distributions in the sample plots, and a maximum likelihood estimation (MLE) was used to predict the parameters of the Weibull distributions. The goodness-of-fit of the predicted species-specific Weibull diameter distributions in each plot was evaluated by Kolmogorov-Smirnov (KS) test and an error index. The kNN model was used to impute the pixel-level stand mean DBH.ResultsWeibull distribution accurately described the species-specific diameter distributions. The imputed stand mean DBH from the kNN model showed comparable accuracy with earlier studies. No difference was detected between predicted and observed tree lists, with a small error index (0.24–0.58) of diameter distributions by species. The fitted species-specific diameter distributions generally showed a right-skewed unimodal or reverse J-shaped pattern.ConclusionOverall, the coupled framework developed in this study was well-suited for predicting the tree lists of large forested areas. Our results evidenced the spatial patterns and abundance of tree species in Northeast China and captured the forest regions affected by disturbances such as fire.

Patterns and drivers of tree carbon stocks in Kashmir Himalayan forests: implications for climate change mitigation

BackgroundTemperate forests are major carbon sinks because of their high storage potential and low decomposition processes. We quantified tree carbon (TC) storage from 143 plots distributed across three major forest types of Kashmir Himalaya, relative to differences in ecological factors. Combined regression and Random Forest (RF) analysis were used to examine the distribution of TC stock along ecological gradients and recognize the role of driving factors on TC stocks.ResultsAmong the three forest types, sub-alpine (SA) forest was the primary TC sink, accounting for 228.73 t ha−1 of carbon, followed by mixed conifer (MC; 181.29 t C ha−1) and blue pine (BP; 133.04 t C ha−1) forests. The distribution of TC stocks among the three forest types differed significantly (χ2 = 18.87; P = 0.000). Relative carbon stock analysis demonstrated that Abies pindrow and Pinus wallichiana accounted 91% of TC stocks across the landscape. Basal area, mean diameter at breast height (DBH), elevation, disturbance and precipitation had significant effects on TC stocks in bivariate regression models. The RF model explained 86% of the variation; basal area interpreted 30.15%, followed by mean DBH (17.96%), disturbance complex (10.64%), precipitation (8.00%) and elevation (7.34%).ConclusionsKashmir Himalayan forests are significant carbon sinks as they store a substantial quantum of carbon in trees. Forest carbon, an essential climatic indicator, is determined by a complex interaction of other ecological variables, particularly stand structural features. The study provides insights into the role of these natural forests in climate change mitigation and in REDD+/national commitments to offset the carbon.

Infestation patterns of incipient red turpentine beetle populations in fire-affected, logged and undisturbed forest stands of northern China

The red turpentine beetle (RTB) Dendroctonus valens is an alien invasive bark beetle that has become one of the most important pests of pine forests in China. In recent years, RTB has spread to the Heilihe area of northern China, where, within a short period of time, its population density has reached an incipient level. Understanding the attack behavior of RTB in the early stages of an infestation can help contain its population and avoid the transition from incipient to outbreak levels. In addition, numerous wildfires and illegal selective logging events in the Heilihe area give us the opportunity to study the attack behavior of RTB in forest stands with different disturbances. In the present study, we explored the infestation pattern of RTB in 20 wildfire-disturbed forests, 19 selectively logged forests and 42 undisturbed forests at the incipient population level. We measured stand and landscape-level variables, including stand mean diameter at breast height (DBH), canopy cover, aspect, elevation, slope and host connectivity. The landscape-level variable of host connectivity was extracted from a Sentinel-2 image through graph theory. In disturbed stands, we also measured bole scorch height and the number of stumps as proxies for fire and logging intensity. Generalized linear models were used to determine the relative importance of these explanatory variables in RTB infestations. Our results showed that wildfire-disturbed and logged stands had higher RTB infestation levels than undisturbed stands and disturbance intensity was the most important predicting variable across all factors. Furthermore, stand mean DBH had a positive relationship with RTB attacks in disturbed stands. In undisturbed stands, stand-level factors such aspect and canopy cover were the main driving factors of RTB attacks rather than host connectivity. However, the role of host connectivity shifted in wildfire-disturbed stands with high fire intensity, where interconnected stands promoted RTB infestations at the 500 m and 700 m scales. Our findings are valuable for identifying stands that are more vulnerable to RTB attacks and prioritizing management interventions aimed at controlling beetle populations.

Preferential sampling for bivariate spatial data

Preferential sampling provides a formal modeling specification to capture the effect of bias in a set of sampling locations on inference when a geostatistical model is used to explain observed responses at the sampled locations. In particular, it enables modification of spatial prediction adjusted for the bias. Its original presentation in the literature addressed assessment of the presence of such sampling bias while follow on work focused on regression specification to improve spatial interpolation under such bias. All of the work in the literature to date considers the case of a univariate response variable at each location, either continuous or modeled through a latent continuous variable. The contribution here is to extend the notion of preferential sampling to the case of bivariate response at each location. This exposes sampling scenarios where both responses are observed at a given location as well as scenarios where, for some locations, only one of the responses is recorded. That is, there may be different sampling bias for one response than for the other. It leads to assessing the impact of such bias on co-kriging. It also exposes the possibility that preferential sampling can bias inference regarding dependence between responses at a location. We develop the idea of bivariate preferential sampling through various model specifications and illustrate the effect of these specifications on prediction and dependence behavior. We do this both through simulation examples as well as with a forestry dataset that provides mean diameter at breast height (MDBH) and trees per hectare (TPH) as the point-referenced bivariate responses.

Individual-level distance-independent-based growth and yield prediction models for long-term Japanese cedar (Cryptomeria japonica)

Yield prediction has been determined to be vital in sustainable forest management. Recently, research trends have shifted from stand-level to individual-level yield prediction. In this study, we examined the effectiveness of yield prediction models based on a distance-independent approach for Japanese cedar (Cryptomeria japonica (L.f.) D.Don) trees in western Japan. We further examined the accuracy of the models with reference to existing data collected over the long-term. First, we constructed distance-independent height, diameter growth, and survival models. Then, we simulated for approximately 50 years individual tree height, diameter at breast height (DBH), and volume growth using the test data. We then compared the predicted and observed values and calculated root-mean-square error (RMSE) and bias to evaluate the model accuracy. The models were noted to perform well when predicting mean height, DBH, and volume for Japanese cedar trees; in fact, they adequately predicted the diameter distribution. Our results suggest that distance-independent models could adequately predict long-term mean values and diameter distribution. However, RMSE and bias indicated that error propagation occurred over longer time spans. Thus, it is effective to conduct actual measurements at some point in the forest development phase and use the measurements as initial values for short- or medium-term predictions.

Assessment of Population Status of Melia Volkensii Gürke and Diversity of Tree Species in Kasaala Location in Kitui County Kenya

This study was conducted to evaluate the population status of Melia volkensii and the diversity of tree species in Kasaala Location in Kitui County. Subsequently assessing the natural regeneration of M. volkensii and thus promote its propagation and conservation in the dry lands of Kenya. Plant population was determined in situ across seven transect lines measuring 1050 meters in length. Sampling was carried out in five plots measuring 50 × 50 meters established at intervals of 1,000 meters. Transect 1 and 7 were laid in farmland while the transects between these two were laid in bushland. All tree species represented in each plot were counted. Height and diameter at breast height (DBH) were measured for all M. volkensii trees within the plots. Melia volkensii seedlings and coppices were counted in 5 × 5 meter nested plots within the larger plots. One-way analysis of variance (ANOVA) at 95% confidence interval was used to test for variance in parameters measured and means separated using Tukey’s HSD. There were significant differences in mean number of height and DBH of M. volkensii that were found in transect one and two. Transect 2 had the lowest mean height and DBH while the tallest trees were in the other transects. Tukey honestly significant difference (HSD test) was used to test separation of means (of mature trees and coppices of M. volkensii). There were no significant differences between the mean number of coppices and seedlings found in transect two and four. Moreover, relative abundance, species richness and diversity of plant species observed were analyzed using Simpson’s index of biodiversity and Shannon-Wiener species diversity index. Melia volkensii was the most frequently occurring species with 12.2% (n=67) followed by Acacia tortilis10.0% (n=55). Calotropis strophela, Commiphora capensis, Maerua crassifolia were the least represented relative abundance of 0.18%. Values of indices used varied among transects and did not follow the location of transect implying that diversity was not determined by land disturbance. Based on diversity and relative abundance of M. volkensii and associated tree species in the study area, the results show clearly that the risk of tree depletion in Kasaala Location has no significant effects on the population status of M. volkensii.

Greater glider (Petauroides volans) den tree and hollow characteristics

Hollow-bearing trees provide essential habitat for a range of threatened Australian wildlife species. Limited data exist for the hollow choice of greater gliders (Petauroides volans). This study aimed to provide the first comprehensive overview of the dimensions and characteristics of the den trees and hollows used by greater gliders, in the context of an endangered population. Through spotlighting and stag-watching, we identified 68 greater glider hollows in 54 den trees. When compared to reference hollows, greater gliders appeared to be preferentially choosing dens based on tree species, tree diameter at breast height (DBH), hollow type, hollow height and hollow depth. The aspect, entrance diameter, and cavity wall thickness of hollows did not appear to be influencing den choice, when compared to reference hollows. Greater gliders preferred to den in blackbutt (Eucalyptus pilularis) trees with a mean DBH of 114.1 cm (±4.3 cm). Hollows were most commonly a ‘branch end’ type of hollow. Mean depth of hollows was 252 cm (±12 cm). Mean hollow height was 15.4 m (±0.4 m). While not significant, hollows had a mean minimum hollow entrance of 18.1 cm (±0.6 cm) and a mean maximum cavity wall thickness of 8.0 cm (±0.7 cm). It is likely that hollow depth contributes to temperature buffering within dens, which is important for den choice as greater gliders are highly sensitive to hot temperatures. Our findings have important conservation implications for assessing den trees, and for improving designs of nest boxes and artificial cavities.

Population dynamics and regeneration of Shorea roxburghii, a threatened timber species in Southern region, Viet Nam

Abstract. Bao TQ, Viet LH, Hai NH, Tuan NT, Cuong LV. 2021. Population dynamics and regeneration of Shorea roxburghii, a threatened timber species in Southern region, Viet Nam. Biodiversitas 22: 5649-5656. Despite its wide distribution in South and Southeast Asia, Shorea roxburghii G. Don is classified as Vulnerable in the IUCN Red List of Threatened Species due to over-exploitation for its valuable timber. This study aims to investigate the population dynamics and regeneration of S. roxburghii in southeastern Vietnam, serving for conservation and sustainable development plan. Six plots of 2,500 m2 each (50 m × 50 m) were established at two forest conditions: i) forest with standing volume > 200 m3/ha (SV>200), and ii) < 200 m3/ha (SV<200); to investigate stems with diameter at breast height (DBH) ? 5 cm and that < 5 cm. Moisture (%), pHH2O of the topsoil and the occurrence of regenerating S. roxburghii were collected from 125 points in the study site. The results indicated that mean stem height, DBH, basal area, and aboveground biomass were significantly higher at the forest stand with SV>200 than that at the forest stand with SV<200 for the pool of all species. Similar higher figures were found in SV>200 for the pool of S. roxburghii compared to that in SV<200, except mean DBH, which was larger in SV<200. There were missing stems with DBH < 5 cm in SV<200, while it was numerous in SV>200 (1,313 stems/ha). DBH/stem distributions in both forest types had an inverted-J shape with a peak at 10-15 cm DBH for the pool of all species, while there was no clear pattern for the pool of S. roxburghii in both forest types. Regression analysis indicated that higher total crown area of stems ? 23 tall leads to higher S. roxburghii stems, while the higher total crown area of stems < 23 tall leads to fewer S. roxburghii stems with DBH < 5 cm. It is concluded that the total crown area of forest stand plays an important role in the sustainable regeneration of S. roxburghii. Silvicultural treatment should be applied to reduce stand density and crown area of stems < 23 m tall to enhance sunlight reaching the forest floor for germination, growth, and survival of S. roxburghii. The moisture of the topsoil ranging from 60 - 80% and the pHH2O ranging from 3.8 - 4.6 are suitable conditions for natural regeneration of S. roxburghii.

The structural characteristics and climatic and human impacts of deciduous oak forests in China

AbstractDeciduous oak forest is one of the typical vegetation types in temperate and subtropical mountain zones in China. However, the patterns and determinants of the structural characteristics of these forests remain poorly understood. We investigated 682 oak forest plots across China to characterize the community structures of the oak forests and analyze the underlying factors controlling their spatial patterns. Across all plots, the overall mean values were 13.7 cm, 10.0 m, 1468 stems/ha and 24.3 m2/ha for the diameter at breast height (DBH), height, stem density and total basal area (TBA) of trees, respectively. The average species richness was 6 species/600 m2, 10 species/100 m2 and 4 species/1 m2 for the tree, shrub and herb layers, respectively. As latitude increased, the mean tree height, stem density, TBA, tree species richness and shrub species richness decreased, and the mean DBH did not show a significant trend, while species richness of herbs increased significantly. Climatic and anthropogenic variables could explain more variations in mean DBH, mean tree height, TBA, tree species richness, shrub species richness than those in stem density and herb species richness. Further analysis showed that precipitation-related climatic factors were major factors shaping the spatial patterns of community structures. Our findings provide a basis for recognizing the biogeographic patterns of oak forest structures and their responses to global change in China.

Long‐term stand‐level resilience in natural secondary forest stands recovering from severe windthrow damage

AbstractLong‐term stand‐level resilience in three natural secondary forests after a stand‐replacing windthrow damage event was examined by analyzing stand composition, structure, and function using repetitive measurement data collected in permanent plots over 60 yr. The secondary forests differed among pre‐disturbance forest types. For the purposes of this study, stand resilience comprised resistance to and recovery from windthrow damage. To analyze composition, the dynamics of species numbers in the permanent plots were tracked and temporal trends in similarity between pre‐ and post‐disturbance compositions were examined. To investigate stand structure, the dynamics of tree density, mean diameter at breast height (DBH), and temporal trends in similarity between pre‐ and post‐disturbance DBH frequency distributions were analyzed. To investigate stand function, the dynamics of stand basal area were analyzed. The calculations showed that tree density, basal area, species composition, and DBH frequency distribution were associated with low resistance to windthrow damage. By contrast, the number of species and mean DBH were resistant to windthrow damage. Basal areas recovered quickly in the 60 yr post‐windthrow damage, but recovery of the pre‐damage mean DBH and DBH frequency distribution was slow. Tree density and the number of species recovered to levels that exceeded those in the stands prior to the windthrow event. The recovery of species composition varied by pre‐disturbance forest type. Among the stands analyzed, the hardwood forest that existed prior to disturbance was resistant to and recovered well from windthrow damage in comparison with other types of pre‐disturbance forests. In conclusion, stand‐replacing windthrow damage can have a long‐lasting influence on secondary forests, especially in terms of stand composition and structure.