On the average stack size of regularly distributed binary trees

From April to July of 2003–2005, we investigated habitat selection of breeding brown eared-pheasants (Crossoptilon mantchuricum) in the Xiaowutaishan National Nature Reserve, Hebei Province. Our results show that brown eared-pheasants preferred deciduous-coniferous mixed or deciduous forests with altitudes ranging from 1600 to 2200 m, steep gradients of slopes and medium or high positions on slopes. Moreover, they preferred habitats with more tree species, larger diameters at the breast height, more density and cover of trees and habitats with more types of grasses, high density and cover of grasses, but with fewer types of shrubs and lower density and cover of shrubs. They had larger territories in the early breeding stage than in the late breeding stage. There were significant differences in diameters at the breast height of trees, average height of trees, cover of trees, density of shrubs, cover of shrubs, aspect, distance to path, distance to water, distance to forest edge (P < 0.01, respectively), density of trees, type of shrubs, height of shrubs, type of grasses, density of grasses and proportion of bareness (P < 0.05, respectively). The result of the principal component analysis suggested that the principal components among the 23 habitat factors were the average height of trees, density of trees, diameters at the breast height of trees, density of shrubs, cover of shrubs and density of grasses. The differences in habitat selection of brown eared-pheasants between early breeding and late breeding stages may correlate with the dynamics of ambient environmental conditions, the reproductive behavior and energy requirements in their sub-stages of breeding.

There is a global drive to increase forest cover to protect biodiversity and help combat climate change. Tree planting is widely used to increase forest cover, although there is growing interest in using natural processes. However, predicting the outcome of natural colonization is challenging as it is a highly variable process and evidence is sparse, especially in temperate landscapes. Our study aims to evaluate the spatial and temporal scale over which natural colonization may be an effective approach to create new forests within temperate agriculturally dominated landscapes. We examine the spatial patterns in tree density and height across 90 sites in the United Kingdom that attempted to use natural colonization to create new forests between 1994 and 2004. Tree density and tree height were measured using light detecting and ranging point cloud data, an increasingly common technique for surveying forest characteristics. This research shows that natural colonization is a highly variable, relatively slow process in temperate agricultural landscapes, spatially restricted to a narrow fringe around existing forests and trees (105 m; 95% CI: 70–174 m, within approximately 19 years), although exact distances vary with former land use. This suggests that in some circumstances natural colonization will need to be assisted and supplemented with tree planting to increase forest cover, especially in areas away from a seed source. In reality, a blend of approaches will be needed to meet policy and land manager objectives, increase forest cover and tackle the biodiversity and climate crises.

Approximately, 20% of arable land worldwide, as well as nearly half of irrigated land, is subjected to salt stress. Osmotic stress and ion toxicity due to saline soils cause low crop yields. In this study, we introduced 18 families of salt-tolerant birch (Betula pendula Roth., Betula kirghisorum Sav.-Ryczg., and Betula pubescens Ehrh) into five high-salinity locations in northeastern China and evaluated their survival abilities. We also analyzed variation and stability of genotype–environment interactions of the different families under an additive main effect and multiplicative interaction model. Survival rate analysis indicated that the introduced families were well adapted to the high-salinity environments, whereas native families died. Variation analysis revealed significant differences between location × family interaction mean values for height and basic stem diameter (BSD), suggesting that most genotypes responded differently to different sites. The heritability of tree height and BSD at different sites varied from 0.416 to 0.940, with the coefficient of phenotypic variation ranging from 9.88% to 35.53%. Stability analysis indicated that some families had high tree heights but were sensitive to environmental conditions, whereas others were resistant but had average tree heights. These results suggest that families should be bred in various habitats to assess growth under favorable and unfavorable environments.

Growth characteristics have a complex inheritance pattern, and gene–environment interactions make predicting tree responses to environmental change difficult. In this study, we planted 44 Betula platyphylla families at three different sites (Mao er shan forestry center in Shangzhi, Jilin experiment forestry center in Jilin, Lang xiang forestry center in Langxiang) in northeastern China. Variation and stability of genotype–environment interactions of different families were analyzed using additive main effect and multiplicative interaction models. Variation analysis indicated significant differences between site × family interaction mean values for height, diameter at breast height, volume, and stem straight degree, suggesting that most genotypes responded differently according to location. The phenotypic coefficients of variation of different traits ranged from 12.84 % (stem straight degree in Langxiang) to 53.34 % (volume in Langxiang) and heritabilities of the different traits varied from 0.485 (diameter at breast height in Mao er shan) to 0.781 (height in Jilin). Correlation analysis showed a significantly positive association between tree height, diameter at breast height, and volume at the same and different sites, but stem straight degree showing a weaker correlation with other traits. Stability analysis indicated that some families had high tree heights but were sensitive to environmental conditions, whereas others had average tree heights but were resistant to environmental conditions. These results suggest that families should be bred in various habitats to assess growth under favorable and unfavorable environments. Under a selection ratio of 10 %, four families (family 1–7, 4–7, 3–12 and 4–13) were rated as superior families. The average height, diameter at breast height, volume, and stem straight degree of these four families were higher than average of all the families by 12.24, 16.82, 32.28 and 6.28 % in the four test sites, respectively.

The objective of the study was to investigate the relationship between radar response and forest parameters, i.e. stem density, tree height and biomass. Field measurements of trees and the underlying soil surface of a conifer forest stand were used in modeling of radar backscattering from 100 simulated forest stands with average tree height and stem density randomly generated within specified ranges (height from 2 to 20 meters, stem density from 10 to 3400 trees/ha). The modeling results were also compared with measured backscatter from stands in Maine, USA. The results show that radar return is more sensitive to tree height than to stem density. The total biomass has much higher correlation to the radar return than to tree height or stem density alone. Modeling results also show that the cross-polarization return at a longer wavelength has the best correlation with forest physical parameters. >

Independent distributions on a multi-branching AND–OR tree of height 2

We describe the distribution and amount of foliage, expressed as foliated branch surface area, weight, or number of buds in the live crown of healthy open-grown and closed-canopy balsam fir and white spruce trees. Balsam fir and white spruce have very similar total foliage surface area and weight. The live crown of white spruce trees contains fewer buds than balsam fir of similar dimensions. Thus, bud density per unit foliage weight or surface area is higher in balsam fir than in white spruce. We also observed that buds tend to grow in clusters more often on balsam fir than on white spruce, and that larvae of the spruce budworm preferentially attack buds that grow in clusters. Equations were developed to predict the total surface area and weight of foliage as well as number of buds in the live crown for estimation of absolute population density of spruce budworm. These equations use diameter at breast height (DBH) and the number of nodes in the live crown as predictors. When data on the number of live nodes are unavailable, it can be estimated from tree height. Equations were also developed from which to estimate foliage area, weight or bud numbers from DBH only.

Опрацьовано можливість використання безпілотного літального апарата (квадрокоптера) для вимірювання висоти дерев і чагарників. Встановлено, що візування прицілу безпілотного літального апарата з розміщеною на ньому камерою на основу дерева і його верхівку перпендикулярно до прямовисної осі стовбура дає змогу фіксувати його параметри за допомогою GPS-приймача у тривимірній системі координат x, y, z. Цю інформацію можна використати для визначення висоти вимірюваного об'єкта зі збереженням просторової та висотної атрибутивної інформації в цифровому вигляді разом із фотознімком верхівки. Апробацію запропонованого способу вимірювання висоти проведено на базі змішаних насаджень лісових масивів ДП "Бережанське лісомисливське господарство" та паркових насаджень у Бережанському призамковому парку на Тернопільщині. При цьому, для порівняння точності вимірювання, виконано одночасне визначення висот дерев і чагарників за допомогою лазерного висотоміра Nikon Forestry 550, оптичного висотоміра ВА та лісового висотоміра-кутоміра ВУЛ-1. Виявлено, що запропонований спосіб визначення висоти дерев та чагарникових порід дає змогу отримувати результати високої точності (з відхиленням до 2 %) без необхідності встановлення базисної віддалі під час вимірювань. Окрім цього, такий підхід дає змогу проводити візування на дійсну верхівку дерева та полегшує визначити висоту в умовах загущених деревостанів.

Abstract. Using terrestrial laser scanning (TLS), forest attributes such as diameter at breast height (DBH) and tree location can be measured accurately. However, due to low penetration of laser pulses to tree tops, tree height measurements are typically underestimated. In this study, data acquired by TLS and drones were combined; DBH and tree locations were determined by TLS, and tree heights were measured by drone use. The average tree height error and root mean square error (RMSE) of tree height were 0.8 and 1.2 m, respectively, for the combined method, and –0.4 and 1.7 m using TLS alone. The tree height difference was compared using airborne laser scanning (ALS). Furthermore, a method to acquire 100 % tree detection rate based on TLS data is suggested in this study.

The influence of two apple rootstocks (M9 and MM106) on growth and yielding of four apple cultivars (ʻPinovaʼ‚ ʻTopazʼ, ʻFlorinaʼ and ʻGolden Reindersʻ) in two culture system was studied. The experiment was placed in a commercial orchard at SC Agroindustriala Cluj-Napoca Romania, planted in 2007, during 2012-2104. In the experimental field some growth parameters (length of annual shoots, trunk cross-sectional area, tree height,) and fructification (average yield, and productivity index) were observed. The studied cultivars had a different response, on hand, due to the genetic characteristic of each one and on the other hand, due to the rootstock. The results showed that MM 106 transmit much strongly growth than M 9. The longest shoots, in mean values, gave the variants where the cultivars were grafted on MM 106 (53 cm) and the shortest (34.4 cm) on M9. The biggest average height of trees with the MM 106 rootstock were obtained (290 cm). The smallest average height of trees with the variants where the trees were grafted on M 9 (239 cm) was registered. The biggest average trunk cross sectional area with the MM 106 were obtained (102.1 cm 2 ). The best yield was obtained in variant where the cultivars were grafted on M 9 (47.03 t/ha) M9 rootstock has controlled the tree size of all cultivars more than MM 106 resulting in the lowest TCSA (58.8 cm 2 ) and the highest yield per hectar (47.03 tone/ha) and yield efficiency (925 kg/cm 2 ).

Seasonal patterns of the energy balance of a young jack pine site near Thompson, Manitoba, in the summer of 1994 are reported. The experiment was part of the Boreal Ecosystem‐Atmosphere Study (BOREAS), and it ran from May 24 to September 19. The average tree density was 4.4 trees m−2, but there was substantial spatial variation associated with three primary vegetation patterns: dense cover of short trees, sparse cover of tall trees, and a mixture of short and tall trees. The frequency distribution of tree heights was bimodal with peaks at 1 and 2 m and a range from 0.3 to 5.7 m. The average tree height was 2.3 m. The daily average photosynthetically active radiation albedo was conservative, varying from 0.054 under clear‐sky conditions to 0.051 under cloudy skies. The shortwave albedo was 0.136 under clear‐sky conditions and decreased by 1% following rain; the presence of smoke over the site increased it by 1%. Heat storage in the soil, trees, and air was an important component of the energy balance throughout the season with soil heat flux comprising the bulk of the total storage. On the average, for the whole experimental period, the sensible heat flux was approximately twice the latent heat flux (Bowen ratio ≈2). The average daily energy balance closure varied from 85% before day‐of‐year (DOY) 200 to 95% after DOY 200. As a result of problems with the measurement of the net CO2 flux above the canopy under stable nighttime conditions, all nighttime values were modeled. The typical diurnal pattern of net CO2 flux shows maximum uptake by the surface in the morning and a gradual decrease through the afternoon. For the whole field season of 118 days, the site fixed 224 g m−2 of carbon.

Terrestrial laser scanning (TLS) can be used to characterize a woodland site by measuring structural attributes of the vegetation community. In Australia, government funded programs monitor vegetation structure using manual field surveys to assess change and ecological condition. In this study, we examined whether structural attributes commonly assessed in woodland ecology surveys can be extracted from a single TLS scan. Attributes of the ground, shrub and overstory vegetation layers were evaluated at nine open woodland sites in central Western Queensland. We used 0.1 m voxels to aggregate returns. Our results show that, compared with field assessment by highly experienced ecologists, TLS can rapidly characterize structural attributes for tree canopy cover, maximum tree height, average tree height (R2 &gt; 0.9) and average diameter at breast height (R2 = 0.77). However, we could not accurately determine shrub height, shrub canopy cover, shrub average height, ground cover (grass, litter and coarse woody debris) or the number of trees per hectare (R2 &lt; 0.45). By analysing local minima in the histogram of the maximum height, we determined height thresholds for canopy strata, and applied these to determine the canopy layer with the most biomass – the ecologically dominant layer (EDL). While these results are promising for overstory assessment and defining canopy strata heights using TLS, they suggest that future research should focus on investigating improved classification methods to separate laser returns into shrub and tree objects for structural assessment at the plot scale.

Increasing soil carbon storage is an important strategy for achieving sustainable development. Enhancing soil carbon sequestration capacity can effectively reduce the concentration of atmospheric carbon dioxide, which not only contributes to the carbon neutrality goal but also helps maintain ecosystem stability. Based on 146 soil samples collected at plot locations selected across Beijing, we examined relationships between soil organic carbon (SOC) and key characteristics of urban forests, including their spatial structure and species complexity. The results showed that SOC in the topsoil with a depth of 20 cm was highest over forested plots (6.384 g/kg–20.349 g/kg) and lowest in soils without any vegetation cover (5.586 g/kg–6.783 g/kg). The plots with herbaceous/shrub vegetation but no tree cover had SOC values in between (5.586 g/kg–15.162 g/kg). The plot data revealed that SOC was better correlated with the physical structure than the species diversity of Beijing’s urban trees. The correlation coefficients (r) between SOC and five physical structure indicators, including average diameter at breast height (DBH), average tree height, basal area density, and the diversity of DBH and tree height, ranged from 0.32 to 0.52, whereas the r values for four species diversity indicators ranged from 0.10 to 0.25, two of which were not statistically different from 0. Stepwise linear regression analyses revealed that the species diversity indicators were not very sensitive to SOC variations among a large portion of the plots and were about half as effective as the physical structure indicators for explaining the total variance of SOC. These results suggest that urban planning and greenspace management policies could be tailored to maximize the carbon co-benefits of urban land. Specifically, trees should be planted in urban areas wherever possible, preferably as densely as what can be allowed given other urban planning considerations. Protection of large, old trees should be encouraged, as these trees will continue to sequester and store large quantities of carbon in above- and belowground biomass as well as in soil. Such policies will enhance the contribution of urban land, especially urban forests and other greenspaces, to nature-based solutions (NBS) to climate change.

Leaf area influences dry matter production of trees, as well as the growth of trees and forest stands. The accurate estimation of leaf area plays an important role in analyzing the growth of trees and forest stands. Based on data of 76 Larix olgensis trees in a plantation of Heilongjiang Province, predicting models of branch leaf area (BLA) and crown leaf area (CLA) were constructed, respectively. The results showed that a form of lnBLA=β1+(β2+b2)lnBD+(β3+b3)lnRDINC+β4lnDBH+β5lnHT/DBH+(β6+b6)lnCR was selected as the optimal BLA mixed-effect model with the considera-tion of tree-level random effects, composed of three random-effect on lnBD, lnRDINC and lnCR (βi represented model fixed parameters, bi represented model random-effect parameters, BD was branch diameter, RDINC was the relative depth into crown from tree apex, DBH was tree diameter at breast height, HT/DBH represented the ratio of tree height to DBH, and CR represented the ratio of crown length to tree height). The adjusted coefficient of determination (Ra2), residual mean squares error (RMSE), mean error (ME), mean absolute error (MAE) and precision estimation (P) of the optimal BLA mixed model were 0.90, 0.5477, -0.03, 0.24 and 91%, respectively, indicating the model had a good performance in predicting. The CLA was calculated by predicted values of all branches based on developed BLA model and the final form of CLA model was as follows: lnCLA=γ0+γ1lnDBH+γ2CR (γi, model parameters). Results of likelihood ratio test (P>0.05) showed that plot-level random effect had no influence on the model performance, which can be ignored. The CLA model got a good-fitting effect with R2 and RMSE being 0.87 and 0.3847, respectively. The CLA predicting model developed in this study could provide a good prediction of CLA for L. olgensis trees and provided a theoretical basis for the research on distribution of leaf area and photosynthesis.

With their widespread utilization, cut-to-length harvesters have become a major source of “big data” for forest management as they constantly capture, and provide a daily flow of, information on log production and assortment over large operational areas. Harvester data afford the calculation of the total log length between the stump and the last cut but not the total height of trees. They also contain the length and end diameters of individual logs but not always the diameter at breast height overbark (DBHOB) of harvested stems largely because of time lapse, operating and processing issues and other system deficiencies. Even when DBHOB is extracted from harvester data, errors and/or bias of the machine measurements due to the variation in the stump height of harvested stems from that specified for the harvester head prior to harvesting and diameter measurement errors may need to be corrected. This study developed (1) a system of equations for estimating DBHOB of trees from diameter overbark (DOB) measured by a harvester head at any height up to 3 m above ground level and (2) an equation to predict the total height of harvested stems in P. radiata plantations from harvester data. To generate the data required for this purpose, cut-to-length simulations of more than 3000 trees with detailed taper measurements were carried out in the computer using the cutting patterns extracted from the harvester data and stump height survey data from clearfall operations. The equation predicted total tree height from DBHOB, total log length and the small end diameter of the top log. Prediction accuracy for total tree height was evaluated both globally over the entire data space and locally within partitioned subspaces through benchmarking statistics. These statistics were better than that of the conventional height-diameter equations for P. radiata found in the literature, even when they incorporated stand age and the average height and diameter of dominant trees in the stand as predictors. So this equation when used with harvester data would outperform the conventional equations in tree height prediction. Tree and stand reconstructions of the harvested forest is the necessary first step to provide the essential link of harvester data to conventional inventory, remote sensing imagery and LiDAR data. The equations developed in this study will provide such a linkage for the most effective combined use of harvester data in predicting the attributes of individual trees, stands and forests, and product recovery for the management and planning of P. radiata plantations in New South Wales, Australia.