Crown Density Research Articles

Impact of Physical and Vegetation Patterns on Parks Environment: A Case Study of Gusan Neighborhood Park, South Korea

This study aims to investigate the impact of the physical structure, such as altitude, slope gradient, slope direction, and topographical structure, and the vegetation pattern, such as existing vegetation, diameter of breast height (DBH), and crown density, on climate. The analysis results showed the significant difference in relative humidity, wind speed, and solar radiation at varying altitudes, the significant difference in all climate factors except for the wind speed at varying slope gradient, and significant difference in temperature and relative humanity at varying slope direction. The topographic structures were divided into valleys, slopes, and ridges. They were found to differ in relative humidity. However, the differences between constant trends and types were found to be insignificant concerning temperature, wind speed, and solar radiation. Significant differences in temperature, relative humidity, and wind speed were recorded with changing existing vegetation. The DBH showed a significant difference in temperature, wind speed, and solar radiation. The crown density showed a significant difference in temperature and solar radiation. The result of the relationship analysis for the analysis of the effect of vegetation pattern and physical structure on the meteorological environment showed that temperature was affected by slope gradient, slope direction, DBH, and crown density. The relative humidity was correlated with the altitude, slope gradient, slope direction, and topological structure in physical structure and the existing vegetation and crow density in vegetation pattern. The wind speed was correlated with the altitude, existing vegetation, and DHB, and the solar radiation was correlated with the slope gradient, DHG, and crown density. The crown density was the most overall significant factor in temperature, relative humidity, and solar radiation, followed by the slope gradient. DBH was also found to be highly correlated with temperature and solar radiation and significantly correlated with wind speed, but there was no statistically significant correlation with relative humidity.

Study of the oil palm crown characteristics associated with Basal Stem Rot (BSR) disease using stratification method of point cloud data

Basal Stem Rot (BSR) disease caused by the Ganoderma boninense fungus is the most serious issue affecting the oil palm industry. Terrestrial laser scanning (TLS) technology is a precise, contact-free, and active remote sensing method which is widely used for determining tree morphology using the crown strata. However, its capability in BSR detection using crown strata solely has not been explored. Therefore, this study used TLS data to study the effect of crown profile due to BSR and develop a BSR detection model using crown strata. Ninety-two palms were selected at random consists of 36 healthy oil palm trees and 56 unhealthy oil palm trees infected by Ganoderma boninense. The palms were each scanned at four different positions around them, and crown strata (named as Cn; where n is the crown length in cm) were generated using crown stratification method. The numbers of laser hits in the strata were used to generate crown profiles comparing healthy and unhealthy oil palm trees, to develop prediction models and to examine the patterns of crown density in different parts. The study has accounted for the occlusion problem by carrying out a systematic multi-scan approach. Moreover, the short traveling distance (less than 12 m) needed for the laser to reach the maximum crown tips ensures greater point density. The profiles of crown strata revealed that the healthy trees have higher crown densities than unhealthy trees starting from 250 cm from the top (strata no. 5) to the bottom. Prediction models using the strata parameters C650, C700, C800, and C850 were 92.5% accurate in the classification of healthy-unhealthy trees.

Impact of emissions from the Orenburg gas chemical complex on the state of forest ecosystems

The article presents the results of a study of the state of forest ecosystems growing in the zone of the Orenburg gas-chemical complex. The authors established a taxation characteristic depending on the degree of remoteness from the source of pollution, the degree of accumulation and the accumulation series of heavy metals in the forest litter, and the horizontal crown density was calculated. All obtained data were analyzed using statistical analysis methods. The data obtained can be used for practical purposes.

The composition and structure of mature aspen forests in Lisinsky Forestry Unit of the Leningrad region

The article addresses the structure of secondary aspen forests, which allows us to predict their productivity, as well as evaluate the features of the formation of the main types of taiga forests. We carried out an analysis of the vitality structure, which forms a basis for forest monitoring. All higher vascular plants, as well as ground, epiphytic and xylophytic species of mosses and lichens were also identified to assess the biological diversity of the stands studied. The study has established that the species diversity of the ground cover in aspen forests depends on the degree of the crown density.

Integrating Landsat Time Series Observations and Corona Images to Characterize Forest Change Patterns in a Mining Region of Nanjing, Eastern China from 1967 to 2019

Long-term surface mining and subsequent vegetation recovery greatly alter land cover types, reshape landscape patterns and impose several impacts on local ecosystem services. However, studies on the history of forest changes in mining areas from the 1960s to the present have not been reported. This study developed a new idea to investigate the spatial and temporal dynamics of forest cover in a mining area of Mufu Mountain (Mt. Mufu) from 1967 to 2019 by integrating Landsat and Corona data, and to explore the relationships among the forest changes, landscape structures and ecosystem functions. Firstly, we applied the vegetation change tracker (VCT) algorithm and visual interpretation to create annual forest change datasets. Subsequently, the forest loss process was divided into subdivision, shrinkage, perforation and attrition components. An improved forest restoration model in this study extended the recovery process to bridge, branch, infilling and increment components. Finally, remote sensing variables and crown density were coupled to assess the forest aboveground biomass (AGB) to reflect the ecosystem function in the restoration area. Results showed that the combined use of Corona and the dense time series of Landsat can provide more detailed information on forest changes. Forest cover sharply decreased from 343.89 in 1967 to 298.44 ha in 1990, and after 2003, the forest area substantially increased and finally reached a maximum of 434.16 ha in 2019. Subdivision and bridge not only occupied the larger areas in the process of forest loss and restoration, but also they had strong correlations with forest changes and the Pearson correlation coefficients (r) were respectively 0.96 and 0.91. These all revealed that forest changes mainly affected landscape structure connectivity. The total forest AGB of Mt. Mufu increased from 20,173.35 in 2006 to 31,035.77 t in 2017, but the increases in AGB were only 30-40 t/ha in most recovery areas with high structure connectivity (bridge regions), indicating there is room for improving restoration projects in the future. The obtained findings can provide mining site restoration managers with clear, long-term forest change information and mine restoration assessment methods.

From Drones to Phenotype: Using UAV-LiDAR to Detect Species and Provenance Variation in Tree Productivity and Structure

The use of unmanned aerial vehicles (UAVs) for remote sensing of natural environments has increased over the last decade. However, applications of this technology for high-throughput individual tree phenotyping in a quantitative genetic framework are rare. We here demonstrate a two-phased analytical pipeline that rapidly phenotypes and filters for genetic signals in traditional and novel tree productivity and architectural traits derived from ultra-dense light detection and ranging (LiDAR) point clouds. The goal of this study was rapidly phenotype individual trees to understand the genetic basis of ecologically and economically significant traits important for guiding the management of natural resources. Individual tree point clouds were acquired using UAV-LiDAR captured over a multi-provenance common-garden restoration field trial located in Tasmania, Australia, established using two eucalypt species (Eucalyptus pauciflora and Eucalyptus tenuiramis). Twenty-five tree productivity and architectural traits were calculated for each individual tree point cloud. The first phase of the analytical pipeline found significant species differences in 13 of the 25 derived traits, revealing key structural differences in productivity and crown architecture between species. The second phase investigated the within species variation in the same 25 structural traits. Significant provenance variation was detected for 20 structural traits in E. pauciflora and 10 in E. tenuiramis, with signals of divergent selection found for 11 and 7 traits, respectively, putatively driven by the home-site environment shaping the observed variation. Our results highlight the genetic-based diversity within and between species for traits important for forest structure, such as crown density and structural complexity. As species and provenances are being increasingly translocated across the landscape to mitigate the effects of rapid climate change, our results that were achieved through rapid phenotyping using UAV-LiDAR, raise the need to understand the functional value of productivity and architectural traits reflecting species and provenance differences in crown structure and the interplay they have on the dependent biotic communities.

Non-linear wave attenuation quantification model improves the estimation of wave attenuation efficiency of mangroves

The wave attenuation function of mangroves follows the Dalrymple model but changes nonlinearly with vegetation structure in various places, which has not been fully addressed. Here, taking the Da Guan Sha of Beihai city, China, as a case study, the landscape metrics characterizing mangrove structures, including the diameter at breast height (DBH), crown breadth, crown density, and rhizome and stem systems, were obtained through remote sensing and field measurements. Then, the nonlinear spatiotemporal pattern of the wave attenuation function (decreasing rate of wave height) was explored and revealed among six 20х200 m parallel transects passing through mangroves along the direction of the current. The results showed the following: (1) The DBH and crown breadth first increased and then decreased from the seaward to landward side of each transect, showing a nonlinear inverted "U" pattern of distribution. (2) The wave attenuation function of mangroves was dominated by the canopy at high tide but significantly affected by the structure of the rhizome or stem system at low tide. The wave height during a specific storm surge could decrease by nearly 97% among the six transects at high tide but by only 87% at low tide on average if the wave crossed through the mangroves over a distance of ≥100 m from the seaward side of the mangroves edge. (3) The wet surface width of a major part of mangrove trees with wave attenuation functions would change with the distribution of the DBH, crown breadth, and tree height along the transects, which would also change with the dynamics of the water level. The wave attenuation of mangroves ranged from 85% to 90% at low tide and from 96% to 97% at high tide if the wave crossed through mangroves at a distance of ≥100 m from the seaward side of the mangrove edge. (4) The predicted practical decreasing rate of wave height based on the forward differencing method (a method that considered the varied vegetation structure along transects in the model during the calculation of wave attenuation, which would be close to reality) would be 12% and 9% higher at low and high tide, respectively, than those estimated by the simplified calculation method (a method of taking the average value of the vegetation structure of each transect to calculate wave attenuation) if the wave crossed through mangroves at a distance of ≥200 m from the seaward side of the mangrove edge. The integration of mangrove structures into the established empirical models improves our understanding of the nonlinear wave attenuation function of mangroves and may provide decision makers with more valuable information on restoring mangrove ecosystems to protect against storm surges.

Importance of overstorey attributes for understorey litter production and nutrient cycling in European forests

BackgroundIn contrast with the negligible contribution of the forest understorey to the total aboveground phytobiomass of a forest, its share in annual litter production and nutrient cycling may be more important. Whether and how this functional role of the understorey differs across forest types and depends upon overstorey characteristics remains to be investigated.MethodsWe sampled 209 plots of the FunDivEUROPE Exploratory Platform, a network of study plots covering local gradients of tree diversity spread over six contrasting forest types in Europe. To estimate the relative contribution of the understorey to carbon and nutrient cycling, we sampled non-lignified aboveground understorey biomass and overstorey leaf litterfall in all plots. Understorey samples were analysed for C, N and P concentrations, overstorey leaf litterfall for C and N concentrations. We additionally quantified a set of overstorey attributes, including species richness, proportion of evergreen species, light availability (representing crown density) and litter quality, and investigated whether they drive the understorey’s contribution to carbon and nutrient cycling.Results and conclusionsOverstorey litter production and nutrient stocks in litterfall clearly exceeded the contribution of the understorey for all forest types, and the share of the understorey was higher in forests at the extremes of the climatic gradient. In most of the investigated forest types, it was mainly light availability that determined the contribution of the understorey to yearly carbon and nutrient cycling. Overstorey species richness did not affect the contribution of the understorey to carbon and nutrient cycling in any of the investigated forest types.

Machine Learning Algorithms to Predict Tree-Related Microhabitats using Airborne Laser Scanning

In the last few years, the occurrence and abundance of tree-related microhabitats and habitat trees have gained great attention across Europe as indicators of forest biodiversity. Nevertheless, observing microhabitats in the field requires time and well-trained staff. For this reason, new efficient semiautomatic systems for their identification and mapping on a large scale are necessary. This study aims at predicting microhabitats in a mixed and multi-layered Mediterranean forest using Airborne Laser Scanning data through the implementation of a Machine Learning algorithm. The study focuses on the identification of LiDAR metrics useful for detecting microhabitats according to the recent hierarchical classification system for Tree-related Microhabitats, from single microhabitats to the habitat trees. The results demonstrate that Airborne Laser Scanning point clouds support the prediction of microhabitat abundance. Better prediction capabilities were obtained at a higher hierarchical level and for some of the single microhabitats, such as epiphytic bryophytes, root buttress cavities, and branch holes. Metrics concerned with tree height distribution and crown density are the most important predictors of microhabitats in a multi-layered forest.

Прогнозирование урожайности ягодников ежевики сизой в лесах степного Придонья

Приводятся результаты краткосрочного прогнозирования урожайности ягодников ежевики сизой в различных группах типов леса степного Придонья. С помощью корреляционного анализа установлена точность полученных прогнозных значений. The article deals with research of specificities of forecasting of yield of Rubus caesius in the main groups of forests of the steppe Pridonye [1]. Relevance of the research is due to the fact that, in natural forests of the steppe Pridonye the Rubus caesius is widely spread. According to data of the previous researches, there are the following factors, that influence growth and fruiting of wild Rubus caesius berry-field: type of forest, crown density and weather conditions. At the same time, the issue of forecasting of yield of Rubus caesius in forests of the steppe Pridonye remains open. As the result of this work, it was established by authors, that the most quantity of flowers of Rubus caesius per square meter is approximately the same in all groups of types of forest of the studied territory (65–86 pcs./m2), except oak ravine thalweg forests, where this value is significantly lower (40–43 pcs./m2). At the same time, the most quantity of sets were founded in black poplars near the riverbed (47–63 pcs./m2) and birch steppe sandy banded forests (48–60 pcs./m2),and the lowest – in oak ravine thalweg forests (21–22 pcs./m2). Long-time average annual weight of a berry on all sample plots under review is almost the same and ranges within the frame of 0,8–0,9 g. The only exceptions are the sample plot 2 and the sample plot 8, where this value is 1,0 g and 1,2 g respectively. Besides that, the authors received forecasting data of yield of Rubus caesius berry-field in the main groups of types of forests of the steppe Pridonye. To hold accuracy analysis of obtained forecasting values there was also calculated and given long-time average annual yield of Rubus caesius on the sample plots under review according to data of field researches 2012–2017 years. The results of comparative analysis represent that the obtained forecasting values in all cases exceed data of actual yield. At the same time, it should be noted, that values, that have been calculated by quantity of sets per square meter of berry-fields by using coefficient of long-time average annual fruitfulness of fruits setting turned out more similar to actual data. Using for calculation the data of flowering has shown large differences from real values. Reference 1. Turchin, Т.Y. The forests of steppe Pridonye / Т.Y. Turchin, Т.А. Turchina. – Rostov-on-Don: Publishing office of Rost. University, 2005. – 204 p.

Category Classification of Tree States Using Visual Data Based on Fuzzy Logic

Introduction: A reliable assessment of tree condition directly affects the planning of economic indicators for the use of forest resources and ecological actions for forest protection. Therefore, the correct evaluation of the sanitary state of forest is very important. At present, the decisions that forest pathologists make about classifying trees or forest areas are based on visual inspection and their subjective knowledge about the tree features. Purpose: Development of a method for classifying the condition of a tree in terms of its crown density degree and other features, based on fuzzy logic with characteristic functions for linguistic variables such as “Crown density”, “Annual branch growth”, “Bark falling off” or “Shrinking branches”. Results: The proposed method classifies the tree condition using pine as an example. The method consists in preliminary image processing, including the removal of background objects, extraction of texture features as extended binary patterns, and application of a specially designed controller based on fuzzy logic. We propose four types of linguistic variables, with their respective terms. For these variables, characteristic functions are specified in tabular form and then approximated by smooth functions. A fuzzy logic controller allows you to obtain an objective assessment of the tree crown condition. Experimental studies confirm the effectiveness of the developed method. Practical relevance: The intelligent system of classifying the tree condition according to visual data can provide a significant support to plantation survey specialists. The proposed method allows you to improve the quality of forest monitoring, minimize the influence of human factor, and organize the forest protection in the best possible way.

Ecological-coenotic characteristics of <i>Cantharellus cibarius</i> Fr. and its tolerance to human impact in southern taiga and sub-taiga forests of the Kirov Region

The paper analyzes plant communities with Cantharellus cibarius Fr. in southern taiga and sub-taiga forests in the Kirov Region. Golden chanterelle occurs mostly in pure pine forests and pine forests mixed with spruce and birch of green-moss, lichen and cowberry types in young to maturing stands; the crown density is low or medium. Species richness of herbaceous-shrub storey in the studied communities varied from 5 to 29. The ecological preferences of C. cibarius, defined with Ellenberg (1974) scales, allow to characterize the species in the following way: temperate climate species, shade-resistant, rarely found in conditions of total shading; mesophyte regarding soil humidity, prefers acidic soils with low nitrogen, but, as an exception, marked on neutral soils rich in nitrogen. The differences in the species ecological preferences in conditions of southern taiga and sub-taiga are insignificant. The hemeroby index varied from 0,05 to 0,33 for the studied communities. The average share of species tolerant to human impact was 13,23%, and the share of anthropophobic species 86,77%. These data characterise C. cibarius as the species capable of tolerating moderate human impact in southern taiga subzone, but being less tolerant to human impact in sub-taiga areas and coniferous-broadleaved forests.

The extent of stunting in trees growing within car parks compared with those situated in peripheral landscaped areas in the UK

ABSTRACT Tree planting in towns and cities offers a range of important social, economic and environmental benefits; however, the harsh growing conditions of urban sites can substantially limit these benefits. This study investigated the effect of a car park environment upon the growth and development of trees planted within 13 sites in the UK. The size and condition of trees planted 11 to 27 years ago in restricted soil volumes surrounded by car park surfaces (n = 160) were compared to trees of the same age and species situated within the landscaped peripheries (n = 33) of 13 sites. Crown density was assessed at three sites planted with Acer platanoides L. as an additional measure of tree health. Analysis of stem diameter identified that trees in the landscaped areas exhibited 64.2% greater girth when compared to those planted in pits and 49.9% greater girth compared to those planted in strips within car park areas (excluding sites containing Platanus x acerifolia (Aiton) Willd., which coped well within car parks). Trees in peripheral landscaping areas were on average 20% taller in height and tree condition was significantly associated with estimated soil volumes. Sampled crown density also identified that the Norway maples within three car parks had around 30% sparser crowns than trees of the same species planted in adjacent landscaping areas. This study concludes that species and substrate conditions are crucial factors influencing the growth of most tree species in a car park setting. The stunted trees arising from inadequate car park design in the last three decades in the UK provide a sanguine lesson on how not to establish the urban forest of the future

Relevance of stem and crown defects to estimate tree vigour in northern hardwood forests

Abstract The visual assessment of tree vigour before partial cutting is a key element of the long-term sustainability of managed hardwood forests. Several classification systems have been developed and applied to perform this task during the tree marking process. They segregate trees in different vigour classes based on the presence and severity of stem and crown defects. Yet, the relevance of using these defects to assess tree vigour has rarely been empirically validated. In this study, we analysed the relationships between quantitative vigour indicators and a full range of individual defects using 336 sugar maple and 84 yellow birch trees. Among the tested defects, the tree crown density showed the best ability to identify slow growing, non-vigorous sugar maple trees, regardless of their size. However, none of the stem-related defects, such as bark aspect, the presence of cambial necrosis or conks and stromata were strongly related to our quantitative vigour indicators. For yellow birch, none of the stem defects and crown conditions were found to be related to our vigour indicators. We conclude that, pending longitudinal studies that will provide a full empirical validation of classification systems, crown density should be used to assess recent growth and vigour of sugar maple trees and guide tree marking.

Видове багатство дендрофлори та естетичне оцінювання фітоценозів парку смт Магдалинівка

Дендрофлора парку смт Магдалинівка налічує 347 прим., що належать до 19 видів і 15 родин. У насадженнях переважають Aesculus hippocastanum, Ulmus scabra, Betula pendula. Родини презентовані переважно 1-2 видами, за винятком Rosaceae. Родини Hippocastanaceae, Ulmaceae та Betulaceae мають найбільшу представленість за кількістю примірників, порівняно з іншими. Частка видів аборигенної дендрофлори становить 53,32 %. Найбільша частка від загальної кількості інтродуцентів становлять представники з Південної та Південно-Східної Європи. Переважна кількість дерев у насадженні має висоту від 8,1 до 10,0 м (23,3 % щодо всіх рослин). За діаметром штамба переважають дерева зі значеннями цього показника від 22,1 до 26,0 см (16,1 %), чисельними є групи рослин з діаметрами 26,1-30,0; 34,1-38,0 та від 18,1-22,0 см. Діаметр одного з найстаріших дерев парку Populus alba становить 108 см. За життєвим станом дещо більше половини насаджень належить до категорії "здорові", серед них багато примірників Betula рendula, Juglans regia, Ulmus scabra, Tilia cordata. До ослаблених належить 110 дерев, до сильно ослаблених – 43, до тих, що відмирають, – усього 6 шт. Індекс стану деревостану для парку становить 80,14, що характеризує його як здоровий. За екологічними вимогами асортимент парку тільки частково відповідає умовам зволоження території, проте майже повністю – родючості ґрунту. За таксаційно-фітоценотичною шкалою загальна естетичне оцінювання фітоценозу парку становить 31 бал. У парку ростуть дерева з вираженими фітонцидними властивостями, а саме: Acer platanoides, Betula pendula, Syringa vulgaris, а також Tilia cordata, Aesculus hippocastanum та Sorbus aucuparia.

Estimating aboveground forest carbon density using Landsat 8 and field-based data: a comparison of modelling approaches

ABSTRACTAccurately estimating and mapping forest aboveground carbon density (AGCD) is important for evaluating forest carbon sequestration efficiency and dynamics. This study compares different modelling approaches for estimating AGCD using Landsat 8 Operational Land Imager (OLI) imagery and field forest inventory data. We tested it in Yongshun County, Hunan Province, China. Linear regression (LR) and Random Forest (RF) were used to map crown density (CD). We fitted models with and without CD dummy variables for AGCD estimations. The fitting results and performances of these two types of AGCD models were analysed and compared. There was a difference in the estimation of remote-sensing-based CD models and AGCD models; the coefficients of determination (R2) were 0.66 for LR and 0.84 for RF, respectively, in CD estimations; R2 values were 0.46 for LR and 0.65 for RF, respectively, in AGCD estimations as indicated by basic AGCD models. RF was the best algorithm for CD and AGCD estimations. All of the dummy variable AGCD models provided more accurate AGCD estimates than their basic AGCD counterparts. The dummy variable models (DLR and DRF), which took the observed CD as a dummy variable, were the most accurate for the R2 were 0.61 and 0.85, respectively. The AGCD estimations were significantly overestimated and underestimated by basic AGCD models in thin and dense CD classes, respectively. Nevertheless, none of the AGCD estimates produced by any of the dummy variable models showed this problem. The models that used predicted CD as a dummy variable were more consistent with those that considered observed CD as a dummy variable. The accuracies of AGCD estimations were significantly improved by the dummy variable AGCD models, especially in thin and dense plots; in addition, the CD estimations produced by CD models could be used as dummy variables in AGCD remote-sensing-based models. This work provides that a method considering CD dummy variable in remote sensing-based models was reliable for mapping AGCD at a regional scale.

Characterizing variations in growth characteristics between Douglas-fir with different genetic gain levels using airborne laser scanning

In British Columbia, Canada, Douglas-fir [Pseudotsuga menziesii (Mirb.) Franco] selective breeding is used to develop genetically improved regeneration stock. To evaluate realized performance of improved stock, breeders take frequent measurements in genetic gain trials to determine whether yield gains are being met. Currently, variables collected focus on individual tree yield attributes; however, information generated from progeny test trials may not directly reflect plantation performance. Realized yield trials help to bridge the gap between progeny test estimated gain and plantation setting performance. High density airborne laser scanning (ALS) has the potential to identify variables that could improve the selection and validation process. We utilized ALS collected from an unmanned aerial system to assess performance of genetic improvement across three genetic levels and three stand spacings. ALS derived metrics were used to test three hypotheses: (1) tree height is correlated with the level of genetic superiority, (2) tree crown shape varies across genetic level, and (3) tree crown density is associated with genetic level. Random forest algorithms were used to identify candidate ALS metrics. To account for interaction effects, a two-way analysis of variance was conducted for each metric, followed by a post-hoc test to investigate significant differences between genetic level and spacing. The scale and shape parameters of Weibull probability density functions, vertical complexity index, and the fraction of euphotic voxels were found to be important metrics. Results show that genetically superior trees are typically taller, with higher, shorter and denser crowns. In addition, variation across genetic level may be indicative of greater phenotypic plasticity, as superior trees possess the ability to respond to tighter stand spacing.

Understanding Tree-to-Tree Variations in Stone Pine (Pinus pinea L.) Cone Production Using Terrestrial Laser Scanner

Kernels found in stone pinecones are of great economic value, often surpassing timber income for most forest owners. Visually evaluating cone production on standing trees is challenging since the cones are located in the sun-exposed part of the crown, and covered by two vegetative shoots. Very few studies were carried out in evaluating how new remote sensing technologies such as terrestrial laser scanners (TLS) can be used in assessing cone production, or in trying to explain the tree-to-tree variability within a given stand. Using data from 129 trees in 26 plots located in the Spanish Northern Plateau, the gain observed by using TLS data when compared to traditional inventory data in predicting the presence, the number, and the average weight of the cones in an individual tree was evaluated. The models using TLS-derived metrics consistently showed better fit statistics, when compared to models using traditional inventory data pertaining to site and tree levels. Crown dimensions such as projected crown area and crown volume, crown density, and crown asymmetry were the key TLS-derived drivers in understanding the variability in inter-tree cone production. These results underline the importance of crown characteristics in assessing cone production in stone pine. Moreover, as cone production (number of cones and average weight) is higher in crowns with lower density, the use of crown pruning, abandoned over 30 years ago, might be the key to increasing production in combination with stand density management.

Improving estimation of forest aboveground biomass using Landsat 8 imagery by incorporating forest crown density as a dummy variable

Optical remote sensing data are widely used in estimation of forest aboveground biomass (AGB), and the accuracy of AGB estimations has drawn wide attention. A method to improve the accuracy of remote sensing-based AGB models was developed by combining Landsat 8’s Operational Land Imager (OLI) and forest crown density (FCD). Remote sensing-based AGB models with and without an FCD dummy variable were developed using linear regression based on vegetation type (coniferous forest, broadleaf forest, mixed forest, and total vegetation). The differences between the models with and without an FCD dummy variable were analysed and compared. The models involving stratification of vegetation types provided more accurate estimations than the models of total vegetation. The models with an FCD dummy variable performed better than the models without an FCD dummy variable for each vegetation type. In each FCD class, the models with an FCD dummy variable provided more accurate estimations than the models without an FCD dummy variable, and the over- and underestimation problems associated with the models without an FCD dummy variable in thin and dense stands were significantly alleviated by the models with an FCD dummy variable. Therefore, introducing FCD into remote sensing-based AGB models has great potential to improve AGB estimation.

Influence of seasonal climatic factors on the dynamics of birds interactions with oaks consortia

The article is devoted to the bird communities in individual oak consortia (Quercus robur L.) of the linden-ash oak forests. This work material was collected during different seasons of the 2004–2010 years in a linden-ash oak grove on the test plot No. 209 of the ecological profile of the NSC «Bel'gard Prisamar`e International Biospheric stationary», Novomoskovsk district, Dnepropetrovsk region. The individual consortia of 281 examples of three age conditions oak trees (virgins – virg, young generative – gl, mature and old generative individuals – g2–g3) has been investigated. The daily time budget decreases by 2–2,5 times in autumn for all oak ages that have been studied. But the number of consort birds is reduced by 2 times only for virgin and old generative oaks. The young generative oak is attractive enough for birds in autumn. The ratio of the trophic and topical share interactions for all trees ages does not change significantly in autumn. Birds don’t interact with the virgin oak in winter practically. This age oak can’t propose enough food or places for birds’ protection from predators. Oaks in age g1–g3, on the contrary, are in demand by the birds. There 7 birds species on g1 oaks and 13 species on g2–g3 oaks were recorded in winter. The birds’ daily time buds for the one oak example are low in winter, and by the 90 times reduce compared with the summer. The bird time budget basis in winter are the trophic interactions. The birds’ activity on oak sharply increases in spring and exceeds 1,5–2 times the summer parameters on virgin and mature generative oak (g2–g3). Birds on oak spend most of their time on topical interactions during this season because of the oak important role in the birds reproduction. On the other hand, the young generative oak (g1) is not in demand by the birds in spring because of insufficient crown density and the oaks of this age location at the edge. The number of bird species on oak in spring is less than in summer due to the late onset of leaf blooming on the oak. A significant part of the birds’ activity in the spring moves to the lower tier of the forest because of the earlier vegetation beginning. As a result of the research, it was revealed that the consorting groups of common oak throughout the year retain the main features of their organization. The virgin oak is characterized by a stochastic nature of the birds interaction with the consortium core and almost hasn’t obligate consort birds. Young generative oak is actively forming a trophic relations system with consorts due to intensive linear growth. At this age, first of all, general indicators are formed – time and mass budgets. The consortium of mature and old generative oak has a significantly larger number of bird species consorts and their interactions diversity with the tree. This can help to increase the stability of consorting groups. In most cases in the oak consortium the trophic component of the consortium form earlier then the topical. The specific location of the virgin and young generative oak at the lit positions in the lime-ash oak forests influences the oak consortia formation in a considerable scale. The number of types of interactions between the consort and the autotroph is the most effective indicator, which shows a high level of the consortium development. The stability of consortial relations between birds and English oak grows throughout the year from virgin oak to mature and old generative. The virgin oak unstable consorting groups have fluctuations of the species number during the year up to 100 % (the number of consort species in summer was chosen as the initial value). The consortia species composition fluctuations reach 81,82 % for young generative oak, and 59,26 % – for mature and old generative oak. The mature and old generative oak consortia attract seasonal bird species that replace each other throughout the year more actively. This ensures the stability of year-round control of phytophage populations.