Estimate Tree Density Research Articles

Examination of Drone Usage in Estimating Hardwood Plantations Structural Metrics

Planting hardwood trees on retired marginal agricultural land is one of the main strategies used to restore forested wetlands. Evaluating effectiveness of wetland restoration requires efficient monitoring to evaluate recovery trajectories and desired conditions. Recent advancements in unmanned aerial system (UAS) technologies have prompted wide-scale adoption of UAS platforms in providing a range of ecological data. In this study, we examined the use of UAS Structure from Motion (SfM) derived point clouds in estimating tree density, canopy height, and percent canopy cover for bottomland hardwood plantations within four wetland reserve easements. Using a local maxima approach for individual tree detection produced plantation level estimates with mean absolute errors of 150 trees per hectare, 0.5 m, and 18.4% for tree density, canopy height, and percent canopy cover, respectively. At the plot level, UAS-derived tree counts (r = 0.53, p < 0.01) and canopy height (r = 0.57, p < 0.01) were significantly correlated with ground-based estimates. We demonstrate that UAS-SfM is a viable method of assessing bottomland hardwood plantations for applications that require precision levels congruent with the mean absolute errors reported here. The accuracy of tree density estimates was reliant upon specific local maxima window parameters relative to stand conditions. Therefore, acquisition of leaf-off and leaf-on imagery may allow for better individual tree detection and subsequently more accurate tree density and other structural attributes.

Long-term field evaluation of Pera sweet orange selections under the Brazilian humid subtropical climate

Currently, a low number of citrus varieties are commercially planted to supply the Brazilian citrus industry demand. The diversification of citrus scion and rootstock varieties is an important strategy to prevent disease outbreaks and to obtain higher off-season profits, as well as to extend fruit supply for the citrus processing industry. The aim of this study was to evaluate 16 Pera sweet orange selections (Citrus ×sinensis Osbeck) under a humid subtropical climate in the northwest region of the state of Paraná, Brazil regarding tree development, production, and disease incidence. The experimental orchard was planted in December 2012 in a randomized block design with three replications and five trees per plot. All scions were grafted on Rangpur lime rootstock (C. ×limonia Osbeck). The evaluations were performed from 2016 through 2022, and included vegetative growth, yield, fruit quality, estimated tree density and productivity for new plantings, and incidence of diseases as citrus canker, huanglongbing (HLB), and citrus tristeza virus (CTV). All data was submitted to ANOVA and means grouped by the Scott Knott’s test (p ≤ 0.05). Pera Perão was the most vigorous variety, with the heaviest and largest fruit, and was among the selections with the highest content of soluble solids (SS), titratable acidity (TA) and juice. However, this variety showed a light-yellow juice color, and one of the lowest SS·TA−1 ratio. This selection had the lowest percentage of fruits with citrus canker but was among the selections with the highest HLB incidence. The selections Ovale, Clone 9, and Clone 42 also showed higher vegetative growth and fruit length, but lower SS content, juice yield and technological indices. All other Pera selections had lower tree height and canopy volume than Ovale, Clone 9, and Clone 42, and adequate overall fruit quality. Conversely, Pera Comprida, Dibbern, Morretes, and Seleç ão 12 scored lower cumulative fruit yield. Pera Pirangi and Comprida had the highest citrus canker incidence on fruits, while Morretes, Ovo, Pirangi, Seleç ão 12, and Seleç ão 27 had the highest HLB incidence alongside Perão. Low severity level of stem pitting was observed within the evaluated selections. The scores ranged from one (absence of stem pitting) to two (sparse surface stem pitting). IAC, Olímpia, Mel, Bianchi, and IPR 159 revealed to be the most suitable for new plantings under humid subtropical edaphoclimatic conditions, as trees had small vegetative growth, high yield performance and fruit quality, in addition to showing lower incidences of citrus canker, HLB and CTV.

Trifoliate Orange-Related Rootstocks Enhance the Horticultural Performance of ‘Shamouti’ Sweet Orange under Humid Subtropical Condition

The narrow genetic pool for both scions and rootstocks used in the Brazilian orchards makes the citrus industry vulnerable to biotic and abiotic threats. Orchard diversification by using different scion–rootstock combinations is an efficient measure to promote citrus protection, through increasing the level of genetic diversity. In this paper, we report the horticultural performance of the mid-season ‘Shamouti’ sweet orange grafted on five different rootstocks (‘Rangpur’ lime, ‘Swingle’ citrumelo, ‘C-13′ citrange, and ‘Cleopatra’ and ‘Sunki’ mandarins) in a long-term experiment (2007–2017) under the Brazilian humid subtropical condition. ‘Shamouti’ trees were assessed for vegetative growth, yield, and fruit quality. Additionally, a study was performed to estimate tree density and yield for new plantings. Trees grafted on ‘Swingle’ and ‘C-13′ rootstocks were less vigorous and more productive, with cumulative yields of &gt;480 kg per tree, allowing high-density plantings (363–337 trees·ha−1). Trees on ‘Cleopatra’, ‘Sunki’, and ‘Rangpur’ were the most vigorous among the tested rootstocks, with tree heights &gt; 4.20 m. However, they took longer to establish in the field, evidenced by their growth progress. These combinations also displayed the lowest tree density estimation (≤311 trees·ha−1). Trees on ‘Cleopatra’ exhibited the lowest cumulative yield (255 kg per tree). Although some significant differences were found for fruit quality, all rootstock combinations produced fruit of suitable quality, attending the commercial grading. Our findings evidence the potential of the trifoliate orange-related rootstocks ‘C-13′ and ‘Swingle’ to be used as promising rootstocks for ‘Shamouti’ cultivation in the humid subtropics, promoting genetic diversification and enhancing yield and tree density in new orchards.

Fuelwood Production and Carbon Sequestration in Public Urban Green Spaces in Bulawayo, Zimbabwe

Trees in public urban green spaces provide a variety of ecosystem goods and services that are greatly appreciated by urban residents. A commonly used good, especially in Global South regions, is that of fuelwood for household energy needs. Yet the production potential of fuelwood from public urban green spaces has rarely been examined. This study quantifies the fuelwood production and allied carbon sequestration potential of 12 public urban green spaces in Bulawayo (Zimbabwe) stratified across neighborhoods of different housing densities. We estimated tree density in the green spaces by means of line transects, and annual production through estimates of the mean annual increment of a sample of marked trees. We found that Bulawayo’s public green spaces produce 1.9 t/ha/yr of fuelwood with a value of $340 to $490/ha/yr, and that production varied across spaces and housing density neighborhoods. This production is much lower than the documented demand but it is likely to be significant for fuelwood-dependent households. In contrast, the amount (1010 ± 160 kg/ha/yr) and value (US$4.04/ha/yr) of carbon sequestration were lower. Formal public green spaces produced more fuelwood as compared to informal green spaces and no difference was evident in tree growth rates between exotic and indigenous tree species. This is one of the first studies to show the value of the fuelwood production and carbon sequestration potential of public green spaces in the region and continent and requires that they are integrated into public urban green space policies, planning, and management in the city.

Using Leaf-Off and Leaf-On Multispectral Airborne Laser Scanning Data to Characterize Seedling Stands

Information from seedling stands in time and space is essential for sustainable forest management. To fulfil these informational needs with limited resources, remote sensing is seen as an intriguing alternative for forest inventorying. The structure and tree species composition in seedling stands have created challenges for capturing this information using sensors providing sparse point densities that do not have the ability to penetrate canopy gaps or provide spectral information. Therefore, multispectral airborne laser scanning (mALS) systems providing dense point clouds coupled with multispectral intensity data theoretically offer advantages for the characterization of seedling stands. The aim of this study was to investigate the capability of Optech Titan mALS data to characterize seedling stands in leaf-off and leaf-on conditions, as well as to retrieve the most important forest inventory attributes, such as distinguishing deciduous from coniferous trees, and estimating tree density and height. First, single-tree detection approaches were used to derive crown boundaries and tree heights from which forest structural attributes were aggregated for sample plots. To predict tree species, a random forests classifier was trained using features from two single-channel intensities (SCIs) with wavelengths of 1550 (SCI-Ch1) and 1064 nm (SCI-Ch2), and multichannel intensity (MCI) data composed of three mALS channels. The most important and uncorrelated features were analyzed and selected from 208 features. The highest overall accuracies in classification of Norway spruce, birch, and nontree class in leaf-off and leaf-on conditions obtained using SCI-Ch1 and SCI-Ch2 were 87.36% and 69.47%, respectively. The use of MCI data improved classification by up to 96.55% and 92.54% in leaf-off and leaf-on conditions, respectively. Overall, leaf-off data were favorable for distinguishing deciduous from coniferous trees and tree density estimation with a relative root mean square error (RMSE) of 37.9%, whereas leaf-on data provided more accurate height estimations, with a relative RMSE of 10.76%. Determining the canopy threshold for separating ground returns from vegetation returns was found to be critical, as mapped trees might have a height below one meter. The results showed that mALS data provided benefits for characterizing seedling stands compared to single-channel ALS systems.

Carbon stock assessment using forest canopy density mapper in agroforestry land in Berau, East Kalimantan, Indonesia

Abstract. Hartoyo APP, Prasetyo LB, Siregar IZ, Supriyanto, Theilade I, Siregar UJ. 2019. Carbon stock assessment using forest canopy density mapper in agroforestry land in Berau, East Kalimantan, Indonesia. Biodiversitas 20: 2661-2676. In the Reducing Emissions from Deforestation and forest Degradation (REDD+) program, remote sensing is the most important tool for measuring forest cover and carbon dynamic, including the utilization of software Forest Canopy Density (FCD) mapper. However, there have been rarely untested the accuracy of FCD applied in agroforestry landscapes to support carbon stock assessment compared to conventional field measurement data. This research was aimed to investigate the correlation between: (i) the value of FCD (%) and tree stand density (N/ha), (ii) the value of FCD (%) and basal area (m2/ha), (iii) the value of FCD (%) and total carbon stock (Mg C/ha), and iv) total carbon stock and percentage of canopy closure (%). Tree stand density, basal area, carbon stock and canopy profile were conventionally measured by trained members of local communities. The results of this study showed that the R2 between FCD and tree density was 37.7% (r = 61.4%), while the R2 between FCD and the basal area was 3.33% (r = 18.3%). The result of normality and heteroscedasticity tests showed that FCD was more accurate and precise in estimating the tree stand density model than the basal area model. Total carbon stock differed significantly (p&lt;0.1) from tree density with R2 = 27.7% (r = 27.3%). Total carbon can be predicted using FCD with total carbon (Mg C/ha) = 13.005 + 0.826 FCD. Our findings suggest that FCD can be used as a new method to estimate tree density and total carbon stock cheaply, efficiently and accurately to support carbon stock assessment in agroforest practices. In carbon assessment, total carbon stock can also be estimated using canopy closure measurement.

Estimating tree height from TanDEM-X data at the northwestern Canadian treeline

The circum-Arctic transitional zone between forest and tundra, i.e. the treeline zone, is shifting northward due to current Arctic warming and, therefore, requires systematic monitoring. Up to now, radar remote sensing was hardly possible in the treeline zone due to spatial resolution and/or temporal decorrelation constraints of preceding satellite missions. The unique constellation of the TanDEM-X satellites with its bistatic mode and very high spatial resolution opens up opportunities for monitoring small (≥0.01 km2) and isolated patches of very sparse forest which are typical for the transitional zone. We focused on an area at the northern edge of the treeline zone in the Northwest Territories, Canada, and evaluated the potential of TanDEM-X bistatic data to characterize the tree height in the forest patches in this region. TanDEM-X data were acquired during the TanDEM-X Science Phase in 2015, when the perpendicular baseline was large (corresponding to the height of ambiguity of approximately 14.6 m) and kept constant. We employed TanDEM-X backscatter, bistatic coherence, and interferometric height from the stack of seven multitemporal bistatic pairs and compared them to maximum vegetation height obtained from full-waveform airborne LiDAR data. We found strong linear relationships between all TanDEM-X metrics and LiDAR vegetation height within the forest patches with r = 0.67, r = −0.69, and r = 0.78 for the backscatter, coherence, and interferometric height, respectively. Furthermore, we extracted the position of individual trees from the LiDAR data and estimated tree density as the number of trees per unit area. The linear relationships between all TanDEM-X metrics and the tree density were very weak. The relationships between all TanDEM-X metrics and tree height differentiated for three tree density classes (low, medium, and high) remained strong. Random forests regression using all three TanDEM-X metrics predicted the tree height with a mean absolute error of 0.7 m (mean forest height in the study area was 2.5 m). CoSSC pairs were generally consistent with each other and the multitemporal averaging slightly improved the performance compared to single pairs. Taking into account the global coverage of bistatic TanDEM-X data acquired for the global digital elevation model, our results show a potential for quantifying the tree height in small forest patches along the circum-Arctic treeline zone.

AGROFORESTRY TREE DENSITY ESTIMATION BASED ON HEMISPHERICAL PHOTOS &amp; LANDSAT 8 OLI/TIRS IMAGE: A CASE STUDY AT CIDANAU WATERSHED, BANTEN-INDONESIA

Abstract. The Cidanau watershed is the only watershed in Indonesia that implements Payment for Environmental Services (PES) for farmers who can maintain tree/stand density of 500 trees/hectare on their land. Payments are made upon the verification on the field by the project supervisor. This method requires a lot of time and costly, so it is necessary to build more efficient indirect methods, including using satellite imagery or camera data. The aim of this study is to understand Landsat OLI 8 and hemispherical photo can estimate tree density in the farmer’s agroforestry stand. To obtain tree density, the number of trees with diameter more than 10 cm in 50 plots (50 m x 50 m) were counted. Some predictor variables were utilized, such as Leaf Area Index (LAI) based on hemispherical photos, Normalized Difference Vegetation Index (NDVI), Forest Cover Density (FCD), as well as NDVI and FCD which were enhanced with topographic correction. The imagery used was Landsat 8 OLI acquired on July 5, 2015, with Path/Row 123/64. The relationship between tree density and predictor variables was done using linear regression analysis. Prior to regression analysis, normality (Kolmogorov Smirnov/K-S), heteroscedasticity (Glejser test) and auto correlation (Durbin Watson) test were performed. The results of the analysis showed that tree density was estimated better with hemispherical photos-based LAI, with determination coefficient of 80.6%. Meanwhile, estimation using NDVI and FCD has lower determination coefficient. Even though, the use of topographic correction had been able to increase the determination coefficient of the regression relationship between tree density and FCD, from 4.64% to 35.18%.

Mapping Tree Density in Forests of the Southwestern USA Using Landsat 8 Data

The increase of tree density in forests of the American Southwest promotes extreme fire events, understory biodiversity losses, and degraded habitat conditions for many wildlife species. To ameliorate these changes, managers and scientists have begun planning treatments aimed at reducing fuels and increasing understory biodiversity. However, spatial variability in tree density across the landscape is not well-characterized, and if better known, could greatly influence planning efforts. We used reflectance values from individual Landsat 8 bands (bands 2, 3, 4, 5, 6, and 7) and calculated vegetation indices (difference vegetation index, simple ratios, and normalized vegetation indices) to estimate tree density in an area planned for treatment in the Jemez Mountains, New Mexico, characterized by multiple vegetation types and a complex topography. Because different vegetation types have different spectral signatures, we derived models with multiple predictor variables for each vegetation type, rather than using a single model for the entire project area, and compared the model-derived values to values collected from on-the-ground transects. Among conifer-dominated areas (73% of the project area), the best models (as determined by corrected Akaike Information Criteria (AICc)) included Landsat bands 2, 3, 4, and 7 along with simple ratios, normalized vegetation indices, and the difference vegetation index (R2 values for ponderosa: 0.47, piñon-juniper: 0.52, and spruce-fir: 0.66). On the other hand, in aspen-dominated areas (9% of the project area), the best model included individual bands 4 and 2, simple ratio, and normalized vegetation index (R2 value: 0.97). Most areas dominated by ponderosa, pinyon-juniper, or spruce-fir had more than 100 trees per hectare. About 54% of the study area has medium to high density of trees (100–1000 trees/hectare), and a small fraction (4.5%) of the area has very high density (&gt;1000 trees/hectare). Our results provide a better understanding of tree density for identifying areas in need of treatment and planning for more effective treatment. Our analysis also provides an integrated method of estimating tree density across complex landscapes that could be useful for further restoration planning.

ESTRUTURA ARBÓREA E SAZONALIDADE DA COBERTURA DO DOSSEL EM VEGETAÇÃO FLORESTADA E ABERTA NO PARQUE NACIONAL SERRA DE ITABAIANA, SERGIPE, BRASIL

As florestas de areias brancas quartzosas constituem um tipo de ecossistema oligotrófico, cujos caracteres fitofisionômicos são afetados pela sazonalidade climática. Entre tais características está a abertura do dossel, cujas variações influenciam na distribuição espacial da luz solar no ambiente. Este estudo avaliou e comparou a estrutura da vegetação e as alterações sazonais do dossel em habitat de areias brancas do Parque Nacional Serra de Itabaiana, Sergipe. Os dados foram coletados em dois ambientes: vegetação aberta de areias brancas strictu sensu (VA) e mata fechada de vegetação ripária (MR). Para estimar a densidade arbórea utilizou-se o método quadrante, no qual foram amostradas árvores com CAP ≥ 5 cm. Para avaliar a dinâmica do dossel foram estabelecidos, em cada área, dois transectos compostos por cinco pontos equidistantes 20 m, totalizando 10 pontos por ambiente. Em cada ponto foram obtidas fotografias hemisféricas do dossel nos meses de janeiro (seca) e junho (chuva). As imagens foram analisadas pelo software Gap Light Analyzer, sendo avaliadas as variáveis abertura do dossel e índice de área foliar (IAF). A vegetação ripária apresentou densidade arbórea de 498 ind ha-1 e a vegetação aberta 296 ind ha-1. Esta última, não evidenciou variações na abertura do dossel (t = 2,0146; p &gt; 0,05) e no IAF (t = -2,0052; p &gt; 0,05) entre os períodos de chuva (52,24% ± 18,13% e 0,68 ± 0,45) e seca (67,39% ± 15,38% e 0,36 ± 0,23). Na mata ripária, a abertura do dossel (t = 7,1739; p &lt; 0,05) e o IAF (t = -5,1609; p &lt; 0,05) variou entre os períodos de chuva (13,70% ± 2,24% e 2,13 ± 0,23) e seca (21,08% ± 2,36% e 1,63 ± 0,20). As diferenças observadas destacam a heterogeneidade ambiental na Serra de Itabaiana e demonstram que as formações florestais de areias bancas respondem de maneira distinta à sazonalidade hídrica deste ecossistema. Por estar localizada em uma área de ecótono entre floresta perene e Floresta Estacional Semidecidual, a mata ripária tende a perder parte de suas folhas durante o período seco. Além disso, o padrão de distribuição das plantas pode contribuir para as diferenças entre os habitat estudados.

Tree Density and Forest Productivity in a Heterogeneous Alpine Environment: Insights from Airborne Laser Scanning and Imaging Spectroscopy

We outline an approach combining airborne laser scanning (ALS) and imaging spectroscopy (IS) to quantify and assess patterns of tree density (TD) and forest productivity (FP) in a protected heterogeneous alpine forest in the Swiss National Park (SNP). We use ALS data and a local maxima (LM) approach to predict TD, as well as IS data (Airborne Prism Experiment—APEX) and an empirical model to estimate FP. We investigate the dependency of TD and FP on site related factors, in particular on surface exposition and elevation. Based on reference data (i.e., 1598 trees measured in 35 field plots), we observed an underestimation of ALS-based TD estimates of 40%. Our results suggest a limited sensitivity of the ALS approach to small trees as well as a dependency of TD estimates on canopy heterogeneity, structure, and species composition. We found a weak to moderate relationship between surface elevation and TD (R2 = 0.18–0.69) and a less pronounced trend with FP (R2 = 0.0–0.56), suggesting that both variables depend on gradients of resource availability. Further to the limitations faced in the sensitivity of the applied approaches, we conclude that the combined application of ALS and IS data was convenient for estimating tree density and mapping FP in north-facing forested areas, however, the accuracy was lower in south-facing forested areas covered with multi-stemmed trees.

Evaluating a new method for reconstructing forest conditions from General Land Office survey records.

Historical forest conditions are often used to inform contemporary management goals because historical forests are considered to be resilient to ecological disturbances. The General Land Office (GLO) surveys of the late 19th and early 20th centuries provide regionally quasi-contiguous data sets of historical forests across much of the Western United States. Multiple methods exist for estimating tree density from point-based sampling such as the GLO surveys, including distance-based and area-based approaches. Area-based approaches have been applied in California mixed-conifer forests but their estimates have not been validated. To assess the accuracy and precision of plotless density estimators with potential for application to GLO data in this region, we imposed a GLO sampling scheme on six mapped forest stands of known densities (159-784 trees/ha) in the Sierra Nevada in California, USA, and Baja California Norte, Mexico. We compared three distance-based plotless density estimators (Cottam, Pollard, and Morisita) as well as two Voronoi area (VA) estimators, the Delincé and mean harmonic Voronoi density (MHVD), to the true densities. We simulated sampling schemes of increasing intensity to assess sampling error. The relative error (RE) of density estimates for the GLO sampling scheme ranged from 0.36 to 4.78. The least biased estimate of tree density in every stand was obtained with the Morisita estimator and the most biased was obtained with the MHVD estimator. The MHVD estimates of tree density were 1.2-3.8 times larger than the true densities and performed best in stands subject to fire exclusion for 100yr. The Delincé approach obtained accurate estimates of density, implying that the Voronoi approach is theoretically sound but that its application in the MHVD was flawed. The misapplication was attributed to two causes: (1) the use of a crown scaling factor that does not correct for the number of trees sampled and (2) the persistent underestimate of the true VA due to a weak relationship between tree size and VA. The magnitude of differences between true densities and MHVD estimates suggest caution in using results based on the MHVD to inform management and restoration practices in the conifer forests of the American West.

Revisiting Fraser's Triangles as the Basis for Estimating Tree Density, Spatial Distribution, and Stocking

Revisiting Fraser's Triangles as the Basis for Estimating Tree Density, Spatial Distribution, and Stocking

Forest certification as a policy option in conserving biodiversity: An empirical study of forest management in Tanzania

Forest certification management standards aim at maintaining forest ecosystem integrity, including forest biodiversity conservation. However, studies from the Amazon and Congo basin find that forest certification may not protect forest biodiversity and ecosystems, and may therefore be unsustainable. This study evaluates the influence of forest certification on conserving biodiversity. Specifically, we (a) estimate tree (adult and seedling) species richness, diversity and density among different forest management regimes; (b) assess the relationship between environmental and human forest use variables, and species richness, diversity and density among the forest management regimes; and (c) assess the influence of forest governance of villages adjacent to the forests on tree (adult and seedling) species richness, diversity and density among the forest management regimes. This is achieved in a comparative study of Forest Stewardship Council certified community forests, non-certified open access forests, and non-certified state forest reserves in the Kilwa District in Tanzania.Our results show that forest certification standards and implementation processes are positively related to biodiversity conservation. There are significantly higher tree (adults) species richness, diversity, and density in certified community forests than in open access forests and state forest reserves. These findings suggest that forest certification may be a good policy option to conserve biodiversity. The present study is one of the first studies in tropical Africa, which contributes to the limited data on the influence of forest certification on conserving biodiversity. Our results may also serve as baseline for further research on the contribution of certified forests in conserving biodiversity at both temporal and spatial scales.

Triangle Method: A New Distance Method for Density Estimation

Quantitative data are essential in characterizing vegetation. Considerable attention has been paid to vegetation sampling techniques. A series of methods have been developed for tree density estimation which utilize spacing distances instead of fixed-area quadrats. In this paper, a new plotless sampling method was proposed which we denominated a triangle method. With the new method and a conventional distance method (point-centred quarter method), we investigated Larixprincipis-rupprechtii population in larch forests at Xiaolongmen Forest Station of Donglingshan Mountain, Beijing. Compared the two methods with quadrat method, not only the accuracy, but also the precision of the new method are better than the old one. The results indicate that the new method is adequate to estimate tree density and easy to use in wood engineering and forest survey work.

Characteristics and Growing Stocks Volume of Forest Stand in Dry Temperate Forest of Chilas Gilgit-Baltistan

Chilas forest sub division in Diamer district, of Gilgit-Baltistan is located at northern regions of Pakistan. We estimated tree density, diameter, height and volume of the dominant tree species in four blocks (Thore, Chilas, Thak Niat and Gunar) of Chilas forest sub division. The tree density of deodar was maximum with average 26 tree·ha-1 and minimum was of Chalgoza 4 trees·ha-1. The maximum average height showed by the dominant species (Fir, Kail, Deodar, and Chilgoza) of the study area to be 20.40, 16.06, 12.24 and 12.12 m respectively. Moreover the average maximum volume attained by the Kail, Fir, Deodar and Chalgoza trees was 1.92, 1.57, 0.46 and 0.291 m3·tree-1 respectively. Regression analysis was carried out to determine the relationship between diameter (cm), height (m), tree density (trees·ha-1) and volume (m3·ha-1). The findings of the study will help the future scientific management of the forest for sustained yield. The study also provides information about the unexplored growing stock and structure of the forests. Additionally, this study will help to understand the patterns of tree species composition and diversity in the northern part of Pakistan with dry temperate climate.

PPBio Australasia Long Term Ecological Research Sites – flora and fauna database

PPBio (Program for Planned Biodiversity and Ecosystem Research) Australasia Long Term Ecological Research Sites (GIVD ID AU-AU-001) is a system for long-term ecological research (LTER) designed to answer integrated multidisciplinary research questions. PPBio was developed in Brazil with a broad aim of establishing a cost-effective and efficient network of standardized LTER plots to collect comparable information on biodiversity and ecosystem processes around the world. Infrastructure includes permanent plots that follow contour lines (survey lines with all measurements recorded on the horizontal plane) which facilitate orthorectification and validation of satellite imagery. Grids and modules consist of arrays of plots located one kilometre apart (or 500 metres at small sites). Each plot has a 250 metre midline that is permanently marked at 10 m intervals. Plot width varies to suit the taxon or abiotic variable being examined. Small and/or numerous taxa are surveyed in narrow plots (e.g. frogs, reptiles, herbs and grasses are within a 2 m strip on one side of the midline) while wide plots are used for larger or more dispersed organisms (e.g. large trees, birds or small mammals). Low density species (e.g. large mammals such as monkeys, koalas and kangaroos) and additional environmental variables are monitored using the series of grid trails that connect the plots, using standardized sampling methodologies. The first PPBio LTER site at Karawatha Forest Park in Brisbane City (Queensland, Australia) was established in 2007. A second site was established at Lake Broadwater in the Brigalow Belt in 2008. The establishment of a third grid in Chitwan National Park in Nepal was initiated in 2009. A fourth grid with 40 plots was established in Currawinya National Park (western Queensland, Australia) in 2010, and a fifth project establishing modules at Cooloola in the Great Sandy National Park commenced in 2010. To date, vegetation has been measured at four sites (with approximately 99 one hectare plots now completed). Repeat surveys will provide data on vegetation productivity through time. All woody stemmed trees and shrubs are individually tagged and identified within each plot. A hierarchical design was used to sample trees of different size classes in order to estimate tree density. The diameter at breast height (DBH) was measured at 130 cm unless disfigurement made this impossible. Large trees (DBH ≥ 30 cm) were sampled to 20 m either side of the midline (40 m x 250 m ≈ 1 ha). Trees with DBH ≥10 cm were sampled within 10 m either side of the midline (20 m x 250 m ≈ 0.5 ha). All woody stems with DBH ≥1 cm were sampled along a 4 m strip on the right hand side of the midline (4 m x 250 m ≈ 0.1 ha). The location of each tree is recorded in relation to its distance along the transect and distance from the transect. All trees are given an individual identifying number which is tagged to the tree and recorded in the vegetation database.

Small-scale variation of vegetation in a mixed forest understorey is partly controlled by the effect of overstory composition on litter accumulation

We investigated how richness and composition of vascular plant species in the understory of a mixed hardwood forest stand varied with respect to the abundance and composition of the overstory. The stand is in central Spain and represents the southernmost range of distribution of several tree and herbaceous species in Europe. Understory species were identified in 46 quadrats (0.25 m2) where variables litter depth and light availability were measured. In addition, we estimated tree density, basal area, and percent basal area by tree species within 6-m-radius areas around each plot. Species richness and composition were studied using path analysis and scale-dependent geostatistical methods, respectively. We found that the relative abundance of certain trees species in the overstory was more important than total overstory abundance in explaining understory species richness. Richness decreased as soil litter depth increased, and soil litter increased as the relative proportion of Fagus sylvatica in the overstory increased, which accounted for a negative, indirect effect of Fagus sylvatica on richness. Regarding understory species composition, we found that some species distributed preferentially below certain tree species. For example, Melica uniflora was most frequent below Fagus sylvatica and Quercus petraea while the increasing proportion of Q. pyrenaica in the overstory favored the presence of Cruciata glabra, Arenaria montana, Prunus avium, Conopodium bourgaei, Holcus mollis, Stellaria media and Galium aparine in the understory. Overall, these results emphasize the importance of individual tree species in controlling the assemblage and richness of understory species in mixed stands. We conclude that soil litter accumulation is one way through which overstory composition shapes the understory community.

Integrating Grouse Habitat and Forestry: An Example Using The Ruffed Grouse Bonasa umbellus in Minnesota

We quantified forest stand attributes at ruffed grouse Bonasa umbellus drumming display sites to develop tree stocking guides as a tool for guiding ruffed grouse management. We estimated tree density and basal area surrounding grouse drumming sites and compared these with unused sites. We used model selection to assess predictions about whether tree density and basal area surrounding drumming sites varied by site classification (primary drumming site, alternate site, unused site) or forest type. We plotted the predicted values from the best model on tree stocking guides, which are tools commonly used by forest managers. Tree density and basal area varied by site classification and by forest type. Our results show that stem density was higher and basal area lower at both primary and alternate drumming sites compared to unused sites in all forest types. We also found that grouse site si n aspen stands had a greater stem density and lower basal area than grouse sites in pine and spruce/fir stands. Incorporating these results into a tree stocking guide suggested that management for grouse in aspen stands should attempt tomaintainstandswithaveragestem densityandbasalareaforthisspecies.In contrast, foresters who are managing for conifers and also wish to maintain some grouse habitat should favour wider spacing of trees in stands. Wider spacing will encourage the development of dense understory vegetation favoured by grouse as well as enhance the growth of quality saw-logs. Our study describes a method for incorporating habitat data on ruffed grouse and other wildlife into tree stocking charts, which are commonly used to facilitate management of forest stands.

Estimation of the density of a clustered point pattern using a distance method

Distance-based methods use point-to-point distances or random-location-to-point distances in a cloud of points to estimate characteristics of the point pattern. One such characteristics is the density of points. The difficulty with distance-based density estimators is that their distribution depends on the spatial pattern of points. In particular, the distribution of distances is untractable for usual clustered patterns, that are often observed in natural systems. Here, we propose a density estimator for clustered patterns, based on the random-location-to-pth-point distance X p . An approximate expression for the distribution function, F p , of X p was obtained by identifying the first two moments of the count of individuals in disks for a given point process with the first two moments of a negative binomial distribution. The approximate expression of F p was then used to derive a maximum-likelihood estimator of the intensity of the point process. The quality of the approximation of F p was assessed for homogeneous Poisson processes (for which the expression of F p is exact) and for Matern processes. The intensity estimator based on Matern processes was then used to estimate tree density in a tree savanna in Mali, and it compared favorably with six robust estimators found in the literature.