Intraspecific Competition Affects Crown and Stem Characteristics of Non-Native Quercus rubra L. Stands in Germany

Accurate guidelines for silvicultural management of exotic tree species in Germany are sparse. For example, northern red oak (Quercus rubra L.) is the most commonly planted exotic deciduous tree species in Germany, but its response to varying levels of competition intensity has not yet been adequately explored. Here, we used terrestrial laser scanning to non-destructively examine the responses of stem and crown characteristics of Quercus rubra to intraspecific competition. A total of 100 dominant red oak trees were investigated in ten pure red oak stands, located in five federal states of Germany. The external stem quality characteristics namely stem non-circularity and bark anomalies decreased with increasing tree competition. Also, the crown characteristics crown volume, crown surface area, maximum crown area, crown length, and branch length declined by the degree of individual tree competition. We conclude that individual tree properties can be controlled by competition intensity, resulting in improved timber quality as shown for other tree species.

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Tree segmentation and classification of deciduous park trees in Sanssouci Park, Potsdam, Germany, using airborne and terrestrial lidar point clouds

10.5194/egusphere-egu21-8689 ◽

2021 ◽

Author(s):

Aljoscha Rheinwalt ◽

Bodo Bookhagen

Keyword(s):

Tree Species ◽

Supervised Classification ◽

Spatial Scales ◽

Point Clouds ◽

Airborne Lidar ◽

Deciduous Tree ◽

Individual Tree ◽

Terrestrial Lidar ◽

Common Tree

While automated, lidar-based tree delineation has proven successful for conifer-dominated forests, deciduous tree stands remain a challenge. &#160;But automatic and reliable segmentation of trees at large spatial scales is a prerequisite for a supervised classification into tree species. We propose an aspect driven tree segmentation that clusters local elevation minima across different aspects. These clusters define tree outlines that respect tree inherent local elevation minima. We validate this approach with more than 25.000 mapped trees of the Sanssouci Park, Potsdam, using an airborne lidar point cloud collected in 2018, and various terrestrial lidar scans for a large fraction of the same park. Further, we demonstrate the tree segmentation by supervised tree species classifications for the most common tree species using random forests and Gaussian process classifiers with geometric parameters derived from individual tree crowns.

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Oak Forest Composition on Contrasting Soil Types at the Mohonk Preserve, Eastern New York

Northern Journal of Applied Forestry ◽

10.1093/njaf/27.3.105 ◽

2010 ◽

Vol 27 (3) ◽

pp. 105-109 ◽

Cited By ~ 1

Author(s):

Marc D. Abrams ◽

Benjamin A. Sands

Keyword(s):

New York ◽

Tree Species ◽

Quercus Rubra ◽

Management Strategies ◽

Parent Material ◽

Soil Types ◽

Forest Composition ◽

Red Oak ◽

Red Maple ◽

Overstory Composition

Abstract This research investigated overstory and understory forest composition for 10 sites derived from either shale or sandstone conglomerate parent material on the Shawangunk Ridge in eastern New York. Overstory composition in both soil types was dominated by red oak (Quercus rubra) and chestnut oak (Quercus montana), but the overstory on shale sites was more diverse (14 tree species) and had less oak than sandstone sites (with only 6 tree species). A total of 17 species were recorded as regeneration on shale sites, where seedlings averaged 21,466/ha and saplings averaged 1,833/ha. Dominant seedling on shale sites were chestnut oak (7,100/ha) and red oak (3,583/ha); chestnut oak had significantly more seedlings on shale versus sandstone sites. Saplings on shale sites were predominantly Hamamelis virginiana and Acer pensylvanicum. On sandstone sites, seedlings averaged 6,425/ha (including 2,075 oaks and 2,250 red maple per ha). Sapling numbers for all species were low (1,400/ha) and were mostly red maple. These forests are unique because of the relatively high density of oak seedlings on certain sites and low density of red maple across all sites. This variation in regeneration as well as management strategies to promote additional oak regeneration and canopy recruitment are discussed for these and similar forests.

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A comparative study of physiological and morphological seedling traits associated with shade tolerance in introduced red oak (Quercus rubra) and native hardwood tree species in southwestern Germany

Tree Physiology ◽

10.1093/treephys/tpt124 ◽

2014 ◽

Vol 34 (2) ◽

pp. 184-193 ◽

Cited By ~ 17

Author(s):

C. Kuehne ◽

P. Nosko ◽

T. Horwath ◽

J. Bauhus

Keyword(s):

Comparative Study ◽

Tree Species ◽

Shade Tolerance ◽

Quercus Rubra ◽

Red Oak ◽

Seedling Traits ◽

Hardwood Tree

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Comparison of the herb layer composition in stands of several tree species in the Louny region

Beskydy ◽

10.11118/beskyd201609010041 ◽

2016 ◽

Vol 9 (1-2) ◽

pp. 41-48

Author(s):

Jiří Viewegh ◽

Stanislav Miltner ◽

Karel Matějka ◽

Vilém Podrázský

Keyword(s):

Pinus Sylvestris ◽

Tree Species ◽

Natural Regeneration ◽

Quercus Rubra ◽

Quercus Petraea ◽

Ground Vegetation ◽

Red Oak ◽

Northern Red Oak ◽

Herb Layer ◽

Layer Composition

Influence of introduced northern red oak stands (Quercus rubra L.) on herb understory with comparison with herb understory of autochthonous Sessile oak (Quercus petraea agg. L) and Scots pine (Pinus sylvestris L.) was observed in Louny region area on 14 plots. The analysis of the ground vegetation was performed using classical phytosociological methods. Significant changes were not determined in the site character, when comparing particular tree species stands, the differences consisted especially in the natural regeneration of tree species. Northern red oak showed a tendency of more fast penetration in the neighboring stands.

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Single Tree Classification Using Multi-Temporal ALS Data and CIR Imagery in Mixed Old-Growth Forest in Poland

Remote Sensing ◽

10.3390/rs13245101 ◽

2021 ◽

Vol 13 (24) ◽

pp. 5101

Author(s):

Agnieszka Kamińska ◽

Maciej Lisiewicz ◽

Krzysztof Stereńczak

Keyword(s):

Tree Species ◽

Classification Accuracy ◽

Sustainable Forest Management ◽

Point Clouds ◽

Deciduous Tree ◽

Spectral Information ◽

Species Classification ◽

Individual Tree ◽

Mean Values ◽

Old Growth Forest

Tree species classification is important for a variety of environmental applications, including biodiversity monitoring, wildfire risk assessment, ecosystem services assessment, and sustainable forest management. In this study we used a fusion of three remote sensing (RM) datasets including ALS (leaf-on and leaf-off) and colour-infrared (CIR) imagery (leaf-on), to classify different coniferous and deciduous tree species, including dead class, in a mixed temperate forest in Poland. We used intensity and structural variables from the ALS data and spectral information derived from aerial imagery for the classification procedure. Additionally, we tested the differences in classification accuracy of all the variants included in the data integration. The random forest classifier was used in the study. The highest accuracies were obtained for classification based on both point clouds and including image spectral information. The mean values for overall accuracy and kappa were 84.3% and 0.82, respectively. Analysis of the leaf-on and leaf-off alone is not sufficient to identify individual tree species due to their different discriminatory power. Leaf-on and leaf-off ALS point cloud features alone gave the lowest accuracies of 72% ≤ OA ≤ 74% and 0.67 ≤ κ ≤ 0.70. Classification based on both point clouds was found to give satisfactory and comparable results to classification based on combined information from all three sources (83% ≤ OA ≤ 84% and 0.81 ≤ κ ≤ 0.82). The classification accuracy varied between species. The classification results for coniferous trees were always better than for deciduous trees independent of the datasets. In the classification based on both point clouds (leaf-on and leaf-off), the intensity features seemed to be more important than the other groups of variables, especially the coefficient of variation, skewness, and percentiles. The NDVI was the most important CIR-based feature.

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OPTIMAL DATES FOR DECIDUOUS TREE SPECIES MAPPING USING FULL YEARS SENTINEL-2 TIME SERIES IN SOUTH WEST FRANCE

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-v-3-2020-469-2020 ◽

2020 ◽

Vol V-3-2020 ◽

pp. 469-476

Author(s):

N. Karasiak ◽

M. Fauvel ◽

J.-F. Dejoux ◽

C. Monteil ◽

D. Sheeren

Keyword(s):

Time Series ◽

Species Distribution ◽

Tree Species ◽

Satellite Image ◽

Deciduous Tree ◽

Support Vector ◽

Red Oak ◽

Spectral Bands ◽

One Year ◽

Sentinel 2

Abstract. The free to use Sentinel-2 (S2) sensors with 5-day revisit time at high spatial resolution in 10 spectral bands is a revolution in the remote sensing domain. Including 6 spectral bands in the near infrared, with 3 dedicated for the red-edge (where the vegetation significatively increases), these european satellites are very promising for mapping tree species distribution at a national scale. Here, we study the contribution of three one-year S2 Satellite Image Time Series (SITS) for mapping deciduous species distribution in the southwest of France. The annual cycle of vegetation (called phenology) can contribute to the identification of tree species. For some specific dates, species can have different phenological behaviours (senesence, flowering…). To train and validate the maps, we used the Support Vector Machine algorithm with a spatial cross-validation method. To train the algorithm with the same number of samples per species, we decided to undersample each class to the smallest class using a K-means clustering method. Moreover, a Sequential Feature Selection (SFS) has been implemented to detect the optimal dates per species. Our results are promising with high accuracy for Red oak andWillow (average score of the three one-year respectively F1 = 0.99, F1 = 0.94) based on the optimal dates. However, it appears that the performances when using the each full SITS are far below the optimal dates models (average ΔF1 = 0.32). We did not find, except for Willow and Red oak, that the optimal dates were the same for each year. Perspectives is to find an algorithm robust to temporal or spectral noise and to smooth the time series.

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Assessment of Carbon Sequestration Potential of some Selected Urban Tree Species

10.1101/2021.08.19.457022 ◽

2021 ◽

Author(s):

Ezekiel Ajayi

Keyword(s):

Carbon Sequestration ◽

Tree Species ◽

Carbon Sink ◽

Total Carbon ◽

Acacia Auriculiformis ◽

Gmelina Arborea ◽

Individual Tree ◽

Urban Tree ◽

Sequestration Potential ◽

Exotic Tree

Tree species carbon assessment and quantification remain the only opportunity to determine the position of forest in climate change amelioration potentials. Forest biomass constitutes the largest terrestrial carbon sink and accounts for approximately 90% of all living terrestrial biomass. The aim of this study is to assess tree species carbon sequestration potentials of selected urban tree species. The study was carried out in Adekunle Ajasin University Campus, Akungba Akoko, Ondo State, Nigeria. All trees species ≥10 cm Diameter at Breast Height (Dbh) within the area were identified and their Dbh measured as well as other variables for volume computation such as height, diameters at the base, middle and top. Also, for density assessment; stem core samples were collected. Again, the coordinate of individual tree was recorded using a Global Positioning System (GPS) receiver. A total of 124 individual trees were encountered with varying growth variables as well as carbon values. The study area contains some indigenous and exotic tree species such as Acacia auriculiformis, Terminalia mantily, Gmelina arborea and Tectona grandis etc. but Acacia auriculiformis had the highest frequency. The tree species with highest carbon sequestration was Gmelina arborea as recorded for this study. The total carbon and carbon dioxide sequestered in the study area were reported as 47.94 kg and 176.03 kg respectively.

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