Localized neighborhood species mingling is correlated with individual tree size inequality in natural forests in South China

2021 ◽  
Vol 78 (4) ◽  
Author(s):  
Hong-Xiang Wang ◽  
Shao-Xian Huang ◽  
Shu-Sheng Zhang ◽  
Hui Peng ◽  
Kun-Fang Cao
Keyword(s):  
South China ◽  
Tree Size ◽  
Natural Forests ◽  
Individual Tree ◽  
Size Inequality

A New Index Representing Individual Tree Competitive Status

1973 ◽  
Vol 3 (4) ◽  
pp. 495-500 ◽  
Author(s):  
James A. Moore ◽  
Carl A. Budelsky ◽  
Richard C. Schlesinger
Keyword(s):  
Spatial Distribution ◽  
Strong Correlation ◽  
Basal Area ◽  
Tree Size ◽  
Competition Index ◽  
Individual Tree ◽  
Silvicultural Practices ◽  
Basal Area Growth ◽  
Hardwood Species ◽  
Area Growth

A new competition index, modified Area Potentially Available (APA), was tested in a complex unevenaged stand composed of 19 different hardwood species. APA considers tree size, spatial distribution, and distance relationships in quantifying intertree competition and exhibits a strong correlation with individual tree basal area growth. The most important characteristic of APA is its potential for evaluating silvicultural practices.

Intertree competition in uneven-aged ponderosa pine stands

2003 ◽  
Vol 33 (9) ◽  
pp. 1719-1726 ◽  
Author(s):  
C W Woodall ◽  
C E Fiedler ◽  
K S Milner
Keyword(s):  
Pinus Ponderosa ◽  
Ponderosa Pine ◽  
Basal Area ◽  
Growth Efficiency ◽  
Tree Size ◽  
Basal Area Increment ◽  
Diameter Class ◽  
Individual Tree ◽  
Sapwood Area ◽  
Competition Indices

Intertree competition indices and effects were examined in 14 uneven-aged ponderosa pine (Pinus ponderosa var. scopulorum Engelm.) stands in eastern Montana. Location, height, diameter at breast height (DBH), basal area increment, crown ratio, and sapwood area were determined for each tree (DBH >3.8 cm) on one stem-mapped plot (0.2-0.4 ha) in each sample stand. Based on tree locations, various competition indices were derived for each sample tree and correlated with its growth efficiency by diameter class. In addition, trends in individual tree attributes by diameter class and level of surrounding competition were determined. For trees with a DBH <10 cm, growth efficiency was most strongly correlated with the sum of surrounding tree heights within 10.6 m. The index most highly correlated for larger trees was the sum of surrounding basal area within 6.1 m. Regardless of tree size, individual tree growth efficiency, basal area increment, and crown ratio all decreased under increasing levels of competition, with the effect more pronounced in smaller trees. These results suggest that individual trees in uneven-aged stands experience competition from differing sources at varying scales based on their size, with response to competition diminishing as tree size increases.

Trend surface analysis of spatial patterns of tree size, microsite effects, and competitive stress

1986 ◽  
Vol 16 (2) ◽  
pp. 279-282 ◽  
Author(s):  
A. J. Thomson
Keyword(s):  
Surface Analysis ◽  
Spatial Patterns ◽  
Three Dimensional ◽  
Tree Size ◽  
Dimensional Representation ◽  
Trend Surface Analysis ◽  
Individual Tree ◽  
Spatial Trend ◽  
Trend Surface ◽  
Three Dimensional Representation

Trend surface analysis was used to determine the spatial patterns of tree size, competitive stress, and effects of microsite on growth. A three-dimensional representation of the trend surface facilitated interpretation. Gradients of competitive stress depended on the competition index used. Microsite effects have a spatial trend and individual tree genetic effects are represented by the residuals from this trend.

Development and evaluation of an automated tree detection–delineation algorithm for monitoring regenerating coniferous forests

2005 ◽  
Vol 35 (10) ◽  
pp. 2332-2345 ◽  
Author(s):  
D A Pouliot ◽  
D J King ◽  
D G Pitt
Keyword(s):  
Absolute Error ◽  
Tree Regeneration ◽  
Tree Size ◽  
Detection Accuracy ◽  
Individual Tree ◽  
Commission Errors ◽  
Tree Detection ◽  
Crown Diameter ◽  
Accuracy Index ◽  
The Individual

An algorithm is presented for automated detection–delineation of coniferous tree regeneration that combines strategies of several existing algorithms, including image processing to isolate conifer crowns, optimal image scale determination, initial crown detection, and crown boundary segmentation and refinement. The algorithm is evaluated using 6-cm pixel airborne imagery in operational regeneration conditions typically encountered in the boreal forest 5–10 years after harvest. Detection omission and commission errors as well as an accuracy index combining both error types were assessed on a tree by tree basis, on an aggregated basis for each study area, in relation to tree size and the amount of woody competition present. Delineation error was assessed in a similar manner using field-measured crown diameters as a reference. The individual tree detection accuracy index improved with increasing tree size and was >70% for trees larger than 30 cm crown diameter. Crown diameter absolute error measured from automated delineations was <23%. Large crown diameters tended to be slightly underestimated. The presence of overtopping woody competition had a negligible effect on detection accuracy and only reduced estimates of crown diameter slightly.

Lidar detection of individual tree size in tropical forests

2016 ◽  
Vol 183 ◽  
pp. 318-333 ◽  
Author(s):  
António Ferraz ◽  
Sassan Saatchi ◽  
Clément Mallet ◽  
Victoria Meyer
Keyword(s):  
Tropical Forests ◽  
Tree Size ◽  
Individual Tree

Plot Edge Bias in Forest Stand Growth Simulation Models

1974 ◽  
Vol 4 (4) ◽  
pp. 419-423 ◽  
Author(s):  
Robert A. Monserud ◽  
Alan R. Ek
Keyword(s):  
Spatial Pattern ◽  
Spatial Patterns ◽  
Simulation Models ◽  
Bias Reduction ◽  
Forest Stand ◽  
Tree Size ◽  
Individual Tree ◽  
Growth Simulation ◽  
Relative Simplicity ◽  
Stand Growth

The problem of edge bias arising in the computation of individual tree competition in stand growth simulation models is discussed. The problem arises from difficulty in characterizing tree size and spatial patterns beyond the edge of the simulation plot. Various methods for reducing this bias are reviewed along with related assumptions and major sources of error. Methods which involve shifting the simulation plot image to form a set of border plots are judged best on the basis of likely bias reduction and the relative simplicity of introduced spatial pattern periodicity.

scholarly journals A Novel Approach for the Detection of Standing Tree Stems from Plot-Level Terrestrial Laser Scanning Data

2019 ◽  
Vol 11 (2) ◽  
pp. 211 ◽  
Author(s):  
Wuming Zhang ◽  
Peng Wan ◽  
Tiejun Wang ◽  
Shangshu Cai ◽  
Yiming Chen ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Natural Forests ◽  
Individual Tree ◽  
Urban Scenes ◽  
Novel Approach ◽  
Wide Range ◽  
Standing Trees ◽  
The Mean ◽  
Point Cloud Classification

Tree stem detection is a key step toward retrieving detailed stem attributes from terrestrial laser scanning (TLS) data. Various point-based methods have been proposed for the stem point extraction at both individual tree and plot levels. The main limitation of the point-based methods is their high computing demand when dealing with plot-level TLS data. Although segment-based methods can reduce the computational burden and uncertainties of point cloud classification, its application is largely limited to urban scenes due to the complexity of the algorithm, as well as the conditions of natural forests. Here we propose a novel and simple segment-based method for efficient stem detection at the plot level, which is based on the curvature feature of the points and connected component segmentation. We tested our method using a public TLS dataset with six forest plots that were collected for the international TLS benchmarking project in Evo, Finland. Results showed that the mean accuracies of the stem point extraction were comparable to the state-of-art methods (>95%). The accuracies of the stem mappings were also comparable to the methods tested in the international TLS benchmarking project. Additionally, our method was applicable to a wide range of stem forms. In short, the proposed method is accurate and simple; it is a sensible solution for the stem detection of standing trees using TLS data.

Sign in / Sign up

Export Citation Format

Share Document