scholarly journals Quantifying Crown Morphology of Mixed Pine-Oak Forests Using Terrestrial Laser Scanning

2021 ◽  
Vol 13 (23) ◽  
pp. 4955
Author(s):  
Sara Uzquiano ◽  
Ignacio Barbeito ◽  
Roberto San Martín ◽  
Martin Ehbrecht ◽  
Dominik Seidel ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Specific Interaction ◽  
Structural Complexity ◽  
Continuous Variable ◽  
Permanent Plots ◽  
Projection Area ◽  
Natural Forests ◽  
Northern Spain ◽  
Widespread Species ◽  
Crown Morphology

Mixed forests make up the majority of natural forests, and they are conducive to improving the resilience and resistance of forest ecosystems. Moreover, it is in the crown of the trees where the effect of inter- and intra-specific interaction between them is evident. However, our knowledge of changes in crown morphology caused by density, competition, and mixture of specific species is still limited. Here, we provide insight on stand structural complexity based on the study of four response crown variables (Maximum Crown Width Height, MCWH; Crown Base Height, CBH; Crown Volume, CV; and Crown Projection Area, CPA) derived from multiple terrestrial laser scans. Data were obtained from six permanent plots in Northern Spain comprising of two widespread species across Europe; Scots pine (Pinus sylvestris L.) and sessile oak (Quercus petraea (Matt.) Liebl.). A total of 193 pines and 256 oaks were extracted from the point cloud. Correlation test were conducted (ρ ≥ 0.9) and finally eleven independent variables for each target tree were calculated and categorized into size, density, competition and mixture, which was included as a continuous variable. Linear and non-linear multiple regressions were used to fit models to the four crown variables and the best models were selected according to the lowest AIC Index and biological sense. Our results provide evidence for species plasticity to diverse neighborhoods and show complementarity between pines and oaks in mixtures, where pines have higher MCWH and CBH than oaks but lower CV and CPA, contrary to oaks. The species complementarity in crown variables confirm that mixtures can be used to increase above ground structural diversity.

Crown structure of European beech (Fagus sylvatica L.): a non-causal proxy for mechanical–physical wood properties

2020 ◽  
Author(s):  
Andreas Rais ◽  
Martin Jacobs ◽  
Jan-Willem G. van de Kuilen ◽  
Hans Pretzsch
Keyword(s):  
Fagus Sylvatica ◽  
Laser Scanning ◽  
European Beech ◽  
Wood Properties ◽  
Projection Area ◽  
Mixed Stands ◽  
Crown Volume ◽  
Crown Structure ◽  
Crown Morphology ◽  
Crown Projection Area

The current tendency towards the silvicultural promotion of mixed tree species has increased the variability in the crown structure within stands. This study shows how neighbouring trees can influence both the external crown features and internal wood properties of trees. Using terrestrial laser scanning, the crown features of 100 European beech trees, <i>Fagus sylvatica</i> L., from pure beech stands and mixed stands of beech with Douglas fir, Norway spruce, sessile oak and Scots pine were recorded. After felling and sawing, the dynamic modulus of elasticity was determined on 1623 boards from the two lower 4.1-m logs. Significant differences were found between beech trees from pure stands and those from beech–pine mixed stands in terms of crown volume (415 m<sup>3</sup> vs 766 m<sup>3</sup>), crown ratio (50.0% vs 71.5%), crown projection ratio (0.182 m cm<sup>−1</sup> vs 0.253 m cm<sup>−1</sup>) and branch angle (30.7° vs 54.1°). Multiple regression mixed models revealed significant relationships between timber stiffness and crown volume (-1.7 N mm<sup>−2</sup> m<sup>−3</sup>), crown ratio (-28.4 N mm<sup>−2</sup> %<sup>−1</sup>) and crown projection area (-9835 N mm<sup>−2</sup> m<sup>−1</sup> cm). Thus, the crown morphology of broad-leaved species reflects the tree’s long-term competitive status and suggests indicators for the assessment of mechanical–physical wood properties.

scholarly journals Global patterns and climatic controls of forest structural complexity

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Martin Ehbrecht ◽  
Dominik Seidel ◽  
Peter Annighöfer ◽  
Holger Kreft ◽  
Michael Köhler ◽  
...  
Keyword(s):  
Forest Structure ◽  
Laser Scanning ◽  
Structural Complexity ◽  
Terrestrial Laser Scanning ◽  
Ecosystem Functions ◽  
The Earth ◽  
Precipitation Seasonality ◽  
Latitudinal Patterns ◽  
Global Patterns ◽  
Primary Forests

AbstractThe complexity of forest structures plays a crucial role in regulating forest ecosystem functions and strongly influences biodiversity. Yet, knowledge of the global patterns and determinants of forest structural complexity remains scarce. Using a stand structural complexity index based on terrestrial laser scanning, we quantify the structural complexity of boreal, temperate, subtropical and tropical primary forests. We find that the global variation of forest structural complexity is largely explained by annual precipitation and precipitation seasonality (R² = 0.89). Using the structural complexity of primary forests as benchmark, we model the potential structural complexity across biomes and present a global map of the potential structural complexity of the earth´s forest ecoregions. Our analyses reveal distinct latitudinal patterns of forest structure and show that hotspots of high structural complexity coincide with hotspots of plant diversity. Considering the mechanistic underpinnings of forest structural complexity, our results suggest spatially contrasting changes of forest structure with climate change within and across biomes.

scholarly journals Quantifying Understory Complexity in Unmanaged Forests Using TLS and Identifying Some of Its Major Drivers

2021 ◽  
Vol 13 (8) ◽  
pp. 1513
Author(s):  
Dominik Seidel ◽  
Peter Annighöfer ◽  
Christian Ammer ◽  
Martin Ehbrecht ◽  
Katharina Willim ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Structural Equation Models ◽  
Light Availability ◽  
Structural Complexity ◽  
Basal Area ◽  
Ecosystem Functions ◽  
Canopy Openness ◽  
Seasonal Precipitation ◽  
Wide Range ◽  
Precipitation And Temperature

The structural complexity of the understory layer of forests or shrub layer vegetation in open shrublands affects many ecosystem functions and services provided by these ecosystems. We investigated how the basal area of the overstory layer, annual and seasonal precipitation, annual mean temperature, as well as light availability affect the structural complexity of the understory layer along a gradient from closed forests to open shrubland with only scattered trees. Using terrestrial laser scanning data and the understory complexity index (UCI), we measured the structural complexity of sites across a wide range of precipitation and temperature, also covering a gradient in light availability and basal area. We found significant relationships between the UCI and tree basal area as well as canopy openness. Structural equation models (SEMs) confirmed significant direct effects of seasonal precipitation on the UCI without mediation through basal area or canopy openness. However, annual precipitation and temperature effects on the UCI are mediated through canopy openness and basal area, respectively. Understory complexity is, despite clear dependencies on the available light and overall stand density, significantly and directly driven by climatic parameters, particularly the amount of precipitation during the driest month.

scholarly journals Measuring the Contribution of Leaves to the Structural Complexity of Urban Tree Crowns with Terrestrial Laser Scanning

2021 ◽  
Vol 13 (14) ◽  
pp. 2773
Author(s):  
Georgios Arseniou ◽  
David W. MacFarlane ◽  
Dominik Seidel
Keyword(s):  
Laser Scanning ◽  
Structural Complexity ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Urban Trees ◽  
Box Dimension ◽  
State University ◽  
Leaf Removal ◽  
Quercus Macrocarpa ◽  
Methodological Considerations

Trees have a fractal-like branching architecture that determines their structural complexity. We used terrestrial laser scanning technology to study the role of foliage in the structural complexity of urban trees. Forty-five trees of three deciduous species, Gleditsia triacanthos, Quercus macrocarpa, Metasequoia glyptostroboides, were sampled on the Michigan State University campus. We studied their structural complexity by calculating the box-dimension (Db) metric from point clouds generated for the trees using terrestrial laser scanning, during the leaf-on and -off conditions. Furthermore, we artificially defoliated the leaf-on point clouds by applying an algorithm that separates the foliage from the woody material of the trees, and then recalculated the Db metric. The Db of the leaf-on tree point clouds was significantly greater than the Db of the leaf-off point clouds across all species. Additionally, the leaf removal algorithm introduced bias to the estimation of the leaf-removed Db of the G. triacanthos and M. glyptostroboides trees. The index capturing the contribution of leaves to the structural complexity of the study trees (the ratio of the Db of the leaf-on point clouds divided by the Db of the leaf-off point clouds minus one), was negatively correlated with branch surface area and different metrics of the length of paths through the branch network of the trees, indicating that the contribution of leaves decreases as branch network complexity increases. Underestimation of the Db of the G. triacanthos trees, after the artificial leaf removal, was related to maximum branch order. These results enhance our understanding of tree structural complexity by disentangling the contribution of leaves from that of the woody structures. The study also highlighted important methodological considerations for studying tree structure, with and without leaves, from laser-derived point clouds.

scholarly journals Deriving Stand Structural Complexity from Airborne Laser Scanning Data—What Does It Tell Us about a Forest?

2020 ◽  
Vol 12 (11) ◽  
pp. 1854
Author(s):  
Dominik Seidel ◽  
Peter Annighöfer ◽  
Martin Ehbrecht ◽  
Paul Magdon ◽  
Stephan Wöllauer ◽  
...  
Keyword(s):  
Forest Structure ◽  
Laser Scanning ◽  
Structural Complexity ◽  
Basal Area ◽  
Airborne Laser Scanning ◽  
Stand Age ◽  
Box Dimension ◽  
Forest Types ◽  
3D Point Clouds ◽  
Airborne Laser

The three-dimensional forest structure is an important driver of several ecosystem functions and services. Recent advancements in laser scanning technologies have set the path to measuring structural complexity directly from 3D point clouds. Here, we show that the box-dimension (Db) from fractal analysis, a measure of structural complexity, can be obtained from airborne laser scanning data. Based on 66 plots across different forest types in Germany, each 1 ha in size, we tested the performance of the Db by evaluating it against conventional ground-based measures of forest structure and commonly used stand characteristics. We found that the Db was related (0.34 < R < 0.51) to stand age, management intensity, microclimatic stability, and several measures characterizing the overall stand structural complexity. For the basal area, we could not find a significant relationship, indicating that structural complexity is not tied to the basal area of a forest. We also showed that Db derived from airborne data holds the potential to distinguish forest types, management types, and the developmental phases of forests. We conclude that the box-dimension is a promising measure to describe the structural complexity of forests in an ecologically meaningful way.

scholarly journals Assessing the Relationship Between Vegetation Structure and Harvestmen Assemblage in an Amazonian Upland Forest

2016 ◽  
Author(s):  
Pío Colmenares ◽  
Fabrício B. Baccaro ◽  
Ana Lúcia Tourinho
Keyword(s):  
Vegetation Structure ◽  
Plant Architecture ◽  
Spatial Scales ◽  
Structural Complexity ◽  
Local Scale ◽  
Permanent Plots ◽  
Arthropod Diversity ◽  
Manual Search ◽  
Large Trees ◽  
The Relationship

Abstract1. Arthropod diversity and non-flying arthropod food web are strongly influenced by habitat components related to plant architecture and habitat structural complexity. However, we still poorly understand the relationship between arthropod diversity and the vegetation structure at different spatial scales. Here, we examined how harvestmen assemblages are distributed across six local scale habitats (trees, dead trunks, palms, bushes, herbs and litter), and along three proxies of vegetation structure (number of palms, number of trees and litter depth) at mesoscale.2. We collected harvestmen using cryptic manual search in 30 permanent plots of 250 m at Reserva Ducke, Amazonas, Brazil. The 30 plots cover approximately 25 km2 of upland forests. At a local scale, harvestmen were most diverse and abundant on trees. The likely preference of trees by harvestmen may be related to the variety of local microhabitats offered by large trees. However, despite the strong link between number of harvestman species and individuals with large trees, only harvestmen assemblages composition were related with number of trees and with number of palms, at mesoscale.3. Harvestman richness and abundance were not related with any vegetation structure predictor at mesoscale. Therefore, areas of upland forest in the central Amazon with large trees and palms do not harbor more harvestman species nor individuals, but are suitable to maintain different harvestmen assemblages.

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.

scholarly journals Point-cloud segmentation of individual trees in complex natural forest scenes based on a trunk-growth method

2021 ◽  
Author(s):  
Qianwei Liu ◽  
Weifeng Ma ◽  
Jianpeng Zhang ◽  
Yicheng Liu ◽  
Dongfan Xu ◽  
...  
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Plant Morphology ◽  
Natural Forest ◽  
Normal Vector ◽  
Natural Forests ◽  
Individual Tree ◽  
Single Tree ◽  
Point Cloud Segmentation ◽  
Individual Trees

AbstractForest resource management and ecological assessment have been recently supported by emerging technologies. Terrestrial laser scanning (TLS) is one that can be quickly and accurately used to obtain three-dimensional forest information, and create good representations of forest vertical structure. TLS data can be exploited for highly significant tasks, particularly the segmentation and information extraction for individual trees. However, the existing single-tree segmentation methods suffer from low segmentation accuracy and poor robustness, and hence do not lead to satisfactory results for natural forests in complex environments. In this paper, we propose a trunk-growth (TG) method for single-tree point-cloud segmentation, and apply this method to the natural forest scenes of Shangri-La City in Northwest Yunnan, China. First, the point normal vector and its Z-axis component are used as trunk-growth constraints. Then, the points surrounding the trunk are searched to account for regrowth. Finally, the nearest distributed branch and leaf points are used to complete the individual tree segmentation. The results show that the TG method can effectively segment individual trees with an average F-score of 0.96. The proposed method applies to many types of trees with various growth shapes, and can effectively identify shrubs and herbs in complex scenes of natural forests. The promising outcomes of the TG method demonstrate the key advantages of combining plant morphology theory and LiDAR technology for advancing and optimizing forestry systems.

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