Sapflow and water use of freshwater wetland trees exposed to saltwater incursion in a tidally influenced South Carolina watershed

2010 ◽  
Vol 40 (3) ◽  
pp. 525-535 ◽  
Author(s):  
Ken W. Krauss ◽  
Jamie A. Duberstein
Keyword(s):  
South Carolina ◽  
Water Use ◽  
Forested Wetlands ◽  
Site Effect ◽  
Freshwater Wetland ◽  
Anthropogenic Activity ◽  
Individual Tree ◽  
Osmotic Balance ◽  
Individual Trees ◽  
A Site

Sea-level rise and anthropogenic activity promote salinity incursion into many tidal freshwater forested wetlands. Interestingly, individual trees can persist for decades after salt impact. To understand why, we documented sapflow (Js), reduction in Jswith sapwood depth, and water use (F) of baldcypress ( Taxodium distichum (L.) Rich.) trees undergoing exposure to salinity. The mean Jsof individual trees was reduced by 2.8 g H2O·m–2·s–1(or by 18%) in the outer sapwood on a saline site versus a freshwater site; however, the smallest trees, present only on the saline site, also registered the lowest Js. Hence, tree size significantly influenced the overall site effect on Js. Trees undergoing perennial exposure to salt used greater relative amounts of water in outer sapwood than in inner sapwood depths, which identifies a potentially different strategy for baldcypress trees coping with saline site conditions over decades. Overall, individual trees used 100 kg H2O·day–1on a site that remained relatively fresh versus 23.9 kg H2O·day–1on the saline site. We surmise that perennial salinization of coastal freshwater forests forces shifts in individual-tree osmotic balance and water-use strategy to extend survival time on suboptimal sites, which further influences growth and morphology.

scholarly journals Adjudicating Perspectives on Forest Structure: How Do Airborne, Terrestrial, and Mobile Lidar-Derived Estimates Compare?

2021 ◽  
Vol 13 (12) ◽  
pp. 2297
Author(s):  
Jonathon J. Donager ◽  
Andrew J. Sánchez Meador ◽  
Ryan C. Blackburn
Keyword(s):  
Ponderosa Pine ◽  
Laser Scanning ◽  
Canopy Cover ◽  
Basal Area ◽  
Tree Height ◽  
Absolute Error ◽  
Forest Monitoring ◽  
Individual Tree ◽  
Structural Configurations ◽  
Individual Trees

Applications of lidar in ecosystem conservation and management continue to expand as technology has rapidly evolved. An accounting of relative accuracy and errors among lidar platforms within a range of forest types and structural configurations was needed. Within a ponderosa pine forest in northern Arizona, we compare vegetation attributes at the tree-, plot-, and stand-scales derived from three lidar platforms: fixed-wing airborne (ALS), fixed-location terrestrial (TLS), and hand-held mobile laser scanning (MLS). We present a methodology to segment individual trees from TLS and MLS datasets, incorporating eigen-value and density metrics to locate trees, then assigning point returns to trees using a graph-theory shortest-path approach. Overall, we found MLS consistently provided more accurate structural metrics at the tree- (e.g., mean absolute error for DBH in cm was 4.8, 5.0, and 9.1 for MLS, TLS and ALS, respectively) and plot-scale (e.g., R2 for field observed and lidar-derived basal area, m2 ha−1, was 0.986, 0.974, and 0.851 for MLS, TLS, and ALS, respectively) as compared to ALS and TLS. While TLS data produced estimates similar to MLS, attributes derived from TLS often underpredicted structural values due to occlusion. Additionally, ALS data provided accurate estimates of tree height for larger trees, yet consistently missed and underpredicted small trees (≤35 cm). MLS produced accurate estimates of canopy cover and landscape metrics up to 50 m from plot center. TLS tended to underpredict both canopy cover and patch metrics with constant bias due to occlusion. Taking full advantage of minimal occlusion effects, MLS data consistently provided the best individual tree and plot-based metrics, with ALS providing the best estimates for volume, biomass, and canopy cover. Overall, we found MLS data logistically simple, quickly acquirable, and accurate for small area inventories, assessments, and monitoring activities. We suggest further work exploring the active use of MLS for forest monitoring and inventory.

Assyrian sacred trees in the Brooklyn Museum

Iraq ◽  
1994 ◽  
Vol 56 ◽  
pp. 123-133 ◽  
Author(s):  
Pauline Albenda
Keyword(s):  
Present Author ◽  
Ninth Century ◽  
Palm Tree ◽  
The West ◽  
Individual Tree ◽  
Sacred Tree ◽  
The Individual ◽  
Individual Trees ◽  
Brooklyn Museum ◽  
Tree Type

The Brooklyn Museum houses twelve stone slabs with carved decoration from the Northwest Palace of Ashurnasirpal II. The motif of a stylized tree — the so-called Sacred Tree (see Figs. 1, 4, 6) — appears on seven of those slabs which come from rooms F, I, L, S, T of the ninth century palace at Nimrud. These tree renderings are representative of the sacred tree-type found in ten rooms of the royal residence and the west wing. Approximately 96 sacred trees, in two-register arrangement, appeared on the pictorial decorations in room I; the same motif occurred about 75 times in one-register arrangement on the reliefs of the other rooms. The abundance of the sacred tree motif on the wall decorations of the Northwest Palace attests to the significance of this plant. Its design deserves investigation; in Layard's words, “the tree, evidently a sacred symbol, is elaborately and tastefully formed.”In his study of the Ashurnasirpal II reliefs in American collections, Stearns did not attempt to list the sacred trees, because “variations in the sacred tree occur only in minor details,” and “the tree in itself is rarely useful in identifying the location of the reliefs.” These statements make clear Stearns' belief that the sacred trees were nearly alike. Other scholars, notably Weidner and Reade, have pointed out that on a number of slabs now in American and European museums are carvings of matching half trees, therefore indicating that when paired, these trees belonged to adjoining slabs originally. In trying to match half trees, one finds that individual sacred trees do differ in the rendering of specific details. Bleibtreu, in her analysis of the sacred tree-type, lists three variants of the flower found on the palmette-garland framing the individual tree on three sides. The present author, after examining the sacred trees carved on the slabs in The Brooklyn Museum, concludes that the design of the tree-type is more varied than heretofore presumed, and that its construction is more complex than indicated in previous descriptions of the subjects. An analysis of the Assyrian sacred tree-type may lead to possible conclusions regarding its intended image: a stylized palm tree, a cult object, an emblem of vegetation or “tree of life”, an imperial symbol, or a combination of those forms. In addition, one may consider to what extent the rendering of individual trees was the consequence of artistic inventiveness.

scholarly journals Automatic Extraction of Grasses and Individual Trees in Urban Areas Based on Airborne Hyperspectral and LiDAR Data

2020 ◽  
Vol 12 (17) ◽  
pp. 2725
Author(s):  
Qixia Man ◽  
Pinliang Dong ◽  
Xinming Yang ◽  
Quanyuan Wu ◽  
Rongqing Han
Keyword(s):  
Urban Areas ◽  
Three Dimensional ◽  
Hyperspectral Data ◽  
Classification Method ◽  
Urban Vegetation ◽  
Individual Tree ◽  
Cloud Data ◽  
Random Forest Classification ◽  
The Individual ◽  
Individual Trees

Urban vegetation extraction is very important for urban biodiversity assessment and protection. However, due to the diversity of vegetation types and vertical structure, it is still challenging to extract vertical information of urban vegetation accurately with single remotely sensed data. Airborne light detection and ranging (LiDAR) can provide elevation information with high-precision, whereas hyperspectral data can provide abundant spectral information on ground objects. The complementary advantages of LiDAR and hyperspectral data could extract urban vegetation much more accurately. Therefore, a three-dimensional (3D) vegetation extraction workflow is proposed to extract urban grasses and trees at individual tree level in urban areas using airborne LiDAR and hyperspectral data. The specific steps are as follows: (1) airborne hyperspectral and LiDAR data were processed to extract spectral and elevation parameters, (2) random forest classification method and object-based classification method were used to extract the two-dimensional distribution map of urban vegetation, (3) individual tree segmentation was conducted on a canopy height model (CHM) and point cloud data separately to obtain three-dimensional characteristics of urban trees, and (4) the spatial distribution of urban vegetation and the individual tree delineation were assessed by validation samples and manual delineation results. The results showed that (1) both the random forest classification method and object-based classification method could extract urban vegetation accurately, with accuracies above 99%; (2) the watershed segmentation method based on the CHM could extract individual trees correctly, except for the small trees and the large tree groups; and (3) the individual tree segmentation based on point cloud data could delineate individual trees in three-dimensional space, which is much better than CHM segmentation as it can preserve the understory trees. All the results suggest that two- and three-dimensional urban vegetation extraction could play a significant role in spatial layout optimization and scientific management of urban vegetation.

scholarly journals Spatial Models With Inter-Tree Competition From Airborne Laser Scanning Improve Estimates of Genetic Variance

2021 ◽  
Vol 11 ◽  
Author(s):  
David Pont ◽  
Heidi S. Dungey ◽  
Mari Suontama ◽  
Grahame T. Stovold
Keyword(s):  
Laser Scanning ◽  
Management Practices ◽  
Spatial Models ◽  
Airborne Laser Scanning ◽  
Tree Level ◽  
Residual Variance ◽  
Spatial Effects ◽  
Individual Tree ◽  
Airborne Laser ◽  
Individual Trees

Phenotyping individual trees to quantify interactions among genotype, environment, and management practices is critical to the development of precision forestry and to maximize the opportunity of improved tree breeds. In this study we utilized airborne laser scanning (ALS) data to detect and characterize individual trees in order to generate tree-level phenotypes and tree-to-tree competition metrics. To examine our ability to account for environmental variation and its relative importance on individual-tree traits, we investigated the use of spatial models using ALS-derived competition metrics and conventional autoregressive spatial techniques. Models utilizing competition covariate terms were found to quantify previously unexplained phenotypic variation compared with standard models, substantially reducing residual variance and improving estimates of heritabilities for a set of operationally relevant traits. Models including terms for spatial autocorrelation and competition performed the best and were labelled ACE (autocorrelation-competition-error) models. The best ACE models provided statistically significant reductions in residuals ranging from −65.48% for tree height (H) to −21.03% for wood stiffness (A), and improvements in narrow sense heritabilities from 38.64% for H to 14.01% for A. Individual tree phenotyping using an ACE approach is therefore recommended for analyses of research trials where traits are susceptible to spatial effects.

scholarly journals A-Site Effect on the Conversion of Bio-Ethanol into Isobutene over Ternary A<sub>1</sub>Zn<sub>y</sub>Zr<sub>z</sub>O<sub>n</sub> Catalysts

2016 ◽  
Vol 05 (03) ◽  
pp. 95-101
Author(s):  
Feng Liu ◽  
Yong Men ◽  
Jinguo Wang ◽  
Xiaoxiong Huang ◽  
Biao Zhao ◽  
...  
Keyword(s):  
Site Effect ◽  
A Site

Predicting Future Diameter Distributions Given Current Stand Attributes

2022 ◽  
Author(s):  
Quang V. Cao
Keyword(s):  
Prediction Method ◽  
Diameter Distribution ◽  
Tree Level ◽  
Individual Tree ◽  
Distribution Parameters ◽  
Level Model ◽  
Novel Method ◽  
Quadratic Mean Diameter ◽  
Stand Attributes ◽  
Individual Trees

This study discussed four methods to project a diameter distribution from age A1 to age A2. Method 1 recovers parameters of the distribution at age A2 from stand attributes at that age. Method 2 uses a stand-level model to grow the quadratic mean diameter, and then recovers the distribution parameters from that prediction. Method 3 grows the diameter distribution by assuming tree-level survival and diameter growth functions. Method 4 first converts the diameter distribution at age A1 into a list of individual trees before growing these trees to age A2. In a numerical example employing the Weibull distribution, methods 3 and 4 produced better results based on two types of error indices and the relative predictive error for each diameter class. Method 4 is a novel method that converts a diameter distribution into a list of individual-trees, and in the process, successfully links together diameter distribution, individual-tree, and whole stand models.

scholarly journals LiDAR-Based Wildfire Prevention in WUI: The Automatic Detection, Measurement and Evaluation of Forest Fuels

Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 148 ◽  
Author(s):  
Marta Fernández-Álvarez ◽  
Julia Armesto ◽  
Juan Picos
Keyword(s):  
Point Clouds ◽  
Individual Tree ◽  
Forest Fuels ◽  
Gis Tools ◽  
Biomass Management ◽  
Measurement And Evaluation ◽  
The Individual ◽  
Individual Trees ◽  
Height Model

This paper describes a methodology using LiDAR point clouds with an ultra-high resolution in the characterization of forest fuels for further wildfire prevention and management. Biomass management strips were defined in three case studies using a particular Spanish framework. The data were acquired through a UAV platform. The proposed methodology allows for the detection, measurement and characterization of individual trees, as well as the analysis of shrubs. The individual tree segmentation process employed a canopy height model, and shrub cover LiDAR-derived models were used to characterize the vegetation in the strips. This way, the verification of the geometric legal restrictions was performed automatically and objectively using decision trees and GIS tools. As a result, priority areas, where wildfire prevention efforts should be concentrated in order to control wildfires, can be identified.

Revealing the A‐Site Effect of Lead‐Free A 3 Sb 2 Br 9 Perovskite in Photocatalytic C(sp 3 )−H Bond Activation

2020 ◽  
Vol 59 (41) ◽  
pp. 18136-18139 ◽  
Author(s):  
Zhenzhen Zhang ◽  
Yuying Yang ◽  
Yingying Wang ◽  
Lanlan Yang ◽  
Qi Li ◽  
...  
Keyword(s):  
Bond Activation ◽  
Site Effect ◽  
Lead Free ◽  
A Site

scholarly journals Individual Tree Position Extraction and Structural Parameter Retrieval Based on Airborne LiDAR Data: Performance Evaluation and Comparison of Four Algorithms

2020 ◽  
Vol 12 (3) ◽  
pp. 571 ◽  
Author(s):  
Chen ◽  
Xiang ◽  
Moriya
Keyword(s):  
Template Matching ◽  
Local Maximum ◽  
Airborne Lidar ◽  
Forest Monitoring ◽  
Lidar Data ◽  
Individual Tree ◽  
Matching Algorithm ◽  
Crown Width ◽  
Individual Trees ◽  
Airborne Lidar Data

Information for individual trees (e.g., position, treetop, height, crown width, and crown edge) is beneficial for forest monitoring and management. Light Detection and Ranging (LiDAR) data have been widely used to retrieve these individual tree parameters from different algorithms, with varying successes. In this study, we used an iterative Triangulated Irregular Network (TIN) algorithm to separate ground and canopy points in airborne LiDAR data, and generated Digital Elevation Models (DEM) by Inverse Distance Weighted (IDW) interpolation, thin spline interpolation, and trend surface interpolation, as well as by using the Kriging algorithm. The height of the point cloud was assigned to a Digital Surface Model (DSM), and a Canopy Height Model (CHM) was acquired. Then, four algorithms (point-cloud-based local maximum algorithm, CHM-based local maximum algorithm, watershed algorithm, and template-matching algorithm) were comparatively used to extract the structural parameters of individual trees. The results indicated that the two local maximum algorithms can effectively detect the treetop; the watershed algorithm can accurately extract individual tree height and determine the tree crown edge; and the template-matching algorithm works well to extract accurate crown width. This study provides a reference for the selection of algorithms in individual tree parameter inversion based on airborne LiDAR data and is of great significance for LiDAR-based forest monitoring and management.

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