scholarly journals MAESPA: a model to study interactions between water limitation, environmental drivers and vegetation function at tree and stand levels, with an example application to [CO<sub>2</sub>] × drought interactions

2012 ◽  
Vol 5 (4) ◽  
pp. 919-940 ◽  
Author(s):  
R. A. Duursma ◽  
B. E. Medlyn
Keyword(s):  
Forest Canopy ◽  
Spatial Scales ◽  
Root Water Uptake ◽  
Experimental Results ◽  
Environmental Drivers ◽  
Canopy Interception ◽  
Individual Tree ◽  
Water Limitation ◽  
Leaf Physiology ◽  
Potential Applications

Abstract. Process-based models (PBMs) of vegetation function can be used to interpret and integrate experimental results. Water limitation to plant carbon uptake is a highly uncertain process in the context of environmental change, and many experiments have been carried out that study drought limitations to vegetation function at spatial scales from seedlings to entire canopies. What is lacking in the synthesis of these experiments is a quantitative tool incorporating a detailed mechanistic representation of the water balance that can be used to integrate and analyse experimental results at scales of both the whole-plant and the forest canopy. To fill this gap, we developed an individual tree-based model (MAESPA), largely based on combining the well-known MAESTRA and SPA ecosystem models. The model includes a hydraulically-based model of stomatal conductance, root water uptake routines, drainage, infiltration, runoff and canopy interception, as well as detailed radiation interception and leaf physiology routines from the MAESTRA model. The model can be applied both to single plants of arbitrary size and shape, as well as stands of trees. The utility of this model is demonstrated by studying the interaction between elevated [CO2] (eCa) and drought. Based on theory, this interaction is generally expected to be positive, so that plants growing in eCa should be less susceptible to drought. Experimental results, however, are varied. We apply the model to a previously published experiment on droughted cherry, and show that changes in plant parameters due to long-term growth at eCa (acclimation) may strongly affect the outcome of Ca × drought experiments. We discuss potential applications of MAESPA and some of the key uncertainties in process representation.

scholarly journals MAESPA: a model to study interactions between water limitation, environmental drivers and vegetation function at tree and stand levels, with an example application to [CO<sub>2</sub>] × drought interactions

2012 ◽  
Vol 5 (1) ◽  
pp. 459-513 ◽  
Author(s):  
R. A. Duursma ◽  
B.E. Medlyn
Keyword(s):  
Forest Canopy ◽  
Spatial Scales ◽  
Root Water Uptake ◽  
Experimental Results ◽  
Environmental Drivers ◽  
Canopy Interception ◽  
Individual Tree ◽  
Water Limitation ◽  
Leaf Physiology ◽  
Potential Applications

Abstract. Process-based models (PBMs) of vegetation function can be used to interpret and integrate experimental results. Water limitation to plant carbon uptake is a highly uncertain process in the context of environmental change, and many experiments have been carried out that study drought limitations to vegetation function at spatial scales from seedlings to entire canopies. What is lacking in the synthesis of these experiments is a quantitative tool that can be used to integrate and analyse experimental results at scales of both the whole-plant and the forest canopy, and that includes a detailed mechanistic representation of the water balance. To fill this gap, we developed an individual tree-based model (MAESPA), largely based on combining the well-known MAESTRA and SPA ecosystem models. The model includes a hydraulically-based model of stomatal conductance, root water uptake routines, drainage, infiltration, runoff and canopy interception, as well as detailed radiation interception and leaf physiology routines from the MAESTRA model. The model can be applied both to single plants of arbitrary size and shape, as well as stands of trees. The utility of this model is demonstrated by studying the interaction between elevated [CO2] (eCa) and drought. Based on theory, this interaction is generally expected to be positive, so that plants growing in eCa should be less susceptible to drought. Experimental results, however, are varied. We apply the model to a previously published experiment on droughted cherry, and show that changes in plant parameters due to long-term growth at eCa (acclimation) may strongly affect the outcome of Ca × drought experiments. We discuss potential applications of MAESPA and some of the key uncertainties in process representation.

scholarly journals ACCURACY ASSESSMENT OF CROWN DELINEATION METHODS FOR THE INDIVIDUAL TREES USING LIDAR DATA

2016 ◽  
Vol XLI-B8 ◽  
pp. 585-588
Author(s):  
K. T Chang ◽  
C. Lin ◽  
Y. C. Lin ◽  
J. K. Liu
Keyword(s):  
Forest Canopy ◽  
Accuracy Assessment ◽  
Tree Height ◽  
Experimental Results ◽  
Estimation Methods ◽  
Surface Model ◽  
Individual Tree ◽  
Free Process ◽  
Crown Shape ◽  
Individual Trees

Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR) is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs). The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM) from a digital surface model (DSM), and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC) and a variable window filter (VWF), are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits") that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.

scholarly journals Improved 3D Stem Mapping Method and Elliptic Hypothesis-Based DBH Estimation from Terrestrial Laser Scanning Data

2020 ◽  
Vol 12 (3) ◽  
pp. 352 ◽  
Author(s):  
WenFang Ye ◽  
Chuang Qian ◽  
Jian Tang ◽  
Hui Liu ◽  
XiaoYun Fan ◽  
...  
Keyword(s):  
High Precision ◽  
Laser Scanning ◽  
Forest Canopy ◽  
Estimation Method ◽  
Terrestrial Laser Scanning ◽  
Growth Direction ◽  
Relative Accuracy ◽  
Experimental Results ◽  
Individual Tree ◽  
The Mean

The detailed structure information under the forest canopy is important for forestry surveying. As a high-precision environmental sensing and measurement method, terrestrial laser scanning (TLS) is widely used in high-precision forestry surveying. In TLS-based forestry surveys, stem-mapping, which is focused on detecting and extracting trunks, is one of the core data processing tasks and the basis for the subsequent calculation of tree attributes; one of the most basic attributes is the diameter at breast height (DBH). This article explores and improves the methods for stem mapping and DBH estimation from TLS data. Firstly, an improved 3D stem mapping algorithm considering the growth direction in random sample consistency (RANSAC) cylinder fitting is proposed to extract and fit the individual tree point cloud section. It constructs the hierarchical optimum cylinder of the trunk and introduces the growth direction into the establishment of the backbone buffer in the next layer. Experimental results show that it can effectively remove most of the branches and reduce the interference of the branches to the discrimination of trunks and improve the integrity of stem extraction by about 36%. Secondly, a robust least squares ellipse fitting method based on the elliptic hypothesis is proposed for DBH estimation. Experimental results show that the DBH estimation accuracy of the proposed estimation method is improved compared with other methods. The mean root mean squared error (RMSE) of the proposed estimation method is 1.14 cm, compared with other methods with a mean RMSE of 1.70, 2.03, and 2.14 cm. The mean relative accuracy of the proposed estimation method is 95.2%, compared with other methods with a mean relative accuracy of 92.9%, 91.9%, and 90.9%.

scholarly journals ACCURACY ASSESSMENT OF CROWN DELINEATION METHODS FOR THE INDIVIDUAL TREES USING LIDAR DATA

2016 ◽  
Vol XLI-B8 ◽  
pp. 585-588
Author(s):  
K. T Chang ◽  
C. Lin ◽  
Y. C. Lin ◽  
J. K. Liu
Keyword(s):  
Forest Canopy ◽  
Accuracy Assessment ◽  
Tree Height ◽  
Experimental Results ◽  
Estimation Methods ◽  
Surface Model ◽  
Individual Tree ◽  
Free Process ◽  
Crown Shape ◽  
Individual Trees

Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR) is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs). The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM) from a digital surface model (DSM), and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC) and a variable window filter (VWF), are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits") that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.

scholarly journals Remotely Sensed Single Tree Data Enable the Determination of Habitat Thresholds for the Three-Toed Woodpecker (Picoides tridactylus)

2018 ◽  
Vol 10 (12) ◽  
pp. 1972 ◽  
Author(s):  
Katarzyna Zielewska-Büttner ◽  
Marco Heurich ◽  
Jörg Müller ◽  
Veronika Braunisch
Keyword(s):  
Bark Beetles ◽  
Laser Scanning ◽  
Positive Relationship ◽  
Spatial Scales ◽  
Keystone Species ◽  
Remote Sensing Data ◽  
Individual Tree ◽  
Substrate Quality ◽  
Dead Trees ◽  
Negative Effect

Forest biodiversity conservation requires precise, area-wide information on the abundance and distribution of key habitat structures at multiple spatial scales. We combined airborne laser scanning (ALS) data with color-infrared (CIR) aerial imagery for identifying individual tree characteristics and quantifying multi-scale habitat requirements using the example of the three-toed woodpecker (Picoides tridactylus) (TTW) in the Bavarian Forest National Park (Germany). This bird, a keystone species of boreal and mountainous forests, is highly reliant on bark beetles dwelling in dead or dying trees. While previous studies showed a positive relationship between the TTW presence and the amount of deadwood as a limiting resource, we hypothesized a unimodal response with a negative effect of very high deadwood amounts and tested for effects of substrate quality. Based on 104 woodpecker presence or absence locations, habitat selection was modelled at four spatial scales reflecting different woodpecker home range sizes. The abundance of standing dead trees was the most important predictor, with an increase in the probability of TTW occurrence up to a threshold of 44–50 dead trees per hectare, followed by a decrease in the probability of occurrence. A positive relationship with the deadwood crown size indicated the importance of fresh deadwood. Remote sensing data allowed both an area-wide prediction of species occurrence and the derivation of ecological threshold values for deadwood quality and quantity for more informed conservation management.

scholarly journals Evapotranspiration seasonality across the Amazon basin

2017 ◽  
Author(s):  
Eduardo Eiji Maeda ◽  
Xuanlong Ma ◽  
Fabien Wagner ◽  
Hyungjun Kim ◽  
Taikan Oki ◽  
...  
Keyword(s):  
Amazon Basin ◽  
Regional Climate ◽  
Root Water Uptake ◽  
Environmental Drivers ◽  
Seasonal Patterns ◽  
Wet Season ◽  
Important Indicator ◽  
Seasonally Dry ◽  
Basin Scale ◽  
Terrestrial Water

Abstract. Evapotranspiration (ET) of Amazon forests is a main driver of regional climate patterns and an important indicator of ecosystem functioning. Despite its importance, the seasonal variability of ET over Amazon forests, and its relationship with environmental drivers, is still poorly understood. In this study, we carry out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers over five sub-basins across the Amazon basin. We used in-situ measurements of river discharge, and remotely sensed estimates of terrestrial water storage, rainfall, and solar radiation. We show that the characteristics of ET seasonality in all sub-basins differ in timing and magnitude. The highest mean annual ET was found in the northern Rio Negro basin (~ 1497 mm year−1) and the lowest values in the Solimões River basin (~ 986 mm year−1). For the first time in a basin-scale study, using observational data, we show that factors limiting ET vary across climatic gradients in the Amazon, confirming local-scale eddy covariance studies. Both annual mean and seasonality in ET are driven by a combination of energy and water availability, as neither rainfall nor radiation alone could explain patterns in ET. In southern basins, despite seasonal rainfall deficits, deep root water uptake allows increasing rates of ET during the dry season, when radiation is usually higher than in the wet season. We demonstrate contrasting ET seasonality with satellite greenness across Amazon forests, with strong asynchronous relationships in ever-wet watersheds, and positive correlations observed in seasonally dry watersheds. Finally, we compared our results with estimates obtained by two ET models, and we conclude that neither of the two tested models could provide a consistent representation of ET seasonal patterns across the Amazon.

scholarly journals Spatial Variation in Canopy Structure across Forest Landscapes

2018 ◽  
Author(s):  
Brady S. Hardiman ◽  
Elizabeth A. LaRue ◽  
Jeff W. Atkins ◽  
Robert T. Fahey ◽  
Franklin W. Wagner ◽  
...  
Keyword(s):  
Temperate Forest ◽  
Forest Canopy ◽  
Spatial Scales ◽  
Canopy Structure ◽  
Ecosystem Functions ◽  
Lidar System ◽  
Stable Point ◽  
Eastern Usa ◽  
Forested Landscapes ◽  
Patch Scale

Forest canopy structure (CS) controls many ecosystem functions and is highly variable across landscapes, but the magnitude and scale of this variation is not well understood. We used a portable canopy lidar system to characterize variation in five categories of CS along N = 3 transects (140&ndash;800 m long) at each of six forested landscapes within the eastern USA. The cumulative coefficient of variation was calculated for subsegments of each transect to determine the point of stability for individual CS metrics. We then quantified the scale at which CS is autocorrelated using Moran&rsquo;s I in an Incremental Autocorrelation analysis. All CS metrics reached stable values within 300 m but varied substantially within and among forested landscapes. A stable point of 300 m for CS metrics corresponds with the spatial extent that many ecosystem functions are measured and modeled. Additionally, CS metrics were spatially autocorrelated at 40 to 88 m, suggesting that patch scale disturbance or environmental factors drive these patterns. Our study shows CS is heterogeneous across temperate forest landscapes at the scale of 10&rsquo;s of meters, requiring a resolution of this size for upscaling CS with remote sensing to large spatial scales.

scholarly journals Analysis of a lidar voxel-derived vertical profile at the plot and individual tree scales for the estimation of forest canopy layer characteristics

2016 ◽  
Vol 37 (11) ◽  
pp. 2653-2681 ◽  
Author(s):  
Matthew Sumnall ◽  
Alicia Peduzzi ◽  
Thomas R. Fox ◽  
Randolph H. Wynne ◽  
Valerie A. Thomas
Keyword(s):  
Vertical Profile ◽  
Forest Canopy ◽  
Canopy Layer ◽  
Individual Tree

scholarly journals Universal predictability of mobility patterns in cities

2014 ◽  
Vol 11 (100) ◽  
pp. 20140834 ◽  
Author(s):  
Xiao-Yong Yan ◽  
Chen Zhao ◽  
Ying Fan ◽  
Zengru Di ◽  
Wen-Xu Wang
Keyword(s):  
Spatial Scales ◽  
Human Mobility ◽  
Mobility Patterns ◽  
Mobility Data ◽  
Universal Prediction ◽  
Potential Applications ◽  
Mobility Behaviour ◽  
History Of ◽  
Different Characteristics ◽  
The City

Despite the long history of modelling human mobility, we continue to lack a highly accurate approach with low data requirements for predicting mobility patterns in cities. Here, we present a population-weighted opportunities model without any adjustable parameters to capture the underlying driving force accounting for human mobility patterns at the city scale. We use various mobility data collected from a number of cities with different characteristics to demonstrate the predictive power of our model. We find that insofar as the spatial distribution of population is available, our model offers universal prediction of mobility patterns in good agreement with real observations, including distance distribution, destination travel constraints and flux. By contrast, the models that succeed in modelling mobility patterns in countries are not applicable in cities, which suggests that there is a diversity of human mobility at different spatial scales. Our model has potential applications in many fields relevant to mobility behaviour in cities, without relying on previous mobility measurements.

scholarly journals Wavelength dependent nonlinear optical response of tetraphenylethene aggregation-induced emission luminogens

2018 ◽  
Vol 2 (12) ◽  
pp. 2263-2271 ◽  
Author(s):  
Jianbo Xiong ◽  
Xinyue Li ◽  
Chunqing Yuan ◽  
Sergey Semin ◽  
Zhaoquan Yao ◽  
...  
Keyword(s):  
Optical Properties ◽  
Nonlinear Optical ◽  
Theoretical Calculations ◽  
Experimental Results ◽  
Nlo Properties ◽  
Aggregation Induced Emission ◽  
Non Linear ◽  
Potential Applications ◽  
Linear Optical Properties ◽  
Linear Optical

Studies of the non-linear optical properties of classical AIEgens are rare, despite their important potential applications in organic composite photonic circuits. Here, we present experimental results, supported by theoretical calculations, of the non-linear optical (NLO) properties of TPE and its halogenated derivates.

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