scholarly journals Microtopography is a fundamental organizing structure in black ash wetlands

2019 ◽  
Author(s):  
Jacob S. Diamond ◽  
Daniel L. McLaughlin ◽  
Robert A. Slesak ◽  
Atticus Stovall
Keyword(s):  
Water Table ◽  
Laser Scanning ◽  
Binary Classification ◽  
Base Cations ◽  
Basal Area ◽  
Forested Wetlands ◽  
Primary Control ◽  
Structural Element ◽  
Soil Elevation ◽  
Black Ash

Abstract. All wetland ecosystems are controlled by water table and soil saturation dynamics, so any local scale deviation in soil elevation represents variability in this primary control. Wetland microtopography is the structured variability in soil elevation, and is typically categorized into a binary classification of local high points (hummocks) and local low points (hollows). Although the influence of microtopography on vegetation composition and biogeochemical processes has received attention in wetlands around the globe, its role in forested wetlands is still poorly understood. We studied relationships among microtopography on understory vegetation communities, tree biomass, and soil chemistry in 10 black ash (Fraxinus nigra Marshall) wetlands in northern Minnesota, U.S.A. To do so, we combined a 1-cm resolution surface elevation model generated from terrestrial laser scanning (TLS) with co-located water table, vegetation, and soil measurements. We observed that microtopography was an important structural element across sites, where hummocks were loci of greater species richness, greater midstory and canopy basal area, and higher soil concentrations of chloride, phosphorus, and base cations. In contrast, hollows were associated with higher soil nitrate and sulfate concentrations. We also found that the effect of microtopography on vegetation and soils was greater at wetter sites than at drier sites, suggesting that distance to mean water table is a primary determinant of wetland biogeochemistry. These findings highlight clear controls of mictopography on vegetation and soil distributions, while also supporting the notion that microtopography arises from feedbacks that concentrate biomass, soil nutrients, and productivity on microsite highs, especially in otherwise wet conditions. We therefore conclude that microtopography is a fundamental organizing structure in black ash wetlands.

scholarly journals Microtopography is a fundamental organizing structure of vegetation and soil chemistry in black ash wetlands

2020 ◽  
Vol 17 (4) ◽  
pp. 901-915 ◽  
Author(s):  
Jacob S. Diamond ◽  
Daniel L. McLaughlin ◽  
Robert A. Slesak ◽  
Atticus Stovall
Keyword(s):  
Water Table ◽  
Soil Chemistry ◽  
Laser Scanning ◽  
Binary Classification ◽  
Base Cations ◽  
Basal Area ◽  
Primary Control ◽  
Structural Element ◽  
Soil Elevation ◽  
Black Ash

Abstract. All wetland ecosystems are controlled by water table and soil saturation dynamics, so any local-scale deviation in soil elevation and thus water table position represents variability in this primary control. Wetland microtopography is the structured variability in soil elevation and is typically categorized into a binary classification of local high points (hummocks) and local low points (hollows). Although the influence of microtopography on vegetation composition and biogeochemical processes in wetlands has received attention around the globe, its role in forested wetlands is still less understood. We studied relationships among microtopography and understory vegetation communities, tree biomass, and soil chemistry in 10 black ash (Fraxinus nigra Marshall) wetlands in northern Minnesota, USA. To do so, we combined a 1 cm resolution surface elevation model generated from terrestrial laser scanning (TLS) with colocated water table, vegetation, and soil measurements. We observed that microtopography was an important structural element across sites, where hummocks were loci of greater species richness; greater midstory and canopy basal area; and higher soil concentrations of chloride, phosphorus, and base cations. In contrast, hollows were associated with higher soil nitrate and sulfate concentrations. We also found that the effect of microtopography on vegetation and soils was greater at wetter sites than at drier sites, suggesting that the distance-to-mean water table is a primary determinant of wetland biogeochemistry. These findings highlight clear controls of microtopography on vegetation and soil distributions while also supporting the notion that microtopography arises from feedbacks that concentrate biomass, soil nutrients, and productivity on microsite highs, especially in otherwise wet conditions. We therefore conclude that microtopography is a fundamental organizing structure in black ash wetlands.

scholarly journals Pattern and structure of microtopography implies autogenic origins in forested wetlands

2019 ◽  
Vol 23 (12) ◽  
pp. 5069-5088 ◽  
Author(s):  
Jacob S. Diamond ◽  
Daniel L. McLaughlin ◽  
Robert A. Slesak ◽  
Atticus Stovall
Keyword(s):  
Water Level ◽  
Laser Scanning ◽  
Soil Depth ◽  
Soil Surface ◽  
Forested Wetlands ◽  
Water Dynamics ◽  
Specific Yield ◽  
Surface Microtopography ◽  
Plant Environment ◽  
Black Ash

Abstract. Wetland microtopography is a visually striking feature, but also critically influences biogeochemical processes at both the scale of its observation (10−2–102 m2) and at aggregate scales (102–104 m2). However, relatively little is known about how wetland microtopography develops or the factors influencing its structure and pattern. Growing research across different ecosystems suggests that reinforcing processes may be common between plants and their environment, resulting in self-organized patch features, like hummocks. Here, we used landscape ecology metrics and diagnostics to evaluate the plausibility of plant–environment feedback mechanisms in the maintenance of wetland microtopography. We used terrestrial laser scanning (TLS) to quantify the sizing and spatial distribution of hummocks in 10 black ash (Fraxinus nigra Marshall) wetlands in northern Minnesota, USA. We observed clear elevation bimodality in our wettest sites, indicating microsite divergence into two states: elevated hummocks and low elevation hollows. We coupled the TLS dataset to a 3-year water level record and soil-depth measurements, and showed that hummock height (mean = 0.31±0.06 m) variability is largely predicted by mean water level depth (R2=0.8 at the site scale, R2=0.12–0.56 at the hummock scale), with little influence of subsurface microtopography on surface microtopography. Hummocks at wetter sites exhibited regular spatial patterning (i.e., regular spacing of ca. 1.5 m, 25 %–30 % further apart than expected by chance) in contrast to the more random spatial arrangements of hummocks at drier sites. Hummock size distributions (perimeters, areas, and volumes) were lognormal, with a characteristic patch area of approximately 1 m2 across sites. Hummocks increase the effective soil surface area for redox gradients and exchange interfaces in black ash wetlands by up to 32 %, and influence surface water dynamics through modulation of specific yield by up to 30 %. Taken together, the data support the hypothesis that vegetation develops and maintains hummocks in response to anaerobic stresses from saturated soils, with a potential for a microtopographic signature of life.

scholarly journals A microtopographic signature of life: Ecohydrologic feedbacks structure wetland microtopography

2019 ◽  
Author(s):  
Jacob S. Diamond ◽  
Daniel L. McLaughlin ◽  
Robert A. Slesak ◽  
Atticus Stovall
Keyword(s):  
Water Table ◽  
Laser Scanning ◽  
Soil Depth ◽  
Wetland Vegetation ◽  
Water Dynamics ◽  
Specific Yield ◽  
Surface Microtopography ◽  
Plant Environment ◽  
Base Elevation ◽  
Black Ash

Abstract. Microtopography in wetlands can be a visually striking landscape feature, and also critically influences biogeochemical processes at both the scale of its observation (10−2–102m2) and at aggregate scales (102–104m2). However, relatively little is known about how microtopography develops in wetlands or the factors that influence its structure and pattern. For example, wetland vegetation appears to have a strong affinity to elevated microsites, but the degree to which wetland vegetation simply preferentially occupies elevated microsites (“hummocks”) versus the degree to which wetland vegetation reinforces and maintains these elevated microsites is not clear. Growing research across different ecosystems suggests that such reinforcing processes may be common between plants and their environment, resulting in self-organized patch features, like hummocks. Here, we made use of landscape ecology techniques and diagnostics to evaluate the plausibility of plant-environment feedback mechanisms in the maintenance of wetland microtopography. Using a novel terrestrial laser scanning dataset, we were able to quantify the sizing and spatial distribution of hummocks in 10 black ash (Fraxinus nigra Marshall) wetlands in northern Minnesota, U.S.A. We observed clear elevation bimodality in our wettest sites, indicating microsite divergence into two states: elevated hummocks and base elevation hollows. We coupled the TLS dataset to a three-year water table record and soil-depth measurements, and showed that hummock height is largely predicted by mean water table depth, with little influence of subsurface microtopography on surface microtopography. We further show that hummocks in wetter sites exhibit regular spatial patterning in contrast to hummocks in drier sites, which exhibit more random spatial arrangements. We show that hummock size distributions (perimeters, areas, and volumes) are lognormal, and that hummocks exhibit a characteristic patch area of approximately 1 m2 across sites. Finally, we show that hummocks may be responsible for increased reactive surface area in black ash wetlands by up to 32 %, and may also influence surface water dynamics through modulation of specific yield by up to 30 %. We suggest that vegetation develops and maintains hummocks in response to anaerobic stresses from saturated soils, leading to a microtopographic signature of life.

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 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.

Inoptimality losses in forest management decisions caused by errors in an inventory based on airborne laser scanning and aerial photographs

2010 ◽  
Vol 40 (12) ◽  
pp. 2427-2438 ◽  
Author(s):  
Md. Nurul Islam ◽  
Mikko Kurttila ◽  
Lauri Mehtätalo ◽  
Timo Pukkala
Keyword(s):  
Input Data ◽  
Laser Scanning ◽  
Basal Area ◽  
Airborne Laser Scanning ◽  
Aerial Photographs ◽  
Stand Age ◽  
Inventory Data ◽  
Airborne Laser ◽  
Mean Diameter ◽  
The Mean

Errors in inventory data may lead to inoptimal decisions that ultimately result in financial losses for forest owners. We estimated the expected monetary losses resulting from data errors that are similar to errors in laser-based forest inventory. The mean loss was estimated for 67 stands by simulating 100 realizations of inventory data for each stand with errors that mimic those in airborne laser scanning (ALS) based inventory. These realizations were used as input data in stand management optimization, which maximized the present value of all future net incomes (NPV). The inoptimality loss was calculated as the difference between the NPV of the optimal solution and the true NPV of the solution obtained with erroneous input data. The results showed that the mean loss exceeded €300·ha–1 (US$425·ha–1) in 84% of the stands. On average, the losses increased with decreasing stand age and mean diameter. Furthermore, increasing errors in the basal area weighted mean diameter and basal area of spruce were found to significantly increase the loss. It has been discussed that improvements in the accuracy of ALS-based inventory could be financially justified.

scholarly journals Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR

2019 ◽  
Vol 11 (6) ◽  
pp. 709 ◽  
Author(s):  
Ekena Rangel Pinagé ◽  
Michael Keller ◽  
Paul Duffy ◽  
Marcos Longo ◽  
Maiza dos-Santos ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Forest Canopy ◽  
Binary Classification ◽  
Forest Degradation ◽  
Selective Logging ◽  
Ecological Impacts ◽  
Airborne Lidar ◽  
Classification Model ◽  
Amazon Forest ◽  
Gap Formation

Forest degradation is common in tropical landscapes, but estimates of the extent and duration of degradation impacts are highly uncertain. In particular, selective logging is a form of forest degradation that alters canopy structure and function, with persistent ecological impacts following forest harvest. In this study, we employed airborne laser scanning in 2012 and 2014 to estimate three-dimensional changes in the forest canopy and understory structure and aboveground biomass following reduced-impact selective logging in a site in Eastern Amazon. Also, we developed a binary classification model to distinguish intact versus logged forests. We found that canopy gap frequency was significantly higher in logged versus intact forests even after 8 years (the time span of our study). In contrast, the understory of logged areas could not be distinguished from the understory of intact forests after 6–7 years of logging activities. Measuring new gap formation between LiDAR acquisitions in 2012 and 2014, we showed rates 2 to 7 times higher in logged areas compared to intact forests. New gaps were spatially clumped with 76 to 89% of new gaps within 5 m of prior logging damage. The biomass dynamics in areas logged between the two LiDAR acquisitions was clearly detected with an average estimated loss of −4.14 ± 0.76 MgC ha−1 y−1. In areas recovering from logging prior to the first acquisition, we estimated biomass gains close to zero. Together, our findings unravel the magnitude and duration of delayed impacts of selective logging in forest structural attributes, confirm the high potential of airborne LiDAR multitemporal data to characterize forest degradation in the tropics, and present a novel approach to forest classification using LiDAR data.

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 Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 905 ◽  
Author(s):  
Guerra-Hernández ◽  
Cosenza ◽  
Cardil ◽  
Silva ◽  
Botequim ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Basal Area ◽  
Remote Sensing Data ◽  
Tree Height ◽  
Point Clouds ◽  
Volume Estimation ◽  
P Value ◽  
Test Statistic ◽  
Individual Tree ◽  
Significant Difference

Estimating forest inventory variables is important in monitoring forest resources and mitigating climate change. In this respect, forest managers require flexible, non-destructive methods for estimating volume and biomass. High-resolution and low-cost remote sensing data are increasingly available to measure three-dimensional (3D) canopy structure and to model forest structural attributes. The main objective of this study was to evaluate and compare the individual tree volume estimates derived from high-density point clouds obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) in Eucalyptus spp. plantations. Object-based image analysis (OBIA) techniques were applied for individual tree crown (ITC) delineation. The ITC algorithm applied correctly detected and delineated 199 trees from ALS-derived data, while 192 trees were correctly identified using DAP-based point clouds acquired from Unmanned Aerial Vehicles (UAV), representing accuracy levels of respectively 62% and 60%. Addressing volume modelling, non-linear regression fit based on individual tree height and individual crown area derived from the ITC provided the following results: Model Efficiency (Mef) = 0.43 and 0.46, Root Mean Square Error (RMSE) = 0.030 m3 and 0.026 m3, rRMSE = 20.31% and 19.97%, and an approximately unbiased results (0.025 m3 and 0.0004 m3) using DAP and ALS-based estimations, respectively. No significant difference was found between the observed value (field data) and volume estimation from ALS and DAP (p-value from t-test statistic = 0.99 and 0.98, respectively). The proposed approaches could also be used to estimate basal area or biomass stocks in Eucalyptus spp. plantations.

Sign in / Sign up

Export Citation Format

Share Document