Terrestrial laser scanning is a powerful technology for capturing the three-dimensional structure of forests with a high level of detail and accuracy. Over the last decade, many algorithms have been ...developed to extract various tree parameters from terrestrial laser scanning data. Here we present 3D Forest, an open-source non-platform-specific software application with an easy-to-use graphical user interface with the compilation of algorithms focused on the forest environment and extraction of tree parameters. The current version (0.42) extracts important parameters of forest structure from the terrestrial laser scanning data, such as stem positions (X, Y, Z), tree heights, diameters at breast height (DBH), as well as more advanced parameters such as tree planar projections, stem profiles or detailed crown parameters including convex and concave crown surface and volume. Moreover, 3D Forest provides quantitative measures of between-crown interactions and their real arrangement in 3D space. 3D Forest also includes an original algorithm of automatic tree segmentation and crown segmentation. Comparison with field data measurements showed no significant difference in measuring DBH or tree height using 3D Forest, although for DBH only the Randomized Hough Transform algorithm proved to be sufficiently resistant to noise and provided results comparable to traditional field measurements.
The role of tree uprooting in soil formation was evaluated using an analysis of scientific articles published from 1940 to 2009. The potential for generalizing these published results across a range ...of regions, forest and soil types was assessed. We focused on the following topics: ecological conditions within pit–mound microsites; the area of pit–mounds in different landscapes; the age of pit–mounds; rotation period; and the effect of tree uprooting on soil properties, including the absence of pit–mound dynamics in forests that have been managed long-term. These topics were analysed on the spatial scales of the pit–mound, forest stand, and landscape.
The effect of tree uprooting on soil formation has been particularly studied in northern hardwood forests on Podzols in the region of the Great Lakes (USA, Canada). Fewer studies have been done in Europe, Asia or Australia, and we are not aware of any studies from tropical rain forests and temperate forests in South America or Africa. The ecological characteristics of pit–mound microsites with moister, colder and more stable pit conditions are well known and can be generalized. On the other hand, the proportional area of pit–mounds is highly variable, ranging from 0 to 90% depending on forest history and natural conditions, and therefore has only local validity. The maximum age of pit–mounds is most often 200–500
years, though sometimes pit–mounds can be older than 2000
years. The duration of pit–mounds depends on geologic, geomorphologic and climatic conditions, and thus has regional validity. The rotation period (how often an area equivalent to the entire study area is disturbed) is a synthetic characteristic which is largely similar within specific biomes, and usually is as long as 10
3
years. However, there is still an open question concerning the heterogeneity of the rotation period on fine spatial scales, especially considering the assumed higher susceptibility of some microsites to disturbances.
On fine spatial scales, the effect of tree uprooting on soil formation is relatively well understood. However, the traditional method of approximating the development of pit–mound soil properties by using a linear function is a gross simplification. Faster leaching from pits compared with mounds and currently undisturbed soils is a common phenomenon, and is valid across forest and site types. Under specific site conditions and under specific disturbance regimes, however, this phenomenon may not necessarily be applicable.
On the scale of the forest stand, the opinion predominates that pit–mound dynamics inhibit the development of soils. This theory is hardly ever supported with quality data, however, and results from some important studies do not fully reflect this. In managed forests, where there is a long-term absence of pit–mound dynamics, studies have indicated that the stage of soil formation is more advanced compared with naturally disturbed forests. The impact of tree uprooting on the development of soil spatial variability is thus still insufficiently explained.
At the landscape scale, there are only few relevant studies dealing with the importance of tree uprooting where authors have demonstrated the significant effect of pit–mounds on erosion–sedimentation processes.
Summary
It is well established that solar irradiance greatly influences tree metabolism and growth through photosynthesis, but its effects acting through individual climate metrics have not yet been ...well quantified. Understanding these effects is crucial for assessing the impacts of climate change on forest ecosystems.
To describe the effects of solar irradiance on tree growth, we installed 110 automatic dendrometers in two old‐growth mountain forest reserves in Central Europe, performed detailed terrestrial and aerial laser scanning to obtain precise tree profiles, and used these to simulate the sum of solar irradiance received by each tree on a daily basis. Generalized linear mixed‐effect models were applied to simulate the probability of growth and the growth intensity over seven growing seasons.
Our results demonstrated various contrasting effects of solar irradiance on the growth of canopy trees. On the one hand, the highest daily growth rates corresponded with the highest solar irradiance potentials (i.e. the longest photoperiod). Intense solar irradiance significantly decreased tree growth, through an increase in the vapor pressure deficit. These effects were consistent for all species but had different magnitude.
Tree growth is the most effective on long rainy/cloudy days with low solar irradiance.
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•We conceptualized the approach for measuring three-dimensional crown asymmetry.•Our novel approach separates the effects of crown shift and local crown plasticity.•Smaller trees ...exhibited higher ability to shift and re-shape their crowns.•Crown models neglecting tree asymmetry were poor predictors of direct competitors.•Light availability computed by geometric crown models were significantly biased.
There are many indications that for a true understanding of aboveground canopy competition, the concept of symmetric trees is oversimplified and unsatisfactory; in spite of that, this concept is still commonly used in forest ecology research. In this study we analyzed and quantified the effect of tree/crown asymmetry on crown-to-crown interactions and canopy light availability with respect to tree size and species.
Geometric crown models were used to represent the concept of symmetric trees, while data from terrestrial laser scanning were employed to constitute real crown shapes, positions and mutual crown-to-crown interactions. We developed an original approach for measuring three-dimensional crown asymmetry, separating the effect of positional crown shift and local crown plasticity, and analyzed their effect in aboveground competition for space and light.
In comparison with reality, the models neglecting tree asymmetry were only poor predictors of trees mutually competing for space. Geometric models taking the positional crown shift into account were good predictors of ‘space competitors’ for Norway spruce, but were still insufficient for European beech. This is because for spruce crown shifting seems to be the major neighbor avoidance strategy, while beech in addition exhibited high local crown shape plasticity. Additionally, of the two species beech showed overall greater crown plasticity, which (in contrast to spruce) decreased only slowly with increasing tree size.
Importantly, the concept of symmetric trees significantly underestimates the potential canopy light availability (and thus overestimates canopy competition for light), because asymmetric and the plastic ‘puzzle-like’ arrangement of real tree crowns is more effective than assumed symmetric organization. This most likely inserts a systematic bias into stand growth simulators that are based on the concept of symmetric trees.
We applied a supervised individual-tree segmentation algorithm to ultra-high-density drone lidar in a temperate mountain forest in the southern Czech Republic. We compared the number of trees ...correctly segmented, stem diameter at breast height (DBH), and tree height from drone-lidar segmentations to field-inventory measurements and segmentations from terrestrial laser scanning (TLS) data acquired within two days of the drone-lidar acquisition. Our analysis detected 51% of the stems >15 cm DBH, and 87% of stems >50 cm DBH. Errors of omission were much more common for smaller trees than for larger ones, and were caused by removal of points prior to segmentation using a low-intensity and morphological filter. Analysis of segmented trees indicates a strong linear relationship between DBH from drone-lidar segmentations and TLS data. The slope of this relationship is 0.93, the intercept is 4.28 cm, and the r2 is 0.98. However, drone lidar and TLS segmentations overestimated DBH for the smallest trees and underestimated DBH for the largest trees in comparison to field data. We evaluate the impact of random error in point locations and variation in footprint size, and demonstrate that random error in point locations is likely to cause an overestimation bias for small-DBH trees. A Random Forest classifier correctly identified broadleaf and needleleaf trees using stem and crown geometric properties with overall accuracy of 85.9%. We used these classifications and DBH estimates from drone-lidar segmentations to apply allometric scaling equations to segmented individual trees. The stand-level aboveground biomass (AGB) estimate using these data is 76% of the value obtained using a traditional field inventory. We demonstrate that 71% of the omitted AGB is due to segmentation errors of omission, and the remaining 29% is due to DBH estimation errors. Our analysis indicates that high-density measurements from low-altitude drone flight can produce DBH estimates for individual trees that are comparable to TLS. These data can be collected rapidly throughout areas large enough to produce landscape-scale estimates. With additional refinement, these estimates could augment or replace manual field inventories, and could support the calibration and validation of current and forthcoming space missions.
Current and planned space missions will produce aboveground biomass density data products at varying spatial resolution. Calibration and validation of these data products is critically dependent on ...the existence of field estimates of aboveground biomass and coincident remote sensing data from airborne or terrestrial lidar. There are few places that meet these requirements, and they are mostly in the northern hemisphere and temperate zone. Here we summarize the potential for low-altitude drones to produce new observations in support of mission science. We describe technical requirements for producing high-quality measurements from autonomous platforms and highlight differences among commercially available laser scanners and drone aircraft. We then describe a case study using a heavy-lift autonomous helicopter in a temperate mountain forest in the southern Czech Republic in support of calibration and validation activities for the NASA Global Ecosystem Dynamics Investigation. Low-altitude flight using drones enables the collection of ultra-high-density point clouds using wider laser scan angles than have been possible from traditional airborne platforms. These measurements can be precise and accurate and can achieve measurement densities of thousands of points · m
−2
. Analysis of surface elevation measurements on a heterogeneous target observed 51 days apart indicates that the realized range accuracy is 2.4 cm. The single-date precision is 2.1–4.5 cm. These estimates are net of all processing artifacts and geolocation errors under fully autonomous flight. The 3D model produced by these data can clearly resolve branch and stem structure that is comparable to terrestrial laser scans and can be acquired rapidly over large landscapes at a fraction of the cost of traditional airborne laser scanning.
Abstract
The Global Ecosystem Dynamics Investigation (GEDI) is a waveform lidar instrument on the International Space Station used to estimate aboveground biomass density (AGBD) in temperate and ...tropical forests. Algorithms to predict footprint AGBD from GEDI relative height (RH) metrics were developed from simulated waveforms with leaf-on (growing season) conditions. Leaf-off GEDI data with lower canopy cover are expected to have shorter RH metrics, and are therefore excluded from GEDI’s gridded AGBD products. However, the effects of leaf phenology on RH metric heights, and implications for GEDI footprint AGBD models that can include multiple nonlinear RH predictors, have not been quantified. Here, we test the sensitivity of GEDI data and AGBD predictions to leaf phenology. We simulated GEDI data using high-density drone lidar collected in a temperate mountain forest in the Czech Republic under leaf-off and leaf-on conditions, 51 d apart. We compared simulated GEDI RH metrics and footprint-level AGBD predictions from GEDI Level 4 A models from leaf-off and leaf-on datasets. Mean canopy cover increased by 31% from leaf-off to leaf-on conditions, from 57% to 88%. RH metrics < RH50 were more sensitive to changes in leaf phenology than RH metrics ⩾ RH50. Candidate AGBD models for the deciduous-broadleaf-trees prediction stratum in Europe that were trained using leaf-on measurements exhibited a systematic prediction difference of 0.6%–19% when applied to leaf-off data, as compared to leaf-on predictions. Models with the least systematic prediction difference contained only the highest RH metrics, or contained multiple predictor terms that contained both positive and negative coefficients, such that the difference from systematically shorter leaf-off RH metrics was partially offset among the multiple terms. These results suggest that, with consideration of model choice, leaf-off GEDI data can be suitable for AGBD prediction, which could increase data availability and reduce sampling error in some forests.
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•There is an impact of macroclimate on the residence time of beech deadwood.•Lower temperature extended the residence time (average 8 years).•Residence times of logs from various ...mortality mode differed by ca. 2–10years.•Logs with lower water availability have longer residence time about 9–15years.
European beech is one of the most important European trees, not only because of its expected role in the face of climate change, but also as a frequent species in forest reserves, national parks and the NATURA 2000 network. For such areas, naturalness and biodiversity conservation are significant issues, in which the presence of deadwood plays an important role. To manage deadwood in forests, one needs to know how the residence time of coarse woody debris is influenced by the environment. In this study, we analysed a dataset of 4260 logs from beech-dominated primeval and natural forest reserves in three climatically different regions (cold-dry, warm-dry and warm-humid region), working with a time series of more than 40years (1972–2015). With the help of Bayesian Survival Trajectory Analysis, we examined differences between residence times in the three regions and in three DBH classes. In addition, we analysed qualitative characteristics of fallen logs – the mortality mode and the position of logs during decomposition – and calculated their total decomposition time and time to reach an advanced decay stage. The analyses confirmed the significant impact of macroclimate on residence time. In the cold-dry region the diameter classes 10–24cm (small-sized logs) and 25–54cm (medium-sized logs) had the longest residence time (38and48years, respectively). In the warm-dry region with a favourable composition of fungal communities, the diameter class 55+ cm (large-sized logs) logs had the shortest residence time (43years). The rates of decomposition of beech logs in contact with the ground or suspended logs were significantly different in all three regions, with logs lying on the ground decomposing 9–15years sooner. These results can be used in retention forestry. If the continuity of the deadwood environment is to be preserved, it is necessary to ensure a “supply” of dead stems (offering differing habitats) at least once every 24–35years. During this period, 50% of logs decay completely and the other 50% of logs progress to an advanced decay stage.
There is little information about long-term spontaneous forest development after industrial disturbances. A field study was done along the chronosequence of unreclaimed post-mining sites (12, 25, 32, ...60 and 90 years old), developing by spontaneous succession in the northwestern Czech Republic. Initial stages of forest development (12- to 60-yr-old) were dominated mainly by silver birch (Betula pendula) goat willow (Salix caprea) and aspen (Populus tremula), Norway spruce (Picea abies) also established naturally in the intermediate stages of succession. A 90-yr-old site was close to the expected climax forest with 21 woody species dominated by European oak (Quercus robus L.), supplemented by beech (Fagus sylvatica). The youngest and oldest sites were more diverse and richer sites in woody species than others, as expressed by the Shannon-Weiner and Simpson indices. Conversely, spatial heterogeneity (aggregation) increased with increasing age; however, it became lower at the age of 90 years. Woody species in the understory were more diverse than in the tree layer. Overall, our study found that spontaneous processes can lead to the development of the late-successional forest in fewer than 100 years in Central Europe.
•Spontaneous processes can lead to the development of the late-successional forest in ∼100 years in Central Europe.•The late-successional species can establish spontaneously in stands of pioneer trees in ∼30 years after mining.•Oak is a demanding dominant species in the secondary forest after mining.•Tree species diversity creates a U-shaped pattern over successional stages in Central Europe.•The sequence of change in the spatial pattern of populations from the early to the late stage: random → cluster → random.
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