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Synthetic Aperture Radar Tomography (TomoSAR) allows the reconstruction of the 3D reflectivity of natural volume scatterers such as forests, thus providing an opportunity to infer structure information in 3D. In this paper, the potential of TomoSAR data at L-band to monitor temporal variations of forest structure is addressed using simulated and experimental datasets. First, 3D reflectivity profiles were extracted by means of TomoSAR reconstruction based on a Compressive Sensing (CS) approach. Next, two complementary indices for the description of horizontal and vertical forest structure were defined and estimated by means of the distribution of local maxima of the reconstructed reflectivity profiles. To assess the sensitivity and consistency of the proposed methodology, variations of these indices for different types of forest changes in simulated as well as in real scenarios were analyzed and assessed against different sources of reference data: airborne Lidar measurements, high resolution optical images, and forest inventory data. The forest structure maps obtained indicated the potential to distinguish between different forest stages and the identification of different types of forest structure changes induced by logging, natural disturbance, or forest management.

The context in which trees and forests grow in cities is highly variable and influences the provision of ecological, social, and economic benefits. Understanding the spatial extent, structure, and composition of forests is necessary to guide urban forest policy and management, yet current forest assessment methodologies vary widely in scale, sampling intensity, and focus. Current definitions of the urban forest include all trees growing in the urban environment, and have been translated to the design of urban forest assessments. However, such broad assessments may aggregate types of urban forest that differ significantly in usage and management needs. For example, street trees occur in highly developed environments, and are planted and cared for on an individual basis, whereas forested natural areas often occur in parkland, are managed at the stand level, and are primarily sustained by natural processes such as regeneration. We use multiple datasets for New York City to compare the outcomes from assessments of the entire urban forest, street trees, and forested natural areas. We find that non-stratified assessments of the entire urban forest are biased towards abundant canopy types in cities (e.g. street trees) and underestimate the condition of forested natural areas due to their uneven spatial arrangement. These natural areas account for one quarter of the city's tree canopy, but represent the majority of trees both numerically and in terms of biomass. Non-stratified assessments of urban forest canopy must be modified to accurately represent the true composition of different urban forest types to inform effective policy and management.

Increasing forest fuel aridity with climate change may be expanding mid‐to‐high‐elevation forests' vulnerability to large, severe, and frequent wildfire. Long‐lasting changes in forests' structure and composition may occur if dominant tree species are poorly adapted to shifting wildfire patterns. We hypothesized that altered fire activity may lower existing forest resilience and disrupt the recovery of upper‐montane and subalpine conifer forest types. We empirically tested this hypothesis by quantifying post‐fire forest structure and conifer tree regeneration after spatially large, severe, and rapidly repeated wildfires (<12‐yr interval) in the Central Cascade Range in the U.S. Pacific Northwest. Post‐fire conifer regeneration was generally very poor among plots that experienced either a single high‐severity fire or rapid reburn, driven primarily by lack of proximate seed source. Pre‐fire dominant, shade‐tolerant species' abundance was highly negatively correlated with increasing seed source distances and dry, exposed post‐fire environmental conditions. In rapidly reburned plots, the order of burn severity was critical and promoted establishment of all conifer species, if low‐then‐high severity, or primarily fire‐adapted pines, if high‐then‐low severity. Our findings suggest that these forests, affected by expansive high‐severity and/or short‐interval wildfire, may transition into a patchy, low‐density, pine‐dominated forest state under future warming trends. These emerging, early seral ecosystems will incorporate more fire‐adapted tree species, lower tree densities, and more non‐forest patches than prior forests, likely expanding their resilience to anticipated increases in fire frequency. If future larger, more severe, and more frequent wildfire patterns manifest as expected in the Cascade Range, previously denser, moist mid‐to‐high‐elevation forests may begin resembling their drier, lower‐elevation mixed‐conifer counterparts in structure and composition.

The use of terrestrial laser scanning (TLS) to provide accurate estimates of 3D forest canopy structure and above-ground biomass (AGB) has developed rapidly. Here, we provide an overview of the state of the art in using TLS for estimating forest structure for AGB. We provide a general overview of TLS methods and then outline the advantages and limitations of TLS for estimating AGB. We discuss the specific type of measurements that TLS can provide, tools and methods that have been developed for turning TLS point clouds into quantifiable metrics of tree size and volume, as well as some of the challenges to improving these measurements. We discuss the role of TLS for enabling accurate calibration and validation (cal/val) of Earth observation (EO)-derived estimates of AGB from spaceborne lidar and RADAR missions. We give examples of the types of TLS equipment that are in use and how these might develop in future, and we show examples of where TLS has already been applied to measuring AGB in the tropics in particular. Comparing TLS with harvested AGB shows r2 > 0.95 for all studies thus far, with absolute agreement to within 10% at the individual tree level for all trees and to within 2% in the majority of cases. Current limitations to the uptake of TLS include the capital cost of some TLS equipment, processing complexity and the relatively small coverage that is possible. We argue that combining TLS measurements with the existing ground-based survey approaches will allow improved allometric models and better cal/val, resulting in improved regional and global estimates of AGB from space, with better-characterised, lower uncertainties. The development of new, improved equipment and methods will accelerate this process and make TLS more accessible.

Forest ecosystems are strongly impacted by continuing climate change and increasing disturbance activity, but how forest dynamics will respond remains highly uncertain. Here, we argue that a short time window after disturbance (i.e., a discrete event that disrupts prevailing ecosystem structure and composition and releases resources) is pivotal for future forest development. Trees that establish during this reorganization phase can shape forest structure and composition for centuries, providing operational early indications of forest change. While forest change has been fruitfully studied through a lens of resilience, profound ecological changes can be masked by a resilience versus regime shift dichotomy. We present a framework for characterizing the full spectrum of change after disturbance, analyzing forest reorganization along dimensions of forest structure (number, size, and spatial arrangement of trees) and composition (identity and diversity of tree species). We propose four major pathways through which forest cover can persist but reorganize following disturbance: resilience (no change in structure and composition), restructuring (structure changes but composition does not), reassembly (composition changes but structure does not), and replacement (structure and composition both change). Regime shifts occur when vegetation structure and composition are altered so profoundly that the emerging trajectory leads to nonforest. We identify fundamental processes underpinning forest reorganization which, if disrupted, deflect ecosystems away from resilience. To understand and predict forest reorganization, assessing these processes and the traits modulating them is crucial. A new wave of experiments, measurements, and models emphasizing the reorganization phase will further the capacity to anticipate future forest dynamics.

The aim of this paper was to validate factors affecting the in-stand landscape quality and how important each factor was in determining scenic beauty of natural secondary forests. The study was limited to 23 stand-level cases of natural secondary forests in Shen Zhen city in southern China. Typical samples of photographs and public estimations were applied to evaluate scenic beauty inside the natural secondary forests. The major factors were then selected by multiple linear-regression analysis and a model between scenic beauty estimation (SBE) values and in-stand landscape features was established. Rise in crown density, fall in plant litter, glow in color of trunk, fall in arbor richness, and rise in visible distance increased scenic beauty values of in-stand landscape. These five factors significantly explained the differences in scenic beauty, and together accounted for 45% of total variance in SBEs. Personal factors (e.g. gender, age and education) did not significantly affect the ratings of landscape photos, although variations of landscape quality were affected by some personal factors. Results of this study will assist policymakers, silviculturists and planners in landscape design and management of natural secondary forests in Shenzhen city. People can improve the scenic beauty values by pruning branches and clearing plant litter, which subsequently improve the forest health and contribute to forest recreation.

Aim: To examine the contribution of large-diameter trees to biomass, stand structure, and species richness across forest biomes. Location: Global. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: We examined the contribution of large trees to forest density, richness and biomass using a global network of 48 large (from 2 to 60 ha) forest plots representing 5,601,473 stems across 9,298 species and 210 plant families. This contribution was assessed using three metrics: the largest 1% of trees ≥ 1 cm diameter at breast height (DBH), all trees ≥ 60 cm DBH, and those rank-ordered largest trees that cumulatively comprise 50% of forest biomass. Results: Averaged across these 48 forest plots, the largest 1% of trees ≥ 1 cm DBH comprised 50% of aboveground live biomass, with hectare-scale standard deviation of 26%. Trees ≥ 60 cm DBH comprised 41% of aboveground live tree biomass. The size of the largest trees correlated with total forest biomass (r2 = .62, p < .001). Large-diameter trees in high biomass forests represented far fewer species relative to overall forest richness (r2 = .45, p < .001). Forests with more diverse large-diameter tree communities were comprised of smaller trees (r2 = .33, p < .001). Lower large-diameter richness was associated with large-diameter trees being individuals of more common species (r2 = .17, p = .002). The concentration of biomass in the largest 1% of trees declined with increasing absolute latitude (r2 = .46, p < .001), as did forest density (r2 = .31, p < .001). Forest structural complexity increased with increasing absolute latitude (r2 = .26, p < .001). Main conclusions: Because large-diameter trees constitute roughly half of the mature forest biomass worldwide, their dynamics and sensitivities to environmental change represent potentially large controls on global forest carbon cycling. We recommend managing forests for conservation of existing large-diameter trees or those that can soon reach large diameters as a simple way to conserve and potentially enhance ecosystem services.

QUESTIONS: Is the accuracy of predictions of above‐ground biomass (AGB) and plant species richness of tropical dry forests from LIDAR data compromised during leaf‐off canopy period, when most of the vegetation is leafless, compared to the leaf‐on period? How does topographic position affect prediction accuracy of AGB for leaf‐off and leaf‐on canopy conditions? LOCATION: Tropical dry forest, Yucatan Peninsula, Mexico. METHODS: We evaluated the accuracy of predictions using both leaf‐on and leaf‐off LIDAR estimates of biomass and species richness, and assessed the adequacy of both LIDAR data sets for characterizing these vegetation attributes in tropical dry forests using multiple regression analysis and ANOVA. The performance of the models was assessed by leave‐one‐out cross‐validation. We also investigated differences in vegetation structure between two topographic conditions using PCA and ANOSIM. Finally, we evaluated the influence of topography on the accuracy of biomass estimates from LIDAR using multiple regression analysis and ANOVA. RESULTS: A higher overall accuracy was obtained with leaf‐on vs leaf‐off conditions for AGB (root mean square error (RMSE) = 21.6 vs 25.7 ton·ha⁻¹), as well as for species richness (RMSE = 5.5 vs 5.8 species, respectively). However, no significant differences in mean dissimilarities between biomass estimates from LIDAR and in situ biomass estimates comparing the two canopy conditions were found (F₁,₃₉ = 0.03, P = 0.87). In addition, no significant differences in dissimilarities of AGB estimation were found between flat and hilly areas (F₁,₃₉ = 1.36, P = 0.25). CONCLUSIONS: Our results suggest that estimates of species richness and AGB from LIDAR are not significantly influenced by canopy conditions or slope, indicating that both leaf‐on and leaf‐off models are appropriate for these variables regardless of topographic position in these tropical dry forests.

Even-aged forests usually act as carbon sinks during most of their rotation. However, after clearcut they become sources of carbon for a period of several years. Applying uneven-aged forest management with selective cuttings will maintain tree cover and reduce the environmental impact on forest floor. The aim of this study was to compare the soil CO2 efflux between uneven-aged and even-aged Norway spruce stands with similar site properties, to investigate the effect of management practices on soil CO2 efflux and its possible correlation with soil environmental and chemical properties. We measured soil CO2 efflux in even- and uneven-aged Norway spruce stands (Picea abies [L.] Karst) in southern Finland during the summer of 2013 using closed chamber method on fixed measuring points. The study included two uneven-aged stands and two even-aged stands (a clearcut site and a mature even-aged stand). Soil moisture and soil temperature were measured at the same time as soil CO2 efflux. Soil cores were collected from the topsoil of each study plot to determine soil carbon and nitrogen concentrations. Mean soil CO2 efflux through the summer was highest in the clearcut plot (0.367 mg m-2 s-1) followed by the uneven-aged stands (0.298 and 0.257 mg m-2 s-1, respectively) and the smallest fluxes were measured in the mature even-aged stand (0.224 mg m-2 s-1). There was no statistically significant difference in soil CO2 efflux between the even- and uneven-aged stands of the same site fertility. Even- and uneven-aged stands did not differ significantly in soil moisture or soil temperature. Soil CO2 efflux increased steadily with soil temperature, whereas increasing soil moisture considerably increased soil CO2 efflux at lower moisture levels but only moderately at higher soil moisture levels. Soil carbon and nitrogen concentration did not differ between the study plots of the same fertility. Uneven-aged structure forestry did not prevent the increase in soil CO2 efflux after cuttings. However, the large variation in soil CO2 efflux rates within the uneven-aged stands suggests that the stand level CO2 efflux can be controlled with the intensity of the cutting.

ABSTRACT Pinus tabuliformis plantations on the Loess Plateau face challenges such as poor quality and high mortality rates due to high initial value density and improper thinning practices. To prevent further deterioration of these forests, it is essential to identify suitable forest management methods as soon as possible. Within Pinus tabuliformis plantations under different management methods (structure‐based forest management [SBFM], close‐to‐nature forest management [CNFM], and unmanaged), after 5 years of investigation, we analyzed the changes in forest structural complexity and growth partitioning using size inequality (Gini), size–growth relationship (SGR), and growth dominance coefficient (GDC). A linear mixed‐effects model was applied to evaluate the impact of these practices on forest stands. We also compared the trends of the average annual breast height area increment (BAI) and projected the net‐zero timeline after thinning. The results showed that: (1) thinning management temporarily reduced the Gini due to the removal of a certain number of trees. However, the Gini rebounded significantly, and the forest structure became increasingly complex again, and the rebound of SBFM stands was greater than that of CNFM; (2) in the unmanaged stands, larger trees contribute more to stand growth. In the managed stands, the changes in GDC and SGR reflected an increasing contribution of smaller trees to overall growth; and (3) thinning management increased BAI, and this effect became more pronounced over time. Notably, carbon neutrality was projected to be achieved 7.8 years in CNFM stands, which was earlier than the 8.7 years in SBFM stands. These research results will provide a theoretical basis for managing and determining the trees to be harvested for high‐density, low‐quality Pinus tabuliformis plantations of the Loess Plateau. Carbon neutrality was projected to be achieved 7.8 years in stands under close‐to‐nature forest management (CNFM), which was earlier than the 8.7 years in stands under structure‐based forest management (SBFM). CNFM's low‐disturbance characteristics are more sustainable in regions prioritizing ecological restoration, while SBFM could serve as a complementary strategy in extreme scenarios such as severe soil degradation or pest outbreaks.