Forest Canopy Research Articles

Examining the Impact of Topography and Vegetation on Existing Forest Canopy Height Products from ICESat-2 ATLAS/GEDI Data

Forest canopy height (FCH) is an important variable for estimating forest biomass and ecosystem carbon sequestration. Spaceborne LiDAR data have been used to create wall-to-wall FCH maps, such as the forest tree height map of China (FCHChina), Global Forest Canopy Height 2020 (GFCH2020), and Global Forest Canopy Height 2019 (GFCH2019). However, these products lack comprehensive assessment. This study used airborne LiDAR data from various topographies (e.g., plain, hill, and mountain) to assess the impacts of different topographical and vegetation characteristics on spaceborne LiDAR-derived FCH products. The results show that GEDI–FCH demonstrates better accuracy in plain and hill regions, while ICESat-2 ATLAS–FCH shows superior accuracy in the mountainous region. The difficulty in accurately capturing photons from sparse tree canopies by ATLAS and the geolocation errors of GEDI has led to partial underestimations of FCH products in plain areas. Spaceborne LiDAR FCH retrievals are more accurate in hilly regions, with a root mean square error (RMSE) of 4.99 m for ATLAS and 3.85 m for GEDI. GEDI–FCH is significantly affected by slope in mountainous regions, with an RMSE of 13.26 m. For wall-to-wall FCH products, the availability of FCH data is limited in plain areas. Optimal accuracy is achieved in hilly regions by FCHChina, GFCH2020, and GFCH2019, with RMSEs of 5.52 m, 5.07 m, and 4.85 m, respectively. In mountainous regions, the accuracy of wall-to-wall FCH products is influenced by factors such as tree canopy coverage, forest cover types, and slope. However, some of these errors may stem from directly using current ATL08 and GEDI L2A FCH products for mountainous FCH estimation. Introducing accurate digital elevation model (DEM) data can improve FCH retrieval from spaceborne LiDAR to some extent. This research improves our understanding of the existing FCH products and provides valuable insights into methods for more effectively extracting accurate FCH from spaceborne LiDAR data. Further research should focus on developing suitable approaches to enhance the FCH retrieval accuracy from spaceborne LiDAR data and integrating multi-source data and modeling algorithms to produce accurate wall-to-wall FCH distribution in a large area.

Total deposition of sulphur to coniferous forests in Sweden - Taking canopy exchange into account

In the low deposition situation of today at many of the long-term Swedish forest monitoring sites, the deposition measured as precipitation to the open field, i.e. bulk deposition of oxidized sulphur (S) is often higher or equal to deposition of S sampled under the forest canopies, i.e. as throughfall. This suggests that the total S deposition estimated using throughfall is underestimated. The reason for this is direct exchange of S with the forest canopies, leading to an underestimation which becomes evident in low-deposition areas. We describe a new method to estimate the dry deposition of S to coniferous forest based on measurements with Teflon string samplers as surrogate surfaces, in combination with measurements of the net throughfall for sodium (throughfall subtracted with wet deposition). The wet deposition was estimated from bulk deposition measurements on the open field, corrected for dry deposition to the collectors. The method was applied for Norway spruce forests at monitoring sites across Sweden during nine years 2014–2022, and total deposition was calculated based on wet deposition and the estimated dry deposition. The estimated annual total deposition of S as a mean value for coniferous forests ranged between 0.8 and 5.2 kg S ha−1 yr−1 with lowest values in northern Sweden and highest in southwest Sweden. The share of dry deposition of the total S deposition was between 20 and 53%. The mean annual deposition of S measured as throughfall during 2014–2022 for three different regions in Sweden was between 16 and 41% lower compared to the corresponding total deposition estimated with the new method. The canopy exchange of S was analyzed on a monthly basis as the difference between the estimated total deposition and the measured throughfall deposition of S. At most sites, there was a canopy uptake of S during the summer months and a leakage of S during the winter months. This indicates that the canopy exchange of S is a phenomenon that involves some biological activity.

Smoke Emissions and Buoyant Plumes above Prescribed Burns in the Pinelands National Reserve, New Jersey

Prescribed burning is a cost-effective method for reducing hazardous fuels in pine- and oak-dominated forests, but smoke emissions contribute to atmospheric pollutant loads, and the potential exists for exceeding federal air quality standards designed to protect human health. Fire behavior during prescribed burns influences above-canopy sensible heat flux and turbulent kinetic energy (TKE) in buoyant plumes, affecting the lofting and dispersion of smoke. A more comprehensive understanding of how enhanced energy fluxes and turbulence are related during the passage of flame fronts could improve efforts to mitigate the impacts of smoke emissions. Pre- and post-fire fuel loading measurements taken during 48 operational prescribed burns were used to estimate the combustion completeness factors (CC) and emissions of fine particulates (PM2.5), carbon dioxide (CO2), and carbon monoxide (CO) in pine- and oak-dominated stands in the Pinelands National Reserve of southern New Jersey. During 11 of the prescribed burns, sensible heat flux and turbulence statistics were measured by tower networks above the forest canopy. Fire behavior when fire fronts passed the towers ranged from low-intensity backing fires to high-intensity head fires with some crown torching. Consumption of forest-floor and understory vegetation was a near-linear function of pre-burn loading, and combustion of fine litter on the forest floor was the predominant source of emissions, even during head fires with some crowning activity. Tower measurements indicated that above-canopy sensible heat flux and TKE calculated at 1 min intervals during the passage of fire fronts were strongly influenced by fire behavior. Low-intensity backing fires, regardless of forest type, had weaker enhancement of above-canopy air temperature, vertical and horizontal wind velocities, sensible heat fluxes, and TKE compared to higher-intensity head and flanking fires. Sensible heat flux and TKE in buoyant plumes were unrelated during low-intensity burns but more tightly coupled during higher-intensity burns. The weak coupling during low-intensity backing fires resulted in reduced rates of smoke transport and dispersion, and likely in more prolonged periods of elevated surface concentrations. This research facilitates more accurate estimates of PM2.5, CO, and CO2 emissions from prescribed burns in the Pinelands, and it provides a better understanding of the relationships among fire behavior, sensible heat fluxes and turbulence, and smoke dispersion in pine- and oak-dominated forests.

Forest Canopy Height Estimation Combining Dual-Polarization PolSAR and Spaceborne LiDAR Data

Forest canopy height data are fundamental parameters of forest structure and are critical for understanding terrestrial carbon stock, global carbon cycle dynamics and forest productivity. To address the limitations of retrieving forest canopy height using conventional PolInSAR-based methods, we proposed a method to estimate forest height by combining single-temporal polarimetric synthetic aperture radar (PolSAR) images with sparse spaceborne LiDAR (forest height) measurements. The core idea of our method is that volume scattering energy variations which are linked to forest canopy height occur during radar acquisition. Specifically, our methodology begins by employing a semi-empirical inversion model directly derived from the random volume over ground (RVoG) formulation to establish the relationship between forest canopy height, volume scattering energy and wave extinction. Subsequently, PolSAR decomposition techniques are used to extract canopy volume scattering energy. Additionally, machine learning is employed to generate a spatially continuous extinction coefficient product, utilizing sparse LiDAR samples for assistance. Finally, with the derived inversion model and the resulting model parameters (i.e., volume scattering power and extinction coefficient), forest canopy height can be estimated. The performance of the proposed forest height inversion method is illustrated with L-band NASA/JPL UAVSAR from AfriSAR data conducted over the Gabon Lope National Park and airborne LiDAR data. Compared to high-accuracy airborne LiDAR data, the obtained forest canopy height from the proposed approach exhibited higher accuracy (R2 = 0.92, RMSE = 6.09 m). The results demonstrate the potential and merit of the synergistic combination of PolSAR (volume scattering power) and sparse LiDAR (forest height) measurements for forest height estimation. Additionally, our approach achieves good performance in forest height estimation, with accuracy comparable to that of the multi-baseline PolInSAR-based inversion method (RMSE = 5.80 m), surpassing traditional PolSAR-based methods with an accuracy of 10.86 m. Given the simplicity and efficiency of the proposed method, it has the potential for large-scale forest height estimation applications when only single-temporal dual-polarization acquisitions are available.

Forest floor nematode communities and associated tree canopies: Is there an ecological linkage?

We searched for patterns supporting the hypothesis of compositional and functional linkage between forest floor nematode communities and dominant tree canopies, while controlling for some relevant soil and climate variables. Twenty-one forest sampling sites scattered throughout the South-Eastern Carpathian basin were selected under spruce, beech, and hornbeam-oak canopies. The relative contribution of forest canopy type to nematode assemblage differentiation was estimated through nematode taxonomic composition and feeding guild structure. The forest canopy type had a significant effect on nematode taxon/feeding guild composition and diversity at stand level. Several (diagnostic) nematode taxa and feeding guilds were positively associated with and accurately predicted the forest canopy types considered. Apart from the herbivorous nematodes, all the other trophic guilds were significantly related, in terms of their relative abundance, to the forest canopy type. Both nematode taxonomic and trophic diversity were significantly higher under beech canopy compared with its two counterparts. The highest total nematode beta diversity, either taxonomic or trophic, was attained between hornbeam-oak and spruce canopies. Nematode taxonomic and trophic beta diversity between forest canopy types were largely determined by taxon replacement and respectively, by a nested trophic structure. Overall, four concordant and two discordant patterns were revealed between nematode taxon and feeding guild composition with respect to overlying forest canopy, all underpinning the addressed ecological linkage. The present results bring evidence regarding the important contribution of the forest canopy, along with climatic variables, in driving the taxonomic and functional composition/diversity of nematode communities from the soil organic horizon.

Tree diversity drives understory carbon storage rather than overstory carbon storage across forest types

Although numerous studies have proposed explanations for the specific and relative effects of stand structure, plant diversity, and environmental conditions on carbon (C) storage in forest ecosystems, understanding how these factors collectively affect C storage in different community layers (trees, shrubs, and herbs) and forest types (mixed, broad-leaved (E), broad-leaved (M), and coniferous forest) continues to pose challenges. To address this, we used structural equation models to quantify the influence of biotic factors (mean DBH, mean height, maximum height, stem density, and basal area) and abiotic factors (elevation and canopy openness), as well as metrics of species diversity (Shannon–Wiener index, Simpson index, and Pielou’s evenness) in various forest types. Our analysis revealed the critical roles of forest types and elevation in explaining a substantial portion of variability in C storage in the overstory layer, with a moderate influence of stand factors (mean DBH and basal area) and a slightly negative impact of tree species diversity (Shannon–Wiener index). Notably, forest height emerged as the primary predictor of C storage in the herb layer. Regression relationships further highlighted the significant contribution of tree species diversity to mean height, understory C storage, and branch biomass within the forest ecosystem. Our insights into tree species diversity, derived from structural equation modeling of C storage in the overstory, suggest that the effects of tree species diversity may be influenced by stem biomass in statistical reasoning within temperate forests. Further research should also integrate tree species diversity with tree components biomass, forest mean height, understory C, and canopy openness to understand complex relationships and maintain healthy and sustainable ecosystems in the face of global climate challenges.

On Canopy Rainfall Interception Modeling in a Eucalyptus Plantation

The interaction between the forest canopy and precipitation is a fundamental process for understanding the hydrological cycle in forests. Physical models have been applied to estimate canopy water interception, and their efficiency has been tested based on metrics used to assess hydrological models. For eucalyptus plantations in Brazil, more studies are needed on the canopy rainfall interception model. Thus, we calibrated the Gash model using two complete hydrological years of observation in a eucalyptus plantation in southeastern Brazil. The model’s parametrization was conducted using 17 trees individually in different planting spacings (3 m × 2 m, 3 m × 3 m, and 3 m × 5 m). The average values of the model’s parameters were taken to represent the forest, and the average parameters for each planting spacing were used to assess the model’s performance according to the planting spacings. We used NSE, KGE, and Pbias statistical metrics to assess the model’s performance. For individual trees and rainfall events, the model showed an average NSE and Pbias of 0.59 and 18.2%, respectively, meaning a “satisfactory” performance for eight trees and “poor” performance for nine trees. When the model was averaged for the entire forest and individual rainfall events were considered, the metrics were improved, being 0.643 for NSE and 8.2% for Pbias, indicating a “good” model performance, which was strengthened by an average KGE of 0.746. Regarding the model for the planting spacings, the best results were found for the 3.0 m × 2.0 m spacing (“a good performance”). For the other spacings, Pbias was higher than 15%, leading to inferior performance, but with the NSE and KGE compatible with “good” performance. The practical implications of our findings are significant, as they can be used to enhance the accuracy of models for a better understanding of the hydrological cycle in eucalyptus forests in Brazil, thereby contributing to more effective forest management and conservation.

L-Band Synthetic Aperture Radar and Its Application for Forest Parameter Estimation, 1972 to 2024: A Review.

Optical remote sensing can effectively capture 2-dimensional (2D) forest information, such as woodland area and percentage forest cover. However, accurately estimating forest vertical-structure relevant parameters such as height using optical images remains challenging, which leads to low accuracy of estimating forest stocks like biomass and carbon stocks. Thus, accurately obtaining vertical structure information of forests has become a significant bottleneck in the application of optical remote sensing to forestry. Microwave remote sensing such as synthetic aperture radar (SAR) and polarimetric SAR provides the capability to penetrate forest canopies with the L-band signal, and is particularly adept at capturing the vertical structure information of forests, which is an alternative ideal remote-sensing data source to overcome the aforementioned limitation. This paper utilizes the Citexs data analysis platform, along with the CNKI and PubMed databases, to investigate the advancements of applying L-band SAR technology to forest canopy penetration and structure-parameter estimation, and provides a comprehensive review based on 58 relevant articles from 1978 to 2024 in the PubMed database. The metrics, including annual publication numbers, countries/regions from which the publications come, institutions, and first authors, with the visualization of results, were utilized to identify development trends. The paper summarizes the state of the art and effectiveness of L-band SAR in addressing the estimation of forest height, moisture, and forest stocks, and also examines the penetration depth of the L-band in forests and highlights key influencing factors. This review identifies existing limitations and suggests research directions in the future and the potential of using L-band SAR technology for forest parameter estimation.

The genera Chrysillaand Phintelloidesrevisited with the description of a new species (Araneae, Salticidae) using digital specimen DOIs and nanopublications.

Two Southeast Asian spider collections: that of Frances and John Murphy, now in the Manchester University Museum and the Deeleman collection, now at the Naturalis Biodiversity Center in Leiden constituted the basis of this analysis of Chrysilla Thorell, 1887 and related genera. The latter collection also includes many thousands of spiders obtained by canopy fogging for an ecological project in Borneo by A. Floren. Some incongruences within the genera of the tribe Chrysillini are disentangled. The transfer of C.jesudasi Caleb & Mathai, 2014 from Chrysilla as type species of Phintelloides Kanesharatnam & Benjamin, 2019, based on analysis of molecular data is validated by morphology. An interesting new species known only from the forest canopy in Borneo, Phintelloidesscandens sp. nov, is described based on both male and female specimens. Distinguishing chrysilline genera is mostly based on traditional somatic characters, e.g., habitus, carapace and abdomen patterns, mouthparts, and genital organs. The utility of two character systems for distinguishing chrysilline genera is highlighted: 1) the presence of a flexible, articulating embolic tegular branch (etb) in combination with the conformation of the characteristic construction of the epigyne in Chrysilla and Phintelloides; 2) presence of red colour on carapace and abdomen of live males and females, in combination with abundant blue/violet/white iridescent scales such as inChrysilla and Siler. The red colour usually gets lost in alcohol, hampering species identification of alcohol material. The genera Chrysilla andPhintelloidesare redefined. Specimens of the heretofore unknown female of Chrysilla deelemani Prószyński & Deeleman-Reinhold, 2010 are described. The male and female ofChrysillalauta and male of C.volupe are redescribed. The genus Chrysilla is diagnosed and discriminated from PhintellaBösenberg & Strand, 1906, SilerSimon, 1889, Phintelloides Kanesharatnam & Benjamin, 2019 andProszynskiaKanesharatnam & Benjamin, 2019. The structure of the female genital organ of Phintelloidesflavumi Kanesharatnam & Benjamin, 2019 is scrutinized and the generic placement of Phintelloides is discussed. Males and females of one of the most variable species, Phintelloidesversicolor (C. L. Koch, 1846) are redescribed.Phintelloidesmunita(Bösenberg & Strand, 1906) is removed from synonymy with P.versicolor. Phintellaleucaspis Simon 1903 (male, Sumatra) is synonymized withP.versicolor.Biodiversity data are increasingly reliant on digital infrastructure. By linking physical specimens to digital representations of their associated data, we can lower barriers to information flow. Here we demonstrate a workflow whereby persistent identifiers (PIDs) in the form of DOIs issued by DataCite are assigned to specimens. Recognized taxa are identified by their catalog of life identifier, or by registration in ZooBank where no catalog of life identifier is available. We demonstrate the use of nanopublications, creating a series of machine readable, scientifically meaningful assertions regarding the provenance and identification of cited specimens. All human agents associated with the specimen data are linked to a persistent identifier issued by either ORCiD or Wikidata.

Larger and older church forests promote bird species richness, diversity and resilience across northwest Ethiopia's deforested landscapes

Birds are vital bioindicators of biodiversity and ecosystem health, but their persistence and ecological roles are under severe threat from human activities in the Lake Tana Basin, Ethiopia. Rapid land and forest degradation driven by agricultural expansion, urbanization, and the rising demand for fuelwood imperil avian community structure and ecosystem functions in this region. However, amidst this ecological challenge, church forests have emerged as crucial sanctuaries. Despite their small size and isolation from each other by mainly agricultural land-use, these church forests provide indispensable ecosystem services and play a pivotal role in preserving biodiversity. Understanding the significance of church forests for avian biodiversity and the factors influencing bird species richness and community composition is paramount. To this end, a comprehensive survey was conducted in 24 church forests between November and December 2018. Data collection involved both point counts utilizing Audiomoth acoustic loggers and transect surveys. The study revealed a total of 131 bird species in the surveyed church forests, including endemic and threatened species. These birds exhibited diverse foraging habits and functional traits. Notably, church forest size and canopy cover were positively associated with species richness, highlighting the importance of preserving and potentially expanding these forested areas. Furthermore, the research identified key factors driving the similarity of bird communities in church forests, notably forest surface area, canopy cover, and altitude. Importantly, resilience metrics demonstrated significant positive relationships with species richness, emphasizing the conservation value of these unique ecosystems. Our study underscores the critical role of church forests in safeguarding avian biodiversity in the Lake Tana Basin, and our findings advocate for conservation efforts aimed at preserving and enhancing the region's church forests, as their continued degradation could jeopardize both ecological and socio-economic potential in this network of remnant forests.

Characterizing annual leaf area index changes and volume growth using ALS and satellite data in forest plantations

While Leaf Area Index (LAI) is critical for understanding forest canopy, photosynthesis and forest growth, traditional field-based LAI measurements are laborious and costly. Remote sensing offers a practical alternative for extensive assessments. Satellite imagery provides broad-scale, long-term monitoring; however, may lack detail needed to guide specific forest management actions. Conversely, Airborne Laser Scanning (ALS) provides accurate LAI estimates at fine spatial detail but is limited by cost and temporal monitoring constraints. Combining ALS data with satellite observations could enhance plantation management decisions by balancing extensive coverage with detailed observations. This study explores the integration of ALS and satellite remote sensing as a comprehensive alternative for assessing LAI and stand volume growth rate (m3/ha/year) in operational Pinus radiata plantations in central-south Chile. Our approach comprised four major steps. First, we applied the Beer-Lambert law using ALS vertical profiles to estimate LAI across a forest plantation (LAIALS). We found that ALS accurately estimated LAI across 121 plots (R2 = 0.82 and RMSE = 0.51). Second, we built a simple linear regression to link LAIALS with the Normalized Difference Moisture Index (NDMI) derived from surface reflectance information from the Landsat/Sentinel-2 satellites, resulting in an R2 of 0.53 and an RMSE of 1.17. This step showed a higher correlation with satellite data compared to using only ground-based LAI estimates (R2 = 0.38; RMSE = 1.18). Third, we transformed biweekly NDMI time series to LAI, then derived peak annual LAI as an indicator of mean annual increment (MAI) (R2 = 0.51; RMSE = 5.27 m³/ha/year). This allowed us to characterize stand growth and LAI on a yearly wall-to-wall basis. Throughout the modelling steps, we incorporated error propagation, allowing final estimates to be error bounded. This integrated approach serves as a tool for identifying and visualizing growth irregularities, guiding adaptive management strategies to maintain or enhance stand productivity over time.

Forest canopy cover affects microclimate buffering during an extreme heat event

Increasing temperatures and extreme heat episodes have become more common with climate change. While forests are known to buffer increasing temperatures (relative to non-forested areas), whether this buffering is maintained under extreme temperature events is relatively unknown. Here we assess whether forests continue to buffer microclimate (specifically temperatures) during an extreme heat event: the Pacific Northwest (PNW) heat dome in June 2021. We use a combination of ground-based and regional climate data and find that forest understories were 3 °C cooler than a clear-cut area and 4 °C cooler than regional temperatures during the PNW heat dome. By examining forests with different levels of canopy cover we also found that the buffering capacity of forests is greater under denser canopies even under extreme heat events. Additionally, we found vertical variation in thermal buffering, with the greatest amount of buffering at the surface of the forest floor. Overall, our findings suggest that temperate coastal forests, that are known to buffer average temperatures, can also act as microclimate buffers during extreme heat events like the heat dome that occurred in the PNW in 2021. This could be good news for forest dwelling organisms that are sensitive to such extreme heat events.

An efficient method for estimating tropical forest canopy height from airborne PolInSAR data

The study on PolInSAR forest canopy height(FCH) inversion is an essential branch within the SAR field, where the temporal decorrelation(TD) inherent in the interferometric complex coherence of repeat-pass Polarization Interferometric Synthetic Aperture Radar (PolInSAR) data significantly impacts the precision of FCH estimation.This study is grounded in airborne multi-baseline PolInSAR data, employing Random Volume over Ground (RVoG) + VTD and Random Motion over Ground(RMoG) as the FCH inversion models. The classical RVoG three-stage method(TS) process was used to simplify the solution of RVoG+VTD and RMoG, and a novel, more efficient method was attempted to further streamline the solution of the RVoG+VTD model(RVoG+VTDs). The results demonstrate that the RVoG+VTDs model obtains the most satisfactory results, and the efficiency of the RVoG+VTDs model is 23 times more efficient than that of the RVoG+VTD; 19 times more efficient than that of the RMoG model, and 22 times more efficient than that of the RVoG model, respectively; and the inversion time consumed by the four models is 1.5 min, 35 min, 28 min, and 33 min, respectively. In the accuracy validation, the estimation accuracy of RVoG+VTDs still keeps the best accuracy, with corresponding R2 values for the four methods (RVoG+VTDs, RVoG+VTD, RMoG, and RVoG) equal to 0.813, 0.774, 0.804, and 0.770, respectively. The RMSE values are 6.626 m, 7.277 m, 6.774 m, and 7.335 m.The study’s conclusions illustrate the feasibility of solving the RVoG+VTD and RMoG model by fixing the extinction coefficients in the model, with RVoG+VTDs taking precedence over the model selection, which can provide a valuable reference for the application of spaceborne PolInSAR data.

Canopy temperatures strongly overestimate leaf thermal safety margins of tropical trees.

Current estimates of temperature effects on plants mostly rely on air temperature, although it can significantly deviate from leaf temperature (Tleaf). To address this, some studies have used canopy temperature (Tcan). However, Tcan fails to capture the fine-scale variation in Tleaf among leaves and species in diverse canopies. We used infrared radiometers to study Tleaf and Tcan and how they deviate from air temperature (ΔTleaf and ΔTcan) in multispecies tropical tree plantations at three sites along an elevation and temperature gradient in Rwanda. Our results showed high Tleaf (up to c. 50°C) and ΔTleaf (on average 8-10°C and up to c.20°C) of sun-exposed leaves during 10:00 h-15:00 h, being close to or exceeding photosynthetic heat tolerance thresholds. These values greatly exceeded simultaneously measured values of Tcan and ΔTcan, respectively, leading to strongly overestimated leaf thermal safety margins if basing those on Tcan data. Stomatal conductance and leaf size affected Tleaf and Tcan in line with their expected influences on leaf energy balance. Our findings highlight the importance of leaf traits for leaf thermoregulation and show that monitoring Tcan is not enough to capture the peak temperatures and heat stress experienced by individual leaves of different species in tropical forest canopies.

Error Analysis and Accuracy Improvement in Forest Canopy Height Estimation Based on GEDI L2A Product: A Case Study in the United States

Various error factors influence the inversion of forest canopy height using GEDI full-waveform LiDAR data, and the interaction of these factors impacts the accuracy of forest canopy height estimation. From an error perspective, there is still a lack of methods to fully correct the impact of various error factors on the retrieval of forest canopy height from GEDI. From the modeling perspective, establishing clear coupling models between various environments, collection parameters, and GEDI forest canopy height errors is challenging. Understanding the comprehensive impact of various environments and collection parameters on the accuracy of GEDI data is crucial for extracting high-quality and precise forest canopy heights. First, we quantitatively assessed the accuracy of GEDI L2A data in forest canopy height inversion and conducted an error analysis. A GEDI forest canopy height error correction model has been developed, taking into account both forest density and terrain effects. This study elucidated the influence of forest density and terrain on the error in forest canopy height estimation, ultimately leading to an improvement in the accuracy of forest canopy height inversion. In light of the identified error patterns, quality control criteria for GEDI footprints are formulated, and a correction model for GEDI forest canopy height is established to achieve high-precision inversion. We selected 19 forest areas located in the United States with high-accuracy Digital Terrain Models (DTMs) and Canopy Height Models (CHMs) to analyze the error factors of GEDI forest canopy heights and assess the proposed accuracy improvement for GEDI forest canopy heights. The findings reveal a decrease in the corrected RMSE value of forest canopy height from 5.60 m to 4.19 m, indicating a 25.18% improvement in accuracy.

The Impact of Changing Climate on an Endangered Epiphytic Orchid (Pleione formosana) in a Montane Cloud Forest and the Conservation Challenge Ahead.

Pleione formosana Hayata is an endemic orchid that was once widely distributed across the mid-elevations of Taiwan. However, populations of this orchid have steadily shrunk due to orchid poaching in most of its habitats. By correlating data from micrometeorological stations that we installed in the cloud forest canopy at the study site, Yuanyang Lake (YYL) from 2017, we discovered the critical role of spring rainfall in triggering flowering and summer rainfall in promoting the growth of new bulbs. We found that rising temperatures and frequent drought events threaten orchid growth, potentially leading to pathogen infections. We climbed old-growth yellow cypresses to collect seed capsules of P. formosana for in vitro germination at YYL beginning in the autumn of 2018. Orchid plantlets were reintroduced to the study site in mid-August of 2022. However, the seedlings failed to survive the summer of 2023. This study is the first persistent monitoring of this rare orchid in the forest canopy of this old-growth cloud forest. Based on the result, we propose conservation strategies and directions for protecting this orchid on a regional scale. Our study highlights the mounting challenge to conservation efforts posed by global climate change.

Improving extraction of forest canopy height through reprocessing ICESat-2 ATLAS and GEDI data in sparsely forested plain regions

ABSTRACT Forest canopy height (FCH) is one of the most important variables for carbon stock estimation. While many studies have focused on extracting FCH from spaceborne LiDAR in regions with spatially continuous and large patch sizes of forested lands, limited research has addressed the challenges of FCH extraction in plain regions with sparse and fragmented forest distributions. In this study, we proposed innovative processing approaches to extract FCH from ICESat-2 photons and GEDI footprints in the plain regions of Anhui Province, China. Specifically, we proposed a sectional photon denoising method for processing ICESat-2 data and a geolocation error correction method for processing GEDI data. Airborne LiDAR data were used to validate the extracted FCH products across typical plain regions. The results demonstrated the effectiveness of the proposed methods in improving FCH extraction accuracy. Evaluation indicated that the directly extracted FCH products from ATL08 and GEDI L2A had Pearson’s correlation coefficients (r) of 0.6 and 0.93, respectively. After processing with the proposed methods, the 2019 FCH products from ICESat-2 exhibited r of 0.82 and relative root mean square error (rRMSE) of 31.11% based on 3,217 ICESat-2 segments, and the products from GEDI showed r of 0.96 and rRMSE of 18.35% based on 4,862 GEDI footprints. Further application of these methods to extract FCH products from GEDI and ICESat-2 for the years 2020, 2021, and 2022 indicated their promise for addressing sparse vegetation coverage in plain regions.

Physically based modelling of spectral transmittance through forest canopies

Abstract Physically based models simulating the spectral transmittance of solar radiation through forest canopies are useful tools for examining the connections between the shortwave radiation environment and the productivity and biodiversity of the forest floor. We report a comprehensive evaluation of two approaches simulating forest canopy spectral transmittance. The approaches were (i) three‐dimensional radiative transfer modelling in canopies composed of individual trees filled with turbid media and (ii) photon recollision probability theory (p‐theory), and were implemented using DART‐FT and PARAS models, respectively. The simulations were evaluated against mean and standard deviation of canopy transmittance spectra measured under clear‐sky conditions in forest plots across central and Northern Europe. In general, both models agreed well with the in situ measurements. They performed equally in conifer forests, while PARAS had a slightly lower accuracy than DART‐FT in broadleaved forests. We conclude that both approaches produce realistic simulations of canopy spectral transmittance at the spatial scale tested in this study, and that p‐theory constitutes a computationally efficient and easy‐to‐parameterize alternative to three‐dimensional radiative transfer.

Impacts of forest canopy heterogeneity on plot-scale hydrometeorological variables - Insights from an experiment in the humid boreal forest with the Canadian Land Surface Scheme

High latitude regions, including the circumpolar boreal biome, are experiencing important changes in the availability of usable surface water because of climate change. In this context, an adequate representation of the land-atmosphere interaction is critical to ensure optimal management of current and future water resources, forest management, and climate prediction. However, the task is particularly intricate in high-latitude boreal forest, as land surface model faces several challenges due to the unique environmental conditions and ecological characteristics. The objective of this study is to quantify the impact of forest landscape heterogeneity, specifically stand leaf-area index (LAI), soil texture, and drainage regime, on surface water and energy balance in a small boreal high-latitude sub-catchment. To this end, hydrometeorological conditions at seventeen 20×20 m plots in a 1-km2 boreal forest sub-basin are simulated using the Canadian Land Surface Scheme (CLASS), a land surface model, at the point scale. The subplot-scale soil texture, drainage regime, and vegetation characteristics and type are based as closely as possible on field measurements and observations for the 17 plots. The model-driven experiment comprises two sets of simulations using CLASS, each employing the same model setup and run for the 17 experimental plots. The main set employs meteorological forcing from a local micrometeorological tower within the sub-basin to investigate the plot-to-plot variability of albedo, energy fluxes, and soil state variables. A second set of simulations is conducted using meteorological forcing from the ERA5-Land reanalysis, which spans from 1986 to 2022. This data provides a longer time series, enabling a more accurate representation of the interannual climatic variability in the sub-basin. The results of the main and secondary sets of CLASS simulations are used to assess the plot-to-plot and temporal variability of several key hydrometeorological variables by calculating a monthly spread. In brief, the following conclusions and broader implications can be drawn from the findings: i) The simulated total annual evapotranspiration remains relatively uniform between plots despite notable variation in its partitioning from plot to plot. ii) In the presence of a full snowpack, the albedo exhibits substantial heterogeneity at the subplot scale, linked to the canopy's LAI. iii) Local soil properties, drainage regime, and vegetation structure and type exhibit substantial influence on the plot-to-plot variability in soil water content. iv) When parameterized with localized observations and measurements, CLASS can represent and be responsive to the complex dynamics of energy and water fluxes at the plot scale within the heterogeneous surface of boreal forests.

Evaluating crown scorch predictions from a computational fluid dynamics wildland fire simulator

BackgroundCrown scorch—the heating of live leaves, needles, and buds in the vegetative canopy to lethal temperatures without widespread combustion—is one of the most common fire effects shaping post-fire canopies. Despite the ability of computational fluid dynamic models to finely resolve fire activity and buoyant plume dynamics including heterogenous 3D distributions of forest canopy heating, these models have had only limited use in simulating fire effects and have not been used to evaluate crown scorch. Here, we demonstrate a method of evaluating crown scorch using a computational fluid dynamics model, FIRETEC, and validate this approach by simulating the experiments that were used to develop Van Wagner’s 1973 crown scorch model.ResultsThe average scorch height prediction from FIRETEC compares well with the empirical model derived by Van Wagner, which is the most widely used empirical model for crown scorch. We further find that the 3D buoyant plume dynamics from a steady and homogeneous idealized heat source on the ground results in a spatially heterogenous crown scorch pattern reflecting complex heating dynamics that are best represented by percent scorch rather than height of scorch.ConclusionsThe ability of the computational fluid dynamics model to capture variation in crown scorch due to 3D buoyant plume dynamics provides direct links between forest structure, fire behavior, and fire effects that can be used by forest managers and researchers to better understand how fires result in crown damage under various environmental and management scenarios.