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The effect of climate change on forest dynamics is likely to increase in importance in the forthcoming decades. For this reason, it is essential to predict the extent to which changes in temperature, precipitation, and atmospheric CO2 might affect the development of forest ecosystems and successional pathways. The gap model ZELIG-CFS was used to simulate the potential long-term effects of climate change on species-specific annual change in mean basal area and stand density under two scenarios of representative concentration pathways (RCP), 4.5 and 8.5, for the boreal forest region of Ontario, Canada, where mean temperature, precipitation, and atmospheric CO2 are expected to increase. Forest ecosystems in this boreal region included pure and mixed stands of black spruce (Picea mariana [Mill.] B.S.P.), paper birch (Betula papyrifera Marsh.), balsam fir (Abies balsamea [L.] Mill.), jack pine (Pinus banksiana Lamb.), trembling aspen (Populus tremuloides Michx.), white spruce (Picea glauca [Moench] Voss), northern white cedar (Thuja occidentalis L.), American larch (Larix laricina [Du Roi] K. Koch), and balsam poplar (Populus balsamifera L.). Simulation results under climate change generally predicted a decline in the basal area and stand density for black spruce, balsam fir, jack pine, and white spruce, but an increase for paper birch, trembling aspen, American larch, and balsam poplar. However, the extent of change differed regionally among species. Forest composition is expected to change over the long term. Simulation results indicated that shade-intolerant deciduous and conifer species will increase their dominance over the 100-year time horizon. This transition toward the increasing presence of deciduous forests is likely explained by more favorable temperature conditions for their growth and development. [ABSTRACT FROM AUTHOR]

Extreme forest fires have historically been a significant concern in Canada, the Russian Federation, the USA, and now pose an increasing threat in boreal Europe. This paper deals with application of the wildFire cLimate impacts and Adaptation Model (FLAM) in boreal forests. FLAM operates on a daily time step and utilizes mechanistic algorithms to quantify the impact of climate, human activities, and fuel availability on wildfire probabilities, frequencies, and burned areas. In our paper, we calibrate the model using historical remote sensing data and explore future projections of burned areas under different climate change scenarios. The study consists of the following steps: (i) analysis of the historical burned areas over 2001–2020; (ii) analysis of temperature and precipitation changes in the future projections as compared to the historical period; (iii) analysis of the future burned areas projected by FLAM and driven by climate change scenarios until the year 2100; (iv) simulation of adaptation options under the worst-case scenario. The modeling results show an increase in burned areas under all Representative Concentration Pathway (RCP) scenarios. Maintaining current temperatures (RCP 2.6) will still result in an increase in burned area (total and forest), but in the worst-case scenario (RCP 8.5), projected burned forest area will more than triple by 2100. Based on FLAM calibration, we identify hotspots for wildland fires in the boreal forest and suggest adaptation options such as increasing suppression efficiency at the hotspots. We model two scenarios of improved reaction times—stopping a fire within 4 days and within 24 h—which could reduce average burned forest areas by 48.6% and 79.2%, respectively, compared to projected burned areas without adaptation from 2021–2099. [ABSTRACT FROM AUTHOR]

The use of mobile laser scanning for mapping forests has scarcely been studied in difficult forest conditions. In this paper, we compare the accuracy of retrieving tree attributes, particularly diameter at breast height (DBH), stem curve, stem volume, and tree height, using six different laser scanning systems in a managed natural boreal forest. These compared systems operated both under the forest canopy on handheld and unmanned aerial vehicle (UAV) platforms and above the canopy from a helicopter. The complexity of the studied forest sites ranged from easy to difficult, and thus, this is the first study to compare the performance of several laser scanning systems for the direct measurement of stem curve in difficult forest conditions. To automatically detect tree stems and to calculate their attributes, we utilized our previously developed algorithm integrated with a novel bias compensation method to reduce the overestimation of stem diameter arising from finite laser beam divergence. The bias compensation method reduced the absolute value of the diameter bias by 55–99%. The most accurate laser scanning systems were equipped with a Velodyne VLP-16 sensor, which has a relatively low beam divergence, on a handheld or UAV platform. In easy plots, these systems found a root-mean-square error (RMSE) of below 10% for DBH and stem curve estimates and approximately 10% for stem volume. With the handheld system in difficult plots, the DBH and stem curve estimates had an RMSE under 10%, and the stem volume RMSE was below 20%. Even though bias compensation reduced the difference in bias and RMSE between laser scanners with high and low beam divergence, the RMSE remained higher for systems with a high beam divergence. The airborne laser scanner operating above the forest canopy provided tree attribute estimates close to the accuracy of the under-canopy laser scanners, but with a significantly lower completeness rate for stem detection, especially in difficult forest conditions. [ABSTRACT FROM AUTHOR]

This paper presents the development and application of a deep learning-based approach for semi-automated detection of tar production kilns using new Finnish high-density Airborne Laser Scanning (ALS) data in the boreal taiga forest zone. The historical significance of tar production, an important livelihood for centuries, has had extensive environmental and ecological impacts, particularly in the thinly inhabited northern and eastern parts of Finland. Despite being one of the most widespread archaeological features in the country, tar kilns have received relatively little attention until recently. The authors employed a Convolutional Neural Networks (CNN) U-Net-based algorithm to detect these features from the ALS data, which proved to be more accurate, faster, and capable of covering systematically larger spatial areas than human actors. It also produces more consistent, replicable, and ethically sustainable results. This semi-automated approach enabled the efficient location of a vast number of previously unknown archaeological features, significantly increasing the number of tar kilns in each study area compared to the previous situation. This has implications also for the cultural resource management in Finland. The authors' findings have influenced the preparation of the renewal of the Finnish Antiquities Act, raising concerns about the perceived impacts on cultural heritage management and land use sectors due to the projected tenfold increase in archaeological site detection using deep learning algorithms. The use of environmental remote sensing data may provide a means of examining the long-term cultural and ecological impacts of tar production in greater detail. Our pilot studies suggest that artificial intelligence and deep learning techniques have the potential to revolutionize archaeological research and cultural resource management in Finland, offering promising avenues for future exploration. [ABSTRACT FROM AUTHOR]

Fires are one of the most widespread factors of changes in the ecosystems of boreal forests. The paper presents the results of a study of the morphological and physicochemical properties and soil organic matter (SOM) of Albic Podzols under pine forests (Pinus sylvestris L.) of the middle taiga zone of Siberia (Krasnoyrsky kray) with various time passed after a surface fire (from 1 to 121 years ago). The influence of forest fires in the early years on the chemical properties of Albic Podzols includes a decrease in acidity, a decrease in the content of water-soluble compounds of carbon and nitrogen and an increase in the content of light polycyclic aromatic hydrocarbons (PAHs) in organic and upper mineral horizons. Podzols of pine forests that were affected by fires more than forty-five years ago are close to manure forest soils according to most physical and chemical properties. Significant correlations were found between the thickness (r = 0.75, p < 0.05), the moisture content (r = 0.90, p < 0.05) of organic horizons and the content of ∑PAHs in the organic horizon (r = −0.71, p < 0.05) with the time elapsed after the fire (i.e., from 1 to 121 years). The index of the age of pyrogenic activity (IPA) calculated as the ratio of ∑ PAHs content in the organic horizon to ∑ PAHs at the upper mineral horizon is significantly higher in forests affected by fires from 1 to 23 years than for plots with «older» fires (45–121 years). Thus, the article presents the conserved and most changing factors under the impact of fires in the boreal forests of Russia. [ABSTRACT FROM AUTHOR]

Fires are a naturally cyclical factor regulating ecosystems' function and forming new postfire ecosystems. Peat soils are unique archives that store information about ecological and climatic changes and the history of past fires during the Holocene. The paper presents a reconstruction of the dynamics of fires in the subzone of the middle taiga of Western Siberia in the Holocene. Data on fires were obtained based on the results of a study of the content of macroscopic coal particles and radiocarbon dating. The effect of fires on soil organic matter (SOM) was estimated using 13C NMR spectroscopy and the content of polyaromatic hydrocarbons (PAHs). It is shown that throughout the Holocene, the peatlands studied were prone to fires. The conducted analyses show that the maximum content of charcoal particles is observed in the Atlantic (~9100–5800 cal. B.P.) and Subatlantic (~3100 cal. B.P. to the present) periods. The high correlation dependence of the content of coals with the content of PAHs (r = 0.56, p < 0.05) and aromatic structures of SOM (r = 0.61, p < 0.05) in peat horizons is shown, which can characterize these parameters as a reliable marker of pyrogenesis. [ABSTRACT FROM AUTHOR]

Wildfire is a threat for many boreal ecosystems and induces deep modifications in organic horizons. In this paper, we have considered fire-induced changes to the organic horizon properties. The effect of fire was studied by using a forest litter burning experiment. Sample heating was performed in the lab at fixed temperatures (200, 300 and 500 °C), on a set of O horizons developed under pine (Flavocetraria-Pinetum association) and spruce (Piceetum hylocomium splendens association) forest litters. Litters were analyzed in terms of pH, specific electrical conductivity, specific surface area, total carbon (Ctot) and nitrogen (Ntot) content, water-soluble carbon and nitrogen, δ13C and δ15N stable isotope analysis and 13C NMR spectroscopy. The mean pH values increased from ~5 to ~8.2 with an increase in the influence of temperature. The specific electrical conductivity and specific surface area properties increased as well from ~255 to ~432 and from 0.42 to 1.84, respectively. Ctot and Ntot decreased, but at the same time the inorganic carbon content increased. The aromaticity of organic matter after the fire increased. The results of the present study show that organic horizons are changed by wildfire and this discussion made it clear to help with the understanding how fire affects organic matter. [ABSTRACT FROM AUTHOR]

Wildfires in permafrost areas, including smoldering fires (e.g., "zombie fires"), have increasingly become a concern in the Arctic and subarctic. Their detection is difficult and requires ground truthing. Local and Indigenous knowledge are becoming useful sources of information that could guide future research and wildfire management. This paper focuses on permafrost peatland fires in the Siberian subarctic taiga linked to local communities and their infrastructure. It presents the results of field studies in Evenki and old-settler communities of Tokma and Khanda in the Irkutsk region of Russia in conjunction with concurrent remote sensing data analysis. The study areas located in the discontinuous permafrost zone allow examination of the dynamics of wildfires in permafrost peatlands and adjacent forested areas. Interviews revealed an unusual prevalence and witness-observed characteristics of smoldering peatland fires over permafrost, such as longer than expected fire risk periods, impacts on community infrastructure, changes in migration of wild animals, and an increasing number of smoldering wildfires including overwintering "zombie fires" in the last five years. The analysis of concurrent satellite remote sensing data confirmed observations from communities, but demonstrated a limited capacity of satellite imagery to accurately capture changing wildfire activity in permafrost peatlands, which may have significant implications for global climate. [ABSTRACT FROM AUTHOR]

Glyphosate herbicide is widely used to control bluejoint reedgrass (Calamagrostis canadensis (Michx.) Beauv.), trembling aspen (Populus tremuloides Michx.), and other competing species in regenerating white spruce (Picea glauca (Moench) Voss) plantations in Alberta, Canada. In 2004, we initiated a study to examine the effects of the aerial application of glyphosate herbicide on plant community diversity and tree growth near Calling Lake, Alberta. Four treatments were applied: (a) no treatment (control); (b) herbicide application in the first growing season after harvesting; (c) herbicide application in the third growing season after harvesting; and (d) herbicide application in the second and fourth growing seasons after harvesting (two treatments). After 11 growing seasons, species richness was not significantly affected by treatment, while Shannon and Simpson index values were highest in areas treated with herbicide in the first growing season. Herbicide treatment did not have a significant effect on the cover of bluejoint reedgrass after 11 growing seasons, but did significantly reduce trembling aspen and paper birch cover and height. Application of glyphosate in the second and fourth growing seasons resulted in the greatest reductions to aspen cover and height, as well as significant increases in spruce diameter at age 11. Simulations with the Mixedwood Growth Model indicate that all tested herbicide treatments will reduce aspen volume while increasing spruce volume at age 90, with the largest impacts evident where two treatments were applied. [ABSTRACT FROM AUTHOR]

Recently, as global climate change and local disturbances such as wildfires continue, long- and short-term changes in the high-latitude vegetation systems have been observed in various studies. Although remote sensing technology using optical satellites has been widely used in understanding vegetation dynamics in high-latitude areas, there has been limited understanding of various landscape changes at different spatiotemporal scales, their mutual relationships, and overall long-term landscape changes. The objective of this study is to devise a change monitoring strategy that can effectively observe landscape changes at different spatiotemporal scales in the boreal ecosystems from temporally sparse time series remote sensing data. We presented a new post-classification-based change analysis scheme and applied it to time series Landsat data for the central Yakutian study area. Spectral variability between time series data has been a major problem in the analysis of changes that make it difficult to distinguish long- and short-term land cover changes from seasonal growth activities. To address this issue effectively, two ideas in the time series classification, such as the stepwise classification and the lateral stacking strategies were implemented in the classification process. The proposed classification results showed consistently higher overall accuracies of more than 90% obtained in all classes throughout the study period. The temporal classification results revealed the distinct spatial and temporal patterns of the land cover changes in central Yakutia. The spatiotemporal distribution of the short-term class illustrated that the ecosystem disturbance caused by fire could be affected by local thermal and hydrological conditions of the active layer as well as climatic conditions. On the other hand, the long-term class changes revealed land cover trajectories that could not be explained by monotonic increase or decrease. To characterize the long-term land cover change patterns, we applied a piecewise linear model with two line segments to areal class changes. During the former half of the study period, which corresponds to the 2000s, the areal expansion of lakes on the eastern Lena River terrace was the dominant feature of the land cover change. On the other hand, the land cover changes in the latter half of the study period, which corresponds to the 2010s, exhibited that lake area decreased, particularly in the thermokarst lowlands close to the Lena and Aldan rivers. In this area, significant forest decline can also be identified during the 2010s. [ABSTRACT FROM AUTHOR]

In the context of global warming, the study of the long-term spatial change characteristics of boreal forest cover is not only important for global climate change and sustainable development research but can also provide support for further research on the response of boreal forest changes to climate change. Using Landsat TM/OLI images from 1980 to 2020 as the data source and Google Earth Engine (GEE) as the platform, Finland was selected as the study area of boreal forests, and typical sample points of different features were chosen to classify forested and non-forested land using the random forest algorithm combined with spectral indices and classified feature sets of tasseled cap transform to obtain the four-phase forest cover change maps of the region. GEE test sample points and random selection points of images from the GF-2 and GF-7 satellites were used for verification. The classification accuracy was 97.17% and 88.9%. The five-phase forest cover images were segmented by a 2° latitude zone, and the spatial and temporal dynamic changes in forest cover in the whole area and each latitude zone were quantified by pixel superposition analysis. The results showed that, in the past 40 years, the boreal forest cover in Finland changed significantly, and the forest cover decreased from 75.79% to 65.36%, by 10.43%. Forest change mainly occurs in coniferous forests, whereas broadleaf forests are more stable. The forest coverage in each latitude zone decreased to varying degrees, with higher changes occurring in high-latitude areas above 64° N between 1980 and 2000, and higher and more severe changes occurring in low-latitude areas below 64° N between 2000 and 2020. Coniferous forests are the dominant type of forest in Finland, and the degradation of coniferous forests in the south is likely to become more severe, whereas the north and above is likely to become more favorable for coniferous forests. More monitoring and research are needed to follow up on the very different changes in the north and south regions. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is increasing the occurrence of wildfires, especially in northern high latitudes, leading to a shift in land surface climate. This study aims to determine the predominant climatic effects of fires in boreal forests to assess their impact on vegetation composition, surface albedo, and snow dynamics. The influence of fire-induced changes on Earth's radiative forcing is investigated, while considering variations in burn severity and postfire vegetation structure. Six burn sites are explored in central Alaska's boreal region, alongside six control sites, by utilizing Moderate Resolution Imaging Spectroradiometer (MODIS)-derived albedo, Leaf Area Index (LAI), snowmelt timing data, AmeriFlux radiation, National Land Cover Database (NLCD) land cover, and Monitoring Trends in Burn Severity (MTBS) data. Key findings reveal significant postfire shifts in land cover at each site, mainly from high- to low-stature vegetation. A continuous increase in postfire surface albedo and negative surface shortwave forcing was noted even after 12 years postfire, particularly during the spring and at high-severity burn areas. Results indicate that the cooling effect from increased albedo during the snow season may surpass the warming effects of earlier snowmelt. The overall climate impact of fires depends on burn severity and vegetation composition. [ABSTRACT FROM AUTHOR]

Boreal forests nowadays act as a sink for atmospheric carbon dioxide; however, their sequestration capacity is highly sensitive to weather conditions and, specifically to ongoing climate warming. Extreme weather events such as heavy rainfalls or, conversely, heat waves during the growing season might perturb the ecosystem carbon balance and convert them to an additional CO2 source. Thus, there is an urgent need to revise ecosystem carbon fluxes in vast Siberian taiga ecosystems as influenced by extreme weather events. In this study, we focused on the soil CO2 pulses appearing after the rainfall events and quantification of their input to the seasonal cumulative CO2 efflux in the boreal forests in Central Siberia. Seasonal measurements of soil CO2 fluxes (both soil respiration and net soil exchange) were conducted during three consecutive frost-free seasons using the dynamic chamber method. Seasonal dynamics of net soil exchange fluxes demonstrated positive values, reflecting that soil respiration rates exceeded CO2 uptake in the forest floor vegetation layer. Moreover, the heavy rains caused a rapid pulse of soil emissions and, as a consequence, the release of additional amounts of CO2 from the soil into the atmosphere. A single rain event may cause a 5–11-fold increase of the NSE flux compared to the pre-rainfall values. The input of CO2 pulses to the seasonal cumulative efflux varied from near zero to 39% depending on precipitation patterns of a particular season. These findings emphasize the critical need for more frequent measurements of soil CO2 fluxes throughout the growing season which capture the CO2 pulses induced by rain events. This approach has inevitable importance for the accurate assessment of seasonal CO2 soil emissions and adequate predictions of response of boreal pine forests to climatic changes. [ABSTRACT FROM AUTHOR]

Roads are known to alter environmental conditions and the composition of road edge plant communities, particularly when exogenous materials are used as road surfacing. In this study, we evaluate the impact of gravel roads on the organic layer thickness (OLT) and aspen distribution in a boreal forest landscape of Eastern Canada. The OLT and aspen distribution were compared at different distances from the roads (0 m, 10 m, and >10 m) to determine whether a reduction in the OLT along the roads could explain the distribution of aspen along the road network, and in particular the role of the roads as habitat corridors. In addition, germination tests were carried out to determine whether mineral soil from the roads could promote aspen establishment, by comparing the germination rate of substrates consisting only of mineral soil or mosses, and substrates consisting of mosses covered with 0.5 cm or 2 cm of mineral soil. The presence of aspen in the study landscape is limited by thick organic deposits (≥50 cm). However, the thickness of these deposits is reduced to approximately 10 cm at the edges of gravel roads, in part by the transport of mineral soil from the roads. This reduction in the OLT facilitates the establishment of aspen and helps explain its distribution along the road network. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine whether the iPad Pro 12th generation LiDAR sensor is useful to measure tree diameter at breast height (DBH) in natural boreal forests. This is a follow-up to a previous study that was conducted in a research forest and identified the optimal method for (DBH) estimation as a circular scanning and fitting ellipses to 4 cm stem cross-sections at breast height. The iPad Pro LiDAR scanner was used to acquire point clouds for 15 sites representing a range of natural boreal forest conditions in Ontario, Canada, and estimate DBH. The secondary objective was to determine if tested stand (species composition, age, density, understory) or tree (species, DBH) factors affected the accuracy of estimated DBH. Overall, estimated DBH values were within 1 cm of actual DBH values for 78 of 133 measured trees (59%). An RMSE of 1.5 cm (8.6%) was achieved. Stand age had a large effect (>0.15) on the accuracy of estimated DBH values, while density, understory, and DBH had moderate effects (0.05–0.14). No trend was identified between accuracy and stand age. Accuracy improved as understory density decreased and as tree DBH increased. Inertial measurement unit (IMU) and positional accuracy errors with the iPad Pro scanner limit the feasibility of using this device for forest inventories. [ABSTRACT FROM AUTHOR]

Data on the main properties of Histic Podzols in the pine forests of semi-hydromorphic landscapes in the middle taiga of the Komi Republic after forest fires are presented. A decrease in topsoil horizon thickness by more than 7.6 times, an increase in litter density by 6 times, and a decrease in litter stock by 4 times were observed in postfire soil. There was an increase in carbon content in the pyrogenic horizon (48%) and in the upper part of the podzolic horizon—from 0.49 at the control plot to 1.16% after the fire. The accumulation of all studied trace metals (Cu—from 2.5 to 6.8 mg × kg−1; Zn—from 35.7 to 127.4 mg × kg−1; Ni—from 2.2 to 8.1 mg × kg−1; Pb—from 1.4 to 28.3 mg × kg−1; Cd—from 0.3 to 1.1 mg × kg−1) in soils after wildfires was recorded. The effect of the fire can be traced to a depth of approximately 20–30 cm. A significant influence of the pyrogenic factor on the alpha and beta bacterial diversity was noted. The bacterial response to a forest fire can be divided into an increased proportion of spore-forming and Gram-negative species with complex metabolism as well. [ABSTRACT FROM AUTHOR]

Northern boreal forests are characterized by accumulation of accumulation of peat (e.g., known as paludification). The functioning of northern boreal forest species and their capacity to adapt to environmental changes appear to depend on soil conditions. Climate warming is expected to have particularly pronounced effects on paludified boreal ecosystems and can alter current forest species composition and adaptation by changing soil conditions such as moisture, temperature regimes, and soil respiration. In this paper, we review and synthesize results from various reported studies (i.e., 88 research articles cited hereafter) to assess the effects of climatic warming on soil conditions of paludified forests in North America. Predictions that global warming may increase the decomposition rate must be considered in combination with its impact on soil moisture, which appears to be a limiting factor. Local adaptation or acclimation to current climatic conditions is occurring in boreal forests, which is likely to be important for continued ecosystem stability in the context of climate change. The most commonly cited response of boreal forest species to global warming is a northward migration that tracks the climate and soil conditions (e.g., temperature and moisture) to which they are adapted. Yet, some constraints may influence this kind of adaptation, such as water availability, changes in fire regimes, decomposer adaptations, and the dynamic of peat accumulation. In this paper, as a study case, we examined an example of potential effects of climatic warming on future paludification changes in the eastern lowland region of Canada through three different combined hypothetical scenarios based on temperature and precipitation (e.g., unchanged, increase, or decrease). An increase scenario in precipitation will likely favor peat accumulation in boreal forest stands prone to paludification and facilitate forested peatland expansion into upland forest, while decreased or unchanged precipitation combined with an increase in temperature will probably favor succession of forested peatlands to upland boreal forests. Each of the three scenarios were discussed in this study, and consequent silvicultural treatment options were suggested for each scenario to cope with anticipated soil and species changes in the boreal forests. We concluded that, despite the fact boreal soils will not constrain adaptation of boreal forests, some consequences of climatic warming may reduce the ability of certain species to respond to natural disturbances such as pest and disease outbreaks, and extreme weather events. [ABSTRACT FROM AUTHOR]

Stand age distribution is an important descriptor of boreal forest structure, which is directly linked to many ecosystem processes including the carbon cycle, the land-atmosphere interaction and ecosystem services, among others. Almost half of the global boreal biome is located in Russia. The vast extent, remote location, and limited accessibility of Russian boreal forests make remote sensing the only feasible approach to characterize these forests to their full extent. A wide variety of satellite observations are currently available to monitor forest change and infer its structure; however, the period of observations is mostly limited to the 2000s era. Reconstruction of wall-to-wall maps of stand age distribution requires merging longer-term site observations of forest cover change available at the Landsat scale at a subset of locations in Russia with the wall-to-wall coverage available from coarse resolution satellites since 2000. This paper presents a dataset consisting of a suite of multi-year forest disturbance samples and samples of undisturbed forests across Russia derived from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus images from 1985 to 2000. These samples provide crucial information regarding disturbance history in selected regions across the Russian boreal forest and are designed to serve as a training and/or validation dataset for coarse resolution data products. The overall accuracy and Kappa coefficient for the entire sample collection was found to be 83.98% and 0.83%, respectively. It is hoped that the presented dataset will benefit subsequent studies on a variety of aspects of the Russian boreal forest, especially in relation to the carbon budget and climate. [ABSTRACT FROM AUTHOR]

Numerous studies demonstrated the potential of the magnitude of interferometric coherence ∣γ∣ for forest growing stock volume (GSV) estimation in boreal forests. Coherence derived from images acquired under frozen conditions proved to be of specific interest. This also applies to PALSAR coherence, although affected by a comparatively large temporal baseline of at least 46 days. However, when working with spaceborne L-band data, acquired under unfrozen conditions, a large spread of ∣γ∣ was observed at all GSV levels. This scatter negatively affects the correlation of GSV and ∣γ∣. So far, the impact of tree species on ∣γ∣ has rarely been studied in this context, although the different tree geometries are likely to have an impact on volumetric decorrelation. This paper presents the results of a study investigating the impact of tree species on PALSAR coherence employing 36 interferograms. The observations show only a small impact of the tree species on ∣γ∣ during frozen conditions. At unfrozen conditions, the impact is about three times larger. Deciduous species (aspen, birch, larch) exhibit the lowest ∣γ∣, while coniferous species (fir, pine) feature the highest ∣γ∣. For example, at unfrozen conditions, the ∣γ∣ of fir is 0.15 greater than the ∣γ∣ of larch, while the mean ∣γ∣ of dense forest is 0.38. Accordingly, the impact of tree species on ∣γ∣ under unfrozen conditions causes a portion of the observed spread of the GSV-∣γ∣ relationship. Consequently, when aiming at ∣γ∣ based GSV assessment using L-band SAR data acquired during unfrozen conditions, the impact of the species on ∣γ∣ needs to be considered. For studies aiming at ∣γ∣ based GSV estimation across species, PALSAR data acquired at frozen conditions is preferable. [ABSTRACT FROM AUTHOR]

This paper describes the long-term effects on vegetation following the catastrophic fire in 1987 on the northern Great Xing'an Mountain by analyzing the AVHRR GIMMS 15-day composite normalized difference vegetation index (NDVI) dataset. Both temporal and spatial characteristics were analyzed for natural regeneration and tree planting scenarios from 1984 to 2006. Regressing post-fire NDVI values on the pre-fire values helped identify the NDVI for burnt pixels in vegetation stands. Stand differences in fire damage were classified into five levels: Very High (VH), High (H), Moderate (M), Low (L) and Slight (S). Furthermore, intra-annual and inter-annual post-fire vegetation recovery trajectories were analyzed by deriving a time series of NDVI and relative regrowth index (RRI) values for the entire burned area. Finally, spatial pattern and trend analyses were conducted using the pixel-based post-fire annual stands regrowth index (SRI) with a nonparametric Mann-Kendall (MK) statistics method. The results show that October was a better period compared to other months for distinguishing the post- and pre-fire vegetation conditions using the NDVI signals in boreal forests of China because colored leaves on grasses and shrubs fall down, while the leaves on healthy trees remain green in October. The MK statistics method is robustly capable of detecting vegetation trends in a relatively long time series. Because tree planting primarily occurred in the severely burned area (approximately equal to the Medium, High and Very High fire damage areas) following the Daxing'anling fire in 1987, the severely burned area exhibited a better recovery trend than the lightly burned regions. Reasonable tree planting can substantially quicken the recovery and shorten the restoration time of the target species. More detailed satellite analyses and field data will be required in the future for a more convincing validation of the results. [ABSTRACT FROM AUTHOR]

Leaf Area Index (LAI) is an important input variable for forest ecosystem modeling as it is a factor in predicting productivity and biomass, two key aspects of forest health. Current in situ methods of determining LAI are sometimes destructive and generally very time consuming. Other LAI derivation methods, mainly satellite-based in nature, do not provide sufficient spatial resolution or the precision required by forest managers for tactical planning. This paper focuses on estimating LAI from: (i) height and density metrics derived from Light Detection and Ranging (LiDAR); (ii) spectral vegetation indices (SVIs), in particular the Normalized Difference Vegetation Index (NDVI); and (iii) a combination of these methods. For the Hearst Forest of Northern Ontario, in situ measurements of LAI were derived from digital hemispherical photographs (DHPs) while remote sensing variables were derived from low density LiDAR (i.e., 1 m-2) and high spatial resolution WorldView-2 data (2 m). Multiple Linear Regression (MLR) models were generated using these variables. Results from these analyses demonstrate: (i) moderate explanatory power (i.e., R² = 0.53) for LiDAR height and density metrics that have proven to be related to canopy structure; (ii) no relationship when using SVIs; and (iii) no significant improvement of LiDAR models when combining them with SVI variables. The results suggest that LiDAR models in boreal forest environments provide satisfactory estimations of LAI, even with narrow ranges of LAI for model calibration. Models derived from low point density LiDAR in a mixedwood boreal environment seem to offer a reliable method of estimating LAI at high spatial resolution for decision makers in the forestry community. This method can be easily incorporated into simultaneous modeling efforts for forest inventory variables using LiDAR. [ABSTRACT FROM AUTHOR]

Wildfire in Siberia is extensive, affecting up to 15 Mha annually. The proportion of the vegetation affected by severe fires is yet unknown, and it is a problem that requires a solution because post-fire mortality of tree stands in Siberian taiga has a strong effect on the global budget of carbon. The impact of fire in our area of interest in eastern Siberia was analyzed using the normalized burn ratio (NBR) and its pre- versus post-fire difference (dNBR) applied to Landsat-8 (OLI) collected in 2020–2021. In this paper, we present the classification of fire impact in relation to dominant tree stands and vegetation types in boreal forests of eastern Siberia. The dNBR of post-fire plots ranged widely (0.30–0.60) in homogeneous larch (Larix sibirica, L. gmelinii) forests, pine (Pinus sylvestris) forests, dark coniferous stands (Pinus sibirica, Abies sibirica, Picea obovata), sparse larch stands, and Siberian dwarf pine (Pinus pumila) stands. We quantified the proportions of low, moderate, and high fire severity (37%, 39%, and 24% of the total area burned, respectively) in dense tree stands, which were varied to 30%, 57%, and 13%, respectively, for sparse stands and tundra vegetation dominated in the north of eastern Siberia. The proportion of severe fires varied according to the transition from dominant larch stands (33.2% of the area burned) to pine (12.6%) and dark coniferous (up to 26.4%). The current proportion of stand-replacement fires in eastern Siberia is 12–33%, depending on vegetation type and tree density, which is about 2500 thousand hectares in 2021 in the region. According to our findings, the "healthy/unburned vegetation" class was quantified as well at least 700 thousand hectares in 2021. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI) is one of the most commonly used ecological variables in describing forests. Since 2000, 1-km resolution Moderate Resolution Imaging Spectroradiometer (MODIS)-based 8-day composites of LAI have been operationally available from the National Aeronautics and Space Administration (NASA), USA, at no cost to the user. In this paper, we present a simple protocol to enhance the spatial resolution of NASA-produced LAI composites to 250-m resolution. This is done by fusing MODIS-based estimates of enhanced vegetation index (EVI), consisting of 16-day 250-m resolution composites (also from NASA), with estimates of LAI. We apply the protocol to derive 250-m resolution maps of LAI for the boreal forest region of northern Alberta, Canada. Data fusion was possible in this study because of the inherent linear correlation that exists between EVI and LAI for the April to October growing period of 2005-2008, producing r²-values of 0.85-0.95 and p-values < 0.0001. Comparison of MODIS-based LAI with field-based measurements using the Tracing Radiation and Architecture of Canopies (TRAC) sensor and LAI-2000 Plant Canopy Analyzer showed reasonable agreement across values; statistical comparison of LAI data points produced an r²-value of 0.71 and a p-value <0.0001. Seventy one percent of MODIS-based LAI were within ±20% of field estimates. [ABSTRACT FROM AUTHOR]

Boreal forest ecosystems are regions vulnerable to climate change. Such areas act as the main atmospheric carbon sinks in the world. Wildfires are among the drivers of ecosystem modification and functioning. Boreal wildfires emit an annual average of about 10% of global fire emissions. Taking into account recent climate warming and increases in the frequency of wildfires, boreal forests might switch their functional role from carbon sink to an additional source of atmospheric carbon. Soil respiration is the second largest component of the global carbon cycle and is highly sensitive to disturbance factors, including wildfires. To study the effect of wildfires on soil CO2 emission rates, the fire chronosequence was investigated. During the first few years following the fire, the soil CO2 emission rates were lower compared with the usual levels. It was found that 23 years after a fire, the site demonstrated transition behavior in soil emission rates between disturbed and completely recovered areas. The emission rates at the earliest successional stages are mainly controlled by soil moisture during the summer period. For the other successional stages, soil temperature had a huge impact on soil emission. [ABSTRACT FROM AUTHOR]

The boreal forest of northwestern North America covers an extensive area, contains vast amounts of carbon in its vegetation and soil, and is characterized by extensive wildfires. Catastrophic crown fires in these forests are fueled predominantly by only two evergreen needle-leaf tree species, black spruce (Picea mariana (Mill.) B.S.P.) and lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.). Identifying where these flammable species grow through time in the landscape is critical for understanding wildfire risk, damages, and human exposure. Because medium resolution landcover data that include species detail are lacking, we developed a compound modeling approach that enabled us to refine the available evergreen forest category into highly flammable species and less flammable species. We then expanded our refined landcover at decadal time steps from 1984 to 2014. With the aid of an existing burn model, FlamMap, and simple succession rules, we were able to predict future landcover at decadal steps until 2054. Our resulting land covers provide important information to communities in our study area on current and future wildfire risk and vegetation changes and could be developed in a similar fashion for other areas. [ABSTRACT FROM AUTHOR]

This study aimed to determine the optimal approach for estimating stem diameter distributions (SDD) from airborne laser scanning (ALS) data using point cloud metrics (Mals), a canopy height model (CHM) texture metrics (Mtex), and a combination thereof (Mcomb). We developed area-based models (i) to classify SDD modality and (ii) predict SDD function parameters, which we tested for 5 modelling techniques. Our results demonstrated little variability in the performance of SDD modality classification models (mean overall accuracy: 72%; SD: 2%). Our best SDD function parameter models were generally fitted with Mcomb, with R2 improvements up to 0.25. We found the variable Correlation, originating from Mtex, to be the most important predictor within Mcomb. Trends in the performance of the predictor groups were mostly consistent across the modelling techniques within each parameter. Using an Error Index (EI), we determined that differentiating modality prior to estimating SDD improved the accuracy of estimates for bimodal plots (~12% decrease in EI), which was trivially not the case for unimodal plots (<1% increase in EI). We concluded that (i) CHM texture metrics can be used to improve the estimate of SDD parameters and that (ii) differentiating for modality prior to estimating SSD is especially beneficial in stands with bimodal SDD. [ABSTRACT FROM AUTHOR]

In this review and synthesis paper, we review the resilience of secondary forests to climate change through the lenses of ecosystem legacies and landscape diversity. Ecosystem legacy of secondary forests was categorized as continuous forest, non-continuous forest, reassembled after conversion to other land uses, and novel reassembled forests of non-native species. Landscape diversity, including landforms that create varied local climatic and soil conditions, can buffer changing climate to some extent by allowing species from warmer climates to exist on warm microsites, while also providing refugial locations for species that grow in cool climates. We present five frames that allow forest managers to visualize a trajectory of change in the context of projected regional climate change, which are: Frame 1 (persistence), keep the same dominant tree species with little change; Frame 2 (moderate change), keep the same tree species with large changes in relative abundance; Frame 3 (forest biome change), major turnover in dominant tree species to a different forest biome; Frame 4 (forest loss), change from a forest to a non-forest biome; and Frame 5 (planted novel ecosystem), establish a novel ecosystem to maintain forest. These frames interact with ecosystem legacies and landscape diversity to determine levels of ecosystem resilience in a changing climate. Although forest readiness to adapt to Frame 1 and 2 scenarios, which would occur with reduced greenhouse gas emissions, is high, a business as usual climate change scenario would likely overwhelm the capacity of ecosystem legacies to buffer forest response, so that many forests would change to warmer forest biomes or non-forested biomes. Furthermore, the interactions among frames, legacies, and landscape diversity influence the transient dynamics of forest change; only Frame 1 leads to stable endpoints, while the other frames would have transient dynamics of change for the remainder of the 21st century. [ABSTRACT FROM AUTHOR]

This paper presents a scaling approach for estimating sapwood area at the stand level using knowledge obtained for individual trees of five boreal species: Populus tremuloides (Michx.), Pinus contorta (Doug. ex Loud. var. latifolia Engelm.), Pinus banksiana (Lamb.), Picea mariana (Mill.) BSP, and Picea glauca (Moench) Voss. Previously developed allometric models for sapwood depth and diameter at breast height for individual tree species were used to build stand level sapwood area estimates as well as stand level leaf area estimates, in pure and mixed vascular vegetation stands. A stand's vegetation heterogeneity is considered in the scaling approach by proposing regression models for each species. The new combined scaling approach drew strong linear correlations at the stand scale between sapwood area and leaf area using observations taken in mixed stands of Southern Alberta, Canada. This last outcome suggests a good linear relationship between stand sapwood area and stand leaf area. The accuracy of the results was tested by observing each regression model's adequacy and by estimating the error propagated through the whole scaling process. [ABSTRACT FROM AUTHOR]

Alterations in plant litter inputs into the soil are expected to significantly affect soil greenhouse gas (GHG) emissions. However, the influence on boreal forest soils is not clear, given the large amount of accumulated soil organic matter that may buffer the impacts from the input of fresh litter. In this study, we conducted a litter manipulation experiment to explore the effects of the litter layer on soil GHG fluxes in a Dahurian larch (Larix gmelinii) forest ecosystem in northeastern China. Three litter treatments were implemented, namely aboveground litter removal (LR), litter double (LD), and unchanged litter input (CK). The associated microclimate, litter characteristics, and soil properties were also measured. The results showed that this larch forest soil acts as a source of CO2 and N2O but acts as a sink for CH4 for all litter manipulation treatments. LD increased the soil CO2 and N2O fluxes by 15% and 34%, while LR decreased them by 8% and 21%, respectively. However, soil CH4 uptake decreased by 34% in LD treatment and increased by 22% in LR treatment, respectively. Litter manipulation treatments can not only affect soil GHG fluxes directly but also, via their effects on soil MBC, NH4+−N, and NO3−−N content, indirectly affect variations in soil CO2, CH4 and N2O fluxes, respectively. Our study highlights the importance of the plant litter layer in regulating soil GHG between the atmosphere and soil in a Dahurian larch forest ecosystem, especially for litter addition. Considering the natural increase in litter quantity over time, this important regulatory function is essential for an accurate estimation of the role of boreal forests in mitigating future climate change. [ABSTRACT FROM AUTHOR]

Time series of SAR imagery combined with reference ground data can be suitable for producing forest inventories. Copernicus Sentinel-1 imagery is particularly interesting for forest mapping because of its free availability to data users; however, temporal dependencies within SAR time series that can potentially improve mapping accuracy are rarely explored. In this study, we introduce a novel semi-supervised Long Short-Term Memory (LSTM) model, CrsHelix-LSTM, and demonstrate its utility for predicting forest tree height using time series of Sentinel-1 images. The model brings three important modifications to the conventional LSTM model. Firstly, it uses a Helix-Elapse (HE) projection to capture the relationship between forest temporal patterns and Sentinel-1 time series, when time intervals between datatakes are irregular. A skip-link based LSTM block is introduced and a novel backbone network, Helix-LSTM, is proposed to retrieve temporal features at different receptive scales. Finally, a novel semisupervised strategy, Cross-Pseudo Regression, is employed to achieve better model performance when reference training data are limited. CrsHelix-LSTM model is demonstrated over a representative boreal forest site located in Central Finland. A time series of 96 Sentinel-1 images are used in the study. The developed model is compared with basic LSTM model, attention-based bidirectional LSTM and several other established regression approaches used in forest variable mapping, demonstrating consistent improvement of forest height prediction accuracy. At best, the achieved accuracy of forest height mapping was 28.3% relative root mean squared error (rRMSE) for pixel-level predictions and 18.0% rRMSE on stand level. We expect that the developed model can also be used for modeling relationships between other forest variables and satellite image time series. [ABSTRACT FROM AUTHOR]

Albic podzols under pine forests are more prone to fires on the planet. The influence of fire extends to all soil components, including chemical properties, microbiological characteristics, and the composition and structure of soil organic matter, which persists for a long time. Here, we present the results of a study of the morphological, physicochemical, and microbiological properties and features of soil organic matter (SOM) in the albic podzols of pine forests (Pinus sylvestris L.) not exposed to fires for a long time (from 45 to 131 years). The study areas are characterized by different numbers of old fires (from four to five) that occurred over the previous several centuries in various territories of the Russian Federation such as Central Siberia (CS) and the European North (EN). In general, the albic podzols developing in CS and EN are characterized by similar morphological and physicochemical properties, with high acidity and poor mineral horizons. In terms of the lower vegetation layer and stand parameters, forest communities at the CS sites have a lower density and species diversity than those in EN. The ground cover is almost completely restored 45 years after the surface fire. The upper mineral horizon of albic podzols in EN contains higher PAHs in comparison with similar horizons of the CS sites. In the soil of EN pine forests, the MB content in the mineral horizons is, on average, three times higher than those in CS. Differences were also found in the qualitative composition of the studied soils' microbiomes. The EN soil communities are represented by a wide variety of bacteria and fungi. The presented soil parameters can be used as a reference in assessing the increasing impact of fires on pine forests and podzols. [ABSTRACT FROM AUTHOR]

Seismic lines are narrow, linear corridors cleared through forests for oil and gas exploration. Their inconsistent recovery has led to Alberta's forests being highly fragmented, resulting in the need for seismic line restoration programs and subsequent monitoring. Light detection and ranging (LiDAR) is becoming an increasingly popular technology for the fast and accurate measurement of forests. Mobile LiDAR scanners (MLS) are emerging as an alternative to traditional aerial LiDAR due to their increased point cloud density. To determine whether MLS could be effective for collecting vegetation data on seismic lines, we sampled 17 seismic lines using the Emesent Hovermap™ in leaf-on and leaf-off conditions. Processing the LiDAR data was conducted with GreenValley International's LiDAR 360 software, and data derived from the point clouds were compared to physically measured field data. Overall, the tree detection algorithm was unsuccessful at accurately segmenting the point clouds. Complex vegetation environments on seismic lines, including small conifers with obscured stems or extremely dense and tall shrubs with overlapping canopies, posed a challenge for the software's capacity to differentiate trees As a result, tree densities and diameters were overestimated, while tree heights were underestimated. Exploration of alternative algorithms and software is needed if measuring vegetation data on seismic lines with MLS is to be implemented. [ABSTRACT FROM AUTHOR]

Stand tending using glyphosate to promote coniferous overstory trees has been a common practice in the boreal forests of Alberta. However, there are concerns about the impact of this practice on biodiversity of understory species. This study examined the impact of broadcast glyphosate application during the active reforestation phase, two to several years post-harvest, on forest plant diversity 25 to 40 years post-harvest. Herbicide treatments had the desired effect of shifting tree layer dominance from deciduous to coniferous species, driven by a 25-fold reduction in the density of trembling aspen (3927 vs. 154 stems·ha−1, untreated and treated, respectively). However, understory plant diversity was not significantly different between treated and untreated sites as examined by the Shannon–Wiener (H) and evenness (E) indices. Shared plant species (beta) across sites was high. Of the seven site-indicator species examined, three had significantly lower cover on treated sites: Wild sarsaparilla, low bush-cranberry and oak fern. Total understory plant cover was significantly greater in the treated portion (98.0%) versus untreated (71.4%); however, this difference was not significant when bryophytes were excluded in the analysis. The establishment, maintenance and monitoring of larger long-term trials is strongly recommended. [ABSTRACT FROM AUTHOR]

Alaska's boreal region stores large amounts of carbon both in its woodlands and in the grounds that sustain them. Any alteration to the fire system that has naturally regulated the region's ecology for centuries poses a concern regarding global climate change. Satellite-based remote sensors are key to analyzing those spatial and temporal patterns of fire occurrence. This paper compiles four burned area (BA) time series based on remote sensing imagery for the Alaska region between 1982–2015: Burned Areas Boundaries Dataset-Monitoring Trends in Burn Severity (BABD-MTBS) derived from Landsat sensors, Fire Climate Change Initiative (Fire_CCI) (2001–2015) and Moderate-Resolution Imaging Spectroradiometer (MODIS) Direct Broadcast Monthly Burned Area Product (MCD64A1) (2000–2015) with MODIS data, and Burned Area-Long-Term Data Record (BA-LTDR) using Advanced Very High Resolution Radiometer LTDR (AVHRR-LTDR) dataset. All products were analyzed and compared against one another, and their accuracy was assessed through reference data obtained by the Alaskan Fire Service (AFS). The BABD-MTBS product, with the highest spatial resolution (30 m), shows the best overall estimation of BA (81%), however, for the years before 2000 (pre-MODIS era), the BA sensed by this product was only 44.3%, against the 55.5% obtained by the BA-LTDR product with a lower spatial resolution (5 km). In contrast, for the MODIS era (after 2000), BABD-MTBS virtually matches the reference data (98.5%), while the other three time series showed similar results of around 60%. Based on the theoretical limits of their corresponding Pareto boundaries, the lower resolution BA products could be improved, although those based on MODIS data are currently limited by the algorithm's reliance on the active fire MODIS product, with a 1 km nominal spatial resolution. The large inter-annual variation found in the commission and omission errors in this study suggests that for a fair assessment of the accuracy of any BA product, all available reference data for space and time should be considered and should not be carried out by selective sampling. [ABSTRACT FROM AUTHOR]

The taiga forest, a semi-arid and nitrogen-limited ecosystem on permafrost, has changed under extreme wet events. This study aims to understand the changes that occurred in a larch forest in Eastern Siberia after the wet event of 2006–2007. In the summer of 2018, studies were conducted at the Spasskaya Pad Experimental Forest Station near Yakutsk, Russia, where a transect (60 m × 510 m) with 34 plots (30 m × 30 m) was set. It included intact sites and affected sites with different levels of forest damage, owing to the extreme wet event. We observed spatial variations in the normalized difference vegetation index (NDVI) calculated from Landsat satellite-observed data, and the foliar δ13C, δ15N, and C/N (carbon/nitrogen) ratio obtained from the needle samples of 105 mature larch trees. Our results reveal that the affected plots had a lower NDVI than the intact plots, resulting from a difference in tree stand density. In addition, the stand density is suggested to be a controlling factor in the spatial variations in the foliar C/N and δ13C values based on their significant relationships with the NDVI in June. We concluded that the larch trees from the regenerating forests in the affected areas have a higher nitrogen level and light availability (relatively low C/N and high δ13C) because of the slight competition for resources, owing to a low-stand density. This may lead to further succession of the larch forests after the extreme wet event. [ABSTRACT FROM AUTHOR]

Historical temperature records reveal that the boreal forest has been subjected to a significant lengthening of the thermal growing season since the middle of the last century, and climate models predict that this lengthening will continue in the future. Nevertheless, the potential phenological response of trees to changes in growing season length remains relatively undocumented, particularly for evergreen boreal tree species growing in cold environments. Here, we used the recently defined zero growth (ZG) concept to extract and characterize the metrics of seasonal radial growth dynamics for 12 balsam fir trees subjected to a 12-year soil warming experiment using high resolution radius dendrometer measurements. The ZG concept provides an accurate determination of growth seasonality (onset, cessation, duration, growth rates, and total growth) for these slow-growing trees characterized by significant shrinkage in tree diameter due to dehydration in the winter. Our analysis revealed that, on average, growth onset starts at day 152 ± 7 (±1 SE, 31 May–1 June) and ceases at day 244 ± 27 (31 August–1 September), for a growing season duration of about 3 months (93 ± 26 days) over a 12-year period. Growing season duration is mainly determined by growth cessation, while growth onset varies little between years. A large part (80%) of the total growth occurs in the first 50 days of the growing season. Given the dynamics of growth, early growth cessation (shorter growing season) results in a higher average seasonal growth rate, meaning that longer growing seasons are not necessarily associated with greater tree growth. Soil warming induces earlier growth cessation, but increases the mean tree growth rate by 18.1% and the total annual growth by 9.1%, on average, as compared to the control trees. Our results suggest that a higher soil temperature for warmed trees contributes to providing better growth conditions and higher growth rates in the early growing season, when the soil temperature is low and the soil water content is elevated because of snowmelt. Attaining a critical soil temperature earlier, coupled with lower soil water content, may have contributed to the earlier growth cessation and shorter growing season of warmed trees. [ABSTRACT FROM AUTHOR]

Fires play an important role in the modern dynamics of boreal ecosystems. The article presents the results of studying the effect of old fires on soils and soil organic matter (SOM) of native spruce forests that were last affected by fires in the previous 100 to 200 years. The studies were carried out in the European north-east of Russia (Komi Republic) and Central Siberia (Krasnoyarsk region). The objects of the study were typical Glossic Stagnic Retisol (Siltic, Cutanic). The time after the fire was determined by dendrochronological methods. Data on the content of water-soluble organic matter and densimetric fractions of soils were obtained; carbon and nitrogen stocks were calculated. The content of polycyclic aromatic hydrocarbons (PAHs) was established to characterize the effect of fires. Pyrogenic carbonaceous inclusions were morphologically diagnosed 200 years after the fire. In this regard, it is proposed to distinguish a "pyrogenic" subtype for soils with pronounced signs of pyrogenesis. Carbon stocks in soils of the Komi Republic varied from 5.7 to 15.7 kg C m−2, and soils of the Krasnoyarsk region had an accumulation of 6.9–12.5 kg C m−2. The contribution of the pyrogenic horizon Epyr to the total carbon and nitrogen stocks was 9–45%. It is suggested that pyrogenic carbon (PyC) can accumulate in light densimetric fractions (fPOM<1.6 and oPOM<1.6). The analysis of PAH content showed their high concentrations in the organic and upper mineral horizons of the studied soils (24 to 605 ng g−1). The coefficient FLA (fluoranthene)/(FLA+PYR(pyrene)) was the most useful to diagnose the pyrogenic origin of PAHs in the studied Retisols. [ABSTRACT FROM AUTHOR]

In order to determine the relationships between bird assemblages and forest habitat, we conducted surveys for bird assemblages in different forest habitats in the Khentii Mountain region, Northern Mongolia. A total of 1730 individuals belonging to 71 species from 23 families of 11 orders were recorded. Our findings revealed that passeriformes are the most species-rich order, accounting for 86.2% of the total species. The dominant species were Anthus hodgsoni, Parus major, Poecile palustris, and Sitta europaea in study area. Non-metric multidimensional scaling (NMDS) and permutation multivariate analysis of variance (PERMANOVA) showed that bird assemblages were affected by forest habitat types. Our findings also showed significant relationships between bird assemblages and canopy height and ground cover vegetation structure, whereas there were no relationships between altitude and other habitat variables. Thus, maintaining diverse forest habitats or restoring forest would play a key role in bird conservation and sustainable management of forest areas. [ABSTRACT FROM AUTHOR]

Surface mining for oil sand results in the formation of large pits that must be reclaimed. Some of these pits are backfilled with a myriad of substrates, including tailings rich in cations and anions, to form a solid surface. Experimental reclamation of the East in-pit located on the Syncrude Canada Ltd. mine lease was initiated in 2011 with Sandhill Wetland. Here, we report on monitoring (between 2015 and 2021) of Sandhill Wetland plant communities and significant environmental features, including base cations and water tables. Multivariate analyses demonstrated that the three dominant plant communities established in 2013 have continued to be dominated by the same species nine years after reclamation was initiated, but with reduced species richness. Plant communities have shifted across the wetland in response to water table changes and increases in sodium concentrations. The stoichiometry of base cations is unlike the natural wetlands of the region, and the surficial water chemistry of the wetland is unique. In response to variability in precipitation events coupled with wetland design, water tables have been highly variable, creating shifting water regimes across the wetland. Plant community responses to these shifting conditions, along with increases in base cation concentrations, especially sodium, provide background data for future in-pit reclamation designs. The plant responses underscore the need to develop reclamation designs for landscapes disturbed by mining that alleviate extreme water table fluctuation events and decrease cation concentrations to levels that approach natural wetlands. [ABSTRACT FROM AUTHOR]

A large long-term field trial was established in the Upper and Lower Foothills sub-regions of the Canadian boreal forest to monitor the effects of planting, vegetation management, and pre-commercial thinning on the development of lodgepole pine stands following harvesting. Data collected at the end of the trial's regeneration phase, 17 to 20 years after its establishment, were tested for treatment effects and projected to rotation age. Planting generally improved stocking and increased projected growth and yield of lodgepole pine. On modal sites, planted trees were often greatly outnumbered by natural regeneration; however, on others, typically with either poorer or richer soils, satisfactory restocking was not achieved without planting. Control of competing vegetation by herbicide application facilitated regeneration of pine where it was otherwise difficult or impossible on sites with excessive herbaceous or hardwood competition. Pre-commercial thinning accelerated the growth of individual trees and was projected to shorten rotations in dense stands. Responses to the treatments varied depending on environmental factors. Particular treatments may be effective to meet management objectives under some site conditions but unnecessary or counterproductive elsewhere. [ABSTRACT FROM AUTHOR]

Peatlands store carbon (C), nitrogen (N), and phosphorus (P), and the stoichiometric relationship among them may be modified by ecosystem disturbances, with major implications for boreal peatland ecosystem functions. To understand the potential impact of landscape fragmentation on peatland nutrient stoichiometry, we characterize the stoichiometric ratios of C, N and P in the soil–plant systems of disturbed boreal forest peatlands and also assessed relationships among site conditions, nutrient availability, stoichiometric ratios (C:N:P) and C storage in four sites that represent the forms of disturbed peatlands in the Athabasca oil sands region. Our results showed that nutrient stoichiometric balance differed across and within these peatlands, among plants, peat, and groundwater. Ratios of C:N and C:P in peat is a function of nutrient and moisture conditions, increasing from nutrient-rich (C:N = 28; C:P = 86) to nutrient-poor fens (C:N = 82; C:P = 1061), and were lower in moist hollows relative to drier hummock microforms. In groundwater, the drier nutrient-rich fen had higher N:P ratios relative to the nutrient-poor fen, reflecting interactions between dominant hydrologic conditions and stoichiometric relationships. The N:P ratio of plants was more similar to those of peat than groundwater pools, especially in the most recently disturbed nutrient-poor fen, where plant C:N:P ratios were greater compared to older disturbed sites in the region. These findings suggest that disturbances that modify moisture and nutrient regimes could potentially upset the C:N:P stoichiometric balance of boreal forest peatlands. It also provides valuable insights and essential baseline data to inform our understanding of how peatland C:N:P stoichiometry would respond to disturbance and restoration interventions in a boreal forest region at the tipping point of environmental change. [ABSTRACT FROM AUTHOR]

The land disturbed by open-pit oil sands mining must be restored to support the survival and growth of native boreal plants. Because tailings sand and sodic shale overburden are commonly used as an underlying parent substrate that is capped by boreal forest cover soils, the soil pH in reclamation sites is often higher compared with undisturbed boreal forest soil. Sulfur is a major byproduct of oil sands refining and could potentially be used as an amendment to lower the soil pH on reclamation sites. In this study, we examined the effects of soil pH and elemental sulfur on growth and physiological responses in Saskatoon berry and beaked hazelnut seedlings. We found that elemental sulfur was effective in lowering soil pH. However, addition of elemental sulfur to a forest soil of pH 5.7 lowered the soil pH to around 3, which impaired the growth and physiological performance of both plant species. The addition of 5 and 25 g kg−1 elemental sulfur to the pH 8.5 soil did not substantially improve the examined growth and physiological parameters in Saskatoon berry and beaked hazelnut seedlings. Further, excess addition of elemental sulfur in high pH soil could reduce the uptake of nitrogen, phosphorus, and calcium in Saskatoon berry. The results demonstrate that the amount of sulfur applied to the soil would need to be carefully determined for different soil types and pH levels to avoid potential toxicity effects. [ABSTRACT FROM AUTHOR]

Many nutrient-poor coarse-textured Kalmia L.–black spruce forest sites in eastern Canada turn to ericaceous heath dominated by Kalmia angustifolia L. after clearcutting and fire. While the mechanisms of post-fire forest and heath formation have been well documented, the origin of shrub savanna vegetation has received limited attention. This study demonstrates the significance of post-fire island regeneration of black spruce in Kalmia heath to the origin of shrub savannah alternate state. The study was conducted in Three Brooks, 10 km west of Grand Falls-Windsor, Newfoundland (48°51′ N; 55°37′ E). Black spruce forest in the site was clearcut, then a wildfire burned the area, and the site was subsequently planted with black spruce. Plant species cover, black spruce growth (stem density, stem height, basal diameter, and yearly volume increment), and foliar nutrients of planted spruce and soil properties (pH, humus and Ae horizon depth, and nutrients) in tree islands were compared with adjacent Kalmia heath. Black spruce islands had significantly lower cover of Kalmia and higher stem density of black spruce compared to Kalmia heath (7100 stems/ha in islands vs. 1920 stems/ha in heath). Height, basal diameter, and yearly volume increment of black spruce were more than three times higher in spruce islands than in Kalmia heath. Foliar nutrients of black spruce growing in Kalmia heath had significantly lower N and Mg (33 and 38%, respectively) but had significantly higher Mn and Zn (46 and 33%, respectively) than in black spruce islands. Black spruce growth inhibition in Kalmia heath is attributed to soil nutrient imbalance due to Kalmia evidenced by reduced concentrations of N and Mg and increased concentrations of Al, Fe, and other inorganic ions in the foliage. These results suggest that post-fire black spruce islands in severely burned patches provide "safe sites" for spruce regeneration, whereas Kalmia heath developing in non-severe burn area inhibits spruce regeneration and creates shrub savannah community as an alternate vegetation state. [ABSTRACT FROM AUTHOR]

While considerable research has focused on using either L-band or P-band SAR (Synthetic Aperture Radar) on their own for forest biomass retrieval, the use of the two bands simultaneously to improve forest biomass retrieval remains less explored. In this paper, we make use of L- and P-band airborne SAR and in situ data measured in the field together with laser scanning data acquired over one hemi-boreal (Remningstorp) and one boreal (Krycklan) forest study area in Sweden. We fit statistical models to different combinations of topographic-corrected SAR backscatter and forest heights estimated from PolInSAR for the biomass estimation, and evaluate retrieval performance in terms of R 2 and using 10-fold cross-validation. The study shows that specific combinations of radar observables from L- and P-band lead to biomass predictions that are more accurate in comparison with single-band retrievals. The correlations and accuracies between the combinations of SAR features and aboveground biomass are consistent across the two study areas, whereas the retrieval performance varied for individual bands. P-band-based retrievals were more accurate than L-band for the hemi-boreal Remningstorp site and less accurate than L-band for the boreal Krycklan site. The aboveground biomass levels as well as the ground topography differ between the two sites. The results suggest that P-band is more sensitive to higher biomass and L-band to lower biomass forests. The forest height from PolInSAR improved the results at L-band in the higher biomass substantially, whereas no improvement was observed at P-band in both study areas. These results are relevant in the context of combining information over boreal forests from future low-frequency SAR missions such as the European Space Agency (ESA) BIOMASS mission, which will operate at P-band, and future L-band missions planned by several space agencies. [ABSTRACT FROM AUTHOR]

The increasing frequency of fires inhibits the estimation of carbon reserves in boreal forest ecosystems because fires release significant amounts of carbon into the atmosphere through combustion. However, less is known regarding the effects of vegetation succession processes on ecosystem C-flux that follow fires. This paper describes intra- and inter-annual vegetation restoration trajectories via MODIS time-series and Landsat data. The temporal and spatial characteristics of the natural succession were analyzed from 2000 to 2016. Finally, we regressed post-fire MODIS EVI, LST and LSWI values onto GPP and NPP values to identify the main limiting factors during post-fire carbon exchange. The results show immediate variations after the fire event, with EVI and LSWI decreasing by 0.21 and 0.31, respectively, and the LST increasing to 6.89 °C. After this initial variation, subsequent fire-induced variations were significantly smaller; instead, seasonality began governing the change characteristics. The greatest differences in EVI, LST and LSWI were observed in August and September compared to those in other months (0.29, 6.9 and 0.35, respectively), including July, which was the second month after the fire. We estimated the mean EVI recovery periods under different fire intensities (approximately 10, 12 and 16 years): the LST recovery time is one year earlier than that of the EVI. GPP and NPP decreased after the fire by 22–45 g C·m−2·month−1 (30–80%) and 0.13–0.35 kg C·m−2·year−1 (20–60%), respectively. Excluding the winter period, when no photosynthesis occurred, the correlation between the EVI and GPP was the strongest, and the correlation coefficient varied with the burn intensity. When changes in EVI, LST and LSWI after the fire in the boreal forest were more significant, the severity of the fire determined the magnitude of the changes, and the seasonality aggravated these changes. On the other hand, the seasonality is another important factor that affects vegetation restoration and land-surface energy fluxes in boreal forests. The strong correlations between EVI and GPP/NPP reveal that the C-flux can be simply and directly estimated on a per-pixel basis from EVI data, which can be used to accurately estimate land-surface energy fluxes during vegetation restoration and reduce uncertainties in the estimation of forests' carbon reserves. [ABSTRACT FROM AUTHOR]

Solar-induced chlorophyll fluorescence (SIF) is a novel approach to gain information about plant activity from remote sensing observations. However, there are currently no continuous SIF data produced at high spatial resolutions. Many previous studies have discussed the relationship between SIF and gross primary production (GPP) and showed a significant correlation between them, but few researchers have focused on forests, which are one the most important terrestrial ecosystems. This study takes Greater Khingan Mountains, a typical boreal forest in China, as an example to explore the feasibility of using MODerate resolution Imaging Spectroradiometer (MODIS) products and Orbiting Carbon Observatory-2 (OCO-2) SIF data to simulate continuous SIF at higher spatial resolutions. The results show that there is no significant correlation between SIF and MODIS GPP at a spatial resolution of 1 km; however, significant correlations between SIF and the enhanced vegetation index (EVI) were found during growing seasons. Furthermore, the broadleaf forest has a higher SIF than coniferous forest because of the difference in leaf and canopy bio-chemical and structural characteristic. When using MODIS EVI to model SIF, linear regression models show average performance (R2 = 0.58, Root Mean Squared Error (RMSE) = 0.14 from Julian day 145 to 257) at a 16-day time scale. However, when using MODIS EVI and temperature, multiple regressions perform better (R2 = 0.71, RMSE = 0.13 from Julian day 145 to 241). An important contribution of this paper is the analysis of the relationships between SIF and vegetation indices at different spatial resolutions and the finding that the relationships became closer with a decrease in spatial resolution. From this research, we conclude that the SIF of the boreal forest investigated can mainly be explained by EVI and air temperature. [ABSTRACT FROM AUTHOR]

Research Highlights: We show the difference in the long-term effects on economic and ecological forest values between four forest management scenarios of a large representative forest landscape. The scenarios were largely formulated by stakeholders representing the main views on how to manage north-European forests. Background and Objectives: Views on how to balance forest management between wood production and biodiversity differ widely between different stakeholder groups. We aim to show the long-term consequences of stakeholder-defined management scenarios, in terms of ecological and economic forest values. Materials and Methods: We simulated management scenarios for a forest landscape in Sweden, based on the management objectives and strategies of key stakeholders. We specifically investigated the difference in economic forest values coupled to wood supply and ecological indicators coupled to structural biodiversity between the scenarios over a 100-year period. The indicators were net present value, harvest, growing stock and increment, along with deadwood volume, the density of large trees, area of old forests and mature broad leaf-rich forests. Results: We show that the scenarios have widely different outcomes in terms of the studied indicators, and that differences in indicator outcome were largely due to different distributions in management regimes, i.e., the proportion of forest left unmanaged or under even-aged management or continuous cover forest, as well as specific retention practices. Retention and continuous cover forestry mitigate the negative effects that clear-cut forestry has upon biodiversity. Conclusions: We found that an increase in the forest area under the continuous cover forestry regime could be a cost-efficient way to increase structural diversity in managed boreal forests. On the other hand, no single management regime performed best with respect to all indicators, which means that a mixture of several management regimes is needed to balance conflicting objectives. We also show that the trade-off between economic and ecological indicators was not directly proportional, meaning that an increase in structural biodiversity may be obtained at a proportionally low cost with appropriate management planning. [ABSTRACT FROM AUTHOR]

Managing competing vegetation is crucial in stand establishment strategies; forecasting the abundance, composition, and impact of competing vegetation after harvesting is needed to optimize silviculture scenarios and maintain long-term site productivity. Our main objective was to identify factors influencing the short-term abundance and composition of competing vegetation over a large area of the Canadian boreal forest. Our second objective was to better understand the mid-term evolution of the regeneration/competing vegetation complex in cases of marginal regeneration conditions. We used operational regeneration surveys of 4471 transects sampled ≈5 years after harvesting that contained data on regeneration, competing vegetation, elevation, ecological classification, soil attributes, and pre-harvest forest stands. We performed a redundancy analysis to identify the relationships between competing vegetation, harvesting and biophysical variables. We then estimated the probability of observing a given competing species cover based on these variables. In 2015, we re-sampled a portion of the sites, where conifer regeneration was marginal early after harvesting, to assess the temporal impact of different competing levels and species groups on the free-to-grow stocking, vigour and basal area of softwood regeneration. Results from the first inventory showed that, after careful logging around advance growth, ericaceous shrubs and hardwoods were not associated with the same sets of site attributes. Ericaceous shrubs were mainly found on low fertility sites associated with black spruce (Picea mariana (Mill.) BSP) or jack pine (Pinus banksiana Lamb.). The distinction between suitable environments for commercial shade-intolerant hardwoods and non-commercial hardwoods was less clear, as they responded similarly to many variables. Analysis of data from the second inventory showed a significant improvement in conifer free-to-grow stocking when commercial shade-intolerant hardwood competing levels were low (stocking 0%–40%) and when ericaceous shrubs competing levels were moderate (percent cover 26%–75%). In these conditions of marginal regeneration, the different types and intensities of competition did not affect the vigour or basal area of softwood regeneration, 9–14 years after harvesting. [ABSTRACT FROM AUTHOR]

Globally, intensive forestry has led to habitat degradation and fragmentation of the forest landscape. Taking Sweden as an example, this development is contradictory to international commitments, EU obligations, and to the fulfillment of the Parliament's environmental quality objective "Living Forests", which according to Naturvårdsverket (The Swedish Environmental Protection Agency) will not be achieved in 2020 as stipulated. One important reason for the implementation deficit is the fragmented forestry management. In a forest landscape, felling and other measures are conducted at different times on separate forest stands (often relatively small units) by different operators. Consequently, the authorities take case by case decisions on felling restrictions for conservation purposes. In contrast, conservation biology research indicates a need for a broad geographical and strategical approach in order to, in good time, select the most appropriate habitats for conservation and to provide for a functioning connectivity between different habitats. In line with the EU Commission, we argue that landscape forestry planning could be a useful instrument to achieve ecological functionality in a large area. Landscape planning may also contribute to the fulfilment of Sweden's climate and energy policy, by indicating forest areas with insignificant conservation values, where intensive forestry may be performed for biomass production etc. Forest owners should be involved in the planning and would, under certain circumstances, be entitled to compensation. As state resources for providing compensation are scarce, an alternative could be to introduce a tax-fund system within the forestry sector. Such a system may open for voluntary agreements between forest owners for the protection of habitats within a large area. [ABSTRACT FROM AUTHOR]

Gross primary productivity (GPP) is an important parameter that represents the productivity of vegetation and responses to various ecological environments. The Greater Khingan Mountain (GKM) is one of the most important state-owned forest bases, and boreal forests, including the largest primeval cold-temperature bright coniferous forest in China, are widely distributed in the GKM. This study aimed to reveal spatiotemporal vegetation variations in the GKM on the basis of GPP products that were generated by the Global LAnd Surface Satellite (GLASS) program from 1982 to 2015. First, we explored the spatiotemporal distribution of vegetation across the GKM. Then we analyzed the relationships between GPP variation and driving factors, including meteorological elements, growing season length (GSL), and Fraction of Photosynthetically Active Radiation (FPAR), to investigate the dominant factor for GPP dynamics. Results demonstrated that (1) the spatial distribution of accumulated GPP (AG) in spring, summer, autumn, and the growing season varied due to three main reasons: understory vegetation, altitude, and land cover; (2) interannual AG in summer, autumn, and the growing season significantly increased at the regional scale during the past 34 years under climate warming and drying; (3) interannual changes of accumulated GPP in the growing season (AGG) at the pixel scale displayed a rapid expansion in areas with a significant increasing trend (p < 0.05) during the period of 1982-2015 and this trend was caused by the natural forest protection project launched in 1998; and finally, (4) an analysis of driving factors showed that daily sunshine duration in summer was the most important factor for GPP in the GKM and this is different from previous studies, which reported that the GSL plays a crucial role in other areas. [ABSTRACT FROM AUTHOR]