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Black spruce is the most common tree species in Canada, dominating treed peatlands where they are usually stunted. We used 495 destructively sampled trees from 56 plots to develop allometric models of aboveground biomass by components (stem, branches, and needles) for small (<5 m tall) black spruce from peatlands in the Taiga Plains and Boreal Plains Ecozones of Western Canada, for which there were no specific models available of biomass by components. We used leave-one-plot-out cross-validation to assess transferability and compare our models with existing national and ecozone-specific equations. Our models predicted total tree biomass with better accuracy and less biased estimates than the national model (relative RMSE: 30% versus 35% national; relative bias: +1% versus –12% national). Similar results were obtained in other external datasets. Existing ecozone equations performed worse than either our models or the national ones. When we applied the models at the plot level to predict aboveground biomass density (Mg·ha−1), our models outperformed the national model again (relative RMSE: 15.9% versus 18.6% national, relative bias: +3.5% versus –13.6% national). These results indicate that at least for peatlands of Western Canada, our models provide better aboveground biomass estimates for small black spruce trees than existing models. [ABSTRACT FROM AUTHOR]

The recent expansion of mountain pine beetle (MPB, Dendroctonus ponderosae) from its native range in western North America into northern boreal pine forests in Alberta, Canada has resulted in conditions for tree regeneration that are dramatically different from those after wildfire, the predominant natural disturbance in these forests. We assessed natural regeneration post-MPB for northern boreal lodgepole pine sites in Alberta, Canada via intensive surveys of small plots at 33 severely attacked pine stands and using data from 205 permanent sample plots representing various site types and levels of MPB mortality. We used model selection to identify factors explaining regeneration. Overall, pine regeneration was very poor 6–9 years post-MPB; only 42% of the 33 intensively surveyed plots and only 9% of the 205 permanent plots had pine seedlings. This poor regeneration is attributed to high levels of cone serotiny in these populations, unsuitable regeneration microsites due to undisturbed litter or feathermoss layers, and competition from the residual canopy and understory vegetation. Other species (aspen, birch, poplar, and black and white spruce) were found on most sites, either as post-attack regeneration or regeneration established in advance. Without intervention, many of these stands will likely transition away from pine, to broadleaf and other conifer species. [ABSTRACT FROM AUTHOR]

Woodland caribou (Rangifer tarandus caribou (Gmelin, 1788)) use older forests that provide abundant terrestrial lichen forage and refuge from predators. However, forest structural characteristics vary widely, differing in forage availability but also, perhaps, in the ability of caribou to move freely to access forage or to escape predation. We conducted a multivariate analysis of habitat in two geographically and biophysically distinct regions to identify the independent effects of various attributes, including forest understorey stand density, defined as standing and downed biomass, on caribou habitat selection. We developed Bayesian network models to predict the probability of habitat selection based on a set of remotely sensed habitat inputs. Caribou in the Bistcho range (northwestern Alberta) selected non-forest/sparsely forested areas, while caribou in the Trout Lake region (northwestern Ontario) selected primarily forested habitats, nevertheless consistent with selection for reduced predation risk in both cases. Caribou also selected forest stands with lower understorey stand density in both regions, consistent with selection for stands that would allow greater ease of movement. The high-resolution satellite data resolved habitat characteristics more consistently and in greater detail than standard forest cover datasets that are most often used for these analyses, and led us to conclude that habitat management may require different treatments in different parts of the species' range to address what are nevertheless common pathways to decline. [ABSTRACT FROM AUTHOR]

Boreal forests are one of the most important biomes storing carbon (C). Wildfires burn yearly on average more than 1% of the boreal forest, and it is expected that the fire return intervals will shorten due to climate change. Fire is one of the most influential factors affecting soil organic matter quantity and quality, soil C pools, and presumably also the time C resides in the soil (soil C turnover time in years). We compared the potential effects of forest fire through post-fire succession on soil carbon dioxide (CO2) emission rates and soil C turnover time in two fire chronosequences, one with underlying permafrost soil and the other without permafrost. We found that fire had a significant effect on potential soil C turnover times, but surprisingly there was no significant difference in soil C turnover times between the permafrost and non-permafrost areas, although the soil CO2 emissions rates in permafrost areas are approximately three times higher compared to non-permafrost areas. In recently burned areas the potential soil C turnover times were two times longer compared to control areas located in forests burned more than 100 years ago. The longest potential soil C turnover times were recorded in mineral soil layers (30 cm) of permafrost soils, and the shortest potential soil C turnover times were recorded in humus layers of non-permafrost areas. [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]

Soil shear strength (SSS) is an important soil attribute that is influenced by vegetation. If aboveground biomass estimates can be used to predict soil shear strength, it would greatly enhance our ability to estimate SSS across large areas. Using data collected from 24 plots in Alaska, we analyzed the relationship between soil shear strength and ground-collected vegetation attributes and remotely sensed (RS) variables. We constructed both univariate and multivariate models to assess the predictive capabilities of the vegetation and RS variables. Total trees and total conifers were significant predictors of SSS, with a negative relationship existing between total trees/total conifers and SSS. Graminoid cover (%) was positively correlated with soil shear strength and was also a significant predictor of SSS. Of the RS variables, the bands B1 (0.443 µm), B2 (0.490 µm), and B3 (0.560 µm) from the Sentinel 2 satellite system were all significant predictors of SSS. A multivariate model improved model fit over the simple univariate models, with an R² = 0.46. We have both demonstrated a connection between SSS and aboveground vegetation attributes for areas within interior Alaska and that it is possible to link SSS to RS variables using a multivariate model. [ABSTRACT FROM AUTHOR]

Carbon release from thawing permafrost soils could significantly exacerbate global warming as the active-layer deepens, exposing more carbon to decay. Plant community and soil properties provide a major control on this by influencing the maximum depth of thaw each summer (active-layer thickness; ALT), but a quantitative understanding of the relative importance of plant and soil characteristics, and their interactions in determine ALTs, is currently lacking. To address this, we undertook an extensive survey of multiple vegetation and edaphic characteristics and ALTs across multiple plots in four field sites within boreal forest in the discontinuous permafrost zone ( NWT, Canada). Our sites included mature black spruce, burned black spruce and paper birch, allowing us to determine vegetation and edaphic drivers that emerge as the most important and broadly applicable across these key vegetation and disturbance gradients, as well as providing insight into site-specific differences. Across sites, the most important vegetation characteristics limiting thaw (shallower ALTs) were tree leaf area index ( LAI), moss layer thickness and understory LAI in that order. Thicker soil organic layers also reduced ALTs, though were less influential than moss thickness. Surface moisture (0-6 cm) promoted increased ALTs, whereas deeper soil moisture (11-16 cm) acted to modify the impact of the vegetation, in particular increasing the importance of understory or tree canopy shading in reducing thaw. These direct and indirect effects of moisture indicate that future changes in precipitation and evapotranspiration may have large influences on ALTs. Our work also suggests that forest fires cause greater ALTs by simultaneously decreasing multiple ecosystem characteristics which otherwise protect permafrost. Given that vegetation and edaphic characteristics have such clear and large influences on ALTs, our data provide a key benchmark against which to evaluate process models used to predict future impacts of climate warming on permafrost degradation and subsequent feedback to climate. [ABSTRACT FROM AUTHOR]

Climate drives ecosystem processes and impacts biodiversity. Biodiversity patterns over large areas, such as Canada's boreal, can be monitored using indirect indicators derived from remotely sensed imagery. In this paper, we characterized the historical space–time relationships between climate and a suite of indirect indicators of biodiversity, known as the Dynamic Habitat Index (DHI) to identify where climate variability is co-occurring with changes in biodiversity indicators. We represented biodiversity using three indirect indicators generated from 1987 to 2007 National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer images. By quantifying and clustering temporal variability in climate data, we defined eight homogeneous climate variability zones, where we then analyzed the DHI. Results identified unique areas of change in climate, such as the Hudson Plains, that explain significant variations in DHI. Past variability in temperatures and growing season index had a strong influence on observed vegetation productivity and seasonality changes throughout Canada's boreal. Variation in precipitation, for most of the area, was not associated with DHI changes. The methodology presented here enables assessment of spatial–temporal relationships between biodiversity and climate variability and characterizes distinctive zones of variation that may be used for prioritization and planning to ensure long-term biodiversity conservation in Canada. [ABSTRACT FROM PUBLISHER]

Wood harvesting in boreal forests typically consists of sequential harvesting operations within a rotation: a few thinnings and a final felling. The aim of this paper is to model differentiated relative global warming potential ( GWP) coefficients for stemwood use from different thinnings and final fellings, and correction factors for long-lived wood products, potentially applicable in life cycle assessment studies. All thinnings and final fellings influence the development of forest carbon stocks. The climate impact of a single harvesting operation is generated in comparison with no harvesting, thus encountering a methodological problem on how to handle the subsequent operations. The dynamic forest stand simulator MOTTI was applied in the modelling of evolution of forest carbon stocks at landscape level in Southern Finland. The landscape-level approach for climate impact assessment gave results similar to some stand-level approaches presented in previous literature that included the same forest C pools and also studied the impacts relative to the no-harvest situation. The climate impacts of stemwood use decreased over time. For energy use, the impacts were higher or similar in the short term and 0-50% lower in the midterm in comparison with an identical amount of fossil CO2. The impacts were to some extent (approximately 20-40%) lower for wood from intermediate thinnings than for wood from final fellings or first thinnings. However, the study reveals that product lifetime has higher relative influence on the climate impacts of wood-based value chains than whether the stemwood originates from thinnings or final fellings. Although the evolution of future C stocks in unmanaged boreal forests is uncertain, a sensitivity analysis suggests that landscape-level model results for climate impacts would not be sensitive to the assumptions made on the future evolution of C stocks in unmanaged forest. Energy use of boreal stemwood seems to be far from climate neutral. [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]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Wildfire is the main natural disturbance in forest ecosystems; it controls and modifies vegetation compositions, landscape properties and global carbon cycle. Estimates of areas burned by wildfires vary greatly depending on the environmental conditions, data availability and methods used. This paper aims to develop a framework for reconstructing time series of burned areas in the taiga-steppe transition zone using MODIS composites. The estimated accuracy of the developed mapping algorithm and other statistical indications denote that the clear land surface composites of MODIS data in spring (Julian dates, JD 97-177), logistic regression and MODIS active fire product can be integrated successfully for reconstructing burned areas in the taiga-steppe transition zone. Time series of burned areas between 2000 and 2012 derived from the MODIS spring composite algorithm were validated using Landsat-based burned areas, showing average omission and commission errors of 18% and 31%. Compared with the MCD45A1 burned area product, the developed algorithm significantly improved the prediction of burned areas and successfully separated late-season from early-season burns. The derived long-term burned areas will assist in understanding the complex relationships among forest dynamics, forest recovery and fire in the vulnerable boreal forest ecosystem as well as its transition zone under climate change in northern Mongolia and Central Asia. [ABSTRACT FROM AUTHOR]

Northern forested ecosystems are predicted to change dramatically in response to climate change during the next century. The purpose of this paper was to use logistic regression analysis to model the effects of climate and topography on the spatial distribution of the northern forest around Churchill, Manitoba, Canada. Climate maps were modeled using kriging interpolation of actual climate data collected from 34 long-term monitoring sites distributed throughout the study area, and topographic information was derived from commercially available digital elevation models. Five of the 18 independent variables contributed appreciably (p < 0.15) to the final logistic regression model: distance from the Hudson Bay coast, summer soil temperature, snow density, slope, and snow water equivalent. Current forest distribution was predicted with 66% accuracy using the final model, and Kappa statistics indicated significant agreement between modeled and actual forest extents. Significant explanatory variables demonstrate important synergistic effects of Hudson Bay, wind, and snow in determining forest distribution. Modeled forest extents were further south than actual forest limits, which suggest that the treeline is not likely in equilibrium with the present climate. [ABSTRACT FROM AUTHOR]

The influence of substrate lithology on the distribution of many vascular and nonvascular plants has long been recognized, especially in alpine, subalpine, and other rocky habitats. In particular, plants have been classified as dependent on high-calcium substrates (i.e., calcicoles) based on common restriction to habitats developed in calcareous rocks, such as limestone and marble. In a classic 1907 paper on the influence of substrate on plants, M. L. Fernald singled out a particular meadow on Mont de la Table in the Chic-Choc Mountains of Québec for its unusual co-occurrence of strict calcicole and calcifuge (i.e., acidophile) plant taxa. We re-located this site, investigated substrate factors responsible for its unusual plant diversity, and documented current plant distributions. No calcareous rocks were found on site. However, inclusions of calcareous rocks were found farther up the mountain. The highest pH and dissolved calcium concentrations in surface waters were found in a series of springs that deliver groundwater, presumably influenced by calcareous rocks up the slope. Within the habitat delineated by common occurrences of calcicole species, available soil calcium varied by a factor of five and soil pH varied by almost 1.5 units, depending on microtopography and relative connection with groundwater. Variation in hydrologic delivery of weathering products leads to large variation in chemical composition of soils and waters within calcareous-influenced habitats. Here, the fine-scale variability of habitat, rather than plasticity in the plants' tolerances, appeared to be responsible for co-occurrence of taxa considered to be strict calcicoles or calcifuges. The flora in 2005-2008 was very similar to what it was in 1906, although in-filling of woody vegetation and strong chemical gradients driven by climatically controlled hydrologic processes suggest the possibility of future vegetation changes with continued climate change. [ABSTRACT FROM AUTHOR]

Copyright of Environmental Reviews is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Key message: A rain exclusion repeated for 3 years resulted in larger summer stem contractions in three of the sites in the third year of the experiment and in larger winter contractions in the northern sites. However, there was no pronounced stress reaction in the stem radius variations of mature black spruce since total stem expansion was not reduced. Abstract: Future climate warming is expected to produce more severe and frequent periods of drought with consequent water stresses for boreal species. In this paper, we present a high-resolution analysis of stem radius variations in black spruce under rain exclusion. All summer long rain exclusions were applied for three consecutive summers to mature trees on four sites along a latitudinal gradient. The stem radius variations of control and treated trees were monitored year-round at an hourly resolution with automatic point dendrometers. The seasonal patterns of shrinking and swelling were analyzed using a sequential analysis technique and the daily patterns of contraction and expansion were extracted. Overall, the treated trees followed their diurnal cycles of contraction and expansion during the rain exclusions and no significant cumulative difference in stem expansion between control and treated trees was observed over the 3 years. In the third year trees subjected to rain exclusion showed larger stem contractions in summer on three out of four sites and larger winter contractions were observed on the northern sites. This study shows that repeated summer rain exclusion does not necessarily lead to a direct evident stress reaction, showing the resilience of the boreal forest. [ABSTRACT FROM AUTHOR]

Alberta's forests are becoming increasingly disturbed and fragmented by the cumulative effects of anthropogenic disturbances exacerbated by the enduring footprint of seismic lines on the landscape. Forest harvesting and subsequent reforestation activities (e.g., site preparation and tree planting) may facilitate tree growth on seismic lines when forestry companies incorporate them into management areas. In this study, forest regeneration was assessed along transects on and off seismic lines within four cutblocks in northwestern Alberta. Tree, sapling, and shrub characteristics were measured, and tree cookies from a subset of trees on and off seismic lines were used to model height growth. No difference in total tree, sapling, or shrub counts on and off seismic lines was found although trees on seismic lines were growing at slightly slower rates compared to the adjacent cutblock, and Alnus viridis was more abundant on seismic lines. Our results suggest that, despite some species-level differences and modest differences in tree growth rates, trees on seismic lines within cutblocks are regenerating similarly to other trees growing in the post-harvest stand. These findings indicate that forest harvesting, and subsequent reforestation, could represent an important tool in conducting landscape-level restoration in mixedwood forests where seismic lines have not naturally recovered. [ABSTRACT FROM AUTHOR]

Seismic lines are linear features created by the oil and gas industry for energy exploration. Though individually narrow, collectively seismic lines are a pervasive management challenge, resulting in changes to biogeochemical cycles, plant and animal abundance and behaviour, predator–prey relationships, and forest successional trajectories. These impacts arise from historical construction methods that used bulldozers to remove vegetation and substrate leaving lines as persistent openings in a state of arrested succession. In the mid-1990s, "low-impact seismic" (LIS) line construction began, using mulchers to remove vegetation aboveground to minimize impacts and hasten reforestation. Here, we evaluated the effectiveness of LIS in retention, recruitment, and growth of seedlings in forested peatlands in northeast British Columbia. Retained and recruited trees on LIS lines were found at 69% and 64% of sites, had mean densities of 3400 and 6000 stems/ha, and mean heights of 42 and 11 cm, respectively. These LIS lines appeared to recover along expected trajectories toward tree cover, thereby mitigating challenges typical of older seismic exploration. Our results suggest it is feasible to further fast-forward line recovery by ensuring mulcher drums are kept as high as possible to increase the number and height of trees through the mulching process. [ABSTRACT FROM AUTHOR]

Context: In interior Alaska, increasing wildfire activity associated with climate change is projected to continue, potentially altering regional forest composition. Conifers are emblematic of boreal forest; however, greater frequency and severity of wildfires has been found to favor broadleaf-deciduous species in numerous studies. Objectives: This study examines potential shifts in forest type in interior Alaska and how shifts may be impacted by recurring wildfires under future climate change. Methods: A spatially-explicit forest landscape model, LANDIS-II, was used to simulate forest succession and wildfire over a 380,400-hectare landscape under historic and future (RCP 8.5) climate. Wildfire was modeled using the SCRPPLE fire extension and vegetation growth, belowground carbon, hydrologic, and permafrost dynamics were modeled with the DGS succession extension. The relative importance of drivers of forest type change away from black spruce was quantified using random forest models for areas on the landscape experiencing different numbers of wildfires. Results: Greater frequencies of fire activity were associated with shifts in conifer-dominant areas to broadleaf-deciduous, which climate change accelerated. Vegetation transitions were most strongly influenced by percent tree mortality from the most recent wildfire. Starting deciduous fraction and proximity of mature black spruce to a site pre-fire were also influential, indicating pre-fire composition and context modified the effect of vegetation shifts. Conclusions: These results underscore how shifts in forest type may occur in a nonlinear manner in this region as the landscape experiences pressure from climate change and forests are subject to complex interactions between wildfire, climate, belowground processes, and the arrangement of forest communities. [ABSTRACT FROM AUTHOR]

Copyright of Environmental Reviews is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Climate is an important driver of dissolved organic carbon (DOC) dynamics in boreal catchments characterized by networks of streams within forest-wetland landscape mosaics. In this paper, we assess how climate change may affect stream DOC concentrations ([DOC]) and export from boreal forest streams with a multi-model ensemble approach. First, we apply an ensemble of regional climate models (RCMs) to project soil temperatures and stream-flows. These data are then used to drive two biogeochemical models of surface water DOC: (1) The Integrated Catchment model for Carbon (INCA-C), a detailed process-based model of DOC operating at the catchment scale, and (2) The Riparian Integration Model (RIM), a simple dynamic hillslope scale model of stream [DOC]. All RCMs project a consistent increase in temperature and precipitation as well as a shift in spring runoff peaks from May to April. However, they present a considerable range of possible future runoff conditions with an ensemble median increase of 31 % between current and future (2061-2090) conditions. Both biogeochemical models perform well in describing the dynamics of present-day stream [DOC] and fluxes, but disagree in their future projections. Here, we assess possible futures in three boreal catchments representative of forest, mire and mixed landscape elements. INCA-C projects a wider range of stream [DOC] due to its temperature sensitivity, whereas RIM gives consistently larger inter-annual variation and a wider range of exports due to its sensitivity to hydrological variations. The uncertainties associated with modeling complex processes that control future DOC dynamics in boreal and temperate catchments are still the main limitation to our understanding of DOC mechanisms under changing climate conditions. Novel, currently overlooked or unknown drivers may appear that will present new challenges to modelling DOC in the future. [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]

The boreal zone and its ecosystems provide numerous provisioning, regulating, cultural, and supporting services. Because of its resources and its hydroelectric potential, Canada's boreal zone is important to the country's resource-based economy. The region presently occupied by Canada's boreal zone has experienced dramatic changes during the past 3 million years as the climate cooled and repeated glaciations affected both the biota and the landscape. For about the past 7000 years, climate, fire, insects, diseases, and their interactions have been the most important natural drivers of boreal ecosystem dynamics, including rejuvenation, biogeochemical cycling, maintenance of productivity, and landscape variability. Layered upon natural drivers are changes increasingly caused by people and development and those related to human-caused climate change. Effects of these agents vary spatially and temporally, and, as global population increases, the demands and impacts on ecosystems will likely increase. Understanding how humans directly affect terrestrial and aquatic ecosystems in Canada's boreal zone and how these effects and actions interact with natural disturbance agents is a prerequisite for informed and adaptive decisions about management of natural resources, while maintaining the economy and environment upon which humans depend. This paper reports on the genesis and present condition of the boreal zone and its ecosystems and sets the context for a detailed scientific investigation in subsequent papers published in this journal on several key aspects: carbon in boreal forests; climate change consequences, adaptation, and mitigation; nutrient and elemental cycling; protected areas; status, impacts, and risks of non-native species; factors affecting sustainable timber harvest levels; terrestrial and aquatic biodiversity; and water and wetland resources. [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]

Abstract: This paper provides an account of ‘vital ecosystem security’. The central claim is that ‘vital ecosystem security’ and the processual ontology of ‘complex adaptive becoming’ provide useful terms with which to think environmental citizenship biopolitically within the contingent matrix of climate change. The paper identifies how complex adaptation, the operative form of vital ecosystem security, defines an emerging form of environmental citizenship, which can be found operating at the interface of a new type of forestry and the global carbon cycle. The specific case developed here concerns the boreal forest of northern Canada. [Copyright &y& Elsevier]

The taxonomic knowledge gap and lack of knowledge on species-level diversity has been a global concern within conservation biology through the recent two decades. As a national response, Finland has funded a Research Program of Poorly Known and Threatened Forest Species from the year 2003. The program is an essential part of the knowledge base applied in Finnish forest policy. The present paper evaluates the outcomes of the program, covering scientific publication, training, taxonomic coverage, increased knowledge on boreal forest biodiversity and awareness rising. The ongoing program has been funded by 6.5 million Euros to date including 59 projects. The program has produced 19 master's theses and six doctoral theses. Due to their expertise the graduated biologists have been employed in environmental administration or become researchers. The program has produced 163 refereed scientific articles, 104 of which are recognized by the Web of Science; with an average impact factor of 1.81. The results of the program include 15 genera and 348 species new to science, and 60 genera and 1,664 species to Finland's list of known species. Due to new knowledge gathered in the program 3,000-4,000 species could be included in the most recent National Red List assessment. The publishing of identification books on local language has proved as the most effective way of advancing general species knowledge among the public and end-users. The high number of new species to science from a biodiversity-poor boreal country describes the scale of the huge work still be done in describing the global species-level diversity. The program has achieved its goals in many ways, but the program leaves out a large part of the species that do not occur in forest biotopes. Moreover, the funding has decreased through the years despite the international goal of halting the world's biodiversity loss has not been met. [ABSTRACT FROM AUTHOR]

This paper presents a modified robust stem volume retrieval approach suitable for use with L-band SAR imagery. Multitemporal dual-polarization SAR imagery acquired by ALOS PALSAR during the summer-autumn 2007 is used in the study, along with stand-wise forest inventory data from two boreal forest sites situated in central Finland. The average sizes of forest stands at the study sites were 3 ha and 4.8 ha. The method used employs model fitting with an inverted semi-empirical boreal forest model, and takes advantage of the multitemporal aspect in order to improve the stability and accuracy of stem volume estimation. Multitemporal combination of model output in a multivariate regression framework allows volume estimates to be obtained with an RMSE about 43% of the mean of 110 m^3/ha, and a coefficient of determination R^2 of 0.71 in the best case. The methodology used can be employed to produce large-area stem volume maps from dual-polarization ALOS PALSAR imagery mosaics. [ABSTRACT FROM PUBLISHER]

Isle Royale National Park (IRNP) is an archipelago in west central Lake Superior. In 2010, the National Park Service Great Lakes Inventory and Monitoring Network initiated a long-term monitoring program at IRNP with the goals being to: ( 1 ) determine the current forest structure, (2) assess how succession and climate change will impact species assemblages, and (3) develop realistic management targets related to climate change impacts on IRNP forests. Five forest types were identified, with three of these (sugar maple {Acer saccharum Marsh.)/birch, eastern white cedar {Thuja occidentalis L), and balsam fir {Abies balsamea (L.) Mill.)) being climax types with little likelihood of succeeding into any other type over the next two to three decades. Two forest types (white spruce {Picea glauca (Moench) Voss),/trembling aspen {Populus tremuloides Michx.), and paper birch {Betula papyrifera Marsh.)) were in a state of transition. The long-term (> 50 year) successional pathways of all five forest types will be influenced by climate change, species' migration abilities, and disease. Many dominant species currently on the island, including balsam fir, black spruce {Picea mariana (Mill.) Britton, Sterns & Poggenb.), and white spruce, are expected to become extirpated, while the abundance of other common species, including paper birch and trembling aspen, is expected to decline. The 21 km distance between the mainland and the islands will prohibit timely immigration of new species onto the island in the face of climate change. Immigration will likely be led by avian-dispersed species {Prunus spp., exotic Lonicera spp., and Rhamnus cathartica, another exotic species) with dispersal of other taxa relying on stochastic events or human transport. Managers should consider assisted migration to ensure that species assemblages remain congruent; otherwise, stable ecosystems dominated by a few non-native taxa may result. This is especially relevant on the eastern side of the island where balsam fir forests dominate in shallow, bedrock-derived soils. [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.

Longer wavelength synthetic aperture radars (SARs) are precious in the remote sensing of forested areas, being sensitive to contributions from the whole vegetation layer and from the ground below. The electromagnetic properties of such contributions are retrieved from multipolarimetric acquisitions, whereas their vertical structure is retrieved from multibaseline acquisitions through tomographic imaging. Combining baseline and polarization diversity provides most information, allowing the decomposition of the SAR signal into ground- and volume-only contributions. A formal treatment of this problem is provided with the algebraic synthesis technique, which extends the concepts of PolInSAR. The decomposition, however, is shown to be ambiguous in that different solutions are equally consistent with the data. The main goal of this paper is to discuss this topic in light of the experimental results from a tomographic and polarimetric analysis of the boreal forest within the Krycklan River catchment, Northern Sweden, investigated at P- and L-bands during the ESA campaign BioSAR 2008. Different solutions to the decomposition problem will be discussed by examining the corresponding vertical structures accessible through tomographic techniques. Elements are shown supporting the idea that ground-volume interactions play a nonnegligible role at P-band, and a solution is proposed to isolate contributions from direct volume backscattering. The retrieval of forest top height is discussed as well, leading to the conclusion that such parameter is robust against erroneous choices in the identification of volume-only contributions, thus corroborating the PolInSAR approach for the analysis of single-baseline data. [ABSTRACT FROM AUTHOR]

Natural and anthropogenic disturbances on natural landscapes reduce the abundance and alter the spatial arrangement of certain habitat types. Measuring and modeling such alterations, and their biological effects, remains challenging in part because many widely used configuration metrics are correlated with habitat amount. In this paper, we consider the sources of such correlation, and distinguish process or sample-based correlation from functional correlation that may be an artifact of the metrics themselves. Process correlation is not necessarily a serious problem for statistical inference, but functional correlation would be. We propose that functional correlation may be reduced by normalizing metrics by habitat abundance. We illustrate with normalized versions of total core area, mean nearest neighbor distance, and mean shape index, and show informally that the standard versions of these metrics should exhibit functional correlation. We evaluate the normalized metrics on samples of harvested and undisturbed forested landscapes, and on simulated landscapes generated with varying degrees of spatial autocorrelation. Normalization markedly reduced correlations with habitat abundance on natural landscapes, but not on simulated landscapes. The reasons for this appear to be a combination of differing variances in metric values within levels of habitat abundance, and of the precise form of the relationships between habitat abundance and the un-normalized metrics. In all cases, the normalization changes the ordering of landscapes by metric values across levels of habitat abundance. In consequence, normalized and standard metrics cannot both be accurate measures of configuration. We conclude that statistical modeling of ecological response data is needed to finally determine the merits of the normalizations. [ABSTRACT FROM AUTHOR]

Abstract: ERS-1/2 tandem coherence was reported to have high potential for the mapping of boreal forest stem volume (e.g. Santoro et al., 2002, 2007a; Wagner et al., 2003; Askne & Santoro, 2005). Large-scale application of the data for forest stem volume mapping, however, is hindered by the variability of coherence with meteorological and environmental acquisition conditions. The traditional way of stem volume retrieval is based on the training of models, relating coherence to stem volume, with the aid of forest inventory data which is generally available for a few small test sites but not for large areas. In this paper a new approach is presented that allows model training using the MODIS Vegetation Continuous Fields canopy cover product (Hansen et al., 2003) without further need for ground data. A comparison of the new approach with the traditional regression-based and ground-data dependent model training is presented in this paper for a multi-seasonal ERS-1/2 tandem dataset covering several well known Central Siberian forest sites. As a test scenario for large-area application, the approach was applied to a multi-seasonal ERS-1/2 tandem dataset of 223 ERS-1 and ERS-2 image pairs covering Northeast China (~1.5millionkm2) to map four stem volume classes (0–20, 20–50, 50–80, and >80m3/ha). [ABSTRACT FROM AUTHOR]