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Copyright of Botany 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.)

Forest plantations play an increasingly important role in meeting global demand for wood. They usually have higher yield than naturally regenerated forests. Thus, plantations can support economically viable wood production, enable forest conservation elsewere, help mitigate climate change by contributing to carbon sequestration and increase forest resilience and resistance to biotic and abiotic stressors. If yield of plantations is not as high as anticipated, then their use could generate important sustainability issues. There are still major gaps in our understanding of the factors that influence yield, even with respect to black spruce, white spruce, and jack pine, three of the most commonly planted tree species in northeastern North America. Our objective was to evaluate the yield of forest plantations of these species over a 416 000 km2 region that was representative of northeastern North American forests. Contrary to our prediction, realized yield of operational plantations was consistently lower than anticipated. Site index and competition both played a significant role in determining the yield of plantations. In the context of uncertain realized yield of operational plantations, we emphasize the necessity of relying on adaptive management to determine harvest levels that are compatible with sustainable management objectives. [ABSTRACT FROM AUTHOR]

The monitoring of forest ecosystems is significantly affected by the lack of consistent historical data of low-severity (forest partially disturbed) or gradual disturbance (e.g. eastern spruce budworm epidemic). The goal of this paper is to explore the use of a subset of Landsat time series and deep learning models to identify both the type and the year of disturbances, including low-severity and gradual disturbances, in the boreal forest of eastern Canada at the pixel level. Remote sensing data such as the spectral information from Landsat time series are the best available option for large scale observations of disturbances that go back decades. Traditional modeling approaches, like LandTrendr, require substantial handcrafted pre-processing to remove noise and to extract temporal features from the image sequences before using them as input to a classical machine-learning model. Deep-learning models can autonomously discern which features are relevant within the coarse temporal and spectral information from the Landsat annual dense time series. We evaluated the performance of TempCNN and Transformer model in detecting and classifying the type and the year of the forest disturbance using Landsat time series subsequences. Our findings resulted in the generation of four disturbance maps outlining the forest history from 1986 to 2021 within the eastern Canadian boreal forest. Our experimental outcomes demonstrate several significant benefits of employing deep learning models. Firstly, using noisy Landsat time series they achieve comparable accuracy for classifying fire and total harvesting than existing publicly available disturbance maps. Secondly, the use of shorter time series subsequence with deep learning models enables to map adequately different overlapping disturbances occurring in the complete time series. Finally, they increase the number of distinguishable disturbance classes by adding partial harvesting, gradual disturbances, and forest recovery from older events, making them useful approaches for obtaining the first remote sensing-based map for areas affected by the eastern spruce budworm. • TempCNN, Transformer tested on Landsat time series for disturbance classification. • The type and the year of disturbance events were classified with good accuracy. • Deep learning effective for identifying partial and progressive disturbances. • Landsat subsequences extract overlapping disturbances. [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]

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]

Linear features are pervasive across the boreal forest of Canada, negatively impacting several wildlife species. Understanding how wildlife responds to different types and characteristics of linear features is necessary for coordinated landscape restoration. Currently, linear feature restoration is focused on recovering threatened woodland caribou (Rangifer tarandus) which may have unintended impacts on other boreal species like moose (Alces alces). Understanding how moose respond to different linear features can help ensure restoration is targeted and effective. We used GPS data from seven moose collected between 2008 and 2010 to investigate response to linear features and to determine how moose response was influenced by characteristics of linear features like the surrounding habitat and regeneration. At the landscape scale, moose selected areas closer to seismic lines when they were in areas with lower densities of seismic lines and higher densities of harvest blocks and wildfires. This response was stronger during winter. Moose selected areas closer to pipelines when they were in areas with lower densities of other linear features, harvest blocks, and wildfires and were indifferent to roads at the population‐level. At the fine scale, during winter, moose selected areas closer to seismic lines regardless of vegetation height or the surrounding habitat, but were indifferent to seismic lines during summer, and were indifferent to roads and pipelines during summer and winter. Combined, our results suggest that there are characteristics of seismic lines which make them attractive to moose regardless of the regeneration height on the seismic lines, providing further evidence that effective linear feature restoration will need to address the fact that linear features increase landscape permeability and provide forage for multiple boreal wildlife species. Our results also further illustrate the importance of considering how linear feature restoration efforts focused on caribou may shift the distribution of other boreal wildlife species. Ultimately, conservation efforts for threatened species should recognize that conservation efforts focused on one species may have unintended consequences for interacting species. [ABSTRACT FROM AUTHOR]

Aim: Altitudinal and latitudinal treeline ecotones have not consistently responded to climate warming in the direction and/or magnitude predicted by climate alone, suggesting that non‐climatic mechanisms (e.g. biotic interactions) also mediate treeline range dynamics. Through a collaborative research approach, we assessed environmental conditions associated with pre‐dispersal insect cone granivory and how this biotic interaction may govern the reproductive potential, and therefore range dynamics, of spruce‐dominated treelines across northern Canada. Location: In all, 10 boreal forest treelines, tundra and alpine, from Yukon to Newfoundland and Labrador, Canada. Taxa: White spruce (Picea glauca [Moench] Voss), Black spruce (Picea mariana [Mill.] B.S.P.), Strobilomyia spp., Megastigmus spp. Methods: Treeline sites were assessed for presence and magnitude of pre‐dispersal seed granivory by insects along with viable seed availability. We quantified stand density metrics, organic layer depth and understorey vegetation composition at each location and, subsequently, incorporated those variables into generalized linear mixed models to establish predictors of granivory magnitude and viability of available seed. Results: Insect granivory was widespread across sites; however, site‐specific patterns of granivory were associated with increased moss cover and decreased shrub cover and stand density. While all black spruce‐dominated sites exhibited seed viability rates > 50%, the number of seeds produced per cone varied, suggesting that within‐site abiotic conditions and biotic interaction pressures limit successful colonization of novel environments in advance of seed dispersal. Main Conclusions: The modelled relationships between granivory, seed viability and environmental conditions represent an essential step towards generalizing how and when biotic interactions across subarctic treelines influence boreal tree range dynamics before seed dispersal. Connections between granivory magnitude and site‐level treeline characteristics (e.g. stand density, understorey vegetation) will provide a more comprehensive understanding of treeline range dynamics under continued climate change. [ABSTRACT FROM AUTHOR]

The boreal forest covers a significant portion of the Northern Hemisphere and is snow‐covered for over half of the year. Understanding the interactions between the forest canopy and snow is essential in hydrological, meteorological, and climate modelling. However, this is challenging because the density of a forest can range from closed canopies to open gaps. In winter 2018–2019, we assessed differences in snowpack microstructure in small forest gaps and under the canopy of a humid boreal site in eastern Canada. Our experimental approach consisted of quasi‐continuous weekly observations of stratigraphy and measurements of density profiles and temperature in a series of snow pits in both environments. High‐resolution specific surface area (SSA) profiles were measured twice, allowing for an estimation of snow permeability and hydraulic conductivity. The shallower snowpack under the canopy displayed a stronger vertical temperature gradient and less compaction than in forest gaps. This resulted in the dominance of faceted snow crystals with a small SSA. In contrast, we observed that small, rounded grains with a larger SSA than that of faceted crystals prevailed in the gaps. Due to denser snow and higher SSA, snow permeability inside gaps was found to be lower than under the canopy. Implicitly, the estimated hydraulic conductivity was also lower in gaps. Following rain‐on‐snow events, snow under the canopy displayed layers of melt‐freeze polycrystals, while in the gaps, well‐defined ice layers were formed. The combination of low snow permeability and ice layers is likely to affect liquid water transport in the gap snowpack as compared to the canopy. Although observed at relatively small scales in our study, if these differences are confirmed at a catchment scale, they are likely to impact the hydrology of forested areas during snowmelt. [ABSTRACT FROM AUTHOR]

Copyright of Ecoscience (Ecoscience) is the property of Taylor & Francis Ltd 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.)

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]

As northern latitudes experience rapid winter warming, there is an urgent need to assess the effect of varying winter conditions on tree growth and forest carbon sequestration potential. We examined tree growth responses to variability in cold-season (November–- April) frequency of freeze days (FFD) over 1951 to 2018 using tree-ring data from 35,217 trees and 57 species at 4,375 sites distributed across Canada. We found that annual radial growth responses to FFD varied by species, with some commonalities across genera and clades. The growth of gymnosperms with late spring leaf-out strategies was negatively related to FFD; years with high FFD were most detrimental to the annual growth of Pinus banksiana, Pinus contorta, Larix lyalli, Abies amabilis, and Abies lasiocarpa. In contrast, the growth of angiosperms with early leaf-out strategies, namely, Populus tremuloides and Betula papyrifera, was better in the coldest years, and gymnosperms with intermediate leaf-out timing, such as widespread Picea mariana and Picea glauca, had no consistent relationship to FFD. Tree growth responses to FFD were further modulated by tree size, tree age, regional climate (i.e., mean cold-season temperature), and local site conditions. Overall, our results suggest that moderately warming winters may temporarily improve the growth of widespread pines and some high-elevation conifers in western Canada, whereas warming winters may be detrimental to the growth of widespread boreal angiosperms. Our findings also highlight the value of using species-specific climate-growth relationships to refine predictions of forest carbon dynamics. [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]

Satellite forest inventories are the only feasible way to map Canada's vast, remote forest regions, such as those in the Northwest Territories (NWT). A method used to create such inventories is the k-nearest neighbour (k-NN) algorithm, which spatially extends information from forest inventory (FI) plots to the entire forest land base using wall-to-wall features typically derived from Landsat data. However, the benefits of integrating L-band synthetic aperture radar (SAR) data, strongly correlated to forest biomass, have not been assessed for Canadian northern boreal forests. Here we describe an optimized multivariate k-NN implementation of a 151,700 km2 area in southern NWT that included ca. 2007 Landsat and dual-polarized Phased Array type L-band SAR (PALSAR) data on board the Advanced Land Observing Satellite (ALOS). Five forest attributes were mapped at 30 m cells: stand height, crown closure, stand/total volume and aboveground biomass (AGB). We assessed accuracy gains compared to Landsat-based maps. To circumvent the scarcity of FI plots, we used 3600 footprints from the Geoscience Laser Altimeter System (GLAS) as surrogate FI plots, where forest attributes were estimated using Light Detection and Ranging (LiDAR) metrics as predictors. After optimization, k-NN predicted forest attribute values for each pixel as the average of the 4 nearest (k = 4) surrogate FI plots within the Euclidian space of 9 best features (selected among 6 PALSAR, 10 Landsat, and 6 environmental features). Accuracy comparisons were based on 31 National Forest Inventory ground plots and over 1 million airborne LiDAR plots. Maps that included PALSAR HV backscatter resulted in forest attribute predictions with higher goodness of fit (adj. R2), lower percent mean error (ME%), and percent root mean square error (RMSE%), and lower underestimation for larger attribute values. Predictions were most accurate for conifer stand height (RMSE% = 32.1%, adj. R2 = 0.58) and AGB (RMSE% = 47.8%, adj. R2 = 0.74), which is much more abundant in the area than mixedwood or broadleaf. Our study demonstrates that optimizing k-NN parameters and feature space, including PALSAR, Landsat, and environmental variables, is a viable approach for inventory mapping of the northern boreal forest regions of Canada. [ABSTRACT FROM AUTHOR]