The reproductive ecology of the semi-serotinous species black spruce (Picea mariana (Mill.) BSP) in northern boreal forests remains poorly understood. There is a general lack of data on cone/seed production and viability as a function of biotic tree-level characteristics and abiotic variables. No studies currently exist to quantify these differences over a large gradient in temperature, elevation, and precipitation. Extensive physical, ecological, dendrometric, and reproductive data were collected from young to very old black spruce stands in northern Quebec. ANOVA and general linear mixed models were used to examine interannual cone production, and the relative importance of the biotic and abiotic explanatory factors in determining total cone production; length of the cone-bearing zone; filled seeds per cone; proportion of filled seeds; and seed viability. The results illustrate that the reproductive ecology of black spruce in northern cold forests is mainly explained by biotic variables such as age and diameter at breast height, and by abiotic variables related to temperature such as elevation, length of the growing season, and growing degree-days. Black spruce exhibits a lower reproductive potential in northern cold forests, making it possibly less resilient to increased fire frequency, particularly in unproductive and very young or very old stands.

Old-growth forests of different ages provide specific structures, habitats and ecosystem services. Methods to distinguish this internal diversity are still rare, especially in boreal forests. This research therefore aims to determine the ability of Airborne Laser Scanning (ALS) technology to identify age-related structural diversity in old-growth boreal forests. The study area was located in primary boreal forests in Quebec (Canada) dominated by black spruce (Picea mariana). This area contained 71.8 km2 of early old-growth forests (burned 110 years ago), 17.1 km2 of late old-growth forests (protected areas; unburned for at least 250 years) and 370 km2 of old-growth forests of unknown age (> 125-years-old). We divided the study area into 1 ha tiles, where we extracted seven ALS indices representing vertical and horizontal forest structure. We trained random forest models using an iterative approach to discriminate between early and late old-growth forests based on ALS indices. Model predictions were applied to the old-growth tiles of unknown age, and to 86 field plots (28 from provincial forest surveys and 58 from a dedicated survey of old-growth forests) to evaluate the predictive capacity of the models. The models very accurately distinguished early and late old-growth forests (error-rate = 4.9%). Old-growth survey plots confirmed model ability to discriminate early and late old-growth forests, but not provincial survey plots, possibly because of a lower reliability of these data when forest age exceeds 150 years. Model predictions for tiles of unknown age highlighted the presence of very large tracts of late old-growth forests within a matrix of old-growth forests of intermediate age (≈150–200 years). Overall, ALS-data can contribute to a finer structural age distinction and mapping of boreal old-growth forests. This enhanced knowledge of old-growth landscapes will greatly help to improve their protection, restoration and management. The scarcity of reliable field data for model evaluation is, however, a limitation to be addressed.

Even-aged silviculture based on short-rotation clearcuts had severely altered boreal forests. Silvicultural alternatives (e.g. continuous cover or retention forestry) have the potential to restore and protect the habitats and functions of boreal forests. These alternatives are however often restricted to structurally complex old-growth forest, which are particularly threatened by anthropogenic disturbances. Increasing the use of alternatives to even-aged silviculture in early-successional stands could help recruit more structurally complex forests, with characteristics closer to the old-growth. In this article, we therefore evaluate the potential for silvicultural alternatives to even-aged management in boreal forests that burned less than a century ago.

We analysed 1085 field plots in a 243,000 km² area situated in the boreal forest of eastern Canada. These plots burned 30–100 years before the survey and had not been subjected to previous or subsequent anthropogenic disturbance; they hence represent young primary forests. The main patterns of tree diameter distribution variation within the plots were identified using k-means clustering. Stand structure, tree species composition and environmental variables that most explained the differences among the clusters were identified with a random forest model, and then compared using Kruskal–Wallis and Fisher's exact tests.

The majority (>75%) of the plots presented an irregular structure of stem diameters (i.e. non-normally distributed, with many small diameter trees). The understorey was generally dominated by black spruce (Picea mariana [Mill.] BSP), a shade-tolerant species. Irregular structures were observed in both forests of high and low productivity, implying that different processes (e.g. early regeneration, variable tree growth) can lead to observed early irregular structure. Regular structures were generally characterized by a higher productivity and abundance in hardwood species compared to the irregular structures.

Synthesis and applications. Many boreal forests of eastern Canada progress towards an irregular structure in the decades following the last stand-replacing fire. A substantial part of these early-successional forests may be suitable for alternatives to even-aged silviculture that better maintains habitats and functions of preindustrial boreal forests.

Successive disturbances such as fire can affect post-disturbance regeneration density, with documented adverse effects on subsequent stand productivity. We conducted a simulation study to assess the potential of reactive (reforestation) and proactive (variable retention harvesting) post-fire regeneration failure mitigation strategies in a 1.37 Mha fire-prone boreal landscape dominated by black spruce (Picea mariana (Mill.) B.S.P.) and jack pine (Pinus banksiana Lamb.). We quantified their respective capacity to maintain landscape productivity and post-fire resilience, as well as their associated financial returns under current and projected (RCP 8.5) fire regimes. While post-fire reforestation with jack pine revealed to be the most effective strategy to maintain potential production, associated costs quickly became prohibitive when applied over extensive areas. Proactive strategies such as an extensive use of variable retention harvesting, combined with replanting of fire-adapted jack pine only in easily accessible areas, appeared as a more promising approach. Despite this, our results suggest an inevitable erosion of forest productivity due to post-fire regeneration failure events, highlighting the importance of integrating fire a priori in strategic forest management planning as well as its effects on long-term regeneration dynamics.

Recovery of bryophyte diversity following silvicultural treatments depends upon the reestablishment of favorable microhabitats and microclimatic conditions. Without sources of propagules (reproductive structures) within the managed landscape, however, even optimal habitat conditions would not be sufficient to ensure bryophyte diversity. To identify sources of propagules and ensure their protection, we used indices that were derived from a Digital Elevation Model (DEMs) and an airborne point cloud (LiDAR; Light Detection and Ranging) as explanatory variables to predict bryophyte biodiversity. Bryophytes were collected in the intensively managed Black Brook District of New Brunswick, Canada, in eight mature managed and unmanaged forest types (n = 38). Our results show a strong bryophyte community gradient between wetter stands (Cedar, riparian zone and Spruce-Fir) and drier stands (Tolerant Harwood and Plantation) forming two distinctive groups. Indices explaining bryophyte composition and richness were related to moisture (closest distance to a stream), canopy (canopy relief ratio, canopy closure and density) and microtopography (Topographic Position Index). Models obtained from these indices explained 75% of bryophyte composition and predicted composition with a certainty of 71% The predominance of the closest distance to a stream in our model reinforces the great importance of buffer along the hydrological network. Buffers represent a substantial propagule source for the landscape and notably increase its ecological connectivity. Although wetter sites had greater richness, the completely different composition find at drier sites suggest that biodiversity management efforts to maintain bryophytes should not be restricted to wetter stands. Our model demonstrates the potential of airborne LiDAR-derived indices as surrogates for field data in estimating and mapping bryophyte compositions to understand the variation in diversity across the managed landscape. This model can be used as a dynamic tool to target areas that represent the overall bryophyte diversity of the managed landscape to ensure protection of propagule sources and favors reestablishment.

Degradation of forest roads in Canada has strong negative effects on access to forestlands, together with economic (e.g., increased maintenance costs), environmental (e.g., erosion of materials and subsequent habitat contamination), and social (e.g., use risks) impacts. Maintaining sustainable and safe access to forestland requires a better understanding and knowledge of forest road degradation over time and space. Our study aimed to identify relevant spatiotemporal variables regarding the state of eastern Canadian forest road networks by (1) building predictive models of gravel forest road degradation and assessing effects of the slope, time, loss of the road surface, and road width (field approach), and (2) evaluating the potential of topography, roughness and vegetation indices obtained from Airborne Laser Scanning (ALS) data and Sentinel-2 optical images to estimate degradation rates (remote sensing approach). The field approach (n = 207 sample plots) confirmed that only four variables were efficient to estimate degradation rates (pseudo-R2 = 0.43 with ±8% error). Simulations that were conducted showed that after about five years without maintenance, the rate of degradation on a road, regardless of its width, increased exponentially, exacerbated by a high slope gradient and loss of road surface. The narrowest roads tended to degrade more rapidly over time. The remote sensing approach performed quite well (pseudo-R2 = 0.34 with ±9% error) in terms of predicting road degradation, giving us the valuable tools to spatialise the state of gravel forest road degradation in eastern Canadian forest. This study provided new knowledge and tools that are critical for maintaining and sustaining access to Canada’s boreal forest territory in both the short- and the long-term.

In Canadian boreal forests, bryophytes represent an essential component of biodiversity and play a significant role in ecosystem functioning. Despite their ecological importance and sensitivity to disturbances, bryophytes are overlooked in conservation strategies due to knowledge gaps on their distribution, which is known as the Wallacean shortfall. Rare species deserve priority attention in conservation as they are at a high risk of extinction. This study aims to elaborate predictive models of rare bryophyte species in Canadian boreal forests using remote sensing-derived predictors in an Ensemble of Small Models (ESMs) framework. We hypothesize that high ESMs-based prediction accuracy can be achieved for rare bryophyte species despite their low number of occurrences. We also assess if there is a spatial correspondence between rare and overall bryophyte richness patterns. The study area is located in western Quebec and covers 72,292 km2. We selected 52 bryophyte species with <30 occurrences from a presence-only database (214 species, 389 plots in total). ESMs were built from Random Forest and Maxent techniques using remote sensing-derived predictors related to topography and vegetation. Lee’s L statistic was used to assess and map the spatial relationship between rare and overall bryophyte richness patterns. ESMs yielded poor to excellent prediction accuracy (AUC > 0.5) for 73% of the modeled species, with AUC values > 0.8 for 19 species, which confirmed our hypothesis. In fact, ESMs provided better predictions for the rarest bryophytes. Likewise, our study revealed a spatial concordance between rare and overall bryophyte richness patterns in different regions of the study area, which have important implications for conservation planning. This study demonstrates the potential of remote sensing for assessing and making predictions on inconspicuous and rare species across the landscape and lays the basis for the eventual inclusion of bryophytes into sustainable development planning.

In the context of global warming, forest fires are expected to occur more frequently and intensively, and impose more significant impacts on human society, terrestrial ecosystems, and atmosphere. Most of the existing methods in monitoring large-scale forest fire are based either on satellite visible and infrared observations or weather-based indices. This work explored the advantages of a new satellite microwave-based vegetation index in monitoring forest fire occurrence and fire intensity in Northeastern Asia and Southern China. Specifically, we used satellite observations during 2002–2011 to investigate the correlation at different temporal scales between forest fire properties (fire count, FC; fire radiative power, FRP) and the vegetation water content proxy of the Microwave Emissivity Difference Vegetation Index (EDVI) derived from the Moderate Resolution Imaging Spectroradiometer and the Advanced Microwave Scanning Radiometer-EOS on Aqua satellite. The correlations were compared to that with three weather-based indices including the Fine Fuel Moisture Code, Initial Spread Index and Fire Weather Index (FWI) to determine whether EDVI provides new independent information of forest fires. Finally, EDVI and the weather-based indices FWI were combined to establish multivariate linear regression models to estimate FC and FRP. Results show that: 1) the temporal variations of FC and total FRP are negatively correlated with EDVI using the daily and monthly observations at 1° grid and regional scales; and overall opposite annual cycles and interannual variations between FC (and total FRP) and EDVI are observed in Northeastern Asia and Southern China; 2) compared to the weather-based indices, EDVI shows higher correlation with the temperate forest fire properties in Southern China while shows weaker correlation with the forest fire properties in Northeastern Asia; and a combination of the two kind of indices is found to improve the explained variance for fire properties in both regions; 3) multivariate linear regression models based on EDVI and FWI provide better estimation of FC and FRP compared to the linear regression models based on FWI alone. To our knowledge, this is the first work that comprehensively investigates the potential application of the microwave-based vegetation water content index in forest fire count and fire intensity.