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.

In old-growth forests, natural disturbances form a complex mosaic of structures, providing a wide diversity of habitats and functions of great importance. Old-growth forests are still often seen as a homogeneous whole and few remote-sensing approaches have been tested to identify their structural diversity, especially in boreal forests. The aim of this study is to use a combination of airborne LiDAR and satellite imagery to identify and discriminate old-growth forest structures resulting from different disturbance histories. The study area, which was located in the mixed boreal forest of Quebec (Canada), is Monts Valin National Park and adjacent managed territories. Balsam fir (Abies balsamea (L.) Mill) is the dominant species in the study area, but hardwood species such as white birch (Betula papyrifera Marsh.) and trembling aspen (Populus tremuloides Michx.) can also be abundant in the early succession stages. Four forest classes were studied: second-growth (logged between 1970 and 1980); transition old-growth (burned in 1920); undisturbed old-growth (unburned for at least 125 years); and disturbed old-growth forest (unburned for at least 125 years, but severely disturbed by an insect outbreak around 1980). A multivariate Random Forest model was used to discriminate the classes on 6466 1 ha tiles, based on 11 complementary LiDAR and satellite-derived indices describing stand vertical and horizontal structure, together with “greenness” and disturbance history over the last 30 years. This model had high predictive efficiency (AUC = 94.2), with 81.8% of the tiles accurately classified. Interestingly, undisturbed old-growth forests exhibited intermediate characteristics compared to transition and disturbed old-growth forests. This emphasizes that some structural attributes recognized as important for the classification of temperate and tropical old-growth forests, such as high vertical complexity, are of lesser relevance for boreal old-growth forests. In comparison to undisturbed old-growth forests, transition old-growth forests had a taller canopy of high “greenness” due to a greater hardwood abundance; disturbed old-growth forests had a higher gap fraction and heterogeneity in tree size; second-growth forests exhibited a lower and more even canopy. Misclassified tiles were explained by spatial variation in disturbance severity or different levels of forest resistance and resilience to disturbance. These misclassifications are also of ecological interest, as they highlight the nuances in structural diversity that are rarely identified by disturbance mapping. A reasonable combination of LiDAR and satellite indices was effective not only in discriminating old-growth forests from second-growth forests, but also identifying their different structures, which result from specific disturbance histories. This method could contribute to effective monitoring of changes in the areas and characteristics old-growth forest that are caused by anthropogenic and natural disturbances.

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.