Old-growth forests provide many precious ecological, economic, cultural, recreational and spiritual ecosystem services (Wirth et al., 2009). These ecosystem services are generally specific in comparison to younger or managed forests, explaining the high ecological and social value we place on their conservation, especially considering worldwide threats to them from human activities. These pressures are expected to increase in the coming decades in the face of global change (Wright and Muller-Landau, 2006; Kuuluvainen and Gauthier, 2018; Sabatini et al., 2018). Understanding how to protect and restore these old-growth forests in a changing world has therefore become a major forest management issue (Puettmann et al., 2015).

Assessing the impacts of natural disturbance on the functioning of complex forest systems are imperative in the context of global change. The unprecedented rate of contemporary species extirpations, coupled with widely held expectations that future disturbance intensity will increase with warming, highlights a need to better understand how natural processes structure habitat availability in forest ecosystems. Standardised typologies of tree-related microhabitats (TreMs) have been developed to facilitate assessments of resource availability for multiple taxa. However, natural disturbance effects on TreM diversity have never been assessed. We amassed a comprehensive dataset of TreM occurrences and a concomitant 300-year disturbance history reconstruction that spanned large environmental gradients in temperate primary forests. We used nonlinear analyses to quantify relations between past disturbance parameters and contemporary patterns of TreM occurrence. Our results reveal that natural forest dynamics, characterised by fluctuating disturbance intervals and variable severity levels, maintained structurally complex landscapes rich in TreMs. Different microhabitat types developed over time in response to divergent disturbance histories. The relative abundance of alternate TreMs was maximised by unique interactions between past disturbance severity and elapsed time. Despite an unequal distribution of individual TreMs, total microhabitat diversity was maintained at constant levels, suggesting that spatially heterogeneous disturbances maintained a shifting mosaic of habitat types over the region as a whole. Our findings underscore the fundamental role of natural processes in promoting conditions that maximise biodiversity potential. Strict conservation and management systems that preserve natural disturbance outcomes, including associated biological legacies, may therefore safeguard biodiversity at large scales.

Sustainable management of forest ecosystems requires the use of reliable and easy to implement biodiversity and naturalness indicators. Tree-related microhabitats (TreMs) can fulfill these roles as they harbor specialized species that directly or indirectly depend on them, and are generally more abundant and diverse in natural forests or forests unmanaged for several decades. The TreM concept is however still recent, implying the existence of many knowledge gaps that can challenge its robustness and applicability. To evaluate the current state of knowledge on TreMs, we conducted a systematic review followed by a bibliometric analysis of the literature identified. A total of 101 articles constituted the final corpus. Most of the articles (60.3%) were published in 2017 or after. TreM research presented a marked lack of geographical representativity, as the vast majority (68.3%) of the articles studied French, German or Italian forests. The main themes addressed by the literature were the value of TreMs as biodiversity indicators, the impact of forest management on TreMs and the factors at the tree- and stand-scales favoring TreMs occurrence. Old-growth and unmanaged forests played a key role as a “natural” forest reference for these previous themes, as TreMs were often much more abundant and diverse compared to managed forests. Arthropods were the main phylum studied for the theme of TreMs as biodiversity indicators. Other more diverse themes were identified, such as restoration, remote sensing, climate change and economy and there was a lack of research related to the social sciences. Overall, current research on TreMs has focused on assessing its robustness as an indicator of biodiversity and naturalness at the stand scale. The important geographical gap identified underscores the importance of expanding the use of the TreMs in other forest ecosystems of the world. The notable efforts made in recent years to standardize TreM studies are an important step in this direction. The novelty of the TreM concept can partially explain the thematic knowledge gaps. Our results nevertheless stress the high potential of TreMs for multidisciplinary research, and we discuss the benefits of expanding the use of TreMs on a larger spatial scale.

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.