Biology subjects

Boucher, Y.

Publications and source records attributed to Boucher, Y..

5 recordsLinked to original sources

bioRxiv2025

High-severity fires undermine resilience of black spruce-dominated boreal forests in eastern North America

Climate-induced fire regime shifts may reduce post-fire resilience of black spruce-dominated (BS; Picea mariana) North American boreal forests. While post-fire vulnerability of immature BS stands has been extensively studied, no study has evaluated simultaneous effects of fire severity and seasonality on the post-fire regeneration of mature (> 60-year-old) BS stands. This study aims to quantify post-fire regeneration levels of BS and co-occurring tree species to assess ecosystem recovery and possible loss of resilience due to regeneration failure. We analyzed effects of seed bank conditions, fire regime characteristics (fire severity and seasonality), and seedbed conditions on BS post-fire regeneration in mature forests in Quebec, Canada. Post-fire regeneration density was extensively surveyed across [~]50 400 km2 through a network of 536 plots that were distributed in 21 fires, which burned between 1995 and 2016. One-third of plots failed to regenerate (< 1750 conifer seedlings/ha) at levels adequate to produce closed-crown forest, whereas one-fifth experienced compositional changes, mainly towards jack pine (JP; Pinus banksiana) dominance. Pre-fire basal area of BS and living Sphagnum ground cover increased BS post-fire regeneration, whereas high-severity crown fires and spring fires reduced it. These findings suggest that mature BS-dominated forests may lose resilience in response to high-severity and spring fires. Given the projected increase in fire severity, and the extension towards an early-fire season in response to climate change, our study suggests that post-fire regeneration failure may become more frequent over the coming decades, with potential negative consequences on ecosystem services that are provided by BS-dominated boreal forests.

ecology↗

bioRxiv2024

The 2023 wildfire season in Quebec: an overview of extreme conditions, impacts, lessons learned and considerations for the future.

The 2023 wildfire season in Quebec set records due to extreme warm and dry conditions, burning 4.5 million hectares and indicating persistent and escalating impacts associated with climate change. The study reviews the unusual weather conditions that led to the fires, discussing their extensive impacts on the forest sector, fire management, boreal caribou habitats, and particularly the profound effects on First Nation communities. The wildfires led to significant declines in forest productivity and timber supply, overwhelming fire management resources, and necessitating widespread evacuations. First Nation territories were dramatically altered, facing severe air quality issues and disruptions. While caribou impacts were modest across the province, the broader ecological, economical, and social repercussions were considerable. To mitigate future extreme wildfire seasons, the study suggests changes in forest management practices to increase forest resilience and resistance, adapting industrial structures to new timber supplies, and enhancing fire suppression and risk management strategies. It calls for a comprehensive, unified approach to risk management that incorporates the lessons from the 2023 fire season and accounts for ongoing climate change. The study underscores the urgent need for detailed planning and proactive measures to reduce the growing risks and impacts of wildfires in a changing climate.

ecology↗

bioRxiv2022

Positive effects of projected climate change on post-disturbance forest regrowth rates in northeastern North American boreal forests

Forest anthropogenic and natural stand-replacing disturbances are increasing worldwide due to global change. Many uncertainties regarding the regeneration and growth of these young forests remain within the context of changing climate. In this study, we investigate the effects of climate, tree species composition, and other landscape-scale environmental variables upon boreal forest regrowth following clearcut logging in eastern Canada. Our main objective was to predict the effects of future climate changes upon post-logging forest height regrowth at a subcontinental scale using high spatial resolution remote sensing data. We modeled forest canopy height (estimated from airborne laser scanning [LiDAR] data over 20-m resolution virtual plots) as a function of time elapsed since the last clearcut along with climatic (i.e., temperature and moisture), tree species composition, and other environmental variables (e.g., topography and soil hydrology). Once trained and validated with [~]240,000 plots, the model that was developed in this study was used to predict potential post-logging canopy height regrowth at 20-m resolution across a 240,000 km2 area following scenarios depicting a range of projected changes in temperature and moisture across the region for 2041-2070. Our results predict an overall beneficial, but limited effect of projected climate changes upon forest regrowth rates in our study area. Stimulatory effects of projected climate change were more pronounced for conifer forests, with growth rates increasing between +5% and +50% over the study area, while mixed and broadleaved forests recorded changes that mostly ranged from -5% to +35%. Predicted increased regrowth rates were mainly associated with increased temperature, while changes in climate moisture had a minor effect. We conclude that such gains in regrowth rates may partially compensate for projected substantial increases in fire activity and other natural disturbances that are expected with climate change in these boreal forests.

ecology↗

bioRxiv2021

Pandemic Vibrio cholerae Acquired Competitive Traits from an Environmental Vibrio Species

BackgroundVibrio cholerae, the causative agent of cholera, is a human pathogen that thrives in estuarine environments. V. cholerae competes with neighboring microbes by the contact-dependent translocation of toxic effectors with the type VI secretion system (T6SS). Effector types are highly variable across V. cholerae strains, but all pandemic isolates encode the same set of distinct effectors. It is possible that acquisition of these effectors via horizontal gene transfer played a role in the development of pandemic V. cholerae. ResultsWe assessed the distribution of V. cholerae T6SS loci across multiple Vibrio species. We showed that the fish-pathogen V. anguillarum encodes all three V. cholerae core loci as well as two of the four additional auxiliary clusters. We further demonstrated that V. anguillarum shares T6SS effectors with V. cholerae, including every pandemic-associated V. cholerae effector. We identified a novel T6SS cluster (Accessory Aux1) that is widespread in V. anguillarum and encodes the pandemic V. cholerae effector TseL. We highlighted potential gene transfer events of Accessory Aux1 from V. anguillarum to V. cholerae. Finally, we showed that TseL from V. cholerae can be neutralized by the V. anguillarum Accessory Aux1 immunity protein and vice versa, indicating V. anguillarum as the donor of tseL to the V. cholerae species. ConclusionsV. anguillarum constitutes an environmental reservoir of pandemic-associated V. cholerae T6SS effectors. V. anguillarum and V. cholerae likely share an environmental niche, compete, and exchange T6SS effectors. Further, our findings highlight the fish as a potential reservoir of pandemic V. cholerae.

genomics↗

bioRxiv2021

Modeling post-logging height growth of black spruce forests by combining airborne LiDAR and historical forestry maps in eastern Canadian boreal forest

Increase in forest disturbance due to land use as well as climate change has led to an expansion of young forests worldwide, which affects global carbon dynamics and forest management. In this study, we present a novel method that combines a single airborne LiDAR acquisition and historical harvesting maps to model height growth of post-logged black spruce-dominated forests in a 1700 km2 eastern Canadian boreal landscape. We developed a random forest model where forest height is a function of stand age, combined with environmental variables. Our results highlight the strong predictive power of this model: least-square regression between predicted and observed height of our validation dataset was very close to the 1:1 relation and strongly supported by validation metrics (R2 = 0.75; relative RMSE = 19%). Moreover, our findings indicated an ecological gradient responsible for differences in height growth at the landscape scale, with better growth rates on mesic slopes compared to badly drained soils on flat lands. With the increased availability of LiDAR data, this method is promising since it can be applied to forests across the globe that are affected by stand-replacing disturbances.

ecology↗