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21Male little brown bat (Myotis lucifugus (Le Conte, 1831)) and northern long-eared bat (Myotis 22 septentrionalis (Trouessart, 1897)), often roost under exfoliating bark, within the trunks and 23 cavities of trees during summer. Current lack of knowledge about the roosting ecology of these 24 species in boreal forest limits our understanding of how they may be affected by logging. The 25 main objective was to identify tree and forest stand features that were selected by bats for genre Myotis au sein des sapinières à bouleau blanc. 58Mots clés: arbre-gîte, chicots, chauve-souris nordique, forêt boréale, LiDAR, Myotis lucifugus, 59Myotis septentrionalis, petite chauve-souris brune, Québec, sélection d'habitat 60 61 4

Background : Understanding the immune response to natural infection by SARS-CoV-2 is key to pandemic management, especially in the current context of emerging variants. Uncertainty remains regarding the efficacy and duration of natural immunity against reinfection. Method : We conducted an observational prospective cohort study in Canadian healthcare workers (HCWs) with a history of PCR-confirmed SARS-CoV-2 infection to : (i) measure the average incidence rate of reinfection and (ii), describe the serological immune response to the primary infection. Results : We detected 5 cases of reinfection over 14 months of follow-up, for a reinfection incidence rate of 3.3 per 100 person-years. Median duration of seropositivity was 420 days in symptomatics at primary infection compared to 213 days in asymptomatics (p<0.0001). Other variables associated with prolonged seropositivity for IgG against the spike protein included age 55 and above, obesity, and non-Caucasian ethnicity. Summary : Among healthcare workers, the incidence of reinfection with SARS-CoV-2 following a primary infection remained rare, although our analysis predates the circulation of the Omicron variant.

Influenza and RSV are human viruses responsible for outbreaks in hospitals, long-term care facilities and nursing homes. The present study assessed an air treatment using ozone at two relative humidity conditions (RHs) in order to reduce the infectivity of airborne influenza. Bovine pulmonary surfactant (BPS) and synthetic tracheal mucus (STM) were used as aerosols protectants to better reflect the human aerosol composition. Residual ozone concentration inside the aerosol chamber was also measured. RSV’s sensitivity resulted in testing its resistance to aerosolization and sampling processes instead of ozone exposure. The results showed that without supplement and with STM, a reduction in influenza A infectivity of four orders of magnitude was obtained with an exposure to 1.70 ± 0.19 ppm of ozone at 76% RH for 80 min. Consequently, ozone could be considered as a virucidal disinfectant for airborne influenza A. RSV did not withstand the aerosolization and sampling processes required for the use of the experimental setup. Therefore, ozone exposure could not be performed for this virus. Nonetheless, this study provides great insight for the efficacy of ozone as an air treatment for the control of nosocomial influenza A outbreaks.

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Key message We assessed even-aged stand vertical distributions of LiDAR returns and found that tree species, age, and crown cover each have a distinct pattern that together explains up to 47% of the variation. Abstract Light detection and ranging (LiDAR) provides information on the vertical structure of forest stands enabling detailed and extensive ecosystem study. The vertical structure is often summarized by scalar features and data-reduction techniques that limit the interpretation of results. Instead, we quantified the influence of three variables, species, crown cover, and age, on the vertical distribution of airborne LiDAR returns from forest stands. We studied 5428 regular, even-aged stands in Quebec (Canada) with five dominant species: balsam fir [Abies balsamea (L.) Mill.], paper birch (Betula papyrifera Marsh), black spruce [Picea mariana (Mill.) BSP], white spruce (Picea glauca Moench) and aspen (Populus tremuloides Michx.). We modeled the vertical distribution against the three variables using a functional general linear model and a novel nonparametric graphical test of significance. Results indicate that LiDAR returns from aspen stands had the most uniform vertical distribution. Balsam fir and white birch distributions were similar and centered at around 50% of the stand height, and black spruce and white spruce distributions were skewed to below 30% of stand height ($$p$$ p <0.001). Increased crown cover concentrated the distributions around 50% of stand height. Increasing age gradually shifted the distributions higher in the stand for stands younger than 70-years, before plateauing and slowly declining at 90–120 years. Results suggest that the vertical distributions of LiDAR returns depend on the three variables studied.

Monitoring crown closure evolution using multi-temporal Light Detection and Ranging (LiDAR) surveys is a method that we expect to be increasingly adopted given the availability of LiDAR sensors and the accumulating survey archives. However, little attention was devoted to comparing crown closure estimates from independent surveys. Although survey parameters cannot be modified after the data collection, we speculate that the error associated to crown closure estimates comparison can be reduced by selecting optimal post-survey parameters. In this study, we compared crown closure estimates of three airborne LiDAR surveys from 2018 (40 pt/m²) used as a reference, and two lower-density surveys from 2016 (4.5 pt/m²) and 2018 (2 pt/m²). We studied the effect of the height threshold used to separate canopy points and the grid resolution, using skewness and variance of lagged difference of crown closure. Crown closure estimates using low height thresholds were more different across surveys, resulting in higher root mean squared error (RMSE), bias and more different variograms. Results show that optimal height threshold was 3 m and grid resolution was 25 m, although there was room for decision (RMSE of 7% and 5%, and bias of 4% and 0% for 2016 and 2018 low-density surveys).