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L'ÉQUIPE La direction scientifique du programme est assurée par Alexis Achim et Nicholas Coops. Douze chercheurs principaux et environ 50 collaborateurs de tout le pays contribueront à cet effort de recherche sans précédent dans le domaine de la sylviculture. Le projet réunit un consortium de cinq universités, cinq entreprises forestières privées, une communauté des Premières Nations, cinq agences gouvernementales provinciales, ainsi que le Centre Canadien sur la Fibre de Bois (CCFB) et FPInnovations en tant qu'organismes de recherche nationaux. Structure de gouvernance Direction Scientifique Codemandeurs Contacts clés PHQ Partenaires Direction scientifique Codemandeurs Alexis Achim, UL alexis.achim@sbf.ulaval.ca Nicholas Coops, UBC nicholas.coops@UBC.CA Direction Scienifique Codemandeurs Brad Pinno, UoA bpinno@UALBERTA.CA Charles Nock, UoA nock@UALBERTA.CA Evelyne Thiffault, UL Evelyne.Thiffault@SBF.ULAVAL.CA Loïc D’Orangeville, UNB loic.dorangeville@UNB.CA Shannon Hagerman, UBC shannon.hagerman@UBC.CA Bianca Eskelson, UBC bianca.eskelson@UBC.CA Dominik Roeser, UBC dominik.roeser@UBC.CA John Caspersen, UoT john.caspersen@UTORONTO.CA Maude Flamand-Hubert, UL maude.flamand-hubert@SBF.ULAVAL.CA Contact clé pour les organisations partenaires Vincent Roy, CWFC Joanne White, CFS John MacLellan, Kruger Faron Knott, Kruger Jean Girard, MFFP-QC Jennifer Dacosta, NDMNRF Chris McDonell, GreenFirst Adam Gorgolewski, Haliburton Forest Jodi Axelson, BC MFLNRO Mathieu Blouin, FPInnovations Éric Lapointe, Domtar David Bernard, Grand-Conseil de la Nation Waban-Aki Kevin Jewett, NRR-NS Bruce Stewart, NRR-NS Chris Hennigar, DNRED NB Shane Furze, JDI Personnel hautement qualifié Sandrine Paquin, UL (projet complété) Laurence Boudreault, UL Anne Bernard, UL (projet complété) Catherine Chagnon, UL Amy Wotherspoon, UBC Christina Howard, UBC Jamie Ring, UBC Lisa Han, UofT José Riofrío, UBC Lukas Olson, UBC Mario Stolz, UBC Spencer Shields, UBC Guillaume Moreau, UofT (projet complété) João Paulo Czarnecki de Liz, UL Marilou Yargeau, UL ( projet complété) Catherine Beaulieu, UL Sarah Smith-Tripp, UBC Gabrielle Thibault, UL (projet complété) Chris Mulverhill, UBC Florence Leduc, UL Kirk Johnson, UBC Madison Brown, UBC Emmannuelle Baby-Bouchard, UL Ethan Ramsfield, UA Taylor Bottoms-Cau, UNB Alexandre Morin-Bernard, UL (projet complété) Sergio Alonso Sanchez, UBC Liam Irwin, UBC Tommaso Trotto, UBC Rover Liu, UBC Dane Pedersen, UBC Jacob Ravn, UNB Chloe Larstone Hunt, UNB Philippe Riel, UL Sébastien Dumont, UL Helin Dura, UL Michael Burnett (projet complété) Meghan Clayton, UAlberta Contacts clé PHQ Nos partenaires Partenaires

< Retour Targeted assisted migration AN 5 Hub: All Year: 2022-2025 João Paulo Czarnecki de Liz, PhD Through AN.1b, we will have access to broad-scale species distribution coverages for key species as well as predictions of changes in the distribution of the species under climate change. However, broad scale species distribution changes will not alter short term silviculture decision making. Using predictions of key species and provenances targeted for assisted migration made by AN.1b for all Hub sites, a PhD project will have the objective to develop a framework allowing ecological, silvicultural and socio-economic criteria to be weighed when evaluating the relevance of assisted migration measures. We will evaluate strategies both in terms of the likelihood of establishment success and of reaching harvestable age to assist silvicultural decision-making at a fine scale. Outcome: Spatially-explicit recommendations of silvicultural treatments that will favour success of assisted migration strategies. João Paulo Czarnecki de Liz, PhD at Université Laval Main Partner: Domtar Professor Alexis Achim Collaborator Nicholas Coops ​

PUBLICATIONS Developing aboveground biomass yield curves for dominant boreal tree species from time series remote sensing data Tompalski, P., Wulder, M.A., White, J.C., Hermosilla, T., Riofrio, J., Kurz, W.A. ISPRS Forest Ecology and Management, 561: 121894. Landsat assessment of variable spectral recovery linked to post-fire forest structure in dry sub-boreal forests Smith-Tripp, S.M., Coops, N.C., Mulverhill, C., White, J.C., Axelson, J. 2023. ISPRS Journal of Photogrammetry and Remote Sensing. 208:121-135. https://doi.org/10.1016/j.isprsjprs.2024.01.008 Predicting net growth rates in boreal forests using Landsat time series and permanent sample plot data Morin-Bernard, A., Coops, N.C., White, J.C., Achim, A. 2023. Forestry: An International Journal of Forest Research, cpad055, https://doi.org/10.1093/forestry/cpad055 Local adaptation of balsam fir seedlings improves growth resilience to heat stress Ravn, J., Taylor, A.R., Lavigne, M.B., D'Orangeville, L. Canadian Journal of Forest Research, https://doi.org/10.1139/cjfr-2023-0128 Characterizing non-stand replacing (NSR) disturbances using bitemporal airborne laser scanning (ALS) data Trotto, T., Coops, N.C., Achim, A. (2023). SilviLaser Conference Poster Presentation. 6 - 8 September, UCL, London, UK. Modelling height growth of temperate mixedwood forests using an age-independent approach and multi-temporal airborne laser scanning data Riofrio, J., White, J.C., Tompalski, P., Coops, N., Wulder, M.A (2023). Forest Ecology and Management, 543, 121137. https://doi.org/10.1016/j.foreco.2023.121137 Thinning as a tool to increase resistance to stressors Alonso, S., Roeser, D., Mologni, O. (2023) BC Community Forest Association 2023 Conference and AGM. Langley, BC. June 7-9, 2023 Attributing a Causal Agent and Assessing the Severity of Non-Stand Replacing Disturbances in a Northern Hardwood Forest using Landsat-Derived Vegetation Indices. Morin-Bernard, A., Achim, A., Coops, N.C. 2023. Canadian Journal of Remote Sensing, 49(1), https://doi.org/10.1080/07038992.2023.2196356 Visual assessment of tree vigour in Canadian northern hardwood forests: The need for a simplified system Moreau, G., Cecil-Cockwell, M.J.L., Pothier, D. et al. (2023). Forest Ecology and Management, 529; 120720. https://doi.org/10.1016/j.foreco.2022.120720 Automated Forest Harvest Detection With a Normalized PlanetScope Imagery Time Series Keay, L., Mulverhill, C., Coops, N.C., McCartney, (2022) Canadian Journal of Remote Sensing, 1-15; https://doi.org/10.1080/07038992.2022.2154598 Deciphering the black spruce response to climate variation across eastern Canada using a meta-analysis approach Chagnon, C., Wotherspoon, A.R., Achim, A. (2022) Forest Ecology and Management, 520: 120375. https://doi.org/10.1016/j.foreco.2022.120375 Analysis of a wood production strategy from expert perspectives Canuel, C-M., Bernard, A., Thiffault, N., et al. (2022). The Forestry Chronicle, 98(1): 1-9. https://pubs.cif-ifc.org/doi/pdf/10.5558/tfc2022-004 Broad-scale wood degradation dynamics in the face of climate change: A meta-analysis Chagnon, C., Moreau, G., Bombardier-Cauffopé, C., Barrette, J., Havreljuk, F., Achim, A. (2022). GCB-Bioenergy, 14(8): 941-958. https://doi.org/10.1111/gcbb.12951 Opportunities and limitations of thinning to increase resistance and resilience of trees and forests to global change Moreau, G., Chagnon, C., Achim, A., et al. (2022). Forestry, 1-21. https://doi.org/10.1093/forestry/cpac010 Single photon lidar signal attenuation under boreal forest conditions Irwin, L., Coops, C.C., Queinnec, M., McCartney, G., White, J. (2021) Remote Sensing Letters, 12(10). https://doi.org/10.1080/2150704X.2021.1962575 Integration of tree-ring data, Landsat time series, and ALS-derived topographic variables to quantify growth declines in black spruce Morin-Bernard, A., Achim, A., Coops, N.C., White, J. 2024. Forest Ecology and Management, 557(1):121765 American beech outgrows sugar maple at the sapling stage regardless of partial harvest intensity in northern hardwood forests Leduc, F., Chagnon, C., Moreau, G., Dumont, S., St-Jean E., Achim, A. 2024. Forest Ecology and Management, 553:121630. https://doi.org/10.1016/j.foreco.2023.121630 Assessing future climate trends and implications for managed forests across Canadian ecozones Wotherspoon, A.R., Achim, A., Coops, N.C. (2023) Canadian Journal of Forest Research. https://doi.org/10.1139/cjfr-2023-0058 Simplified tree marking guidelines enhance value recovery as well as stand vigour in northern hardwood forests under selection management Moreau, G., Chagnon, C., Cecil-Cockwell, MJL, Pothier, D., Achim, A., Bédard, S., Guillemette, F., Caspersen, J. (2023) Forestry: An International Journal of Forest Research. https://doi.org/10.1093/forestry/cpad045 Extension Note Vol 3: Becoming a foreign drone pilot Smith-Tripp, S*., Stackhouse, L., Wotherspoon, A.R. Strong latitudinal gradient in temperature-growth coupling near the treeline of the Canadian subarctic forest. Front. For. Glob. Change 6:1181653. Chagnon C, Moreau G, D’Orangeville L, Caspersen J, Labrecque-Foy J-P and Achim A Seeing the forest through the trees: Collaborative climate-informed forest governance in Quesnel, British Columbia (poster) Pedersen, D., Hagerman, S. (2023) BC Community Forest Association 2023 Conference and AGM. Langley, BC. June 7-9, 2023 Continuous monitoring and sub-annual change detection in high-latitude forests using Harmonized Landsat Sentinel-2 data Mulverhill, C., Coops, N.C., Achim, A. (2023) ISPRS Journal of Photogrammetry and Remote Sensing. 197: 309-319. https://doi.org/10.1016/j.isprsjprs.2023.02.002. Quantifying the Probability of Decline in Quality: Implications for Selection Management in Northern Hardwood Forests Moreau, G., Cecil-Cockwell, M.J.L., Achim, A. et al. (2023). Forests; 14(2):280. https://doi.org/10.3390/f14020280 Climate Scenarios for Canadian Forests Wotherspoon, A.R., Burnett, M., Bernard, A., Achim, A., Coops, N.C. (2022) Climate Scenarios for Canadian Forests. Silva21, University of British Columbia, Vancouver, Canada Harmonizing multi-temporal airborne laser scanning point clouds to derive periodic annual height increments in temperate mixedwood forests Riofrio, J., White, J.C., Tompalski, P., Coops, N., Wulder, M.A (2022) Canadian Journal of Forest Research, 52(10): 1334-1352. https://doi.org/10.1139/cjfr-2022-0055 La multifonctionnalité du territoire forestier dans tous ses états Bernard, A., Gélinas, N. (2022) In: Une économie écologique pour le Québec: Comment opérationnaliser une nécessaire transition, PUQ. Framework for near real-time forest inventory using multi source remote sensing data Coops, N., Tompalski, P., Goodbody, T.R,H., et al. (2022). Forestry cpac015. https://doi.org/10.1093/forestry/cpac015 The changing culture of silviculture Achim, A., Moreau, G., Coops, N., et al. (2021) Forestry, 95(2):143-152. https://doi.org/10.1093/forestry/cpab047

Acadia Research Forest Acadia is a 91 square kilometres acadian forest hub site located in New Brunswick, nearby and to the east of Fredericton and north of Nova Scotia. To gain access to more raw data, please contact Shane Furze with JD Irving; Shona Millican, Martin Noel, and Chris Hennigar with the Government of Nova Scotia; and Adam Dick with Natural Resources Canada. [Click on any image to magnify] Site Details Climate LiDAR Products Vector Products Forest Monitoring Anchor 1 Site Details Best Available Pixel (2020) Acadia Hub Site Boundary Best Available Pixel (BAP) composites use Landsat scenes to develop cloud-free, surface reflectance pixel-based image composites capable of large-area production. When incorporated in a time series, they generate land cover, land cover change, and forest structural attributes information products in a dynamic, transparent, systematic, repeatable, and spatially exhaustive manner. This figure displays the 2020 BAP composite within the Haliburton hub site in Ontario. The acquisition of all pixels for this BAP composite were within 30 days of the first of August, 2020. Acadia Digital Elevation Model (DEM) at 30 m resolution Acadia Digital Elevation Model (DEM) at 250 m resolution Anchor 2 Climate Projections for change in minimum temperature for the years 2050 and 2090 relative to the reference period (1981-2010) Projections for change in maximum temperature for the years 2050 and 2090 relative to the reference period (1981-2010) Projections for change in seasonal precipitation for the years 2050 and 2090 relative to the reference period (1981-2010) Climate data for historical (1981-2010) and future (2050 and 2090) projections Anchor 3 LiDAR Derived Products Digital Elevation Model (1m) Description - An interpolation of last returns classified as 'ground' points using TIN. Pixel Values - Elevation at a 1 metre resolution. Forestry Application - The Digital Elevation Model is important for topographical information, including slope, aspect, and radiation Slope (1m) Description - Steepness or the degree of incline of a surface based on the DEM model Pixel Values - Raster containing numeric values representing degrees of incline Forestry Application - Slope influences tree stability, harvesting solutions, productivity of harvesting and collection means, architecture of the road networks, road characteristics, and solutions related to the reclamation of degraded forested land. Aspect (1m) Description - Orientation of slope, measured clockwise in radians based on the DEM model Pixel Values - Raster containing a numeric value representing the radians of orientation Forestry Application - Land oriented in northerly are typically wetter and cooler compared to land oriented in southerly Radiation (1m) Description - A technique to visualize a shaded relief, illuminating it with a hypothetical light Pixel Values - Raster containing a numeric value representing the solar-radiation aspect index. Values range from 0 (land oriented in a northern direction resulting in less solar radiation exposure) and 1 (land oriented with southern slopes) Forestry Application - Land oriented in northerly (values closer to zero) are typically wetter and cooler compared to land oriented in southerly (values closer to one) 20th Height Percentile (20m) Description - Height at which 20% of LiDAR returns fall below from 2m above the ground Pixel Values - Height measurement in metres describing the height at which 20% of LiDAR returns fall below Forestry Application - Assists in determining the height and distribution of the lower section of the canopy 95th Height Percentile (20m) Description - Height at which 95% of LiDAR returns fall below from 2m above the ground Pixel Values - Height measurement in metres describing the height at which 95% of LiDAR returns fall below Forestry Application - Assists in determining the height and distribution of the lower section of the canopy Canopy Height Model (1m) Description - Based on an interpolation of the height of the top of trees (using the pitfree algorithm) Pixel Values - Raster containing a numeric value for the distance between the ground and the top of trees Forestry Application - Helpful for determining the distribution of canopy coverage Entropy (20m) Description - Shannon entropy quantifies the diversity and evenness of an elevation distribution of LiDAR points from 2m above the ground Pixel Values - Entropy results range from 0 to 1. Random data has a Shannon entropy value of 1 Forestry Application - Useful for describing and quantifying species diversity in biological systems. Mean Height (20m) Description - Mean height of first returns above 2m from "ground" (last return data) Pixel Values - Mean height of all point cloud returns greater than 2m above last returns Forestry Application - Determines the mean height of all objects (trees) that are at least 2m tall Mean Standard Deviation (20m) Description - Standard Deviation of height distributions above 2m Pixel Values - Standard deviation height of all point cloud returns greater than 2m above last returns Forestry Application - Determines the standard deviation for the height of all objects (trees) that are at least 2m tall Skewness (20m) Description - A measure of the distribution's symmetry from 2m above the ground Pixel Values - A normal distribution would produce skewness results of zero. Negative values indicate that data is skewed to the left, and positive values indicate that data is skewed to the right. Forestry Application - Skewness is often used with kurtosis to separate ground points and object points from a LiDAR point cloud. It has a variety of applications, including optimizing the DEM, segmentation and classification, and road extraction. Kurtosis (20m) Description - The size of the tails of a distribution (likelihood that the distribution will produce outliers) from 2m above the ground Pixel Values - A normal distribution would produce kurtosis results of 3. Distributions with kurtosis less than 3 are platykurtic (fewer and less extreme outliers) and distributions with kurtosis greater than 3 are laptokurtic (produce more outliers) Forestry Application - Kurtosis is often used with skewness to separate ground points and object points from a LiDAR point cloud. It has a variety of applications, including optimizing the DEM, segmentation and classification, and road extraction. Canopy Cover > 2m (20m) Description - Canopy cover at a height greater than 2 metres Pixel Values - Ratio from the sum of first returns > 2 metres divided by the total first returns Forestry Application - Important for determining the area occupied by the vertical projection of tree crowns greater than 2 metres Canopy Cover > 5m (20m) Description - Canopy cover at a height greater than 5 metres Pixel Values - Ratio from the sum of first returns > 5 metres divided by the total first returns Forestry Application - Important for determining the area occupied by the vertical projection of tree crowns greater than 5 metres Canopy Cover > 15m (20m) Description - Canopy cover at a height greater than 15 metres Pixel Values - Ratio from the sum of first returns > 15 metres divided by the total first returns Forestry Application - Important for determining the area occupied by the vertical projection of tree crowns greater than 15 metres LAIe (20m) Description - A measurement of the gap fraction through the probability of beam penetration of sunlight through the vegetation. Pixel Values - Ratio of one-sided green leaf area per unit ground surface area Forestry Application - Important growth index for the status of crop populations Rumple (20m) Description - Crown Surface Roughness from 2m above the ground Pixel Values - A ratio of canopy outer surface area to ground surface area Forestry Application - Higher rumple values indicate more vertical and horizontal heterogeneity Anchor 4 Vector Products

< Retour Continuous forest inventory framework OB 5a Hub: All Year: 2021-2022 Chris Mulverhill, PDF While OB.3 focuses on broader scale strategic monitoring, there is also a need for improved monitoring of key stand forest metrics that drive the silvicultural decision-making process. Key to prescriptions such as thinning, fertilising and final harvesting is accurate tactical, tree and stand level, information such as tree location, height, as well as stand density, composition and health. Forest companies such as JDI require continual update of these conditions to implement agile, adaptive forest management. To support two MSc students in OB.5b and OB.5c a two-year PDF will first have the objective to develop a framework to determine which key stand attributes could be integrated into an continuous monitoring framework, at what level of spatial detail (ideally within a 20m grid) and at what level of accuracy (ideally at the 1ha level). The PDF will first undertake an evaluation of needs in terms of attributes and their desired accuracy, and then make an assessment of the most appropriate remote sensing tools to meet these desired outcomes across a number of HUB sites. Outcome (OB.5a): A continuous forest inventory updating framework using a range of remote sensing data sources for implementation at operational scales at relevant Hub sites. Chris Mulverhill, PDF at University of British Columbia Main Partner: J.D. Irving Ltd. Professor Nicholas Coops Collaborator Alexis Achim Smith-Tripp, S., Coops, N.C., Mulverhill, C., White, J.C., Axelson, J. 2024. Landsat assessment of variable spectral recovery linked to post-fire forest structure in dry sub-boreal forests. ISPRS Journal of Photogrammetry and Remote Sensing, 208:121-135. https://doi.org/10.1016/j.isprsjprs.2024.01.008. Mulverhill, C., Coops, N.C., Achim, A. (2023). Continuous monitoring and sub-annual change detection in high-latitude forests using Harmonized Landsat Sentinel-2 data. ISPRS Journal of Photogrammetry and Remote Sensing, 197: 309-319. https://doi.org/10.1016/j.isprsjprs.2023.02.002 Coops, N., Tompalski, P., Goodbody, T.R,H., et al. (2022). Framework for near real-time forest inventory using multi source remote sensing data. Forestry cpac015. https://doi.org/10.1093/forestry/cpac015 Keay, L., Mulverhill, C., Coops, N.C., McCartney, (2022) Automated Forest Harvest Detection With a Normalized PlanetScope Imagery Time Series. Canadian Journal of Remote Sensing, 1-15; https://doi.org/10.1080/07038992.2022.2154598

< Retour Metrics for silvicultural prescription: composition and structure OB 5b Hub: MRF, LSJ, MM, Estrie (East Focus) Year: 2023-2024 Spencer Shields, MSc Once a robust continuous forest inventory framework has been developed (OB 5a), we will implement the proposed methodologies through two MSc projects at the ARF and BB Hub sites. The MSc will have the objective to apply the framework to update attributes such as species composition and abundance and classes of stand densities. Results will be assessed by their usefulness to drive key silvicultural decision-making. Outcome (OB.5b): Recommendations of a series of metrics that can be derived at a 20 x 20 m resolution to guide silvicultural interventions dependent on stand composition and structure. Spencer Shields, MSc University of British Columbia Main Partner: J.D. Irving Ltd. Professor Nicholas Coops ​

< Retour Deliberative-analytic framework to engage publics and stakeholders AD 5a Hub: Quesnel, BC Year: 2022-2025 Dane Pedersen, PhD Tenure changes and increased disturbance rates in interior BC are resulting in collaborative models of forest management through, for example, community forests with First Nations representation and, in the case of the QN Hub, the establishment of a forestry think tank initiative. As different adaptive forest management solutions are proposed, as well as silvicultural prescriptions examined, continual dialogue is required with forest professionals, community forest members, and QN think tank participants on their wider implications. Working with social scientists, a PhD student will have for objective to build and apply an analytic-deliberative framework to enhance dialogue around emerging forest plans and scenarios, in order to better understand the diversity of community and First Nations perspectives about acceptable solutions. Additional focus groups and interviews will delve further into the basis of inevitably diverse perspectives and preferred governance solutions that exist in BCs publicly-owned forests so as to generate locally-informed, scientifically sound, and institutionally realistic solutions. Outcome (AD.5a): A novel deliberative-analytic framework designed specifically to engage diverse publics and stakeholders, and identify the most acceptable pathways to implement adaptive silvicultural measures. Dane Pedersen, PhD at University of British Columbia Main Partner: FPInnovations Professor: Shannon Hagerman Pedersen, D., Hagerman, S. 2023. Seeing the forest through the trees: Collaborative climate-informed forest governance in Quesnel, British Columbia (poster). BC Community Forest Association 2023 Conference and AGM, Langley, BC. June 7-9, 2023. http://bit.ly/3oPuTN7

Lac St. Jean Research Forest Lac St. Jean is a 20,607 square kilometres boreal forest hub site located in Quebec, north of Quebec City. To gain access to more raw data, please contact Patrice Boucher with the Government of Quebec. [Click on any image to magnify] Site Details Climate LiDAR Products Vector Products Forest Monitoring Anchor 1 Site Details Best Available Pixel (2020) Lac St. Jean Hub Site Boundary Best Available Pixel (BAP) composites use Landsat scenes to develop cloud-free, surface reflectance pixel-based image composites capable of large-area production. When incorporated in a time series, they generate land cover, land cover change, and forest structural attributes information products in a dynamic, transparent, systematic, repeatable, and spatially exhaustive manner. This figure displays the 2020 BAP composite within the Haliburton hub site in Ontario. The acquisition of all pixels for this BAP composite were within 30 days of the first of August, 2020. Lac St. Jean Digital Elevation Model (DEM) at 30 m resolution Lac St. Jean Digital Elevation Model (DEM) at 250 m resolution Anchor 2 Climate Projections for change in minimum temperature for the years 2050 and 2090 relative to the reference period (1981-2010) Projections for change in maximum temperature for the years 2050 and 2090 relative to the reference period (1981-2010) Projections for change in seasonal precipitation for the years 2050 and 2090 relative to the reference period (1981-2010) Climate data for historical (1981-2020) and future (2050 and 2090) projections Anchor 3 LiDAR Derived Products Digital Elevation Model (1m) Description - An interpolation of last returns classified as 'ground' points using TIN. Pixel Values - Elevation at a 1 metre resolution. Forestry Application - The Digital Elevation Model is important for topographical information, including slope, aspect, and radiation Radiation (1m) Description - A technique to visualize a shaded relief, illuminating it with a hypothetical light Pixel Values - Raster containing a numeric value representing the solar-radiation aspect index. Values range from 0 (land oriented in a northern direction resulting in less solar radiation exposure) and 1 (land oriented with southern slopes) Forestry Application - Land oriented in northerly (values closer to zero) are typically wetter and cooler compared to land oriented in southerly (values closer to one) Slope (1m) Description - Steepness or the degree of incline of a surface based on the DEM model Pixel Values - Raster containing numeric values representing degrees of incline Forestry Application - Slope influences tree stability, harvesting solutions, productivity of harvesting and collection means, architecture of the road networks, road characteristics, and solutions related to the reclamation of degraded forested land. 20th Height Percentile (20m) Description - Height at which 20% of LiDAR returns fall below from 2m above the ground Pixel Values - Height measurement in metres describing the height at which 20% of LiDAR returns fall below Forestry Application - Assists in determining the height and distribution of the lower section of the canopy Aspect (1m) Description - Orientation of slope, measured clockwise in radians based on the DEM model Pixel Values - Raster containing a numeric value representing the radians of orientation Forestry Application - Land oriented in northerly are typically wetter and cooler compared to land oriented in southerly 95th Height Percentile (20m) Description - Height at which 95% of LiDAR returns fall below from 2m above the ground Pixel Values - Height measurement in metres describing the height at which 95% of LiDAR returns fall below Forestry Application - Assists in determining the height and distribution of the lower section of the canopy Canopy Height Model (1m) Description - Based on an interpolation of the height of the top of trees (using the pitfree algorithm) Pixel Values - Raster containing a numeric value for the distance between the ground and the top of trees Forestry Application - Helpful for determining the distribution of canopy coverage Entropy (20m) Description - Shannon entropy quantifies the diversity and evenness of an elevation distribution of LiDAR points from 2m above the ground Pixel Values - Entropy results range from 0 to 1. Random data has a Shannon entropy value of 1 Forestry Application - Useful for describing and quantifying species diversity in biological systems. Canopy Cover > 2m (20m) Description - Canopy cover at a height greater than 2 metres Pixel Values - Ratio from the sum of first returns > 2 metres divided by the total first returns Forestry Application - Important for determining the area occupied by the vertical projection of tree crowns greater than 2 metres LAIe (20m) Description - A measurement of the gap fraction through the probability of beam penetration of sunlight through the vegetation. Pixel Values - Ratio of one-sided green leaf area per unit ground surface area Forestry Application - Important growth index for the status of crop populations Mean Height (20m) Description - Mean height of first returns above 2m from "ground" (last return data) Pixel Values - Mean height of all point cloud returns greater than 2m above last returns Forestry Application - Determines the mean height of all objects (trees) that are at least 2m tall Mean Standard Deviation (20m) Description - Standard Deviation of height distributions above 2m Pixel Values - Standard deviation height of all point cloud returns greater than 2m above last returns Forestry Application - Determines the standard deviation for the height of all objects (trees) that are at least 2m tall Skewness (20m) Description - A measure of the distribution's symmetry from 2m above the ground Pixel Values - A normal distribution would produce skewness results of zero. Negative values indicate that data is skewed to the left, and positive values indicate that data is skewed to the right. Forestry Application - Skewness is often used with kurtosis to separate ground points and object points from a LiDAR point cloud. It has a variety of applications, including optimizing the DEM, segmentation and classification, and road extraction. Canopy Cover > 5m (20m) Description - Canopy cover at a height greater than 5 metres Pixel Values - Ratio from the sum of first returns > 5 metres divided by the total first returns Forestry Application - Important for determining the area occupied by the vertical projection of tree crowns greater than 5 metres Kurtosis (20m) Description - The size of the tails of a distribution (likelihood that the distribution will produce outliers) from 2m above the ground Pixel Values - A normal distribution would produce kurtosis results of 3. Distributions with kurtosis less than 3 are platykurtic (fewer and less extreme outliers) and distributions with kurtosis greater than 3 are laptokurtic (produce more outliers) Forestry Application - Kurtosis is often used with skewness to separate ground points and object points from a LiDAR point cloud. It has a variety of applications, including optimizing the DEM, segmentation and classification, and road extraction. Canopy Cover > 15m (20m) Description - Canopy cover at a height greater than 15 metres Pixel Values - Ratio from the sum of first returns > 15 metres divided by the total first returns Forestry Application - Important for determining the area occupied by the vertical projection of tree crowns greater than 15 metres Rumple (20m) Description - Crown Surface Roughness from 2m above the ground Pixel Values - A ratio of canopy outer surface area to ground surface area Forestry Application - Higher rumple values indicate more vertical and horizontal heterogeneity Anchor 4 Vector Products

< Retour Optimization of the characterization of burning patterns OB 1b Hub: Lac-St-Jean, QC Year: 2021-2022 Gabrielle Thibault, MSc Despite being less frequent in the East, fires remain the main cause of natural disturbances in the boreal forests of Quebec (QC) and Ontario (ON) and regeneration success is highly variable in forests dominated by black spruce. An MSc student will collaborate with the PhD student (OB.1a) and adapt the workflow to the LSJ and RM boreal Hubs. Using metrics of natural stand establishment that characterize failures or successes, the objective will be to improve our understanding the ecological factors that lead to black spruce regeneration after fire disturbance. Outcome (OB.1b): Identification of key stand- and landscape-level characteristics that favour regeneration success and improve forest resilience. Gabrielle Thibault, MSc at Université Laval Main Partner: Ministère des Forêts, de la Faune et des Parcs (Québec) Professor Alexis Achim ​

< Retour Seasonal mosaics of forest cover OB 3a Hub: All Year: 2021-2023 Micheal Burnett, RA There is a critical need for accurate and timely monitoring for near real time forest condition assessment. The increasing availability of moderate and high-resolution imagery, with daily or weekly repeat, is enabling the regular characterization of entire forest areas. Micheal Burnett will apply and adapt approaches to image fusion and compositing to Sentinel-2, Landsat and Planet multispectral data to produce seasonal composites over large forest areas. Outcome (OB.3a): For each Hub site, an operational coding framework on how to derive seasonal mosaics of forest cover and condition and implement a change detection approach. Micheal Burnett, RA at University of British Columbia Main Partner: Kruger Inc. Professor Nicholas Coops Collaborator Alexis Achim ​

< Retour Silvicultural practices at the pace of global changes: a public policy challenge AD 8a Hub: All Year: 2022-2023 Anne Bernard, PDF In the face of global changes, the scientific community is actively developing solutions to respond to the pressures on forest ecosystems and, more broadly, on territories. In order to be implemented, the innovative silvicultural practices that result from these research initiatives will have to integrate the various legislative frameworks that govern forestry practices. In Canada, this involves the provincial and federal levels. In this research project, we will attempt to answer the following question: How can new forestry practices be linked to global changes? More specifically, the research objective is to understand the regulatory and social context of forestry practices in Canada. To achieve this, an analysis of public policies in six provinces will be conducted. We will also look at the influence of international organizations on national and regional forest policies. This research is part of the Silva21 partnership, which includes 11 study areas in six provinces (British Columbia, Ontario, Quebec, New Brunswick, Nova Scotia and Newfoundland-Labrador). For these areas, we will develop different socio-economic portraits for each forest case study. The methodologies envisioned to meet the project's objectives are part of public policy analysis. The expected results will take various forms. First, it is expected to produce scientific articles for Canadian forestry professionals (approximately one per province or per region: West, Ontario-Quebec and Maritimes). The case studies will document local realities for use by all Silva 21 members to present the social and political context of the study areas. Finally, one or two scientific articles will be developed for the scientific community specialized in public policy and/or forest governance. Anne Bernard, PDF at Université Laval Main Partner: Ministère des Forêts, de la Faune et des Parcs (Québec) Professor Alexis Achim Collaborator Maude Flamand-Hubert Canuel, C-M., Bernard, A., Thiffault, N., et al. (2022). Analysis of a wood production strategy from expert perspectives. The Forestry Chronicle, 98(1): 1-9. https://pubs.cif-ifc.org/doi/pdf/10.5558/tfc2022-004 Bernard, A., Gélinas, N. (2022) La multifonctionnalité du territoire forestier dans tous ses états. In: Une économie écologique pour le Québec: Comment opérationnaliser une nécessaire transition, PUQ.

< Retour Identifying and assessing the impact of non-stand-replacing disturbances within a near- real-time context OB 5c Hub: Quesnel Year: 2023-2024 Madison Brown, M.Sc. Once a robust continuous forest inventory framework has been developed (OB 5a), we will implement the proposed methodologies through two MSc projects at the Quesnel hub site. This third MSc student will have the objective to apply the framework and develop tools to assess forest stand stresses, such as infestation, wind damage or disease. The MSc student will use a series of indicators of forest health derived at the 20 x 20 m resolution and assess which predicted metrics are sufficiently reliable to be considered into silvicultural prescriptions for a range of stand ages and composition. Outcome (OB.5c): Recommendations of a series of metrics that can be derived at a 30 x 30 m resolution to guide silvicultural interventions dependent on stand condition. Madison Brown, MSc at University of British Columbia Main Partner: Department of Energy and Resource Development (New Brunswick) Professor Nicholas Coops ​