Fall 2023 updates: Silvicultural strategies from climate resilience
- Amy Wotherspoon
- 9 oct. 2023
- 1 min de lecture
Dernière mise à jour : 16 oct. 2023
As summer 2023 field season came to a close, the Silva21 community got together for another round of update meetings to catch up on project updates, latest results and ask burning questions.
This time our meetings were divided into four themes:
Silvicultural strategies for climate resilience
Disturbance and resistant-focused adaptation
Innovative technologies and data-driven adaptation
Community engagement, collaboration and policy
HQPs were divided into different themes to provide updates on their projects, share current results, discuss the implications for adaptive silviculture and ask the Silva21 community questions. In each theme, we had a member from government or industry also present an update as well as discuss implications and ask questions to the community.
On Tuesday, October 10th the Silva21 community discussed silvicultural strategies for climate resilience, hearing from seven research projects and a partner from the Ontario Ministry of Natural Resources and Forestry. Click the research title and name below to read their update.
Fine-scale structural characterization of non-stand replacing (NSR) disturbances using bitemporal aerial laser scanning (ALS) data- Tommaso Trotto, PhD candidate, UBC
Natural disturbances have a significant impact on forest structure at varying spatial and temporal scales. Forests may experience abrupt changes caused by stand-replacing disturbances like severe wildfires or more subtle and pervasive modifications due to non-stand replacing (NSR) disturbances. NSR disturbances, such as moderate insect defoliations, may affect various aspects of forest structure, including crown height, shape and cover, spatial arrangement of tree patches, and growth dynamics. The complex response of forest structure to NSR disturbances poses challenges for developing approaches that can accurately capture temporal and spatial changes for informed forest management. However, the application of active remote sensing tools, such as aerial laser scanner (ALS), may offer valuable insights into forest structural changes resulting from NSR disturbances when repeated acquisitions are available.
This study aims to investigate forest structural changes at a fine scale using a bitemporal ALS dataset acquired in the southern portion of the Lac St-Jean region, Quebec, Canada in 2014 and 2020. Change detection on ALS data was performed via a raster differencing approach, which is widely adopted for change detection tasks given its robustness in handling data acquisition inconsistencies, such as varying ALS system specifications. This approach involves regularizing 3-dimensional ALS information onto a 2-dimensional grid.
The raster differencing was conducted on a set of 14 uncorrelated ALS-derived metrics, which were rasterized to 10 m for both ALS acquisitions and subtracted over time (t2 – t1, hereafter delta metrics). Metric selection included height metrics, canopy cover, light interception metrics (e.g., leaf area index), and shape metrics derived from covariance matrix eigendecomposition. To identify regions of pixels exhibiting similar response patterns to NSR disturbances (i.e. ecological regions), a two-stage clustering approach was applied to the delta metrics. This approach involved an initial kmeans pass, followed by multivariate agglomerative clustering, resulting in the identification of 8 ecological regions. The clusters were further assessed in terms of their ecological impact on crown decoloration, defoliation, and gaps through photointerpretation of 2 aerial imagery in 2012 and 2020. Lastly, a Random Forest model was fit on the delta metrics to identify the best ALS-derived structural attributes at separating the clusters, which we deemed sensitive to detecting NSR disturbances.
We observed increasing decoloration and defoliation levels as disturbance severity increased, which was associated with a decrease in lower height percentiles, canopy cover, and LAI. Eigendecomposition metrics also showed a consistent response as disturbance severity increased, with a greater vertical variance spread at moderate disturbance severity levels, possibly indicating a greater stand vertical structural complexity. In conclusion, we detected the occurrence of NSR disturbances based on the delta metrics with an overall accuracy of 67.5% across the region.
This study revealed the importance of considering cover and height metrics for the detection of NSR disturbances in the region, derived from the Random Forest model. Furthermore, it provided the foundation for the detection and characterization of NSR disturbances in a boreal forest context, leveraging the availability of bitemporal ALS data. This research aimed to support the use of ALSderived structural metrics for the detection, characterization, and implications of NSR disturbances on forest structure for ecosystem-based management.
Tommaso Trotto
PhD Candidate
University of British Columbia
Supervisor: Nicholas Coops
tommaso.trotto@ubc.ca
Can thinning mitigate the impact of natural disturbance? - Catherine Chagnon, RA, Laval
Thinning is one of the most common silvicultural treatments used worldwide. By reducing the overall stand density, thinning induces a redistribution on the site resources among the residual trees. Doing so, it represents an opportunity to increase the growth of the residual trees, which in turn generally leads to stands that are more resilient and resistant to natural disturbances. Following previous work by Moreau et al. 2022 that summarized the recent literature on the influence of thinning on stands response to environmental stressors, we aim to quantify the impact of thinning of forest response (as described by stand survival, growth, and resistance) following fires, droughts, windstorms, and insects and pathogens outbreaks using a meta-analysis. We will also evaluate the effect of thinning intensity, type of treatment, and number of treatments on the forest response. Doing so, we aim to identify the situations in which thinning be used as an efficient tool to mitigate risk and damage to disturbances, and to identify the best way to implement the treatment. To date, we reviewed 1022 papers identified as potential data source from our research queries and identified 43 papers to be used in our meta-analysis. From these, we have extracted 186 case studies, and we will be ready to start the data analysis shortly.
Catherine Chagnon
Research Associate
Université Laval
Supervisor: Alexis Achim
Tree growth response to current climate change in Ontario - Emmanuelle Baby-Bouchard, RA, ULaval
This project aims to understand Ontario’s boreal forest growth dynamics in the face of climate change. With the extensive warming we’ve been experiencing in the last decades, different trends in black spruce growth have been observed across the country. These variations appear to be explained the different precipitation regimes, as greater precipitation favors increased growth in the East and lower precipitation are associated with growth declines in the West. However, recent work suggests that the beneficial effect of warming on black spruce growth observed in Eastern Canada is transitory, and further warming is likely to rapidly lead to water-limitation and decrease black spruce growth across the whole country. As we all know, black spruce response to climate has been extensively studied, but what about co-occurring species?
I will use a large dataset of tree cores obtained from the Ontario Growth & Yield Program that I will measure and date. The cores originate from plots of unmanaged stands of different composition situated all around the province and we have 8 different species. Out of the 2700 cores we received, about 500 have been measured so far. Using the basal area increment chronologies, I will try to assess which species react positively to current climate change. Knowing which species will be favored by climate change will enable foresters to make better informed decisions for sustainable and adapted forest management to different climate scenarios.
Emmanuelle Baby-Bouchard
Research Associate
Université Laval
Supervisor: Alexis Achim
emmanuelle.baby-bouchard.1@ulaval.ca
Climate sensitivity mortality modeling of Québec Tree Species - Christina Howard, PhD student, UBC
Christina’s main objective is to contribute to a climate sensitive growth model for Quebec tree species. Specifically, she is focused on modelling those species’ mortality rates.
Currently, she is finalizing candidate mortality models for each species, which includes making changes to or adding transformations of some plot-level variables. She is also re-fitting models based on the availability of new permanent sample plot data. This also required updating disturbance data, including insect, fire, ice, and windthrow data.
Evaluating any forest management strategies requires having reliable climate-sensitive forecasts of tree growth. Therefore, in terms of implications for adaptive silviculture, Christina’s research will be important to evaluate different management strategies into the future, as well as evaluate different climate change mitigation strategies in the forest sector.
Christina Howard
PhD candidate
University of British Columbia
Supervisor: Bianca Eskelson
christina.howard@alumni.ubc.ca
Integrations of climate drivers into tree-list growth modeling in the Acadian forest region - Jamie Ring, MSc student, UBC
To support climate-sensitive growth and yield modelling in the Acadian Forest Region, an evaluation of two existing tree-list growth and yield models developed for use in the Acadian Forest Region are being evaluated, using Nova Scotia’s Permanent Sample Plot (PSP) data. The results from this evaluation will then be used to inform what model components are a priority (diameter increment, height increment, mortality, ingrowth) for incorporating climate sensitivity. Nova Scotia has a PSP dataset with approximately 3,000 individual plots that have been remeasured a combined 19,000 times, with nearly 1,000,000 individual tree observations. The simulations using Open Stand Model (OSM) are completed, and simulations using Forest Vegetation Simulator (FVS) – Acadian Variant are underway. Once a climate-sensitive model component is developed, it will be compatible with the existing framework of these growth and yield models, to assist in long-term forecasting of forest growth and yield under various climate scenarios.
Jamie Ring
MSc student
University of British Columbia
Supervisor: Bianca Eskelson
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Forgot the password? Email amy.wotherspoon@ubc.ca.
Our next update meetings will take place in Spring 2024! Stay tuned with all news Silva21 by subscribing to our newsletter at the bottom of this page.