Chasmer, Laura

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    Aboveground biomass allocation of boreal shrubs and short-stature trees in northwestern Canada
    (MDPI, 2021) Flade, Linda; Hopkinson, Christopher; Chasmer, Laura
    In this follow-on study on aboveground biomass of shrubs and short-stature trees, we provide plant component aboveground biomass (herein ‘AGB’) as well as plant component AGB allometric models for five common boreal shrub and four common boreal short-stature tree genera/species. The analyzed plant components consist of stem, branch, and leaf organs. We found similar ratios of component biomass to total AGB for stems, branches, and leaves amongst shrubs and deciduous tree genera/species across the southern Northwest Territories, while the evergreen Picea genus differed in the biomass allocation to aboveground plant organs compared to the deciduous genera/species. Shrub component AGB allometric models were derived using the three-dimensional variable volume as predictor, determined as the sum of line-intercept cover, upper foliage width, and maximum height above ground. Tree component AGB was modeled using the cross-sectional area of the stem diameter as predictor variable, measured at 0.30 m along the stem length. For shrub component AGB, we achieved better model fits for stem biomass (60.33 g ≤ RMSE ≤ 163.59 g; 0.651 ≤ R2 ≤ 0.885) compared to leaf biomass (12.62 g ≤ RMSE ≤ 35.04 g; 0.380 ≤ R2 ≤ 0.735), as has been reported by others. For short-stature trees, leaf biomass predictions resulted in similar model fits (18.21 g ≤ RMSE ≤ 70.0 g; 0.702 ≤ R2 ≤ 0.882) compared to branch biomass (6.88 g ≤ RMSE ≤ 45.08 g; 0.736 ≤ R2 ≤ 0.923) and only slightly better model fits for stem biomass (30.87 g ≤ RMSE ≤ 11.72 g; 0.887 ≤ R2 ≤ 0.960), which suggests that leaf AGB of short-stature trees (<4.5 m) can be more accurately predicted using cross-sectional area as opposed to diameter at breast height for tall-stature trees. Our multi-species shrub and short-stature tree allometric models showed promising results for predicting plant component AGB, which can be utilized for remote sensing applications where plant functional types cannot always be distinguished. This study provides critical information on plant AGB allocation as well as component AGB modeling, required for understanding boreal AGB and aboveground carbon pools within the dynamic and rapidly changing Taiga Plains and Taiga Shield ecozones. In addition, the structural information and component AGB equations are important for integrating shrubs and short-stature tree AGB into carbon accounting strategies in order to improve our understanding of the rapidly changing boreal ecosystem function.
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    Allometric equations for shrubs and short-stature tree aboveground biomass within boreal ecosystems of northwestern Canada
    (MDPI, 2020) Flade, Linda; Hopkinson, Christopher; Chasmer, Laura
    Aboveground biomass (AGB) of short-stature shrubs and trees contain a substantial part of the total carbon pool within boreal ecosystems. These ecosystems, however, are changing rapidly due to climate-mediated atmospheric changes, with overall observed decline in woody plant AGB in boreal northwestern Canada. Allometric equations provide a means to quantify woody plant AGB and are useful to understand aboveground carbon stocks as well as changes through time in unmanaged boreal ecosystems. In this paper, we provide allometric equations, regression coefficients, and error statistics to quantify total AGB of shrubs and short-stature trees. We provide species- and genus-specific as well as multispecies allometric models for shrub and tree species commonly found in northwestern boreal forest and peatland ecosystems. We found that the three-dimensional field variable (volume) provided the most accurate prediction of shrub multispecies AGB (R2 = 0.79, p < 0.001), as opposed to the commonly used one-dimensional variable (basal diameter) measured on the longest and thickest stem (R2 = 0.23, p < 0.001). Short-stature tree AGB was most accurately predicted by stem diameter measured at 0.3 m along the stem length (R2 = 0.99, p < 0.001) rather than stem length (R2 = 0.29, p < 0.001). Via the two-dimensional variable cross-sectional area, small-stature shrub AGB was combined with small-stature tree AGB within one single allometric model (R2 = 0.78, p < 0.001). The AGB models provided in this paper will improve our understanding of shrub and tree AGB within rapidly changing boreal environments.
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    Delineating and reconstructing 3D forest fuel components and volumes with terrestrial laser scanning
    (MDPI, 2023) Xi, Zhouxin; Chasmer, Laura; Hopkinson, Christopher
    Predictive accuracy in wildland fire behavior is contingent on a thorough understanding of the 3D fuel distribution. However, this task is complicated by the complex nature of fuel forms and the associated constraints in sampling and quantification. In this study, twelve terrestrial laser scanning (TLS) plot scans were sampled within the mountain pine beetle-impacted forests of Jasper National Park, Canada. The TLS point clouds were delineated into eight classes, namely individual-tree stems, branches, foliage, downed woody logs, sapling stems, below-canopy branches, grass layer, and ground-surface points using a transformer-based deep learning classifier. The fine-scale 3D architecture of trees and branches was reconstructed using a quantitative structural model (QSM) based on the multi-class components from the previous step, with volume attributes extracted and analyzed at the branch, tree, and plot levels. The classification accuracy was evaluated by partially validating the results through field measurements of tree height, diameter-at-breast height (DBH), and live crown base height (LCBH). The extraction and reconstruction of 3D wood components enable advanced fuel characterization with high heterogeneity. The existence of ladder trees was found to increase the vertical overlap of volumes between tree branches and below-canopy branches from 8.4% to 10.8%.
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    Ecological impacts of shortening fire return intervals on boreal peatlands and transition zones using integrated in situ field sampling and lidar approaches
    (Wiley, 2022) Jones, Emily; Chasmer, Laura; Devito, Kevin; Rood, Stewart; Hopkinson, Christopher
    Aridity associated with rising air temperatures in northern latitudes is expected to contribute to increased frequency of wildland fires. Here, we examined regenerating vegetation following short return interval (SRI) fire (56 years post-fire) compared to long return interval (LRI) fire (>80 years post-fire) in boreal peatlands and their adjacent transitional areas. The objectives of this study were to quantify if differences exist between (1) peatland and transitional soil characteristics in LRI versus SRI areas and (2) regenerating vegetation species, structural characteristics and diversity. We also determined if patterns of vegetation structural characteristics observed using field data also occur across the broader landscape using airborne lidar data. The Utikuma Region Study Area (URSA) is located in central Alberta, Canada. Here, 19 peatlands were sampled, coincident with an airborne lidar survey of the broader region, where 120 peatlands in short and long fire return intervals were identified. We found that SRI transitional areas had significantly deeper organic soil deposits than those found in LRI (p < 0.0001). Proportions of regenerating species differed significantly between peatlands and transitional areas in SRI versus LRI, where greater proportion of coniferous species were observed in LRI. Deciduous transitional–upland species and taller post-fire vegetation heights were more commonly found SRI peatlands compared with LRI. This suggest that fires with SRIs in this region may result in enhanced deciduous succession, which may transition boreal peatlands into ecosystems that have some characteristics of transitional and upland forests.
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    Educating the next generation of remote sensing specialists: skills and industry needs in a changing world
    (Taylor & Francis, 2021) Chasmer, Laura; Ryerson, Robert A.; Coburn, Craig A.
    The landscape of post-secondary education has experienced a dramatic change in student outcomes over the past 20 years. The expectation for students in advanced education was a career in research and toward gaining employment in either academia or in government science. From our survey of university students and early career professionals, it was clear that there is an expectation gap between desired and probable post-secondary education outcomes. Our survey indicated that the majority of trainees, regardless of level of education, undervalue the importance of written and oral communication skills and overvalue specific methodological understanding relative to those employed in the field. While some of these dichotomies can be explained by the relative lack of experience of students, it also points to the nature of the foci of our training. While we are concerned with the production of the next leaders in remote sensing science, most will have careers that are different from their training. There is an opportunity to optimize the post-secondary education experience (student and faculty) with the inclusion of a broader view toward career outcomes.
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    Examining drivers of post-fire seismic line ecotone regeneration in a boreal peatland environment
    (MDPI, 2023) Enayetullah, Humaira; Chasmer, Laura; Hopkinson, Christopher; Thompson, Daniel; Cobbaert, Danielle
    Seismic lines are the dominant anthropogenic disturbance in the boreal forest of the Canadian province of Alberta, fragmenting over 1900 km2 of peatland areas and accounting for more than 80% of all anthropogenic disturbance in this region. The goal of this study is to determine whether the wildland fires that burn across seismic lines in peatlands result in the regeneration of woody vegetation within the ecotonal areas adjacent to seismic lines. We use a combination of seismic line and vegetation structural characteristics derived from multi-spectral airborne lidar across a post-fire peatland chronosequence. We found an increasing encroachment of shrubs and trees into seismic lines after many years since a fire, especially in fens, relative to unburned peatlands. Fens typically had shorter woody vegetation regeneration (average = 3.3 m ± 0.9 m, standard deviation) adjacent to seismic lines compared to bogs (average = 3.8 m ± 1.0 m, standard deviation), despite enhanced shrubification closer to seismic lines. The incoming solar radiation and seismic line age since the establishment of seismic line(s) were the factors most strongly correlated with enhanced shrubification, suggesting that the increased light and time since a disturbance are driving these vegetation changes. Shrub encroachment closer to seismic lines tends to occur within fens, indicating that these may be more sensitive to drying conditions and vegetation regeneration after several years post-fire/post-seismic line disturbance.
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    Filtering stems and branches from terrestrial laser scanning point clouds using deep 3-D fully convolutional networks
    (MDPI, 2018) Xi, Zhouxin; Hopkinson, Christopher; Chasmer, Laura
    Terrestrial laser scanning (TLS) can produce precise and detailed point clouds of forest environment, thus enabling quantitative structure modeling (QSM) for accurate tree morphology and wood volume allocation. Applying QSM to plot-scale wood delineation is highly dependent on wood visibility from forest scans. A common problem is to filter wood point from noisy leafy points in the crowns and understory. This study proposed a deep 3-D fully convolution network (FCN) to filter both stem and branch points from complex plot scans. To train the 3-D FCN, reference stem and branch points were delineated semi-automatically for 14 sampled areas and three common species. Among seven testing areas, agreements between reference and model prediction, measured by intersection over union (IoU) and overall accuracy (OA), were 0.89 (stem IoU), 0.54 (branch IoU), 0.79 (mean IoU), and 0.94 (OA). Wood filtering results were further incorporated to a plot-scale QSM to extract individual tree forms, isolated wood, and understory wood from three plot scans with visual assessment. The wood filtering experiment provides evidence that deep learning is a powerful tool in 3-D point cloud processing and parsing.
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    Forest stand complexity controls ecosystem-scale evapotranspiration dynamics: Implications for landscape flux simulations
    (Wiley, 2022) Leonard, Rhoswen; Moore, Paul; Krause, Stefan; Chasmer, Laura; Devito, Kevin J.; Petrone, Richard M.; Mendoza, Carl; Waddington, James M.; Kettridge, Nicholas
    Open-canopy forested systems are found across a range of terrestrial biomes. Forest structure and organization in open-canopy systems exhibit substantial controls on system process dynamics such as evapotranspiration (ET). The energy reaching sub-canopy forest layers is greater in open-canopy systems compared to closed canopy systems, with high spatiotemporal variability in the distribution of energy that both drives ET and controls sub canopy species composition and organization. Yet the impact of their structural complexity and organization on whole system ET dynamics is poorly understood. Using the BETA+ model and measured eddy covariance-based ET fluxes from a boreal treed peatland, we critically evaluate how stand compositional and organizational complexity influences ET dynamics. Model simulations iteratively increase complexity from a simple ‘big-leaf’ model to a model representing spatial complexity of all system layers, demonstrating the effect of each complex system component on stand ET dynamics. We show that including forest stand complexity and associated canopy and radiation variability increases ET model estimates by ~26%. In addition to changes in the ET estimates, the inclusion of this spatial complexity is shown to induce temporal variations in the simulated ET that improves model performance by reducing unexplained variance between modelled and measured ET by 10% and reducing hysteresis in model results. These results have clear implications for flux modelling of forest systems and for larger scale climate models where open canopy systems such as this dominate the landscape. Demonstrating that whilst big leaf simulation can approximate ET fluxes, the inclusion of forest-stand complexity and its influence on spatiotemporal radiation fluxes and ecohydrological processes are necessary to effectively represent ET dynamics within open canopies.
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    Identifying conifer tree vs. deciduous shrub and tree regeneration trajectories in a space-for-time boreal peatland fire chronosequence using multispectral lidar
    (MDPI, 2022) Enayetullah, Humaira; Chasmer, Laura; Hopkinson, Christopher; Thompson, Dan; Cobbaert, Danielle
    Wildland fires and anthropogenic disturbances can cause changes in vegetation species composition and structure in boreal peatlands. These could potentially alter regeneration trajectories following severe fire or through cumulative impacts of climate-mediated drying, fire, and/or anthropogenic disturbance. We used lidar-derived point cloud metrics, and site-specific locational attributes to assess trajectories of post-disturbance vegetation regeneration in boreal peatlands south of Fort McMurray, Alberta, Canada using a space-for-time-chronosequence. The objectives were to (a) develop methods to identify conifer trees vs. deciduous shrubs and trees using multi-spectral lidar data, (b) quantify the proportional coverage of shrubs and trees to determine environmental conditions driving shrub regeneration, and (c) determine the spatial variations in shrub and tree heights as an indicator of cumulative growth since the fire. The results show that the use of lidar-derived structural metrics predicted areas of deciduous shrub establishment (92% accuracy) and classification of deciduous and conifer trees (71% accuracy). Burned bogs and fens were more prone to shrub regeneration up to and including 38 years after the fire. The transition from deciduous to conifer trees occurred approximately 30 years post-fire. These results improve the understanding of environmental conditions that are sensitive to disturbance and impacts of disturbance on northern peatlands within a changing climate.
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    Mapping and understanding the vulnerability of northern peatlands to permafrost thaw at scales relevant to community adaptation planning
    (IOP Science Publishing, 2021) Gibson, C.; Cottenie, K.; Gingras-Hill, T.; Kokelj, S. V.; Baltzer, J. L.; Chasmer, Laura; Turetsky, M. R.
    Developing spatially explicit permafrost datasets and climate assessments at scales relevant to northern communities is increasingly important as land users and decision makers incorporate changing permafrost conditions in community and adaptation planning. This need is particularly strong within the discontinuous permafrost zone of the Northwest Territories (NWT) Canada where permafrost peatlands are undergoing rapid thaw due to a warming climate. Current data products for predicting landscapes at risk of thaw are generally built at circumpolar scales and do not lend themselves well to fine-scale regional interpretations. Here, we present a new permafrost vulnerability dataset that assesses the degree of permafrost thaw within peatlands across a 750 km latitudinal gradient in the NWT. This updated dataset provides spatially explicit estimates of where peatland thermokarst potential exists, thus making it much more suitable for local, regional or community usage. Within southern peatland complexes, we show that permafrost thaw affects up to 70% of the peatland area and that thaw is strongly mediated by both latitude and elevation, with widespread thaw occuring particularly at low elevations. At the northern end of our latitudinal gradient, peatland permafrost remains climate-protected with relatively little thaw. Collectively these results demonstrate the importance of scale in permafrost analyses and mapping if research is to support northern communities and decision makers in a changing climate. This study offers a more scale-appropriate approach to support community adaptative planning under scenarios of continued warming and widespread permafrost thaw.
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    Multi-decadal floodplain classification and trend analysis in the Upper Columbia River valley, British Columbia
    (Copernicus Publications, 2024) Rodrigues, Italo Sampaio; Hopkinson, Christopher; Chasmer, Laura; MacDonald, Ryan J.; Bayley, Suzanne E.; Brisco, Brian
    Floodplain wetland ecosystems experience significant seasonal water fluctuation over the year, resulting in a dynamic hydroperiod, with a range of vegetation community responses. This paper assesses trends and changes in land cover and hydroclimatological variables, including air temperature, river discharge, and water level in the Upper Columbia River Wetlands (UCRW), British Columbia, Canada. A land cover classification time series from 1984 to 2022 was generated from the Landsat image archive using a random forest algorithm. Peak river flow timing, duration, and anomalies were examined to evaluate temporal coincidence with observed land cover trends. The land cover classifier used to segment changes in wetland area and open water performed well (kappa of 0.82). Over the last 4 decades, observed river discharge and air temperature have increased, precipitation has decreased, the timing of peak flow is earlier, and the flow duration has been reduced. The frequency of both high-discharge events and dry years have increased, indicating a shift towards more extreme floodplain flow behavior. These hydrometeorological changes are associated with a shift in the timing of snowmelt, from April to mid-May, and with seasonal changes in the vegetative communities over the 39-year period. Thus, woody shrubs (+6 % to +12 %) have expanded as they gradually replaced marsh and wet-meadow land covers with a reduction in open-water area. This suggests that increasing temperatures have already impacted the regional hydrology, wetland hydroperiod, and floodplain land cover in the Upper Columbia River valley. Overall, there is substantial variation in seasonal and annual land cover, reflecting the dynamic nature of floodplain wetlands, but the results show that the wetlands are drying out with increasing areas of woody/shrub habitat and loss of aquatic habitat. The results suggest that floodplain wetlands, particularly marsh and open-water habitats, are vulnerable to climatic and hydrological changes that could further reduce their areal extent in the future.
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    Partitioning carbon losses from fire combustion in a montane valley, Alberta Canada
    (Elsevier, 2021) Gerrand, S.; Aspinall, Jesse; Jensen, T.; Hopkinson, Christopher; Collingwood, A.; Chasmer, Laura
    Direct carbon (C) emissions from wildland fires have been difficult to quantify, especially in montane environments where sites are difficult to access. Here we examined pre-fire C partitioning and losses in a southern Canadian montane valley ecosystem, in Waterton Lakes National Park, Alberta Canada. The objectives of this study were to: (a) quantify the C loss due to combustion at a moist riparian site compared with a dry undulating upland site and (b) compare C loss observations to an active multi-spectral lidar remote sensing index. C losses from wildfire were consistently greater at the wet riparian site compared with the dry valley site. Average soil C losses were 92.92 Mg C ha −1 (st. dev. ± 48.60 Mg C ha −1) and 58.05 Mg C ha −1 (st. dev. ± 37.19 Mg C ha −1). Average tree C losses were 114.0 Mg C ha −1 (std.dev. ± 9.9 Mg C ha −1) and 86.9 Mg C ha −1 (std.dev. ± 13.5 Mg C ha −1) respectively. C losses from trees were greater than soils, where trees lost 55% (moist riparian ecosystem) and about 60% (drier valley site) of C during combustion. Using post-fire multi-spectral airborne lidar data, we found that increased proportion of charred soils were significantly related to enhanced reflectivity in SWIR, resulted in more negative active normalised burn ratio (aNBR) results, indicating enhanced burn severity. Increased proportional cover of regenerating vegetation resulted in less negative aNBR both at the drier site, though no significant relationships between aNBR and charred vs. vegetated results were observed at the moist riparian site. No significant relationship was observed between depth of burn/soil C loss and aNBR derived from lidar data, indicating potential limitations when using burn indices for below canopy burn severity. The use of multi-spectral lidar may improve understanding of below canopy fire fuels and C losses in optical imagery, which often occludes these important components of fire ecology. The results of this research improve understanding of C losses associated with wildland fire in montane ecosystems that have undergone fire suppression and management by Euro-American colonizers for over 100 years.
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    Peatland-fire interactions: a review of wildland fire feedbacks and interactions in Canadian boreal peatlands
    (Elsevier, 2021) Nelson, Kailyn; Thompson, Dan; Hopkinson, Christopher; Petrone, R.; Chasmer, Laura
    Boreal peatlands store a disproportionately large quantity of soil carbon (C) and play a critical role within the global C-climate system; however, with climatic warming, these C stores are at risk. Increased wildfire frequency and severity are expected to increase C loss from boreal peatlands, contributing to a shift from C sink to source. Here, we provide a comprehensive review of pre- and post-fire hydrological and ecological interactions that affect the likelihood of peatland burning, address the connections between peatland fires and the C-climate cycle, and provide a conceptual model of peatland processes as they relate to wildland fire, hydro-climate, and ecosystem change. Despite negative ecohydrological feedback mechanisms that may compensate for increased C loss initially, the cumulative effects of climatic warming, anthropogenic peatland fragmentation, and subsequent peatland drying will increase C loss to the atmosphere, driving a positive C feedback cycle. However, the extent to which negative and positive feedbacks will compensate for one another and the timelines for each remains unclear. We suggest that a multi-disciplinary approach of combining process knowledge with remotely sensed data and ecohydrological and wildland fire models is essential for better understanding the role of boreal peatlands and wildland fire in the global climate system.
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    Quantifying land use effects on forested riparian buffer vegetation structure using LiDAR data
    (2015) Wasser, Leah; Chasmer, Laura; Day, Rick; Taylor, Alan
    Quantifying variability of forested riparian buffer (FRB) vegetation structure with variation in adjacent land use supports an understanding of how anthropogenic disturbance influences the ability of riparian systems to perform ecosystem services. However, quantifying FRB structure over large regions is a challenge and requires efficient data collection and processing methods that integrate conventional in situ vegetation sampling with remote sensing data. This study uses automated algorithms to process airborne light detection and ranging (LiDAR) data for mapping of riparian vegetation height, canopy cover and corridor width along 5,900 transects using methods validated in 80 mensuration plots in central Pennsylvania, USA. The key objective of this study was to use airborne LiDAR data to quantify differences in edge vs interior vegetation structure as influenced by buffer width and adjacent land use type, continuously throughout a watershed. Riparian vegetation height, canopy cover and buffer width were estimated along FRB transects adjacent to developed (residential/commercial and agricultural) and undeveloped (grassland) land use types and compared to reference transects within larger forested areas and thus without an edge. On average, buffers adjacent to developed land use types were narrower than those adjacent to natural, undeveloped land use types. Approximately 50% of streams in the watershed had FRB corridors 30 m wide. Only 23% of streams had a corridor width 200 m, the width recommended to support key ecosystem services. Undeveloped land use types contained taller riparian vegetation and wider corridors, whereas developed land use types contained shorter riparian vegetation and narrow FRB corridors. Edge effects also affected vegetation structure. Vegetation height was 5–8 m shorter at the interface between the FRB and the adjacent land use (the matrix) than in the naturally occurring stream edge or in the corridor interior. Canopy cover was not influenced by adjacent land use type or width. This study demonstrates that airborne LiDAR data can be used to accurately map riparian buffer vegetation width, height and canopy cover to support ecological based management of riparian corridors over wide areas.
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    Quantifying lidar elevation accuracy: parameterization and wavelength selection for optimal ground classifications based on time since fire/disturbance
    (MDPI, 2022) Nelson, Kailyn; Chasmer, Laura; Hopkinson, Christopher
    Pre- and post-fire airborne lidar data provide an opportunity to determine peat combustion/loss across broad spatial extents. However, lidar measurements of ground surface elevation are prone to uncertainties. Errors may be introduced in several ways, particularly associated with the timing of data collection and the classification of ground points. Ground elevation data must be accurate and precise when estimating relatively small elevation changes due to combustion and subsequent carbon losses. This study identifies the impact of post-fire vegetation regeneration on ground classification parameterizations for optimal accuracy using TerraScan and LAStools with airborne lidar data collected in three wavelengths: 532 nm, 1064 nm, and 1550 nm in low relief boreal peatland environments. While the focus of the study is on elevation accuracy and losses from fire, the research is also highly pertinent to hydrological modelling, forestry, geomorphological change, etc. The study area includes burned and unburned boreal peatlands south of Fort McMurray, Alberta. Lidar and field validation data were collected in July 2018, following the 2016 Horse River Wildfire. An iterative ground classification analysis was conducted whereby validation points were compared with lidar ground-classified data in five environments: road, unburned, burned with shorter vegetative regeneration (SR), burned with taller vegetative regeneration (TR), and cumulative burned (both SR and TR areas) in each of the three laser emission wavelengths individually, as well as combinations of 1550 nm and 1064 nm and 1550 nm, 1064 nm, and 532 nm. We find an optimal average elevational offset of ~0.00 m in SR areas with a range (RMSE) of ~0.09 m using 532 nm data. Average accuracy remains the same in cumulative burned and TR areas, but RMSE increased to ~0.13 m and ~0.16 m, respectively, using 1550 nm and 1064 nm combined data. Finally, data averages ~0.01 m above the field-measured ground surface in unburned boreal peatland and transition areas (RMSE of ~0.19 m) using all wavelengths combined. We conclude that the ‘best’ offset for depth of burn within boreal peatlands is expected to be ~0.01 m, with single point measurement uncertainties upwards of ~0.25 m (RMSE) in areas of tall, dense vegetation regeneration. The importance of classification parameterization identified in this study also highlights the need for more intelligent adaptative classification routines, which can be used in other environments.
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    Remote sensing of boreal wetlands 1: data use for policy and mangement
    (MDPI, 2020) Chasmer, Laura; Cobbaert, Danielle; Mahoney, Craig; Millard, Koreen; Peters, Daniel; Devito, Kevin; Brisco, Brian; Hopkinson, Christopher; Merchant, Michael; Montgomery, Joshua; Nelson, Kailyn; Niemann, Olaf
    Wetlands have and continue to undergo rapid environmental and anthropogenic modification and change to their extent, condition, and therefore, ecosystem services. In this first part of a two-part review, we provide decision-makers with an overview on the use of remote sensing technologies for the ‘wise use of wetlands’, following Ramsar Convention protocols. The objectives of this review are to provide: (1) a synthesis of the history of remote sensing of wetlands, (2) a feasibility study to quantify the accuracy of remotely sensed data products when compared with field data based on 286 comparisons found in the literature from 209 articles, (3) recommendations for best approaches based on case studies, and (4) a decision tree to assist users and policymakers at numerous governmental levels and industrial agencies to identify optimal remote sensing approaches based on needs, feasibility, and cost. We argue that in order for remote sensing approaches to be adopted by wetland scientists, land-use managers, and policymakers, there is a need for greater understanding of the use of remote sensing for wetland inventory, condition, and underlying processes at scales relevant for management and policy decisions. The literature review focuses on boreal wetlands primarily from a Canadian perspective, but the results are broadly applicable to policymakers and wetland scientists globally, providing knowledge on how to best incorporate remotely sensed data into their monitoring and measurement procedures. This is the first review quantifying the accuracy and feasibility of remotely sensed data and data combinations needed for monitoring and assessment. These include, baseline classification for wetland inventory, monitoring through time, and prediction of ecosystem processes from individual wetlands to a national scale.
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    Remote sensing of boreal wetlands 2: methods for evaluating boreal wetland ecosystem state and drivers of change
    (MDPI, 2020) Chasmer, Laura; Mahoney, Craig; Millard, Koreen; Nelson, Kailyn; Peters, Daniel; Merchant, Michael; Hopkinson, Christopher; Brisco, Brian; Niemann, Olaf; Montgomery, Joshua; Devito, Kevin; Cobbaert, Danielle
    The following review is the second part of a two part series on the use of remotely sensed data for quantifying wetland extent and inferring or measuring condition for monitoring drivers of change on wetland environments. In the first part, we introduce policy makers and non-users of remotely sensed data with an effective feasibility guide on how data can be used. In the current review, we explore the more technical aspects of remotely sensed data processing and analysis using case studies within the literature. Here we describe: (a) current technologies used for wetland assessment and monitoring; (b) the latest algorithmic developments for wetland assessment; (c) new technologies; and (d) a framework for wetland sampling in support of remotely sensed data collection. Results illustrate that high or fine spatial resolution pixels (≤10 m) are critical for identifying wetland boundaries and extent, and wetland class, form and type, but are not required for all wetland sizes. Average accuracies can be up to 11% better (on average) than medium resolution (11–30 m) data pixels when compared with field validation. Wetland size is also a critical factor such that large wetlands may be almost as accurately classified using medium-resolution data (average = 76% accuracy, stdev = 21%). Decision-tree and machine learning algorithms provide the most accurate wetland classification methods currently available, however, these also require sampling of all permutations of variability. Hydroperiod accuracy, which is dependent on instantaneous water extent for single time period datasets does not vary greatly with pixel resolution when compared with field data (average = 87%, 86%) for high and medium resolution pixels, respectively. The results of this review provide users with a guideline for optimal use of remotely sensed data and suggested field methods for boreal and global wetland studies.
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    SAR and lidar temporal data fusion approaches to boreal wetland ecosystem monitoring
    (MDPI, 2019) Montgomery, Joshua; Brisco, Brian; Chasmer, Laura; Devito, Kevin; Cobbaert, Danielle; Hopkinson, Christopher
    The objective of this study was to develop a decision-based methodology, focused on data fusion for wetland classification based on surface water hydroperiod and associated riparian (transitional area between aquatic and upland zones) vegetation community attributes. Multi-temporal, multi-mode data were examined from airborne Lidar (Teledyne Optech, Inc., Toronto, ON, Canada, Titan), synthetic aperture radar (Radarsat-2, single and quad polarization), and optical (SPOT) sensors with near-coincident acquisition dates. Results were compared with 31 field measurement points for six wetlands at riparian transition zones and surface water extents in the Utikuma Regional Study Area (URSA). The methodology was repeated in the Peace-Athabasca Delta (PAD) to determine the transferability of the methods to other boreal environments. Water mask frequency analysis showed accuracies of 93% to 97%, and kappa values of 0.8–0.9 when compared to optical data. Concordance results comparing the semi-permanent/permanent hydroperiod between 2015 and 2016 were found to be 98% similar, suggesting little change in wetland surface water extent between these two years. The results illustrate that the decision-based methodology and data fusion could be applied to a wide range of boreal wetland types and, so far, is not geographically limited. This provides a platform for land use permitting, reclamation monitoring, and wetland regulation in a region of rapid development and uncertainty due to climate change. The methodology offers an innovative time series-based boreal wetland classification approach using data fusion of multiple remote sensing data sources.
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    Shortening fire return interval predisposes west-central Canadian boreal peatlands to more rapid vegetation growth and transition to forest cover
    (Wiley, 2024) Jones, Emily Ann; Chasmer, Laura; Devito, Kevin J.; Hopkinson, Christopher
    Climate change in northern latitudes is increasing the vulnerability of peatlands and the riparian transition zones between peatlands and upland forests (referred to as ecotones) to greater frequency of wildland fires. We examined early post-fire vegetation regeneration following the 2011 Utikuma complex fire (central Alberta, Canada). This study examined 779 peatlands and adjacent ecotones, covering an area of ~182 km2. Based on the known regional fire history, peatlands that burned in 2011 were stratified into either long return interval (LRI) fire regimes of >80 years (i.e., no recorded prior fire history) or short fire return interval (SRI) of 55 years (i.e., within the boundary of a documented severe fire in 1956). Data from six multitemporal airborne lidar surveys were used to quantify trajectories of vegetation change for 8 years prior to and 8 years following the 2011 fire. To date, no studies have quantified the impacts of post-fire regeneration following short versus long return interval fires across this broad range of peatlands with variable environmental and post-fire successional trajectories. We found that SRI peatlands demonstrated more rapid vascular and shrub growth rates, especially in peatland centers, than LRI peatlands. Bogs and fens burned in 1956, and with little vascular vegetation (classified as “open peatlands”) prior to the 2011 fire, experienced the greatest changes. These peatlands tended to transition to vascular/shrub forms following the SRI fire, while open LRI peatlands were not significantly different from pre-fire conditions. The results of this study suggest the emergence of a positive feedback, where areas experiencing SRI fires in southern boreal peatlands are expected to transition to forested vegetation forms. Along fen edges and within bog centers, SRI fires are expected to reduce local peatland groundwater moisture-holding capacity and promote favorable conditions for increased fire frequency and severity in the future.
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    Shrub changes with proximity to anthropogenic disturbance in boreal wetlands determined using bi-temporal airborne lidar in the Oil Sands Region, Alberta, Canada
    (Elsevier, 2021) Chasmer, Laura; Lima, E. Moura; Mahoney, Craig; Hopkinson, Christopher; Montgomery, Joshua; Cobbaert, Danielle
    In this study, we used bi-temporal airborne lidar data to compare changes in vegetation height proximal to anthropogenic disturbances in the Oil Sands Region of Alberta, Canada. We hypothesize that relatively low-impact disturbances such as seismic lines will increase the fragmentation of wetlands, resulting in shrub growth. Bi-temporal lidar data collected circa 2008 and 2018 were used to identify correspondence between the density of anthropogenic disturbances, wetland shape complexity and changes in vegetation height within >1800 wetlands near Fort McKay, Alberta, Canada. We found that up to 50% of wetlands were disturbed by anthropogenic disturbance in some parts of the region, with the highest proportional disturbance occurring within fens. Areas of dense anthropogenic disturbance in bogs resulted in increased growth and expansion of shrubs, while we found the opposite to occur in fens and swamps during the 10-year period. Up to 30% of bogs had increased shrubification, while shrub changes in fens and swamps varied depending on density of disturbance and did not necessarily correspond with shrub growth. As wetland shapes became increasingly elongated, the prevalence of shrubs declined between the two time periods, which may be associated with hydrological drivers (e.g. elongated may indicate surface and ground-water discharge influences). The results of this study indicate that linear disturbances such as seismic lines, considered to have relatively minimal impacts on ecosystems, can impact proximal wetland shape, fragmentation and vegetation community changes, especially in bogs.