Abstract
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.
Highlights
Peatlands constitute 12% of Canada’s landscape and are characterized by the slow decomposition of soil organic matter, having a minimum depth of 40 cm [1,2]
We found that deciduous shrubs in peatlands were found in areas with shallow slopes (0–3◦) in both burned and unburned sites determined using the random forest classification
This study explored the use of airborne multi-spectral lidar data to identify deciduous shrubs/trees and conifers in a space-for-time post-fire chronosequence boreal peatland environment using forest-based classification
Summary
Peatlands constitute 12% of Canada’s landscape and are characterized by the slow decomposition of soil organic matter (i.e., peat), having a minimum depth of 40 cm [1,2]. The combined impacts of drying on successional trajectories, including peatland shrubification and more severe fires could result in a decline in boreal species such as black spruce, and a possible transition to younger deciduous species. Such transitions in peatland vascular tree/shrub species may have significant implications for the climate–carbon system by altering carbon dynamics across broad peatland-forest complexes [16,17]. The objectives of this research were to (a) determine the utility of multi-spectral lidar for identifying deciduous vs conifer trees, shrubs, and herbaceous ground cover species; (b) quantify proportional coverage of post-fire shrub vs tree regeneration within peatlands; and (c) determine the approximate. TThhee oollddeerr ffiirreess iinn 11998822 aanndd 11999900 bbuurrnneedd 3366,,999966 aanndd 99445511 hheeccttaarreess,, rreessppeeccttiivveellyy [[3366]],, wwhhiillee ffiirreess iinn 22000022 aanndd 22001155 bbuurrnneedd mmoorree tthhaann 223366,6,66622aanndd98988383hehcetcatraerse,sr,ersepsepceticvteivlye,layn, danindcilnucdleusdoemseomunebuunrnbeudrniseldanidslsanandds apnadrtipaallrytibalulyrnbeudranreedasa.reas
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