Applications of and Barriers to Prescribed Fire for Grassland Management in Saskatchewan
Bibliographic record
Abstract
Fire can be a powerful tool for the management and conservation of remaining grasslands in the northern Great Plains. Extensive modification of northern prairies driven by persistent management ideologies have significantly altered the historic pattern of disturbances. Elevated risks associated with wildfire, further declines in grassland biodiversity, and growing threats to ecosystem goods and services are prevalent. The intersection of climate change mitigation, biodiversity conservation, and adaptive governance requires a multifaceted, socioecological approach to confront current and impending challenges in the region. The intentional use of fire, as an Indigenous cultural practice and natural ecosystem process, has been shown to be an effective land management tool to meet numerous objectives but continues to be underutilized in southern Saskatchewan and elsewhere. The purpose of this research was to explore the risk management and ecological applications of prescribed fire with a focus on barriers to the effective use of fire. Specifically, I 1) use remote sensing of grassland vegetation at different scales to preemptively identify hazards associated with prairie fire and describe how prescribed burning could mitigate those hazards, 2) examine ungulate grazing selectively in response to prescribed burning and impacts to heterogeneity of prairie habitat for grassland management and conservation; and 3) conduct a comparative analysis of strategies for reintroducing prescribed fire in Saskatchewan’s prairie ecozone, and to identify barriers to interagency collaboration and expansion of the practice as a culturally significant endeavour and important economic, ecological, and community-building process.\nImagery from satellites and unmanned aerial vehicles (UAVs), combined within a simple, integrated model identified fire hazard metrics suitable for operational use in topographically variable, northern mixed prairie. Grazing intensity altered vegetation distribution and fuelbed heterogeneity. Normalized difference vegetation index (NDVI) and slope were predictors of burn patterns, offering those tasked with fire mitigation and suppression useful information for safe and effective planning, implementation, and analysis. Reintroduction of fire into a semi-arid, grazed grassland had heterogeneous effects on vegetation and temporarily altered spatiotemporal patterns of herbivory by bison and cattle. Multiscale observations from remote sensing platforms evaluated changes pre- and post-burning and demonstrated bison and cattle selectivity at a very fine spatial scale. Limited impacts to plant community composition, with year-to-year variation a dominant factor, suggested prudently managed northern mixed prairie was resilient to the fire-grazing interaction. Finally, comparative analysis of agency strategies for restoring fire in southern Saskatchewan acknowledged the importance of developing a community of practice within a multiscalar, collaborative effort. Current programs were limited by a range of social, informational, practical, and regulatory constraints. Established programs with significant investment in trained personnel and equipment accomplished the largest and most complex areas burned. Those with limited funding using a collaborative approach in a centralized location burned most frequently. A newly formed, coordinating agency provided structure and additional funding to support various organizations, beginning to close a gap between research and implementation to advance the practice in Canadian prairies. Greater integration with federal and provincial fire management organizations is required to emulate similar U.S. models. Increased understanding, coordination, and implementation of prescribed fire will build adaptive capacity and community resilience to confront rising threats locally and globally.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".