Landscape-level vegetation dynamics in Riding Mountain National Park, Manitoba, Canada
Bibliographic record
Abstract
The complex physiography and disturbance history of Riding Mountain National Park have resulted in a complex assemblage of aspen parkland, eastern deciduous and boreal forest communities on the landscape. Few studies have examined forest composition, structure and dynamics in the eastern extension of the mixedwood forest region. This study uses detailed vegetation, edaphic and environmental data collected from 202-100 m2 forest plots distributed throughout the Park to elucidate landscape-level trends in forest structure and dynamics. Stands were first classified into 8 dominant stand types, and described in terms of their biotic and abiotic characteristics. Factors affecting patterns of understory tree regeneration and the timing of their recruitment were examined on the landscape, and growth of understory green ash (Fraxinus pennsylvanica Marsh.) and white spruce (Picea glauca (Moench) Voss) were analyzed in different habitats to infer future changes in stand composition. Successional trajectories were created for each of the 8 stand types using a static size-class analysis of tree species, and a comprehensive conceptual model of stand dynamics was created. Sections of this thesis have previously been published in Caners and Kenkel (1998). Results indicate that successional trajectories for stand types in the Park do not converge towards a single self-perpetuating 'climax' community. Instead, vectors diverge, converge and remain cyclical, with multiple potential pathways recognized for each stand type. This study demonstrates that species assemblages, and the propensity for change, are governed by the cumulative and synergistic effects of climate, topography, disturbance frequency, size and intensity, edaphic conditions and the proximity of parental seed sources. These factors have resulted in a patchwork mosaic of forest stands on the landscape of varying structure, composition and seral stage. Overall, results are in general agreement with studies from central and eastern regions of the boreal forest. Post-fire stands are dominated by pioneering hardwoods such as aspen, balsam poplar and paper birch. Mid-succession stands show an increasingly greater proportion of white spruce in the canopy, whereas late-succession stands are dominated by white spruce and balsam fir and are driven by gap dynamic processes. The oldest stands are commonly open and shrub-dominated, especially by beaked hazelnut and mountain maple. In areas of dense shrub cover and/or areas without a proximate seed source, regeneration of tree species is dramatically reduced. Ungulate herbivores selectively browse trees and shrubs, impacting the long-terms dynamics of forest systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".