Changes in peatland plant community composition and stand structure due to road induced flooding and desiccation
Bibliographic record
Abstract
Roads built through peatlands with horizontal water flow can to act as dams that affect local hydrology and thus vegetation composition and structure. On the ‘upstream’ side of roads, soils can become waterlogged causing either increased tree mortality, or stunted tree growth; conversely, the ‘downstream’ side may experience drying resulting in deeper root growth and increased canopy cover. Interestingly, this phenomenon is not consistent between classes of peatlands (i.e. bogs, fens, and swamps) and comparable roads may disrupt tree growth patterns in one peatland, while another may be unaffected. This study examines the conditions that maintain or alter stand structure and vegetation composition in different types of road-bisected peatlands, namely that of landscape position and mineral soil substrate composition (clay, sand, silt). I assessed tree stand structure for 96 peatlands in northeast Alberta using airborne LiDAR-derived canopy cover. Vegetation data were collected for 25 peatland sites in northeastern Alberta. These sites were subsampled with 4 plots per peatland, one pair adjacent to the road, reflecting the dry versus wet conditions, and a second pair 100 meters from the road. Generalized Linear Mixed Models (GLMMs) and distance-based redundancy analyses were used to evaluate relationships between LiDAR-derived canopy cover, vascular plant species richness, vegetation cover among different groups of species or species indicators, and overall species composition among different peatland types, environmental factors, landscape postion, and road characteristics. Canopy cover and tree species composition increased on the downstream side of roads and decreased on the upstream side of roads. Species richness increased in bogs on the upstream side of roads, while being comparably lower on the upstream side than on the downstream side of roads in fens. Carex limosa, Carex canescens, and Andromeda polifolia were identified as indicators of the upstream side of roads in fens, swamps, and bogs respectively, with significant differences confirmed in GLMMs. Substrate conditions below the peat further affected responses of plants, with ericaceous shrubs positively related to amount of clay, while some forbs and sedges were positively related to amount of sand. Substrate underlying the peat also influenced the effect that roads had on species composition. Bogs developed over substrates with high sand content had floristic shifts on the upstream side of the road whereas vegetation communities were similar on both sides of the road in bogs with very little sand. This study demonstrates the value of LiDAR-derived vegetation structure metrics in evaluating changes in woody vegetation structure for road-fragmented peatlands and that wetland classifications stratified with surficial geology can be a useful indicator of responses of vegetation to roads. However, responses were variable among sites due to interactions between road orientation, substrate texture, landscape position, and peatland type.
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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 | 0.000 | 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) | 0.001 | 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".