Revisiting reclaimed well pads in boreal forests: the role of time and changing criteria in the recovery of vegetation composition, forest structure, and plant traits
Bibliographic record
Abstract
Boreal forests provide multiple ecological and economic services, including carbon storage, provision of wildlife habitat and recreational space, and timber supply. In Canada’s western boreal forests, natural resource energy exploration and extraction results in substantial anthropogenic disturbances, including clearing forests for well pads. Well sites are decommissioned and then reclaimed: a process whereby disturbed land is to be set on a trajectory of ecological recovery. However, after meeting reclamation requirements sites are rarely monitored, resulting in uncertainty about long-term successional trajectories. Ecological succession of these post-reclaimed sites may be arrested, contributing to landscape fragmentation and its associated negative consequences. This includes loss of habitat and thus biodiversity, greater vulnerability to invasive species, and changes to ecosystem processes. To understand post-reclamation recovery, we collected data on vegetation at 25 well pads and adjacent reference boreal forests in north-west Alberta, Canada. Taxonomic (e.g., species occurrence), structural (e.g., basal area), functional (e.g., specific leaf area) and soil property (e.g., bulk density) data were used to assess the recovery trajectories of well pads of varying post-certification ages. Multivariate ordinations and analyses, generalized additive mixed models, and mixed effect models were used to quantify recovery patterns. Our analyses demonstrated that well pads of varying ages and criteria groups differed from adjacent reference forests. However, soil FH depth, leaf carbon, and diversity measures showed resilience. Overall, our data suggest that many well pads are not recovering even 44 years post-reclamation and that more time is needed to assess if recent changes to criteria are aiding recovery. Other factors may be influencing the trajectory of recovery in the understory plant community more than the time since post-reclamation. Results from this study can improve our understanding of post-disturbance successional dynamics and may help inform mitigation actions used to remove biological and environmental barriers limiting ecological recovery.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".