Vascular plant community data for Northwest Territories, Canada
Bibliographic record
Abstract
This record is for the dataset “Vascular plant community data for Northwest Territories, Canada” at https://doi.org/10.5061/dryad.76hdr7sth. Climate change is altering disturbance regimes outside of historical norms, which can impact biodiversity by selecting for plants with particular traits. The relative impact of disturbance characteristics on plant traits and community structure may be mediated by environmental gradients. We aimed to understand how wildfire impacted understory plant communities and plant regeneration strategies along gradients of environmental conditions and wildfire characteristics in boreal forests. We established 207 plots (60m2) in recently burned stands and 133 plots in mature stands with no recent fire history in comparable gradients of stand type, site moisture (drainage), and soil organic layer (SOL) depth in two ecozones in Canada’s Northwest Territories. At each plot, we recorded all vascular plant taxa in the understory and measured the regeneration strategy (seeder, resprouter, survivor) in burned plots, along with seedbed conditions (mineral soil and bryophyte cover). Dispersal, longevity, and growth form traits were determined for each taxon. Fire characteristics measured included proportion pre-fire SOL combusted (fire severity), date of burn (fire seasonality), and pre-fire stand age (time following fire). Results showed understory community composition was altered by fire. However, burned and mature stands had similar plant communities in wet sites with deep SOL. In the burned plots, regeneration strategies were determined by fire severity, drainage, and pre- and post-fire SOL depth. Resprouters were more common in wet sites with deeper SOL and lower fire severity, while seeders were associated with drier sites with thinner SOL and greater fire severity. This led to drier burned stands being compositionally different from their mature counterparts and seedbed conditions were important. Our study highlights the importance of environment-wildfire interactions in shaping plant regeneration strategies and patterns of understory plant community structure across landscapes, and the overriding importance of SOL depth and site drainage in mediating fire severity, plant regeneration, and community structure. This data can be downloaded at https://doi.org/10.5061/dryad.76hdr7sth
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.068 | 0.033 |
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".