Effects of Forest Fire on Young-of-the-year Northern Pike, <em>Esox lucius</em>, in the Northwest Territories
Bibliographic record
Abstract
In 1998, a forest fire burned 58% of the forested shoreline surrounding Tibbitt Lake, Northwest Territories, including riparian vegetation used by Northern Pike (Esox lucius) as spawning habitat. This presented an opportunity to investigate the effects that habitat disturbance from a natural forest fire had on young-of-the-year (Y-O-Y) Northern Pike. Pike fry were collected from three burned and three unburned sites around Tibbitt Lake in 1999 (the first post-fire spawning season) and again in 2001. Differences in size and relative abundance were evaluated between sites. Y-O-Y Northern Pike were significantly larger at the unburned sites (P<0.01) and the relative abundance of Y-O-Y Northern Pike increased significantly at burned sites (alpha=0.1; P<0.07) following re-vegetation two years post fire. These differences may be due to fire-induced changes in physical habitat or food availability. Forest fires decrease the density of riparian vegetation, which likely provides better spawning and rearing habitat for Northern Pike in the long-term.En 1998, un feu de forêt a brûlé 58% de la rive boisée entourant le lac Tibbitt, situé dans les Territoires du Nord-Ouest, y compris la végétation riveraine utilisé par le grand brochet (Esox lucius) comme habitat de fraie. Cet événement a présenté une occasion pour étudier les effets causés par un feu de foret sur l'habitat de jeunes de l'année du grand brochet. Les jeunes brochets ont été recueillis sur trois sites brûlées et trois sites non brûlés autour du lac Tibbitt en 1999 (la première année de fraie après le feu de forêt) et à nouveau en 2001. La différence de grandeur et l'abondance relative des poissons ont été analysés entre les différents sites. Les jeunes grands brochets aux sites non-atteints par le feu étaient considérablement plus grands (P < 0,01) que ceux aux sites brulés. Les sites brulés, subissant une rapide revégétation dans les deux années après le feu, ont augmenté en abondance relative de jeunes grands brochets (alpha = 0,1, P < 0,07). Ces différences peuvent être dues aux changements induits par le feu sur l'aspect physique de l'habitat ou sur la disponibilité de nourriture. Les incendies de forêt réduisent la densité de la végétation riveraine, qui fournit probablement de meilleure habitat de fraie et d'alevinage pour le grand brochet à long terme.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".