Field-validated species distribution model of Canada Warbler ( Cardellina canadensis ) in Northwestern Ontario
Bibliographic record
Abstract
The Canada Warbler (Cardellina canadensis) is a species of conservation concern, but its ecological needs and distribution remain poorly understood. The impact of logging on Canada Warbler abundance and habitat use is disputed. Furthermore, its habitat needs may be distorted by limitations in current habitat availability compared to historical conditions. Using Maxent, we developed a predictive high-resolution (30 m) field-validated species distribution model (SDM) in Northwestern Ontario, Canada, where information about the species is limited. We aimed to assess how time since disturbance mainly due to logging affects Canada Warbler occurrence and distribution. The SDM was built on occurrences (2000–2020) from various datasets supplemented with field-collected data from 2021. Environmental covariates included spectral indices from Landsat images (2018), disturbance (usually by logging), and tree canopy height. Model accuracy was assessed through field validation in 2022, using the resulting data for final model validation. The final model showed moderate performance for both training and test data (AUC = 0.7). It achieved a total accuracy of 74.57% and a Kappa value of 0.43, indicating agreement better than expected by chance. The normalized water index, distance to water, enhanced vegetation index, and distance to mature coniferous were the more influential covariates, indicating a high association with deciduous vegetation, riparian zones, high shrub cover, and the importance of coniferous stands. Canada Warbler occurrence probability was high (> 0.7) predominantly in undisturbed forest, but also was high (0.6) within six years since post-disturbance areas, indicating that Canada Warbler may take advantage of regenerated forest depending on shrub density and retention of old-growth forest structure (tree canopy height > 10 m). Recommendations for Canada Warbler conservation include the retention of tall trees and managing logged areas to retain favorable shrub and riparian habitats. We present a field-validated SDM for Canada Warbler, providing valuable insights for its conservation.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".