"Evaluating the effect of tree cover on stream surface temperature and red side dace habitat using thermal infrared imaging."
Bibliographic record
Abstract
The red side dace is an endangered minnow mainly located within the streams flowing around the city of Toronto. Rapid urbanization has significantly impacted land surface temperature, resulting in an urban heat island effect. Developed areas also raise the temperature of the surrounding adjacent areas, including forests, streams, and rivers. In the context of the warming climate, it is vital to understand the drivers influencing stream temperature to mitigate negative biodiversity outcomes. The detrimental impact of urban development and loss of riparian vegetation has increased stream temperatures and modified aquatic species' thermal habitat, including the red side dace. However, it is not clear to what degree tree canopy cover influences stream temperatures and thermal habitat. In this study, I aimed to improve our understanding of how tree cover affects stream surface temperature using drone-mounted thermal infrared imaging with the specific objectives of assessing how tree cover influences red-side dace thermal habitat. The study was carried out at a watershed restoration site owned by Toronto and Region Conservation Authority in Markham, Ontario, Canada. My specific objectives were to 1) assess how stream temperature differs between locations sampled up- and down-stream from the cluster of trees along the watercourse at different distances from the tree cluster using paired t-tests and 2) model how this effect varies with tree foliage cover and run of the stream covered by foliage using linear regression. I found evidence that water temperatures downstream from tree clusters were significantly cooler than upstream temperatures at a distance of 4.5 meters from the cluster. However, I did not find any evidence that the percentage of tree foliage and run of the stream covered by the tree cluster affected this difference. This research highlights the drone-based thermal imaging method as an effective system for evaluating stream surface temperature and understanding tree cover's relationship with the stream's temperature. This study will provide the preliminary foundation to identify the impact of tree cover on thermal habitat and contribute towards red side dace conservation and habitat restoration initiative carried by the Toronto Region Conservation Authority (TRCA).
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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".