Bird and Bat Diversity and Abundance in Agroecosystems in Relation to Drainage Hedgerow and Landscape Structure
Bibliographic record
Abstract
Hedgerows are common semi-natural linear features along agricultural drainages in temperate agroecosystems.Two important variables likely to affect diversity within hedgerows include hedgerow structure and landscape structure.I hypothesized that hedgerows that are taller, wider, and more variable in height, and landscapes with smaller fields and higher forest amount, will support higher diversity within drainage hedgerows by providing more habitat.I used point counts of forest and shrub-edge-associated birds and ultrasonic recordings of bats along drainage hedgerows in eastern Ontario to test my hypotheses.Overall, I found that drainage hedgerow height was positively associated with higher biodiversity for birds and bats.Width and variation in height were also important depending on the response considered.With respect to landscape structure, edge-associated species generally responded positively to smaller field sizes.My results show that structurally complex drainage hedgerows and smaller fields provide valuable habitats for birds and bats in agroecosystems.guidance throughout this project.I would also like to thank my committee members, Scott Wilson and David Currie, for their feedback and suggestions which greatly improved the project.I would also like to thank Niloofar Alavi-Shoushtari, who played an integral role in site selection, drainage hedgerow and landscape structure extraction, and survey region visualization.Thank you also to David Lapen for leading research on drainage ditches in the area, securing funding, and providing input on site selection.I would like to
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".