Nest site selection and nest predation patterns at forest-field edges
Bibliographic record
Abstract
The effects of forest-field edge structure on nest site selection and nest predation at forest-field edges were tested using natural and artificial nests. In the first part of this study, nest site selection patterns of a declining species of edge-nesting neotropical migratory bird, the Golden-winged Warbler (Vermivora chrysopteru) were studied in southeastem Ontario. Habitat features important in nest site selection, and those distinguishing successful and depredated nests were identified. Edges used as nest sites had a more gradual edge slope, and a greater stem density surrounding nests than unused sites along the same edges. Successful nests were associated with greater Goldenrod (Solidago sp.) density and greater nest visibility than depredated nests, but edge shape and woody vegetation density had no effect on nesting success. These results suggest that Golden-winged Warbler breeding habitat could be created by the conversion of abrupt agriculturai edges to more gradual edges by mowing areas adjacent to the edge on a rotating schedule. In the second part of this study, artificial ground nests containing Chinese Painted Quail and plasticine eggs were placed on different forest-field edge structural types to quanti@ the effects of edge Iinearity, edge shape and nest visibility on predation pattems. Edge shape and nest visibility did not affect nest predation intensity, however, nests located on linear edges tended to be depredated more fiequently than those on curvilinear edges, which was attributed to reduced travel along curvilinear boundanes by nest predators. Predator identificati~n revealed individual responses of nest predator groups to variation in edge stmchire and nest Msibility, suggesting that nest predator comrnunity differences between sites may explain the inconsistent results of present studies examining the effects of edge structure on nest predation pattems. Acknowledgements 1 would first like to thank Raleigh Robertson for giving me the oppomuiity to conduct this project. He always had confidence in my abilities, supported my decisions, and he never criticized me when things (fiequently) went wrong. Above all, his sense of humour and fnendship have helped me through many stresshl situations and made this expenence much more enjoyable. 1 would like to express my gratitude to Stephen Lougheed for his guidance that shaped much of this project and his willingness to drop everything vrhen 1 needed his help. 1 especially thank Steve for being disappointed in my decision ta take a hiatus fiom academic biology.. .coming fiom a scientist like yourself, that's about the best compliment that 1 could receive. 1 would also like to thank Demis Jelinski and Vicki Fnesen for inspiring my interest in this topic, and for al1 of their help in focusing this study. Thanks to al1 the folks in the Robertson lab over the past few years for al1 the good times and especially to Barg, Jason Jones and Javier Salgado-Ortiz for ail of their help. For assistance in the field, 1 am indebted to Katharina Manno, Jamie and Erin Beauchamp, and especially William McLeish who, in addition to being a great Wend, is one of the best field ornithologists that I've met. I'd also like to thank Iason Pither and Daniel Memil1 who have both improved this thesis with their many helpful comments. Thanks to the staff (especially Frank Phelan and Floyd C o ~ o r s ) and al1 of my good fnends at QUBS for making my sumrners of research so enriching, enlightening and mernorable. Special thanks go to Ryan DeBniyn, Heather McCracken, and Chris Yourth for their help and friendship, and for always being ready to do anything. Above all, 1 would like to thank the love of my life, Kelly Pageau. 1 wish somehow that 1 could express how much her love, friendship, support, and understanding have helped me through this experience. Despite al1 of the time spent apart, and time spent together where 1 was locked up in my office writing, she endured as a source of constant happiness for me. Thanks KeI. This work was made possible by funding from NSERC, Queen's Graduate Fellowship, and Wildlife Habitat Canada. Abstract Table of
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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 | 0.000 |
| 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".