Determining When Bobolink Finish Breeding to Time Agricultural Activity in Nesting Refuges
Bibliographic record
Abstract
ABSTRACT Conservation actions are ongoing for the federally and provincially threatened bobolink (Dolichonyx oryzivorus) in Ontario, Canada because of population declines. One conservation action being implemented in agricultural grasslands is the delay of hay harvesting and livestock grazing until 15 July, a general guideline for when bobolink finish breeding. Efficient methods to assess when breeding ceases could benefit bobolink and farmers engaged in conservation by ensuring nesting is finished before agricultural activity occurs and enabling agricultural activity earlier when breeding is finished before 15 July. We conducted field surveys to assess if low‐intensity surveys (i.e., transect surveys, point counts, roadside counts) could accurately detect when bobolink finish breeding compared to intensive monitoring (i.e., spot mapping and nest monitoring). We monitored 29 pastures in 2017 in eastern Ontario and 9 hay fields, 10 restored grasslands, and 6 fallow fields in 2018 in southern Ontario. The date breeding finished varied across fields in 2017 from 13 June to 29 July and in 2018 from 24 June to 30 July, based on spot mapping and nest monitoring. Transect surveys and point counts were good predictors of breeding in a field, as confirmed through spot mapping and nest monitoring, based on generalized linear mixed models. We recommend using transect surveys or point counts as an efficient field method to assess when bobolink finish breeding in a field targeted for bobolink conservation. Our results suggest that 2 consecutive visits that fail to detect evidence of breeding in early July are needed to reasonably infer that breeding has likely finished, leaving a small probability (i.e., <0.01) that breeding may still be occurring. Determining when bobolink finish breeding in fields intended to provide nesting refuges can help maximize conservation benefits and minimize negative effects on agricultural production. © 2020 The Wildlife Society.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".