Assessing baseline glucocorticoids as conservation biomarkers in a declining aerial insectivore
Bibliographic record
Abstract
Conservation biologists are increasingly incorporating a diversity of integrative approaches to monitor, manage, and mitigate the growing threats to biodiversity imparted by climate change and other anthropogenic pressures. Over the past 15 years, stress hormones (i.e., glucocorticoids: corticosterone and cortisol) have been gaining considerable attention as sensitive physiological biomarkers of wildlife disturbance. However, despite a substantial accumulation of studies citing glucocorticoids (GCs) as potential indicators of condition, health, or disturbance, comparatively little is known about their actual utility for conservation monitoring. This thesis aims to validate three key characteristics of baseline plasma GCs that are necessary to their employment as sensitive, predictive biomarkers of wildlife disturbance: 1) correlation with environmental quality; 2) consistency across individuals in response to environmental alteration; 3) relationship with fitness metrics at the individual and population level. I complete these validations across two different reproductive stages in female tree swallows (Tachycineta bicolor), a member of the aerial insectivore guild of birds that is in population decline in North America. My results indicate that baseline GCs may not reflect the natural variation in components of the internal and extrinsic environment that are associated with habitat quality or disturbance. In addition, baseline GCs show considerable within-individual variation across the breeding season, and display individually-specific responses to an experimentally-induced change in environmental quality (i.e., a decline in foraging profitability). Further, baseline GC levels do not relate to multiple metrics of fitness (offspring quality, reproductive output, or survival) despite the careful control of potentially confounding contexts such as age, reproductive stage, time of day, and body condition. Finally, at the average level, my results indicate that an environmental perturbation (i.e., a decline in foraging profitability) can have consequences for body condition, behaviour, and current and future baseline GC levels in habitat type-specific ways without concomitant influences on fitness. Collectively, my findings suggest that baseline GCs may not be easily interpretable as individual or population-level indicators of disturbance or fitness. Importantly, these results indicate that GCs cannot be assumed to represent conservation biomarkers across species or time periods without careful validation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".