Secretive marsh bird occupancy across a spectrum of hydroelectric reservoir management in western montane Canada
Bibliographic record
Abstract
Abstract Dam construction projects have created opportunities for water security, targeted flood protection, and energy production but at the cost of increasing anthropogenic pressure on affected aquatic ecosystems. Wetland ecosystems are often among the most vulnerable, as underlying hydrological regimes influence overall wetland structure and function. Marsh bird species are wetland and riparian habitat specialists, many of which are experiencing population declines across North America. We examined how the alteration of hydrological regimes for generating hydroelectric power affected the occurrence of secretive marsh bird species in the western montane region of British Columbia, Canada. We established survey stations in wetlands across 2 regions, the West Kootenay and the Columbia Wetlands, sampling across a spectrum of hydrological regimes and other potentially relevant factors. At each station, we assessed wetland occupancy during the breeding season using broadcast‐callback surveys focused on 5 secretive marsh bird species: American bittern (Botaurus lentiginosus), American coot (Fulica americana), pied‐billed grebe (Podilymbus podiceps), sora (Porzana carolina), and Virginia rail (Rallus limicola). Additionally, we measured vegetation structure and the proximity and size of nearby water bodies for each survey station. We then used occupancy models to assess important correlates behind wetland occupancy for these marsh bird species, considering water management operations, regional differences, and local‐ and landscape‐level wetland characteristics. Secretive marsh bird species were more likely to occupy wetlands in areas with less frequently altered hydrological regimes. Occupancy models highlighted local‐ and landscape‐level characteristics as important correlates for wetland occupancy by marsh birds. Wetlands with frequently altered hydrological regimes had more open water cover and less tall vegetation present, conditions that were negatively associated with occupancy. Altered wetlands in this study were farther from the next nearest wetland, which was also negatively associated with occupancy. We suggest reservoir management is altering vegetation communities within these wetlands, indirectly promoting lower occupancy of secretive marsh bird species.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".