Flexible migration and habitat use strategies of an endangered waterbird during hydrological drought
Bibliographic record
Abstract
Abstract Wildlife species confront threats from climate and land use change, exacerbating the influence of extreme climatic events on populations and biodiversity. Migratory waterbirds are especially vulnerable to hydrological drought via reduced availability of surface water habitats. We assessed how whooping cranes ( Grus americana ) modified habitat use and migration strategies during drought to evaluate their resilience to changing conditions and adaptive capacity. We categorized >8000 night‐roost sites used by 146 cranes from 2010 to 2022 and examined relative use during non‐drought, moderate drought, and extreme drought conditions. We found cultivated and uncultivated palustrine and lacustrine wetlands were generally used less during droughts than non‐drought conditions. Conversely, impounded palustrine and lacustrine systems and rivers served more frequently as drought refugia (i.e., used more during drought than non‐drought conditions). Night roosts occurred primarily on private lands (86% overall); public land use decreased with latitude and increased with drought severity, with greatest use (56%) occurring during severe autumn drought in the southern Great Plains. Quantifying use of identified critical habitats in the United States indicated that Cheyenne Bottoms State Waterfowl Management Area and Quivira National Wildlife Refuge were used less during drought, and the Central Platte River and Salt Plains National Wildlife Refuge received similar use during drought compared to non‐drought conditions. Our findings provide insights into compensatory use of habitats, where impounded surface water may function in a complementary fashion with natural wetlands. Collectively, these and other types of wetlands distributed across the migration corridor provided a reliable network of habitat available across the Great Plains. A diversity of wetlands available during variable environmental conditions would be useful in supporting continued recovery of whooping cranes and likely have benefits for a wide array of migratory birds.
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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".