Avian osmoregulation in flight: unique metabolic adaptations present novel challenges
Bibliographic record
Abstract
Migratory birds face unique challenges as they routinely complete extremely long flights where rates of respiratory water losses are high, but the continual maintenance of ion homeostasis is crucial. Songbirds (order Passeriformes ) typically complete migration through a series of long duration nocturnal flights, each followed by a brief stopover period where fuel reserves are replenished. In flight, migratory birds rely on endogenous fat and protein for energy, resulting in dramatic reductions in lean and fat masses of individuals. During flight, rates of respiratory water loss are extremely high due to the high breathing frequency and tidal volumes required for sustained aerobic exercise. Despite prolonged flights over inhospitable environments, no studies to date have documented dehydration in migratory birds after long flights in the wild. In order to investigate the osmoregulatory strategies used by migratory birds, we developed a method to measure glomerular filtration rate in flying birds using a single injection of FITC inulin, which was eliminated following second order exponential decay kinetics. Using this methodology we investigated GFR in flight, during fasting and in fed birds and found no difference among fed, fasted and flown birds in GFR, but fractional water reabsorption was increased during both fasting and flight. We found no influence of rate of water loss on the increase in FWR during flight. In separate experiments we investigated the metabolic response of thrushes to dehydrating conditions during flight and found that birds increase rates of protein catabolism as a means to increase endogenous water production to offset high rates of respiratory water loss. In these studies we show that migrating birds do not dynamically regulate GFR, as has been found for other environmental challenges, but instead dynamically regulate rates of metabolic water production in order to maintain water balance in flight. This strategy allows the completion of long duration flights, but at the cost of organ and muscle mass. Moving forward we are investigating the mechanisms regulating lean mass catabolism in response to dehydration stress and the functional consequences of organ and muscle catabolism during flight in 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 | 0.001 | 0.001 |
| 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".