Modelling migration dynamics of Common Cranes and Eurasian Spoonbills as hydrological flow
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Bibliographic record
Abstract
The migration of birds through a stopover site may be understood as a physical process of hydrological flow through a reservoir whose water levels rise and fall over a migration period. Hydrological flow models show promise as a way of integrating information on storage (daily counts of birds), inflow/outflow (number of birds arriving/departing each day) and transit time (length of stay (LOS)) over a migration period. We used a hydrological flow model to evaluate the relationship between stopover duration and passage population sizes of migrant birds under variable wetland conditions in two case studies. First, we considered the northward migration of Common Cranes Grus grus at Gallocanta Nature Reserve in Spain. We calibrated the model with daily counts recorded in 1984 and 1985, and then used it to predict transit time distributions based on counts of cranes 30 years later (2015–17). The model was calibrated with a mean transit time of 6.5 days observed in 1984/85, consistent with observed values of LOS, and predicted a mean transit time of 5.2 days for the 2015–17 period. The model also predicted an ~6.2× increase of the total migratory passage population of cranes at Gallocanta, which qualitatively agreed with the large increase in the overall population from the 1980s to 2010s. Second, migration dynamics of Eurasian Spoonbills Platalea leucorodia were considered during southward migration at two intertidal coastal wetlands in northern Spain from 2002 to 2005. The model well captured the observed differences in transit time between Urdaibai Biosphere Reserve (median transit time of 1.1 days) and Santoña Marshes Natural Park (median transit time of 2.1 days). Transit times of both species were negatively correlated with estimates of annual population sizes. These results indicate that hydrological flow models can provide insights into the migration ecology of waterbirds (or species where regular counts during migration are available), and that LOS is a dynamic decision that can depend on the population sizes of migratory birds.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it