Modeling spring migration patterns of scoters and loons in the Bay of Fundy
Bibliographic record
Abstract
Populations of scoter and loon species that winter in the Atlantic are understudied in North America, but coastal observatories may provide the data required to fill some of the knowledge gaps. The migration of scoters and loons has been monitored at the Point Lepreau Bird Observatory (PLBO) in the Bay of Fundy every spring since 1996, but little peer-reviewed research based on the resultant database has been published. Using data collected over 18 years at the Bay of Fundy (2000–2017), our objectives were to (1) determine the most accurate method of modeling hourly migration rates for Surf (Melanitta perspicillata), White-winged (M. deglandi), and Black (M. americana) scoters, and Red-throated (Gavia stellata) and Common (G. immer) loons, and (2) assess trends in hourly migration rates for our five focal species to determine if the numbers of migrants passing PLBO have changed over time. We calculated hourly migration rates for each of our five focal species and evaluated drivers (i.e., timing and environmental conditions) of migration and annual trends using zero-inflated generalized linear mixed models (GLMMs). We found that drivers of migration differed among species. Specifically, hourly migration rates decreased with increasing tide height for all species except Red-throated Loons. In addition, hourly migration rates increased with increasing wind vector (i.e., a tailwind) for the three scoter species, but decreased with increasing wind vector for the two loon species. Scoter migration rates peaked daily between 11:00 and 13:00 UTC, but we found no daily peak for either loon species. Peak hourly migration rates of Black and Surf scoters occurred from 12 to 26 April, but migration rates of White-winged Scoters and both loon species continued to increase throughout our migration-monitoring window. Finally, we found no changes in hourly migration rates over time for any of our focal species, suggesting no changes in abundance over the 18 years of data collection. Our study reveals the importance and utility of long-term, coastal observation stations, and we recommend their continued funding and use as valuable sources of monitoring data. Modelado de patrones de migración primaveral de negrones y colimbos en la Bahía de Fundy Las poblaciones de especies de negrones y colimbos que pasan el invierno en el Atlántico están poco estudiadas en América del Norte, pero los observatorios costeros pueden proporcionar los datos necesarios para llenar algunos de los vacíos de conocimiento. La migración de negrones y colimbos ha sido monitoreada en el Observatorio de Aves Point Lepreau (PLBO) en la Bahía de Fundy cada primavera desde 1996, pero se han publicado pocos estudias arbitrados por pares basados en la base de datos resultante. Utilizando los datos recopilados durante 18 años en la Bahía de Fundy (2000–2017), nuestros objetivos fueron (1) determinar el método más preciso para modelar las tasas de migración por hora para el Negrón costero (Melanitta perspicillata), el aliblanco (M. deglandi), y el americano (M. americana), y el Colimbo chico (Gavia stellata) y grande (G. immer), y (2) evalúan las tendencias en las tasas de migración por hora para nuestras cinco especies focales para determinar si el número de migrantes que pasan PLBO han cambiado con el tiempo. Calculamos las tasas de migración por hora para cada una de nuestras cinco especies focales y evaluamos los factores impulsores (es decir, el tiempo y las condiciones ambientales) de la migración y las tendencias anuales utilizando modelos mixtos lineales generalizados inflados a cero (GLMM). Encontramos que los impulsores de la migración diferen entre las especies. Específicamente, las tasas de migración por hora disminuyeron con el aumento de la altura de la marea para todas las especies, excepto para el Colimbo chico. Además, las tasas de migración por hora aumentaron al aumentar el vector de viento (es decir, un viento de cola) para las tres especies de negrones, pero disminuyeron al aumentar el vector de viento para las dos especies de colimbos. Las tasas de migración de negrones alcanzaron su punto máximo diariamente entre las 11:00 y las 13:00 UTC, pero no encontramos un pico diario para ninguna de las especies de colimbos. Las tasas pico de migración por hora del Negrón americano y costero ocurrieron del 12 al 26 de abril, pero las tasas de migración del Negrón aliblanco y ambas especies de colimbos continuaron aumentando a lo largo de nuestra ventana de monitoreo de la migración. Finalmente, no encontramos cambios en las tasas de migración por hora a lo largo del tiempo para ninguna de nuestras especies focales, lo que sugiere que no hubo cambios en la abundancia durante los 18 años de recopilación de datos. Nuestro estudio revela la importancia y utilidad de las estaciones de observación costera a largo plazo, y recomendamos su financiamiento continuo y su uso como valiosas fuentes de datos de monitoreo. Table S1. List of 72 a priori candidate models used to evaluate the relationship between hourly migration rate (MR) and parameters (wind vector [WVec], tide height [TH], hour of day [Hour], migration week [MW], and year [Year]). Table S2. Parameter likelihoods (Lik), model-averaged parameter estimates (Est), and unconditional standard errors (μSE) for each of our five focal waterfowl species (Surf Scoter [Melanitta perspicillata], White-winged Scoter [M. deglandi], Black Scoter [M. americana], Red-throated Loon [Gavia stellata], and Common Loon [G. immer]) migrating past the Point Lepreau Bird Observatory over 659 days between March 30–May 9, 2000–2017 (N = 2781 h), describing the relationship between hourly migration rate and environmental conditions (wind vector [WVec], tide height [TH], hour of day [Hour], migration week [MW], and Year [Year]). Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".