Data for "Movement patterns of foraging common terns breeding in an urban environment in coastal Virginia"

• Main Author: Daniel Catlin
• Format: Dataset
• Language: unknown
• Published: 2024
• Subjects: Biological sciences; Ecology; common tern; hidden Markov model (HMM) database; McClintock; Common tern
• Online Access: https://doi.org/10.7294/25569333.v1; https://figshare.com/articles/dataset/Data_for_Movement_patterns_of_foraging_common_terns_breeding_in_an_urban_environment_in_coastal_Virginia_/25569333

Common tern tracking data for analysis in R via the momentumHMM package: *REQUIRES R statistical software which is freely available here: https://cran.r-project.org. The package and data analysis are all within the R statistical framework. For information: [e-mail], reference COTE tracking project # R version 4.3.3 "Angel Food Cake". These are tracking data collected from 18 common terns that were nesting on the South Island of the HRBT tunnel. For full description of the model and the package, see the publication. Also see momentuHMM vignette: https://cran.r-project.org/web/packages/momentuHMM/vignettes/momentuHMM.pdf Also see: McClintock, BT, T Michelot. 2018. momentuHMM: R package for generalized hidden Markov models of animal movement. Methods in Ecology and Evolution 9: 1518–1530. Doi:10.1111/2041-210X.12995 Common tern tracking repeatability data: *REQUIRES R statistical software which is freely available here: https://cran.r-project.org. The package and data analysis are all within the R statistical framework. Data used for repeatability analysis. We quantified the proportion of the total variation in space associated with the Foraging state that was explained by within-individual level variation relative to among-individual variation. We used a nested, generalized linear mixed effects model (GLMM) to decompose the spatial variance of all model-assigned foraging locations into variance components attributed to variation within and among individuals at four levels. We specified this GLMM within R with the package ‘jagsUI’ to call JAGS. For each model, we generated posterior distributions from four chains of 50,000 iterations (thin = 2) with additional adapt and burn-in periods of 25,000 iterations each. Citation for the method used: Wolak, M.E., D.J. Fairbairn, and Y.R. Paulsen. 2012. Guidelines for estimating repeatability. Methods in Ecology and Evolution 3: 129–137. Analysis code for COTE movement study: This information can be found as supplemental materials to the manuscript. For information: ...