DOI: 10.5061/dryad.2bvq83bxq
title: Data from: Satellite tracking of American Woodcock reveals a gradient of migration strategies

description: Diversity in behavior is important for migratory birds in adapting to
 dynamic environmental and habitat conditions and responding to global
 change. Migratory behavior can be described by a variety of factors that
 comprise migration strategies. We characterized variation in migration
 strategies in American Woodcock (Scolopax minor), a migratory gamebird
 experiencing long-term population decline, using GPS data from
 approximately 300 individuals tracked throughout eastern North America. We
 classified woodcock migratory movements using a step-length threshold, and
 calculated characteristics of migration related to distance, path, and
 stopping events. We then used principal components analysis (PCA) to
 ordinate variation in migration characteristics along axes that explained
 different fundamental aspects of migration, and tested effects of body
 condition, age-sex class, and starting and ending location on PCA results.
 The PCA did not show evidence for clustering, suggesting a lack of
 discrete strategies among groups of individuals; rather, woodcock
 migration strategies existed along continuous gradients driven most
 heavily by metrics associated with migration distance and duration,
 departure timing, and stopping behavior. Body condition did not explain
 variation in migration strategy during the fall or spring, but during
 spring adult males and young females differed in some characteristics
 related to migration distance and duration. Starting and ending latitude
 and longitude, particularly the northernmost point of migration, explained
 up to 61% of the variation in any one axis of migration strategy. Our
 results reveal gradients in migration behavior of woodcock, and this
 variability should increase the resilience of woodcock to future
 anthropogenic landscape and climate change.
description: This data set contains individual bird information from banding
 data, in addition to migration metrics calculated from GPS tracking data
 for American Woodcock during spring and fall migration. Code for running
 and exploring results of the principal components analysis is also
 included. Please visit the Eastern Woodcock Migration
 Research Cooperative website, woodcockmigration.org for more information about our GPS data collection methods. The raw data are also archived on Movebank (“American Woodcock Migration Ecology in Eastern North America”; Study ID 3515664596). Data from: Satellite tracking of American Woodcock reveals a gradient of migration strategies Sarah J. Clements, Liam A. Berigan, Alexander C. Fish, Rachel L. Darling, Amber M. Roth, Greg Balkcom, Bobbi Carpenter, Gary Costanzo, Jeffrey Duguay, Kayleigh Filkins, Clayton L. Graham, William Harvey, Michael Hook, Douglas L. Howell, Seth Maddox, Scott McWilliams, Shawn W. Mayer, Theodore C. Nichols, J. Bruce Pollard, Christian Roy, David Sausville, Colby Slezak, Josh Stiller, Jacob Straub, Mathieu Tetreault, Dawn Washington, Lisa Williams, Erik J. Blomberg
description: # Satellite tracking of American Woodcock reveals a gradient of migration
 strategies Data and code
 for principal components analysis investigating migration strategy in
 American woodcock. ## Description of the data and file structure The two
 provided files, "amwo_migration_metrics_spring_clean.rds" and
 "amwo_migration_metrics_fall_clean.rds" contain data summarizing
 individual information and migration metrics for spring and fall
 migrations, respectively. There is one row for each individual American
 woodcock. All continuous data, including ordinal dates, are scaled and
 centered. The columns are as follows: nstop=number of stopovers
 mig_duration=migration duration depart_time= departure date
 arrive_time=arrival date coast_dist_km= mean distance from coast
 mig_dist_km=total migration distance straight_dist_km=distance from first
 to last point of migration sex= sex, f for female, m for male age=age,
 Adult or Young start_lat=starting latitude start_lon=staring longitude
 end_lat=ending latitude end_lon=ending longitude body_cond_index=body
 condition index year=year stop_duration=mean duration of stopping events
 dist_difference= difference between mig_dist_km and straight_dist_km ##
 Sharing/Access information More information about the American woodcock
 movement data can be found at woodcockmigration.org Data was derived from
 the following sources: * Raw Woodcock movement GPS data are archived on
 Movebank (“American Woodcock Migration Ecology in Eastern North America”;
 Study ID 3515664596) ## Code/Software The attached R script contains code
 for running the analysis in addition to plots for exploring results.