DOI: 10.5061/dryad.p5hqbzkxd
title: Movement of juvenile migratory birds from settlement to adulthood across the non-breeding range

description: Among migratory vertebrates, high levels of fidelity to non-breeding sites
 during adulthood are common. If occupied sites vary in quality, strong
 site-fidelity can have profound consequences for individual fitness and
 population demography. Given the prevalance of adult site-fidelity, the
 regions of the non-breeding range to which juveniles first migrate, and
 the scale of any subsequent movements, are likely to be pivotal in shaping
 distributions and demographic processes across population ranges. However,
 inherent difficulties in tracking migratory individuals through early life
 mean that opportunities to quantify juvenile settlement and movements
 across non-breeding ranges, and the mechanisms involved, are extremely
 rare.Through long-term, range-wide resightings of hundreds of
 colour-marked individuals from their first migration to adulthood, and
 application of state-space models, we quantify levels of juvenile and
 adult regional-scale movements and distances at different life stages
 across the whole non-breeding distribution range in a migratory shorebird,
 the Black-tailed Godwit (Limosa limosa islandica). We show that the
 probability of individuals changing non-breeding regions (seven historical
 wintering regions spanning the Western Europe range) at all ages are very
 low (mean movement probability = 10.9% from first to subsequent winter,
 and 8.3% from first adult winter to later winters). Movement between
 regions was also low between autumn and winter of the same year for both
 juveniles (mean movement probability = 17.0%) and adults (10.4%). The
 great majority of non-breeding movements from the first autumn to
 adulthood were within regions and less than 100 km. The scarcity of
 regional-scale non-breeding movements from the first autumn to adulthood
 means that the factors influencing where juveniles settle will be key
 determinants of non-breeding distributions and of the rate and direction
 of changes in distributions.
description: # **Movement of juvenile migratory birds from settlement to adulthood
 across the non-breeding range**
 [https://doi.org/10.5061/dryad.p5hqbzkxd](https://doi.org/10.5061/dryad.p5hqbzkxd) The data consists of resighting histories of individually-marked Black-tailed Godwits (Limosa limosa islandica). Birds were caught as unfledged chicks or adults under license in several countries across the range of the population from 1994 to 2013 and resighted across the range over the same period. Movement probabilities at different ages were modeled in a state-space model. Please refer to the above paper for details on field methods and analyses. Dataset provides 1) Movement histories of individual birds 2) Coding of regions for the analysis 3) Maximum distances (in km) moved by individuals between key life-history stages and 4) Script for data processing and model fitting.  Description of the data and file structure: The dataset and analysis script consists of four files. These are numbered 1-4 below. First 3 are data input files and number 4 is the R-script for sorting the data and running the models. Below is a general description of the data files and the coded variables in each dataset.  **1) "all_movement_data.csv"** The data file ‘all_movement_data.csv’ contains the raw observation data, structured in the form of dated individual observation events for each godwit in the sample. Individuals are uniquely assigned numeric identifier codes according to their color-ring combination. Data also includes the region code, latitude and longitude, date and the age of the individual as recorded by the observer (EURING numeric age codes). -coding of variables in this dataset:  a) "age_filled": This is the Euring age code (see here: [https://www.bto.org/sites/default/files/u17/downloads/about/resources/agecodes.pdf](https://www.bto.org/sites/default/files/u17/downloads/about/resources/agecodes.pdf)) b) "date": Date of encounter of the bird c) "N": North co-ordinate d) "W*_*E": East/west co-ordinate e) "region": Code for region in W-Europe where the individual was located at the encounter -regions are: Eng: England, Wal: Wales, Neth: Netherlands, Fra: France, Mor: Morocco, Ire: Ireland, Spa: Spain, Por: Portugal, Bel: Belgium, Ice: Iceland, Jersey: Jersey, Ger: Germany, Sco: Scotland, Nor: Norway, Den: Denmark f) "individual": Code for individual  **2) "settlements_regioncodes.csv**" The data file ‘settlements_regioncodes.csv’ contains the information used to assign individual observations to the 8 geographic regions between which movement transitions are modelled (i.e. the model states), on the basis of their observed region codes. -coding of variables in this dataset: a) "lon": longitude of the centroid of the region where an individual was encountered b) "lat": latitude of the centroid of the region where an individual was encountered c) "region": Code for region in W-Europe where the individual was located at the encounter d) "state": Code for the region or state where an individual was encountered **3) "individual_movement_distances.xls**" This dataset contains maximum distances moved by individuals between key life-history stages. It gives the maximum distance moved between life history stages in km. Life-history stages are: 1a_1w: first autumn to first winter, 1w-2w: first winter to second winter, 1a_adult: first autumn to first or later adult winters. -coding of variables in this dataset: a) "individual": Code for individual b) "max_dist_moved" Maximum distance moved by individuals between life stages in km.  c) "lifestage": Code for life history stages between which maximum distance moved was measured; 1a_1w: first autumn to first winter, 1w-2w: first winter to second winter, 1a_adult: first autumn to first or later adult winters. **4) "godwit_final_model.R"** The file ‘godwit_final_model.R’ contains all R codes needed to process the raw data and fit the multistate survival-movement models. The script reads in the appropriate data files, performs data cleaning and generates the necessary data structures (observation history matrices) to fit the models. The code calls several R packages which must be installed prior to running, as well as JAGS 4.3.0 (the program used to fit the models) which must also be installed on the computer in order for the script to successfully execute. The code creates and writes output files containing the survival, movement and detection probabilities, as well as information about convergence and model goodness of fit. **Code/Software** R is required to run the "godwit_final_model.R" script. Annotations are provided throughout the script.