DOI: 10.5061/dryad.9cnp5hqvm
title: Data from:Using a large citizen science dataset to uncover diverse patterns of elevational migration in Himalayan birds

description: Elevational migration is well-documented in montane birds, yet large-scale
 patterns outside the Americas remain understudied. Using eBird data, we
 analysed the elevational ranges of 377 Himalayan bird species across
 breeding and non-breeding periods. We describe five elevational migration
 patterns which broadly include post-breeding upslope and downslope
 migration. Most high elevation breeders (65-75%) were downslope migrants,
 which were further subdivided into four distinct patterns: “displace”,
 “shift”, “expand”, and “contract”. Notably, 30% of species show partial
 migration (expand and contract). The same species often show different
 migration patterns in the eastern and western Himalayas indicating
 significant intraspecific variation, determined by local biotic and
 abiotic conditions. Specialised dietary guilds like invertivores were more
 likely to show shift or displace migration, potentially tracking
 seasonally fluctuating food resources. Generalists like omnivores and
 human commensals were more likely to be resident. Species found in open
 habitats were also more likely to show shift and displace migration, as
 open habitats have more pronounced exposure to adverse climate conditions
 which many species are unable to withstand. Territorial birds were largely
 non-migratory, most likely to retain high quality breeding territories.
 These migration patterns, shaped by the bounded nature of mountain ranges
 is useful for understanding elevational migration globally.
description: This data is freely available on eBird (EBD Dataset) and data can
 be requested via https://ebird.org/data/download. Data uploaded are eBird (EBD) datasets up to the month of April 2024 for Bhutan and the Indian states of Himachal Pradesh, Uttarakhand, West Bengal, Sikkim, Arunachal Pradesh and the Union Territories of Jammu and Kashmir and Ladakh. The data was processed in RStudio, code for processing the data and reproducing the analysis in the manuscript has been uploaded.
description: # Using a large citizen science dataset to uncover diverse patterns of
 elevational migration in Himalayan birds ## Description of the data and
 file structure The data uploaded are the filtered (eBird_elev_2024.RData)
 and resampled and processed Rdata files (see processing information in the
 Code section below). All resampled data files start with
 "eBird_woNepal_resampled_" followed by
 "east_"/"west_", which represents whether the data is
 from the eastern or western Himalayas. It is then followed by
 "05"/"50"/"95", which represents the lower,
 centre, and upper limit of a species' elevational distribution. It
 ends with ".q1"/".q2"/".q3", which
 represents the first, second, and third quartile of sampling effort
 (number of checklists). eBird data sharing policy doesn't allow us to
 share the raw unprocessed data but it is free to download on their website
 mentioned below hence the data shared here are resampled and processed. We
 downloaded eBird (EBD) datasets up to the month of April 2024 for Bhutan
 and the Indian states of Himachal Pradesh, Uttarakhand, West Bengal,
 Sikkim, Arunachal Pradesh and the Union Territories of Jammu and Kashmir
 and Ladakh. Folder named "elevation" is the digital elevation
 model that was downloaded from SRTM. Subfolder titled "alt"
 contains the raster files needed for extracting elevations for a given set
 of latitudes and longitudes. This has been uploaded as supplementary
 information on Zenodo Folder named "trait" contains the AVONET
 and Sheard trait database with the different taxonomies (and mapping
 information). This has been uploaded as supplementary information on
 Zenodo. Subfolders include 1\) METADATA.csv: All necessary information
 needed to understand all the columns in the AVONET dataset 2\)
 Avonet_trait_birdlife.csv: AVONET trait data using birdlife international
 taxonomy 3\) Avonet_trait_ebird.csv: AVONET trait data using eBird
 taxonomy  4\) treenames.csv: AVONET trait data using taxonomy in BirdTree,
 the most recent global bird phylogeny (Jetz et al., 2012)
 5\) birdlife-ebird.csv: Mapping information for merging eBird and birdlife
 international taxonomy 6\) birdlife-treenames.csv: Mapping information for
 merging BirdTree and birdlife international taxonomy
 7\) ebird_taxonomy_v2023.csv: eBird taxonomy update for 2023 8\)
 Sheard_HWI.csv: dataset from Sheard et al., (2020) where territoriality
 information was extracted. Information on these databases can be found in
 papers given below AVONET: Tobias, J.A., Sheard, C., Pigot, A.L.,
 Devenish, A.J.M., Yang, J., Sayol, F., et al. (2022) AVONET:
 morphological, ecological and geographical data for all birds. Ecology
 Letters, 25, 581–597.
 [https://doi.org/10.1111/ele.13898](https://doi.org/10.1111/ele.13898)
 Sheard: Sheard, C., Neate-Clegg, M.H.C., Alioravainen, N. et al.
 Ecological drivers of global gradients in avian dispersal inferred from
 wing morphology. Nat Commun 11, 2463 (2020).
 [https://doi.org/10.1038/s41467-020-16313-6](https://doi.org/10.1038/s41467-020-16313-6) ## Sharing/Access information This data is freely available on eBird (EBD Dataset) and data can be requested via [https://ebird.org/data/download](https://ebird.org/data/download). ## Code/Software The analysis for this manuscript can be performed in three steps documented below - Steps one and two allow you to replicate the Rdata files that we have uploaded, please find the code on [https://github.com/vjjan91/elevMigration](https://github.com/vjjan91/elevMigration) 1. 03_eBird-data-processing.Rmd: Here, we processed the eBird by applying a number of filters and added elevation data 2. 04_resampling-analysis.Rmd: Following Tsai et al. (2020), we used a resampling protocol to estimate the centre, lower, and upper limit of a species' elevational distribution for 3 levels of sampling effort (number of checklists)- separately for east and west 3. Code_for_Analysis.R: Archived on zenodo and linked to this dataset, this code can be directly used with the Rdata files uploaded to reproduce the visualizations, chi square tests and ANOVA for the current paper. 4. Code_for_SensitivityAnalysis.R: Archived on zenodo and linked to this dataset, this code allows you to replicate the sensitivity analysis related to thresholds used and sample size in the current paper