DOI: 10.6084/m9.figshare.27079090
title: Data and code for <b>Environmental correlates of spatio-temporal patterns of colour variation in a highly variable bird of prey: the Common Buzzard (</b><i>Buteo buteo</i><b>)</b>

description: <b>R code is split into four different scripts</b><b>1) Data assembly scripts.</b> This script compiles datasets to run spatial and temporal analyses. To run you will need the provided datafile "buteo.colour.data.sep24.csv" and to download environmental layers for climate, tree cover, soil type, gamma and UVB radiation from:Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., Zimmermann, N. E., Linder, H. P., & Kessler, M. (2017). Climatologies at high resolution for the earth’s land surface areas. <i>Scientific Data</i>, <i>4</i>(1), 1–20.Defries, R. S., Hansen, M. C., Townshend, J. R. G., Janetos, A. C., & Loveland, T. R. (2000). A new global 1-km dataset of percentage tree cover derived from remote sensing. <i>Global Change Biology</i>, <i>6</i>(2), 247–254. https://doi.org/10.1046/j.1365-2486.2000.00296.xhttps://soilgrids.orgBeckmann, M., Václavík, T., Manceur, A. M., Šprtová, L., von Wehrden, H., Welk, E., & Cord, A. F. (2014). glUV: A global UV-B radiation data set for macroecological studies. Methods in Ecology and Evolution, 5(4), 372–383. https://doi.org/10.1111/2041-210X.12168Tollefsen, T., Cort, M. D., Cinelli, G., Gruber, V., & Bossew, P. (2016). 07. Terrestrial gamma dose [Dataset]. European Commission, Joint Research Centre (JRC). http://data.europa.eu/89h/jrc-eanr-07_terrestrial-gamma-dose<br>0.data.assembly.R (this script obtaines environmental data for each observation as well as computing mean colour and environmental values and temporal effects per hexagonal cell)The final outcome of running these scripts are two datafiles:"buteo.colour.obs.hex.id.150.csv". This file is the same as "buteo.colour.data.sep24.csv", but with an extra variable indicating the ID of the hexagonal cell for each observation and environmental variables (and subsetted to contain only observations between 2000-2022). See variable description below. This is the file used in the spatial analyses (script “1.spatial.analyses.R)."buteo.colour.climate.hex.150.Rds". This file contains data in the right format to carry out temporal meta-analyses and plot spatial variation on the map (scripts: 2.temporal.meta.analyses.R, 3.temporal.meta.analyses.colour.SD.R, 4.plot.maps.R). Each row contains colour, environmental and temporal summaries for each hexagonal cell. See variable descriptions below.<b>2) Spatial analysis script.</b> (1.spatial.analyses.R) This script runs the spatial models on all four colour variables. This script also produces a file of spatially thinned subsets of the data (thinned.locs.10.RDS). As this step is very time consuming we provide this file as well (also for reproducibility since re-computing this file will yield slightly different datasets each time).<b>3) Temporal analysis script.</b> (2.temporal.meta.analyses.R) This script runs the meta-analyses of temporal effects for the four colour variables.<b>4) Temporal analysis script for colour SD. </b>(3.temporal.meta.analyses.colour.SD.R)<b> </b>Extra script running meta-analysis of temporal variation in colour SD.**********************************************************<b>Description of variables in datasets</b><b>buteo.colour.data.sep24.csv</b>#VARIABLES and explanation#id# row idsighting_id #individual identifier of sighting#observer_id #individual identifier of observer#lat #latitude#long #longitude#date #observation date#coloration_code #colour of the observed buzzard (1-7)#country #country of observation, for descriptive purposes only some observations do not have country#dataset #dataset identifier#month #month of observation#year #year of observation#<br><br><br>########################################################<b>buteo.colour.obs.hex.id.150.csv</b>#This dataset has the following variables:#VARIABLES and explanation#id# general observation id#sighting_id# sighting if within each dataset#observer_id# observer id#date# date of observation#coloration_code# colour score of observed buzzard (1-7)#country# country of observation (when available)#dataset# dataset id#month# observation month#year# observation year#dark.yn# 0/1 whether the observation corresponds to a dark buzzard (colour score: 1-2)#light.yn# 0/1 whether the observation corresponds to a intermediate buzzard (colour score: 3-5)#int.yn# # 0/1 whether the observation corresponds to a light buzzard (colour score: 6-7)#hex_id# hexagon id for the observation#geometry# geometry of 5km radius area around observation#lat# original latitude of observation#long# original longitude of observation#bio_1# average annual mean temperature for observation location#bio_12# average annual precipitation for observation location#tree_cover# average forest cover for observation location#UVB# average UVB radiation for observation location#andosol# average proportion of andosol for observation location#gamma# average gamma radiation for observation location#X# transformed longitude#Y# transformed latitude<br>##########################################################<b>Dataset: buteo.colour.climate.hex.150.Rds</b>#This dataset has the following variables#VARIABLES and explanation<br>#hex_id# hexagon identifier<br>#mean_col# mean colour within hexagon#prop_d# proportion of dark buzzards in hexagon#prop_i# proportion of intermediate buzzards in hexagon#prop_l# proportion of light buzzards in hexagon<br>#n# number of observations within hexagon#min.year# minimum year of observations#max.year# maximum year of observations#grid.size# distance between adjacent hexagon centres<br>#x geometry# polygon for each hexagon#long# hexagon centroid longitude#lat# hexagon centroid latitude#long.wgs84# hexagon centroid longitude WGS84#lat.wgs84# hexagon centroid latitude WGS84<br>#bio_1# average annual mean temperature within hexagon#bio_12# average annual precipitation within hexagon#tree_cover# average tree cover within hexagon#UVB# average UVB radiation within hexagon#andosol# proportion of andosols within hexagon#gamma# average gamma radiation within hexagon<br>#mean_col_est# model estimate of mean colour within hexagon#mean_col_est_se# SE for previous estimate#mean_col_y_slope# year slope for mean colour within hexagon#mean_col_y_slope_se# SE for previous estimate#formula# formula used to model temporal variation in mean colour#mean_col_converged# whether model converged or not#mean_col_hess# whether hessian matrix was positive-definite<br>#prop_d_est# model estimate for proportion dark within hexagon#prop_d_est_se# SE for previous estimate#prop_d_y_slope# year slope for proportion dark within hexagon#prop_d_y_slope_se# SE for previous estimate#prop_d_formula# formula used to model temporal variation in prop. dark#prop_d_converged# whether model converged or not#prop_d_hess# whether hessian matrix was positive-definite<br>#prop_i_est# model estimate for proportion intermediate within hexagon#prop_i_est_se# SE for previous estimate#prop_i_y_slope# year slope for proportion intermediate within hexagon#prop_i_y_slope_se# SE for previous estimate#prop_i_formula# formula used to model temporal variation in prop. intermediate#prop_i_converged# whether model converged or not#prop_i_hess# whether hessian matrix was positive-definite<br>#prop_l_est# model estimate for proportion light within hexagon#prop_l_est_se# SE for previous estimate#prop_l_y_slope# year slope for proportion light within hexagon#prop_l_y_slope_se# SE for previous estimate#prop_l_formula# formula used to model temporal variation in prop. light#prop_l_converged# whether model converged or not#prop_l_hess# whether hessian matrix was positive-definite<br>#year.slope.temp# slope of yearly change in temperature within hexagon#se.year.slope.temp# SE of slope of yearly change in temperature within hexagon#year.slope.prec# slope of yearly change in precipitation within hexagon#se.year.slope.prec# SE of slope of yearly change in precipitation within hexagon#year.slope.tree# slope of yearly change in forest cover within hexagon#se.year.slope.tree# SE of slope of yearly change in forest cover within hexagon#year.slope.uv# slope of yearly change in UVB within hexagon#se.year.slope.uv# SE of slope of yearly change in UVB within hexagon<br><br><br><br><br><br>