DOI: 10.5061/dryad.0rxwdbrx5
title: Data from: Cascading effects of climate variability on the breeding success of an edge population of an apex predator

description: 1. Large-scale environmental forces can influence biodiversity at
 different levels of biological organization. Climate, in particular, is
 often associated to species distributions and diversity gradients.
 However, its mechanistic link to population dynamics is still poorly
 understood. 2. Here, we unraveled the full mechanistic path by which a
 climatic driver, the Atlantic trade winds, determines the viability of a
 bird population. 3. We monitored the breeding population of Eleonora’s
 falcons in the Canary Islands for over a decade (2007-2017) and integrated
 different methods and data to reconstruct how the availability of their
 prey (migratory birds) is regulated by trade winds. We tracked foraging
 movements of breeding adults using GPS, monitored departure of migratory
 birds using weather radar, and simulated their migration trajectories
 using an individual-based, spatially explicit model. 4. We demonstrate
 that regional easterly winds regulate the flux of migratory birds that is
 available to hunting falcons, determining food availability for their
 chicks and consequent breeding success. By reconstructing how migratory
 birds are pushed towards the Canary Islands by trade winds, we explain
 most of the variation (up to 86%) in annual productivity for over a
 decade. 5. This study unequivocally illustrates how a climatic driver can
 influence local-scale demographic processes, while providing novel
 evidence of wind as a major determinant of population fitness in a top
 predator. 06-Jul-2020
description: 1. R code for the statistical analyses performed. Code by D.S.
 Viana. 2.  Migration Traffic Rate (MTR, birds
 km<sup>-1</sup> h<sup>-1</sup>). The file contains
 MTR data obtained by analyzing radar data from the weather radar of
 Loulé/Cavalos do Caldeirão (southwestern Portugal, 37º18′ N, 7º57′ W), see
 manuscript for details on data processing. Missing data from 2017 and
 missing values associated with radar maintenance tasks (N= 49 days in
 total) were filled by data imputation through a random forest
 algorithm. 3. GPS-tracking data from 12 adult male
 Eleonora’s falcons (<i>Falco eleonorae</i>) equipped with
 7.5-g solar-powered GPS trackers (www.UvA-BiTS.nl)
 between 2012 and 2017 on Alegranza, Canary Islands, Spain.
 4. Matlab code for the trajectory model. Code by W.
 Bouten.  
description: 2. Data used in the manuscript is provided in column
 “RadarMTR_imputed”. Imputed values are denoted as “1” in the column
 “missing/imputed values”. 3. Each file contains the
 date and time of the recorded position (GMT time; column
 "date_time") and the respective geographical coordinates
 (unprojected WGS84 decimal coordinates; columns "latitude" and
 "longitude") for a single individual (column
 “device_info_serial”: 1010, 1012, 1013, 2038, 2048, 2051, 2336, 2337,
 2341, 2368, 2378, and 2390) and year. 4. Fig3_2017a.m
 and functions rgb.m, suncycle.m, distWB.m contain the matlab code used to
 generate figure 3A. It calculates 10,000 tracks of migratory birds
 departing on the 26th September 2017 (day 43 in code), using ERA40 wind
 data at 925mbar altitude (stored in MeteoMatrix2017_925.mat). The
 coastline used in the figure is loaded from coast.mat, coast2.mat, and
 coast3.mat which are subsets of lines.shp file of
 http://openstreetmapdata.com/. Some parts of the code are commented out
 because they are not needed for the figure, but were used for the analysis
 of other seasons/days.