10.5061/DRYAD.0RXWDBRX5
Gangoso, Laura
0000-0002-6205-6769
University of Amsterdam
Viana, Duarte
German Center for Integrative Biodiversity Research
Dokter, Adriaan
Cornell University
Shamoun-Baranes, Judy
University of Amsterdam
Figuerola, Jordi
Estación Biológica de Doñana
Barbosa, Sergio
Portuguese Sea and Atmosphere Institute
Bouten, Willem
0000-0002-5250-8872
University of Amsterdam
Data from: Cascading effects of climate variability on the breeding
success of an edge population of an apex predator
Dryad
dataset
2020
bird migration
forward trajectory model
Trade Winds
wind-driven food availability
Cabildo Insular de Lanzarote*
European Commission
https://ror.org/00k4n6c32
Marie Sklodowska-Curie Fellowship from the European Commission *
747729, ”EcoEvoClim”
Cabildo Insular de Lanzarote
Marie Sklodowska-Curie Fellowship from the European Commission
747729, ”EcoEvoClim”
2020-08-03T00:00:00Z
2020-08-03T00:00:00Z
en
https://doi.org/10.1111/1365-2656.13304
20336096 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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
1. R code for the statistical analyses performed. Code by D.S. Viana. 2.
Migration Traffic Rate (MTR, birds km-1 h-1). 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 (Falco eleonorae) 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.
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.