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Data from: Cascading effects of climate variability on the breeding success of an edge population of an apex predator


Gangoso, Laura et al. (2020), Data from: Cascading effects of climate variability on the breeding success of an edge population of an apex predator, Dryad, Dataset,


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 ( between 2012 and 2017 on Alegranza, Canary Islands, Spain.

4. Matlab code for the trajectory model. Code by W. Bouten.


Usage Notes

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 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.


Cabildo Insular de Lanzarote

European Social Fund

Marie Sklodowska-Curie Fellowship from the European Commission , Award: 747729, ”EcoEvoClim”

Cabildo Insular de Lanzarote

Marie Sklodowska-Curie Fellowship from the European Commission, Award: 747729, ”EcoEvoClim”