DOI: 10.5061/dryad.z08kprrm8
title: Data from: A new trophic specialization buffers a top predator against climate-driven resource instability

description: Intraspecific phenotypic variability is key to respond to environmental
 changes and anomalies. However, documenting the emergence of behavioral
 diversification in natural populations has remained elusive due to the
 difficulty of observing such phenomenon at the right time and place. Here,
 we investigated how the emergence of a new trophic strategy in a
 population subjected to high fluctuations in the availability of its main
 trophic resource (migrating songbirds) affected the breeding performance,
 population structure, and population fitness of a specialized color
 polymorphic predator, the Eleonora's falcon from the Canary Islands.
 Using long-term data (2007-2022), we found that the exploitation of an
 alternative prey (a local petrel species) was associated with the growth
 of a previously residual falcon colony. Pairs in this colony laid earlier
 and raised more fledglings than in the other established colonies. The
 specialization on petreles increased over time, independently of annual
 fluctuations in prey availability. Importantly, however, the positive
 effect of petrel consumption on productivity was stronger in years with
 lower food availability. This trophic diversification was further
 associated with the genetically-determined color morph, with dark
 individuals preying more frequently on petreles than pale ones, which
 might promote the long-term maintenance of genotypic and phenotypic
 diversity. We empirically demonstrate how the emergence of an alternative
 trophic strategy can buffer populations against harsh environmental
 fluctuations by stabilizing their productivity.
description: The Eleonora's falcon population from the Canary Islands was
 intensively monitored during July-October 2007-2022. Every year and for
 each nest-site, we recorded the color morph of both parents using a
 spotting scope.We visited nests (range = 73-113 nests/year) on at least 2
 occasions each year, first to quantify clutch size, and posteriorly to
 determine the final number of fledged offspring. Laying date (where 1 =
 July 1<sup>st</sup>) was calculated by substracting 30 days
 (the duration of the incubation period) to the hatching date of the older
 chick within a brood, which was calculated after measuring nestling wing
 length to estimate their age using the formula provided by Ristow and Wink
 (2004).The number of fledglings was estimated as the final number of
 fledged offspring from each nest. Mean annual productivity of the
 population was estimated as the number of fledglings divided by the number
 of breeding pairs monitored. We recorded the number of petrels hunted by
 quantifing the number of intact wing pairs that falcons do not consume
 within a 5-m radius of the nest-site by inspecting the nest and nearby
 larders. We calculated food availability during
 September (the chick-rearing period in Eleonora's falcon) for every
 study year using the intensity of easterly winds across the migratory
 corridor that connects Europe (southwest Iberian Peninsula) and the Canary
 Islands. These wind patterns have proven to control the number os
 migratory birds arriving to Alegranza during the falcons' breeding
 season, explaining 70% of the variation in annual productivity (see
 Gangoso et al. 2020 for details). We calculated the mean easterly wind
 intensity as a proxy of overall food availability.
description: # Gangoso, L., Viana, D.S., Merchán, M., Figuerola, J. 2024. Data from: A
 new trophic specialization buffers a top predator against climate-driven
 resource instability. Behavioral Ecology.
 ## Description of the data
 and file structure Data used is included in two tab delimited txt files:
 Dataset_petrel and Winds_daily_Sep_2007-2022. 1. Dataset_petrel was used
 to analyze 1) whether the number of petrels hunted by male Eleonora’s
 falcons throughout the breeding period is associated with their color
 morph and the breeding colony, 2) whether the exploitation of an
 alternative food resource (i.e., petrels) is associated with variation in
 the laying date, and 3) whether variation in productivity is related to
 the number of seabirds consumed (petrels) and/or laying date. The dataset
 contains 9 columns: 1. **nest**: nest ID 2. **petrel_num**:
 number of petrels recorded in each nest site 3. **colony**: name of the
 breeding colony where the nest was located (C = Caldera, R = Rapalobos, N
 = North). 4. **year**: year of study 5. **male**: male color morph (D =
 dark, P = pale) 6. **female**: female color morph (D = dark, P = pale) 7.
 **clutch_size**: number of eggs laid 8. **fledglings**: number of fledged
 offspring 9. **laying.julian**: laying date, where 1 = July 1st
 1. Winds_daily_Sep_2007-2022 was used to analyze 1) whether
 the number of all prey items delivered to nestlings throughout the
 breeding season was associated with the male color morph and the colony,
 while accounting for the availability of food and food demands, and 2)
 whether the effect of petrels on per nest reproductive success depended on
 the availability of food during the breeding season. The dataset contains
 4 columns: 1. **date2**: date 2. **year**: year of study 3.
 **u.wind**: u_wind patterns (the west–east component, m/s) registered
 daily across the migratory flyway connecting southern Europe and the
 Canary Islands at a spatial resolution of 0.75 × 0.75°. 4. **v.wind**:
 v_wind patterns (the south-north component, m/s) registered daily across
 the migratory flyway connecting southern Europe and the Canary Islands at
 a spatial resolution of 0.75 × 0.75°. ## Code/Software The annotated R
 script used in the study Gangoso et al. "A new trophic specialization
 buffers a top predator against climate-driven resource instability"
 is provided. The R packages used are: "lme4" Bates D, Mächler M,
 Bolker B, Walker S (2015). “Fitting Linear Mixed-Effects Models Using
 lme4.” Journal of Statistical Software, 67(1), 1–48.
 doi:10.18637/jss.v067.i01. "MASS" Venables WN, Ripley BD (2002).
 Modern Applied Statistics with S, Fourth edition. Springer, New York. ISBN
 0-387-95457-0, .
 "raster" Hijmans R (2024). raster: Geographic Data Analysis and
 Modeling. R package version 3.6-27, .
 "ggplot2" Wickham H (2016). ggplot2: Elegant Graphics for Data
 Analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4,
 . "ggpubr" Kassambara, A.
 (2022). Ggpubr: ‘Ggplot2’ Based Publication Ready Plots.
 
 "tidyr" Wickham H, Vaughan D, Girlich M (2023). tidyr: Tidy
 Messy Data. R package version 1.3.0,
 ,
 . "dplyr" Wickham H, François
 R, Henry L, Müller K, Vaughan D (2023). dplyr: A Grammar of Data
 Manipulation. R package version 1.1.4,
 ,
 . "hexbin" Carr D, Lewin-Koh
 pbN, Maechler M, Sarkar ccolfwbD (2023). *hexbin: Hexagonal Binning
 Routines*. R package version 1.28.3,
 .