DOI: 10.5061/dryad.1zcrjdfz0
title: Climate change does not equally affect temporal patterns of natural selection on reproductive timing across populations in two songbird species

description: Climate change has led to changes in the strength of directional selection
 on seasonal timing. Understanding the causes and consequences of these
 changes is crucial to predicting the impact of climate change. But are
 observed patterns in one population generalisable to others, and can
 spatial variation in selection be explained by environmental variation
 among populations? We used long-term data (1955–2022) on blue and great
 tits co-occurring in four locations across the Netherlands to assess
 inter-population variation in temporal patterns of selection on laying
 date. To analyse selection, we combine reproduction and adult survival
 into a joined fitness measure. We found distinct spatial variation in
 temporal patterns of selection which overall acted towards earlier laying,
 and which was due to selection through reproduction rather than through
 survival. The underlying relationships between temperature, bird and
 caterpillar phenology were however the same across populations, and the
 spatial variation in selection patterns is thus caused by spatial
 variation in the temperatures and other habitat characteristics to which
 birds and caterpillars respond. This underlines that climate change is not
 necessarily equally affecting populations, but that we can understand this
 spatial variation, which enables us to predict climate change effects on
 selection for other populations.
description: Long-term data on breeding birds were collected by regular nest
 checks and by capturing and ringing birds. Data on caterpillar biomass was
 collected using frass nets. All data was stored in an
 relational SQL database and analysed using R.
description: Excel & R
description: Climate change does not equally affect temporal patterns of natural
 selection on reproductive timing across populations in two songbird
 species --- There are 8 EXCEL files: **1\.
 Tbl\_Fitness\_GT\_HVVLOHLBWH\_FirstClutches:** This file provides the
 breeding data of blue and great tits of four study areas. For each brood,
 it contains information about mother's identity, laying dates, brood
 size and whether manipulations were made. Area Four study areas Species
 Two species YearOfBreeding Year of breeding Mother Ring ID of female
 parent of the brood LayDateApril Date of first egg of first brood of the
 year for that mother (in April days, 1 April = day 1) ClutchSize Number of
 eggs laid within one clutch NumberFledged Number of chicks that fledged
 NumberFlededDeviation The number gives the number of chicks that might
 have fledged in addition to the number given in column
 "NumberFledged". The best estimate of the actual number of
 fledged chicks is: NumberFledged + 0.5 \* NumberFledgedDeviation
 NumberRecruitsAllBroodsSummed Number of recruiting offspring produced,
 summed over all broods of that year Include Is 1 if there has been no
 manipulation of the brood, otherwise is 0 **2\.
 Qry\_survival\_04\_Survial\_output:** This file contains information about
 the survival of each breeding female for all four blue and great tit
 populations. RingNumberFemale Ring numbers of the breeding females
 BroodYear Year Area Four study sites Species Great or blue tit LayDate
 Date of first egg of first brood of the year for that mother (in April
 days, 1 April = day 1) Survival 0-survival means bird has not been seen
 again, 1-survival means bird survived/was seen again **3\.
 tbl\_PeakDate\_Biomass\_AllAreas\_AllSpecies:** This file contains data on
 the caterpillar biomass and the dates, where biomass reached its maximum,
 i.e. peak date. AreaName Four study areas Year Year MidDate Date of
 maximum of the caterpillar biomass (in April days, 1 April = day 1)
 MaxBiom Maximum biomass on peak date in [g/(day \* m²)] **4\.
 Tbl\_budburst\_HV which:** This file gives the annual average date of bud
 burst of oak trees at the Hoge Veluwe. AreaShortName Only data on Hoge
 Veluwe (= HV) Year Year AprilAVG Average April day of oak bud burst (1
 April= day 1) SumOfTrees Total number of trees measured in that year **5\.
 Tbl\_BeechCropIndex:** This file gives the beech crop index at the Hoge
 Veluwe. The index is a 3-point scale categorizing the amount of beech nuts
 into low, intermediate and high crop. Year Year NoTreesSampled Total
 number of trees sampled in that year BeechCropNet Net beech crop in [g/m²]
 BCINet Scale of 1 to 3, grouping net beech crop into low (=1),
 intermediate (=2) and high (=3) **6\. Qry\_mark\_05\_input\_file:** This
 file was created as the input data for the survival analysis with RMark.
 It is a more condensed version of the first file
 (Tbl\_Fitness\_GT\_HVVLOHLBWH\_FirstClutches) and contains information on
 the identity of each breeding female and the timing of her broods.
 RingNumberFemale Ring numbers of breeding females BroodYear Year Area Four
 study sites Species Great or blue tit LayDate Date of first egg of first
 brood of the year for that mother (in April days, 1 April= day 1) **7\.
 deBilt\_1955\_2022:** This file contains the daily temperature data of the
 weather station "de Bilt" for years 1955 to 2022 as derived from
 the KNMI. Temperatures are given in 0.1 °C. STN = 260 Meteo Station =
 DeBilt YYYYMMDD Year - Month - Day TN Minimum daily temperature in [0.1
 °C] TX Maximum daily temperature in [0.1 °C] **8\.
 temp\_deKooy\_1955\_2022:** This file contains the daily temperature data
 of the weather station "de Kooy" for years 1955 to 2022 as
 derived from the KNMI. Temperatures are given in 0.1 °C. STN = 235 Meteo
 Station = DeKooy YYYYMMDD Year - Month - Day TN Minimum daily temperature
 in [0.1 °C] TX Maximum daily temperature in [0.1 °C] Data was derived from
 the following sources: Temperature data of both stations was derived from
 the KNMI (https://www.knmi.nl/nederland-nu/klimatologie/daggegevens).
 There are 3 separate, reproducible R-scripts using the data files listed
 above: 1. R\_script\_Mainanalysis Code to run all selection and phenology
 analyses and to create all figures (except Figure S3) from the main
 manuscript and the electronic supplementary material 2.
 R\_script\_climwin\_analysis Code to run the climate window analysis with
 package climwin to find the respective windows in the year in which
 temperatures are best correlated with either laying date or food peak date
 for all populations 3. R\_script\_Survival\_analysis Code to run the
 survival analyses with RMARK (note that program MARK is additionally
 needed to execute the R package RMARK) and to produce Figure S3 in the
 supplementary material