Continent‐Wide Drivers of Spatial Synchrony in Breeding Demographic Structure Across Wild Great Tit Populations
: Woodman, Joe P.; Vriend, Stefan J. G.; Adriaensen, Frank; Álvarez, Elena; Artemyev, Alexander; Barba, Emilio; Burgess, Malcolm D.; Caro, Samuel P.; Cauchard, Laure; Charmantier, Anne; Cole, Ella F.; Dingemanse, Niels; Doligez, Blandine; Eeva, Tapio; Evans, Simon R.; Grégoire, Arnaud; Lambrechts, Marcel; Leivits, Agu; Liker, András; Matthysen, Erik; Orell, Markku; Park, John S.; Rytkönen, Seppo; Senar, Juan Carlos; Seress, Gábor; Szulkin, Marta; van Oers, Kees; Vatka, Emma; Visser, Marcel E.; Firth, Josh A.; Sheldon, Ben C.
Publisher: Wiley
: 2025
: Ecology Letters
: Ecology Letters
: e70079
: 28
: 2
: 1461-023X
: 1461-0248
DOI: https://doi.org/10.1111/ele.70079
: https://doi.org/10.1111/ele.70079
: https://research.utu.fi/converis/portal/detail/Publication/484859069
Variation in age structure influences population dynamics, yet we have limited understanding of the spatial scale at which its fluctuations are synchronised between populations. Using 32 great tit populations, spanning 4° W–33° E and 35°–65° N involving > 130,000 birds across 67 years, we quantify spatial synchrony in breeding demographic structure (subadult vs. adult breeders) and its drivers. We show that larger clutch sizes, colder winters, and larger beech crops lead to younger populations. We report distance-dependent synchrony of demographic structure, maintained at approximately 650 km. Despite covariation with demographic structure, we do not find evidence for environmental variables influencing the scale of synchrony, except for beech masting. We suggest that local ecological and density-dependent dynamics impact how environmental variation interacts with demographic structure, influencing estimates of the environment's effect on synchrony. Our analyses demonstrate the operation of synchrony in demographic structure over large scales, with implications for age-dependent demography in populations.
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EA & EB from Spanish Ministry of Science and Innovation (PID2021-122171NB-I00/ AEI/10.13039/501100011033/ FEDER, UE); LC by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 838763; BD by the ANR (ANR-06-JCJC-0082-01 and ANR-19-CE2-0007); TE from Research Council of Finland (SA338180); JCS from Ministry of Science and Innovation, Spain, project CGL-2020 PID2020-114907GB-C21; GS by the National Research, Development and Innovation Office (FK-137743); MS from the Polish National Science Foundation (NCN) OPUS (2021/41/B/NZ8/04472); JAF from BBSRC (BB/S009752/1), NERC (NE/S010335/1 and NE/V013483/1); and BCS from ERC AdG250164 and UK Research and Innovation/UKRI (EP/X024520/1).
