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Woodman JP, Vriend SJG, Adriaensen F, Álvarez E, Artemyev A, Barba E, Burgess MD, Caro SP, Cauchard L, Charmantier A, Cole EF, Dingemanse N, Doligez B, Eeva T, Evans SR, Grégoire A, Lambrechts M, Leivits A, Liker A, Matthysen E, Orell M, Park JS, Rytkönen S, Senar JC, Seress G, Szulkin M, van Oers K, Vatka E, Visser ME, Firth JA, Sheldon BC. Continent-Wide Drivers of Spatial Synchrony in Breeding Demographic Structure Across Wild Great Tit Populations. Ecol Lett 2025; 28:e70079. [PMID: 39964053 PMCID: PMC11834383 DOI: 10.1111/ele.70079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Revised: 12/02/2024] [Accepted: 12/17/2024] [Indexed: 02/21/2025]
Abstract
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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Affiliation(s)
- Joe P. Woodman
- Edward Grey Institute of Field Ornithology, Department of BiologyUniversity of OxfordOxfordUK
| | - Stefan J. G. Vriend
- Department of Animal EcologyNetherlands Institute of Ecology (NIOO‐KNAW)Wageningenthe Netherlands
| | - Frank Adriaensen
- Evolutionary Ecology Group, Department of BiologyUniversity of AntwerpAntwerpBelgium
| | - Elena Álvarez
- ‘Cavanilles’ Institute of Biodiversity and Evolutionary BiologyUniversity of ValenciaPaternaSpain
| | - Alexander Artemyev
- Institute of Biology, Karelian Research CentreRussian Academy of SciencesPetrozavodskRussia
| | - Emilio Barba
- ‘Cavanilles’ Institute of Biodiversity and Evolutionary BiologyUniversity of ValenciaPaternaSpain
| | - Malcolm D. Burgess
- Centre for Research in Animal BehaviourUniversity of ExeterExeterDevonUK
| | - Samuel P. Caro
- Centre d'Ecologie Fonctionnelle et EvolutiveUniv Montpellier, CNRS, EPHE, IRDMontpellierFrance
| | - Laure Cauchard
- CNRS, Department of Biometry and Evolutionary Biology (LBBE)University of Lyon, University Lyon 1VilleurbanneFrance
- Anthropogenic Effects Research GroupSwiss Ornithological InstituteSempachSwitzerland
| | - Anne Charmantier
- Centre d'Ecologie Fonctionnelle et EvolutiveUniv Montpellier, CNRS, EPHE, IRDMontpellierFrance
| | - Ella F. Cole
- Edward Grey Institute of Field Ornithology, Department of BiologyUniversity of OxfordOxfordUK
| | - Niels Dingemanse
- Behavioural Ecology, Department of BiologyLudwig Maximilians University of MunichMartinsriedGermany
| | - Blandine Doligez
- Centre d'Ecologie Fonctionnelle et EvolutiveUniv Montpellier, CNRS, EPHE, IRDMontpellierFrance
- Department of Ecology and Genetics, Evolutionary Biology CentreUppsala UniversityUppsalaSweden
| | - Tapio Eeva
- Department of BiologyUniversity of TurkuTurkuFinland
| | - Simon R. Evans
- Edward Grey Institute of Field Ornithology, Department of BiologyUniversity of OxfordOxfordUK
- Centre for Ecology and ConservationUniversity of ExeterPenrynUK
| | - Arnaud Grégoire
- Centre d'Ecologie Fonctionnelle et EvolutiveUniv Montpellier, CNRS, EPHE, IRDMontpellierFrance
| | - Marcel Lambrechts
- Centre d'Ecologie Fonctionnelle et EvolutiveUniv Montpellier, CNRS, EPHE, IRDMontpellierFrance
| | - Agu Leivits
- Department of WildlifeEnvironmental BoardPärnuEstonia
| | - András Liker
- Behavioural Ecology Research Group, Center for Natural SciencesUniversity of PannoniaVeszprémHungary
- HUN‐REN‐Prince Edward Island Evolutionary Ecology Research GroupUniversity of PannoniaVeszprémHungary
| | - Erik Matthysen
- Evolutionary Ecology Group, Department of BiologyUniversity of AntwerpAntwerpBelgium
| | - Markku Orell
- Ecology and Genetics Research Unit, Faculty of ScienceUniversity of OuluOuluFinland
| | - John S. Park
- Edward Grey Institute of Field Ornithology, Department of BiologyUniversity of OxfordOxfordUK
| | - Seppo Rytkönen
- Ecology and Genetics Research Unit, Faculty of ScienceUniversity of OuluOuluFinland
| | | | - Gábor Seress
- Behavioural Ecology Research Group, Center for Natural SciencesUniversity of PannoniaVeszprémHungary
- HUN‐REN‐Prince Edward Island Evolutionary Ecology Research GroupUniversity of PannoniaVeszprémHungary
| | - Marta Szulkin
- Institute of Evolutionary Biology, Faculty of Biology, Biological and Chemical Research CentreUniversity of WarsawWarsawPoland
| | - Kees van Oers
- Department of Animal EcologyNetherlands Institute of Ecology (NIOO‐KNAW)Wageningenthe Netherlands
- Behavioural Ecology GroupWageningen University & Research (WUR)Wageningenthe Netherlands
| | - Emma Vatka
- Ecology and Genetics Research Unit, Faculty of ScienceUniversity of OuluOuluFinland
- Research Programme in Organismal and Evolutionary Biology, Faculty of Biological and Environmental SciencesUniversity of HelsinkiHelsinkiFinland
| | - Marcel E. Visser
- Department of Animal EcologyNetherlands Institute of Ecology (NIOO‐KNAW)Wageningenthe Netherlands
| | - Josh A. Firth
- Edward Grey Institute of Field Ornithology, Department of BiologyUniversity of OxfordOxfordUK
- School of BiologyUniversity of LeedsLeedsUK
| | - Ben C. Sheldon
- Edward Grey Institute of Field Ornithology, Department of BiologyUniversity of OxfordOxfordUK
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Gordon DM. The life history of harvester ant colonies. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230332. [PMID: 39463251 PMCID: PMC11528356 DOI: 10.1098/rstb.2023.0332] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Revised: 02/29/2024] [Accepted: 03/27/2024] [Indexed: 10/29/2024] Open
Abstract
A long-term study of a population of desert seed-eating ant colonies of the red harvester ant, Pogonomyrmex barbatus, in New Mexico, USA, shows that a colony can live for 20-30 years-the lifespan of its founding queen. A colony's collective behaviour shifts in the course of its life history. These changes, generated by social interactions within the colony, adjust the behaviour of the colony as it grows older and larger, in response to its environment and neighbouring colonies. A worker lives only a year and performs different tasks as it ages, in response to interactions with other workers and the local surroundings. A colony's behaviour changes-becoming more stable and consistent-as the colony grows older, with more ants to participate in social interactions. A neighbourhood of colonies, often of similar age, grows old together. Colonies differ in how they regulate foraging behaviour collectively to manage water loss. These differences influence how foragers of neighbouring colonies partition foraging area. In a harsh but stable environment, the gradual behavioural shifts over a colony's lifespan allow it to adjust to slow changes in the composition of its neighbourhood and in environmental conditions.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.
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Moiron M, Bouwhuis S. Age-dependent shaping of the social environment in a long-lived seabird: a quantitative genetic approach. Philos Trans R Soc Lond B Biol Sci 2024; 379:20220465. [PMID: 39463241 PMCID: PMC11513638 DOI: 10.1098/rstb.2022.0465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 05/31/2024] [Accepted: 07/24/2024] [Indexed: 10/29/2024] Open
Abstract
Individual differences in social behaviour can result in fine-scale variation in spatial distribution and, hence, in the social environment experienced. Given the expected fitness consequences associated with differences in social environments, it is imperative to understand the factors that shape them. One potential such factor is age. Age-specific social behaviour-often referred to as 'social ageing'-has only recently attracted attention, requiring more empirical work across taxa. Here, we use 29 years of longitudinal data collected in a pedigreed population of long-lived, colonially breeding common terns (Sterna hirundo) to investigate sources of variation in, and quantitative genetic underpinnings of, an aspect of social ageing: the shaping of the social environment experienced, using the number of neighbours during breeding as a proxy. Our analyses reveal age-specific declines in the number of neighbours during breeding, as well as selective disappearance of individuals with a high number of neighbours. Moreover, we find this social trait, as well as individual variation in the slope of its age-specific decline, to be heritable. These results suggest that social ageing might underpin part of the variation in the overall multicausal ageing phenotype, as well as undergo microevolution, highlighting the potential role of social ageing as a facilitator for, or constraint of, the evolutionary potential of natural populations.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.
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Affiliation(s)
- Maria Moiron
- Institute of Avian Research, Wilhelmshaven26386, Germany
- Department of Evolutionary Biology, Bielefeld University, Bielefeld33501, Germany
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Harrison LM, Churchill ER, Fairweather M, Smithson CH, Chapman T, Bretman A. Ageing effects of social environments in 'non-social' insects. Philos Trans R Soc Lond B Biol Sci 2024; 379:20220463. [PMID: 39463243 PMCID: PMC11513649 DOI: 10.1098/rstb.2022.0463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 01/29/2024] [Accepted: 01/30/2024] [Indexed: 10/29/2024] Open
Abstract
It is increasingly clear that social environments have profound impacts on the life histories of 'non-social' animals. However, it is not yet well known how species with varying degrees of sociality respond to different social contexts and whether such effects are sex-specific. To survey the extent to which social environments specifically affect lifespan and ageing in non-social species, we performed a systematic literature review, focusing on invertebrates but excluding eusocial insects. We found 80 studies in which lifespan or ageing parameters were measured in relation to changes in same-sex or opposite-sex exposure, group size or cues thereof. Most of the studies focused on manipulations of adults, often reporting sex differences in lifespan following exposure to the opposite sex. Some studies highlighted the impacts of developmental environments or social partner age on lifespan. Several studies explored potential underlying mechanisms, emphasizing that studies on insects could provide excellent opportunities to interrogate the basis of social effects on ageing. We discuss what these studies can tell us about the social environment as a stressor, or trade-offs in resources prompted by different social contexts. We suggest fruitful avenues for further research of social effects across a wider and more diverse range of taxa.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.
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Affiliation(s)
- Lauren M. Harrison
- School of Biological Sciences, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK
| | - Emily R. Churchill
- School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
| | - Megan Fairweather
- School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
| | - Claire H. Smithson
- School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
| | - Tracey Chapman
- School of Biological Sciences, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK
| | - Amanda Bretman
- School of Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
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Firth JA, Albery GF, Bouwhuis S, Brent LJN, Salguero-Gómez R. Understanding age and society using natural populations. Philos Trans R Soc Lond B Biol Sci 2024; 379:20220469. [PMID: 39463246 PMCID: PMC11513640 DOI: 10.1098/rstb.2022.0469] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2024] [Accepted: 10/01/2024] [Indexed: 10/29/2024] Open
Abstract
Ageing affects almost all aspects of life and therefore is an important process across societies, human and non-human animal alike. This article introduces new research exploring the complex interplay between individual-level ageing and demography, and the consequences this interplay holds for the structure and functioning of societies across various natural populations. We discuss how this Special Issue provides a foundation for integrating perspectives from evolutionary biology, behavioural ecology and demography to provide new insights into how ageing shapes individuals' social behaviour and social associations, and how this in turn impacts social networks, social processes (such as disease or information transfer) and fitness. Through examining these topics across taxa, from invertebrates to birds and mammals, we outline how contemporary studies are using natural populations to advance our understanding of the relationship between age and society in innovative ways. We highlight key emerging research themes from this Special Issue, such as how sociality affects lifespan and health, the genetic and ecological underpinnings of social ageing and the adaptive strategies employed by different species. We conclude that this Special Issue underscores the importance of studying social ageing using diverse systems and interdisciplinary approaches for advancing evolutionary and ecological insights into both ageing and sociality more generally.This article is part of the discussion meeting issue 'Understanding age and society using natural populations '.
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Affiliation(s)
- Josh A. Firth
- Faculty of Biological Sciences, University of Leeds, Leeds, UK
- Department of Biology, Oxford University, Oxford, UK
| | - Gregory F. Albery
- School of Natural Sciences, Trinity College Dublin, Dublin, Republic of Ireland
- Department of Biology, Georgetown University, Washington, DC, USA
| | | | - Lauren J. N. Brent
- Centre for Research in Animal Behaviour, University of Exeter, Exeter, UK
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Hasenjager MJ, Fefferman NH. Social ageing and higher-order interactions: social selectiveness can enhance older individuals' capacity to transmit knowledge. Philos Trans R Soc Lond B Biol Sci 2024; 379:20220461. [PMID: 39463239 PMCID: PMC11513644 DOI: 10.1098/rstb.2022.0461] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 02/18/2024] [Accepted: 03/18/2024] [Indexed: 10/29/2024] Open
Abstract
In long-lived organisms, experience can accumulate with age, such that older individuals may act as repositories of ecological and social knowledge. Such knowledge is often beneficial and can spread via social transmission, leading to the expectation that ageing individuals will remain socially well-integrated. However, social ageing involves multiple processes that modulate the relationship between age and social connectivity in complex ways. We developed a generative model to explore how social ageing may drive changes in social network position and shape older individuals' capacity to transmit knowledge to others. We further employ novel hypernetwork analyses that capture higher-order interactions (i.e. involving ≥ 3 participants) to reveal potential relationships between age and sociality that conventional dyadic networks may overlook. We find that older individuals in our simulations effectively facilitate transmission across a range of scenarios, especially when transmission resembles a complex contagion or when social selectivity (i.e. prioritization of key relationships) rapidly emerges with age. These patterns result from the formation of tight-knit sets of older associates that co-occur in multiple groups, thereby reinforcing one another's capacity to transmit knowledge. Our findings suggest key avenues for future empirical work and illustrate the use of hypernetworks in advancing the study of social behaviour.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.
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Affiliation(s)
- Matthew J. Hasenjager
- Intelligence Community Postdoctoral Research Fellowship Program, University of Tennessee, Knoxville, TN, USA
- Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN, USA
- National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, TN, USA
| | - Nina H. Fefferman
- Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN, USA
- National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, TN, USA
- Department of Mathematics, University of Tennessee, Knoxville, TN, USA
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Gamelon M, Araya-Ajoy YG, Sæther BE. The concept of critical age group for density dependence: bridging the gap between demographers, evolutionary biologists and behavioural ecologists. Philos Trans R Soc Lond B Biol Sci 2024; 379:20220457. [PMID: 39463250 PMCID: PMC11528359 DOI: 10.1098/rstb.2022.0457] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 03/11/2024] [Accepted: 04/03/2024] [Indexed: 10/29/2024] Open
Abstract
Density dependence plays an important role in population regulation in the wild. It involves a decrease in population growth rate when the population size increases. Fifty years ago, Charlesworth introduced the concept of 'critical age group', denoting the age classes in which variation in the number of individuals most strongly contributes to density regulation. Since this pioneering work, this concept has rarely been used. In light of Charlesworth's concept, we discuss the need to develop work between behavioural ecology, demography and evolutionary biology to better understand the mechanisms acting in density-regulated age-structured populations. We highlight demographic studies that explored age-specific contributions to density dependence and discuss the underlying evolutionary processes. Understanding competitive interactions among individuals is pivotal to identify the ages contributing most strongly to density regulation, highlighting the need to move towards behavioural ecology to decipher mechanisms acting in density-regulated age-structured populations. Because individual characteristics other than age can be linked to competitive abilities, expanding the concept of critical age to other structures (e.g. sex, dominance rank) offers interesting perspectives. Linking research fields based on the concept of the critical age group is key to move from a pattern-oriented view of density regulation to a process-oriented approach.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.
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Affiliation(s)
- Marlène Gamelon
- Laboratoire de Biométrie et Biologie Evolutive, UMR 5558, CNRS, Université Claude Bernard Lyon 1, Villeurbanne69622, France
| | - Yimen G. Araya-Ajoy
- Gjærevoll Centre for Biodiversity Foresight Analysis, Norwegian University of Science and Technology, TrondheimNO-7491, Norway
| | - Bernt-Erik Sæther
- Gjærevoll Centre for Biodiversity Foresight Analysis, Norwegian University of Science and Technology, TrondheimNO-7491, Norway
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