Evol. Ecology of Variation

Head of the Group

Prof. Dr. Niels Dingemanse

Phone:+49 8157 932-424Fax:+49 8157 932-400

Homepage Dingemanse

Contact person

Ilse Bayer


Phone:+49 8157 932-375Fax:+49 8157 932-344


Research Group Evolutionary Ecology of Variation

Why study individual variation?

Individual variation represents a ubiquitous feature of animal populations, yet its evolutionary and ecological causation and consequences are poorly understood (Barber & Dingemanse 2010; Dingemanse & Wolf 2010; Réale et al. 2010). Classic evolutionary theory, for example, explains how negative frequency dependent selection can maintain a mix of ‘hawk’ and ‘dove’ strategies within the same population, but does not provide a compelling explanation for why individual animals consistently play either hawk or dove strategies. Similarly, classic theory explains why genetic variation in phenotypic plasticity might persist, but again does not explain why some individuals are consistently more responsive (i.e. plastic) compared to other animals of the same population (Dingemanse et al. 2010; Mathot et al. 2012). This very notion that novel adaptive theory is warranted for explaining patterns of between-individual variation in labile phenotypic attributes, like behaviour, metabolism, or physiology strongly fuels the research questions addressed in this research group: What are the evolutionary and ecological mechanisms that maintain phenotypic variation in labile phenotypic attributes within and between individuals? We address such types of questions particularly in the context of behaviour (e.g. Mathot et al. 2011), called “animal personality” or “behavioural syndrome” research in the recent behavioural ecology literature.

Does individual variation matter?

For evolutionary processes – Accumulating evidence from a wide variety of taxa implies that natural animal populations consist of individuals that differ from one another in suites of correlated behaviours. For example, certain individuals are more aggressive in a range of biological contexts compared to other individuals from the same population, where relatively aggressive types typically also differ in a whole range of other behavioural and physiological characteristics, such as boldness  (e.g. Dingemanse et al. 2007) or metabolism. Evolutionary theory predicts that trait correlations can strongly alter the cause of evolution, specifically when they are genetically underpinned. Using tools developed in evolutionary biology, particularly quantitative genetics, we quantify correlations between labile phenotypic attributes (such as between behaviour and metabolism) and investigate the contribution of between- and within-individual correlations, such as genetic correlations and correlational plasticity, respectively (e.g. Dingemanse et al. 2007, 2012a; Mutzel et al. 2011) We ask whether the very existence of such individual (co)variation matters for evolutionary processes: Can correlation structure between labile phenotypic attributes constrain the evolutionary trajectories available to populations? Are correlation structures fixed, or do they vary as a function of population or environmental factors (Dingemanse et al. 2007, 2009, 2012a)?

For ecological processes – The ecological consequences of between-individual variation are particularly understudied but likely formidable. For example, modelling studies imply that the existence of individual variation in sociability can greatly affect the speed at which biological invasions spread, that the existence of genetic variation in trustworthiness can select for individual variation in sampling strategies, and that social environments strongly interact with individual phenotypes to determine fitness. We currently address such types of questions by means of large-scale repeated measures data collection of behavioural traits (such as aggressiveness) for large numbers of natural populations and individuals, and specifically study how social environments (both in a competitive and cooperative context) affect individual fitness as well as ecological processes such as settlement decisions and dispersal, and how such patterns interact with ecological parameters such as perceived predation risk and population density.

Model systems

Our research is primarily empirically oriented, and involves both descriptive and experimental approaches to study individual variation in an evolutionary and ecological context. We mostly use the great tit (Parus major), a common cavity-breeding passerine bird, as a model. Our primary study system consists of twelve nest box populations of great tits within a 15 by 25 km2 area situated between the Ammer- and Starnbergersee. Those populations are monitored using standard field methods to acquire life-history data of all breeding birds, such as lay date, clutch size, age of first reproduction, annual adult survival, and genetic parentage. In the breeding season, in addition, each individual male is subjected to a number of standardized territorial intrusions (i.e. aggression tests) both during the egg laying and incubation phase as part of the standard protocol. All adults are captured during the chick-feeding phase and subjected to a portable field activity test. In winter (November/December and January/February), birds that use our boxes for roosting are subjected to a classic laboratory test which measures exploration behaviour, a repeatable and heritable trait in west-European wild great tit populations (Dingemanse et al. 2012b). We use passive integrated transponders (PIT-tags; Nicolaus et al. 2008) to study foraging behaviour in winter and its between-individual and within-individual associations with metabolism and above-mentioned behaviours at artificial feeding stations fitted with automatic readers.

Empirical data collection has a strong seasonal component, with concentrated fieldwork periods occurring in early (November-December) and late (January-February) winter as well as spring (April- August), and is done with the help of many hands (PhD-students, postdocs, MSc-students, and temporary field assistants), directed by our technical assistant and data-manager Jan Wijmenga.

Publications of the Group

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