Atlantic salmon Life-history & behaviour In October 2020, I started a new postdoctoral position (two years, fixed) in Organismal and Evolutionary Biology Research Programme at the University of Helsinki, Finland (link). The research group is led by Prof. Craig Primmer, who is a world leading expert in functional, ecological and evolutionary genomics (link). In my new position, I am studying how genetically underpinned life-history strategies differ in their behavioral phenotypes by using Atlantic salmon (Salmo salar) as a model. Atlantic salmon is a great model system for genetic/genomic life-history research since in Salmon, variation in genomic region around vestigial-like family member 3 gene (vgll3) locus (in chromosome 25) explains around 40% of variation in age at maturation (Barson et al. 2015). Since behaviors are generally linked with life-history variation (Reale et al. 2010, Dammhahn et al. 2020, Laskowski et al. 2021), it is relatively straightforward to draw predictions on how different life-history genotypes differ in their behavioral phenotypes.
References: Barson NJ, Aykanat T, Hindar K, ....., Primmer, CR (2015) Sex-dependent dominance at a single locus maintains variation in age at maturity in salmon. Nature 528:405–408. Dammhahn M, Dingemanse NJ, Niemelä PT, Reale D (2018) Pace-of-life syndromes: a framework for the adaptive integration of behaviour, physiology and life history. Behavioral Ecology and Sociobioly 72, 132. Laskowski KL, Moiron M, Niemelä PT (2020) Integrating behavior in life-history: Allocation versus acquisition? Trends in Ecology and Evolution. Early View. Réale D, Garant D, Humphries MM, et al. (2010) Personality and the emergence of the pace-of-life syndrome concept at the population level. Phil. Trans. R Soc B 365:4051–4063.
Wild field crickets Selection acting on social responsiveness
I initiated my study population of wild field crickets, Gryllus campestris, in 2013 when I was awarded with independent research fellowship and started my work at the Ludwig-Maximilians University of München, Germany. With that population, I broadly study patterns of selection acting on social responsiveness and social behaviours. Field crickets fill all the key requirements to be an outstanding model in studies focusing on social responsiveness. Acoustic signals represent the main source of information about the structure of the social environment in field crickets; these sounds are used to signal competitive ability to males and attractiveness to females. A male field cricket signals (by means of rubbing their wings together) near the entrance of a burrow that it defends, and around which it mates with females (Figure 1). This particular territorial behavior allows me to measure a male’s acoustic signaling (by placing acoustic recorders at the burrow entrance) in the wild for nearly every day of a male’s adult live. Moreover, an automated surveillance system (based on RFID-technology) allows me to record the movements of each individual and their every social interaction. This setup allows me to study i) the existence individual differences in social responsiveness in acoustic signaling and ii) the selection acting on social responsiveness.
Figure 1. Field cricket male signaling from its "territory" in my study population. Above, I show three-second spectrogram from the signal. Cricket is tagged with circular bee-tag and RFID-transponder. RFID-antenna is set around the burrow entrance.
Laboratory work
Behavioral development Since the beginning of my career, I have been interested of whether environmental characteristics can cause long-term changes in the expression of individual differences and reversible plasticity in behaviours. In my work I have, for example, shown that bacterial exposure in adult and juvenile stages (numbers refer to papers in my publication list: 11, 14), social interactions experienced through ontogeny (4), the presence of predators (5), temperature experienced through ontogeny (26) and dietary restrictions experienced through ontogeny (25) cause changes not only in the group mean level behaviours, but also in the expression of individual differences and reversible plasticity in behaviours. Studying environmental effects on behavioural expression at multiple biological levels of variation is the core of the research I am focusing in my laboratory work (Figure 2).
Figure 2. Our laboratory setup. Crickets are raised individually in a large climate room. These pictures are from a large scale collaborative quantitative genetics project, led by Dr. Francesca Santostefano (person in the right side picture).
Integration of behavior, life-history and physiology One of the recent central theories explaining adaptive individual differences in behavioural expression is the Pace-of-life-syndrome (POLS) hypothesis (21). POLS hypothesis is a framework for the adaptive integration of behaviour, physiology and life history at multiple hierarchical levels of variation (genetic, individual, population, species) (21). In my work, I have focused on testing the predictions based on this hypothesis. I have, for example, shown that physiology, life-history and behaviors are associated withe each other, but that association depends on the level of variation (i.e. phenotypic, among-individual, within-individual, genetic) under examination (8, 17, 20, 24).
I have not been only focusing on empirical testing of the theory, but also on revising the conceptual background of POLS hypothesis to allow more accurate predictions (21, 31). I, for example, co-organized (with three other researchers) a series of workshops in Hannover, Germany (2015 & 2016), working with 40 international cross-disciplinary researchers to revise and summarize the conceptual, theoretical, methodological and empirical progress in research focusing on testing the POLS hypothesis. I co-edited a special issue on this topic, which was published in Behavioral Ecology and Sociobiology in winter 2018 (e.g. 21, 22).
I am also working to understand methodological (15, 18, 23, 24, 30), statistical (23, 24, 30) and psychological (15) biases present in the empirical animal behaviour literature. I have, for example, shown that majority of the empirical studies focusing on questions related to individual differences in behavioural expression use a combination of data and statistical tools that cannot answer individual level questions (23, 24). My motivation is to raise awareness about both the actual problem at hand, but also to offer solutions (24, 30).
Using meta-analytic tools to test general behavioral ecology theories
Finally, I am also using meta-analytic tools to test evolutionary theories related to individual differences in behavioral expression (22, 23, 28).