Unifying individual differences in personality, predictability, and plasticity: a practical guide

Abstract

1. Many animal species show individual differences in behaviour that are partially consistent across repeated measurements. Commonly referred to as personality traits, differences in average behaviours are often correlated across individuals, forming ‘behavioural syndromes’ (e.g. individuals who are more aggressive are also bolder).2. Generally, differences in the average behaviour of individuals explains less than half the variation in behavioural traits. To explain the rest, we need to consider how individuals themselves vary both plastically and unpredictably. 3. Here, we integrate the study of multiple individual differences. With a reproducible worked example based on zebrafish (Danio rerio) behaviours, we give guidance for measuring individual differences in average phenotypes (i.e. personality), responses to an environmental or biological context (i.e. plasticity), and intrinsic variability across time (i.e. predictability, or intra-individual variability).4. Individuality is multi-faceted. By modelling personality, plasticity, and predictability simultaneously, empiricists can quantify how these traits covary across individuals, and test theoretical ideas about phenotypic integration. We provide detailed descriptions and resources for measuring behavioural syndromes, plasticity syndromes, predictability syndromes, personality-plasticity associations, personality-predictability associations, and plasticity-predictability associations. These methods can be extended to incorporate plastic changes in predictability (termed ‘stochastic malleability’). 5. Overall, we showcase the unfulfilled potential of existing statistical tools. Empiricists can use these methods to test more holistic and nuanced questions about the evolution, function, and maintenance of phenotypic variation, for any trait that is repeatedly expressed.

Understanding the unexplained: The magnitude and correlates of individual differences in residual variance

“…1: Western fence lizard ( Sceloporus occidentalis ; Adolph & Pickering, 2008), 2: chacma baboon ( Papio ursinus ; Allan et al, 2020), 3: mosquitofish ( Gambusia holbrooki ; Biro & Adriaenssens, 2013), 4: Ward's damselfish ( Pomacentrus bankanensis ; Biro et al., 2010), 5: guppy ( Poecilia reticulata ; Biro et al., 2016), 6: hermit crab ( Pagurus bernhardus ; Bridger et al., 2015), 7: hermit crab ( P. bernhardus ; Briffa, 2013), 8: hermit crab ( P . bernhardus ; Briffa et al., 2013), 9: house sparrow ( Passer domesticus ; Careau, Hoye, et al., 2014), 10: marsh periwinkle ( Littoraria irrorata ; Cornwell et al., 2018), 11: marsh periwinkle ( L. irrorata ; Cornwell et al., 2020), 12: house mouse ( Mus musculus ; Eisenmann et al., 2009), 13: three‐spined stickleback ( Gasterosteus aculeatus ; Fürtbauer et al., 2015), 14: shore crab ( Carcinus maenas ; Fürtbauer, 2015), 15: dog ( Canis familiaris ; Goold & Newberry, 2017), 16: guppy ( P. reticulata ; Herczeg et al., 2019), 17: brown bear ( Ursus arctos ; Hertel, Royauté, et al., 2020), 18: African elephant ( Loxodonta africanus ; Hertel, Niemelä, et al., 2020), 19: Namibian rock agama ( Agama planiceps ; Highcock & Carter, 2014), 20: slater ( Armadillidium vulgare ; Horváth et al., 2019), 21: fallow deer ( Dama dama ; Jennings et al., 2013), 22: three‐spined stickleback ( G. aculeatus ; Jolles et al., 2019), 23: guppy ( P. reticulata ; Kurvers et al., 2018), 24: yellow‐bellied marmot ( Marmota flaviventris ; Martin et al., 2017), 25: guppy ( P. reticulata ; Mitchell et al., 2016), 26: zebra fish ( Danio rerio ; Mitchell, Dujon, et al., 2020), 27: guppy ( P. reticulata ; Mitchell, Beckmann, et al., 2020), 28: guppy ( P. reticulata ; Mitchell, Lefèvre, et al., 2020), 29: eastern chipmunk ( Tamias striatus ; Montiglio et al., 2015), 30: hermit crab ( P. bernhardus ; Nanninga et al., 2020), 31: (Norin & Gamperl, 2017), 32: zebra fish ( D. rerio ; O'Dea et al., 2020), 33: (Osborn & Briffa, 2017), 34: guppy ( P. reticulata ; Prentice et al., 2020), 35: hermin crab ( P. bernhardus ; Stamps et al., 2012), 36: agile frog tadpole ( Rana dalmatina ; Urszán Tamás et al., 2018), 37: hermit crab ( P. bernhardus ; Velasque & Briffa,…”

“…On the log-scale, there is a linear relationship between variance and standard deviations, and the variance in the rIIV can therefore be easily converted as 2 = 2 2 4 (O'Dea et al, 2020).…”

“…Some studies model the residual variance rather than residual standard deviation (e.g., Martin et al., 2017; Prentice et al., 2020) and required conversion. On the log‐scale, there is a linear relationship between variance and standard deviations, and the variance in the rIIV can therefore be easily converted as (O'Dea et al., 2020).…”

Laboratory measures of boldness correlate to ecological niche in threespine stickleback

“…However, the average expression of any behavioral trait only partially reflects the personality of the individual and it is also important to consider how variable behavioral expression is within the individual (Nussey, Wilson and Brommer, 2007;Dingemanse et al, 2010;Mathot et al, 2012). Within individual variability in behavior can be directional, for example, habituation to a novel environment (Brown, 2001;Allan, Bailey and Hill, 2020), change in behavior appropriate to context, such as the level of risk (Steinhoff et al, 2020), but also random or unpredictable (Stamps, Briffa and Biro, 2012;O'Dea, Noble and Nakagawa, 2020). Furthermore, recent research has shown that even the expression of similar traits can have different underlying mechanism depending on the context (Mouchet & Dingemanse, 2021).…”

Personality Science: United in Diversity

“…In this vein, Revelle (2007, p. 37) opined that "[p]ersonality research is the last refuge of the generalist in psychology". The scope of a broader personality-centered science expands even more by also including variations between and within animals or entire species (e.g., Bell et al, 2009;Carere & Maestripieri, 2013;Dall et al, 2004;O'Dea et al, 2020;Sih et al, 2004Sih et al, , 2015Sih et al, , 2020Wolf & Weissing, 2012), virtual avatars and intelligent systems (e.g., Bélisle & Bodur, 2010;Fong & Mar, 2015;McLeod et al, 2014;Pan et al, 2015;Read & Miller, 2002;Ünal et al, 2018), and robots (e.g., Bremner et al, 2016;Broadbent et al, 2013;Churamani et al, 2020;Craenen et al, 2018;Reich & Eyssel, 2013;Robert, 2018). Thus, there is a rich smorgasbord of topics, phenomena, and variables that a science of personality can tackle -with an equally staggering array of perspectives, theories, questions, methodologies, and applications.…”