Shaun S. Killen

Dr. Shaun S. Killen


Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
28 September 2011 in Proceedings Of The Royal Society B-Biological Sciences
Verified
Journal Article
Closed access
TBT. Burton
T. Burton
SKShaun S. Killen
Shaun S. Killen
JAJ. D. Armstrong
J. D. Armstrong
NMN. B. Metcalfe
N. B. Metcalfe
Individual differences in the energy cost of self-maintenance (resting metabolic rate, RMR) are substantial and the focus of an emerging research area. These differences may influence fitness because self-maintenance is considered as a life-history component along with growth and reproduction. In this review, we ask why do some individuals have two to three times the ‘maintenance costs’ of conspecifics, and what are the fitness consequences? Using evidence from a range of species, we demonstrate that diverse factors, such as genotypes, maternal effects, early developmental conditions and personality differences contribute to variation in individual RMR. We review evidence that RMR is linked with fitness, showing correlations with traits such as growth and survival. However, these relationships are modulated by environmental conditions (e.g. food supply), suggesting that the fitness consequences of a given RMR may be context-dependent. Then, using empirical examples, we discuss broad-scale reasons why variation in RMR might persist in natural populations, including the role of both spatial and temporal variation in selection pressures and trans-generational effects. To conclude, we discuss experimental approaches that will enable more rigorous examination of the causes and consequences of individual variation in this key physiological trait.

18 February 2022 in Science
Verified
Journal Article
Closed access
RNRan Nathan
Ran Nathan
CMChristopher T. Monk
Christopher T. Monk
RARobert Arlinghaus
Robert Arlinghaus
TATimo Adam
Timo Adam
JAJosep Alos
Josep Alos
IJIvan Jarić
Ivan Jarić
Understanding animal movement is essential to elucidate how animals interact, survive, and thrive in a changing world. Recent technological advances in data collection and management have transformed our understanding of animal “movement ecology” (the integrated study of organismal movement), creating a big-data discipline that benefits from rapid, cost-effective generation of large amounts of data on movements of animals in the wild. These high-throughput wildlife tracking systems now allow more thorough investigation of variation among individuals and species across space and time, the nature of biological interactions, and behavioral responses to the environment. Movement ecology is rapidly expanding scientific frontiers through large interdisciplinary and collaborative frameworks, providing improved opportunities for conservation and insights into the movements of wild animals, and their causes and consequences.

14 January 2010 in Ecology Letters
Verified
Journal Article
Closed access
PDF file
SKShaun S. Killen
Shaun S. Killen
DADavid Atkinson
David Atkinson
DGDouglas S. Glazier
Douglas S. Glazier

1 November 2013 in Trends in Ecology & Evolution
Verified
Journal Article
Closed access
SKShaun S. Killen
Shaun S. Killen
SMStefano Marras
Stefano Marras
NMNeil B. Metcalfe
Neil B. Metcalfe
DMDavid J. McKenzie
David J. McKenzie
PDPaolo Domenici
Paolo Domenici

30 October 2014 in Behavioral Ecology and Sociobiology
Verified
Journal Article
Open access
PDF file
SMStefano Marras
Stefano Marras
SKShaun S. Killen
Shaun S. Killen
JLJan Lindström
Jan Lindström
DMDavid J. McKenzie
David J. McKenzie
JSJohn Fleng Steffensen
John Fleng Steffensen
PDPaolo Domenici
Paolo Domenici
For animals, being a member of a group provides various advantages, such as reduced vulnerability to predators, increased foraging opportunities and reduced energetic costs of locomotion. In moving groups such as fish schools, there are benefits of group membership for trailing individuals, who can reduce the cost of movement by exploiting the flow patterns generated by the individuals swimming ahead of them. However, whether positions relative to the closest neighbours (e.g. ahead, sided by side or behind) modulate the individual energetic cost of swimming is still unknown. Here, we addressed these questions in grey mulletLiza aurataby measuring tail-beat frequency and amplitude of 15 focal fish, swimming in separate schools, while swimming in isolation and in various positions relative to their closest neighbours, at three speeds. Our results demonstrate that, in a fish school, individuals in any position have reduced costs of swimming, compared to when they swim at the same speed but alone. Although fish swimming behind their neighbours save the most energy, even fish swimming ahead of their nearest neighbour were able to gain a net energetic benefit over swimming in isolation, including those swimming at the front of a school. Interestingly, this energetic saving was greatest at the lowest swimming speed measured in our study. Because any member of a school gains an energetic benefit compared to swimming alone, we suggest that the benefits of membership in moving groups may be more strongly linked to reducing the costs of locomotion than previously appreciated.

1 May 2016 in The American Naturalist
Verified
Journal Article
Open access
SKShaun S. Killen
Shaun S. Killen
DGDouglas S. Glazier
Douglas S. Glazier
EREnrico L. Rezende
Enrico L. Rezende
TCTimothy D. Clark
Timothy D. Clark
DADavid Atkinson
David Atkinson
LHLewis Halsey
Lewis Halsey
Rates of aerobic metabolism vary considerably across evolutionary lineages, but little is known about the proximate and ultimate factors that generate and maintain this variability. Using data for 131 teleost fish species, we performed a large-scale phylogenetic comparative analysis of how interspecific variation in resting metabolic rates (RMRs) and maximum metabolic rates (MMRs) is related to several ecological and morphological variables. Mass- and temperature-adjusted RMR and MMR are highly correlated along a continuum spanning a 30- to 40-fold range. Phylogenetic generalized least squares models suggest that RMR and MMR are higher in pelagic species and that species with higher trophic levels exhibit elevated MMR. This variation is mirrored at various levels of structural organization: gill surface area, muscle protein content, and caudal fin aspect ratio (a proxy for activity) are positively related with aerobic capacity. Muscle protein content and caudal fin aspect ratio are also positively correlated with RMR. Hypoxia-tolerant lineages fall at the lower end of the metabolic continuum. Different ecological lifestyles are associated with contrasting levels of aerobic capacity, possibly reflecting the interplay between selection for increased locomotor performance on one hand and tolerance to low resource availability, particularly oxygen, on the other. These results support the aerobic capacity model of the evolution of endothermy, suggesting elevated body temperatures evolved as correlated responses to selection for high activity levels.