Metabolic rate covaries with fitness and the pace of the life history in the field

Authors: Amanda K Pettersen, Craig R White and Dustin J Marshall

Published in: Proceedings of the Royal Society B, volume 283, issue 1831 (May 2016)


Metabolic rate reflects the ‘pace of life’ in every organism. Metabolic rate is related to an organism’s capacity for essential maintenance, growth and reproduction—all of which interact to affect fitness.

Although thousands of measurements of metabolic rate have been made, the microevolutionary forces that shape metabolic rate remain poorly resolved. The relationship between metabolic rate and components of fitness are often inconsistent, possibly because these fitness components incompletely map to actual fitness and often negatively covary with each other.

Here we measure metabolic rate across ontogeny and monitor its effects on actual fitness (lifetime reproductive output) for a marine bryozoan in the field. We also measure key components of fitness throughout the entire life history including growth rate, longevity and age at the onset of reproduction.

We found that correlational selection favours individuals with higher metabolic rates in one stage and lower metabolic rates in the other—individuals with similar metabolic rates in each developmental stage displayed the lowest fitness. Furthermore, individuals with the lowest metabolic rates lived for longer and reproduced more, but they also grew more slowly and took longer to reproduce initially.

That metabolic rate is related to the pace of the life history in nature has long been suggested by macroevolutionary patterns but this study reveals the microevolutionary processes that probably generated these patterns.


Pettersen A, White CF, Marshall DJ (2016) Metabolic rate covaries with fitness and the pace of the life history in the field, Proceedings of the Royal Society B, 283: 20160323
PDF 548 KB doi: 20160323. doi:10.1098/rspb.2016.0323

Estimating physiological tolerances: a comparison of traditional approaches to nonlinear regression techniques

Authors: Dustin J Marshall, Michael Bode and Craig R White

Published in: The Journal of Experimental Biology, volume 216 (June 2013)


Traditionally, physiologists have estimated the ability of organisms to withstand lower partial pressures of oxygen by estimating the partial pressure at which oxygen consumption begins to decrease (known as the critical PO2 or Pc). For almost 30 years, the principal way in which Pc has been estimated has been via piecewise ʻbroken stickʼ regression (BSR). BSR was a useful approach when more sophisticated analyses were less available, but BSR makes a number of unsupported assumptions about the underlying form of the relationship between the rate of oxygen consumption and oxygen availability. The BSR approach also distils a range of values into a single point with no estimate of error.

In accordance with more general calls to fit functions to continuous data, we propose the use of nonlinear regression (NLR) to fit various curvilinear functions to oxygen consumption data in order to estimate Pc. Importantly, our approach is back-compatible so that estimates using traditional methods in earlier studies can be compared with data estimates from our technique. When we compared the performance of our approach relative to the traditional BSR approach for real world and simulated data, we found that under realistic circumstances, NLR was more accurate and provided more powerful hypothesis tests.

We recommend that future studies make use of NLR to estimate Pc, and also suggest that this approach might be more appropriate for a range of physiological studies that use BSR currently.

Full paper

Marshall DJ, Bode M, White CR (2013) Estimating physiological tolerances – a comparison of traditional approaches to nonlinear regression techniques. The Journal of Experimental Biology, 216 (12), 2176–2182 PDFPDF 562 KB doi:10.1242/jeb.085712