Finding the best estimates of metabolic rates in a coral reef fish

Abstract

SUMMARYMetabolic rates of aquatic organisms are estimated from measurements of oxygen consumption rates (Ṁ O2 ) through swimming and resting respirometry. These distinct approaches are increasingly used in ecophysiology and conservation physiology studies; however, few studies have tested whether they yield comparable results. We examined whether two fundamental Ṁ O2 measures, standard metabolic rate (SMR) and maximum metabolic rate (MMR), vary based on the method employed. Ten bridled monocle bream (Scolopsis bilineata) were exercised using (1) a critical swimming speed (U crit ) protocol, (2) a 15min exhaustive chase protocol and (3) a 3min exhaustive chase protocol followed by brief (1min) air exposure. Protocol 1 was performed in a swimming respirometer whereas protocols 2 and 3 were followed by resting respirometry. SMR estimates in swimming respirometry were similar to those in resting respirometry when a three-parameter exponential or power function was used to extrapolate the swimming speed-Ṁ O2 relationship to zero swimming speed. In contrast, MMR using the U crit protocol was 36% higher than MMR derived from the 15min chase protocol and 23% higher than MMR using the 3min chase/1min air exposure protocol. For strong steady (endurance) swimmers, such as S. bilineata, swimming respirometry can produce more accurate MMR estimates than exhaustive chase protocols because oxygen consumption is measured during exertion. However, when swimming respirometry is impractical, exhaustive chase protocols should be supplemented with brief air exposure to improve measurement accuracy. Caution is warranted when comparing MMR estimates obtained with different respirometry methods unless they are cross-validated on a species-specific basis.

A simple game-theoretic model for upstream fish migration

“…1. The cost function f in (4) shows that the fish is more high speed-averse for larger n, because it more rapidly grows for larger n. The cost function f in (4) is convex and increasing with respect to u; which is in good accordance with the conventional experimental results on swimming behavior of fishes (Brodersen et al 2008;Cucco et al 2012;Mori et al 2015;Roche et al 2013;Svendsen et al 2010;Yoshioka et al 2016a). The objective function is rewritten with (2) as…”

Exploring key issues of aerobic scope interpretation in ectotherms: absolute versus factorial

“…Both of these measurements can show variability for many reasons including among-and within-individual biological variation (Burton et al 2011;Metcalfe et al 2016;Norin and Malte 2011), experimental error and methodological differences (Clark et al 2013;Killen et al 2017;Reidy et al 1995;Roche et al 2013;Rodgers et al 2016;Rummer et al 2016). To interrogate how measurement variability influences calculations of aerobic scope, we generated two simple models that specifically investigated the effects of variability in SMR when MMR is fixed and vice versa.…”

“…Further, while there is a focus on SMR as a source of variation in FAS, our simple models support experimental evidence in showing that variation in MMR (which could be due either to biological variation or experimental noise) is also an important consideration, particularly when aerobic scope is low and defined as AAS. The fact that substantial variation in the calculation of MMR can indeed result from bona fide experimental factors is evident from studies that have specifically tested how different techniques and protocols to exhaust fish can produce significantly different estimates of MMR Reidy et al 1995;Roche et al 2013;Rummer et al 2016;Soofiani and Priede 1985;Killen et al 2017). …”

Repeatability of locomotor performance and of morphology – locomotor performance relationships

“…U crit provides an ecologically relevant measure of prolonged locomotor performance (Kolok, 1999;Plaut, 2001;Wolter and Arlinghaus, 2003;Roche et al, 2013). Population mean U crit is positively correlated with water flow rate (McGuigan et al, 2003;Langerhans, 2008;Haas et al, 2010Haas et al, , 2015, revealing the historical role of flow in shaping freshwater fish diversity.…”