respR publication

respR has been peer reviewed and published. Please cite this paper if you use it in your work:

Harianto, J., Carey, N., & Byrne, M. respR - An R Package for the Manipulation and Analysis of Respirometry Data. Methods in Ecology and Evolution, 10(6), 912–920. doi: 10.1111/2041-210X.13162.


See also

These packages may also help you analyse respirometry data:

Be sure to check out the FishResp site, where the developers are releasing a variety of amazing free and open source tools for conducting respirometry experiments, including resources for building your own respirometry equipment at a fraction of the cost of commercial systems.


The following publications were instrumental in developing respR and writing the vignettes on this site, or are referenced in the various vignettes. See here for references specific to critical oxygen analyses (i.e. \(P_{crit}\)).  

Carey, N, Harianto, J, & Byrne, M. 2016. Sea urchins in a high-CO 2 world: Partitioned effects of body size, ocean warming and acidification on metabolic rate. The Journal of Experimental Biology, 219(8), 1178–1186.
Chabot, D, Zhang, Y, & Farrell, AP. 2021. Valid oxygen uptake measurements: Using high R2 values with good intentions can bias upward the determination of standard metabolic rate. Journal of Fish Biology, 98(5), 1206–1216.
Clark, TD, Sandblom, E, & Jutfelt, F. 2013. Aerobic scope measurements of fishes in an era of climate change: Respirometry, relevance and recommendations. Journal of Experimental Biology, 216(15), 2771–2782.
Gamble, S, Carton, AG, & Pirozzi, I. 2014. Open-top static respirometry is a reliable method to determine the routine metabolic rate of barramundi, Lates Calcarifer. Marine and Freshwater Behaviour and Physiology, 47(1), 19–28.
Jones, MC, Marron, JS, & Sheather, SJ. 1996. A brief survey of bandwidth selection for density estimation. Journal of the American Statistical Association, 91(433), 401–407.
Killen, SS, Christensen, EAF, Cortese, D, Závorka, L, Norin, T, Cotgrove, L, Crespel, A, Munson, A, Nati, JJH, Papatheodoulou, M, & McKenzie, DJ. 2021. Guidelines for reporting methods to estimate metabolic rates by aquatic intermittent-flow respirometry. Journal of Experimental Biology, 224(18), jeb242522.
Kurihara, H, Yin, R, Nishihara, G, Soyano, K, & Ishimatsu, A. 2013. Effect of ocean acidification on growth, gonad development and physiology of the sea urchin Hemicentrotus pulcherrimus. Aquatic Biology, 18(3), 281–292.
Leclercq, N, Gattuso, J-P, & Jaubert, J. 1999. Measurement of oxygen metabolism in open-top aquatic mesocosms:application to a coral reef community. Marine Ecology Progress Series, 177, 299–304.
Lighton, JRB. 2008. Measuring Metabolic Rates. Oxford University Press.
Marshall, D, Bode, M, & White, CR. 2013. Estimating physiological tolerances - a comparison of traditional approaches to nonlinear regression techniques. Journal of Experimental Biology, jeb.085712.
Morozov, S, McCairns, RJS, & Merilä, J. 2019. FishResp: R package and GUI application for analysis of aquatic respirometry data. Conservation Physiology, 7(1).
Moulin, L, Grosjean, P, Leblud, J, Batigny, A, Collard, M, & Dubois, P. 2015. Long-term mesocosms study of the effects of ocean acidification on growth and physiology of the sea urchin Echinometra mathaei. Marine Environmental Research, 103, 103–114.
Muggeo, VMR. 2003. Estimating regression models with unknown break-points. Statistics in Medicine, 22(19), 3055–3071.
Muggeo, VMR. 2008. Modeling temperature effects on mortality: Multiple segmented relationships with common break points. Biostatistics, 9(4), 613–620.
Prinzing, TS, Zhang, Y, Wegner, NC, & Dulvy, NK. 2021. Analytical methods matter too: Establishing a framework for estimating maximum metabolic rate for fishes. Ecology and Evolution.
Raykar, V, & Duraiswami, R. 2006. Fast optimal bandwidth selection for kernel density estimation. Proceedings of the Sixth SIAM International Conference on Data Mining, 2006.
Sheather, SJ, & Jones, MC. 1991. A reliable data-based bandwidth selection method for kernel density estimation. Journal of the Royal Statistical Society. Series B (Methodological), 53(3), 683–690.
Silverman, BW. 1986. Density Estimation for Statistics and Data Analysis. Routledge.
Smith Jr, KL. 1987. Food energy supply and demand: A discrepancy between particulate organic carbon flux and sediment community oxygen consumption in the deep Ocean1: Food energy supply and demand. Limnology and Oceanography, 32(1), 201–220.
Steffensen, JF. 1989. Some errors in respirometry of aquatic breathers: How to avoid and correct for them. Fish Physiology and Biochemistry, 6(1), 49–59.
Stoffels, RJ. 2015. Physiological trade-offs along a fast-slow lifestyle continuum in fishes: What do they tell us about resistance and resilience to hypoxia? PLOS ONE, 10(6), e0130303.
Svendsen, MBS, Bushnell, PG, & Steffensen, JF. 2016. Design and setup of intermittent-flow respirometry system for aquatic organisms: How to set up an aquatic respirometry system. Journal of Fish Biology, 88(1), 26–50.
White, CR, & Kearney, MR. 2013. Determinants of inter-specific variation in basal metabolic rate. Journal of Comparative Physiology B, 183(1), 1–26.
Yeager, DP, & Ultsch, GR. 1989. Physiological regulation and conformation: A BASIC program for the determination of critical points. Physiological Zoology, 62(4), 888–907.
Zivot, E, & Wang, J. 2006. Modeling financial time series with S-PLUS (Second). Springer-Verlag.