Continuous observation of animal behaviour could be quite a challenge in the field, and the situation becomes even more complicated with aquatic species mostly active at night. In such cases, biologging techniques are real game changers in ecology, behavioural ecology or eco-physiology. An accelerating number of methodological applications of these tools in natural condition are thus published each year . Biologging is not limited to movement ecology. For instance, fine grain information about energy expenditure can be inferred from body acceleration , and accelerometers has already proven useful in monitoring reproductive costs in some fish species [3,4]. The first part of the study by Tentelier et al.  is in line with this growing literature. It describes measurements of energy expenditure during reproduction in a fish species, Allis shad (Alosa Alosa), based on tail beat frequency and occurrence of spawning acts. The study has been convincingly conducted, and the results are important for fish biologists. But this is not the whole story: the authors added to this otherwise classical study a very original and insightful analysis which deserves closer interest.
Tentelier et al. propose to use static accelerometer to monitor change in body roundness through the reproductive season. These semelparous fish first mature and built up reserves in the Atlantic Ocean and migrate into fresh water to reproduce. Contrary to iteroparous species, female shads do not have to strategically preserve energy for future reproduction. The females die few days after spawning having exhausted their energetic reserves: they typically lose almost half of their body mass during the spawning season. The beautiful idea in this study was to track down information about this dramatic slimming in the accelerometer data. Indeed, the accelerometer was attached on the side of the fish (close to the dorsal fin). A change in its angle with the vertical plane could be correlated with the change in roundness, the angle declining with the female thinning. Accelerometers have already been used to record body posture  but, in the present study, the novelty was to monitor the change in body shape.
Unfortunately, the data by Tentelier et al. are inconclusive so far. Broadly speaking, the accelerometer angle recorded declined through the spawning season, indicating an average slimming of the females, but there was no correlation between the change in angle and the mass loss at the individual level. This was partly due to the fact that the dorsal position of the accelerometer was not optimized to measures egg laying whose effects are mostly observable on ventral side.
Yet, this nice idea deserves more scrutiny. The method seems to be sensitive enough to detect inflation of swim bladder, the gas-filled organ helping the fish to control their position in the water column, as the accelerometer angle increased when the fish stayed close to the water surface. Additional works and proper calibration are certainly needed to validate the use of accelerometer angle as a proxy for body roundness. The actual data were not strong enough to justify a standalone publication on the subject, but it would have been shame to lose traces of such analysis and keep it in the file drawer. This is why I strongly support its report as a side question in a broader study. Science progresses not only with neat conclusive studies but also when unexpected (apparently anecdotal) observations stimulate new researches.
 Börger L, Bijleveld AI, Fayet AL, Machovsky‐Capuska GE, Patrick SC, Street GM and Vander Wal E. (2020) Biologging special feature. J. Anim. Ecol. 89, 6–15. 10.1111/1365-2656.13163
 Wilson RP et al. (2020) Estimates for energy expenditure in free‐living animals using acceleration proxies: A reappraisal. J. Anim. Ecol. 89, 161–172. 10.1111/1365-2656.13040
 Tsuda Y, Kawabe R, Tanaka H, Mitsunaga Y, Hiraishi T, Yamamoto K and Nashimoto K. (2006) Monitoring the spawning behaviour of chum salmon with an acceleration data logger. Ecol. Freshw. Fish 15, 264–274. 10.1111/j.1600-0633.2006.00147.x
 Sakaji H, Hamada K, Naito Y. 2018 Identifying spawning events of greater amberjack using accelerometers. Mar. Biol. Res. 14, 637–641. 10.1080/17451000.2018.1492140
 Tentelier C, Bouchard C, Bernardin A, Tauzin A, Aymes J-C, Lange F, Récapet C, Rives J (2020) The dynamics of spawning acts by a semelparous fish and its associated energetic costs. bioRxiv, 436295. doi: 10.1101/436295 ver. 7 peer-reviewed and recommended by PCI Ecology. 10.1101/436295
 Brown DD, Kays R, Wikelski M, Wilson R, Klimley AP. 2013 Observing the unwatchable through acceleration logging of animal behavior. Anim. Biotelemetry 1, 20. 10.1186/2050-3385-1-20
Dear Cédric Tentelier,
Both reviewers and myself agree that your preprint deserves recommendation by PCI Ecology. I carefully read through it and I agree that most (but not all) of the referees’ previous concerns were satisfactorily addressed. I think that this new version has greatly improved the paper's clarity, and I am ready to recommend it for PCI Ecology. Yet, the final comments by Mark Hewison must first be properly addressed. Could you please modify your MS in line with his comments? In addition, I think that previous uses of accelerometer to monitor spawning behaviour in fish species (e.g. Tsuda et al. 2006, Sakaji et al. 2018) deserve to be cited and commented in the main text. It will help the reader to assess the novelty of your study. Finally, PCI Ecology does not copy-edit the preprints. You should pay particular attention to typographical and other minor issues. For instance, in the abstract (line 56) one should read “complementary” instead of “complimentary”. Please, carefully edit the new version of your preprint prior resubmission.
Pr François-Xavier Dechaume-Moncharmont University of Lyon, France
References - Sakaji, H., Hamada, K., & Naito, Y. (2018). Identifying spawning events of greater amberjack using accelerometers. Marine Biology Research, 14(6), 637 641. https://doi.org/10.1080/17451000.2018.1492140 - Tsuda, Y., Kawabe, R., Tanaka, H., Mitsunaga, Y., Hiraishi, T., Yamamoto, K., & Nashimoto, K. (2006). Monitoring the spawning behaviour of chum salmon with an acceleration data logger. Ecology of Freshwater Fish, 15(3), 264 274. https://doi.org/10.1111/j.1600-0633.2006.00147.x
The present manuscript is a methodological study assessing the potential use of accelerometer for estimating spawning activity in a fish species. Despite the limited sample size, the idea is original, appealing and, if its reliability is confirmed, possibly very useful in field works. It could therefore be a valuable contribution to the field and it could be recommended by PCI-Ecology provided some clarifications and developments.
In its present form, one of the major weaknesses of the manuscript lies in the lack of argumentation about the chosen equations and metrics: how were they calibrated? How appropriate were they to estimate the energy consumption? Two referees expressed serious concerns about the calibration of the measures. I understand that it will not be possible to perform additional experiments. Yet, complementary statistical analysis may be presented. At the very least, if relevant information is not accessible any more, these caveats and limitations should be extensively discussed in the MS as a warning for the reader. The referees also pointed out that utmost care must be taken to justify the measurement as a proxy for energy expenditure. I strongly advise the authors to carefully take into account their suggestions.
Finally, I share one referee's opinion about the structure of the manuscript. The end of the Introduction section is too abrupt. By contrast, a great deal of information presented in the Material and Methods section (p.8) concern hypotheses and predictions and should be moved at the end of the Introduction section. Similarly, some details about the statistical analysis (around line 270) should be moved down to the Statistics section. This latter section should be carefully edited. In its present form, it contains many details which are more related with experimental procedure than statistical analysis.
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