Response to ‘On the importance of understanding physiology when estimating energetics in cetaceans’

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biology Open 6 (2017): 307-308, doi:10.1242/bio.023143.We are grateful for the interest in our paper by two eminent physiologists and hope this response to their comments will clarify the objectives of our paper. The analysis in Fahlman et al. (2016) was not intended to provide an accurate method to estimate field metabolic rate (FMR) in large mysticetes; the objective was to measure the dynamic changes in physiology associated with recovery from exercise and show that they are important to consider when estimating FMR. While static averages can provide useful estimates of FMR for a variety of situations, these need to be appropriately selected. For example, we illustrate that it is not possible to use selected average values chosen from excised tissues or resting animals (as in Blix and Folkow, 1995) to provide meaningful estimates of FMR for animals at different activities (i.e. the dolphins in our study). Our study highlights the importance of temporal variation in physiological models: the Blix and Folkow (1995) estimates rely on the assumption that only breathing frequency (fR) changes with activity, while we argue that both the tidal volume (VT) and mixed lung O2 content also vary with activity and recovery from a dive (Ridgway et al., 1969). Including this variation in all three parameters reduces temporal uncertainty in the same conceptual model (see Eqn. 1 in Fahlman et al., 2016)

Estimating energetics in cetaceans from respiratory frequency : why we need to understand physiology

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Biology Open 5 (2016): 436-442, doi:10.1242/bio.017251.The accurate estimation of field metabolic rates (FMR) in wild animals is a key component of bioenergetic models, and is important for understanding the routine limitations for survival as well as individual responses to disturbances or environmental changes. Several methods have been used to estimate FMR, including accelerometer-derived activity budgets, isotope dilution techniques, and proxies from heart rate. Counting the number of breaths is another method used to assess FMR in cetaceans, which is attractive in its simplicity and the ability to measure respiration frequency from visual cues or data loggers. This method hinges on the assumption that over time a constant tidal volume (VT) and O2 exchange fraction (ΔO2) can be used to predict FMR. To test whether this method of estimating FMR is valid, we measured breath-by-breath tidal volumes and expired O2 levels of bottlenose dolphins, and computed the O2 consumption rate (V̇O2) before and after a pre-determined duration of exercise. The measured V̇O2 was compared with three methods to estimate FMR. Each method to estimate V̇O2 included variable VT and/or ΔO2. Two assumption-based methods overestimated V̇O2 by 216-501%. Once the temporal changes in cardio-respiratory physiology, such as variation in VT and ΔO2, were taken into account, pre-exercise resting V̇O2 was predicted to within 2%, and post-exercise V̇O2 was overestimated by 12%. Our data show that a better understanding of cardiorespiratory physiology significantly improves the ability to estimate metabolic rate from respiratory frequency, and further emphasizes the importance of eco-physiology for conservation management efforts.Funding for this project was provided by the Office of Naval Research [ONR YIP Award # N000141410563]. M.J.M. received funding from National Oceanographic Partnership Program [9N00014-11-1-0113]

A day in the life of a dolphin: Using bio-logging tags for improved animal health and well-being

Little quantitative information on the behavior, health, and activity level of managed marine mammals is currently collected, though it has the potential to significantly contribute to management and welfare of these animals. To address this, highâ resolution motionâ sensing digital acoustic recording tags (DTAGs) collected data from animals under human care (n = 5) during their daily routine, and classification algorithms were used for gait analysis and event detection. We collected and examined ~57 h of data from five bottlenose dolphins (Tursiops truncatus). Dayâ scale changes in behavior and activity level were observed and diurnal changes were detected with lower activity at night (n = 1). During the day, animals spent about 70% of their time swimming. The deepest part of the lagoon is ~3 m and individual dives were typically shallow (~1 m) with the dolphins tending to utilize a fluke and glide gait pattern. Activity level was quantified using overall dynamic body acceleration. A significant relationship between normalized activity level and glide duration during different portions of the dive was measured; animals fluked more during descent and glided more during ascent. This could indicate that even during very shallow dives the dolphins use their positive buoyancy to improve energy economy.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137721/1/mms12408_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137721/2/mms12408.pd

Simulated and experimental estimates of hydrodynamic drag from bioâ logging tags

Drag force acting on swimming marine mammals is difficult to measure directly. Researchers often use simple modeling and kinematic measurements from animals, or computational fluid dynamics (CFD) simulations to estimate drag. However, studies that compare these methods are lacking. Here, computational simulation and physical experiments were used to estimate drag forces on gliding bottlenose dolphins (Tursiops truncatus). To facilitate comparison, variable drag loading (noâ tag, tag, tagâ +â 4, tagâ +â 8) was used to increase force in both simulations and experiments. During the experiments, two dolphins were trained to perform controlled glides with variable loading. CFD simulations of dolphin/tag geometry in steady flow (1â 6â m/s) were used to model drag forces. We expect both techniques will capture relative changes created by experimental conditions, but absolute forces predicted by the methods will differ. CFD estimates were within a calculated 90% confidence interval of the experimental results for all but the tag condition. Relative drag increase predicted by the simulation vs. experiment, respectively, differed by between 21% and 31%: tag, 4% vs. 33%; tagâ +â 4, 47% vs. 68%; and tagâ +â 8, 108% vs. 77%. The results from this work provide a direct comparison of computational and experimental estimates of drag, and provide a framework to quantify uncertainty.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152630/1/mms12627.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152630/2/mms12627_am.pd

Bottlenose dolphins modify behavior to reduce metabolic effect of tag attachment

Author Posting. © The Author(s), 2014. This is the author's version of the work. It is posted here by permission of The Company of Biologists for personal use, not for redistribution. The definitive version was published in Journal of Experimental Biology 217 (2014): 4229-4236, doi:10.1242/​jeb.108225.Attaching bio-telemetry or -logging devices (‘tags’) to marine animals for research and monitoring adds drag to streamlined bodies, thus affecting posture, swimming gaits and energy balance. These costs have never been measured in free-swimming cetaceans. To examine the effect of drag from a tag on metabolic rate, cost of transport and swimming behavior, four captive male dolphins (Tursiops truncatus) were trained to swim a set course, either non-tagged (n=7) or fitted with a tag (DTAG2; n=12), and surface exclusively in a flow-through respirometer in which oxygen consumption (Graphic) and carbon dioxide production (Graphic; ml kg−1 min−1) rates were measured and respiratory exchange ratio (Graphic/Graphic) was calculated. Tags did not significantly affect individual mass-specific oxygen consumption, physical activity ratios (exercise Graphic/resting Graphic), total or net cost of transport (COT; J m−1 kg−1) or locomotor costs during swimming or two-minute recovery phases. However, individuals swam significantly slower when tagged (by ~11%; mean ± s.d., 3.31±0.35 m s−1) than when non-tagged (3.73±0.41 m s−1). A combined theoretical and computational fluid dynamics model estimating drag forces and power exertion during swimming suggests that drag loading and energy consumption are reduced at lower swimming speeds. Bottlenose dolphins in the specific swimming task in this experiment slowed to the point where the tag yielded no increases in drag or power, while showing no difference in metabolic parameters when instrumented with a DTAG2. These results, and our observations, suggest that animals modify their behavior to maintain metabolic output and energy expenditure when faced with tag-induced drag.This project was funded by the National Oceanographic Partnership Program [National Science Foundation via the Office of Naval Research, N00014-11-1-0113]. J.v.d.H. was supported by a Postgraduate Scholarship from the Natural Sciences and Engineering Research Council of Canada.2015-10-1

Using Respiratory Sinus Arrhythmia to Estimate Inspired Tidal Volume in the Bottlenose Dolphin (Tursiops truncatus)

Man-made environmental change may have significant impact on apex predators, like marine mammals. Thus, it is important to assess the physiological boundaries for survival in these species, and assess how climate change may affect foraging efficiency and the limits for survival. In the current study, we investigated whether the respiratory sinus arrhythmia (RSA) could estimate tidal volume (VT) in resting bottlenose dolphins (Tursiops truncatus). For this purpose, we measured respiratory flow and electrocardiogram (ECG) in five adult bottlenose dolphins at rest while breathing voluntarily. Initially, an exponential decay function, using three parameters (baseline heart rate, the change in heart rate following a breath, and an exponential decay constant) was used to describe the temporal change in instantaneous heart rate following a breath. The three descriptors, in addition to body mass, were used to develop a Generalized Additive Model (GAM) to predict the inspired tidal volume (VTinsp). The GAM allowed us to predict VTinsp with an average ( ± SD) overestimate of 3 ± 2%. A jackknife sensitivity analysis, where 4 of the five dolphins were used to fit the GAM and the 5th dolphin used to make predictions resulted in an average overestimate of 2 ± 10%. Future studies should be used to assess whether similar relationships exist in active animals, allowing VT to be studied in free-ranging animals provided that heart rate can be measured

Swimming Energy Economy in Bottlenose Dolphins Under Variable Drag Loading

Instrumenting animals with tags contributes additional resistive forces (weight, buoyancy, lift, and drag) that may result in increased energetic costs; however, additional metabolic expense can be moderated by adjusting behavior to maintain power output. We sought to increase hydrodynamic drag for near-surface swimming bottlenose dolphins, to investigate the metabolic effect of instrumentation. In this experiment, we investigate whether (1) metabolic rate increases systematically with hydrodynamic drag loading from tags of different sizes or (2) whether tagged individuals modulate speed, swimming distance, and/or fluking motions under increased drag loading. We detected no significant difference in oxygen consumption rates when four male dolphins performed a repeated swimming task, but measured swimming speeds that were 34% (>1 m s-1) slower in the highest drag condition. To further investigate this observed response, we incrementally decreased and then increased drag in six loading conditions. When drag was reduced, dolphins increased swimming speed (+1.4 m s-1; +45%) and fluking frequency (+0.28 Hz; +16%). As drag was increased, swimming speed (-0.96 m s-1; -23%) and fluking frequency (-14 Hz; 7%) decreased again. Results from computational fluid dynamics simulations indicate that the experimentally observed changes in swimming speed would have maintained the level of external drag forces experienced by the animals. Together, these results indicate that dolphins may adjust swimming speed to modulate the drag force opposing their motion during swimming, adapting their behavior to maintain a level of energy economy during locomotion.Summary Statement: Biologging and tracking tags add drag to study subjects. When wearing tags of different sizes, dolphins changed their swimming paths, speed, and movements to modulate power output and energy consumption

Quantifying the age structure of free-ranging delphinid populations : testing the accuracy of Unoccupied Aerial System photogrammetry

This study was funded by NOAA-PIFSC and RCUH JIMAR (NA19NMF4720181, NA16NMF4320058), CIMAR (NA21NMF4320043), and the Office of Naval Research (N000142012624).Understanding the population health status of long-lived and slow-reproducing species is critical for their management. However, it can take decades with traditional monitoring techniques to detect population-level changes in demographic parameters. Early detection of the effects of environmental and anthropogenic stressors on vital rates would aid in forecasting changes in population dynamics and therefore inform management efforts. Changes in vital rates strongly correlate with deviations in population growth, highlighting the need for novel approaches that can provide early warning signs of population decline (e.g., changes in age structure). We tested a novel and frequentist approach, using Unoccupied Aerial System (UAS) photogrammetry, to assess the population age structure of small delphinids. First, we measured the precision and accuracy of UAS photogrammetry in estimating total body length (TL) of trained bottlenose dolphins (Tursiops truncatus). Using a log-transformed linear model, we estimated TL using the blowhole to dorsal fin distance (BHDF) for surfacing animals. To test the performance of UAS photogrammetry to age-classify individuals, we then used length measurements from a 35-year dataset from a free-ranging bottlenose dolphin community to simulate UAS estimates of BHDF and TL. We tested five age classifiers and determined where young individuals (Publisher PDFPeer reviewe

Quantifying the age structure of free-ranging delphinid populations:testing the accuracy of Unoccupied Aerial System photogrammetry

Understanding the population health status of long-lived and slow-reproducing species is critical for their management. However, it can take decades with traditional monitoring techniques to detect population-level changes in demographic parameters. Early detection of the effects of environmental and anthropogenic stressors on vital rates would aid in forecasting changes in population dynamics and therefore inform management efforts. Changes in vital rates strongly correlate with deviations in population growth, highlighting the need for novel approaches that can provide early warning signs of population decline (e.g., changes in age structure). We tested a novel and frequentist approach, using Unoccupied Aerial System (UAS) photogrammetry, to assess the population age structure of small delphinids. First, we measured the precision and accuracy of UAS photogrammetry in estimating total body length (TL) of trained bottlenose dolphins (Tursiops truncatus). Using a log-transformed linear model, we estimated TL using the blowhole to dorsal fin distance (BHDF) for surfacing animals. To test the performance of UAS photogrammetry to age-classify individuals, we then used length measurements from a 35-year dataset from a free-ranging bottlenose dolphin community to simulate UAS estimates of BHDF and TL. We tested five age classifiers and determined where young individuals (<10 years) were assigned when misclassified. Finally, we tested whether UAS-simulated BHDF only or the associated TL estimates provided better classifications. TL of surfacing dolphins was overestimated by 3.3% ±3.1% based on UAS-estimated BHDF. Our age classifiers performed best in predicting age-class when using broader and fewer (two and three) age-class bins with ~80% and ~72% assignment performance, respectively. Overall, 72.5%–93% of the individuals were correctly classified within 2 years of their actual age-class bin. Similar classification performances were obtained using both proxies. UAS photogrammetry is a non-invasive, inexpensive, and effective method to estimate TL and age-class of free-swimming dolphins. UAS photogrammetry can facilitate the detection of early signs of population changes, which can provide important insights for timely management decisions