In the belly of the beast: resolving stomach tag data to link temperature, acceleration and feeding in white sharks (Carcharodon carcharias)
© Jorgensen et al. 2015
Received: 2 February 2015
Accepted: 11 September 2015
Published: 2 November 2015
Motion detecting archival data loggers such as accelerometers have become increasingly important in animal biotelemetry and offer unique insights into animal behavior, energetics, and kinematics. However, challenges remain for successful deployment and interpretation of data from captive and wild animals. Accelerometer sensors require being packaged in an archival tag that has a firm attachment in a fixed (known) orientation to accurately measure the relevant motion of the animal. This requirement can lead to handling stress and attachment techniques that can affect the tagged animal’s natural behavior and welfare, and lead to behavioral artifacts in the data. Accelerometer data also require careful interpretation to correctly identify behavioral events of interest such as foraging. For endothermic species, changes in stomach temperature can produce temperature signatures indicative of foraging events. In this paper, we present a novel method for recording foraging events in free-swimming white sharks.
We used a combination of accelerometer loggers and pop-up archival transmitting (PAT) tags (MK10, Wildlife Computers) to examine the feeding and kinematics of white sharks (Carcharodon carcharias) in the wild. We validated feeding results using a captive juvenile white shark where controlled feeding experiments could be conducted in an aquarium setting at the Monterey Bay Aquarium. We fed data logger instrument packages to eight free-swimming white sharks. Deployment durations ended naturally when the package was regurgitated and ranged from 2 to 12 days. While inside the stomach, the orientation of the data logger package was arbitrary and resulted in slow shifting over time, a challenge for normal analysis routines. We present one of these datasets to illustrate a novel methodology for calibrating accelerometer orientation, and evaluate the utility of resulting data.
We obtained accurate accelerometer measurements including surge, heave, and sway from data loggers with shifting orientation through data post-processing. We measured consistent dips in stomach temperature followed by a steady prolonged heating during controlled feeding events in a captive white shark. Similar thermal signatures identified in wild white shark records confirmed feeding events while acceleration data characterized the associated prey capture behavior.
We provided proof of concept for a novel and non-invasive technique for accelerometer data logger deployment extending the possibilities for their use in bio-logging. The placement of data-logging tags in the stomachs of endothermic white sharks produced high quality tri-axial acceleration data in addition to stomach temperature data capable of detecting feeding events. The technique has the potential for distinguishing between attempted and successful foraging events. This approach to accelerometer coordinate correction could be applied in other systems where logger orientation is unknown or changes after deployment.
Animals spend the vast majority of their lives outside of our view, historically making the acquisition of data on their behavior, ecology and physiology challenging [1, 2]. This is especially true for marine animals. The advent of biotelemetry and more recently biologging has opened the doors to gathering data on many aspects of the biology of these animals. Initially, such data included simple locational telemetry (e.g., via radio or acoustic signals) and largely focused on reconstructing the geographical movement of the tagged individuals. Over the last decade, advances in data-logging capacity have resulted in a proliferation in the sensors available to measure behavioral, as well as physiological parameters [3–6]. Tags containing these new sensors collect vast amounts of data that are not easily remotely transferable due to data transmission limitations. As a result, data are usually archived in on-board memory and have to be physically recovered to be accessed. While many of these sensors have been increasingly used in air-breathing endotherms [7, 8], their incorporation into research studying fish has been slower [9–11]. Whereas most birds or seals predictably roost or haul-out on land, permitting their capture and recapture with minimal stress, fish can often only be captured with hook and line, with attendant risks to the animal’s health [12–14]. Another significant hurdle is represented by the ability to recapture a tagged individual, which in most cases is unlikely using conventional fishing. Although, this can be a viable method to reacquire archival tags in a heavily fished commercial species . One way to tag individuals without capture stress is to deploy tags on free-swimming animals, which is usually performed using some form of darting system [16, 17]. Because such systems are usually based on tethers, they are unlikely to have much application in motion-sensitive tags .
A number of methodological solutions have been adopted to facilitate recovery of data-logging tags. The most common rely on a timed release mechanism (either of galvanic nature or electronic), a buoyant housing, and a VHF or Argos transmitter [10, 18]. This allows tags to be located after they have released from the fish. Although VHF transmitters have substantial ranges, fish can swim long distances in a matter of days. This limits the technique, in general to short deployments (<5 days) to ensure that tags are recovered [10, 19, 20]. Additionally, stressful capture and release can disrupt the natural behavior of tagged fish for periods ranging from a few hours to days [14, 21, 22], reducing the amount of natural behavior recorded from individuals, and risking the animal’s survival and well-being, which might be especially important in threatened species .
Accelerometer data also require careful interpretation to correctly identify behavioral events of interest such as foraging. For endothermic species, changes in stomach temperature can produce temperature signatures indicative of foraging. Heat increment of feeding has been recorded in endothermic sharks and tunas with stomach tags [24–26]. Although many factors influence the thermal record of digestion events (e.g., body size, meal size, and ambient temperature), the capacity to detect feeding events in stomach or peritoneal tag thermal records has been well established. The heat increment is associated with the metabolic processes of digestion. Once ingested, food is subject to mechanical and enzymatic digestion and the process of this specific dynamic action (SDA) results in a metabolic increment of oxygen consumption with a heat by-product . Furthermore, in many cases ingestion results in stomach temperature reductions attributable to the potential cooler temperature of the prey, or food item, and associated influx of ambient water. These reductions in temperature or dips can be used to mark the initiation of the feeding event [27, 28].
Here we describe a novel method to deploy accelerometers in the stomachs of large free-swimming sharks and how, with the addition of stomach sensors, unique insights into feeding behavior can be achieved . The system is tested on white sharks (Carcharodon carcharias) during their annual coastal residency off the California coast. Stomach temperature data interpretation was validated in a captive specimen in a controlled ocean pen and aquarium setting .
While inside the shark’s stomach, the orientation of the acceleration data logger was arbitrary and resulted in slow shifting over time, a challenge for acceleration data analysis. To address this problem, we developed a procedure using the acceleration data in relation to the recorded changes in depth and tail motion to solve the orientation of the logger relative to the shark’s body iteratively over the course of the record (Fig. 1b).
Acceleration data analysis
We developed a post-processing procedure (described below) for determining the logger orientation at regular time intervals, and then transformed the data coordinate system to align with a prone orientation of the sharks body (Fig. 1b). A calibrated tri-axial accelerometer that is held static should measure −1.0 g in the direction of the earth’s center of mass. Re-setting the coordinate space orientation to a static accelerometer would require only a simple coordinate transformation minimizing acceleration along the Z axis; however, the dynamic motion of the shark must be accounted for (e.g., ascending, descending, rolling, turning or surging). Over long time periods it is accurate to assume that the average orientation of a continually swimming ram-ventilating shark is in the prone position since the duration of ascending and descending periods should tend toward parity. This applies to the frequency of other motions such as left and right tail beats. We sought to determine the minimum time window (non-overlapping) over which this assumption holds. We calculated the mean change in depth between successive measurements within time windows ranging from 1 to 20 min. We then calculated the mean and variance among the window means and plotted these as a function of window size. We selected the minimum window threshold at a point when the mean tended toward zero and variance also approached a minimum asymptote. We then developed routines for coordinate space correction within each time window. We assumed that over short time periods (>time window) the tag orientation inside the shark’s stomach remained constant, and tested this assumption post hoc. The orientation solution has three steps, corresponding with the three dimensions. We developed Matlab (Mathworks) routines to execute these steps (Additional files 1, 2, 3, 4, 5, 6, 7).
Step 1: solve the vertical orientation of the Z axis
Once the vertical (Z axis) orientation of the logger has been solved relative to the shark’s average prone position, the remaining solution must lie along a single rotational plain about the Z axis (Fig. 1b) and can be accomplished in two additional steps.
Step 2: solve the lateral orientation of the Y axis
While this step aligns the coordinate space laterally, it does not discriminate between left and right; therefore the final remaining step, determining front and back, has two possible solutions.
Step 3: solve the horizontal orientation of the X axis
After solving for the lateral axis, the adjusted coordinate space should be either already correctly oriented (front-back) or else remains to be reversed 180° with respect to the horizontal X axis (rotating about the Z axis). Assuming a clear positive relationship between vertical displacement and pitch over the time window, we tested the slope of this relationship (standard linear regression) and, if a negative slope was found, the coordinate space orientation was re-set by multiplying vectors X i and Y i by negative one; effectively rotating 180° about the Z axis.
Overall dynamic body acceleration (ODBA) was calculated from the X, Y, and Z acceleration as their sum minus static acceleration determined from a 6 s running mean of the same as per . To visually evaluate relative sustained ODBA over a longer time period (300 min), ODBA was further smoothed by applying a 40-s running mean.
Controlled feeding validation
For a controlled validation experiment of stomach temperature as a measure of prey ingestion, we instrumented a captive white shark with an acoustic sensor tag (V16TP, Vemco) measuring temperature and pressure. The tag was concealed in a salmon fillet and freely ingested by the shark. Stomach temperature data transmitted from the tag were recorded via acoustic receiver (VR2, VEMCO) and ambient temperature was logged using a temperature logger (Tidbit, ONSET). The time, mass, and caloric content of meals fed to the captive white shark were recorded in relation to changes in stomach temperature.
Using a novel method for determining accelerometer logger orientation inside a swimming animal, we corrected tri-axial acceleration data coordinate space to produce accurate measurements of sway, surge, and heave after post-processing. Signature dips in stomach temperature followed by steady and prolonged heating occurred during controlled feeding events in a captive white shark.
Stomach tag packages deployed in white sharks in the wild
Date and time
Accelerometer data correction
Stomach temperature and feeding signature
Some additional stomach temperature dips were recorded at times other than when food was intentionally offered both in the pen and inside the Aquarium (for instance on day eight; Fig. 4) and may be associated with ad lib feeding events. Subsequent steady rises in the stomach temperature were consistent with caloric intake, whereas a temperature dip without a subsequent increment would suggest water influx without food. At both locations, schooling fishes such as Pacific sardine (Sardinops sagax) were available for potential predation by the instrumented white shark; therefore, the occurrence of additional uncontrolled feeding events could not be ruled out.
The field of biologging has increasingly relied on the use of accelerometers and other motion-based sensors as vital new tools to advance physiological, kinematic, and behavioral aspects of animal ecology [6, 30–32]. However, key challenges remain for increasing deployment feasibility and reducing deployment related stress that can introduce behavioral artifacts and animal health risks . One key challenge is to further develop tag placement options that can reduce stress and additionally provide secondary validation for identifying specific biological activities such as foraging. Here we demonstrated the effective use of motion-sensitive data loggers inside the stomach of a large swimming endotherm, the white shark. By introducing the tag wrapped in appropriate food material, the instruments were voluntarily consumed and stress was minimized. The instrument packages were naturally retained in the sharks’ stomach for time periods appropriate to the memory and power capacity of contemporary instruments (2–29 days). We also overcame the requirement to firmly mount the instruments using potentially invasive techniques, and instead solved for the tag’s orientation inside the shark’s stomach and then reoriented the coordinate space in post-process.
Stomach tags have been used to measure and identify signature temperature changes and quantify feeding in a variety of endothermic marine taxa including fishes , birds , and mammals . In combination, acceleration and stomach temperature data have the capacity to distinguish between successful and attempted prey capture, while stomach temperature alone cannot detect unsuccessful foraging attempts, and acceleration alone cannot confirm successful ingestion of prey. Distinguishing foraging attempts and successful ingestion can help better inform energy budgets and foraging strategies which can be particularly relevant for species such as large predatory sharks that may forage only occasionally . This approach could also be extended to ectothermic species by recording additional measurements such as impedance  that can reflect digestive activity when temperature alone cannot.
Acceleration data can also provide invaluable data on hunting behavior. In this record presented, after coordinate space correction, we were able to recreate the motion and locomotion of the shark during a successful predation event. The captive feeding experiment provided an opportunity to evaluate stomach temperature responses to feeding in both constant and variable ambient temperature environments, validating the interpretation of the wild shark record. For instance, the captive shark was offered single bite-size meals, and the stomach temperature dips corresponded to each feeding event. In the wild shark record there was a series of temperature dips over approximately 45 min. A series of temperature dips, rather than a single dip, could result from multiple feedings on small prey, or consumption of a large prey requiring multiple bites to consume. Capturing multiple small prey should elicit a corresponding number of locomotory bursts from the predator, whereas capturing one large prey could result from only a single relatively large burst of acceleration. The single large burst in ODBA in the wild shark prior to the stomach temperature dips (Fig. 6c) was therefore more consistent with pursuit and capture of a single large prey item, which was then consumed in a series of bites. The corrected heave, surge, and sway traces together with the depth and temperature data enable further reconstruction of the predation sequence.
During coastal foraging in California white sharks commonly patrol at depths between 5 and 50 m [36, 37], presumably facilitating visual perception of pinniped prey silhouetted against the diffuse lighting of the ocean surface [38, 39]. Visually oriented vertical approaches to experimental decoys are typically initiated from depths ≥17 m . The constant depth (~28 m) swimming in the minutes before the burst assent in our wild shark data was consistent with this scenario (Fig. 6a, b). Contact with the prey likely occurred at the apex of the ascent just after second 90 (Fig. 6). At this point, there was a sudden decrease in surge and sway, while heave remained relatively constant, indicative of sudden deceleration or rapid turning. Such sudden deceleration is consistent with impacting a large prey item. Following this purported initial ‘strike,’ a sustained period of relatively high overall acceleration and body movement followed, lasting about 30 s. Together, the burst ascent and period of elevated body movement near the surface lasted 40–50 s and accounted for the sustained elevated ODBA period prior to ingestion (Figs. 5d, 6c).
Interestingly, the series of stomach temperature dips indicating ingestion only began some 60 min after the burst ascent. Following initial strikes, white sharks often release their prey and return to it after minutes or hours [38, 41]. Occasionally, they also seize and transport pinniped prey tens or hundreds of meters away  (unpublished observations). Relocating a large prey outside the initial blood plume before partitioning into bites may reduce competition from opportunistic conspecifics attracted by the scent. After the initial burst ascent, the shark made two more ascents to a similar shallow depth over a period of 10 min (Fig. 6a). Following the third ascent, there was period of near-surface swimming (Fig. 6b) characterized by low sustained ODBA (Fig. 6c) and gradually decreasing stomach temperature (Fig. 6b). This period lasted almost an hour and ended with the onset of the stomach temperature dips (~minute 100). This discrete pattern of relatively constant depth swimming differed substantially from the subsequent depth oscillations after minute 120 when the stomach temperature rose smoothly indicating feeding was complete. Between the purported initial ‘strike’ and the ingestion of the prey, the stomach temperature decreased gradually but unevenly (Fig. 6; minutes 30–90). This variable decrease likely reflected small intermittent influxes of ambient seawater, which might be expected if the shark swam with mouth opened wider than usual while holding and transporting the prey.
This detailed reconstruction provides a proof of concept for stomach deployment of motion-based sensors including accelerometers. It has to be noted that during accelerated motions accelerometers become increasingly unreliable in estimating attitude in sea turtles, and that full inertial sensors, including gyroscopes are needed to more accurately determine pitch and roll . This same technique can extend to magnetometer and gyroscopic sensors as well, and should lead to even better behavior reconstruction.
Successful re-orientation of the coordinate space depends on the diving behavior of the subject. The time window over which mean position of the shark can be assumed to be prone will vary as a function of factors such as habitat depth, and extent and frequency of vertical excursions. For example in a subject that makes only short ascents and descents (narrow depth-range), a relatively small time window will suffice compared to a subject that makes longer or slower vertical excursions. Therefore, the appropriate time window should be calculated independently for each deployment while the same threshold for variance and mean vertical displacement can be used as described here (Fig. 2).
This specific example of successful accelerometer logger deployment and data interpretation illustrates a general approach to deployment options that does not require fastening or a priori knowledge of logger orientation. This approach can be extended to numerous other systems, and to cases where recalibration is necessary following post-deployment shifting of logger orientation. Although approaches to solving logger orientation will likely differ between swimming and other modes of locomotion, the same principles will apply in many cases.
In this example of accelerometer deployment, we provide proof of concept for a novel and non-invasive technique extending the possible uses of motion sensors such as accelerometers, magnetometers and gyroscopes in bio-logging. By placing data logging tags in the stomachs of endothermic white sharks through voluntary consumption, we were able to produce high quality tri-axial acceleration data in addition to stomach temperature data to detect feeding events and behavior. In this application, the technique has the potential for distinguishing between attempted and successful foraging events. Furthermore, this approach to motion sensor deployment and coordinate correction can be applied in other systems where logger orientation is unknown or has changed after deployment.
Conceived and designed the experiments: SJJ ACG JME BAB. Performed the experiments: SJJ ACG PEK SDAWTB TKC PEK. Analyzed the data: SJJ WTB. Contributed reagents/materials/analysis tools: SJJ ACG BAB. Wrote the paper: SJJ ACG. Edited and improved the manuscript: ACG BAB JME PEK. All authors read and approved the final manuscript.
We thank J. Barlow, R. Elliot, A. Carlisle, R. Hamilton, T. O’Leary, C. Logan, J. Cornelius, B. Becker, C. Farwell, C. Harrold, R. Kochevar, K. Lewand, J. O’Sullivan, J. Ganong, L. Rodriguez, J. Welsh, M. Murray, C. Lowe, B. Bettencourt, A. Swithenbank, M. Castleton, A. P. Klimley, and C. Winkler and the entire elasmobranch husbandry team at the Monterey Bay Aquarium for assistance with field work, lab work, data processing, editing and inspiration. We are grateful to the UC Davis boating program, and the crew of the F/V Barbara H for vessel support. Funding was provided by the Monterey Bay Aquarium Foundation.
The authors declare no competing interests.
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