Bio-Logging, New Technologies to Study Conservation Physiology On
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Erschienen in: Journal of Comparative Physiology A ; 203 (2017), 6-7. - S. 531-542 http://dx.doi.org/10.1007/s00359-017-1180-x J Comp Physiol A (2017) 203:531–542 DOI 10.1007/s00359-017-1180-x ORIGINAL PAPER Bio‑logging, new technologies to study conservation physiology on the move: a case study on annual survival of Himalayan vultures Sherub Sherub1,2,3 · Wolfgang Fiedler2,3 · Olivier Duriez4 · Martin Wikelski2,3 Received: 5 March 2017 / Revised: 1 May 2017 / Accepted: 4 May 2017 / Published online: 13 June 2017 © The Author(s) 2017. This article is an open access publication Abstract Bio-logging, the on-animal deployment of min- We highlight fight experience, long distance movements, iaturised electronic data recorders, allows for the study and remote places with low human population as factors of location, body position, and physiology of individuals critical for the survival of Himalayan vultures. High-reso- throughout their ontogeny. For terrestrial animals, 1 Hz lution bio-logging studies can advance conservation man- GPS-position, 3D-body acceleration, and ambient tem- agement by pinpointing where and why migratory animals perature provide standard data to link to the physiology of have problems and die. life histories. Environmental context is added at ever fner scales using remote sensing earth observation data. Here Keywords Conservation physiology · Migration · Annual we showcase the use of such bio-logging approaches in a movement · Survival · Environmental parameters conservation physiology study on endangered Himalayan vultures (Gyps himalayensis). We determine environmen- Abbreviations tal, behavioural, and physiological causes of survival in 3D Three dimensional immature birds that roam from wintering sites in India, ACC Acceleration Bhutan, and Nepal towards summer areas in Tibet and ECMWF European centre for medium-range weather Mongolia. Five of 18 immature griffons died during one Forecasts year. Individuals that died had failed to migrate suffciently GPRS General packet radio service far northward (>1500 km) in spring. Individuals likely GPS Global positioning system died if they few against headwinds from the north or were GSM Global system for mobile communications less able to fnd thermal updrafts. Surviving individuals Hz Hertz migrated to cold and dry areas with low population density. IMU Inertial measurement unit IUCN International union for conservation of nature MODIS Moderate-resolution imaging * Martin Wikelski Spectroradiometer [email protected] NDVI Normalized difference vegetation index 1 Ugyen Wangchuck Institute for Conservation NSAID Non-steroidal infammatory drugs and Environment Research, Lamai Goempa, Bumthang, ODBA Overall dynamic body acceleration Bhutan SRTM Shuttle radar topography mission 2 Department of Migration and Immuno‑Ecology, Max-Planck UTC Coordinated universal time Institute of Ornithology, Am Obstberg 1, 78315 Radolfzell, Germany 3 Ornithology, Konstanz University, 78457 Constance, Introduction Germany 4 Centre d’Ecologie Fonctionnelle et Evolutive, UMR 5175 Physiological investigations of animals can now increas- CNRS-Université de Montpellier-EPHE-Université Paul Valery, 1919 Route de Mende, 34293 Montpellier Cedex 5, ingly ‘go wild’ with the rapid advancement of ever smaller France electronic bio-logging units (Block 2005; Ropert-Coudert 1 3 Konstanzer Online-Publikations-System (KOPS) URL: http://nbn-resolving.de/urn:nbn:de:bsz:352-0-422721 532 J Comp Physiol A (2017) 203:531–542 and Wilson 2005; Wilson et al. 2008, 2014, 2015; Bridge et al. 2015). Similarly, the sickness behaviour of ani- et al. 2011). Such investigations into the exact details and mals—perhaps one of the best remote measurements of physiological mechanisms underlying life history or popu- health in wildlife—can be inferred from 3D-acceleration lation processes are increasingly important today in light loggers (Wilson et al. 2014). Even more so, stressful situ- of widespread, global population declines of many animal ations generally change the way bodies are moving, which species (Wikelski and Cooke 2006; Morales et al. 2010; again is easily detected using 3D-acceleration sensors. Ide- Cooke et al. 2014; Lennox et al. 2016). Researchers in the ally, other sensors that help to fne-position a body in space bio-logging feld deploy animal-attached micro-electronic such as gyroscopic, magnetic, and pressure sensors can be units (‘tags’) that record behaviour, movement, physiol- combined with 3D-acceleration sensing to achieve a near- ogy, and environment while an individual is conducting its perfect reconstruction of the spatial state of an individual day-to-day activities, potentially leading to a golden age at critical times during its life (Wilson et al. 2014; Williams in ecology and physiological ecology (Kays et al. 2015; et al. 2017). Such IMU (inertial measurement unit) tech- Wilmers et al. 2015). nology is already highly developed in commercial felds State-of-the-art bio-logging tags include many different such as drone fight and is now adapted to physiological sensors and record from them with a suffciently high sam- wildlife studies (Floreano and Wood 2015). 3D-accelera- pling rate to allow for a near-complete reconstruction of an tion logging also allows a frst glimpse into the energetics individual’s 3D-path through its environment, its movement of an individual via the calculation of ODBA, the overall characteristics, behavioural changes as well as a dynamic dynamic body acceleration (Wilson et al. 2006; Halsey assessment of its internal physiological state (Hawkes et al. et al. 2011). Although it is only a crude frst estimate of the 2013; Bishop et al. 2015; Scott et al. 2015). Usually, the detailed energy expenditure of an individual, ODBA is very on-board power supply is too weak and the memory capac- helpful in understanding long-term differences in energy ity of the bio-logging tag is too small to record high-defni- use between species, populations, and individuals, as well tion data continuously, thus, timed sub-sampling is used to as in individuals over time and space. As a very helpful tool gain a statistically valid picture of an individual life (Hol- in conservation physiology, it is now possible to construct land et al. 2009; Shamoun-Baranes et al. 2012). Commonly ‘energetic landscapes’ to understand which locations within used sensors report GPS position, 3D-accelerometry, light- the movement range of an individual demand more power level information, conductivity, salinity, external as well from the animal than others (Scharf et al. 2016). as body temperature, heart rate or neuro-state (Rattenborg The internal state of an individual is perhaps best et al. 2008a; Nathan et al. 2012). As these sensors have dif- approximated from body temperature and heart rate log- ferent power requirements, not all of them can be recorded ging (Butler et al. 2002, 2004). Based on Fick’s equation, at the same rate. The most power hungry sensor, GPS posi- heart rate can provide a good proxy for true energy expend- tioning, is often scheduled either using a ‘behavioural’ iture of an individual if the stroke volume is constant 3D-acceleration trigger, i.e., only starts when the animals or known, and if the oxygenation of the blood does not become very active or when it starts beating its wings change much (Halsey et al. 2008). Combined with ODBA (Brown et al. 2012; LaPoint et al. 2013). Alternatively, GPS measurements, the quantifcation of heart rate provides a sensing is scheduled whenever the battery power is suff- rather comprehensive assessment of instantaneous energy ciently high to allow for high-defnition reporting, usually expenditure, stress, and movement energetics (Halsey et al. at 1 Hz intervals (Flack et al. 2016), but reaching up to 2009; Clark et al. 2010; Duriez et al. 2014). The concurrent 10 Hz (Bouten et al. 2013). quantifcation of body temperature adds an important com- One of the most powerful and simple sensors for con- ponent of thermoregulation (potential heat and cold stress), servation physiologists, 3D-acceleration, has not yet but—depending on context—may also indicate a disease or reached its full analytical potential (Wilson et al. 2006; an immune response (Adelman et al. 2010, 2014). Shepard et al. 2008; Gleiss et al. 2011; Nathan et al. 2012). In the future, bio-logging tags that possess all above- 3D-acceleration sensors can easily be attached externally, mentioned sensors will become common and be miniatur- e.g., in a leg band or an ear tag, and can be calibrated ised massively (Wikelski et al. 2007; Bridge et al. 2011). against behaviour either on a population or (ideally) indi- Additional features in tags will include on-board cameras vidual level (Nathan et al. 2012; Brown et al. 2013). Com- that are triggered by pre-set (previously observed and bined with the location context from GPS logging, the internally programmed) behavioural changes to also allow body acceleration can provide unprecedented details about researchers to study the social context of individuals, both the physiological and health state of an individual. Wil- within conspecifc groups as well as during interspecifc son et al. (2014) showed that even the past medical his- interactions (Watanabe and Takahashi 2013; Kane and tory of people can be detected via the fne-scale reporting Zamani 2014; Hays 2015). Understanding the collective of 3D-acceleration vibrations (Wilson et al. 2014; Sands behaviour of individuals in the wild is of great importance 1 3 J Comp Physiol A (2017) 203:531–542 533 as we appreciate more and more that physiological changes and time (Shamoun-Baranes et al. 2010). As the satellite during the life history of individuals are strongly infu- and in situ remote sensing systems have become public enced by biological interactions (Chikersal et al. 2017). and much more generally available recently (Turner et al. Another aspect of the movement physiology of animals 2015), there even exist automated environmental annota- that can soon be quantifed better is the relative positioning tion facilities such as the Env-Data Module in Movebank of limbs or other body parts relative to each other.