- Open Access
Circadian behaviour of Tectus (Trochus) niloticus in the southwest Pacific inferred from accelerometry
© Jolivet et al. 2015
- Received: 2 January 2015
- Accepted: 6 September 2015
- Published: 16 September 2015
Behaviour and time spent active and inactive are key factors in animal ecology, with important consequences for bioenergetics. For the first time, here, we equipped the gastropod Tectus (= Trochus) niloticus with accelerometers to describe activity rhythms at two sites in the Southwest Pacific with different temperature regimes: New Caledonia and Vanuatu.
Based on a 24-hour cycle, T. niloticus activity began at dusk and gradually stopped during the night, before sunrise. This nocturnal behaviour was characterised by short (duration <30 s), low intensity (acceleration < 0.12 ɡ) movements and was probably associated with foraging behaviour. We assumed that activity ceased once the animal was satiated. Our analysis of two size groups in Vanuatu (80–90 mm vs. 120–140 mm, basal shell diameter) revealed a size effect; smaller specimens displayed greater activity, reflected by more intense and longer movements while migrating at night toward the edge of the reef. This nocturnal behaviour is not uncommon for grazing gastropods and is mainly associated with attempting to avoid visual predators whilst feeding.
The use of accelerometers coupled with light and temperature sensors provided detailed information on topshell behaviour and physiology under natural conditions. These data provide a foundation for identifying potential changes in the fine-scale behaviour of T. niloticus in response to environmental changes, which is essential in animal ecology and stock conservation.
- 24-hour periodicity
- Tectus niloticus
Behaviour is a fundamental part of the biology of organisms; it is a manifestation of the response of an individual to its environment and provides a connection to the organism’s physiological condition [1, 2]. Understanding and quantifying animal behaviour has important implications for conservation, particularly when combined with knowledge on space usage, since appropriate localities often need to be protected. Generally, behavioural descriptions have been obtained through direct observations that are limited to a small fraction of an animal’s daily activities; however, animals could be affected by the presence of the human investigator [3–5].
Over the past few years, animal-attached technology has been increasingly used to address issues related to conservation [1, 6, 7]. Remote monitoring of animal behaviour allows investigators to locate and observe animals and to record their habits with virtually no limitations due to visibility, observer bias, or geographic scale [1, 8, 9]. Accelerometry is a valuable method for obtaining descriptions of behaviours, such as locomotion, foraging, and escaping predators, as well as exploring the influence of environmental parameters and/or energy budgets in a range of animals [10–14]. Combining this technology with others sensors on tagged animals, such as light and ambient temperature sensors, allows the examination of activity rhythms in relation to environmental conditions [15–17]. Brown et al.  noted that accelerometry studies between 1998 and 2012 generally focused on mammals, birds, fish or reptiles, encompassing only three molluscs: the cuttlefish Sepia apama , the giant squid Dosidicus gigas , and the great scallop Pecten maximus [11, 19]. To our knowledge, gastropods have not yet been investigated in this framework.
The topshell Tectus niloticus, formerly known as Trochus niloticus, has been harvested for subsistence and commercial purposes in the Indo-West Pacific [20, 21]. Overfishing of topshells has been reported in many areas [22, 23], resulting in the implementation of fisheries management -based size restrictions, closed seasons, marine sanctuaries, and restocking [24–30]. This species is distributed on outer reef flats and reef crests with abundant stony corals, on areas of turf algae for adults, and on intertidal reef flats with stony coral/rubble bottom for juveniles [28, 31–33]. T. niloticus is found on coral reefs from high water to 20 m depth but they are abundant at depths of <8 m [28, 34]. The highest densities of T. niloticus are in areas characterized by substrates with low structural complexity with a heavy cover of coral rubble, algal pavement and unobstructed exposure to surf [22, 34, 35]. These topshells are nocturnally active, grazing herbivores that hide in the holes and crevices of massive corals like Porites during daytime [21, 36, 37]. T. niloticus usually live for 15–20 years , reach reproductive maturity after two years (when they are ~ 6 cm, basal shell diameter) [21, 36, 39] and have limited dispersal capabilities [20, 39].
Although the nocturnal behaviour of topshells has already been observed [21, 36, 37], to our knowledge no quantification of their nocturnal activity has been performed. Here, we applied accelerometry technology to characterise the duration and intensity of T. niloticus activity in their natural environment in New Caledonia and Vanuatu. We also compared T. niloticus activity to metabolic measurements performed simultaneously and published in a companion paper .
The HOBO Pendant G data logger (UA-004-64, Onset Computer Corporation) is an accelerometer with the ability to measure acceleration in three axes with a range of ± 3 ɡ (29.4 m.s−2) at a resolution of 0.025 ɡ (0.245 m.s−2) and with accuracies of ± 0.075 ɡ (0.735 m.s−2) at 25 °C and ± 0.105 ɡ (1.03 m.s−2) from −20 °C to 70 °C. The data logger is packaged in waterproof housing and has dimensions of 58 × 33 × 23 mm (sectional area 7.6 cm2). Its memory capacity of 64 kB allows the data logger to record movements for 24 h and 13 min at a frequency of 0.25 Hz. Data were downloaded and recording was reset every 24 h using a HOBO Waterproof Shuttle (U-DTW-1, Onset Computer Corporation). The download took less than one minute per individual, and was carried out directly on the topshells without moving or manipulating them.
Fieldwork was conducted in New Caledonia in July 2012 and in Vanuatu in June 2013, representing the cool season for each location. All T. niloticus specimens were harvested via scuba diving or snorkelling. Study sites were reef flats characterised by mixed substrate (slab, live coral branching, and coral debris) and shallow water (~2 m in depth). For both sites, a HOBO Waterproof Pendant data logger (UA-002-68, Onset Computer Corporation) was used to acquire temperature (°C) and relative light level (lumens m−2) with a frequency of one measurement per minute over the monitoring period.
Main characteristics (mean ± standard deviation) of topshells and activities according to site and size
108.9 ± 25.9
132.3 ± 9.2
85.5 ± 5.1
Activity (per specimen)
414 ± 101
335 ± 85
484 ± 94
443 ± 151
327 ± 118
560 ± 66
393 ± 98
319 ± 85
449 ± 99
429 ± 145
320 ± 119
539 ± 60
1 ± 3
0 ± 1
2 ± 2
2 ± 5
0 ± 1
4 ± 6
7 ± 11
5 ± 7
15 ± 13
9 ± 13
5 ± 4
14 ± 17
13 ± 6
10 ± 5
17 ± 7
1 ± 2
2 ± 3
1 ± 2
Movement duration (min)
131 ± 50
89 ± 25
188 ± 54
178 ± 103
88 ± 38
269 ± 53
In Vanuatu, four large and four small topshells were equipped with accelerometers (Table 1). They were harvested on June 3, 2014 off Mangaliliu (17°38.248 S; 168°12.034 E; Fig. 1) and released 1 h later, equipped with accelerometers, 10 m away from the capture site. Recording began on June 4, 2013 at 12:30:00 and was stopped June 7, 2013 at 11:25:00, corresponding to a 71-h recording period.
Data from the accelerometers were downloaded onto a personal computer using HOBOware ® Pro 3.0.0. Acceleration values were given in units of ɡ, where ɡ represents acceleration due to gravity (1 ɡ = 9.81 m s−2).
Under static circumstances, such as during rest or after death or in the case of any absence of movement caused by the environment, accelerometer signals only represent the gravitational force acting on the sensors. When an animal is moving, sensor output represents acceleration due to gravity plus the inertial acceleration generated by movement. An approximation of absolute acceleration (in ɡ) resulting only from dynamic acceleration in each dimension was extracted from each axis following removal of static acceleration using a running mean over 25 points corresponding to 1.5 min . A derivative of dynamic body acceleration, the vector sum of dynamic body acceleration (VeDBA, in ɡ), was calculated from tri-axial acceleration data as VeDBA = √ (ax2 + ay2 + az2) [42–45]. Here, ax, ay and az were dynamic acceleration values derived from raw x,y,z acceleration data . These data represented the acceleration recorded by the data logger owing to the dynamic movement of that individual [41, 43]. Acceleration data were then processed using the packages FullDBA and BeFeatures within BEnergetix in the free R software .
After data processing, each identified movement was characterised by its duration D (in seconds and minutes), the average acceleration VeDBA mean (in ɡ) and the total acceleration VeDBAtot (VeDBAtot = VeDBAmean x D). For each analysed specimen, these data were compiled in 30-min intervals (a time slot of 00:00 corresponded to movement that occurred between 00:00:00 and 00:29:59) by summing the movement data within each interval (denoted by the subscript act), or by averaging these data to characterise movements performed over this period (denoted by the subscript mov). The obtained parameters were: N = number of movements made in the interval; Dact = cumulative duration of movement; Dmov = average duration of movements; VeDBAact = average acceleration of activity during the interval (VeDBA act (in ɡ) = (Σ VeDBAtot)/30 min); and VeDBAmov = average acceleration of movements performed during the interval.
Where S is a scalar, Topt is the temperature (in °C) at which VeDBA is maximised, σ is the standard deviation for the normally distributed curve.
We identified 52 977 and 10 638 movements in New Caledonia and Vanuatu, respectively (Table 1). Overall, the characteristics of these data were similar between sites: Dmov ranged from 4 s (acquisition frequency) to 10 min, with average acceleration VeDBAmov of 0.017 - 0.75 ɡ. Eighty-three percent of movements lasted < 30 s, with VeDBAmov of 0.08 ± 0.03 ɡ.
The effect of size on activity
Rhythms of activity
Determining the periods of active behaviour is essential in animal ecology. In this study, we presented one of the first uses of accelerometers on a gastropod, T. niloticus, in order to describe the activity rhythms of this organism at two sites (Vanuatu and New Caledonia).
The instrumented topshells clearly displayed activity based on a 24-h cycle, with 95 % of movements made at night. Activity began abruptly around 17:30, regardless of the study site and water temperature. Activity levels were intense until midnight and then slowly decreased until sunrise. This nocturnal activity was previously known due to direct observations and was associated with reproduction [36, 39] as well as feeding; topshells are grazing herbivores and detritivores, but no quantification of this activity has been made [21, 36, 37]. Since the breeding season is between November and May, the movements measured here in June-July and mostly of low intensity (duration <30 s, VeDBAmean <0.12 ɡ) would likely correspond to foraging movements. While the activity start was common to all topshells, the activity stop varied among individuals during the night time. This behaviour could be associated with a state of satiation being reached during the night. This nocturnal behaviour is not unusual and has been observed in other gastropods such as Gibbula nivosa , Turbo marmoratus , Turbo chrysostomus , and Haliotis asinia , and was always associated with feeding behaviour. To validate this hypothesis, the study of the gut contents of T. niloticus during a 24-h cycle could be considered as previously performed on Haliotis asinia .
On a 24-h cycle, dusk is a period in which algae had maximum nutrients at the end of the photosynthetic period corresponding to profitable conditions for grazers to feed at the end of the light period [53, 54]. Moreover, the concentration of oxygen was maximized [55, 56], and turbulence due to trade winds was low  which were favourable conditions for the initiation of topshell activity. For many of the common coral reef herbivorous macroinvertebrates, such as gastropods [51, 58, 59] and small crabs , nocturnal feeding activity has been proposed to be a response to predation and competition with grazing fishes . Herbivorous fishes are abundant in New Caledonia [62, 63] and their importance as grazers is well recognized .
Comparisons between study sites and the effect of size
The main difference between the two study sites was the sampling temperatures measured during monitoring. This temperature was on average 22.5 ° C in New Caledonia and 27.3 °C in Vanuatu. It is well known that fundamental physiological functions of ectotherms are particularly influenced by temperature [65–67]. However, the pattern and intensity of the measured activity were comparable between the two sites despite this difference of 5 °C. The voluntary performance of free ranging topshells did not seem to be influenced by environmental temperature. Moreover, since in our study the variations in light and temperature are correlated at both sites, it is difficult to discern whether peaks of activity were a response either factors. Animals usually select temperature ranges that maximize their physiological performance e.g. through optimizing muscle function . In addition, during our study, the tagged topshells did not experience the extreme temperatures that can occur in their environment or within their geographical distribution. Indeed, the temperatures measured in Vanuatu are comparable to those found in New Caledonia during the warm season . Thus, in the present study, we were not able to measure the activity corresponding to the thermal performance curve of this species as reported by Gannon et al. .
During monitoring, two size classes were identified: small (Bd < 100 mm) and large topshells (Bd > 100 mm) showing comparable activity patterns. Large specimens had similar activity (duration, number of movement, acceleration) regardless of the study site and water temperature. In both sites, small topshells exhibited a higher activity with more intense movements than large ones. Moreover, the small topshells from Vanuatu have also depicted a higher activity than the small specimen from New Caledonia. These results were comparable to the measurements of respiration made by Lorrain et al.  on topshells from New Caledonia during the warm and cool seasons. Indeed, the large specimens had similar respiration rates during the night between the warm and cool seasons (9.9 vs 8.6 μmol.C.g−1). Small trochus had respiration rates higher than large specimens with a maximum during the warm season (17.6 vs 12.7 μmol.C.g−1). Previous studies have demonstrated that oxygen consumption correlates with temperature [40, 68, 69]. Body size would be one of the most important factors affecting metabolism. Indeed, the ratio between the gas exchange surface for respiration and the body volume decreases with growth. Thus, per gram of dry body weight, oxygen consumption is higher among younger, small individuals than in adults [70–72].
The activity observed for small topshells was characterized by longer and more intense movements. This activity could be associated with topshells moving longer distances during the night. During the present monitoring in Vanuatu, the location of each individual was identified in relation to 3 fixed poles (used as landmarks) every 90 min. Small topshells travelled an average distance of 26.3 ± 5.3 m against 11.5 ± 2.6 m for large specimens during 71 h of monitoring. Moreover, smaller specimens clearly migrated to the reef edge, while the four largest specimens remained in the tracking area (Dumas et al., in prep.). Byers  previously showed that for estuarine snails, although the amount of food was sufficient, smaller snails always dispersed at relatively higher rates than larger specimens. These intense movements may correspond to migration/dispersion from the intertidal reef flat to outer reef crests [28, 31–33]. These movements may also be associated with occasional trips related to the local microhabitat. T. niloticus can move quickly when small-scale biotic/abiotic factors, such as hydrodynamics, nature of the substrate, and food availability, do not suit them .
Strengths and limitations of the present study
The use of HOBO accelerometers yielded many advantages. They were easy to use, data were downloadable daily while specimens remained underwater, and the files were small and easy to handle. The monitoring period was only limited by the accelerometers’ battery life and the diver’s availability to visit the sites each day. However, this type of accelerometer also has limitations, particularly with regard to sampling frequency. The minimum programmable frequency of the device is 0.25 Hz which corresponds to one measurement every 4 s. In the present study, this frequency was high enough to describe activity patterns of topshells but this frequency range excludes motions with a duration less than 4 s and induces inaccuracies in the characterization of the movements. In the context of future bioenergetic studies dedicated to the study of the oxygen consumption versus activity, it would be preferable to increase the frequency of acquisition. In addition, this sampling time step was insufficient to estimate the distance travelled by the topshells during the monitoring period. Indeed, estimating speed and distance travelled from the acceleration data is theoretically possible , but doing so amplifies measurements errors producing unreliable predictions of future location . Finally, combining these accelerometers with a current sensor and video recordings allow us to further characterise of the types of topshell movements, including locomotion, feeding, escape, or defence against predators. In particular, calibrating movements according to body angles, pitch, and roll [11, 19] is useful in the classification of animal movement patterns , as any body posture will narrow the range of possible behaviours or be characteristic of one behavioural pattern for the study animal.
Combined with other instruments, accelerometers can provide a wide range of detailed information on the environmental context of animal behaviour and physiology that can exceed the descriptive abilities of the human observer, particularly during cryptic periods. The ability to identify locomotion has broad ecological applications. For instance, temporal patterns in locomotion can provide insights, complementary to direct observations and experimental studies, into changes in behavioural rhythms such as those that occur during the onset of migration [20, 39, 76, 77] or reproduction [36, 39] and in response to environmental change . Such information can be applied to specific conservation problems for T. niloticus. For example, at the level of individual topshells, monitoring the behaviour of captive-bred individuals after release, particularly individuals <60 mm [30, 78–80] may be useful. Monitoring may be scaled up to estimate area use at the population level through multiple device deployments, to assess behavioural responses to changes in the environment, including restocking  and establishing marine protected areas , and to assess the exploitation of this species.
This study was supported by IRD, INSU EC2CO PNEC, CYTRIX IBANOE, and EFITAV 2. AAR was supported by the “Laboratoire d’Excellence” LabexMER (ANR-10-LABX-19) and co-funded by a grant from the French government under the program “Investissements d’avenir”, and by a grant from the Regional council of Brittany (SAD programme). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank Erwan Amice and the crew of the N/O COriS for helping during cruises, and N. Daffont for extensive help with the fabrication of aluminium devices for accelerometer fixation on topshells.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Cooke SJ, Hinch SG, Wikelski M, Andrews RD, Kuchel LJ, Wolcott TG, et al. Biotelemetry - a mechanistic approach to ecology. Trends Ecol Evol. 2004;19:334–43.View ArticleGoogle Scholar
- Fryxell JM, Hazell M, Borger L, Dalziel BD, Haydon DT, Morales JM, et al. Multiple movement modes by large herbivores at multiple spatiotemporal scales. Proc Natl Acad Sci U S A. 2008;105:19114–9.View ArticleGoogle Scholar
- Jack KM, Lenz BB, Healan E, Rudman S, Schoof VAM, Fedigan L. The effect of observer presence on the behavior of Cebus capucinus in Costa Rica. Am J Primatol. 2008;70:490–4.View ArticleGoogle Scholar
- Schneirla TC. The relationship between observation and experimentation in the field study of behaviour. Annals NY Acad Sci. 1950;51:1022–44.View ArticleGoogle Scholar
- Wikelski M, Cooke SJ. Conservation physiology. Trends Ecol Evol. 2006;21:38–46.View ArticleGoogle Scholar
- Ellwood SA, Wilson RP, Addison AC. Technology in conservation: a boon but with small print. In: Macdonald D, Service K, editors. Key topics in conservation biology. Oxford: Blackwell Publishing; 2007. p. 105–19.Google Scholar
- Ropert-Coudert Y, Wilson RP. Trends and perspectives in animal-attached remote sensing. Front Ecol Environ. 2005;3:437–44.View ArticleGoogle Scholar
- Hart KM, Hyrenbach KD. Satellite telemetry of marine megavertebrates: the coming of age of an experimental science. Endangered Spec Res. 2009;10:9–20.View ArticleGoogle Scholar
- Kooyman GL. Genesis and evolution of bio-logging devices: 1963–2002. Memoirs Nat Inst Pol Res Special Issue. 2004;58:15–22.Google Scholar
- Payne N, Gillanders B, Seymour R, Webber D, Snelling E, Semmens J. Accelerometry estimates field metabolic rate in giant Australian cuttlefish Sepia apama during breeding. J Anim Ecol. 2011;80:422–30.View ArticleGoogle Scholar
- Robson AA, Chauvaud L, Wilson RP, Halsey LG. Small actions, big costs : the behavioural energetics of a commercially important invertebrate. J R Soc Interface. 2012:doi: 10.1098/rsif.2011.0713.
- Shepard ELC, Wilson RP, Quintana F, Laich AG, Liebsch N, Albareda DA, et al. Identification of animal movement patterns using tri-axial accelerometry. Endangered Spec Res. 2008:doi: 10.3354/esr00084.
- Tsuda Y, Kawabe R, Tanaka H, Mitsunaga Y, Hiraishi T, Yamamoto K, et al. Monitoring the spawning behaviour of chum salmon with an acceleration data logger. Ecol Freshwater Fish. 2006;15:264–74.View ArticleGoogle Scholar
- Wilson RP, Shepard ELC, Liebsch N. Prying into the intimate details of animal lives: use of a daily diary on animals. Endangered Spec Res. 2008;4:123–7.View ArticleGoogle Scholar
- Baras E, Togola B, Sicard B, Benech V. Behaviour of tigerfish Hydrocynus brevis in the River Niger, Mali, as revealed by simultaneous telemetry of activity and swimming depth. Hydrobiologia. 2002;483:103–10.View ArticleGoogle Scholar
- Gilly WF, Zeidberg LD, Booth JAT, Stewart JS, Marshall G, Abernathy K, et al. Locomotion and behaviour of Humboldt squid, Dosidicus gigas, in relation to natural hypoxia in the gulf of California, Mexico. J Experiment Biol. 2012;215:3175–90.View ArticleGoogle Scholar
- Whitney NM, Papastamatiou YP, Holland KN, Lowe CG. Use of an acceleration data logger to measure diel activity patterns in captive whitetip reef sharks, Triaenodon obseus. Aquat Living Resour. 2007;29:299–305.View ArticleGoogle Scholar
- Brown DD, Kays R, Wikelski M, Wilson R, Kimley AP. Observing the unwatchable through acceleration logging of animal behavior. Animal Biotelemetry. 2013;1:1–16.View ArticleGoogle Scholar
- Robson AA, Mansfield RP. Overinflated behavioural energetics: using dynamic body acceleration to accurately measure behaviour duration and estimate energy expenditure. Aquat Biol. 2014;21:121–6.View ArticleGoogle Scholar
- Heslinga GA. Growth and maturity of Trochus niloticus in the laboratory. Proc Fourth Int Coral Reef Symp. 1981;1:39–45.Google Scholar
- Heslinga GA, Hillmann A. Hatchery culture of the commercial top snail Trochus niloticus in Palau, Caroline islands. Aquaculture. 1981;22:3–43.View ArticleGoogle Scholar
- Long BG, Poiner IR, Harris ANM. Method of estimating the standing stock of Trochus niloticus incorporating Landsat satellite date, with application to the trochus resources of the Bourke Isles, Torres Strait, Australia. Mar Biol. 1993;115:587–93.View ArticleGoogle Scholar
- Wells SM. International trade in ornamental shells. IUCN Conservation Monitoring Center: Cambridge, U.K; 1981.Google Scholar
- Amos MJ. Management policy for the trochus fishery in the Pacific. In: Lee CL, Lynch PW, editors. Trochus: Status, Hatchery Practice and Nutrition; 6–7 June 1996; Northern Territory University. Canberra: ACIAR Proceedings; 1997. p. 164–9.Google Scholar
- Castell LL, Sweatman HPA. Predator–prey interactions among some intertidal gastropods on the Great Barrier Reef. J Zool. 1997;241:145–59.View ArticleGoogle Scholar
- Crowe TP, Amos MJ, Lee CL. the potential of reseeding with juveniles as a tool for the management of trochus fisheries. In: Lee CL, Lynch PW, editors. Trochus: Status, Hatchery Practice and Nutrition; Northern Territory University. Canberra: ACIAR Proceedings; 1997. p. 170–7.Google Scholar
- Heslinga GA, Orak O, Ngiramengior M. Coral Reef Sanctuaries for Trochus Shells. Mar Fish Rev. 1984;46:73–80.Google Scholar
- Nash WJ. Trochus. In: Nearshore Marine Resources of the South Pacific: Information for Fisheries Development and Management. 1993. p. 451–9.Google Scholar
- Pakoa K, Friedman K, Damlamian H. the status of trochus (Trochus niloticus) in Tongatapu Lagoon, Kingdom of Tonga. Secr Pac Community. 2010;15:3–15.Google Scholar
- Purcell SW, Cheng YW. Experimental restocking and seasonal visibility of a coral reef gastropod assessed by temporal modelling. Aquat Biol. 2010;9:227–38.View ArticleGoogle Scholar
- Bour W. The fishery resources of Pacific Island countries. Part 3 Trochus. In: FAO Fisheries Technical paper, vol. 272. 1990. p. 3.Google Scholar
- Castell LL. Population studies of juvenile Trochus niloticus on a reef flat on the north-eastern Queensland coast, Australia. Mar Freshw Res. 1997;48:211–7.View ArticleGoogle Scholar
- Smith BD. Growth rate, distribution and abundance of the introduced topshell Trochus niloticus Linnaeus on Guam, Mariana Islands. Bull Mar Sci. 1987;41:466–74.Google Scholar
- McGowan JA. the Trochus fishery of the Trust Territory of the Pacific Islands. In: Report to the Hight Commissioner. Saipan: U.S. Trust Territory of the Pacifi Islands; 1958. p. 46.Google Scholar
- Dumas P, Jimenez H, Peignon C, Wantiez L, Adjeroud M. Small-scale habitat structure modulates the effects of no-take marine reserves for coral reef macroinvertebrates. PLoS One. 2013;8, e58998.View ArticleGoogle Scholar
- Bour W. Biologie, ecologie, exploitation et gestion rationnelle des trocas (Trocus niloticus L.) de Nouvelle Calédonie. Université des sciences et techniques du Languedoc; 1989.Google Scholar
- Villanueva RD, Baria MVB, dela Cruz DW. Effects of grazing by herbivorious gastropod (Trochus niloticus) on the survivorship of cultured coral spat. Zool Stud. 2013;52:1–7.View ArticleGoogle Scholar
- Bour W, Gohin F, Bouchet P. Croissance et mortalité naturelle des trocas (Trochus niloticus L.) de Nouvelle Calédonie (Mollusca, Gastropoda). Haliotis. 1982;12:71–90.Google Scholar
- Nash WJ. Aspects of the biology of trochus niloticus and its fishery in the Great Barrier Reef region. Northern Fisheries Research Centre: Cairns, Queensland, Australia; 1985.Google Scholar
- Lorrain A, Clavier J, Thébault J, Tremblay-Boyer L, Houlbrèque F, Amice E, et al. Variability in diel and seasonal in situ metabolism of the tropical gastropod Tectus niloticus. Aquat Biol. 2015;23:167–82.View ArticleGoogle Scholar
- Shepard ELC, Wilson RP, Halsey LG, Quintana F, Laich AG, Gleiss AC, et al. Derivation of body motion via appropriate smoothing of acceleration data. Aquat Biol. 2008;4:235–41.View ArticleGoogle Scholar
- Gleiss AC, Wilson RP, Shepard ELC. Making overall dynamic body acceleration work: on th theory of acceleration as a proxy for energy expenditure. Methods Ecol Evol. 2011;2:23–33.View ArticleGoogle Scholar
- Wilson RP, White CR, Quintana F, Halsey LG, Liebsch N, Martin GR, et al. Moving towards acceleration for estimates of activity-specific metabolic rate in free-living animals: the case of the cormorant. J Anim Ecol. 2006;75:1081–90.View ArticleGoogle Scholar
- Qasem L, Cardew A, Wilson A, Griffiths I, Halsey LG, Shepard EL, et al. Tri-axial dynamic acceleration as a proxy for animal energy expenditure; should we be summing values or calculating the vector? PLoS One. 2012;7:e31187.View ArticleGoogle Scholar
- Halsey LG, Shepard ELC, Wilson RP. Assessing the development and application of the accelerometry technique for estimating energy expenditure. Comp Biochem Phys A. 2011;158:305–14.View ArticleGoogle Scholar
- Ruff T. The Lomb-Scargle periodogram in biological rhythm research: analysis of incomplete and unequally-spaced time-series. Biol Rhythm Res. 1999;30:178–201.View ArticleGoogle Scholar
- Van Dongen HPA, Olofsen E, Van Hartevelt JH, Kruyt EW. A procedure of multiple period searching in unequally spaced time-series with the Lomb-Scargle method. Biol Rhythm Res. 1999;30:149–77.View ArticleGoogle Scholar
- Gannon R, Taylor MD, Suthers IM, Gray CA, van der Meulen DE, Smith JA, et al. Thermal limitation of performance and biogeography in a free-ranging ectotherm: insights from accelerometry. J Exp Biol. 2014;217:3033–7.View ArticleGoogle Scholar
- Evans J, Borg JA, Schembri PJ. Distribution, habitat preferences and behaviour of the critically endangered Maltese top-shell Gibbula nivosa (Gastropoda: Trochidae). Mar Biol. 2011;158:603–11.View ArticleGoogle Scholar
- Yamaguchi M. A synopsis of the biology of green snail (Turbo marmoratus). In: Workshop on Trochus resource assessmen, management and develpment, vol. 13. Noumea, New Caledonia: South Pacific Commission; 1997. p. 127–33.Google Scholar
- Klumpp DW, Pulfrish A. Trophic significance of herbivorous macroinvertebrates on the central Great Barrier Reef. Coral Reefs. 1989;8:135–44.View ArticleGoogle Scholar
- Tahil AS, Juinio-Menez MA. Natural diet, feeding periodicity and functional response to food density of the abalone, Haliotis asinia L., (Gastropoda). Aquac Res. 1999;30:95–107.View ArticleGoogle Scholar
- Torréton J-P, Rochelle-Newall E, Pringault O, Jacquet S, Faure V, Briand E. Variability of primary and bacterial production in a coral reef lagoon (New Caledonia). Mar Pollut Bull. 2010;61:335–48.View ArticleGoogle Scholar
- Little C. Factors governing patterns of foraging activity in littoral marine herbivorous molluscs. J Mollus Stud. 1989;55:273–84.View ArticleGoogle Scholar
- Clavier J, Boucher G, Garrigue C. Benthic respiratory and photosynthetic quotients in a tropical lagoon. Comptes rendus de l’Académie des Sciences-Series III- Sciences de la Vie. 1994;317:937–42.Google Scholar
- Clavier J, Garrigue C, Boucher G, Bonnet S, Di Matteio A, Hamel P, et al. Flux d’oxygène et de sels nutritifs à l’interface eau-sédiment dans le lagon sud-ouest de Nouvelle-Calédonie: enrichissements en ammonium et action d’un inhibiteur de la photosynthèse. Méthode et recueil des données. In: Rapport scientifique et technique, Sciences de la Mer, Biologie Marine, vol. 61. Nouméa: ORSTOM; 1991. p. 1–56.Google Scholar
- Rougerie F. Le lagon sud-ouest de Nouvelle Calédonie: spécificité hydrologique, dynamique et productivité. PhD thesis. ORSTOM; 1986.Google Scholar
- Carefoot TH. Energy transformation by sea hares (aplysia) in areas of coral rubble. Proc 5th Int Coral Reef Symp. 1985;4:9–16.Google Scholar
- Frank PW. Growth rates and longevity of some gastropod mollusks on the coral reef at Heron Island. Oceologia. 1969;2:232–50.View ArticleGoogle Scholar
- Sammarco PW, Tirendi F, Nott A. Direct determination of organic carbon in modern reef sediments and calcareous organisms after dissolution of carbonate. Mar Geol. 1986;70:321–9.View ArticleGoogle Scholar
- Cloudsley-Thompson JL. Rhythmic activity in animal Physiology and Behavior. New York: Academic; 1961.Google Scholar
- Carassou L, Léopold M, Guillemot N, Wantiez L, Kulbicki M. Does herbivorous fish protection really improve coral reef resilience? A case study from New Caledonia (South Pacific). PLoS One. 2013;8, e60564.View ArticleGoogle Scholar
- Letourneur Y, Kulbicki M, Labrosse P. Spatial structure of commercial reef fish communities along a terrestrial runoff gradient in the northern lagoon of New Caledonia. Environ Biol Fish. 1998;51:141–59.View ArticleGoogle Scholar
- Steneck RS. Herbivory on coral reefs: a synthesis. In: Choat JH, Barnes D, Borowitzka M, Coll JC, Davies PJ, Flood P, Hatcher BG, Hopley D, Hutchings PA, Kinsey D, et al., editors. Proc 6th International Coral Reef Symposium; Townsville, Australia. 1988. p. 37–49.Google Scholar
- Huey RB, Kingsolver JG. Evolution of thermal sensitivity of ectotherm performance. Trends Ecol Evol. 1989;4:131–5.View ArticleGoogle Scholar
- Deutsch CA, Tewksbury JJ, Huey RB, Sheldon KS, Ghalambor CK, Haak DC, et al. Impacts of climate warming on terrestrial ectotherms across latitude. Proc Natl Acad Sci U S A. 2008;105:6668–72.View ArticleGoogle Scholar
- Kingsolver JG. The well-temperatured biologist. Am Nat. 2009;174:755–68.View ArticleGoogle Scholar
- Halsey LG, Matthews PGD, Rezende EL, Chauvaud L, Robson AA. The intercations between temperature and activity levels in driving metabolism rate: theory, with empirical validation from contrasting ectotherms. Oecologia. 2015, In press.Google Scholar
- Yi S, Lee CL. Effects of temperature and salinity on the oxygen consumption and survival of hatchery-reared juvenile topshell Trochus niloticus (Mollusca: Gastropoda). In: Lee CL, Lynch PW, editors. Trochus: Status, Hatchery Practice and Nutrition. Canberra, Australia: Australian Centre for International Agricultural Research; 1997. p. 69–75.Google Scholar
- Brown JH, Allen AP, Gillouly JF. The metabolic theory of ecology and the role of body size in marine and freshwater ecosystems. In: Hildrew AG, Raffaelli DG, Edmonds-Brown R, editors. Body size: the structure and function of aquatic ecosystems. New York: Cambridge University Press; 2007. p. 1–15.View ArticleGoogle Scholar
- Mardsen ID, Shumway SE, Padilla DK. Does size matter? The effects of body size and declining oxygen tension on oxygen uptake in gastropods. J Mar Biol Assoc UK. 2012;92:1603–17.View ArticleGoogle Scholar
- Peters RH. The ecologycal implications of body size. New York: Cambridge University Press; 1983.View ArticleGoogle Scholar
- Byers JE. Effects of body size and resource availability on dispersal in a native and a non-native estuarine snail. J Exp Mar Biol Ecol. 2000;248:133–50.View ArticleGoogle Scholar
- Yoda K, Naito Y, Sato K, Takahashi A, Nishikawa J, Ropert-Coudert Y, et al. A new technique for monitoring the behaviour of free-ranging Adelie penguins. J Experiment Biol. 2001;204:685–90.Google Scholar
- Springer B. Das problem der bestimmung von Bewegungsaktivitaeten bei warmbluetigen Tieren. University of Kiel; 1992.Google Scholar
- Bolger DT, Newmark WD, Morrison TA, Doak DF. The need for integrative approaches to understand and conserve migratory ungulates. Ecol Lett. 2008;11:63–77.Google Scholar
- Tanaka H, Takagi Y, Naito Y. Swimming speeds and buoyancy compensation of migration adult chum salmon Oncorhynchus keta revealed by speed/depth/acceleration data logger. J Experiment Biol. 2001;204:3895–904.Google Scholar
- Clarke PJ, Komatsu T, Bell JD, Lasi F, Oengpepa CP, Leqata J. Combined culture of Trochus niloticus and giant clams (Tridacnidae): benefits for restocking and farming. Aquaculture. 2003;215:123–44.View ArticleGoogle Scholar
- Crowe TP, Lee CL, McGuinness KA, Amos MJ, Dangeugun J, Dwiono SAP, et al. Experimental evaluation of the use of hatchery-reared juveniles to enhance stocks of the topshells Trochus niloticus in Australia, Indonesia and Vanuatu. Aquaculture. 2002;206:175–97.View ArticleGoogle Scholar
- Sutherland WJ. The importance of behavioural studies in conservation biology. Anim Behav. 1998;56:801–9.View ArticleGoogle Scholar
- Caro T. Behavior and conservation: a bridge too far? Trends Ecol Evol. 2007;22:394–400.View ArticleGoogle Scholar