A novel approach to quantifying the spatiotemporal behavior of instrumented grey seals used to sample the environment

Movement Ecology

W Don Bowen¹  Sara J Iverson⁴  Damian C Lidgard⁴  Ian D Jonsen³  Joanna E Mills Flemming²  Laurie L Baker⁴ 

[1] Population Ecology Division, Bedford Institute of Oceanography, Department of Fisheries and Oceans, Dartmouth B2Y 4A2, Canada;Department of Mathematics and Statistics, Dalhousie University, Halifax B3H 4R2, Canada;Department of Biological Sciences, Macquarie University, North Ryde, Sydney NSW 2109, Australia;Department of Biology, Dalhousie University, Halifax B3H 4R2, Canada

关键词: Ocean tracking network;    Ships of opportunity;    Marine acoustics;    Bioprobe;    Animal movement;   

Others  :  1221414
DOI  :  10.1186/s40462-015-0047-4

 received in 2014-11-24, accepted in 2015-05-11,  发布年份 2015

【 摘 要 】

Background

Paired with satellite location telemetry, animal-borne instruments can collect spatiotemporal data describing the animal’s movement and environment at a scale relevant to its behavior.

Ecologists have developed methods for identifying the area(s) used by an animal (e.g., home range) and those used most intensely (utilization distribution) based on location data. However, few have extended these models beyond their traditional roles as descriptive 2D summaries of point data. Here we demonstrate how the home range method, T-LoCoH, can be expanded to quantify collective sampling coverage by multiple instrumented animals using grey seals (Halichoerus grypus) equipped with GPS tags and acoustic transceivers on the Scotian Shelf (Atlantic Canada) as a case study. At the individual level, we illustrate how time and space-use metrics quantifying individual sampling coverage may be used to determine the rate of acoustic transmissions received.

Results

Grey seals collectively sampled an area of 11,308 km²and intensely sampled an area of 31 km²from June-December. The largest area sampled was in July (2094.56 km² ) and the smallest area sampled occurred in August (1259.80 km² ), with changes in sampling coverage observed through time.

Conclusions

T-LoCoH provides an effective means to quantify changes in collective sampling effort by multiple instrumented animals and to compare these changes across time. We also illustrate how time and space-use metrics of individual instrumented seal movement calculated using T-LoCoH can be used to account for differences in the amount of time a bioprobe (biological sampling platform) spends in an area.

【 授权许可】

   
2015 Baker et al.; licensee BioMed Central.

【 图 表 】

Fig. 1.

Fig. 2.

Fig. 3.

Fig. 4.

Fig. 5.

【 参考文献 】

• [1]Hooker SK, Boyd IL. Salinity sensors on seals: use of marine predators to carry CTD data loggers. Deep Sea Research Part I: Oceanographic Research Papers. 2003; 50(7):927-939.
• [2]Biuw M, Boehme L, Guinet C, Hindell M, Costa D, Charrassin J-B et al.. Variations in behavior and condition of a Southern Ocean top predator in relation to in situ oceanographic conditions. Proc Nat Acad Sci. 2007; 104(34):13705-13710.
• [3]Wilson SG, Block BA. Habitat use in Atlantic bluefin tuna Thunnus thynnus inferred from diving behavior. Endangered Species Res. 2009; 10:355-367.
• [4]Lidgard DC, Bowen WD, Jonsen ID, Iverson SJ. Animal-borne acoustic transceivers reveal patterns of at-sea associations in an upper-trophic level predator. PLoS ONE. 2012; 7(11):48962.
• [5]Austin D, Bowen WD, McMillan JI, Iverson SJ. Linking movement, diving, and habitat to foraging success in a large marine predator. Ecology. 2006; 87(12):3095-3108.
• [6]Padman L, Costa DP, Bolmer ST, Goebel ME, Huckstadt LA, Jenkins A, et al. Seals map bathymetry of the Antarctic continental shelf. Geophysical Res Lett. 2010; 37(L21601).
• [7]Kie JG, Matthiopoulos J, Fieberg J, Powell RA, Cagnacci F, Mitchell MS et al.. The home-range concept: are traditional estimators still relevant with modern telemetry technology? Philos Trans R Soc B Biol Sci. 2010; 365(1550):2221-2231.
• [8]Getz WM, Wilmers CC. A local nearest-neighbor convex-hull construction of home ranges and utilization distributions. Ecography. 2004; 27(4):489-505.
• [9]Getz WM, Fortmann-Roe S, Cross PC, Lyons AJ, Ryan SJ, Wilmers CC. LoCoH: nonparameteric kernel methods for constructing home ranges and utilization distributions. PLoS ONE. 2007; 2(2):207.
• [10]Lyons AJ, Turner WC, Getz WM. Home range plus: A space-time characterization of movement over real landscapes. Mov Ecol. 2013; 1(1):1-14. BioMed Central Full Text
• [11]Lidgard DC, Bowen WD, Jonsen ID, Iverson SJ. Predator-borne acoustic transceivers and gps tracking reveal spatiotemporal patterns of encounters with acoustically tagged fish in the open ocean. Mar Ecol Prog Ser. 2014; 501:157-168.
• [12]Beck CA, Bowen WD, Iverson SJ. Sex differences in the seasonal patterns of energy storage and expenditure in a phocid seal. J Anim Ecol. 2003; 72(2):280-291.
• [13]Beck CA, Iverson SJ, Bowen WD, Blanchard W. Sex differences in grey seal diet reflect seasonal variation in foraging behaviour and reproductive expenditure: evidence from quantitative fatty acid signature analysis. J Anim Ecol. 2007; 76(3):490-502.
• [14]Austin D, Bowen WD, McMillan JI. Intraspecific variation in movement patterns: modeling individual behaviour in a large marine predator. Oikos. 2004; 105(1):15-30.
• [15]Breed GA, Bowen WD, McMillan JI, Leonard ML. Sexual segregation of seasonal foraging habitats in a non-migratory marine mammal. Proc R Soc B Biol Sci. 2006; 273(1599):2319-2326.
• [16]Breed GA, Jonsen ID, Myers RA, Bowen WD, Leonard ML. Sex-specific, seasonal foraging tactics of adult grey seals (Halichoerus grypus) revealed by state-space analysis. Ecology. 2009; 90(11):3209-3221.
• [17]Breed GA, Bowen WD, Leonard ML. Behavioral signature of intraspecific competition and density dependence in colony-breeding marine predators. Ecol Evol. 2013; 3(11):3838-3854.
• [18]Aarts G, MacKenzie M, McConnell B, Fedak M, Matthiopoulos J. Estimating space-use and habitat preference from wildlife telemetry data. Ecography. 2008; 31(1):140-160.
• [19]Wakefield ED, Phillips RA, Trathan PN, Arata J, Gales R, Huin N et al.. Habitat preference, accessibility, and competition limit the global distribution of breeding black-browed albatrosses. Ecol Monogr. 2011; 81(1):141-167.
• [20]Manly B, McDonald L, Thomas D, McDonald T, Erickson W. Resource selection by animals: statistical analysis and design for field studies. Nordrecht, The Netherlands: Kluwer; 2002.
• [21]Breed GA, Bowen WD, Leonard ML. Development of foraging strategies with age in a long-lived marine predator. Mar Ecol Prog Ser. 2011; 431:267-279.
• [22]How JR, de Lestang S. Acoustic tracking: issues affecting design, analysis and interpretation of data from movement studies. Mar Freshwater Res. 2012; 63(4):312-324.
• [23]Gjelland K, Hedger R. Environmental influence on transmitter detection probability in biotelemetry: Developing a general model of acoustic transmission. Methods Ecol Evol. 2013; 3(7):665-674.
• [24]Finstad B, Økland F, Thorstad EB, Bjørn PA, McKinley RS. Migration of hatchery-reared Atlantic salmon and wild anadromous brown trout post-smolts in a Norwegian fjord system. J Fish Biol. 2005; 66(1):86-96.
• [25]Singh L, Downey NJ, Roberts MJ, Webber DM, Smale MJ, Van den Berg MA et al.. Design and calibration of an acoustic telemetry system subject to upwelling events. African J Mar Sci. 2009; 31(1):355-364.
• [26]Heupel MR, Semmens JM, Hobday AJ. Automated acoustic tracking of aquatic animals: scales, design and deployment of listening station arrays. Mar Freshwater Res. 2006; 57:1-13.
• [27]Kuperman WA, Lynch JF. Shallow-water acoustics. Physics Today. 2004; 57(10):55-61.
• [28]Fedak M.. The impact of animal platforms on polar ocean observation. Deep Sea Research Part II: Topical Studies in Oceanography. 2013; 88:7-13.
• [29]Roquet F, Wunsch C, Forget G, Heimbach P, Guinet C, Reverdin G et al.. Estimates of the Southern Ocean general circulation improved by animal-borne instruments. Geophysical Res Lett. 2013; 40(23):6176-6180.
• [30]Iverson SJ, Bowen WD, Boness DJ, Oftedal OT. The effect of maternal size and milk energy output on pup growth in grey seals (Halichoerus grypus). Physiol Zool. 1993; 66:61-88.
• [31]Holland KN, Meyer CG, Dagorn LC. Inter-animal telemetry: results from first deployment of acoustic ‘business card’ tags. Endangered Species Res. 2009; 10:287-293.
• [32]Baker LL, Jonsen ID, Flemming JEM, Lidgard DC, Bowen WD, Iverson SJ et al.. Probability of detecting marine predator-prey and species interactions using novel hybrid acoustic transmitter-receiver tags. PLoS ONE. 2014; 9(6):98117.
• [33]Stansbury AL, Götz T, Deecke VB, Janik VM. Grey seals use anthropogenic signals from acoustic tags to locate fish: evidence from a simulated foraging task. Proc R Soc B Biol Sci. 2015; 282(1798):20141595.
• [34]Borchers DL, Buckland ST, Goedhart PW, Clarke ED, Hedley SL. Horvitz-thompson estimators for double-platform line transect surveys. Biometrics. 1998; 12:21-37.
• [35]Guidelines for the treatment of animals in behavioural research and teaching. Animal Behaviour. 2006; 71(1):245-253.
• [36]Bowen WD, McMillan J, Mohn R. Sustained exponential population growth of grey seals at Sable Island, Nova Scotia. ICES J Mar Sci Journal du Conseil. 2003; 60(6):1265-1274.
• [37]Bowen WD, Beck CA, Iverson SJ, Austin D, McMillan JI. Linking predator foraging behaviour and diet with variability in continental shelf ecosystems: Grey seals of eastern Canada. Conserv Biol Series-Cambridge-. 2006; 12:63.
• [38]Baker LL, Flemming JEM, Jonsen ID, Lidgard DC, Iverson SJ, Bowen WD. Data from: A novel approach to quantifying the spatiotemporal behavior of instrumented grey seals used to sample the environment. Movebank Data Repository. 2015. doi:10.5441/001/1.910p0c20.
• [39]Halfyard EA, Gibson AJF, Stokesbury MJ, Ruzzante DE, Whoriskey FG, Zech JM. Correlates of estuarine survival of atlantic salmon postsmolts from the Southern Upland, Nova Scotia, Canada. Can J Fisheries Aquat Sci. 2013; 70(3):452-460.
• [40]Bryant E. 2D location accuracy statistics for Fastloc ®;cores running firmware versions 2.2 & 2.3. Wildtrack Telemetry Systems Ltd. 2007.
• [41]Hazel J. Evaluation of fast-acquisition GPS in stationary tests and fine-scale tracking of green turtles. J Exp Mar Biol Ecol. 2009; 374(1):58-68.
• [42]69 kHz Sea Water Range Calculator. http://vemco.com/range-calculator. Accessed: 2012-06-04.
• [43]Lyons A, Getz W. R Development Core Team: T-LoCoH: Time Local Convex Hull Homerange and Time Use Analysis. 2014. R package version 1.16.
• [44]Lyons A. T-LoCoH for R: Tutorial and Users Guide. 2013. http://tlocoh. r-forge.r-project.org webcite
• [45]ArcGIS Desktop: Release 10. Environmental Systems Research Institute, Redlands, CA; 2011.