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Concepts: Estimating Abundance of Prey Species Using Line Transect Sampling

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Methods For Monitoring Tiger And Prey Populations

Abstract

The principal prey of tigers are typically large, diurnal ungulates and can be visually detected and counted by observers while walking, riding domesticated elephants, or in very open habitats from aircraft, moving along a straight line.

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References

  • Alldredge MW, Simons TR, Pollock KH (2007a) An experimental evaluation of distance measurement error in avian point count surveys. J Wildl Manag 71:2759–2766

    Article  Google Scholar 

  • Alldredge MW, Pollock KH, Simons TR (2007b) Multiple species analysis of point count data: a more parsimonious modeling framework. J Appl Ecol 44:281–290

    Article  Google Scholar 

  • Borchers DL, Langrock R (2015) Double-observer line transect surveys with Markov-modulated Poisson process models for animal availability. Biometrics 71:1060–1069

    Article  CAS  PubMed  Google Scholar 

  • Borchers DL, Buckland ST, Zucchini W (2002) Estimating animal abundance: closed populations. Springer, London

    Book  Google Scholar 

  • Borchers DL, Laake JL, Southwell C, Paxton CGM (2006) Accommodating unmodeled heterogeneity in double-observer distance sampling surveys. Biometrics 62:372–378

    Article  CAS  PubMed  Google Scholar 

  • Borchers DL, Marques TA, Gunnlaugsson T, Jupp P (2010) Estimating distance sampling detection functions when distances are measured with errors. JABES 15:346–361

    Article  Google Scholar 

  • Borchers DL, Zucchini W, Heide-Jorgensen MP, Canadas A, Langrock R (2013) Using hidden markov models to deal with availability bias on line transect surveys. Biometrics 69:703–713

    Article  CAS  PubMed  Google Scholar 

  • Buckland ST, Anderson DR, Burnham KP, Laake JL (1993) Distance sampling: estimating abundance of biological populations. Chapman and Hall, London

    Book  Google Scholar 

  • Buckland ST, Burnham KP, Augustin NH (1997) Model selection: an integral part of inference. Biometrics 53:603–618

    Article  Google Scholar 

  • Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (2001) Introduction to distance sampling. Oxford University Press, London

    Google Scholar 

  • Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (eds) (2004) Advanced distance sampling. Oxford University Press, Oxford

    Google Scholar 

  • Buckland ST, Russell RE, Dickson BG, Saab VA, Gorman DG, Block WM (2009) Analysing designed experiments in distance sampling. JABES 14:432–442

    Article  Google Scholar 

  • Buckland ST, Rexstad EA, Marques TA, Oedekoven CS (2015) Distance sampling: methods and applications. Methods in statistical ecology. Springer, Cham

    Book  Google Scholar 

  • Buckland ST, Oedekoven CS, Borchers DL (2016) Model-based distance sampling. JABES 21:58–75

    Article  Google Scholar 

  • Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach, 2nd edn. Springer, New York

    Google Scholar 

  • Burnham KP, Anderson DR, Laake JL (1980) Estimation of density from line transect sampling of biological populations. Wildl Monogr 72:1–202

    Google Scholar 

  • Burnham, KP, Anderson, DR, White, GC, Brownie, C, Pollock, KH (1987) Design and analysis methods for fish survival experiments based on release-recapture. American Fisheries Society, USA

    Google Scholar 

  • Burt M, Borchers D, Jenkins K, Marques T (2015) Using mark-recapture distance sampling methods on line transect surveys. Methods Ecol Evol 5:1180–1191

    Article  Google Scholar 

  • Cochran WG (1977) Sampling techniques, 3rd edn. Wiley, Singapore

    Google Scholar 

  • Durant SM, Craft ME, Hilborn R, Bashir S, Hando J, Thomas L (2011) Long-term trends in carnivore abundance using distance sampling in Serengeti National Park, Tanzania. J Appl Ecol 48:1490–1500

    Article  Google Scholar 

  • Fewster RM, Pople AR (2008) A comparison of mark–recapture distance-sampling methods applied to aerial surveys of eastern grey kangaroos. Wildl Res 35:320–330

    Article  Google Scholar 

  • Fewster RM, Buckland ST, Burnham KP, Borchers DL, Jupp PE, Laake JL, Thomas L (2009) Estimating the encounter rate variance in distance sampling. Biometrics 65:225–236

    Article  PubMed  Google Scholar 

  • Fiske IJ, Chandler RB (2011) unmarked: an R package for fitting hierarchical models of wildlife occurrence and abundance. J Stat Softw 43:1–23

    Article  Google Scholar 

  • Gerodette T, Forcada J (2005) Non-recovery of two spotted and spinner dolphin populations in the eastern tropical Pacific Ocean. Mar Ecol Prog Ser 291:1–21

    Article  Google Scholar 

  • Hedley SL, Buckland ST (2004) Spatial models for line transect sampling. JABES 9:181–199

    Article  Google Scholar 

  • Hedley SL, Buckland ST, Borchers DL (2004) Spatial distance sampling models. In: Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (eds) Advanced distance sampling. Oxford University Press, Oxford, pp 48–70

    Google Scholar 

  • Johnson D, Laake JL, VerHoef J (2010) A model-based approach for making ecological inference from distance sampling data. Biometrics 66:310–318

    Article  PubMed  Google Scholar 

  • Karanth KU (1988) Population structure, density and biomass of large herbivores in south Indian tropical forest. MS thesis, University of Florida

    Google Scholar 

  • Kéry M, Royle J (2015) Applied hierarchical modeling in ecology: analysis of distribution, abundance and species richness in R and BUGS. Volume 1: Prelude and static models, 1st edn. Academic Press, Amsterdam

    Google Scholar 

  • Laake JL, Borchers DL (2004) Methods for incomplete detection at distance zero. In: Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (eds) Advanced distance sampling. Oxford University Press, Oxford, pp 108–189

    Google Scholar 

  • Laake JL, Buckland ST, Anderson DR, Burnham KP (1993) DISTANCE User’s Guide V2.0. Colorado Cooperative Fish and Wildlife Unit, Colorado State University, Fort Collins

    Google Scholar 

  • Marques FFC, Buckland ST (2004a) Incorporating covariates into standard line transect analysis. Biometrics 59:924–935

    Article  Google Scholar 

  • Marques FFC, Buckland ST (2004b) Covariate models for the detection function. In: Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (eds) Advanced distance sampling. Oxford University Press, Oxford, pp 31–47

    Google Scholar 

  • Marques TA, Thomas L, Fancy SG, Buckland ST (2007) Improving estimates of bird density using multiple covariate distance sampling. Auk 127:1229–1243

    Article  Google Scholar 

  • Marshall L (2016) DSsim: distance sampling simulations. R package version 1.0.8

    Google Scholar 

  • McCullagh P, Nelder JA (1989) Generalized linear models. Chapman & Hall/CRC, Boca Raton

    Book  Google Scholar 

  • Miller DL (2013) Distance: a simple way to fit detection functions to distance sampling data and calculate abundance/density for biological populations. R package version 0.7.3

    Google Scholar 

  • Miller DL, Burt ML, Rexstad EA, Thomas L (2013) Spatial models for distance sampling data: recent developments and future directions. Methods Ecol Evol 4:1001–1010

    Article  Google Scholar 

  • Oedekoven CS, Buckland ST, Mackenzie ML, Evans KO, Burger LW (2013) Improving distance sampling: accounting for covariates and non-independency between sampled sites. J Appl Ecol 50:786–793

    Article  Google Scholar 

  • Oedekoven CS, Buckland ST, Mackenzie ML, King R, Evans KO, Burger LW (2014) Bayesian methods for hierarchical distance sampling models. JABES 19:219–239

    Article  Google Scholar 

  • Oedekoven CS, Laake JL, Skaug HL (2015) Distance sampling with a random scale detection function. Environ Ecol Stat 22:725–737

    Article  CAS  Google Scholar 

  • Oehlert GW (1992) A note on the delta method. Am Stat 46:27–29

    Google Scholar 

  • Pollard JH, Buckland ST (2004) Adaptive distance sampling surveys. In: Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (eds) Advanced distance sampling. Oxford University Press, Oxford, pp 229–259

    Google Scholar 

  • Pollard JH, Palka D, Buckland ST (2002) Adaptive line transect sampling. Biometrics 58:862–870

    Article  CAS  PubMed  Google Scholar 

  • Powell LA (2007) Approximating variance of demographic parameters using the delta method: a reference for avian biologists. Condor 109:949–954

    Article  Google Scholar 

  • Royle JA, Dorazio RM (2008) Hierarchical modeling and inference in ecology. Academic Press, London

    Google Scholar 

  • Royle JA, Dawson DK, Bates S (2004) Modeling abundance effects in distance sampling. Ecology 85:1591–1597

    Article  Google Scholar 

  • Strindberg S (2001) Optimized automated survey design in wildlife population assessment. Dissertation, University of St Andrews

    Google Scholar 

  • Strindberg S, Buckland ST (2004) Zigzag survey designs in line transect sampling. JABES 9:443–461

    Article  Google Scholar 

  • Strindberg S, Buckland ST, Thomas L (2004) Design of distance sampling surveys and Geographic Information Systems. In: Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (eds) Advanced distance sampling. Oxford University Press, Oxford, pp 190–228

    Google Scholar 

  • Sturtz S, Ligges U, Gelman A (2005) R2WinBUGS: a package for running WinBUGS from R. J Stat Softw 12:1–16

    Article  Google Scholar 

  • Thomas L, Buckland ST, Rexstad EA, Laake JL, Strindberg S, Hedley SL, Bishop JRB, Marques TA, Burnham KP (2010) Distance software: design and analysis of distance sampling surveys for estimating population size. J Appl Ecol 47:5–14

    Article  PubMed  PubMed Central  Google Scholar 

  • Thomas L, Karanth KU (2002) Statistical concepts: estimating absolute densities of prey species using line transect sampling. In: Karanth KU, Nichols JD (eds) Monitoring tigers and their prey: a manual for researchers, managers, and conservationists in tropical Asia. Centre for Wildlife Studies, Bangalore, pp 87–110

    Google Scholar 

  • Thompson SK (1992) Sampling. Wiley, New York

    Google Scholar 

  • Thompson SK, Seber GAF (1996) Adaptive sampling. Wiley, New York

    Google Scholar 

  • Wegge P, Storaas T (2009) Sampling tiger ungulate prey by the distance method: lessons learned in Bardia National Park, Nepal. Anim Conserv 12:78–84

    Article  Google Scholar 

  • Williams R, Thomas L (2007) Distribution and abundance of marine mammals in the coastal waters of British Columbia, Canada. J Cetacean Res Manag 9:15–28

    Google Scholar 

  • Wood SN (2006) Generalized additive models: an introduction with R. Chapman & Hall/CRC Press, Boca Raton

    Google Scholar 

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Author information

Authors and Affiliations

  1. Wildlife Conservation Society (WCS), New York, NY, USA

    Samantha Strindberg

  2. Wildlife Conservation Society, India Program, Bengaluru, India

    N. Samba Kumar & Varun R. Goswami

  3. Centre for Research into Ecological and Environmental Modelling, University of St Andrews, Fife, UK

    Len Thomas

  4. Centre for Wildlife Studies, Bengaluru, India

    Varun R. Goswami

Authors
  1. Samantha Strindberg
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  2. N. Samba Kumar
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  3. Len Thomas
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  4. Varun R. Goswami
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Corresponding author

Correspondence to Samantha Strindberg .

Editor information

Editors and Affiliations

  1. Wildlife Conservation Society (WCS), New York, New York, USA

    K. Ullas Karanth

  2. Crofton, Maryland, USA

    James D. Nichols

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Strindberg, S., Kumar, N.S., Thomas, L., Goswami, V.R. (2017). Concepts: Estimating Abundance of Prey Species Using Line Transect Sampling. In: Karanth, K., Nichols, J. (eds) Methods For Monitoring Tiger And Prey Populations. Springer, Singapore. https://doi.org/10.1007/978-981-10-5436-5_6

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