Skip to main content
Log in

Jointly estimating survival and mortality: integrating recapture and recovery data from complex multiple predator systems

  • Published:
Environmental and Ecological Statistics Aims and scope Submit manuscript

Abstract

Identifying where, when, and how many animals live and die over time is principal to understanding factors that influence population dynamics. Capture–recapture–recovery (CRR) models are widely used to estimate animal survival and, in many cases, quantify specific causes of mortality (e.g., harvest, predation, starvation). However, the restrictive CRR framework can inhibit the consideration and inclusion of some types of recovery data. We developed an extension to the CRR framework to allow for the incorporation of recoveries from indeterminate temporal or spatial origin. This model jointly estimates cause-specific mortality and survival probabilities across multiple spatial and temporal scales, while accounting for differences in mortality-specific reporting and recovery rates. We fitted the model to data on a group of juvenile steelhead trout (Oncorhynchus mykiss) marked with passive integrated transponder tags in the Columbia River basin, USA. Following tagging and release, fish were detected alive at up to six downstream locations and/or recovered dead on one of nine bird colonies during seaward migration. We estimated that, in aggregate, avian predators consumed 31% of juvenile steelhead during outmigration to the ocean (95% CRI: [27, 36]). Colony-specific predation rates ranged from < 1 to 14% among river reaches, with avian predation accounting for > 95% of all steelhead mortality within some reaches. This integrated modelling approach provides a flexible framework to integrate multiple recapture and recovery data sources, providing a more holistic understanding of animal life history, including direct comparisons of cause-specific mortality factors and the cumulative impact of multiple mortality factors across time or space.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Barker RJ (1997) Joint modeling of live-recapture, tag-resight, and tag-recovery data. Biometrics 53:666–677

    Article  Google Scholar 

  • Betancourt M, Mark G (2015) Hamiltonian Monte Carlo for hierarchical models. In: Upadhyay SK, Singh U, Dey DK, Loganathan A (eds) Current trends in Bayesian methodology with applications. Chapman and Hall/CRC Press, Boca Raton

    Google Scholar 

  • Bohning D, van der Heijden PG, Bunge J (eds) (2017) Capture-recapture methods for the social and medical sciences. CRC Press, Boca Raton

    Google Scholar 

  • Burnham K (1993) A theory for combined analysis of ring recovery and recapture data. In: Lebreton J, North P (eds) Marked individuals in the study of bird populations. Birkhäuser Verlag, Basel, pp 199–213

    Google Scholar 

  • Catchpole EA, Freeman SN, Morgan BJT, Harris MP (1998) Integrated recovery/recapture data analysis. Biometrics 54:33–46

    Article  Google Scholar 

  • Catchpole EA, Freeman SN, Morgan BJT, Nash WJ (2001) Abalone I: analyzing mark-recapture-recovery data incorporating growth and delayed recovery. Biometrics 57:469–477

    Article  CAS  PubMed  Google Scholar 

  • Colchero F, Clark JS (2012) Bayesian inference on age-specific survival for censored and truncated data. J Anim Ecol 81(1):139–149

    Article  PubMed  Google Scholar 

  • Collis K, Roby DD, Craig DP, Ryan BA, Ledgerwood RD (2001) Colonial waterbird predation on juvenile salmonids tagged with passive integrated transponders in the Columbia River Estuary: vulnerability of different salmonid species, stocks, and rearing types. Trans Am Fish Soc 130:385–396

    Article  Google Scholar 

  • R Development Core Team (2014) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

    Google Scholar 

  • Dietrich JP, Boylen DA, Thompson DE, Loboschefsky EJ, Bravo CF, Spangenberg DK, Ylitalo GM, Collier TK, Fryer DS, Arkoosh MR, Loge FJ (2011) An evaluation of the influence of stock origin and out-migration history on the disease susceptibility and survival of juvenile Chinook Salmon. J Aquat Anim Health 23:35–47

    Article  PubMed  Google Scholar 

  • Evans AF, Hostetter NJ, Roby DD, Collis K, Lyons DE, Sandford BP, Ledgerwood RD (2012) Systemwide evaluation of avian predation on juvenile salmonids from the Columbia River based on recoveries of passive integrated transponder tags. Trans Am Fish Soc 141:975–989

    Article  Google Scholar 

  • Evans AF, Hostetter NJ, Collis K, Roby DD, Loge F (2014) Relationship between juvenile fish condition and survival to adulthood in steelhead. Trans Am Fish Soc 143:899–909

    Article  Google Scholar 

  • Evans AF, Payton Q, Turecek A, Cramer B, Collis K, Roby DD, Loschl PJ, Sullivan L, Skalski J, Weiland M, Dotson C (2016) Avian predation on juvenile salmonids: spatial and temporal analysis based on acoustic and passive integrated transponder tags. Trans Am Fish Soc 145:860–877

    Article  Google Scholar 

  • Gelman A (2004) Parameterization and Bayesian modeling. J Am Stat Assoc 99(466):537–545

    Article  Google Scholar 

  • Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB (2013) Bayesian data analysis, 3rd edn. Chapman and Hall/CRC, Boca Raton

    Google Scholar 

  • Hostetter NJ, Evans AF, Roby DD, Collis K (2012) Susceptibility of juvenile steelhead to avian predation: the influence of individual fish characteristics and river conditions. Trans Am Fish Soc 141:1586–1599

    Article  Google Scholar 

  • Hostetter NJ, Evans AF, Cramer BM, Collis K, Lyons DE, Roby DD (2015a) Quantifying avian predation on fish populations: integrating predator-specific deposition probabilities in tag recovery studies. Trans Am Fish Soc 144:410–422

    Article  Google Scholar 

  • Hostetter NJ, Evans AF, Loge FJ, O’Connor RR, Cramer BM, Fryer D, Collis K (2015b) The influence of individual fish characteristics on survival and detection: similarities across two salmonid species. N Am J Fish Manag 35:1034–1045

    Article  Google Scholar 

  • Hostetter NJ, Gardner B, Evans AF, Cramer BM, Payton Q, Collis K, Roby DD (2018) Wanted dead or alive: a state-space mark–recapture–recovery model incorporating multiple recovery types and state uncertainty. Can J Fish Aquat Sci 75:1117–1127

    Article  Google Scholar 

  • Kareiva P, Marvier M, McClure M (2000) Recovery and management options for Spring/Summer Chinook Salmon in the Columbia River Basin. Science 290:977–979

    Article  CAS  PubMed  Google Scholar 

  • Kendall WL, Conn PB, Hines JE (2006) Combining multistate capture-recapture data with tag recoveries to estimate demographic parameters. Ecology 87:169–177

    Article  PubMed  Google Scholar 

  • Lebreton JD, Nichols JD, Barker RJ, Pradel R, Spendelow JA (2009) Modeling individual animal histories with multistate capture-recapture models. Adv Ecol Res 41:87–173

    Article  Google Scholar 

  • McCrea RS, Morgan BJ (2014) Analysis of capture-recapture data. Chapman and Hall/CRC, Boca Raton

    Book  Google Scholar 

  • Michelot T, Langrock R, Kneib T, King R (2015) Maximum penalized likelihood estimation in semiparametric mark-recapture-recovery models. Biom J 58:222–239

    Article  PubMed  Google Scholar 

  • Muir WD, Smith SG, Williams JG et al (2001) Survival estimates for migrant yearling Chinook salmon and steelhead tagged with passive integrated transponders in the Lower Snake and Lower Columbia rivers, 1993-1998. N Am J Fish Manag 21:269–282

    Article  Google Scholar 

  • Osterback AMK, Frechette DM, Shelton AO, Hayes SA, Bond MH, Shaffer SA, Moore JW (2013) High predation on small populations: avian predation on imperiled salmonids. Ecosphere 4(9):1–21

    Article  Google Scholar 

  • Papaspiliopoulos O, Roberts GO, Sköld M (2007) A general framework for the parametrization of hierarchical models. Stat Sci 22:59–73

    Article  Google Scholar 

  • Pollock KH, Nichols JD, Brownie C, Hines JE (1990) Statistical inference for capture-recapture experiments. Wildl Monogr 107:3–97

    Google Scholar 

  • Pollock KH, Hoenig JM, Hearn WS, Calingaert B (2001) Tag reporting rate estimation: 1. An evaluation of the high-reward tagging method. N Am J Fish Manag 21:521–532

    Article  Google Scholar 

  • Ryan BA, Smith SG, Butzerin JM, Ferguson JW (2003) Relative vulnerability to avian predation of juvenile salmonids tagged with passive integrated transponders in the Columbia River estuary, 1998-2000. Trans Am Fish Soc 132:275–288

    Article  Google Scholar 

  • Sandford BP, Smith SG (2002) Estimation of smolt-to-adult return percentages for Snake River Basin anadromous salmonids, 1990-1997. J Agric Biol Environ Stat 7:243–263

    Article  Google Scholar 

  • Schaub M, Pradel R (2004) Assessing the relative importance of different sources of mortality from recoveries of marked animals. Ecology 85(4):930–938

    Article  Google Scholar 

  • Stan Development Team (2016) RStan: the R interface to Stan. R package version 2.14.1. http://mc-stan.org/

  • Teuscher DM, Green MT, Schill DJ, Brimmer AF, Hillyard RW (2015) Predation by American white pelicans on Yellowstone Cutthroat Trout in the Blackfoot River drainage, Idaho. N Am J Fish Manag 35:454–463

    Article  Google Scholar 

  • Ward DL, Petersen JH, Loch JJ (1995) Index of predation on juvenile salmonids by northern squawfish in the lower and middle Columbia River and in the lower Snake River. Trans Am Fish Soc 124:321–334

    Article  Google Scholar 

  • Zabel RW, Wagner T, Congleton JL, Smith SG, Williams JG (2005) Survival and selection of migrating salmon from capture-recapture models with individual traits. Ecol Appl 15:1427–1439

    Article  Google Scholar 

Download references

Acknowledgements

Brad Cramer, Aaron Turecek, Ken Collis, and Pete Loschl provided assistance collecting and compiling data, for which we are grateful. We are very thankful to James Faulkner at NOAA for helping to compile the PIT-tag codes used in the example dataset. We received in-kind support—through the completion of independent but related studies—from Public Utility District No. 2 of Grant County/PRCC, Bonneville Power Administration, and the U.S. Army Corps of Engineers—Walla Walla and Portland Districts. We specifically want to thank Curtis Dotson, David Roberts, David Trachtenbarg, and Cynthia Studebaker.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Quinn Payton.

Additional information

Handling Editor: Bryan F. J. Manly.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Payton, Q., Hostetter, N.J. & Evans, A.F. Jointly estimating survival and mortality: integrating recapture and recovery data from complex multiple predator systems. Environ Ecol Stat 26, 107–125 (2019). https://doi.org/10.1007/s10651-019-00421-8

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10651-019-00421-8

Keywords

Navigation