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Combining tracking with at-sea surveys to improve occurrence and distribution estimates of two threatened seabirds in Peru

Published online by Cambridge University Press:  21 November 2022

Johannes H. Fischer Open the ORCID record for Johannes H. Fischer [Opens in a new window] ,
Samhita Bose ,
Cynthia Romero ,
Matt Charteris ,
Patrick Crowe ,
Graham C. Parker ,
Samantha Ray ,
Kalinka Rexer-huber ,
Paul M. Sagar  and
David R. Thompson
...Show all authors
Johannes H. Fischer*
Affiliation:
Aquatic Unit, Department of Conservation, Wellington, New Zealand
Samhita Bose
Affiliation:
Aquatic Unit, Department of Conservation, Wellington, New Zealand
Cynthia Romero
Affiliation:
Oficina de Investigaciones en Depredadores Superiores, Instituto del Mar del Perú, Callao, Perú
Matt Charteris
Affiliation:
Waybacks, Charleston, New Zealand
Patrick Crowe
Affiliation:
Wildlife Management International, Blenheim, New Zealand
Graham C. Parker
Affiliation:
Parker Conservation, Dunedin, New Zealand
Samantha Ray
Affiliation:
Wildlife Management International, Blenheim, New Zealand
Kalinka Rexer-huber
Affiliation:
Parker Conservation, Dunedin, New Zealand
Paul M. Sagar
Affiliation:
National Institute of Water and Atmospheric Research, Wellington, New Zealand
David R. Thompson
Affiliation:
National Institute of Water and Atmospheric Research, Wellington, New Zealand
Elizabeth Bell
Affiliation:
Wildlife Management International, Blenheim, New Zealand
Igor Debski
Affiliation:
Aquatic Unit, Department of Conservation, Wellington, New Zealand
Javier Quiñones
Affiliation:
Oficina de Investigaciones en Depredadores Superiores, Instituto del Mar del Perú, Callao, Perú
*
*Author for correspondence: Johannes Fischer, Email: johannesfischer@live.nl
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Summary

Seabirds are highly threatened, including by fisheries bycatch. Accurate understanding of offshore distribution of seabirds is crucial to address this threat. Tracking technologies revolutionised insights into seabird distributions but tracking data may contain a variety of biases. We tracked two threatened seabirds (Salvin’s Albatross Thalassarche salvini n = 60 and Black Petrel Procellaria parkinsoni n = 46) from their breeding colonies in Aotearoa (New Zealand) to their non-breeding grounds in South America, including Peru, while simultaneously completing seven surveys in Peruvian waters. We then used species distribution models to predict occurrence and distribution using either data source alone, and both data sources combined. Results showed seasonal differences between estimates of occurrence and distribution when using data sources independently. Combining data resulted in more balanced insights into occurrence and distributions, and reduced uncertainty. Most notably, both species were predicted to occur in Peruvian waters during all four annual quarters: the northern Humboldt upwelling system for Salvin’s Albatross and northern continental shelf waters for Black Petrels. Our results highlighted that relying on a single data source may introduce biases into distribution estimates. Our tracking data might have contained ontological and/or colony-related biases (e.g. only breeding adults from one colony were tracked), while our survey data might have contained spatiotemporal biases (e.g. surveys were limited to waters <200 nm from the coast). We recommend combining data sources wherever possible to refine predictions of species distributions, which ultimately will improve fisheries bycatch management through better spatiotemporal understanding of risks.

Resumen

Resumen

Las aves marinas están seriamente amenazadas, incluyendo por capturas incidentales en diversas pesquerías. La distribución espacial precisa de aves marinas en zonas oceánica es crucial para hacer frente a estas amenazas. Las tecnologías de seguimiento satelital revolucionaron la información sobre las distribuciones espaciales de aves marinas, pero estos datos pueden contener diversos sesgos. Rastreamos dos aves marinas amenazadas (Albatros de Salvini Thalassarche salvini n = 60 y Petrel Negro Procellaria parkinsoni n = 46) desde sus colonias reproductivas en Aotearoa (Nueva Zelanda) hacia zonas oceánicas de Sudamérica, incluyendo Perú, durante su periodo post reproductivo 2018–2020, de manera simultánea se realizaron siete cruceros científicos de avistamientos de aves marinas en aguas peruanas. Luego se utilizaron variables ambientales y modelos de distribución de especies para predecir su ocurrencia y distribución utilizando una de las fuentes de datos o ambas en combinación. Los resultados muestran diferencias estacionales entre las estimaciones de ocurrencia y distribución cuando se utiliza una sola fuente de datos. Sin embargo, cuando se combinaron ambas fuentes de datos, se obtuvo un resultado mucho más equilibrado con respecto a la ocurrencia y distribución de las especies evaluadas, con una notable disminución del sesgo. En particular, se predijo que ambas especies ocurrirían en aguas peruanas durante todas las estaciones. Donde el Albatros de Salvini se distribuye en Ecosistema de la Corriente de Humboldt, y el Petrel negro en la zona de la plataforma continental al norte del país. Nuestros resultados resaltan que confiar en una sola fuente de datos puede generar un mayor sesgo en las estimaciones de distribución. Nuestros datos de seguimiento satelital podrían tener sesgos ontológicos y/o relacionados al grupo etareo evaluado en las colonias reproductivas (solo se rastrearon a aves adultas), mientras que nuestros datos de avistamientos a bordo de embarcaciones en Perú, tienen sesgos espaciotemporales (por ejemplo, las evaluaciones se limitaron a aguas <200 nm de la costa). Recomendamos usar ambas fuentes de datos en conjunto, siempre que sea posible, para poder tener una predicción más precisa y fina en la distribución de estas aves marinas, esta información será fundamental para una mejor gestión en el manejo de estas pesquerías para mitigar las capturas incidentales de estas especies a través de una adecuada comprensión de los riesgos a escalas espacio temporales.

Keywords

ConservationGeolocationProcellaria parkinsoniSpecies distribution modelsThalassarche salvini
Type
Research Article
Information
Bird Conservation International , Volume 33 , 2023 , e41
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of BirdLife International

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References

Abraham, E., Richard, Y., Walker, N., Gibson, W., Ochi, D., Tsuji, S., et al. (2019) Assessment of the risk of surface longline fisheries in the Southern Hemisphere to albatrosses and petrels, for 2016. In Report prepared for the 13th Meeting of the Ecologically Related Species Working Group (ERSWG13) of the Commission for the Conservation of Southern Bluefin Tuna (CCSBT-ERS/1905/17).Google Scholar
ACAP. (2009a) Species Assessments: Black Petrel Procellaria parkinsoni. Accessed online 04 November 2021 from http://www.acap.aq.Google Scholar
ACAP. (2009b) Species Assessments: Salvin’s Albatross Thalassarche salvini. Accessed online 04 November 2021 from http://www.acap.aq.Google Scholar
ACAP. (2021a) ACAP Review of Mitigation Measures and Best Practice Advice for Reducing the Impact of Demersal Longline Fisheries on Seabirds. Accessed online 22 July 2022 from http://www.acap.aq.Google Scholar
ACAP. (2021b) ACAP Review of Mitigation Measures and Best Practice Advice for Reducing the Impact of Pelagic Longline Fisheries on Seabirds. Accessed online 22 July 2022 from http://www.acap.aq.Google Scholar
Acha, E. M., Piola, A., Iribarne, O. and Mianzan, H. (2015) Ecological processes at marine fronts: oases in the ocean. Heidelberg, Germany: Springer.CrossRefGoogle Scholar
Alfaro-Shigueto, J., Mangel, J., Pajuelo, M., Dutton, P. H., Seminoff, J. A. and Godley, B. J. (2010) Where small can have a large impact: structure and characterization of small-scale fisheries in Peru. Fish. Res. 106: 8–17.CrossRefGoogle Scholar
Anderson, O. R. J., Small, C. J., Croxall, J. P., Dunn, E. K., Sullivan, R. J., Yates, O., et al. (2011) Global seabird bycatch in longline fisheries. Endanger. Species Res. 14: 91–106.CrossRefGoogle Scholar
Arntz, W. E., Gallardo, V. A., Gutierrez, D., Isla, E., Levin, L. A., Mendo, J., et al. (2006) El Niño and similar perturbation effects on the benthos of the Humboldt, California, and Benguela Current upwelling ecosystems. Adv. Geosci. 6: 243–265.CrossRefGoogle Scholar
Baker, B. G. and Jensz, K. (2019) 2018 Aerial survey of Salvin’s albatross at the Bounty Islands. Wellington, NZ: Department of Conservation.Google Scholar
Baker, B., Jensz, K. and Sagar, P. (2015) Aerial survey of Salvin’s albatross at the Snares, Western Chain. Wellington, NZ: Department of Conservation.Google Scholar
Bakun, A. and Weeks, S. J. (2008) The marine ecosystem off Peru: what are the secrets of its fishery productivity and what might its future hold? Prog. Oceanogr. 79: 290–299.CrossRefGoogle Scholar
Bell, E. A., Mischler, C. P., McArthur, N. and Sim, J. L. (2016a) Black petrel (Procellaria parkinsoni) population study on Hauturu-o-Toi/Little Barrier Island, 2015/16. Wellington, NZ: Department of Conservation.Google Scholar
Bell, E. A., Mischler, C., Sim, J. L. and Scofield, P. (2016b) Population parameters of black petrels (Procellaria parkinsoni) on Great Barrier Island (Aotea Island), 2015/16. Wellington, NZ: Department of Conservation.Google Scholar
Bell, E. A., Ray, S. and Crowe, P. (2020) Population trends, at-sea distribution, and breeding population size of black petrels (Procellaria parkinsoni) – 2018/19 operational report. Wellington, NZ: Fisheries New Zealand.Google Scholar
Bell, E. A., Sim, J. L., Abraham, E., Torres, L. and Shaffer, S. (2014) At-sea distribution of the black petrels (Procellaria parkinsoni) on Great Barrier Island (Aotea Island), 2009/10. Wellington, NZ: Department of Conservation.Google Scholar
Bernard, A., Rodrigues, A. S. L., Cazalis, V. and Gremillet, D. (2021) Toward a global strategy for seabird tracking. Conserv. Lett. 14: e12804.CrossRefGoogle Scholar
BirdLife International (2021a) Species Factsheet: Procellaria parkinsoni. Accessed online 04 November 2021 from http://www.birdlife.org.Google Scholar
BirdLife International (2021b) Species Factsheet: Thalassarche salvini. Accessed online 04 November 2021 from http://www.birdlife.org.Google Scholar
Bolton, M., Conolly, G., Carroll, M., Wakefield, E. D. and Caldow, R. (2018) A review of the occurrence of inter-colony segregation of seabirds foraging areas and the implications for marine environmental impact assessment. Ibis 161: 241–259.CrossRefGoogle Scholar
Burger, A. E. and Shaffer, S. A. (2008) Application of tracking and data-logging technology in research and conservation of seabirds. Auk 125: 253–264.CrossRefGoogle Scholar
Carneiro, A. P. B., Pearmain, E. J., Oppel, S., Clay, T. A., Phillips, R. A., Bonnet-Lebrun, A.-S., et al. (2020) A framework for mapping the distribution of seabirds by integrating tracking, demography, and phenology. J. Appl. Ecol. 57: 514–525.CrossRefGoogle Scholar
Carroll, M. J., Wakefield, E. D., Scragg, E. S., Owen, E., Pinder, S., Bolton, M., et al. (2019) Matches and mismatches between seabird distributions estimated from at-sea surveys and concurrent individual-level tracking. Front. Ecol. Evol. 7: 333.CrossRefGoogle Scholar
Chaigneau, A., Dominguez, N., Eldin, G., Vasquez, L., Flores, R., Grados, C., et al. (2013). Near-coastal circulation in the Northern Humboldt Current System from shipboard ADCP data. J. Geophys. Res. Oceans 118: 5251–5266.CrossRefGoogle Scholar
Chaigneau, A., Gizolme, A. and Grados, C. (2008) Mesoscale eddies off Peru in altimeter records: identification algorithms and eddy spatio-temporal patterns. Prog. Oceanogr. 79: 106–119.CrossRefGoogle Scholar
Chavez, F. P., Bertrand, A., Guevara-Carrasco, R., Soler, P. and Csirke, J. (2008) The northern Humboldt Current System: brief history, present status and view towards the future. Prog. Oceanogr. 79: 95–105.CrossRefGoogle Scholar
Clay, T. A., Small, C., Tuck, G. N., Pardo, D., Carneiro, A. P. B., Wood, A. G., et al. (2019) A comprehensive large-scale assessment of fisheries bycatch risk to threatened seabird populations. J. Appl. Ecol. 56: 1882–1893.CrossRefGoogle Scholar
Cleasby, I. R., Owen, E., Wilson, L., Wakefield, E. D., O’Connell, P. and Bolton, M. (2020) Identifying important at-sea areas for seabirds using species distribution models and hotspot mapping. Biol. Conserv. 241: 108375.CrossRefGoogle Scholar
Davies, T. E., Carneiro, A. P. B., Tarzia, M., Wakefield, E., Hennicke, J. C., Frederiksen, M., et al. (2021) Multispecies tracking reveals a major seabird hotspot in the North Atlantic. Conserv. Lett. 14: e12824.CrossRefGoogle Scholar
De Grissac, S., Borger, L., Guitteaud, A. and Weimerskirch, H. (2016) Contrasting movement strategies among juvenile albatrosses and petrels. Sci. Rep. 6: 26103.CrossRefGoogle ScholarPubMed
Degenford, J. H., Liang, D., Bailey, , Hoover, A. L., Zarate, P., Azocar, J., et al. (2021) Using fisheries observation data to develop a predictive species distribution model for endangered sea turtles. Conserv. Sci. Pract. 3: e349.Google Scholar
Derville, S., Torres, L. G., Iovan, C. and Garrigue, C. (2018) Finding the right fit: comparative cetacean distribution models using multiple data sources and statistical approaches. Divers. Distrib. 24: 1657–1673.CrossRefGoogle Scholar
Dias, M. P., Martin, R., Pearmain, E. J., Burfield, I. J., Small, C., Phillips, R.A., et al. (2019) Threats to seabirds: a global assessment. Biol. Conserv. 237: 525–537.CrossRefGoogle Scholar
Doherty, P. D., Alfaro-Shigueto, J., Hodgson, D. J., Mangel, J. C., Witt, M. J. and Godley, B. J. (2014) Big catch, little sharks: insight into Peruvian small-scale longline fisheries. Ecol. Evol. 4: 2375–2383.CrossRefGoogle ScholarPubMed
Fischer, J. H., Debski, I., Spitz, D. B., Taylor, G. A. and Wittmer, H. U. (2021) Year-round offshore distribution, behaviour, and overlap with commercial fisheries of a Critically Endangered small petrel. Mar. Ecol. Prog. Ser. 660: 171–187.CrossRefGoogle Scholar
Frankish, C. K., Cunningham, C., Manica, A., Clay, T. A., Prince, S. and Phillips, R. A. (2021) Tracking juveniles confirms fisheries-bycatch hotspot for an endangered albatross. Biol. Conserv. 261: 109288.CrossRefGoogle Scholar
Freeman, R., Dennis, T., Landers, T., Thompson, D., Bell, E., Walker, M., et al. (2010) Black Petrels (Procellaria parkinsoni) patrol the ocean shelf-break: GPS tracking of a Vulnerable Procellariiform seabird. PLoS One 5: e9236.CrossRefGoogle ScholarPubMed
Goetz, K., Stephenson, F., Hoskins, A., Bindoff, A. D., Orben, R.A., Sagar, P. M., et al. (2022) Data quality influences the predicted distribution and habitat of four southern-hemisphere Albatross species. Front. Mar. Sci. 9: 782923.CrossRefGoogle Scholar
Gremillet, D., Ponchon, A., Paleczny, M., Palomares, M. D., Karpouzi, V. and Pauly, D. (2018) Persistent worldwide seabird-fishery competition despite seabird community decline. Curr. Biol. 28: 4009–4013.CrossRefGoogle ScholarPubMed
Gummer, H. (2013a) Attaching radio and data-storage tags to birds: feather/skin mounts (tape/ties/glue). Standard operating procedure. Wellington, NZ: Department of Conservation.Google Scholar
Gummer, H. (2013b) Attaching radio and data-storage tags to birds: leg mounts. Standard operating procedure. Wellington, NZ: Department of Conservation.Google Scholar
Gutowsky, S. E., Leonard, M. L., Conners, M. G., Shaffer, S. A. and Jonsen, I. D. (2015) Individual-level variation and higher-level interpretation of space use in wide-ranging species: an albatross case study of sampling effects. Front. Mar. Sci. 2: 93.CrossRefGoogle Scholar
Halpin, L. R., Ross, J. D., Ramos, R., Mott, R., Carlile, N., Golding, N., et al. (2021) Double-tagging scores of seabirds reveals that light-level geolocator accuracy is limited by species idiosyncrasies and equatorial solar profiles. Methods Ecol. Evol. 12: 2243–2255.CrossRefGoogle Scholar
Hazel, J. (2009) Evaluation of fast-acquisition GPS in stationary tests and fine-scale tracking of green turtles. J. Exp. Mar. Biol. Ecol. 374: 58–68.CrossRefGoogle Scholar
Ibanez-Erquiaga, B., Pacheco, A. S., Rivadeneira, M. M. and Tejada, C. L. (2018) Biogeographical zonation of rocky intertidal communities along the coast of Peru (3.5–13.5 S Southeast Pacific). PloS One 13: e0208244.CrossRefGoogle Scholar
Irvine, L. M., Winsor, M. H., Follet, T. M., Mate, B. R. and Palacios, D. M. (2020) An at-sea assessment of Argos location accuracy for three species of large whales, and the effect of deep-diving behavior on location error. Anim. Biotelemetry 8: 20.CrossRefGoogle Scholar
Kroodsma, D. A., Mayorga, J., Hochberg, T., Miller, N. A., Boerder, K., Ferretti, F., et al. (2018). Tracking the global footprint of fisheries. Science 359: 904–908.CrossRefGoogle ScholarPubMed
Kruger, L., Ramos, J. A., Xavier, J. C., Gremillet, D.,Gonzalez-Solis, J., Petry, M.V., et al. (2018) Projected distributions of Southern Ocean albatrosses, petrels and fisheries as a consequence of climate change. Ecography 41: 195–208.CrossRefGoogle Scholar
Lascelles, B. G., Taylor, P. R., Miller, M. G. R., Dias, M. P., Oppel, S., Torres, L., et al. (2016) Applying global criteria to tracking data to define important areas for marine conservation. Divers. Distrib. 22: 422–431.CrossRefGoogle Scholar
Louzao, M., Becares, J., Rodriguez, B., Hyrenbach, K. D., Ruiz, A. and Arcos, J. M. (2009) Combining vessel-based surveys and tracking data to identify key marine areas for seabirds. Mar. Ecol. Prog. Ser. 391: 183–197.CrossRefGoogle Scholar
Majluf, P., Babcock, E. A., Riveros, J. C., Schreiber, M. A. and Alderete, W. (2002) Catch and bycatch of sea birds and marine mammals in the small-scale fishery of Punta San Juan, Peru. Conserv. Biol. 16: 1333–1343.CrossRefGoogle Scholar
Merkel, B., Phillips, R. A., Descamps, S., Yoccoz, N. G., Moe, B. and Strom, H. (2016) A probabilistic algorithm to process geolocation data. Mov. Ecol. 4: 26.CrossRefGoogle ScholarPubMed
Moreno, C. and Quiñones, J. (2022) Albatross and petrel interactions with an artisanal squid fishery in southern Peru during El Niño, 2015–2017. Mar. Ornithol. 50: 49–56.Google Scholar
Mott, R., and Clarke, R. H. (2018) Systematic review of geographic biases in the collection of at-sea distribution data for seabirds. Emu 118: 235–246.CrossRefGoogle Scholar
Oppel, S., Meirinho, A., Ramirez, I., Gardner, B., O’Connell, A.F., Miller, P., et al. (2012) Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds. Biol. Conserv. 156: 94–104.CrossRefGoogle Scholar
Orben, R. A., Adams, J., Hester, M., Shaffer, S. A., Suryan, R. M., Deguchi, T., et al. (2021) Across borders: external factors and prior behaviour influence North Pacific Albatross associations with fishing vessels. J. Appl. Ecol. 58: 1272–1283.CrossRefGoogle Scholar
Paulik, G. J. (1981) Anchovies, birds and fisherman in the Peru current. In Glantz, M. H. and Thompson, J. D. eds. Resource management and environmental uncertainty: lessons from coastal upwelling fisheries. New York, USA: John Wiley and Sons, 156–185.Google Scholar
Peron, C. and Gremillet, D. (2013) Tracking through life stages: adult, immature, and juvenile autumn migration in a long-lived seabird. PLoS One 8: e72713.CrossRefGoogle Scholar
Phillips, R. A., Silk, J. R. D., Croxall, J. P., Afanasyev, V. and Briggs, D. R. (2004) Accuracy of geolocation estimates for flying seabirds. Mar. Ecol. Prog. Ser. 266: 265–272.CrossRefGoogle Scholar
Priddel, D., Carlile, N., Portelli, D., Kim, Y., O’Neill, L., and Bretagnolle, V. (2014) Pelagic distribution of Gould’s Petrel (Pterodroma leucoptera): linking shipboard observations and onshore observations with remote-tracking data. Emu 114: 360–370.CrossRefGoogle Scholar
Quiñones, J., Alegre, A., Romero, C., Manrique, M. and Vasquez, L. (2021) Fine-scale distribution, abundance, and foraging behavior of Salvin’s, Buller’s, and Chatham Albatrosses in the Northern Humboldt Upwelling System. Pacific Sci. 75: 85–105.CrossRefGoogle Scholar
Quiñones, J., Calderon, J., Mayaute, L. and Bell, E. (2020) Black petrel (Procellaria parkinsoni) congregations at sea off Perú during the Austral summer. Notornis 67: 573–576.Google Scholar
R Core Team. (2021) R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.Google Scholar
Raine, A. F., Gjerdrum, C., Pratte, I., Madeiros, J., Felis, J. and Adams, J. (2021) Marine distribution and foraging habitat highlight potential threats at sea for the Endangered Bermuda petrel Pterodroma cahow. Endanger. Species Res. 45: 337–356.CrossRefGoogle Scholar
Rayner, M. J., Hauber, M. E., Steeves, T. E., Lawrence, H. A., Thompson, D.R., Sagar, P, M., et al. (2011) Contemporary and historical separation of transequatorial migration between genetically distinct seabird populations. Nat. Commun. 2: 332.CrossRefGoogle ScholarPubMed
Rexer-Huber, K., Parker, G., Sagar, P. and Thompson, D. (2021) Salvin’s Albatross breeding dates and productivity: nest-camera analysis. Wellington, NZ: Department of Conservation.Google Scholar
Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K.S. and Schlax, M.G. (2007) Daily high-resolution-blended analyses for sea surface temperature. J. Clim. 20: 5473–5496.CrossRefGoogle Scholar
Richard, Y., Abraham, E. R. and Berkenbusch, K. (2020) Assessment of the risk of commercial fisheries to New Zealand seabirds, 2006–07 to 2016–17. Wellington, NZ: Fisheries New Zealand.Google Scholar
Sagar, P., Charteris, M., Parker, G., Rexer-Huber, K. and Thompson, D. (2018) Salvin’s albatross: Bounty Islands population project. Ground component. Wellington, NZ: Department of Conservation.Google Scholar
Sansom, A., Wilson, L. J., Caldow, R. W. G. and Bolton, M. (2018) Comparing marine distribution maps for seabirds during the breeding season derived from different survey and analysis methods. PLoS One 13: e0201797.CrossRefGoogle ScholarPubMed
Schaefer, A. L., Lukacs, P. M. and Kissling, M. (2015) Testing factors influencing identification rates of similar species during abundance surveys. Condor 117: 460–472.CrossRefGoogle Scholar
Shaffer, S. A., Tremblay, Y., Weimerskirch, H., Scott, D., Sagar, P. M., Moller, H., et al. (2006) Migratory shearwaters integrate oceanic resources across the Pacific Ocean in an endless summer. Proc. Natl. Acad. Sci. U.S.A. 103: 12799–12802.CrossRefGoogle Scholar
Spear, L. B., Ainley, D. G. and Webb, S. W. (2003) Distribution, abundance, and behaviour of Buller’s, Chatham Island, and Salvin’s Albatrosses off Chile and Peru. Ibis 145: 253–269.CrossRefGoogle Scholar
Spiegelhalter, D., Thomas, A., Best, N. and Lunn, D., (2007) OpenBUGS user manual. Version, 3(2).Google Scholar
Taylor, G. A. (2000) Action plan for seabird conservation in New Zealand. Part A: threatened seabirds. Wellington, NZ: Department of Conservation.Google Scholar
Thompson, D., Sagar, P., Briscoe, D., Parker, G., Rexer-Huber, K. and Charteris, M. (2020) Salvin’s albatross: Bounty Islands population project. Ground component. Wellington, NZ: Department of Conservation.Google Scholar
Thompson, D., Sagar, P., Torres, L. and Charteris, M. (2014) Salvin’s albatrosses at the Bounty Islands: at-sea distribution. Wellington, NZ: Department of Conservation.Google Scholar
Warwick-Evans, V., Atkinson, P. W., Walkington, I. and Green, J. A. (2017) Predicting the impacts of windfarms on seabirds: an individual-based model. J. Appl. Ecol. 55: 503–515.CrossRefGoogle Scholar
Watanuki, Y., Suryan, R. M., Sasaki, H., Yamamoto, T., Hazen, E. L., Renner, M., et al. (2016) Spatial ecology of marine top predators in the North Pacific: tools for integrating datasets and identifying high use areas. Sydney, Australia: Pices.Google Scholar
Yamamoto, T., Watanuki, Y., Hazen, E. L., Nishizawa, B., Sasaki, H. and Takashi, A. (2015) Statistical integration of tracking and vessel survey data to incorporate life history differences in habitat models. Ecol. Appl. 25: 2349–2406.Google ScholarPubMed
Zhang, J., Bell, E. A. and Roberts, J. O. (2020) Demographic assessment of black petrels (Procellaria parkinsoni) on Great Barrier Island (Aotea Island). Wellington, NZ: Fisheries New Zealand.Google Scholar
Zydelis, R., Lewison, R. L., Shaffer, S. A., Moore, J. E., Boustany, A. M., Roberts, J. J., et al. (2011) Dynamic habitat models: using telemetry data to project fisheries bycatch. Proc. R. Soc. Lond. B. Biol. Sci. 278: 3191–3200.Google ScholarPubMed
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