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dc.contributor.authorLiang, D.
dc.contributor.authorBailey, H.
dc.contributor.authorHoover, A.L.
dc.contributor.authorEckert, S.
dc.contributor.authorZarate, P.
dc.contributor.authorAlfaro-Shigueto, J.
dc.contributor.authorMangel, J.C.
dc.contributor.authorde Paz Campos, N.
dc.contributor.authorDavila, J.Q.
dc.contributor.authorBarturen, D.S.
dc.contributor.authorRguez-Baron, J.M.
dc.contributor.authorFahy, C.
dc.contributor.authorRocafuerte, A.
dc.contributor.authorVeelenturf, C.
dc.contributor.authorAbrego, M.
dc.contributor.authorShillinger, G.L.
dc.date.accessioned2025-10-31T18:33:57Z
dc.date.available2025-10-31T18:33:57Z
dc.date.issued2023
dc.identifier.urihttps://hdl.handle.net/20.500.12805/5045
dc.description.abstractSpecies distribution models have been widely used in both terrestrial and marine systems, and applications have included invasive species management, evaluating potential effects of climate change, and conservation. Generally, only a single type of data can be accommodated within the model structures used, which may lead to higher uncertainty in the predictions when the data are sparse. In this case, it can be beneficial to pool data from multiple sources and data types, such as fishery observations and telemetry data. An integrated species distribution model (ISDM) utilizes data integration methods that address the challenges of harnessing multiple data types to estimate species distribution. In this study, an ISDM approach was developed to link turtle locations gathered as part of fishery observations with those derived from satellite telemetry in the East Pacific Ocean to enhance our understanding of a highly migratory and endangered marine species, the leatherback turtle (Dermochelys coriacea). These models were developed to support a dynamic management tool, South Pacific TurtleWatch, to identify high-risk areas of management concern and help inform bycatch reduction efforts for this critically endangered species. This data fusion approach could be applied to other populations and species for which telemetry and other point source data are available.en_US
dc.description.sponsorshipFunding text 1: This study was supported in part by Upwell grant 07‐4‐31697. Upwell ( www.upwell.org ) initiated and underwrote this project with support from the Marisla Foundation. The leatherback satellite tracking dataset ( = 46) from Playa Grande, Costa Rica, during the period of 2004–2008 was collected by George Shillinger (Block Lab, Hopkins Marine Station of Stanford University) and collaborators as part of the Tagging of Pacific Predators program of the Census of Marine Life (Block et al., 2011 ; Shillinger et al., 2008 ). The data product was generated using information from the NOAA CoastWatch/OceanWatch and the E.U. Copernicus Marine Service Information. We are grateful to NASA, NOAA, and the E.U. Copernicus Marine Services Information for providing satellite data, with special thanks to Roy Mendelssohn from the Southwest Fisheries Science Center's Environmental Research Division for his mathematical code and data analysis, systematic troubleshooting, and guidance in creating a regional frontal product for this work. Peru satellite telemetry and bycatch monitoring were supported by the National Fish and Wildlife Foundation and the NOAA Pacific Islands Fisheries Science Center and made possible thanks to participating fishers and ProDelphinus staff. Bycatch monitoring in Peru was also supported by NOAA West Coast Regional Office and made possible thanks to Areas Costeras y Recursos Marinos (ACOREMA) staff and fishers willing to share data. We also acknowledge Amanda S. Williard and Daniel Devia for their contribution to data. n; Funding text 2: This study was supported in part by Upwell grant 07-4-31697. Upwell (www.upwell.org) initiated and underwrote this project with support from the Marisla Foundation. The leatherback satellite tracking dataset (n = 46) from Playa Grande, Costa Rica, during the period of 2004–2008 was collected by George Shillinger (Block Lab, Hopkins Marine Station of Stanford University) and collaborators as part of the Tagging of Pacific Predators program of the Census of Marine Life (Block et al., 2011; Shillinger et al., 2008). The data product was generated using information from the NOAA CoastWatch/OceanWatch and the E.U. Copernicus Marine Service Information. We are grateful to NASA, NOAA, and the E.U. Copernicus Marine Services Information for providing satellite data, with special thanks to Roy Mendelssohn from the Southwest Fisheries Science Center's Environmental Research Division for his mathematical code and data analysis, systematic troubleshooting, and guidance in creating a regional frontal product for this work. Peru satellite telemetry and bycatch monitoring were supported by the National Fish and Wildlife Foundation and the NOAA Pacific Islands Fisheries Science Center and made possible thanks to participating fishers and ProDelphinus staff. Bycatch monitoring in Peru was also supported by NOAA West Coast Regional Office and made possible thanks to Areas Costeras y Recursos Marinos (ACOREMA) staff and fishers willing to share data. We also acknowledge Amanda S. Williard and Daniel Devia for their contribution to data.
dc.formatapplication/pdf
dc.language.isoeng
dc.publisherJohn Wiley and Sons
dc.relation.ispartofurn:issn:2150-8925
dc.rightshttps://purl.org/coar/access_right/c_abf2
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectSDG 13en_US
dc.subjectSDG 14en_US
dc.subjectSDG 15en_US
dc.subjectConservation Strategies for Endangered Marine Speciesen_US
dc.subjectConservation and Ecology of Sea Turtle Populationsen_US
dc.titleIntegrating telemetry and point observations to inform management and conservation of migratory marine speciesen_US
dc.typehttps://purl.org/coar/resource_type/c_2df8fbb1
dc.identifier.doihttps://doi.org/10.1002/ecs2.4375
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.06.12
dc.type.otherResearch article
dc.identifier.journalEcosphere
dc.type.versionhttps://purl.org/coar/version/c_970fb48d4fbd8a85


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