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Integrating telemetry and point observations to inform management and conservation of migratory marine species

  • University of Maryland Center for Environmental Science
    ,
  • Heritage Harbor Complex
    ,
  • Principia College
    ,
  • Wider Caribbean Sea Turtle Conservation Network (WIDECAST)
    ,
  • MigraMar
    ,
  • Instituto de Fomento Pesquero
Research Output: Contribution to journal Article Peer-review

Open access

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Article number

e4375

Journal (Volume, Issue Number)

Ecosphere (Volume 14, Issue 1)

Publication milestones

  • Published - 01/2023

Publication status

Published - 01/2023

Publication IDs

  • Scopus: 85147146774

Abstract

Species 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.

Funding Details

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 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.
FundersFunding numbers
NOAA CoastWatch/OceanWatch
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NOAA West Coast Regional Office
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NASA
-
NOAA
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SU
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NFWF
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Marisla Foundation
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SWFSC
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PIFSC
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