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A satellite‐based mobile warning system to reduce interactions with an endangered species

Earth‐observing satellites are a major research tool for spatially explicit ecosystem nowcasting and forecasting. However, there are practical challenges when integrating satellite data into usable real‐time products for stakeholders. The need of forecast immediacy and accuracy means that forecast s...

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Autores principales: Breece, Matthew W., Oliver, Matthew J., Fox, Dewayne A., Hale, Edward A., Haulsee, Danielle E., Shatley, Matthew, Bograd, Steven J., Hazen, Elliott L., Welch, Heather
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459280/
https://www.ncbi.nlm.nih.gov/pubmed/33870598
http://dx.doi.org/10.1002/eap.2358
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author Breece, Matthew W.
Oliver, Matthew J.
Fox, Dewayne A.
Hale, Edward A.
Haulsee, Danielle E.
Shatley, Matthew
Bograd, Steven J.
Hazen, Elliott L.
Welch, Heather
author_facet Breece, Matthew W.
Oliver, Matthew J.
Fox, Dewayne A.
Hale, Edward A.
Haulsee, Danielle E.
Shatley, Matthew
Bograd, Steven J.
Hazen, Elliott L.
Welch, Heather
author_sort Breece, Matthew W.
collection PubMed
description Earth‐observing satellites are a major research tool for spatially explicit ecosystem nowcasting and forecasting. However, there are practical challenges when integrating satellite data into usable real‐time products for stakeholders. The need of forecast immediacy and accuracy means that forecast systems must account for missing data and data latency while delivering a timely, accurate, and actionable product to stakeholders. This is especially true for species that have legal protection. Acipenser oxyrinchus oxyrinchus (Atlantic sturgeon) were listed under the United States Endangered Species Act in 2012, which triggered immediate management action to foster population recovery and increase conservation measures. Building upon an existing research occurrence model, we developed an Atlantic sturgeon forecast system in the Delaware Bay, USA. To overcome missing satellite data due to clouds and produce a 3‐d forecast of ocean conditions, we implemented data interpolating empirical orthogonal functions (DINEOF) on daily observed satellite data. We applied the Atlantic sturgeon research model to the DINEOF output and found that it correctly predicted Atlantic sturgeon telemetry occurrences over 90% of the time within a 3‐d forecast. A similar framework has been utilized to forecast harmful algal blooms, but to our knowledge, this is the first time a species distribution model has been applied to DINEOF gap‐filled data to produce a forecast product for fishes. To implement this product into an applied management setting, we worked with state and federal organizations to develop real‐time and forecasted risk maps in the Delaware River Estuary for both state‐level managers and commercial fishers. An automated system creates and distributes these risk maps to subscribers’ mobile devices, highlighting areas that should be avoided to reduce interactions. Additionally, an interactive web interface allows users to plot historic, current, future, and climatological risk maps as well as the underlying model output of Atlantic sturgeon occurrence. The mobile system and web tool provide both stakeholders and managers real‐time access to estimated occurrences of Atlantic sturgeon, enabling conservation planning and informing fisher behavior to reduce interactions with this endangered species while minimizing impacts to fisheries and other projects.
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spelling pubmed-84592802021-09-28 A satellite‐based mobile warning system to reduce interactions with an endangered species Breece, Matthew W. Oliver, Matthew J. Fox, Dewayne A. Hale, Edward A. Haulsee, Danielle E. Shatley, Matthew Bograd, Steven J. Hazen, Elliott L. Welch, Heather Ecol Appl Articles Earth‐observing satellites are a major research tool for spatially explicit ecosystem nowcasting and forecasting. However, there are practical challenges when integrating satellite data into usable real‐time products for stakeholders. The need of forecast immediacy and accuracy means that forecast systems must account for missing data and data latency while delivering a timely, accurate, and actionable product to stakeholders. This is especially true for species that have legal protection. Acipenser oxyrinchus oxyrinchus (Atlantic sturgeon) were listed under the United States Endangered Species Act in 2012, which triggered immediate management action to foster population recovery and increase conservation measures. Building upon an existing research occurrence model, we developed an Atlantic sturgeon forecast system in the Delaware Bay, USA. To overcome missing satellite data due to clouds and produce a 3‐d forecast of ocean conditions, we implemented data interpolating empirical orthogonal functions (DINEOF) on daily observed satellite data. We applied the Atlantic sturgeon research model to the DINEOF output and found that it correctly predicted Atlantic sturgeon telemetry occurrences over 90% of the time within a 3‐d forecast. A similar framework has been utilized to forecast harmful algal blooms, but to our knowledge, this is the first time a species distribution model has been applied to DINEOF gap‐filled data to produce a forecast product for fishes. To implement this product into an applied management setting, we worked with state and federal organizations to develop real‐time and forecasted risk maps in the Delaware River Estuary for both state‐level managers and commercial fishers. An automated system creates and distributes these risk maps to subscribers’ mobile devices, highlighting areas that should be avoided to reduce interactions. Additionally, an interactive web interface allows users to plot historic, current, future, and climatological risk maps as well as the underlying model output of Atlantic sturgeon occurrence. The mobile system and web tool provide both stakeholders and managers real‐time access to estimated occurrences of Atlantic sturgeon, enabling conservation planning and informing fisher behavior to reduce interactions with this endangered species while minimizing impacts to fisheries and other projects. John Wiley and Sons Inc. 2021-05-30 2021-09 /pmc/articles/PMC8459280/ /pubmed/33870598 http://dx.doi.org/10.1002/eap.2358 Text en © 2021The Authors. Ecological Applications published by Wiley Periodicals LLC on behalf of Ecological Society of America. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Articles
Breece, Matthew W.
Oliver, Matthew J.
Fox, Dewayne A.
Hale, Edward A.
Haulsee, Danielle E.
Shatley, Matthew
Bograd, Steven J.
Hazen, Elliott L.
Welch, Heather
A satellite‐based mobile warning system to reduce interactions with an endangered species
title A satellite‐based mobile warning system to reduce interactions with an endangered species
title_full A satellite‐based mobile warning system to reduce interactions with an endangered species
title_fullStr A satellite‐based mobile warning system to reduce interactions with an endangered species
title_full_unstemmed A satellite‐based mobile warning system to reduce interactions with an endangered species
title_short A satellite‐based mobile warning system to reduce interactions with an endangered species
title_sort satellite‐based mobile warning system to reduce interactions with an endangered species
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459280/
https://www.ncbi.nlm.nih.gov/pubmed/33870598
http://dx.doi.org/10.1002/eap.2358
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