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Connecting Earth Observation to High-Throughput Biodiversity Data

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Connecting Earth Observation to High-Throughput Biodiversity Data. / White, Piran Crawfurd Limond; Yu, Douglas.

In: Nature Ecology and Evolution, Vol. 1, No. 0176, 22.06.2017, p. 1-9.

Research output: Contribution to journalArticle

Harvard

White, PCL & Yu, D 2017, 'Connecting Earth Observation to High-Throughput Biodiversity Data', Nature Ecology and Evolution, vol. 1, no. 0176, pp. 1-9. https://doi.org/10.1038/s41559-017-0176

APA

White, P. C. L., & Yu, D. (2017). Connecting Earth Observation to High-Throughput Biodiversity Data. Nature Ecology and Evolution, 1(0176), 1-9. https://doi.org/10.1038/s41559-017-0176

Vancouver

White PCL, Yu D. Connecting Earth Observation to High-Throughput Biodiversity Data. Nature Ecology and Evolution. 2017 Jun 22;1(0176):1-9. https://doi.org/10.1038/s41559-017-0176

Author

White, Piran Crawfurd Limond ; Yu, Douglas. / Connecting Earth Observation to High-Throughput Biodiversity Data. In: Nature Ecology and Evolution. 2017 ; Vol. 1, No. 0176. pp. 1-9.

Bibtex - Download

@article{dfff6c73d450427087aec56ca8495b50,
title = "Connecting Earth Observation to High-Throughput Biodiversity Data",
abstract = "There is much interest in using Earth Observation (EO) technology to track biodiversity, ecosystem functions, and ecosystem services, understandable given the fast pace of biodiversity loss. However, because most biodiversity is invisible to EO, EO-based indicators could be misleading, which can reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing, and modern ecological modelling to extract much more of the information available in EO data. This approach is achievable now, 62 offering efficient and near-real time monitoring of management impacts on biodiversity and its functions and services.",
author = "White, {Piran Crawfurd Limond} and Douglas Yu",
note = "{\circledC} 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details",
year = "2017",
month = "6",
day = "22",
doi = "10.1038/s41559-017-0176",
language = "English",
volume = "1",
pages = "1--9",
journal = "Nature Ecology and Evolution",
issn = "2397-334X",
publisher = "Nature Publishing Group",
number = "0176",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Connecting Earth Observation to High-Throughput Biodiversity Data

AU - White, Piran Crawfurd Limond

AU - Yu, Douglas

N1 - © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

PY - 2017/6/22

Y1 - 2017/6/22

N2 - There is much interest in using Earth Observation (EO) technology to track biodiversity, ecosystem functions, and ecosystem services, understandable given the fast pace of biodiversity loss. However, because most biodiversity is invisible to EO, EO-based indicators could be misleading, which can reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing, and modern ecological modelling to extract much more of the information available in EO data. This approach is achievable now, 62 offering efficient and near-real time monitoring of management impacts on biodiversity and its functions and services.

AB - There is much interest in using Earth Observation (EO) technology to track biodiversity, ecosystem functions, and ecosystem services, understandable given the fast pace of biodiversity loss. However, because most biodiversity is invisible to EO, EO-based indicators could be misleading, which can reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing, and modern ecological modelling to extract much more of the information available in EO data. This approach is achievable now, 62 offering efficient and near-real time monitoring of management impacts on biodiversity and its functions and services.

U2 - 10.1038/s41559-017-0176

DO - 10.1038/s41559-017-0176

M3 - Article

VL - 1

SP - 1

EP - 9

JO - Nature Ecology and Evolution

JF - Nature Ecology and Evolution

SN - 2397-334X

IS - 0176

ER -