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Measuring plant biomass remotely using drones in arid landscapes

1. Measurement of variation in plant biomass is essential for answering many ecological and evolutionary questions. Quantitative estimates require plant destruction for laboratory analyses, while field studies use allometric approaches based on simple measurement of plant dimensions. 2. We estimated...

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Detalles Bibliográficos
Autores principales: McCann, Justin A., Keith, David A., Kingsford, Richard T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9106562/
https://www.ncbi.nlm.nih.gov/pubmed/35600687
http://dx.doi.org/10.1002/ece3.8891
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author McCann, Justin A.
Keith, David A.
Kingsford, Richard T.
author_facet McCann, Justin A.
Keith, David A.
Kingsford, Richard T.
author_sort McCann, Justin A.
collection PubMed
description 1. Measurement of variation in plant biomass is essential for answering many ecological and evolutionary questions. Quantitative estimates require plant destruction for laboratory analyses, while field studies use allometric approaches based on simple measurement of plant dimensions. 2. We estimated the biomass of individual shrub‐sized plants, using a low‐cost unmanned aerial system (drone), enabling rapid data collection and non‐destructive sampling. We compared volume measurement (a surrogate for biomass) and sampling time, from the simple dimension measurements and drone, to accurate laboratory‐derived biomass weights. We focused on three Australian plant species which are ecologically important to their terrestrial and floodplain ecosystems: porcupine grass Triodia scariosa, Queensland bluebush Chenopodium auricomum, and lignum Duma florulenta. 3. Estimated volume from the drone was more accurate than simple dimension measurements for porcupine grass and Queensland bluebush, compared to estimates from laboratory analyses but, not for lignum. The latter had a sparse canopy, with thin branches, few vestigial leaves and a similar color to the ground. Data collection and analysis consistently required more time for the drone method than the simple dimension measurements, but this would improve with automation. 4. The drone method promises considerable potential for some plant species, allowing data to be collected over large spatial scales and, in time series, increasing opportunities to answer complex ecological and evolutionary questions and monitor the state of ecosystems and plant populations.
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spelling pubmed-91065622022-05-19 Measuring plant biomass remotely using drones in arid landscapes McCann, Justin A. Keith, David A. Kingsford, Richard T. Ecol Evol Research Articles 1. Measurement of variation in plant biomass is essential for answering many ecological and evolutionary questions. Quantitative estimates require plant destruction for laboratory analyses, while field studies use allometric approaches based on simple measurement of plant dimensions. 2. We estimated the biomass of individual shrub‐sized plants, using a low‐cost unmanned aerial system (drone), enabling rapid data collection and non‐destructive sampling. We compared volume measurement (a surrogate for biomass) and sampling time, from the simple dimension measurements and drone, to accurate laboratory‐derived biomass weights. We focused on three Australian plant species which are ecologically important to their terrestrial and floodplain ecosystems: porcupine grass Triodia scariosa, Queensland bluebush Chenopodium auricomum, and lignum Duma florulenta. 3. Estimated volume from the drone was more accurate than simple dimension measurements for porcupine grass and Queensland bluebush, compared to estimates from laboratory analyses but, not for lignum. The latter had a sparse canopy, with thin branches, few vestigial leaves and a similar color to the ground. Data collection and analysis consistently required more time for the drone method than the simple dimension measurements, but this would improve with automation. 4. The drone method promises considerable potential for some plant species, allowing data to be collected over large spatial scales and, in time series, increasing opportunities to answer complex ecological and evolutionary questions and monitor the state of ecosystems and plant populations. John Wiley and Sons Inc. 2022-05-13 /pmc/articles/PMC9106562/ /pubmed/35600687 http://dx.doi.org/10.1002/ece3.8891 Text en © 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
McCann, Justin A.
Keith, David A.
Kingsford, Richard T.
Measuring plant biomass remotely using drones in arid landscapes
title Measuring plant biomass remotely using drones in arid landscapes
title_full Measuring plant biomass remotely using drones in arid landscapes
title_fullStr Measuring plant biomass remotely using drones in arid landscapes
title_full_unstemmed Measuring plant biomass remotely using drones in arid landscapes
title_short Measuring plant biomass remotely using drones in arid landscapes
title_sort measuring plant biomass remotely using drones in arid landscapes
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9106562/
https://www.ncbi.nlm.nih.gov/pubmed/35600687
http://dx.doi.org/10.1002/ece3.8891
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