Measuring plant biomass remotely using drones in arid landscapes
Abstract 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. We estima...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-05-01
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| Series: | Ecology and Evolution |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ece3.8891 |
| _version_ | 1818156636852715520 |
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| author | Justin A. McCann David A. Keith Richard T. Kingsford |
| author_facet | Justin A. McCann David A. Keith Richard T. Kingsford |
| author_sort | Justin A. McCann |
| collection | DOAJ |
| description | Abstract 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. 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. 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. 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. |
| first_indexed | 2024-12-11T15:01:27Z |
| format | Article |
| id | doaj.art-e29f0df348384b6eae9abd402640e3ee |
| institution | Directory Open Access Journal |
| issn | 2045-7758 |
| language | English |
| last_indexed | 2024-12-11T15:01:27Z |
| publishDate | 2022-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecology and Evolution |
| spelling | doaj.art-e29f0df348384b6eae9abd402640e3ee2022-12-22T01:01:09ZengWileyEcology and Evolution2045-77582022-05-01125n/an/a10.1002/ece3.8891Measuring plant biomass remotely using drones in arid landscapesJustin A. McCann0David A. Keith1Richard T. Kingsford2Centre for Ecosystem Science School of Biological, Earth and Environmental Sciences UNSW Sydney New South Wales AustraliaCentre for Ecosystem Science School of Biological, Earth and Environmental Sciences UNSW Sydney New South Wales AustraliaCentre for Ecosystem Science School of Biological, Earth and Environmental Sciences UNSW Sydney New South Wales AustraliaAbstract 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. 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. 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. 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.https://doi.org/10.1002/ece3.8891allometrybiomassdroneplantunmanned aerial systemunmanned aerial vehicle |
| spellingShingle | Justin A. McCann David A. Keith Richard T. Kingsford Measuring plant biomass remotely using drones in arid landscapes Ecology and Evolution allometry biomass drone plant unmanned aerial system unmanned aerial vehicle |
| 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 | allometry biomass drone plant unmanned aerial system unmanned aerial vehicle |
| url | https://doi.org/10.1002/ece3.8891 |
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