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Mapping the Flowering of an Invasive Plant Using Unmanned Aerial Vehicles: Is There Potential for Biocontrol Monitoring?

Overview of attention for article published in Frontiers in Plant Science, March 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

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1 policy source
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9 X users
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1 Facebook page

Citations

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58 Dimensions

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151 Mendeley
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Title
Mapping the Flowering of an Invasive Plant Using Unmanned Aerial Vehicles: Is There Potential for Biocontrol Monitoring?
Published in
Frontiers in Plant Science, March 2018
DOI 10.3389/fpls.2018.00293
Pubmed ID
Authors

Nuno C. de Sá, Paula Castro, Sabrina Carvalho, Elizabete Marchante, Francisco A. López-Núñez, Hélia Marchante

Abstract

Invasion by alien species is a worldwide phenomenon with negative consequences at both natural and production areas. Acacia longifolia is an invasive shrub/small tree well known for its negative ecological impacts in several places around the world. The recent introduction of a biocontrol agent (Trichilogaster acaciaelongifoliae), an Australian bud-galling wasp which decreases flowering of A. longifolia, in Portugal, demands the development of a cost-efficient method to monitor its establishment. We tested how unmanned aerial vehicles (UAV) can be used to map A. longifolia flowering. Our core assumption is as the population of the biocontrol agent increases, its impacts on the reduction of A. longifolia flowering will be increasingly visible. Additionally, we tested if there is a simple linear correlation between the number of flowers of A. longifolia counted in field and the area covered by flowers in the UAV imagery. UAV imagery was acquired over seven coastal areas including frontal dunes, interior sand dunes and pine forests considering two phenological stages: peak and off-peak flowering season. The number of flowers of A. longifolia was counted, in a minimum of 60 1 m2 quadrats per study area. For each study area, flower presence/absence maps were obtained using supervised Random Forest. The correlation between the number of flowers and the area covered by flowering plants could then be tested. The flowering of A. longifolia was mapped using UAV mounted with RGB and CIR Cannon IXUS/ELPH cameras (Overall Accuracy > 0.96; Cohen's Kappa > 0.85) varying according to habitat type and flowering season. The correlation between the number of flowers counted and the area covered by flowering was weak (r2 between 0.0134 and 0.156). This is probably explained, at least partially, by the high variability of A. longifolia in what regards flowering morphology and distribution. The very high accuracy of our approach to map A. longifolia flowering proved to be cost efficient and replicable, showing great potential for detecting the future decrease in flowering promoted by the biocontrol agent. The attempt to provide a low-cost method to estimate A. longifolia flower productivity using UAV failed, but it provided valuable insights on the future steps.

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X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 151 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 17%
Student > Master 26 17%
Researcher 25 17%
Student > Bachelor 11 7%
Student > Doctoral Student 6 4%
Other 23 15%
Unknown 34 23%
Readers by discipline Count As %
Environmental Science 36 24%
Agricultural and Biological Sciences 35 23%
Engineering 14 9%
Earth and Planetary Sciences 13 9%
Computer Science 2 1%
Other 8 5%
Unknown 43 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 November 2020.
All research outputs
#4,650,911
of 25,657,205 outputs
Outputs from Frontiers in Plant Science
#2,343
of 24,912 outputs
Outputs of similar age
#84,466
of 349,335 outputs
Outputs of similar age from Frontiers in Plant Science
#63
of 478 outputs
Altmetric has tracked 25,657,205 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 24,912 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 349,335 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 478 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.