Back

An unmanned aerial vehicle pipeline to estimate body volume at scale for ecological monitoring

Stone, T. C.; Davis, K. J.

2023-11-23 ecology
10.1101/2023.11.23.567408 bioRxiv
Show abstract

O_LIDemographic data are essential to construct mechanistic models to understand how populations change over time and in response to global threats like climate change. Existing demographic data are either lacking or insufficient for many species, particularly those that are challenging to study, such as marine mammals. A pipeline for collecting accurate demographic data to construct robust demographic models at scale would fill this knowledge gap for many species, including marine mammals like pinnipeds (seals, sea lions, and walruses). C_LIO_LIWe introduce a non-invasive pipeline to estimate the 3D body size (volume) of species that will allow monitoring at high spatial and temporal scales. Our pipeline integrates 3D structure-from-motion photogrammetry data collected via planned flight missions using off-the-shelf, multirotor unmanned aerial vehicles (UAVs). We apply and validate this pipeline on the grey seal Halichoerus grypus, a marine species that spends much of its time at sea but is predictably observable during its annual breeding season. We investigate the optimal ground sampling distance (GSD) for surveys by calculating the success rates and accuracy of volume estimates of individuals at different elevations. C_LIO_LIWe establish an optimal GSD of 0.8 cm px-1 for animals similar in size to UK grey seals ([~]1.4 - 2.5 m length), making our pipeline reproducible and applicable to a broad range of organisms. Volume estimates were accurate and could be made for up to 68% of hauled-out seals in the study areas. Finally, we highlight six key traits that make a species well-suited to estimating body volume following this pipeline. Good candidates include large reptiles like crocodiles, large mammals such as hippopotamus, and shrubs or bushes in deserts and Mediterranean habitats. C_LIO_LIOur pipeline accurately estimates individual body volume of marine macrovertebrates in a time-and cost-effective manner whilst minimising disturbance. Whilst the approach is applied to pinnipeds here, the pipeline is adaptable to many different taxa that are otherwise challenging to study. Our proposed approach therefore opens up previously inaccessible areas of the Tree of Life to demographic studies, which will improve our ability to protect and conserve these species into the future. C_LI

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
PLOS ONE
4510 papers in training set
Top 10%
18.4%
2
Movement Ecology
18 papers in training set
Top 0.1%
18.4%
3
Methods in Ecology and Evolution
160 papers in training set
Top 0.5%
7.1%
4
Remote Sensing in Ecology and Conservation
10 papers in training set
Top 0.1%
6.3%
50% of probability mass above
5
Ecology and Evolution
232 papers in training set
Top 0.4%
6.2%
6
Scientific Reports
3102 papers in training set
Top 38%
3.5%
7
Ecological Informatics
29 papers in training set
Top 0.2%
2.8%
8
Royal Society Open Science
193 papers in training set
Top 1%
2.1%
9
eLife
5422 papers in training set
Top 36%
2.1%
10
Nature Communications
4913 papers in training set
Top 49%
1.9%
11
Journal of Experimental Biology
249 papers in training set
Top 1%
1.7%
12
Global Ecology and Conservation
25 papers in training set
Top 0.7%
1.7%
13
Philosophical Transactions of the Royal Society B
51 papers in training set
Top 3%
1.7%
14
Peer Community Journal
254 papers in training set
Top 2%
1.6%
15
Animal Conservation
11 papers in training set
Top 0.2%
1.5%
16
Journal of The Royal Society Interface
189 papers in training set
Top 3%
1.3%
17
Frontiers in Ecology and Evolution
60 papers in training set
Top 3%
1.2%
18
Ecological Applications
28 papers in training set
Top 0.5%
1.2%
19
Scientific Data
174 papers in training set
Top 2%
1.1%
20
PeerJ
261 papers in training set
Top 12%
0.9%
21
Journal of Applied Ecology
35 papers in training set
Top 0.6%
0.9%
22
Ecography
50 papers in training set
Top 1%
0.8%
23
iScience
1063 papers in training set
Top 30%
0.8%
24
Proceedings of the Royal Society B: Biological Sciences
341 papers in training set
Top 6%
0.8%
25
Ecosphere
53 papers in training set
Top 0.7%
0.7%
26
Conservation Science and Practice
13 papers in training set
Top 0.5%
0.7%