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Drones count wildlife more accurately and precisely than humans

Citation

Hodgson, JC and Mott, R and Baylis, SM and Pham, TT and Wotherspoon, S and Kilpatrick, AD and Raja Segaran, R and Reid, I and Terauds, A and Koh, LP, Drones count wildlife more accurately and precisely than humans, Methods in Ecology and Evolution, 9, (5) pp. 1160-1167. ISSN 2041-210X (2018) [Refereed Article]


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Copyright Statement

Copyright 2018 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

DOI: doi:10.1111/2041-210X.12974

Abstract

Human activities are creating environmental conditions that pose threats and present opportunities for wildlife. In turn, this creates challenges for conservation managers. Some species have benefited from anthropogenic actions. For example, many invasive species profit from human‐assisted dispersal (Banks, Paini, Bayliss, & Hodda, 2015; Hulme, 2009), and mesopredators may thrive following human‐driven loss of top predators (Ritchie & Johnson, 2009). However, in many cases, wildlife populations are undergoing alarming declines, and extinction rates are now as high as 100‐fold greater than the background extinction rate (Ceballos et al., 2015). Ecological monitoring is essential for understanding these population dynamics, and rigorous monitoring facilitates informed management. The effectiveness of management decision‐making is often dependent on the accuracy and timeliness of the relevant ecological data upon which decisions are based, meaning that improvements to data collection methods may herald improved ecological outcomes from management actions.

Item Details

Item Type:Refereed Article
Keywords:bird, drones, ecology, population monitoring, remotely piloted aircraft, surveys, unmanned aerial vehicle, wildlife
Research Division:Technology
Research Group:Other Technology
Research Field:Technology not elsewhere classified
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in Technology
UTAS Author:Wotherspoon, S (Dr Simon Wotherspoon)
ID Code:131777
Year Published:2018
Web of Science® Times Cited:45
Deposited By:Ecology and Biodiversity
Deposited On:2019-04-04
Last Modified:2019-05-02
Downloads:7 View Download Statistics

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