Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/106742
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Type: Journal article
Title: Integrating technologies for scalable ecology and conservation
Author: Marvin, D.
Koh, L.
Lynam, A.
Wich, S.
Davies, A.
Krishnamurthy, R.
Stokes, E.
Starkey, R.
Asner, G.
Citation: Global Ecology and Conservation, 2016; 7:262-275
Publisher: Elsevier BV
Issue Date: 2016
ISSN: 2351-9894
2351-9894
Statement of
Responsibility: 
David C. Marvin, Lian Pin Koh, Antony J. Lynam, Serge Wich, Andrew B. Davies, Ramesh Krishnamurthy, Emma Stokes, Ruth Starkey, Gregory P. Asner
Abstract: Integration of multiple technologies greatly increases the spatial and temporal scales over which ecological patterns and processes can be studied, and threats to protected ecosystems can be identified and mitigated. A range of technology options relevant to ecologists and conservation practitioners are described, including ways they can be linked to increase the dimensionality of data collection efforts. Remote sensing, ground-based, and data fusion technologies are broadly discussed in the context of ecological research and conservation efforts. Examples of technology integration across all of these domains are provided for large-scale protected area management and investigation of ecological dynamics. Most technologies are low-cost or open-source, and when deployed can reach economies of scale that reduce per-area costs dramatically. The large-scale, long-term data collection efforts presented here can generate new spatio-temporal understanding of threats faced by natural ecosystems and endangered species, leading to more effective conservation strategies.
Keywords: Drone; ecological dynamics; protected area management; GPS telemetry; remote sensing; Wireless Sensor Networks
Description: Available online 11 August 2016
Rights: © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
DOI: 10.1016/j.gecco.2016.07.002
Grant ID: ARC
Published version: http://dx.doi.org/10.1016/j.gecco.2016.07.002
Appears in Collections:Aurora harvest 3
Ecology, Evolution and Landscape Science publications

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