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doi:10.3808/jei.201400278
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A Mobile Instrumented Sensor Platform for Long-Term Terrestrial Ecosystem Analysis: An Example Application in an Arctic Tundra Ecosystem

N. C. Healey1*,S. F. Oberbauer1,H. E. Ahrends2,D. Dierick1,J. M. Welker3,A. J. Leffler3,R. D. Hollister4,S. A. Vargas5 and C. E. Tweedie5

1. Department of Biological Sciences, Florida International University, 11200 SW 8th St., Miami FL 33199, USA
2. Institute of Geophysics and Meteorology, University of Cologne, Zülpicher Strasse 49a, Cologne 50674, Germany
3. Department of Biological Sciences, University of Alaska Anchorage, 3101 Science Circle, CPSB 101 Anchorage AK 99508, USA
4. Department of Biological Sciences, Grand Valley State University, 212 Henry Hall 1 Campus Dr., Allendale MI 49401, USA
5. Department of Biological Sciences, University of Texas at El Paso, 500 West University Ave., El Paso TX 79968, USA

*Corresponding author. Tel: +1-305-3486707 Fax: +1-305-3481986 Email: nhealey@fiu.edu

Abstract


To address impacts of climate change on natural ecosystems, researchers need efficient and integrated ground-based sensor systems capable of detecting plant to ecosystem alterations to productivity, species composition, phenology, and structure and function over seasonal, inter-annual, and decadal time scales. Here, we introduce the Mobile Instrumented Sensor Platform (MISP), a versatile robotic sensor system that is suspended above or within the canopy and is designed to be adaptable for both short and long-term observations, and suitable for multiple ecosystems. The system is novel in that it is mobile, rather than static, the suite of sensors can be customized, and installation and operation requires minor surface distur bance relative to comparable systems already in use. MISP was developed as a contribution to the Arctic Observation Network’s International Tundra Experiment (AON-ITEX), where at five locations between the low and high Arctic we record observations of different tundra plant communities over a 50 m transect. Observations include air temperature, surface temperature, incoming and outgoing long- and short-wave radiation, albedo, Normalized Difference Vegetation Index (NDVI), three-dimensional video, two and three-dimensional photography, and hyperspectral reflectance. Data analysis has proven the system’s suitability for detecting subtle ecosystem changes across small-scale soil moisture and other gradients due to the mobile nature of the sampling. Long-term studies will benefit from this approach because sampling is repeatable with high spatial and temporal resolution and the system can be adapted to incorporate future technologies.

Keywords: Arctic tundra vegetation, vegetation change, land cover change, remote sensing, Alaska


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