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Diversity 2011, 3(2), 252-261; doi:10.3390/d3020252

Using Maximum Entropy Modeling for Optimal Selection of Sampling Sites for Monitoring Networks

1
U.S. Geological Survey, Fort Collins Science Center, 2150 Centre Avenue, Building C, Fort Collins, CO 80526, USA
2
1499 NESB, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, USA
3
National Ecological Observatory Network (NEON), Inc., 1685 38th Street, Suite 100, Boulder, CO 80301, USA
*
Author to whom correspondence should be addressed.
Received: 14 April 2011 / Revised: 27 April 2011 / Accepted: 10 May 2011 / Published: 26 May 2011
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Abstract

Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km2) of the National Ecological Observatory Network (NEON). We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint), within which each 1 km2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. This approach can be widely used for cost-efficient selection of survey and monitoring sites. View Full-Text
Keywords: environmental variation; species-environmental matching models; species distribution models; Maxent; optimal sampling schemes environmental variation; species-environmental matching models; species distribution models; Maxent; optimal sampling schemes
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Stohlgren, T.J.; Kumar, S.; Barnett, D.T.; Evangelista, P.H. Using Maximum Entropy Modeling for Optimal Selection of Sampling Sites for Monitoring Networks. Diversity 2011, 3, 252-261.

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