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Remote Sens. 2016, 8(2), 128; doi:10.3390/rs8020128

Seasonal Variation in the NDVI–Species Richness Relationship in a Prairie Grassland Experiment (Cedar Creek)

1
Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB T6G 2E3, Canada
2
Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada
3
School of Natural Resources, University of Nebraska, Lincoln, NE 68583, USA
4
Department of Ecology, Evolution and Behavior, University of Minnesota, Saint Paul, MN 55108, USA
5
Department of Forest and Wildlife Ecology, University of Wisconsin, Madison, WI 53706, USA
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Academic Editors: Susan L. Ustin, Parth Sarathi Roy and Prasad S. Thenkabail
Received: 2 December 2015 / Revised: 28 January 2016 / Accepted: 1 February 2016 / Published: 5 February 2016
(This article belongs to the Special Issue Remote Sensing of Biodiversity)
View Full-Text   |   Download PDF [2168 KB, uploaded 5 February 2016]   |  

Abstract

Species richness generally promotes ecosystem productivity, although the shape of the relationship varies and remains the subject of debate. One reason for this uncertainty lies in the multitude of methodological approaches to sampling biodiversity and productivity, some of which can be subjective. Remote sensing offers new, objective ways of assessing productivity and biodiversity. In this study, we tested the species richness–productivity relationship using a common remote sensing index, the Normalized Difference Vegetation Index (NDVI), as a measure of productivity in experimental prairie grassland plots (Cedar Creek). Our study spanned a growing season (May to October, 2014) to evaluate dynamic changes in the NDVI–species richness relationship through time and in relation to environmental variables and phenology. We show that NDVI, which is strongly associated with vegetation percent cover and biomass, is related to biodiversity for this prairie site, but it is also strongly influenced by other factors, including canopy growth stage, short-term water stress and shifting flowering patterns. Remarkably, the NDVI-biodiversity correlation peaked at mid-season, a period of warm, dry conditions and anthesis, when NDVI reached a local minimum. These findings confirm a positive, but dynamic, productivity–diversity relationship and highlight the benefit of optical remote sensing as an objective and non-invasive tool for assessing diversity–productivity relationships. View Full-Text
Keywords: remote sensing; species richness; productivity; grassland; NDVI remote sensing; species richness; productivity; grassland; NDVI
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Wang, R.; Gamon, J.A.; Montgomery, R.A.; Townsend, P.A.; Zygielbaum, A.I.; Bitan, K.; Tilman, D.; Cavender-Bares, J. Seasonal Variation in the NDVI–Species Richness Relationship in a Prairie Grassland Experiment (Cedar Creek). Remote Sens. 2016, 8, 128.

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