Remote sensing has been used to detect plant biodiversity in a range of ecosystems based on the varying spectral properties of different species or functional groups. However, the most appropriate spatial resolution necessary to detect diversity remains unclear. At coarse resolution, differences among spectral patterns may be too weak to detect. In contrast, at fine resolution, redundant information may be introduced. To explore the effect of spatial resolution, we studied the scale dependence of spectral diversity in a prairie ecosystem experiment at Cedar Creek Ecosystem Science Reserve, Minnesota, USA. Our study involved a scaling exercise comparing synthetic pixels resampled from high-resolution images within manipulated diversity treatments. Hyperspectral data were collected using several instruments on both ground and airborne platforms. We used the coefficient of variation (CV) of spectral reflectance in space as the indicator of spectral diversity and then compared CV at different scales ranging from 1 mm2 to 1 m2 to conventional biodiversity metrics, including species richness, Shannon's index, Simpson's index, phylogenetic species variation, and phylogenetic species evenness. In this study, higher species richness plots generally had higher CV. CV showed higher correlations with Shannon's index and Simpson's index than did species richness alone, indicating evenness contributed to the spectral diversity. Correlations with species richness and Simpson's index were generally higher than with phylogenetic species variation and evenness measured at comparable spatial scales, indicating weaker relationships between spectral diversity and phylogenetic diversity metrics than with species diversity metrics. High resolution imaging spectrometer data (1 mm2 pixels) showed the highest sensitivity to diversity level. With decreasing spatial resolution, the difference in CV between diversity levels decreased and greatly reduced the optical detectability of biodiversity. The optimal pixel size for distinguishing α diversity in these prairie plots appeared to be around 1 mm to 10 cm, a spatial scale similar to the size of an individual herbaceous plant. These results indicate a strong scale-dependence of the spectral diversity-biodiversity relationships, with spectral diversity best able to detect a combination of species richness and evenness, and more weakly detecting phylogenetic diversity. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods.
Bibliographical noteFunding Information:
We thank staff at the Cedar Creek Ecosystem Science Reserve, particularly Troy Mielke and Kally Worm. We thank Rick Perk and Abby Stilwell from CALMIT, University of Nebraska-Lincoln for acquiring and processing airborne data. We also thank Aidan Mazur and Melanie Sinnen from University of Wisconsin-Madison for helping collect the whole-plot reflectance data. We appreciate Anna Schweiger from University of Minnesota for her coordination of data collection in 2015. This study was supported by a NASA and NSF grant (DEB-1342872) to J. Cavender-Bares, a NSF-LTER grant (DEB-1234162) to J. Cavender-Bares, and by iCORE/AITF (G224150012 & 200700172), NSERC (RGPIN-2015-05129), and CFI (26793) grants to J. Gamon, and a China Scholarship Council fellowship to R. Wang.
This study was supported by a NASA and NSF grant (DEB-1342872) to J. Cavender-Bares, a NSF-LTER grant (DEB-1234162) to J. Cavender-Bares, and by iCORE/AITF (G224150012 & 200700172), NSERC (RGPIN-2015-05129), and CFI (26793) grants to J. Gamon, and a China Scholarship Council fellowship to R. Wang.
©2018 The Authors Ecological Applications published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.
- Cedar Creek
- imaging spectroscopy
- remote sensing
- spectral diversity