Biodiversity loss, one of the most crucial challenges of our time, endangers ecosystem services that maintain human wellbeing. Traditional methods of measuring biodiversity require extensive and costly field sampling by biologists with considerable experience in species identification. Remote sensing has the potential to detect plant biodiversity based on optical properties, which vary with different species or functional groups (“optical types”). These approaches offer the potential to provide efficient and cost-effective means to determine plant and ecosystem diversity at different spatial scales and over large areas. However, a number of uncertainties remain, including the appropriate spatial resolution necessary to detect diversity. At low spatial and spectral resolution, differences among optical types may be too weak to detect. Alternatively, at high spatial and/or spectral resolution, optical information may introduce contradictory information.
We studied the scale-dependence of optical diversity in a prairie ecosystem experiment at Cedar Creek Ecosystem Science Reserve, Minnesota, USA. To do this, we used hyperspectral data collected from several instruments on both ground and airborne platforms. We then conducted a scaling exercise comparing pixels of different spatial resolutions within manipulated plant diversity treatments. We used the coefficient of variation (CV) of spectral reflectance in space as the indicator of optical diversity. We then compared the optical diversity measured at different scales ranging from 1 mm2 to 1 m2 to various standard metrics of biodiversity, expressed as species richness and evenness.
Results/Conclusions
High richness plots generally had a higher optical diversity (CV). CV showed higher correlations with Shannon index and Simpson index than species richness alone, indicating evenness contributed to the optical diversity signal. We propose that evenness can add information on community structure, which can affect the spatial variation of optical signal. High resolution imaging spectrometer data (1mm2 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. At a resolution of 10cm or higher, much of the power to assess biodiversity was lost; at 1 m resolution there was very little power to distinguish diversity levels. The optimal pixel size for distinguishing diversity in these prairie plots appeared to be around 1mm to 10cm, a spatial scale similar to the size of a herbaceous plant species. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods.