Abstract

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 1mm2 to 1m2 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 (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. The optimal pixel size for distinguishing α diversity in these prairie plots appeared to be around 1mm to 10cm, 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.

Highlights

  • Biodiversity loss, one of the most crucial challenges of our time, endangers ecosystem services that maintain human wellbeing (Magurran and Dornelas 2010)

  • Increasing pixel size reduced the sensitivity of spectral diversity to planted species richness (Fig. 4a)

  • When applying an analysis of covariance (ANCOVA) test to see whether the regression slopes varied with scales, there was no significant difference between slopes of regression at 1 mm and 1 cm scales, but the difference of slopes between 1 cm and 10 cm was significant (P = 0.009)

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Summary

Introduction

Biodiversity loss, one of the most crucial challenges of our time, endangers ecosystem services that maintain human wellbeing (Magurran and Dornelas 2010). “Essential biodiversity variables” have been proposed by ecologists to monitor the variation of biodiversity globally (Pereira et al 2013). Traditional methods of measuring biodiversity require extensive and costly field sampling by biologists with considerable experience in species identification, and the results may vary with. Manuscript received 17 January 2017; revised 12 May 2017; accepted 26 May 2017. Diversity can be defined by a large range of indices according to the scale of observation (Whittaker 1960, 1972). Alpha (a) diversity is diversity within a defined place or a habitat at a local scale, typically within a single circumscribed community or field plot; beta (b) diversity

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