Hyperspectral Imaging Predicts Differences in Carbon and Nitrogen Status Among Representative Biocrust Functional Groups of the Colorado Plateau

Author:

Yan Dong12ORCID,Reed Sasha C.3ORCID,Rutherford William A.24ORCID,Javadian Mostafa2ORCID,Reibold Robin H.3,Villarreal Miguel5ORCID,Poulter Benjamin6ORCID,Song Shujun1,Smith William K.2ORCID

Affiliation:

1. Information and Data Center China Renewable Energy Engineering Institute Beijing China

2. School of Natural Resources and the Environment University of Arizona Tucson AZ USA

3. U.S. Geological Survey Southwest Biological Science Center Moab UT USA

4. U.S. Department of Agriculture‐Agricultural Research Service Southwest Watershed Research Center Tucson AZ USA

5. U.S. Geological Survey Western Geographic Science Center Moffett Field CA USA

6. National Aeronautics and Space Administration Goddard Space Flight Center Washington DC USA

Abstract

AbstractBiological soil crusts (biocrusts) are widespread soil photosynthetic communities covering about 12% of Earth's land surface, and play crucial roles in terrestrial carbon (C) and nitrogen (N) cycles, yet scalable quantifications of biocrusts and their biogeochemical contributions are notably lacking. While remote sensing has enormous potential to assess, scale, and contextualize biocrusts and their functions, the applicability of hyperspectral data in predicting C‐ and N‐related biocrust traits remains largely unexplored. We address this issue by evaluating the potential of in situ hyperspectral data to predict C and N across a range of biocrust species and different environmental conditions. We found that in situ hyperspectral reflectance measurements can be used to predict biocrust tissue C/N ratios and N concentrations with relatively high accuracy but to a lesser extent for potential biocrust N2 fixation rates. Critical wavelength domains included the visible region of the spectrum from roughly 490–600 nm, which most effectively captured variations in biocrust tissue C, and the shortwave infrared region from 1,150 to 1,350 nm and 1,550–1,650 nm, which most effectively captured biocrust tissue N and N2 fixation potential. Finally, we provide evidence that multi‐ and hyperspectral missions with targeted band placement, such as the proposed 26‐band Landsat Next, could be effective in predicting biocrust traits. This work provides a critical step in understanding how to apply data from new and upcoming satellite missions to the monitoring of biocrusts.

Funder

U.S. Geological Survey

National Aeronautics and Space Administration

U.S. Department of Defense

Strategic Environmental Research and Development Program

Publisher

American Geophysical Union (AGU)

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