Hyperspectral imaging predicts differences in carbon and nitrogen status among representative biocrust functional groups of the Colorado Plateau

Authors: YAN, D. - China Renewable Energy Engineering Institute; REED, S.C. - Us Geological Survey (USGS); Rutherford, William; JAVADIAN, M. - University Of Arizona; REIBOKLDE, R.H. - Us Geological Survey (USGS); VILLARREAL, M. - Us Geological Survey (USGS); POULTER, B. - National Aeronautics And Space Administration (NASA); SONG, S. - China Renewable Energy Engineering Institute

Submitted to: Science of the Total Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/4/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: Biological soil crusts (biocrusts) are widespread soil surface communities estimated to cover 12% of Earth’s land surface and to play crucial roles in terrestrial carbon (C) and nitrogen (N) cycles, yet scalable measurements of biocrusts and their contributions to soil fertility are notably lacking. While soil-surface light reflectance measurements have enormous potential to assess, scale, and contextualize biocrusts and their functions, the promising applicability of fine-scaled reflectance data in predicting C- and N-related biocrust traits remains largely unexplored. In this study, we address this knowledge gap by evaluating the potential of in-situ light reflectance measurements to accurately estimate C and N across a range of biocrust species and different environmental conditions. We found biocrust tissue C/N ratios and N concentrations could be accurately predicted with fine-scaled reflectance measurements. Light reflectance also effectively predicted potential biocrust N-fixation rates. Critical light spectrum regions included the visible region, which most effectively captured variations in biocrust tissue C, and the short-wave infrared region, which most effectively captured biocrust tissue N and N-fixation potential. Finally, we provide evidence that upcoming satellite-based measurements with targeted reflectance domains (e.g., bands), such as the proposed 26-band Landsat Next, could also be effective in accurate biocrust trait Earth surface mapping. This work provides a critical step in understanding how to apply data from new and upcoming satellite missions to the monitoring of biocrusts. Quantitative knowledge of biocrusts and their influence on surface soil C and N storage and cycling is greatly needed for improved accounting of global nutrient cycles, understanding of human-caused feedbacks on the Earth system, and forecasts of future climate conditions.

Technical Abstract: Biological soil crusts (biocrusts) are widespread soil photosynthetic communities estimated to cover 12% of Earth’s land surface and to 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 promising applicability of hyperspectral data in predicting C- and N-related biocrust traits remains largely unexplored. In this study, we address this knowledge gap by evaluating the potential of in-situ hyperspectral remote sensing to accurately estimate C and N across a range of biocrust species and different environmental conditions. We found biocrust tissue C/N ratios (median R=0.91, IQR=0.20) and N concentrations (median R=0.85, IQR=0.06) could be accurately predicted with hyperspectral reflectance measurements. Reflectance data also effectively predicted potential biocrust N2 fixation rates (median R=0.58, IQR=0.04). Critical wavelength domains included the visible region of the spectrum, which most effectively captured variations in biocrust tissue C, and the SWIR domain, which most effectively captured biocrust tissue N and N2 fixation potential. Finally, we provide evidence that multispectral missions with targeted band placement, such as the proposed 26-band Landsat Next, could also be effective in accurate biocrust trait mapping. This work provides a critical step in understanding how to apply data from new and upcoming satellite missions to the monitoring of biocrusts. Quantitative knowledge of biocrusts and their influence on surface soil C and N storage and cycling is greatly needed for improved accounting of global biogeochemical cycles, understanding of anthropogenic feedbacks, and forecasts of future climate.