Biocrust Abundance and Development Determine Soil Restoration Success of Hyper-Arid Phosphate Mines Using Imaging Spectroscopy

Mining operations are critical to economic growth by supplying essential building materials and minerals. However, they significantly impact ecological systems, particularly in arid regions where soil recovery is slow. Biological soil crusts (biocrusts) and their functional importance and vulnerability are crucial for restoring disturbed arid soils. Biocrusts enhance soil health by improving stability, increasing water retention, and reducing erosion. Consequently, biocrust abundance and development provide a valuable indication of soil rehabilitation and mining restoration success in arid environments. This study aims to evaluate the restoration success of phosphate mining in hyper-arid quarried lands by assessing biocrust development and spatial distribution over time across different restoration stages. The research focuses on the Zin phosphate mines in the Negev Desert, southeastern Israel, which have been operational since 1970. Since 2007, a new ecological restoration method using topsoil application has been implemented in the area. We employed imaging spectroscopy (IS) within the visible, near-infrared, and shortwave infrared regions (VIS-NIR-SWIR, 400–2500 nm) to identify biocrusts, create a biocrust-specific index, and link these findings to soil properties indicative of restoration success. Restored plots of varying ages were compared to adjacent natural plots (as a reference). A partial least-squares regression (PLS-R) model was utilized to predict the spatial distribution of key soil indicators from IS, including soil organic matter, polysaccharides, and proteins, and to identify ecologically oriented biocrust development. Moreover, several spectral indices for biocrust identification were examined, where the brightness index (BI) proved effective in distinguishing restored plots from natural plots, showing significant differences (P<0.01). A novel Biocrust Cellulose Absorption Index (BCAI) was developed using the shortwave infrared region, optimally identified biocrust abundance, and displayed significant differences between natural and restored plots (P<0.01). Natural plots exhibited significantly higher polysaccharide content than restored plots (P<0.01). A triangular model incorporating three indicators - polysaccharide content, BI, and BCAI - was further developed to evaluate restoration success. This model assessed biocrust abundance and development, mapping the spatial distribution of biocrusts as a function of time across various restoration stages. The findings demonstrate the utility of IS and novel indices in assessing biocrust abundance and restoration success. This approach provides insights into restoration dynamics and offers a framework for improving restoration strategies in hyper-arid mining as well as other degraded environments.

Keywords: Phosphate Mines, Biological Soil Crusts, Imaging Spectroscopy, Spectral Indices, Partial Least Square Regression.