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Mostafa Javadian

Publications and source records attributed to Mostafa Javadian.

2 recordsLinked to original sources

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

Biological 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.

Utah

Thermography captures the differential sensitivity of dryland functional types to changes in rainfall event timing and magnitude

Drylands of the southwestern United States are rapidly warming, and rainfall is becoming less frequent and more intense, with major yet poorly understood implications for ecosystem structure and function. Thermography-based estimates of plant temperature can be integrated with air temperature to infer changes in plant physiology and response to climate change. However, very few studies have evaluated plant temperature dynamics at high spatiotemporal resolution in rainfall pulse-driven dryland ecosystems. We address this gap by incorporating high-frequency thermal imaging into a field-based precipitation manipulation experiment in a semi-arid grassland to investigate the impacts of rainfall temporal repackaging. All other factors held constant, we found that fewer/larger precipitation events led to cooler plant temperatures (1.4°C) compared to that of many/smaller precipitation events. Perennials, in particular, were 2.5°C cooler than annuals under the fewest/largest treatment. We show these patterns were driven by: increased and consistent soil moisture availability in the deeper soil layers in the fewest/largest treatment; and deeper roots of perennials providing access to deeper plant available water. Our findings highlight the potential for high spatiotemporal resolution thermography to quantify the differential sensitivity of plant functional groups to soil water availability. Detecting these sensitivities is vital to understanding the ecohydrological implications of hydroclimate change.

New Phytologist