Modeling Soil Organic Carbon at Coastal Sabkhas with Different Vegetation Covers at the Red Sea Coast of Saudi Arabia

Healthy coastal sabkhas (sabkha is an Arabic term for a salt flat) offer plenty of ecosystem services including climate change mitigation. However, fewer research studies were conducted at compared to other marshes. This study was in total ten sabkha sites with different vegetation covers along the southern Red Sea coast Saudi Arabia. The main objectives model and predict distribution volumetric soil organic carbon (SOC) density (kg C/m3) cumulative SOC stocks C/m2) using three mathematic functions (allometric, exponential, sigmoid) based on sampled observed (C) data (total 125 cores = 1250 samples). Sigmoid function showed greatest fit predicting over profile depth mean Adj. R2 0.9978, 0.9611, 0.9623 cover >25–50, >50–75, >75–100%, respectively. For modeling stocks, both validation indices p t-test confirmed that exponential most appropriate be used stock among covers. Moreover, assessing topsoil concentration factors (TCFs) content impacted great extent by sabkhas. Sampling parameter interest estimate constrained time cost. Therefore, promising mapping regional global spatial scales.