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 coastal sabkhas compared to other coastal marshes. This study was conducted in a total of ten coastal sabkha si...
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MDPI AG
2023-01-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/11/2/295 |
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| author | Ebrahem M. Eid Amr E. Keshta Sulaiman A. Alrumman Muhammad Arshad Kamal H. Shaltout Mohamed T. Ahmed Dhafer A. Al-Bakre Ahmed H. Alfarhan Damia Barcelo |
| author_facet | Ebrahem M. Eid Amr E. Keshta Sulaiman A. Alrumman Muhammad Arshad Kamal H. Shaltout Mohamed T. Ahmed Dhafer A. Al-Bakre Ahmed H. Alfarhan Damia Barcelo |
| author_sort | Ebrahem M. Eid |
| collection | DOAJ |
| description | 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 coastal sabkhas compared to other coastal marshes. This study was conducted in a total of ten coastal sabkha sites with different vegetation covers along the southern Red Sea coast of Saudi Arabia. The main objectives were to model and predict the distribution of volumetric soil organic carbon (SOC) density (kg C/m<sup>3</sup>) and cumulative SOC stocks (kg C/m<sup>2</sup>) using three different mathematic functions (allometric, exponential, and sigmoid) based on sampled and observed soil carbon (C) data (total of 125 soil cores = 1250 soil samples). Sigmoid function showed the greatest fit for predicting the distribution of volumetric SOC density over soil profile depth with mean Adj. <i>R<sup>2</sup></i> = 0.9978, 0.9611, and 0.9623 for vegetation cover of >25–50, >50–75, and >75–100%, respectively. For modeling the cumulative SOC stocks, both validation indices and <i>p</i> of the <i>t</i>-test confirmed that using the exponential function is the most appropriate to be used for predicting the SOC stock among different vegetation covers. Moreover, assessing the topsoil concentration factors (TCFs) showed that the distribution of the SOC content is impacted to a great extent by the vegetation cover at coastal sabkhas. Sampling the soil parameter of interest to estimate the SOC stocks is constrained by time and cost. Therefore, using the exponential function for predicting the distribution of cumulative SOC stocks at coastal sabkhas over soil profile depth is appropriate and promising for mapping SOC stocks at both regional and global spatial scales. |
| first_indexed | 2024-03-11T08:36:38Z |
| format | Article |
| id | doaj.art-8afda9c717c84b949c06fbeb35492455 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-11T08:36:38Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-8afda9c717c84b949c06fbeb354924552023-11-16T21:27:12ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-01-0111229510.3390/jmse11020295Modeling Soil Organic Carbon at Coastal Sabkhas with Different Vegetation Covers at the Red Sea Coast of Saudi ArabiaEbrahem M. Eid0Amr E. Keshta1Sulaiman A. Alrumman2Muhammad Arshad3Kamal H. Shaltout4Mohamed T. Ahmed5Dhafer A. Al-Bakre6Ahmed H. Alfarhan7Damia Barcelo8Department of Biology, College of Science, King Khalid University, Abha 61321, Saudi ArabiaBotany Department, College of Science, Tanta University, Tanta 31512, EgyptDepartment of Biology, College of Science, King Khalid University, Abha 61321, Saudi ArabiaDepartment of Chemical Engineering, College of Engineering, King Khalid University, Abha 61321, Saudi ArabiaBotany Department, College of Science, Tanta University, Tanta 31512, EgyptDepartment of Biology, College of Science, King Khalid University, Abha 61321, Saudi ArabiaBiology Department, College of Science, Tabuk University, Tabuk 47512, Saudi ArabiaBotany & Microbiology Department, College of Science, King Saud University, Riyadh 11451, Saudi ArabiaBotany & Microbiology Department, College of Science, King Saud University, Riyadh 11451, Saudi ArabiaHealthy 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 coastal sabkhas compared to other coastal marshes. This study was conducted in a total of ten coastal sabkha sites with different vegetation covers along the southern Red Sea coast of Saudi Arabia. The main objectives were to model and predict the distribution of volumetric soil organic carbon (SOC) density (kg C/m<sup>3</sup>) and cumulative SOC stocks (kg C/m<sup>2</sup>) using three different mathematic functions (allometric, exponential, and sigmoid) based on sampled and observed soil carbon (C) data (total of 125 soil cores = 1250 soil samples). Sigmoid function showed the greatest fit for predicting the distribution of volumetric SOC density over soil profile depth with mean Adj. <i>R<sup>2</sup></i> = 0.9978, 0.9611, and 0.9623 for vegetation cover of >25–50, >50–75, and >75–100%, respectively. For modeling the cumulative SOC stocks, both validation indices and <i>p</i> of the <i>t</i>-test confirmed that using the exponential function is the most appropriate to be used for predicting the SOC stock among different vegetation covers. Moreover, assessing the topsoil concentration factors (TCFs) showed that the distribution of the SOC content is impacted to a great extent by the vegetation cover at coastal sabkhas. Sampling the soil parameter of interest to estimate the SOC stocks is constrained by time and cost. Therefore, using the exponential function for predicting the distribution of cumulative SOC stocks at coastal sabkhas over soil profile depth is appropriate and promising for mapping SOC stocks at both regional and global spatial scales.https://www.mdpi.com/2077-1312/11/2/295blue carboncoastal marshesecosystem servicesvalidation indicesglobal emissionsshoreline protection |
| spellingShingle | Ebrahem M. Eid Amr E. Keshta Sulaiman A. Alrumman Muhammad Arshad Kamal H. Shaltout Mohamed T. Ahmed Dhafer A. Al-Bakre Ahmed H. Alfarhan Damia Barcelo Modeling Soil Organic Carbon at Coastal Sabkhas with Different Vegetation Covers at the Red Sea Coast of Saudi Arabia Journal of Marine Science and Engineering blue carbon coastal marshes ecosystem services validation indices global emissions shoreline protection |
| title | Modeling Soil Organic Carbon at Coastal Sabkhas with Different Vegetation Covers at the Red Sea Coast of Saudi Arabia |
| title_full | Modeling Soil Organic Carbon at Coastal Sabkhas with Different Vegetation Covers at the Red Sea Coast of Saudi Arabia |
| title_fullStr | Modeling Soil Organic Carbon at Coastal Sabkhas with Different Vegetation Covers at the Red Sea Coast of Saudi Arabia |
| title_full_unstemmed | Modeling Soil Organic Carbon at Coastal Sabkhas with Different Vegetation Covers at the Red Sea Coast of Saudi Arabia |
| title_short | Modeling Soil Organic Carbon at Coastal Sabkhas with Different Vegetation Covers at the Red Sea Coast of Saudi Arabia |
| title_sort | modeling soil organic carbon at coastal sabkhas with different vegetation covers at the red sea coast of saudi arabia |
| topic | blue carbon coastal marshes ecosystem services validation indices global emissions shoreline protection |
| url | https://www.mdpi.com/2077-1312/11/2/295 |
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