The aim of this study was to conduct the first comprehensive evaluation of carbon stock in the sediments of Avicennia marina (black mangrove) and Rhizophora mucronata (red mangrove) along the coastline of an arid region (Farasan Islands, Saudi Arabia). Such information is necessary for the development of any management plan for the mangrove ecosystems along the Saudi Red Sea islands and provide a rationale for the restoration of mangrove forests in Saudi Arabia. A. marina and R. mucronata locations showed significant (P < 0.001) differences in sediment bulk density (SBD) and sediment organic carbon (SOC) concentration with higher mean values for both in the sediments of A. marina. Considering the whole depth of sediment sampled (0-50 cm), the highest value of SOC stock (12.3 kg C m−2) was recorded at A. marina locations and the lowest (10.8 kg C m−2) at R. mucronata locations. Thus, the SOC stock of A. marina was greater than that of R. mucronata by 114.3%. Consequently, considering the rate of carbon sequestration and the area of mangrove forests (216.4 ha), the total carbon sequestration potential of mangroves in the Farasan Islands ranged between 10.3 Mg C yr−1 and 11.8 Mg C yr−1 for R. mucronata and A. marina locations, respectively. Thus, it is necessary to protect and restore these ecosystems for the sequestration of carbon and for their other valuable ecosystem services.
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Satellite remote sensing and geographical information system (GIS) have been used successfully to monitor and assess the land use and land cover (LULC) dynamics and their impacts on people and the environment. LULC change detection is essential for studying spatiotemporal conditions and for proposing better future planning and development options. The current research analyzes the detection of spatiotemporal variability of spate irrigation systems using remote sensing and GIS in the Khirthar National Range, Sindh Province of Pakistan. We use Landsat images to study the dynamics of LULC using ArcGIS software and categorize fve major LULC types. We obtain secondary data related to precipitation and crop yield from the provincial department of revenue. The maximum likelihood supervised classifcation (MLSC) procedure, augmented with secondary data, reveals a signifcant increase of 86.25% in settlements, 83.85% in spate irrigation systems, and 65% in vegetation, and a substantial negative trend of 39.50% in water bodies and 20% in barren land during the period from 2013 to 2018. Our study highlights an increase in settlements due to the infow of local population for better means of living and an increase in spate irrigation systems, which indicates the water conservation practices for land cultivation and human purpose lead to the shrinkage of water bodies. The confusion matrix using Google Earth data to rectify modeled (classifed) data, which showed an overall accuracy of 82.8%–92%, and the Kappa coefcient estimated at 0.80–0.90 shows the satisfactory results of the LULC classifcation. The study suggests the need to increase water storage potential with the appropriate water conservation techniques to enhance the spate irrigation system in the hilly tracts for sustainable develop‑ ments, which mitigates drought impact and reduces migration rate by providing more opportunities through agricultural activities in the study area.
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