ABSTRACT
Accurate measuring, mapping, and monitoring of mangrove forests support the sustainable management of mangrove blue carbon in the Asia-Pacific. Remote sensing coupled with modeling can efficiently and accurately estimate mangrove blue carbon stocks at larger spatiotemporal extents. This study aimed to identify trends in remote sensing/modeling employed in estimating mangrove blue carbon, attributes/variations in mangrove carbon sequestration estimated using remote sensing, and to compile research gaps and opportunities, followed by providing recommendations for future research. Using a systematic literature review approach, we reviewed 105 remote sensing-based peer-reviewed articles (1990 - June 2023). Despite their high mangrove extent, there was a paucity of studies from Myanmar, Bangladesh, and Papua New Guinea. The most frequently used sensor was Sentinel-2 MSI, accounting for 14.5 % of overall usage, followed by Landsat 8 OLI (11.5 %), ALOS-2 PALSAR-2 (7.3 %), ALOS PALSAR (7.2 %), Landsat 7 ETM+ (6.1 %), Sentinel-1 (6.7 %), Landsat 5 TM (5.5 %), SRTM DEM (5.5 %), and UAV-LiDAR (4.8 %). Although parametric methods like linear regression remain the most widely used, machine learning regression models such as Random Forest (RF) and eXtreme Gradient Boost (XGB) have become popular in recent years and have shown good accuracy. Among a variety of attributes estimated, below-ground mangrove blue carbon and the valuation of carbon stock were less studied. The variation in carbon sequestration potential as a result of location, species, and forest type was widely studied. To improve the accuracy of blue carbon measurements, standardized/coordinated and innovative methodologies accompanied by credible information and actionable data should be carried out. Technical monitoring (every 2-5 years) enhanced by remote sensing can provide accurate and precise data for sustainable mangrove management while opening ventures for voluntary carbon markets to benefit the environment and local livelihood in developing countries in the Asia-Pacific region.
ABSTRACT
Humic substances (HS) and humic acids (HA) are proven to enhance nutrient uptake and growth in plants. Foliar application of urea combined with HS and HA offers an alternative strategy to increase nitrogen use efficiency (NUE). The objective of this study was to understand the effects of foliar application of HA and HS along with urea on NUE and response of different biometric, biochemical and physiological traits of sugarcane with respect to cultivar, mode of foliar application, geographic location and intervals of foliar application. To study this, two different independent Experiments were conducted in green house facilities at two different agro-climatic zones (USA and Brazil) using two different predominant varieties, modes and intervals of foliar applications. The three different foliar applications used in this study were (1) urea (U), (2) mixture of urea and HS (U+HS) and (3) HA (U+HA). In both Experiments, 15N (nitrogen isotope) recovery or NUE was higher in U+HS followed by U+HA. However, magnitude of NUE changed according to the differences in two Experiments. Results showed that foliar application of U+HS and U+HA was rapidly absorbed and stored in the form of protein and starch. Also induced changes in photosynthesis, intrinsic water use efficiency, protein, total soluble sugars and starch signifying a synergistic effect of U+HS and U+HA on carbon and nitrogen metabolism. These results showed promising use of HS and HA with urea to improve NUE in sugarcane compared to using the urea alone. Simultaneously, mode, quantity, and interval of foliar application should be standardized based on the geographic locations and varieties to optimize the NUE.
