Soil organic carbon (SOC) improvement has become a sustainable strategy for enhancing soil resilience and reducing greenhouse gas (GHG) emissions in the rice cropping system. For tropical soils, the SOC accumulation was limited by the unfavorable environment, likely the sandy soil area in Northeast (NE) Thailand. This review aims to quantify and understand SOC in sandy paddy fields of NE Thailand. The existing research gap for alternative management practices is also highlighted to increase ecological and agronomic values. We review previous studies to determine the factors affecting SOC dynamics in sandy paddy fields, in order to enhance SOC and sustain rice yields. High sand content, up to 50% sand, was found in 70.7% of the observations. SOC content has ranged from 0.34 to 31.2 g kg−1 for the past four decades in paddy rice soil of NE Thailand. The conventional and alternative practice managements were chosen based on either increasing rice crop yield or improving soil fertility. The lack of irrigation water during the mild dry season would physically affect carbon sequestration as the soil erosion accelerates. Meanwhile, soil chemical and microbial activity, which directly affect SOC accumulation, would be influenced by nutrient and crop residue management, including chemical fertilizer, manure and green manure, unburned rice straw, and biochar application. Increasing SOC content by 1 g kg−1 can increase rice yield by 302 kg ha−1. The predicted carbon saturation varied tremendously, from 4.1% to 140.6% (52% in average), indicating that the sandy soil in this region has the potential for greater SOC sequestration. Our review also suggests that broadening the research of rice production influenced by sandy soil is still required to implement adaptive management for sustainable agriculture and future food security.
ContextLarge forest-dwelling mammals are highly sensitive to habitat structure. Thus, understanding the responses of reintroduced banteng (Bos javanicus d’Alton 1823) to their habitat is important for ensuring the sustainability of a reintroduction program. AimsThe aim of the present study was to evaluate the habitat preferences of banteng after reintroduction into the Salakphra Wildlife Sanctuary in Thailand on the basis of fieldwork conducted between January 2015 and November 2017. MethodsSeven banteng individuals bred at the Khao Nampu Nature and Wildlife Education Center were systematically reintroduced into the Salakphra Wildlife Sanctuary in 2015 (four individuals) and 2016 (three individuals). The banteng individuals were tracked via radio-collars and camera-traps. The maximum-entropy method (MaxEnt) and multiple logistic regressions (MLR) were used to identify habitat preferences. Kernel-density estimates (KDE) and a minimum convex polygon (MCP) were used to estimate the area of the habitat used. Key resultsIn total, 407 radio-signal locations showed that the MaxEnt habitat-preference models classified the banteng as associated with distance from villages and salt licks (regularised training gain of >1.0). Multiple logistic regressions form 32 camera-trap locations classified the banteng as associated with low elevations far from villages, guard stations and roads in a flat area (no aspect). The two methods for estimating habitat use provided similar results and showed that the reintroduced banteng used a wider range of habitat in the dry than in the wet season. ConclusionsThe results from the present study suggest that the reintroduced banteng individuals prefer low elevations and flat areas without human activity. ImplicationsThese findings are important for possible translocations elsewhere.
The first case of COVID-19 infection was confirmed in Thailand on January 13, 2020; since then, work from home and lockdown measures have slowed the spread of COVID-19. A more stringent, curfew regulation was imposed on April 3, 2020. Under these measures, the activities of businesses, transportation, and industrial sectors were reduced or temporally closed. Therefore, this study aims to investigate the changes in the nitrogen dioxide (NO₂) level in the whole of Thailand and specifically in the Bangkok metropolitan area because NO 2 in the troposphere is an important indicator of air pollution. The concentrations of tropospheric NO 2 were extracted from the Sentinel-5P satellite data. The Google Earth Engine JavaScript API was used
Soil microorganisms play an important role in determining nutrient cycling. The integration of fish into rice fields can influence the diversity and structural composition of soil microbial communities. However, regarding the rice–fish co-culture (RF) farming system in Thailand, the study of the diversity and composition of soil microbes is still limited. Here, we aim to compare the microbial diversity, community composition, and functional structure of the bacterial communities between RF and rice monoculture (MC) farming systems and identify the environmental factors shaping bacterial community composition. Bacterial taxonomy was observed using 16s rRNA gene amplicon sequencing, and the functional structures of the bacterial communities were predicted based on their taxonomy and sequences. The results showed that soil organic carbon, total nitrogen (TN), organic matter, available phosphorous, and clay content were significantly higher in RF than in MC. The most dominant taxa across both paddy rice fields belonged to Actinobacteria, Chloroflexi, Proteobacteria, Acidobacteria, and Planctomycetes. The taxa Nitrosporae, Rokubacteria, GAL15, and Elusimicrobia were significantly different between both rice fields. At the genus level, Bacillus, Anaeromyxobacter, and HSB OF53-F07 were the predominant genera in both rice fields. The most abundant genus in MC was Anaeromyxobacter, whereas RF belonged to Bacillus. The community composition in MC was positively correlated with magnesium and sand content, while in RF was positively correlated with pH, TN, and clay content. Nitrogen fixation, aromatic compound degradation, and hydrocarbon degradation were more abundant in RF, while cellulolysis, nitrification, ureolysis, and phototrophy functional groups were more abundant in MC. The enzymes involved in paddy soil ecosystems included phosphatase, β-glucosidase, cellulase, and urease. These results provide novel insights into integrated fish in the paddy field as an efficient agricultural development strategy for enhancing soil microorganisms that increase soil fertility.
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