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Shihmen Reservoir watershed is vital to the water supply in Northern Taiwan but the reservoir has been heavily impacted by sedimentation and soil erosion since 1964. The purpose of this study was to explore the capability of machine learning algorithms, such as decision tree and random forest, to predict soil erosion (sheet and rill erosion) depths in the Shihmen reservoir watershed. The accuracy of the models was evaluated using the RMSE (Root Mean Squared Error), MAE (Mean Absolute Error), and R2. Moreover, the models were verified against the multiple regression analysis, which is commonly used in statistical analysis. The predictors of these models were 14 environmental factors which influence soil erosion, whereas the target was 550 erosion pins installed at 55 locations (on 55 slopes) and monitored over a period of approximately three years. The data sets for the models were separated into 70% for the training data and 30% for the testing data, using the simple random sampling and stratified random sampling methods. The results show that the random forest algorithm performed the best of the three methods. Moreover, the stratified random sampling method had better results among the two sampling methods, as anticipated. The average error (RMSE relative to 1:1 line) of the stratified random sampling method of the random forest algorithm is 0.93 mm/yr in the training data and 1.75 mm/yr in the testing data, respectively. Finally, the random forest algorithm predicted that type of slope, slope direction, and sub-watershed are the three most important factors of the 14 environmental factors collected and used in this study for splits in the trees and thus they are the three most important factors affecting the depth of sheet and rill erosion in the Shihmen Reservoir watershed. The results of this study can be employed by decision-makers to improve soil conservation planning and watershed remediation.

Flooding in rainfed lowlands greatly impairs the mutualistic relationship between indigenous arbuscular mycorrhizal fungi (AMF) and rice. In flooded soils, root colonization by AMF is arrested, but some AMF genera, defined as the core AMF, remain present. However, the core AMF in rainfed lowlands and their symbiotic roles remain unknown. Here, we showed that Acaulospora fungi were the core AMF in rice seedling roots of the Sangyod Muang Phatthalung (SMP) landrace rice variety grown in non-flooded and flooded paddy soils. Subsequently, indigenous Acaulospora spores were propagated by trap cultures using maize as the host plants. Therefore, to clarify the roles of cultured Acaulospora spores in a symbiotic partnership, the model japonica rice variety Nipponbare was grown in sterile soil inoculated with Acaulospora spores, and recolonized with a native microbial filtrate from the organic rice paddy soil. Our data demonstrated that the inoculation of Acaulospora spores in well-drained soil under a nutrient-sufficient condition for six weeks enabled 70 percent of the rice roots to be colonized by the fungi, leading to higher phosphate (Pi) accumulation in the mycorrhizal roots. Unexpectedly, the growth of rice seedlings was significantly suppressed by inoculation while photosynthetic parameters such as fractions of incoming light energy and relative chlorophyll content were unaltered. In the soil, the Acaulospora fungi increased soil phosphorus (P) availability by enhancing the secretion of acid phosphatase in the mycorrhizal roots. The findings of this work elucidate the symbiotic roles of the dominant Acaulospora fungi from lowland rice paddies.

Rampant loss of biodiversity and ecosystem services undermines the resilience of food systems. Robust knowledge on impacts is the first step to taking action, but long-distance food supply chains and indirect effects on and around farms make understanding impacts a challenge. This paper looks at the tools available for businesses in the food industry, especially retailers, to monitor and assess the biodiversity performance of their products. It groups tools according to their general scope to evaluate what is monitored (processes on-site, pressures on landscapes, impacts on species), at what scale (specific products, company performance, country-wide consumption levels), and compared to which baseline (pristine nature, alternative scenarios, governance targets). Altogether we find major gaps in the criteria for biodiversity or the criteria is weak in certification and standards, business accounting and reporting systems, and scientific modelling and analysis (biodiversity footprints). At the same time, massive investments have been made to strengthen existing tools, develop new ones, increase uptake and improve their effectiveness. We argue that business can and must take a leading role toward mitigating biodiversity impacts in partnership with policy makers and customers. Zero-deforestation commitments, for example, will need to be upheld by supporting changed practices in consumption (e.g., choice editing) and combating degradation within agricultural systems will require a shift toward more regenerative forms of farming (e.g., with norms embedded in robust standard systems). Operational targets are integral to monitoring biodiversity performance across all scales.

The demand for rubber gloves has significantly increased in both medical and non-medical fields due to the spread of the coronavirus in 2019. It is challenging for rubber glove manufacturing industries to balance the production and demand for the product. Additionally, they must determine techniques to decrease the production costs so as to make rubber gloves more economical for consumers. Generally, natural gas, fossil fuels, and renewable energy sources are used worldwide in the manufacturing of rubber gloves. In addition, Thailand uses biomass energy for rubber glove production, but biomass utilization is not economically friendly. This study used different biomasses as fuel in rubber glove production so as to reduce production costs and make the process more environmentally friendly. Wood chip (WC), palm kernel shells (PKS), and oil palm mesocarp fiber (OPMF) biomass were collected from local regions and used in different ratios. The samples of WC, PKS, and OPMF were prepared in four different ratios, namely, 88:12:0, 85:15:0, 85:13:2, and 85:10:5, for efficient biomass utilization. The 85:10:5 (WC: PKS: OPMF) ratio was found to be the optimal ratio as the annual production costs of rubber gloves significantly decreased to USD 1.64 per 1000 units of gloves. Furthermore, this biomass ratio also showed the best boiler efficiency of 74.87%. Therefore, WC, PKS, and OPMF biomass are recommended as fuel for rubber glove industries to make sustainable and economical production processes.

Bats are important reservoir hosts of emerging viruses. Recent viral outbreaks and pandemics have resulted in an increased research focus on the genetic diversity, population structure, and distribution of bat species. Lyle’s flying fox (Pteropus lylei) is widely distributed throughout central Thailand, with most colonies congregating in temples within proximity to humans. A lack of knowledge regarding the genetic connectivity among different colonies hinders the investigation of zoonotic disease epidemiology and wildlife management. In this study, we hypothesized that genetic material may be exchanged between Lyle’s flying fox colonies that live in proximity. We assessed the mitochondrial displacement loop and cytochrome b nucleotide sequences of samples collected from 94 individuals from ten colonies across different roosting sites and detected limited genetic differentiation but increased nucleotide divergence within colonies. This suggests that genetic connectivity among Lyle’s flying fox colonies has experienced frequent and recent gene flow. These findings indicate that this species has maintained demographic equilibrium in a stable population, with a slight expansion event in certain populations. These data provide insights into the dynamics of bat populations, and the genetic knowledge gained presents opportunities for the improved monitoring of bat population structure.

Traditional diets are generally nutrient-rich and utilise locally available resources. Strategies to help conserve local food wisdom and increase its value could facilitate a reduction in the burden of all forms of malnutrition and achieve global goals. Our objectives were to: (1) investigate the variety of local foods and food preparation methods in Loei province, Thailand; (2) investigate ways of increasing the nutritional, social, and economic value of local food in this province; and (3) construct a local food database to catalogue and conserve the local food wisdom. Nine out of fourteen districts in Loei province were purposively selected. All were designated key sustainable tourist destinations and represented a range of terrains. There were 423 interview participants, representing all villages in one subdistrict of each of the nine selected districts. We also conducted nine focus group discussions with a total of 90 participants. Data were analysed and categorised, based on the content analysis technique, and we created an online database of the catalogued recipes. There were 240 dishes, placed into seven categories of recipe type. Many of the characteristics of the local dishes from Loei province today remain closely connected to the history of this part of Thailand. We identified that the value of local foods could be improved by investing in technology used for home preservation, actively engaging younger generations to improve the transfer of local food wisdom, investment in technology to utilise local biodegradable materials, and tourist activities based around local food heritage. Future work will involve further development of the local food database, and research to evaluate the application of the database. Moreover, this research can serve as a model for retaining and valuing local food wisdom elsewhere, to promote food security, combat malnutrition, and benefit the local economy.

In Asia and Africa the poor tend to live in marginal environments where droughts and floods are frequent. Global warming is expected to increase the frequency of these weather-induced perturbations of crop production. Drought tolerance (DT) has been one of the most difficult traits to improve in genetic crop improvement programs worldwide. Biotechnology provides breeders with a number of new tools that may help to develop more drought tolerant varieties such as marker assisted selection (MAS), molecular breeding (MB), and transgenic plants. This paper assesses some preliminary evidence on the potential impact of biotechnology using data from surveys of the initial DT cultivars developed through one of the main programs in Asia that has been funding DT rice breeding since 1998—The Rockefeller Foundation’s Resilient Crops for Water-Limited Environments program in China, India, and Thailand. Yield increases of DT rice varieties are 5 to 10 percent better than conventional varieties or currently grown commercial varieties than it has been in years. So far we only have experiment station evidence that DT varieties yielded better than conventional or improved varieties during moderate drought years (the one drought year during our study period in South India gave inconclusive results) and in severe drought both the DT and the conventional varieties were either not planted or, if planted, did not yield. We find that the governments could help overcome some of the constraints to the spread of DT cultivars by increasing government funding of DT research programs that take advantage of new biotech techniques and new knowledge from genomics. Secondly, public scientists can make breeding lines with DT traits and molecular markers more easily available to the private seed firms so that they can incorporate DT traits into their commercial hybrids particularly for poor areas. Third, governments can subsidize private sector production of DT seed or provide more government money for state extension services to produce DT varieties.