RESUMEN
The Yuanjiang dry-hot valley features hot and dry climate, low vegetation and soil degradation. It had lush vegetation in the past, but has become degraded in recent decades. Understanding the interrelationship between species and the habitat is necessary to explain this change. In this study, a link between fern and fern allies - a group that is hypersensitive to environmental factors and their circumstances is constructed. Intensive transects and plots were designed to be proxies for extant fern and fern allies, and their habitats. Fifty years of meteorological records of precipitation and temperature along altitude and river running direction (latitudinal) were employed. Alpha and beta diversity are used to access diversity. Species_estimated, Singletons, Uniques, ACE, ICE, and Chao2, which associate to abundance and rarity, are subscribed to the correlation between fern and fern allies, and their ecosystem. Eight species, Selaginella pseudopaleifera, Aleuritopteris squamosa, Adiantum malesianum, Pteris vittata, Davallia trichomanoides, Sinephropteris delavayi, Selaginella jugorum, and Lygodium japonicum are used as indicators of a typical xeric and sun-drying habitat. The results indicate (1) accompanied by dramatically shrinking habitats, fern and fern allies are in very low diversity and abundance, whereas the rarity is relatively high; (2) for fern and fern allies, environmental factors are positive when altitude goes up; and (3) eight indicator species are latitudinally correlated with fern and fern allies along the river running direction.
RESUMEN
This study evaluates the performance of 13 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for simulating the temperature over Thailand during 2000-2014, for land-only, sea-only, and both land and sea. Both observation and reanalysis datasets are employed to compare with the GCMs, evaluated by five performance metrics including mean annual temperature, mean bias errors, mean seasonal cycle amplitude, correlation coefficient, and root mean square error. GCMs are ranked by relative error of all performance metrics. Results show that the temperatures from most GCM simulations are below the mean reference data (i.e., average of ground-based and reanalysis datasets), with north to south gradient in the range from 19 °C to 33 °C. In addition, all the GCM biases range from -0.07 °C to 2.78 °C and show severity of the temperature changes in spatial pattern ranging from -5 °C to 15 °C. The correlations of most GCMs range from 0.70 to 0.95, while the magnitudes of error are less than 2 °C. Study cases point out that the 13-MODEL ENSEMBLE, CESM2, and CNRM-CM6-1 perform better than the other models in simulating the temperature over Thailand for land-only and sea-only, and both land and sea cases, respectively, while MIROC6 performs the worst for all study cases in this study area. From the designed methodology, CNRM-CM6-1 has the best performance and is the most appropriate choice to simulate the temperature for the overall Thailand area.
RESUMEN
Biodiesel production from Jatropha curcas Linnaeus (JCL) has been considered for partial substitution of diesel fuel for transportation in Thailand. The aim of this study is to investigate the energy consumption for long-term investment (20 years) of Jatropha Methyl Ester (JME) production in Thailand using a life cycle approach. Apart from the average result, two scenarios--best and worst case--are set up to illustrate the range of results due to the variety of management practices. The main contributors to the energy use are JCL cultivation, transesterification, and transportation process. The net energy gain (NEG) and net energy ratio (NER) of biodiesel and coproducts from the life cycle of JCL are 4720 GJ/ha and 6.03, respectively. Even if only biodiesel is considered without coproducts, the NER is 1.42, still higher than 1. The study will support decision makers in the energy policy sector to make informed decisions vis-a-vis promotion of JCL plantations for biodiesel.