http://scholars.ntou.edu.tw/handle/123456789/20313 Wed, 08 Apr 2026 12:16:55 GMT 2026-04-08T12:16:55Z http://scholars.ntou.edu.tw:80/retrieve/5169/13_CLIMATE_ACTION.png http://scholars.ntou.edu.tw/handle/123456789/20313 http://scholars.ntou.edu.tw/handle/123456789/22077 標題: A climate-driven model for predicting the level of Vibrio parahaemolyticus in oysters harvested from Taiwanese farms using elastic net regularized regression 作者: Ndraha, Nodali; Hsiao, Hsin-, I 摘要: This study aimed at, and developed, a climate-driven model for predicting the abundance of V. parahaemolyticus in oysters based on the local climatological and environmental conditions in Taiwan. The predictive model was constructed using the elastic net machine learning method, and the most influential predictors were evaluated using a permutation-based approach. The abundance of V. parahaemolyticus in oysters in different seasons, time horizons, and representative concentration pathways (RCPs) were predicted using the Elastic-net machine learning model. The results showed: (1) the variation in wind speed or gust wind speed, sea surface temperature, precipitation, and pH influenced the prediction of V. parahaemolyticus concentration in oysters, and (2) the level of V. parahaemolyticus in oysters in Taiwan was projected to be increased by 40-67% in the near future (2046-2065) and by 39-86% by the end of twentieth-century (2081-2100) if the global temperature continues to increase due to climate change. The findings in this study may be used as inputs for quantifying the V. parahaemolyticus infection risk from eating this seafood in Taiwan. Mon, 01 Aug 2022 00:00:00 GMT http://scholars.ntou.edu.tw/handle/123456789/22077 2022-08-01T00:00:00Z http://scholars.ntou.edu.tw/handle/123456789/22053 標題: Using Modified Harmonic Analysis to Estimate the Trend of Sea-Level Rise around Taiwan 作者: Hsieh, Chih-Min; Chou, Dean; Hsu, Tai-Wen 摘要: Sea-level rise (SLR) has become an essential global environmental problem and great importance is attached by all sectors of society. This study aims to estimate the trends of SLR from the tide-gauge measurements located in different sites of Taiwan. Different methods of analysis, such as the linear-regression method (LRM), Hilbert-Huang transform (HHT), and modified harmonic analysis (MHA) are used to estimate SLR and their applicability is discussed. Limitations of these methods are also compared and discussed via the analyzed results. MHA is the focus of the present paper. It has the advantage of representing tidal harmonic motion as well as the long-term trend of SLR more accurately, even in the condition of data loss caused by mechanical failures or anomaly. The analyzing results reveal that MHA is more applicable for estimating SLR than the above traditional methods. The most important analyzed results indicate that the recent 20-year SLR rate is within the range of -0.9 mm/yr and 18.1 mm/yr, using the tidal database observed at 17 stations along the Taiwanese coast. SLR is also compared with analyzed results from different databases or scenarios. The value of SLR is modified by adding the vertical-change rate of the benchmark. It is interesting to note that correction tends to reduce the bias of the variation trend of SLR. Wed, 01 Jun 2022 00:00:00 GMT http://scholars.ntou.edu.tw/handle/123456789/22053 2022-06-01T00:00:00Z http://scholars.ntou.edu.tw/handle/123456789/22045 標題: Variability in the Spatiotemporal Distribution Patterns of Greater Amberjack in Response to Environmental Factors in the Taiwan Strait Using Remote Sensing Data 作者: Mammel, Mubarak; Naimullah, Muhamad; Vayghan, Ali Haghi; Hsu, Jhen; Lee, Ming-An; Wu, Jun-Hong; Wang, Yi-Chen; Lan, Kuo-Wei 摘要: The environmental characteristics of the Taiwan Strait (TS) have been linked to variations in the abundance and distribution of greater amberjack (Seriola dumerili) populations. Greater amberjack is a commercially and ecologically valuable species in ecosystems, and its spatial distribution patterns are pivotal to fisheries management and conservation. However, the relationship between the catch rates of S. dumerili and the environmental changes and their impact on fish communities remains undetermined in the TS. The goal of this study was to determine the spatiotemporal distribution pattern of S. dumerili with environmental characteristics in the TS from south to north (20 degrees N-29 degrees N and 115 degrees E-127 degrees E), applying generalized additive models (GAMs) and spatiotemporal fisheries data from logbooks and voyage data recorders from Taiwanese fishing vessels (2014-2017) as well as satellite-derived remote sensing environmental data. We used the generalized linear model (GLM) and GAM to analyze the effect of environmental factors and catch rates. The predictive performance of the two statistical models was quantitatively assessed by using the root mean square difference. Results reveal that the GAM outperforms the GLM model in terms of the functional relationship of the GAM for generating a reliable predictive tool. The model selection process was based on the significance of model terms, increase in deviance explained, decrease in residual factor, and reduction in Akaike's information criterion. We then developed a species distribution model based on the best GAMs. The deviance explained indicated that sea surface temperature, linked to high catch rates, was the key factor influencing S. dumerili distributions, whereas mixed layer depth was the least relevant factor. The model predicted a relatively high S. dumerili catch rate in the northwestern region of the TS in summer, with the area extending to the East China Sea. The target species is strongly influenced by biophysical environmental conditions, and potential fishing areas are located throughout the waters of the TS. The findings of this study showed how S. dumerili populations respond to environmental variables and predict species distributions. Data on the habitat preferences and distribution patterns of S. dumerili are essential for understanding the environmental conditions of the TS, which can inform future priorities for conservation planning and management. Wed, 01 Jun 2022 00:00:00 GMT http://scholars.ntou.edu.tw/handle/123456789/22045 2022-06-01T00:00:00Z http://scholars.ntou.edu.tw/handle/123456789/22043 標題: On the Reconstruction of Missing Sea Surface Temperature Data from Himawari-8 in Adjacent Waters of Taiwan Using DINEOF Conducted with 25-h Data 作者: Yang, Yi-Chung; Lu, Ching-Yuan; Huang, Shih-Jen; Yang, Thwong-Zong; Chang, Yu-Cheng; Ho, Chung-Ru 摘要: Satellite remote sensing sea surface temperature (SST) data are lost due to cloud cover. Missing data often cause inconvenience in subsequent applications and thus need to be reconstructed. In this study, the Data Interpolating Empirical Orthogonal Function (DINEOF) method was used to reconstruct the hourly SST data missing from the Himawari-8 satellite in the waters near Taiwan. The SST characteristics in the waters around Taiwan are quite complex, with high SST at Kuroshio in the east of Taiwan and great variation in the SST west of Taiwan due to the influence of tides. Therefore, the analysis with DINEOF was conducted using 25-h data to match the tidal cycle. The influence of SST characteristics on the accuracy of SST reconstruction is also discussed. The results show that in the western sea area where the variation of SST is large, the average root-mean-square error of SST between the original SST and the reconstructed SST is the lowest and the average coefficient of determination is the highest. The accuracy of the reconstructed SST is positively correlated with the SST variation. Furthermore, the statistical results also show that the DINEOF method can effectively reconstruct the SST regardless of the missing data rate. Wed, 01 Jun 2022 00:00:00 GMT http://scholars.ntou.edu.tw/handle/123456789/22043 2022-06-01T00:00:00Z