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Typhoon Morakot had a serious impact on Taiwan, especially the uncommon type of landslide called large-scale landslide (LSL), not many in number but serious in effect, the origin of which the study induced. To establish a specific relationship between LSL and triggering rainfall for future applications of LSL early warning predictions, relevant cases from satellite imagery, along with field investigation data, major event reports, and seismic data from 2004 to 2016, were collected. All collected cases are distributed around the mountainous area in Taiwan, and a total of 107 cases which were mainly distributed in the southern part of the mountainous area were finally selected, including 28 occurrence-time-known cases and 79 occurrence-time-unknown cases. In addition, 149 potential areas identified by the Soil and Water Conservation Bureau (SWCB) were used for improving bounding estimates. Based on the concept of safety factor, two dimensionless quantities, rainfall/landslide depth (R/D) and friction angle/slope (ϕ/θ), were analyzed by linear regression. In addition, D was assumed to be nonlinearly dependent on R, θ, and ϕ, and the parameter uncertainties were evaluated by the resampling with bootstrap method. Based on the currently obtained data, there were 8% Type-I errors in the results of the linear regression analysis, and 1% Type-II errors in the results of the nonlinear regression analysis. Through the comparison of statistical indicators, the results of nonlinear regression analysis have a better correlation trend. Based on the needs of early warning operations, more conservative indicators can reduce the risks faced by management operations. Therefore, according to the results of this study, the lower boundary values from nonlinear analysis could be used as the LSL early warning management settings. Incorporated with real-time rainfall forecasts, the variation of statistical indicators will provide the trend information dynamically, and will help to increase the response time for relevant evacuation operations, that will be welcome for the further extended applications to guide the evacuation operations of early warning systems. [ABSTRACT FROM AUTHOR]

Aim: Rapid global warming is threatening global biodiversity, and it will likely lead to varying degrees of local adaptation, particularly amongst plant species. Besides, rising temperatures frequently result in upslope distribution shifts towards climatic optima (i.e. the escalator effect) within a limited dispersal space, such as in insular environments. Here, we integrated ecological and genetic approaches to investigate how climate change will impact the genetic compositions and spatial distributions of Taiwan's endemic maple Acer caudatifolium. Location: Taiwan. Methods: We estimate the distribution range shifts of A. caudatifolium under climate change through species distribution modelling (SDM). We also use 368 genotyped samples to infer dispersal and genetic hotspots and quantify the contributions of geography/environments to genetic variations. We further assess the potential risk to A. caudatifolium under different climate warming scenarios. Results: We detected three genetic diversity hotspots near mountainous glacial refugia and two dispersal hotspots in northern Taiwan and the central‐to‐southern Central Mountain Range. Overall range reductions and an altitudinal upslope shift were observed in SDM. Using both linear and nonlinear regression approaches, we found that genetic variation was significantly associated with geographic distance and elevation‐related climatic variables. The potential risk analysis revealed that the northernmost summit‐dwelling populations were the most vulnerable. Furthermore, the major risk factor differed amongst populations: for central populations, temperature and precipitation jointly determined the potential risk, whereas precipitation was the only risk factor for northern and southern populations. Main conclusions: This case study demonstrates how various climate factors, mountain height and the availability of corridors jointly determine the demographic fates and sustainability of island maples in the face of climate change. This study also provided estimates of the implications of global warming, which can be conducive to developing appropriate conservation strategies. [ABSTRACT FROM AUTHOR]

Objective: To determine the cellulose, hemicellulose, and lignin production in six Cenchrus purpureus cultivars, with and without fertilization, harvested every 21 days during 168 days. Design/methodology/approach: The evaluated cultivars were CT-115, elephant grass, king grass, Maralfalfa, Roxo, and Taiwan, with and without fertilization. The experimental design was a randomized complete block with a split-plot arrangement and four replications. The fertilization dose was 141-43-20 of NPK. Forage was harvested every 21 days during six months in the rainy season. We tested the samples for dry matter (DM), ash, NDF, ADF, hemicellulose, cellulose, and lignin. We performed a nonlinear regression analysis. We determined biomass production with the estimated values and the percentage of each component. The goodness-of-fit indicators were: R², the coefficient of determination (R), and the model selection criterion (MSC). The parameters and goodness-of-fit coefficients were analyzed in ANOVA with the SAS software using the GLM procedure. Means were compared with Tukey's test. Results: The Maralfalfa cultivar presented a higher cellulose production (3,786 kg ha-1), similar (p>0.05) to the elephant grass and Taiwan cultivars, which presented values of 3,451 kg ha-1 and 3,329 kg ha-1, respectively, and different (p<0.05) from CT-115 and king grass, which produced more than 1 t ha-1 of cellulose. Limitations/implications: Cellulose production increased by the effect of fertilization. Findings/conclusions: The fertilized Maralfalfa, elephant grass, and Taiwan cultivars produced more than 4,000 kg ha-1 of cellulose, 3,000 kg ha-1 of hemicellulose, and 1,000 kg ha-1 of lignin. [ABSTRACT FROM AUTHOR]

The characterization of spatially heterogeneous hydraulic conductivity (K) is important in groundwater resources management. We propose a Bayesian statistical method that integrates multiple secondary data (continuous and category data) with primary data (K) to improve regional K field characterization. Considering the disparity of the data scale, spatial scarcity of primary and secondary data, and need for regional‐scale site characterization, the aquifer thickness is used as the scale for data integration. We transform the high‐resolution secondary data to the scale of K and perform linear/nonlinear regression analyses for the transformed secondary data and primary data. A Bayesian approach using Metropolis‐within‐Gibbs sampling is developed for jointly integrating the primary and transformed secondary data without a limitation on the type of data attribute and the number of data set. A synthetic example is first presented to demonstrate the capability of the proposed method. Results show that the correlation strength, not the relation type, is the primary factor for improving the estimates. The Bayesian method is applied to Choushui River alluvial fan in Taiwan. Resistivity logs and a lithological description are first upscaled and then simultaneously integrated in the K estimation. Results indicate that the improvement of the K estimate obtained using resistivity data is higher in the proximal and mid fans but lower in the distal fan compared to that obtained using lithofacies data. Jointly integrating two‐attribute data outperforms using one or no secondary data set for K estimates. The proposed Bayesian integration method is thus versatile and suitable for large‐scale aquifer characterization. Key Points: We propose a Bayesian statistical method that jointly integrates multiattribute and multiscale data to improve hydraulic conductivity estimates for regional‐scale aquifer characterizationIntegrating two‐attribute data outperforms using one or no secondary data set for hydraulic conductivity estimatesSecondary data that are highly correlated with and have more quantity than the primary data can significantly improve estimation [ABSTRACT FROM AUTHOR]

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In the displacement-based seismic design and evaluation, the equivalent linearization method is one of the approximation methods to estimate the maximum displacement response of a single-degree-of-freedom (SDOF) system. Based on the past research conducted by Okano & Miyamoto and the seismic design code in Taiwan, this work proposes modified equivalent linearization method (MELM) of a SDOF system for a mid-rise reinforced concrete (RC) building structure. By considering a modification factor suggested by the equivalent linear method proposed by Okano and Miyamoto and performing the nonlinear regression analysis, the accuracy of the proposed method can be improved. A total of 348 ground motions recorded on the various earthquakes are used to calculate error statistics of MELM. Additionally, a closed-form formula for the constant-damage ductility demand spectrum (CDDDS) that corresponds to a specified reliability is suggested in this work. [ABSTRACT FROM AUTHOR]

We revisit the complete clinic visit records and environmental monitoring data at 50 townships and city districts of Taiwan. Extending the earlier analyses, here we consider a Bayesian analysis using Daubechies wavelet. Appropriate model selection is also considered using Bayesian model averaging. Temperature, dew point, and NO2and CO of the current day and the previous day are identified as the pollutants in different areas of the island following some spatial pattern. [ABSTRACT FROM AUTHOR]

The duration of strong shaking is particularly important for assessing building performance, potential landslides and liquefaction hazards. The results of this investigation can potentially help reduce related fatalities and economic losses. In this study, we analyzed the acceleration seismograms of the Taiwan strong motion network to characterize the strong shaking duration associated with earthquake sources, propagation paths and site effects. This study proposes a new definition for the strong shaking duration called 'effective shaking duration' (ESD), which considers the amplitude and radiation energy decays. We first consider the window of a time series during which the amplitude is ≥0.01 g, and we then defined the ESD as the length of the interval of the dissipated energy within 5-95 % of the total energy during this time frame. We calculated the strong shaking duration for 495 inter-plate events with magnitudes of M > 5.0 and focal depths <50 km in the Taiwan region from 1994 to 2012. Using a nonlinear regression procedure, we thus obtained an empirical equation for strong shaking durations. The equation is a function of earthquake magnitude, distance and site conditions, which are defined by the V30 value (the S-wave velocity structure of the top 30 m of the site). The results indicate that the shaking durations significantly increase with magnitude and also decrease with distance and V30. Compared with empirical equations from global datasets, our empirical equation is applicable to earthquakes in other regions and will produce smaller but more applicable duration values for smaller earthquakes. However, for larger events, our ESD values are comparable with those derived from other definitions (e.g., significant duration). Although the empirical relationship is mainly based on Taiwanese events, in view of the massive dataset, this empirical equation could provide important information to the global community regarding the ground shaking duration estimation in the ground motion prediction of future earthquakes. [ABSTRACT FROM AUTHOR]

We consider the complete clinic visit records and environmental monitoring data at 50 townships and city districts where ambient air monitoring stations of Taiwan Air Quality Monitoring Stations are located. A Bayesian analysis is carried out using regression spline model on principal components obtained from several pollutant covariables. The appropriate model is selected using Bayesian model averaging. A brief account of our results is provided for the elderly patients group. [ABSTRACT FROM AUTHOR]