Modeling the service-route-based crash frequency by a spatiotemporal-random-effect zero-inflated negative binomial model: An empirical analysis for bus-involved crashes

Previous studies related to bus crash frequencies modeling are limited and the statistical models are usually developed at the road segment or zonal level. This study focuses on modeling crash frequencies specifically at the bus-service-route level, which is useful and important to policymakers and bus operation companies toward the improvement of the safety level of bus networks, especially for developing countries where buses are still a major mode of urban travels. Using the observed data adopted from one of the bus operating companies in Beijing, China, we proposed a spatiotemporal-random-effect zero-inflated negative binomial (spatiotemporal ZINB) model to investigate bus crash occurrence and identity key influential factors at the bus-service-route level. The model was motivated to accommodate the special statistical characteristics of the excessive zeros and, more importantly, the potential spatiotemporal correlations of the data. Three degenerated versions of this model were also developed for comparison purposes. Results indicate that the proposed spatiotemporal ZINB model is statistically superior to the others according to a comprehensive judgment based on the EAIC, EBIC, and RMSE criteria. The estimated coefficients reveal the impacts of related factors on the likelihood of bus-involved crashes from bus operation factors including total passengers, number of drivers, and proportion of male drivers as well as planning factors including route length and stop density. On the other hand, the standard deviations of the introduced structured and unstructured spatiotemporal random-effects are statistically significant indicating that the observations are correlated within each route, between neighbor routes and across years. Corresponding policy and practical implications are provided for bus operating companies and planning departments toward the improvement of bus safety

New Insights into Different Reproductive Effort and Sexual Recruitment Contribution between Two Geographic Zostera marina L. Populations in Temperate China

Seagrasses are important components of global coastal ecosystems, and the eelgrass Zostera marina L. is widely distributed along the Atlantic and Pacific coasts in the temperate northern hemisphere, but limited datum related to the contribution of sexual reproduction to population recruitment have been reported. This study aimed to understand eelgrass sexual reproduction and population recruitment in Swan Lake (SLL), and Huiquan Bay (HQB) was included for comparison. Random sampling, permanent quadrats or cores and laboratory seed germination-based experimental methods were employed. The flowering, seed production, seed banks, seed germination, seedling survival, and seedling growth of eelgrass were investigated from July 2014 to December 2015 to evaluate the contribution of sexual reproduction to population recruitment. Results indicated a dominant role of asexual reproduction in HQB, while sexual reproduction played a relatively important role in SLL. The highest flowering shoot density in SLL was 517.27 ± 504.29 shoots m−2 (June) and represented 53.34% of the total shoots at the center site. The potential seed output per reproductive shoot and per unit area in SLL were 103.67 ± 37.95 seeds shoot−1 and 53,623.66 ± 19,628.11 seeds m−2, respectively. The maximum seed bank density in SLL was 552.21 ± 204.94 seeds m−2 (October). Seed germination mainly occurred from the middle of March to the end of May, and the highest seedling density was 296.88 ± 274.27 seedlings m−2 in April. The recruitment from seedlings accounted for 41.36% of the Z. marina population recruitment at the center site, while the sexual recruitment contribution at the patch site (50.52%) was greater than that at the center site. Seeds in SLL were acclimated to spring germination, while in HQB, they were acclimated to autumn germination (early October–late November). Seed bank density in HQB was very low, with a value of 254.35 ± 613.34 seeds m−2 (early October). However, seeds in HQB were significantly larger and heavier than those in SLL (size: P = 0.004; weight: P < 0.001). The recruitment from seedlings accounted for as low as 2.53% of the Z. marina population recruitment in HQB. Our laboratory seed germination experiment, which was conducted in autumn, showed that the seed germination percent in HQB was significantly greater than in SLL at optimal germination temperatures (10 and 15°C; P < 0.001). A laboratory seed germination test at suitable temperature may be a potential novel approach to identify the ecological differences among different geographic populations. It is suggested that the Z. marina population recruitment may have different strategies and adapt to specific local conditions, such as in SLL and HQB, and the temperature regime may control morphological and phonological variations