Biodiversity in Beijing Oriental Outlook Issue 11,2025 Unique geographical and climatic conditions have endowed Beijing with distinctive biodiversity.As one of the metropolises with the richest biodiversity in the wor...Biodiversity in Beijing Oriental Outlook Issue 11,2025 Unique geographical and climatic conditions have endowed Beijing with distinctive biodiversity.As one of the metropolises with the richest biodiversity in the world,it earned the title of Biodiversity Charming City at the COP16 in November 2024.Beijing is now aiming to establish itself as a world-class capital of biodiversity,to enrich its garden city image.展开更多
This study examined gender differences in modal choice among residents of coastal communities of Yenagoa metropolis in Bayelsa State, Nigeria. The Four-Step model of transportation planning and modal choice provided t...This study examined gender differences in modal choice among residents of coastal communities of Yenagoa metropolis in Bayelsa State, Nigeria. The Four-Step model of transportation planning and modal choice provided the theoretical basis for this study. A survey research design involving a stratified sampling technique was adopted. The descriptives on transport modes, amount and time spent revealed that 10 (76.9%) males and 3 (23.1%) females preferred bicycle as means of transportation, 7 (58.3%) males and 5 (41.7%) females preferred motorcycle, while a significant proportion 90 (53.9%) males and 77 (46.1%) females preferred tricycle, 80 (63.0%) males and 47 (37.0%) females preferred cars/taxis, and 12 (46.2%) males and 14 (53.8%) females preferred mass transit bus. However, 14 (46.7%) males and 16 (53.3%) females in marshy terrain and coastal locations preferred canoes and boats. The result of the logistic regression model revealed that gender modal preference is more likely to be influenced by mode of transportation with a beta weight of 1.140, safety considerations 1.139, ownership of transport 1.135 and distance to place of work 1.073. Hence, this study recommends that a combination of these factors should be incorporated into transport planning to achieve effective transport planning and sustainable development in the Yenagoa metropolis.展开更多
Safe and just operating spaces(SJOS)are influenced by complex cross-scale interactions and cascading effects spanning global,regional,and local landscape scales.However,existing SJOS research has often focused on sing...Safe and just operating spaces(SJOS)are influenced by complex cross-scale interactions and cascading effects spanning global,regional,and local landscape scales.However,existing SJOS research has often focused on single-scale assessments,overlooking the impacts of multiscale interactions and within-region heterogeneity on urban SJOS.To address this gap,we developed a cross-scale framework for assessing urban SJOS,explicitly incorporating top-down influences from upper-level constraints and bottom-up effects from lower-level heterogeneity.This approach was applied to China's five major metropolises to examine the states and cross-scale dynamics influencing urban SJOS between 1990 and 2020.Our findings reveal that the SJOS of China's metropolises were primarily influenced by factors at national and local landscape scales,with weaker influences from the global and continental scales.A persistent trade-off between social justice and environmental safety was identified across spatiotemporal scales.For instance,Chongqing in southwestern China lagged behind the eastern four metropolises in social performance but exhibited stronger environmental safety due to its extensive natural landscapes,which mitigated the anthropogenic impacts of urban centers.Regional issues,such as the overshoot of PM_(2.5)and ecological footprints(EF),were primarily driven by the bottom-up accumulation of localized pressures,while the overshoot of CO_(2)was attributed to national policy constraints and the universal exceedance of safe thresholds across scales.Addressing urban sustainability requires avoiding adverse cascading effects from other levels by emphasizing landscape heterogeneity within metropolises and fostering coordinated collaboration across scales,particularly at the regional landscape and national levels.展开更多
基于贝叶斯理论,以马尔可夫链蒙特卡罗方法(Markov chain Monte Carlo Simulation,MCMC法)的自适应差分演化Metropolis算法为参数后验分布抽样计算方法,建立利用时变测试数据的参数随机反分析及模型预测方法。以香港东涌某天然坡地降雨...基于贝叶斯理论,以马尔可夫链蒙特卡罗方法(Markov chain Monte Carlo Simulation,MCMC法)的自适应差分演化Metropolis算法为参数后验分布抽样计算方法,建立利用时变测试数据的参数随机反分析及模型预测方法。以香港东涌某天然坡地降雨入渗测试为算例,采用自适应差分演化Metropolis算法对时变降雨条件下非饱和土一维渗流模型参数进行随机反分析,研究参数后验分布的统计特性,并分别对校准期和验证期内模型预测孔压和实测值进行比较。研究结果表明,DREAM算法得到的各随机变量后验分布标准差较先验分布均显著减小;经过实测孔压数据的校准,模型计算精度很高,校准期内95%总置信区间的覆盖率达到0.964;验证期第2～4个阶段95%总置信区间的覆盖率分别为0.52、0.79和0.79,模型预测结果与实测值吻合程度较高。展开更多
文摘Biodiversity in Beijing Oriental Outlook Issue 11,2025 Unique geographical and climatic conditions have endowed Beijing with distinctive biodiversity.As one of the metropolises with the richest biodiversity in the world,it earned the title of Biodiversity Charming City at the COP16 in November 2024.Beijing is now aiming to establish itself as a world-class capital of biodiversity,to enrich its garden city image.
文摘This study examined gender differences in modal choice among residents of coastal communities of Yenagoa metropolis in Bayelsa State, Nigeria. The Four-Step model of transportation planning and modal choice provided the theoretical basis for this study. A survey research design involving a stratified sampling technique was adopted. The descriptives on transport modes, amount and time spent revealed that 10 (76.9%) males and 3 (23.1%) females preferred bicycle as means of transportation, 7 (58.3%) males and 5 (41.7%) females preferred motorcycle, while a significant proportion 90 (53.9%) males and 77 (46.1%) females preferred tricycle, 80 (63.0%) males and 47 (37.0%) females preferred cars/taxis, and 12 (46.2%) males and 14 (53.8%) females preferred mass transit bus. However, 14 (46.7%) males and 16 (53.3%) females in marshy terrain and coastal locations preferred canoes and boats. The result of the logistic regression model revealed that gender modal preference is more likely to be influenced by mode of transportation with a beta weight of 1.140, safety considerations 1.139, ownership of transport 1.135 and distance to place of work 1.073. Hence, this study recommends that a combination of these factors should be incorporated into transport planning to achieve effective transport planning and sustainable development in the Yenagoa metropolis.
基金supported by the National Natural Science Foundation of China(Grant No.42101296)the Natural Science Foundation of Chongqing(Grant No.CSTB2023NSCQ-MSX0041)Chongqing Municipal Training Program of Innovation and Entrepreneurship Project(Grants No.S202410635155 and X202410635116)。
文摘Safe and just operating spaces(SJOS)are influenced by complex cross-scale interactions and cascading effects spanning global,regional,and local landscape scales.However,existing SJOS research has often focused on single-scale assessments,overlooking the impacts of multiscale interactions and within-region heterogeneity on urban SJOS.To address this gap,we developed a cross-scale framework for assessing urban SJOS,explicitly incorporating top-down influences from upper-level constraints and bottom-up effects from lower-level heterogeneity.This approach was applied to China's five major metropolises to examine the states and cross-scale dynamics influencing urban SJOS between 1990 and 2020.Our findings reveal that the SJOS of China's metropolises were primarily influenced by factors at national and local landscape scales,with weaker influences from the global and continental scales.A persistent trade-off between social justice and environmental safety was identified across spatiotemporal scales.For instance,Chongqing in southwestern China lagged behind the eastern four metropolises in social performance but exhibited stronger environmental safety due to its extensive natural landscapes,which mitigated the anthropogenic impacts of urban centers.Regional issues,such as the overshoot of PM_(2.5)and ecological footprints(EF),were primarily driven by the bottom-up accumulation of localized pressures,while the overshoot of CO_(2)was attributed to national policy constraints and the universal exceedance of safe thresholds across scales.Addressing urban sustainability requires avoiding adverse cascading effects from other levels by emphasizing landscape heterogeneity within metropolises and fostering coordinated collaboration across scales,particularly at the regional landscape and national levels.
文摘基于贝叶斯理论,以马尔可夫链蒙特卡罗方法(Markov chain Monte Carlo Simulation,MCMC法)的自适应差分演化Metropolis算法为参数后验分布抽样计算方法,建立利用时变测试数据的参数随机反分析及模型预测方法。以香港东涌某天然坡地降雨入渗测试为算例,采用自适应差分演化Metropolis算法对时变降雨条件下非饱和土一维渗流模型参数进行随机反分析,研究参数后验分布的统计特性,并分别对校准期和验证期内模型预测孔压和实测值进行比较。研究结果表明,DREAM算法得到的各随机变量后验分布标准差较先验分布均显著减小;经过实测孔压数据的校准,模型计算精度很高,校准期内95%总置信区间的覆盖率达到0.964;验证期第2～4个阶段95%总置信区间的覆盖率分别为0.52、0.79和0.79,模型预测结果与实测值吻合程度较高。
