玉溪烟区烟叶镁含量分布特征及影响因素

为研究玉溪烟区烟叶镁含量的分布状况和影响因素,采集玉溪烟区烟叶和土壤样品,通过描述性统计、方差分析、相关性分析及回归分析的方法,明确了烟叶镁含量的整体分布状况及在不同海拔高度和坡度区间的分布特征,分析了其与土壤全氮、全磷、速效钾、有效镁、有效硼和氯离子之间的关系.结果表明:玉溪烟区烟叶镁平均含量为4.28 g/kg,变...     

Projection of hydrothermal condition in Central Asia under four SSP-RCP scenarios

Hydrothermal condition is mismatched in arid and semi-arid regions, particularly in Central Asia (including Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, and Turkmenistan), resulting many environmental limitations. In this study, we projected hydrothermal condition in Central Asia based on bias-corrected multi-model ensembles (MMEs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios (SSP126 (SSP1-RCP2.6), SSP245 (SSP2-RCP4.5), SSP460 (SSP4-RCP6.0), and SSP585 (SSP5-RCP8.5)) during 2015-2100. The bias correction and spatial disaggregation, water-thermal product index, and sensitivity analysis were used in this study. The results showed that the hydrothermal condition is mismatched in the central and southern deserts, whereas the region of Pamir Mountains and Tianshan Mountains as well as the northern plains of Kazakhstan showed a matched hydrothermal condition. Compared with the historical period, the matched degree of hydrothermal condition improves during 2046-2075, but degenerates during 2015-2044 and 2076-2100. The change of hydrothermal condition is sensitive to precipitation in the northern regions and the maximum temperatures in the southern regions. The result suggests that the optimal scenario in Central Asia is SSP126 scenario, while SSP585 scenario brings further hydrothermal contradictions. This study provides scientific information for the development and sustainable utilization of hydrothermal resources in arid and semi-arid regions under climate change.     

浅谈东南亚佛教园林中的“五树六花”

佛教对东南亚影响深远，“五树六花”在东南亚佛教园林中既有宗教意义，又有功能效益；文章通过对“五树六花”的由来、形态特征、植物造景等方面进行分析，试阐述其在东南亚佛教园林中的地位、作用及其应用。     

基于灰色理论系统的西非海域捕捞渔获量预测

西非海域包括中东大西洋和东南大西洋两个渔区，是全球重要的渔业生产区域，科学预测其未来渔获量变化趋势，有利于该海域渔业资源的科学管理和开发。根据2000—2020年联合国粮农组织（FAO）提供的渔获量数据，采用灰色关联分析法和灰色预测理论，分别分析了影响中东大西洋和东南大西洋总渔获量的主要渔获类别，建立多种 GM (1,N)模型并进行比较分析，同时利用2018—2020年渔获量数据进行验证，获得最优GM（1,N）模型预测2021—2025年中东大西洋和东南大西洋总渔获量。本研究分析发现两海域最优预测模型均为GM（1,6），模型预测值与原始值的灰色关联系数均最大，分别为0.825和0.867，平均相对误差均为最小，分别为2.705%和1.734%；2018—2020年渔获量预测平均相对误差分别为4.63%和8.24%；2021—2025年中东大西洋和东南大西洋总渔获量预测值分别为497.67～588.79万t和138.20～147.41万t。研究认为，中东大西洋总渔获量在十四五期间最多增长约为48万t，增长幅度较小，建议加强资源养护、管控捕捞规模，制定和实施禁渔期等有效管理养护措施，建立科学合理渔业合作机制；东南大西洋总渔获量呈平稳波动状态，建议加强重点鱼种的养护管理，深化区域渔业合作，适当扩大捕捞海域范围，实现渔业可持续利用。