三峡水库135m水位蓄水典型次级河流回水段富营养化监测评价

通过2004年3月份对三峡水库135m水位蓄水状态下库区成库河段典型次级河流朱衣河、梅溪河、大宁河回水河段富营养化监测与评价,掌握了在这一季节三峡库区成库河段次级河流回水河段营养状态不同的分布模式.     

香溪河库湾氮的时空分布及影响因子分析

为研究解决香溪河库湾水体富营养化问题,需探明库湾水体氮的时空分布及影响因子。2010年12月—2011年11月对香溪河与水库干流交界处至香溪河库湾尾部共12个采样点进行连续监测,分析香溪河库湾氮的时空分布,结果表明,香溪河库湾氮存在明显的时空分布规律。空间上,回水末端处TN和NO₃^--N浓度低,河口处浓度高,随着与回水末端距离的增加,浓度逐渐升高。在时间上,香溪河库湾TN和NO₃^--N浓度的变异系数随着与河口距离的增加总体上逐渐增大,研究时间内的变化程度逐渐变大;且香溪河库湾TN和NO₃^--N浓度在三峡水库不同运行阶段的时间变化规律不同。     

Step-up multiple regression model to compute Chlorophyll a in the coastal waters off Cochin, southwest coast of India

The interaction effects of abiotic processes in the production of phytoplankton in a coastal marine region off Cochin are evaluated using multiple regression models. The study shows that chlorophyll production is not limited by nutrients, but their physiological regulations (responses to nutrients, pH, temperature and salinity) are mainly responsible for the increased biological production. The model explaining 77% of variability for chlorophyll a production is indicative of preconditioning of the coastal waters. The phytoplankton production is found to be sensitive to the environment, which varies seasonally. Further, the study suggests that supply of organic matter and grazing of zooplankton (not included) would improve the model efficiency. Despite this, the good agreement in the computed and measured chlorophyll a values shows that step-up multiple regression model is a useful tool to understand the influence of environmental variables on the production of phytoplankton in these coastal waters.     

2013年春夏季莱州湾海水环境要素特征和富营养化评估

根据2013年5（春季）、8月（夏季）莱州湾海水环境要素的调查资料,采用富营养化指数、潜在性富营养化评价模式和灰色聚类分析方法研究环境要素特征和评估海水富营养化状况。结果表明,无机氮是莱州湾水质的主要污染要素,春夏季的N/P平均值分别为100.76、117.84,潜在性富营养化评价模式结果表明,春夏季各站位的营养级均只包括Ⅳ_P、Ⅵ_P两类,磷限制为莱州湾的营养盐结构特征;富营养化指数评价结果表明,春季和夏季E>1站位比例分别为65%、20%;灰色聚类分析结果表明,春季Ⅱ级、Ⅲ级的站位比例分别为95%、5%,夏季Ⅱ、Ⅲ级的站位比例分别为70%、25%,Ⅱ级中的部分站位具有较大潜在富营养化风险。     

Development and Parameterization of a Rain- and Fire-driven Model for Exploring Elephant Effects in African Savannas

We describe the development and parameterization of a grid-based model of African savanna vegetation processes. The model was developed with the objective of exploring elephant effects on the diversity of savanna species and structure, and in this formulation concentrates on the relative cover of grass and woody plants, the vertical structure of the woody plant community, and the distribution of these over space. Grid cells are linked by seed dispersal and fire, and environmental variability is included in the form of stochastic rainfall and fire events. The model was parameterized from an extensive review of the African savanna literature; when available, parameter values varied widely. The most plausible set of parameters produced long-term coexistence between woody plants and grass, with the tree–grass balance being more sensitive to changes in parameters influencing demographic processes and drought incidence and response, while less sensitive to fire regime. There was considerable diversity in the woody structure of savanna systems within the range of uncertainty in tree growth rate parameters. Thus, given the paucity of height growth data regarding woody plant species in southern African savannas, managers of natural areas should be cognizant of different tree species growth and damage response attributes when considering whether to act on perceived elephant threats to vegetation.