黄河三角洲植物群落分布格局及其影响因素

利用双向指示种分析和去趋势典范对应分析的方法,对典型河口滨海湿地黄河三角洲植物群落类型和结构进行了分析,并探讨了植物群落分布格局及其影响因素。结果表明：134个样方可划分为7个群系,即刺槐群落（Form. Robinia pseucdoacacia）、荻群落（Form. Miscanthus saccharifleus）、翅碱蓬群落（Form. Suaeda heteroptera）、獐毛群落（Form. Aeluropus sinensis）、芦苇群落（Form. Phragmites communis）、柽柳群落（Form. Tamarix chinensis）和白茅群落（Form. Imperata cylindrica）。群落类型的划分主要反映了微地貌所决定的地下水埋深及土壤盐分含量的变化。在影响植物群落分布格局的因素中,环境因子解释的部分占45.2%,空间因子解释的部分占11.8%,空间因子和环境因子交互作用解释的部分占2.23%,空间因子和环境因子未能解释的部分占40.8%,这部分主要反映了群落自身互作及人类活动对群落的影响。     

25000年以来勃海湾西岸古环境探讨

本文依据孢粉,微体古生物,放射性碳测年,因子分析等资料,表明25000a,BP以来渤海湾西岸的古植被,古地理环境演变既受气候冷暖变化的影响,又受海平面变化的制约,25000－23000a,BP为高 平面时期,古植被为森林草甸植被,23000－12000a,BP气候冷干,为低海平面时期,以草原植被为主,前期和后期为沼泽草甸植,被12000－5000a,BP气候温凉或温暖湿润为海平面上升时期,为阔叶林草甸或沼泽草佃植被,5000a,BP以来,气候迹凉变干,为海退时期,古植被由沼泽草甸演为盐生草甸。     

孔雀河下游断流河道的环境特征及物种间关系

基于孔雀河下游断流河道的环境因子和植被样地数据,采用聚类与CCA排序法,分析了生境的退化特征以及物种间的相互关系,结果表明:1)断流河道退化生境分为绿洲-荒漠过渡类型、轻度荒漠化类型和盐土荒漠化类型。绿洲-荒漠过渡类型地下水位低、盐分含量相对较低,植被盖度相对较高,土壤维持着原砂质壤土,为潜在退化型;轻度荒漠化类型地下水位、土壤质地与含盐量与前者基本相同,土壤未明显退化,但植被盖度低于10%,植物种类与个体数目都较低,属于轻度退化型;盐土荒漠化类型地下水位高、盐分含量高,土壤机械组成中砂粒比重较大、无建群种幸存,属于重度退化型。2)绿洲-荒漠过渡类型总体联结性为显著正联结,正负联结比小于1,生态系统表现为建群种维系物种关系的不稳定状态;轻度荒漠化类型总体联结性为不显著负联结,正负联结比小于1,表现出生态系统进入退化演替的阶段;盐土荒漠化类型总体联结性为显著正联结,正负联结比大于1,表现出重度退化群落的种间平衡状态,物种间以达到稳定共存,其中,真盐生植物对这种平衡的维持起着重要的作用。3)CCA排序表明,绿洲-荒漠过渡类型形成以胡杨为中心的种间正联结,幸存于盐分适中、水分养分相对较高的生境;轻度荒漠化类型,形成以多枝柽柳与刚毛柽柳相互依存的不显著负联结,幸存于土壤养分、水分相对较低的生境;盐土荒漠化类型形成以盐爪爪、盐节木、盐穗木等真盐生植物维系的显著正联结,幸存于土壤贫瘠、地下水位浅、盐分含量高、沙化严重的生境。     

桂西北典型喀斯特区生态服务价值的环境响应及其空间尺度特征

Study on ecosystem service values (ESVs) is the bridge of understanding ecosystem and economic decision-making. To investigate the response of ESVs to ambient environment and their spatial scales is an urgent work in the process of ecological restoration and sustainable development in southwest China. Based on the previous research results, the remote images, and weather data of 31 years (1975-2005), the response of ESVs to ambient environment and their spatial scales in a typical karst area of northwest Guangxi, China were evaluated with the method of empirical mode decomposition (EMD) in this paper. The results showed that ESVs had obvious variations with changes in elevation, rocky types and soil types, and had corresponding characteristics of spatial scales. The ESVs in middle and low elevation areas were higher, but they decreased due to human activities such as deforestation. The ESVs in peak-cluster depression areas were lower, and they would increase as influenced by policies such as returning farmland to forestland. The ESVs were influenced by rocky types, showing lower values but an increasing trend in the typical karst regions while higher values but a decreasing trend in non-karst regions. The average ESVs in the west part of the study region, which is not only the main nature reserve for rare wildlife species in Guangxi, but also one of the best preserved natural vegetation regions in China, were more than 15,000 RMB Yuan ha-1,. Comparatively, the ESVs were less than 10,000 Yuan ha-1 in the middle part of the region attributed to low vegetation coverage, serious peak-cluster depression and karst rocky desertification. After about 20 years, that is from 1985 to 2005, the ecosystem conditions had been improved and the ESVs had increased in the middle and eastern part of this study region. On the contrary, in most western part, which was dominated by subtropical evergreen broad-leaved forest, they had been worsened, and the balance values of ESVs were negative. As for the relationships of ESVs with rocky types and soil types, lime soil and red soil were the two main soil types that contributed to ESVs (The total contribution was above 60%, and it is 63.77%,64.37%,64.56%,64.91% respectively in the four years of 1985, 1990, 2000 and 2005.). The variance contribution of intrinsic mode function (IMF) and trend (R) showed that there were obvious special sales for ESVs in this study area, and the main spatial scales were about 2.7 km, 5.5 km, and 11.6 km. The variance contribution ratio was 12.29%, 11.26%, 11.49% respectively, and the trend (R) was high (17.74%). In conclusion, this study indicated that ecosystem conditions in the typical karst area were improved owing to the application of rocky desertification control policies, such as ecological migration and returning farmland to forestland. Besides, the main spatial scales of ESVs in the study area were the interactions of terrain, physiognomy, land use / land cover and human activities.     

关于提高血气分析仪测量精度的探讨

血气分析已广泛用于昏迷、休克、严重外伤的危急病人的血液酸碱度、氧分压、二氧化碳分压的测量。测量数据的准确性至关重要。本文对与测量精度有关的几个环节如计量检定、质控与定标、样本采集与测量、日常维护与故障处理进行探讨,提出提高血气分析精度的解决方案。     

生命周期管理研究述评

生命周期管理起源于生命周期思想,它是生命周期思想在实践中的具体应用,是面向可持续生产和消费,对产品、工艺和服务的全生命周期环境影响进行的综合管理,是解决复合生态系统中结构无序、效率不高和代谢冗余的有效途径,是基于生命周期评价原则与框架的一种环境管理手段或环境管理体系。全面回顾了生命周期管理的起源与内涵,阐述了生命周期管理与生命周期评价的区别与联系,梳理了生命周期管理与环境管理体系的关系。对生命周期管理在产品、企业、行业及城市等层次上的具体应用进行了总结与述评,并对其今后需深入研究的方向进行了展望。     

人工模拟条件下青海湖裸鲤自然繁殖环境条件需求研究

为对青海湖裸鲤(Gymnocypris przewalskii)的自然繁殖需求条件进行定量研究, 实验结合青海湖裸鲤自然产卵场原位生境调查, 通过室内人工模拟构建产卵环境诱发野生亲鱼自然繁殖, 解答可控环境中青海湖裸鲤自然繁殖的环境需求。结果表明, 青海湖裸鲤自然繁殖发生与水温、水深、流速、光照及底质因素密切相关, 其中卵石河床质较细砂等底质环境可显著提升自然交配诱导率及繁殖效果; 在合适的底质条件下, 青海湖裸鲤自然繁殖的适宜条件: 水深为0.15—0.2 m、流速为0.2—0.4 m/s、水温为10.8—14.3℃; 15D﹕9L比例的光周期有利于促进青海湖裸鲤自然繁殖的发生。在人工模拟环境中, 水深≥0.45 m、流速≥0.8 m/s、温度≥17℃或≤6℃、全光照等环境中未观测到自然繁殖活动的发生, 这些被认为是其自然繁殖环境的限制条件。研究阐明了可控环境中青海湖裸鲤野生亲鱼自发产卵繁殖的环境需求, 构建人工模拟产卵环境技术, 为自然产卵场生境调查评估、改进人工繁育模式提供技术支撑和新思路。     

草鱼体内肾细胞姐妹染色单体分化及交换的初步研究

本文确立了一个以草鱼体内肾细胞姐妹染色单体交换频率为指标的检测环境诱变或致癌物质的短期试验系统。采用硫堇-UV-Giemsa染色法,分析了草鱼体内肾细胞的SCD-2(注射BrdU后第二个细胞周期的中期分裂相的SCD)频率和SCE频率。用500微克/克体重BrdU体内标记5天,草鱼肾细胞SCD-2频率为8.58±0.22%;SCE频率为3.05±2.523 SCE_5/细胞。以丝裂霉素C(Mitomycin C,MMC)作为阳性对照,分析了化合物亚硝基胍(N-methyl-N~1-nitro-N-nitrosoguanidine,MNNG)和农药叶蝉散(Mipc)诱发SCE的能力。这项工作在评价水质污染方面将起一定的作用。     

中国科学院植被数量生态学重点实验室

实验室概况 中国科学院植物研究所植被数量生态学重点实验室成立于1989年11月,实验室以野外台站,样带,样地等平台为基础,运用信息生态学的理论,方法和生态系统控制实验等手段,致力于全球变化生态学的综合性研究,重点开展植被系统对全球变化的响应与适应、生物多样性变化与保育以及生态系统管理等方面的研究工作,以揭示不同时空尺度生态系统格局与变化规律,为中国植被系统与环境的可持续管理提供理论依据。     

广西隆安蔗区环境地球化学初步研究

通过对广西隆安县甘蔗产区不同地层甘蔗生长状况和产量的调查,划分甘蔗生长的适宜地层,并通过母岩、土壤、甘蔗植株中３１种元素含量的分析,研究植物与地球化学环境之间的关系,确定对甘蔗生产产生影响的元素。结果是：不同地层上甘蔗产量差异显著,以Ｃ３为优势区,Ｃ２、Ｄ２ｄ２为次优势区,Ｄ３、ＱＰ为劣势区,对甘蔗生产有明显促进作用的营养元素有Ｋ、Ｎａ、Ｂ、Ｎ;对甘蔗产量的提高有抑制影响的元素有Ａｓ、Ｃｒ、Ｃｕ、Ｃａ。