三峡库区干支流落干期消落带土壤可转化态氮含量及分布特征

为探明三峡支流水体富营养化频发与库岸消落带土壤氮素"源-库"关系转化之间的内在关系,采用分级浸提法,分析了三峡库区长江万州段干流、苎溪河支流、密溪河支流消落带落干期土壤可转化态氮含量和分布特征.结果表明,与三峡库区万州段干流相比,支流消落带落干期土壤有机质和总氮含量较高,而阳离子交换量(CEC)和p H值较低.三峡干支流消落带土壤可转化态氮(TF-N)以OSF-N(有机态和硫化物结合态)为主,且含量上OSF-NIMOF-N(铁锰氧化物结合态氮)IEF-N(离子交换态氮)CF-N(碳酸盐结合态氮);而空间分布上,TF-N表现为:密溪河苎溪河长江干流,4种TF-N形态中IEF-N和OSF-N在干支流间无显著差异,而CF-N和IMOF-N分布与TF-N相反,是造成干支流消落带TF-N差异的主要因素.     

植物N/P与土壤pH值对湿地植物物种丰富度的影响

通过人工控制模拟试验,研究了植物中全氮与全磷之比(植物N/P)和土壤pH值与湿地植物物种丰富度的关系.结果表明,湿地物种丰富度与植物N/P之间呈单峰变化关系,当2.09.5时,氮、磷供应平衡系统可能被破坏,湿地物种逐渐减少.物种丰富度与土壤pH值表现为显著的正相关关系(R²=0.526),当pH值为5.6～6.8时,物种丰富度随着土壤pH值增加而增加.通过方差分析,土壤pH值和植物N/P对物种丰富度的影响分别为37.96%和15.29%.     

船舶油污染防治的30年

1967年，油轮Torrey Canyon和以后发生的Amoco Cadiz、Exxon Valdez等溢油事件，震动了石油、航运等企业以及海洋环境保护部门。从1969年开始的溢油会议，交流油污染防治经验和成果，到1999年的30年，可以看出船舶污染防治的梗概。文中对此作了综合评述，并说明目前状况和今后的发展。     

中美淡水生物区系中汞物种敏感度分布比较

通过收集无机汞对中国与美国淡水水生生物的毒性数据,构建了脊椎动物(包括鱼类)、无脊椎动物(包括节肢动物和非节肢无脊椎动物)及所有物种对汞的物种敏感度分布(SSD:species sensitivity distributions)曲线,并在此基础上对中国和美国不同类别生物对汞的敏感性分布进行了分析.结果表明:中国与美国各类生物及所有物种对汞的SSD敏感性分布曲线没有显著差异.然而,中国淡水水生物种对汞短期暴露的HC5(hazardous concentration for 5% of the species)较美国淡水物种的阈值小,尤其是非节肢无脊椎动物,汞对美国非节肢动物的HC5值是我国对应物种的7.4倍.在保护95%的物种水平下,中国不同类别试验生物对汞的敏感性排序为无脊椎动物>脊椎动物,其中节肢动物>非节肢无脊椎动物>鱼类;而对应的美国生物对汞的敏感性排序无脊椎动物>脊椎动物,其中节肢动物>鱼类>非节肢无脊椎动物.另外,中美所有节肢动物对汞的敏感性要强于所有鱼类和所有非节肢无脊椎动物.所以在使用所有物种推导水质基准时应考虑其中各类别物种敏感度分布的影响,且需要注意采用美国淡水水生物种推导的水质基准可能会对我国淡水水生物种造成"保护不足".     

甘南高寒草甸植物群落物种多度分布特征

为分析甘南高寒草甸植物群落物种多度分布格局对海拔梯度的响应,探讨物种多样性的形成规律及维持机制,采用典型样地调查法采集数据信息,并通过RAD软件程序包对实验数据进行拟合分析.结果表明:植物群落物种多样性随海拔的升高呈现先增加后降低的"中间膨胀"模式,海拔3500m处群落物种多样性达到最大.利用5个模型对海拔梯度上全部物...     

中国遗传资源优先保护等级评价标准的构建

确定科学合理的生物遗传资源优先保护等级,是当前保护生物学研究的一个核心问题。文章通过分析国内外遗传资源优先保护等级评价研究进展,针对遗传资源的特点,对遗传资源与物种关系、遗传资源多样性、境外种群影响、遗传资源价值、潜在利用价值、人工繁育技术、特有情况等方面进行了探讨并提出相应建议,初步确定了遗传资源优先保护等级的评价标准,以期能为生物遗传资源的有效保护和科学管理提供参考依据。     

吉州生态工业园规划建设探讨

吉州工业园率先在江西省进行了生态工业园规划建设试点。文章介绍了吉州生态工业园规划建设的指导思想与原则,从5个核心系统和三大循环系统阐述了吉州生态工业园规划建设的总体框架,并提出了电子信息产业、机械加工产业、造纸化工产业、食品加工产业4个主导产业的工业生态系统规划,同时提出了吉州生态工业园近期建设的补链项目,预测分析吉州生态工业园近期建设的经济效益、环境效益、社会效益进行。     

GIS支持下的秦岭植被景观梯度分析

秦岭植被景观类型丰富,具有过渡性和复杂性特点,植被垂直分带明显. 在分析了大尺度秦岭植被景观空间水平分布格局的基础上,利用基于GIS梯度分析方法,分析秦岭的植被与海拔梯度的关系,得到秦岭不同植被景观类型的斑块数、分布范围、植被分布的海拨高度平均值和标准差,并以太白山为例,对太白山植物种进行了梯度分析. 结果表明,随着海拔高度的增加,太白山依次出现7种植被景观类型:温带草丛→温带落叶灌丛→温带落叶阔叶林→亚热带针叶林→亚热带和热带山地针叶林→草甸→高寒草甸等植被类型,植物种亦发生相应的变化.      

A genoscape-network model for conservation prioritization in a migratory bird

Migratory animals are declining worldwide and coordinated conservation efforts are needed to reverse current trends. We devised a novel genoscape-network model that combines genetic analyses with species distribution modeling and demographic data to overcome challenges with conceptualizing alternative risk factors in migratory species across their full annual cycle. We applied our method to the long distance, Neotropical migratory bird, Wilson's Warbler (Cardellina pusilla). Despite a lack of data from some wintering locations, we demonstrated how the results can be used to help prioritize conservation of breeding and wintering areas. For example, we showed that when genetic, demographic, and network modeling results were considered together it became clear that conservation recommendations will differ depending on whether the goal is to preserve unique genetic lineages or the largest number of birds per unit area. More specifically, if preservation of genetic lineages is the goal, then limited resources should be focused on preserving habitat in the California Sierra, Basin Rockies, or Coastal California, where the 3 most vulnerable genetic lineages breed, or in western Mexico, where 2 of the 3 most vulnerable lineages overwinter. Alternatively, if preservation of the largest number of individuals per unit area is the goal, then limited conservation dollars should be placed in the Pacific Northwest or Central America, where densities are estimated to be the highest. Overall, our results demonstrated the utility of adopting a genetically based network model for integrating multiple types of data across vast geographic scales and better inform conservation decision-making for migratory animals.     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.