附着硅藻指数在河流水质监测中的适用性技术研究

对广西龙江和柳江中段共18个样点进行了附着硅藻的采样调查,并采用相关分析法、主成分分析法、最优分割分类法、箱须图法、逐步判别分析法和双向指示种分类法等数学方法研究分析了16个硅藻指数在龙江与柳江中段水质监测中的适用性.结果表明,3次4组不同水质类别中,IPS(Specific Pollution Sensitivity Index)和TDI(Trophic Diatom Index)指数与样点的箱须图都表现出合理的趋势,而且IPS和TDI间、及与环境因子及其他硅藻指数间的相关性显著.表明IPS和TDI适合进行龙江与柳江中段的水质生物监测评价,而本文提出的硅藻指数适用性技术也具有一定的推广价值.     

汾河水库水源河着生硅藻群落的DCCA研究

对汾河水库3条主要水源河的11个样点95个着生硅藻进行DCCA排序,这11个样点可分为4组,分别指示水质属于-中污带、-中污带、寡污带和清洁带,DCCA第一轴可反映水体污染程度,第二轴反映河流的流速.DCCA排序表明,COD与水体污染状况关系最大.物种多样性研究采用9个多样性指数,各多样性指数随水体污染等级加大而呈现下降的趋势.     

菲在渤海湾入海河流与河口沉积物上的吸附-解吸行为

采用批量实验方法,研究了菲(Phe)在渤海湾入海河流与河口沉积物上的吸附-解吸过程,以及吸附参数与沉积物有机质性质之间的相关关系.结果表明,Phe在所有沉积物上的吸附和解吸等温线均能由线性分配模型和Freundlich模型很好地拟合.其中,线性分配系数KD值变化在58～743L·kg-1之间,与TOC、TN、DOC、Phe、C/N和DOC/TOC之间呈现显著正相关关系.Freundlich吸附能力参数KF和KFOC值分别在75～367μg1-N·kg-1·LN和2253～34743μg1-N·kg-1·LN之间,均与DOC/TOC呈现显著负相关关系,而与其它有机质参数之间相关性不显著.相比较而言,大多数沉积物的解吸等温线用Freundlich模型拟合的效果更好,并且具有明显的解吸滞后现象.有机质的含量和性质均是影响Phe在沉积物上吸附-解吸的重要因素.对于频繁受到人类活动影响的河流沉积物,溶解性有机质的影响就更为重要.     

北方农牧交错带土地利用及景观格局变化特征

基于1988,1995和2000年3期Landsat TM数据,采用遥感,GIS和景观生态学方法,运用土地利用转移矩阵、景观格局分析软件Fragstats3.3,对北方农牧交错带土地利用及景观格局变化进行了动态研究.结果表明:①减少的耕地主要转为草地,增加的耕地也主要源于开垦草地;②耕地转为草地的空间分布较均匀,草地转为耕地的区域差异明显;③1988—1995年和1995—2000年2个时段参加变化的土地数量差异显著;④增加的沙地主要源于草地退化;⑤景观异质性上升,结构趋向均衡化,稳定性增强,受人类干扰程度在加大.      

城市生态经济系统模型构建与分析

根据城市生态经济系统(UrbanEco-economicSystem,UEES)运行规律和系统调控的目标,建立了UEES指标体系.以宁波市为例,采用偏最小二乘算法构建了UEES模型.本例中,模型的Q2cum值为0·996,表明其具有较好的稳定性和预测能力.计算结果表明,到2007年、2012年和2020年,宁波市国内生产总值将分别达到2588×108元、3250×108元、5261×108元;万元国内生产总值能耗、城市化水平与产业结构是影响经济规模扩大的主要因素,万元工业产值废水排放量和SO2排放量与经济规模呈显著的负相关关系.在此基础上,提出了宁波生态市建设过程中经济发展的若干建议.     

Efficacy of extracting indices from large‐scale acoustic recordings to monitor biodiversity

Passive acoustic monitoring could be a powerful way to assess biodiversity across large spatial and temporal scales. However, extracting meaningful information from recordings can be prohibitively time consuming. Acoustic indices (i.e., a mathematical summary of acoustic energy) offer a relatively rapid method for processing acoustic data and are increasingly used to characterize biological communities. We examined the relationship between acoustic indices and the diversity and abundance of biological sounds in recordings. We reviewed the acoustic‐index literature and found that over 60 indices have been applied to a range of objectives with varying success. We used 36 of the most indicative indices to develop a predictive model of the diversity of animal sounds in recordings. Acoustic data were collected at 43 sites in temperate terrestrial and tropical marine habitats across the continental United States. For terrestrial recordings, random‐forest models with a suite of acoustic indices as covariates predicted Shannon diversity, richness, and total number of biological sounds with high accuracy (R² ≥ 0.94, mean squared error [MSE] ≤170.2). Among the indices assessed, roughness, acoustic activity, and acoustic richness contributed most to the predictive ability of models. Performance of index models was negatively affected by insect, weather, and anthropogenic sounds. For marine recordings, random‐forest models poorly predicted Shannon diversity, richness, and total number of biological sounds (R² ≤ 0.40, MSE ≥ 195). Our results suggest that using a combination of relevant acoustic indices in a flexible model can accurately predict the diversity of biological sounds in temperate terrestrial acoustic recordings. Thus, acoustic approaches could be an important contribution to biodiversity monitoring in some habitats.     

上海市青浦区景观格局的粒度效应分析

以上海市青浦区为研究区域，基于ETM遥感影像数据和GIS技术，采用优势规则栅格聚合方法，对分类的ETM数据进行了粒度变换。以景观格局分析程序Fragstats3．3为分析工具，从景观类型水平和景观水平上研究了景观格局的空间粒度效应。研究结果表明：（1）不同的景观类型、不同的景观特征指数对粒度响应存在差异：居住景观和道路景观是对粒度响应最敏感的两种景观类型；形状指数、聚集度指数、斑块数量指数对粒度响应的敏感程度较高，多样性指数、均匀度指数、景观面积比例指数、分维数对粒度响应的敏感程度较低；此外，还发现优势景观随着粒度增加面积增大，形状规则的景观对粒度响应敏感程度低。（2）景观指数的粒度响应曲线存在尺度转折点，且多出现在40、60、80、120m，其中第一尺度区域多为20～40m或20～60m。第一尺度域是选择适宜粒度的较好取值范围，所以本研究中所用景观类型图进行景观指数计算的适宜粒度范围为30-40m。（3）研究发现由不同指数表征相同的生态现象可能会出现相反的粒度效应，在一定程度上体现了景观指数量化景观格局的局限性。     

A SENSITIVITY ANALYSIS OF THE PALMER HYDROLOGIC DROUGHT INDEX1

ABSTRACT: The sensitivity of the Palmer Hydrologic Drought Index to departures from average temperature and precipitation conditions is examined. A time series of zero index values was calculated and then one monthly temperature or precipitation value was perturbed. The resulting time series shows the effects on the index of one anomalous value. Independent series were calculated for temperature anomalies of plus and minus 1, 3, 5, and 10F and for precipitation anomalies of 25, 50, 75, 125, 150, and 200 percent of normal for each calendar month for Colorado, Indiana, Nevada, New York, Oklahoma, South Carolina, South Dakota, Washington, and Wisconsin. Analysis of the time series showed that the period of time required for the index to reflect actual rather than artificial initial conditions could be more than four years. It was also found that the effects of temperature anomalies are insignificant compared to the effects of precipitation anomalies. In some cases, one anomalous precipitation value could result in established wet or dry spells that last for up to two years. Although not examined in detail, the time series suggest that distributions of index values may be asymmetrical and possibly bimodal.     

企业"绿色度"的模糊评价模型与应用

"绿色度"是绿色的程度或与环境友好的程度.分析了企业"绿色度"绩效评价的理论基础,讨论了在众多因素影响下关于企业"绿色度"绩效评价的指标体系;采用专家法确定各因素权重;运用多层模糊综合评价原理进行系统评价.并通过一个化工厂的实例验证了所建立模型与求解方法的正确性与实用性.     

Characterization of aliphatic hydrocarbons in deep subsurface soils near the outskirts of Beijing, China

Thirty-nine deep subsurface soils( 150—180 cm depth) near the outskirts of Beijing were investagated. The concentrations including n-alkanes from C13 to C36, pristane and phytane were in the range of 0.60 to 170.10μg/g, with a median value of 4.26. Carbon preference index values for n-alkanes ranged from 1.08 to 2.98, with a median value of 1.48. The percentage contribution of “wax” nalkanes was in the range of 6.03%--46.22%. A predominance of odd/even carbon n-alkanes and unresolved complex mixtures with different shapes and ranges were frequently observed. Factor analysis reduced the data set into three principal components and confirming contributions from low ( 19.58% ), medium ( 20.49% ) molecular weight species and long-chain n-alkanes (43.41% ), respectively.Molecular biomarkers such as pristane, phytane, hopanes and steranes were detected. Based on the principal component analysis, the concentration profiles and molecular markers, it was found that the aliphatic hydrocarbons were from both biogenic and anthropogenic sources.