A method for assigning species into groups based on generalized Mahalanobis distance between habitat model coefficients

Habitat association models are commonly developed for individual animal species using generalized linear modeling methods such as logistic regression. We considered the issue of grouping species based on their habitat use so that management decisions can be based on sets of species rather than individual species. This research was motivated by a study of western landbirds in northern Idaho forests. The method we examined was to separately fit models to each species and to use a generalized Mahalanobis distance between coefficient vectors to create a distance matrix among species. Clustering methods were used to group species from the distance matrix, and multidimensional scaling methods were used to visualize the relations among species groups. Methods were also discussed for evaluating the sensitivity of the conclusions because of outliers or influential data points. We illustrate these methods with data from the landbird study conducted in northern Idaho. Simulation results are presented to compare the success of this method to alternative methods using Euclidean distance between coefficient vectors and to methods that do not use habitat association models. These simulations demonstrate that our Mahalanobis-distance-based method was nearly always better than Euclidean-distance-based methods or methods not based on habitat association models. The methods used to develop candidate species groups are easily explained to other scientists and resource managers since they mainly rely on classical multivariate statistical methods.     

定量化土地评价指标体系及评价方法探讨

从可持续发展的角度，提出了定量土地评价指标体系建立的原则与依据；分析了土地评价指标体系的现状与存在的问题；总结了土地评价指标体系的量化表达方法，特别是空间统计分析模型和地理信息系统技术在定量化土地评价中的应用。为可持续利用土地评价提供理论依据和方法上的借鉴。     

从SCI论文看中国黄土研究的发展

中国的黄土研究处于世界领先地位.利用文献计量学,对SCI收录的有关中国黄土研究方面的论文进行统计和分析,考查了1989-2008年近20 a中国黄土研究的SCI论文产出、研究力量、以及论文影响力等方面的情况.研究结果表明,20 a来我国关于中国黄土的研究论文的产出数量持续高速增长,已居世界前列;SCI论文发文的高峰一般发生在国际第四纪联合会(INQUA)大会召开之后;主要研究机构集中于中国科学院、兰州大学、南京大学、我国台湾中央研究院和北京师范大学;从论文被引用情况看,我国学者在黄土研究方面的论文已颇具影响力.揭示了我国黄土研究科研论文总体发展的趋势.     

基于遥感与GIS的土壤侵蚀强度快速估测方法

针对土壤侵蚀问题,提出了一种基于遥感数据、气象数据、土壤数据的区域土壤侵蚀快速估测方法。首先,通过对土壤侵蚀问题形成原因和影响因素的分析,确定土壤侵蚀敏感性因子;其次,利用遥感(RS)、GIS技术提取土壤侵蚀敏感性因子信息;然后,在GIS系统支持下,运用主成分分析方法,进行土壤侵蚀强度分级;以北京密云水库周边区域为例,进行了土壤侵蚀估测方法的应用,并对该区域的土壤侵蚀空间特征进行分析。研究结果表明:(1)区域土壤侵蚀快速估测方法与实际情况有较好的一致性;(2)密云水库周边地区土壤侵蚀以微度和轻度侵蚀为主,所占面积比例为67.51%,中度以上侵蚀仅占面积的1.46%;(3)土壤侵蚀受坡度、地貌影响明显,中度侵蚀主要发生在低山、丘陵区以耕地为主的土地利用上以及坡度在大于25°的阳坡地带。     

低温胁迫对腰果幼苗叶片组织结构和生理指标的影响

以腰果无性系FL30为材料,初步研究了10、12、15℃低温胁迫和不同低温处理时间,对腰果幼苗叶片组织结构和叶绿素含量、过氧化物酶(POD)、过氧化氢酶(CAT)等生理指标的影响.结果与分析表明:低温胁迫对腰果幼苗叶片CTR值没有太大影响;低温胁迫下,随着时间的延长,腰果幼苗叶绿素含量呈下降趋势,处理时间相同时,温度越低,叶绿素含量下降的幅度越大;随着低温胁迫时间的延长,腰果叶片内POD、CAT活性先上升后迅速下降,胁迫温度不同,POD活性上升的幅度和持续时间不同,与10、12℃低温处理相比,15℃低温处理的POD活性上升较为缓慢和持久;低温胁迫下,CAT活性上升幅度较小,温度越低,CAT活性上升幅度越小,上升持续时间也越短.     

A research on the relationship between resistivity index and relative permeability at different measurement conditions based on the pore structure

Environmental Fluid Mechanics - Relative permeability and resistivity index are important parameters in petrophysics experiments and reservoir evaluations. According to the results of previous...     

基于氮磷指数的小流域氮磷流失风险评价

识别区域氮磷流失综合风险分布状况并对氮磷流失进行综合调控是控制非点源污染的有效措施。但传统的研究往往局限于氮或磷流失风险的单独评估和调控,以密云水库沿湖集约化农区东庄小流域为例,应用氮指数、磷指数及氮磷综合指数法,对区域氮磷流失风险进行综合评价。结果表明:流域氮、磷流失风险总体上较小,80%以上的区域均处于氮、磷流失的无风险或低风险区,但氮、磷流失的空间分布存在较大差异。其中氮流失的高度风险区集中在山地中土壤侵蚀指数较大的果园;而磷流失的高风险区域主要分布在河流沿岸的农业用地。氮磷综合风险指数显示,93.1%的区域处于无风险和低风险区,中度以上风险区占总面积的6.9%,主要集中在流域中部有着较高的肥料施用、地势陡峭且处在河流沿岸的农业用地或山地中。单独考虑氮指数或磷指数都难以反映区域氮磷流失的综合风险状况,容易忽略磷指数高氮指数低、氮指数高和磷指数低以及氮、磷风险在中等的区域。因此,在氮、磷流失风险评估基础上,进行氮磷流失风险的综合评价,可为氮磷流失的综合调控提供指导。     

基于氮磷指数的小流域氮磷流失风险评价

识别区域氮磷流失综合风险分布状况并对氮磷流失进行综合调控是控制非点源污染的有效措施。但传统的研究往往局限于氮或磷流失风险的单独评估和调控,以密云水库沿湖集约化农区东庄小流域为例,应用氮指数、磷指数及氮磷综合指数法,对区域氮磷流失风险进行综合评价。结果表明：流域氮、磷流失风险总体上较小,80%以上的区域均处于氮、磷流失的无风险或低风险区,但氮、磷流失的空间分布存在较大差异。其中氮流失的高度风险区集中在山地中土壤侵蚀指数较大的果园;而磷流失的高风险区域主要分布在河流沿岸的农业用地。氮磷综合风险指数显示,93.1%的区域处于无风险和低风险区,中度以上风险区占总面积的6.9%,主要集中在流域中部有着较高的肥料施用、地势陡峭且处在河流沿岸的农业用地或山地中。单独考虑氮指数或磷指数都难以反映区域氮磷流失的综合风险状况,容易忽略磷指数高氮指数低、氮指数高和磷指数低以及氮、磷风险在中等的区域。因此,在氮、磷流失风险评估基础上,进行氮磷流失风险的综合评价,可为氮磷流失的综合调控提供指导。     

黄土高原沟坡地土地生产力评价的指标体系与评价方法

通过对渭北黄土高原地区沟坡地土壤理化性质的分析和对当地社会经济状况的调查研究,应用层次分析法对沟坡地土地自然生产力和现实生产力进行了分析和评价.在分析过程中,把当地主要造林树种根系垂直分布特征及其根系抗旱性特性纳入了分析评价体系.结果表明,嘴头村和西坡村不同树种沟坡地上刺槐(Robinia pseudoacacia)的自然生产力属于中等稍微偏上水平,而山杏(Prunus armeniacia var. ansu)、油松(Pinus tabulaeformis)和侧柏(Platycladus orientalis)的自然生产力水平则较低.两地沟坡地上的现实生产力计算结果则证明刺槐和山杏两个树种表现出了较高的水平,具有较好的发展前途;而油松和侧柏的现实生产力水平则较低,其发展推广受到了限制.群众对沟坡开发治理的态度和对开发方案的认可对沟坡开发的成功起到了重要作用.     

A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification

● Established a quantification method of pollutant emission standard. ● Predicted the SO₂ emission intensity of single coking enterprises in China. ● Evaluated the influence of pollutant discharge standard on prediction accuracy. ● Analyzed the SO₂ emissions of Chinese provincial and municipal coking enterprises. Industrial emissions are the main source of atmospheric pollutants in China. Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely. Based on China’s coking enterprises in 2020, we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards (QRPES) into the construction of support vector regression (SVR) and random forest regression (RFR) prediction methods for SO₂ emission of coking enterprises in China. The results show that, affected by the types of coke ovens and regions, China’s current coking enterprises have implemented a total of 21 emission standards, with marked differences. After adding QRPES, it was found that the root mean squared error (RMSE) of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a, and theR² increased from 0.890 and 0.881 to 0.926 and 0.945, respectively. This shows that the QRPES can greatly improve the prediction accuracy, and the SO₂ emissions of each enterprise are highly correlated with the strictness of standards. The predicted result shows that 45% of SO₂ emissions from Chinese coking enterprises are concentrated in Shanxi, Shaanxi and Hebei provinces in central China. The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.