基于距离相关系数和KNN回归模型的森林蓄积量估测研究

【目的】探究Landsat8 OLI数据和KNN算法在森林蓄积量估测中的潜力。【方法】以湖南省湘潭县为研究区,采用Landsat8 OLI数据和同时期的二类调查数据,通过距离相关系数筛选特征,分别采用线性回归模型(MLR)、K-近邻模型(KNN)、距离加权KNN模型(DW-KNN)和优化欧式KNN模型(FW-KNN)对森林蓄积量进行估测。使用十折交叉方法进行精度检验,对检验结果进行对比分析。【结果】3种KNN模型的估测结果均高于传统的线性模型,并且在3种KNN模型中,FW-KNN算法效果最好,决定系数达到0.69,为3种模型中最高;3种KNN模型中,本研究优化欧氏距离KNN模型的估测精度最高,其均方根误差为30.3%,相比于传统KNN模型的均方根误差降低了5.1%,相比于DW-KNN模型降低了3.3%。【结论】采用DW-KNN蓄积量估测结果明显优于其他两种模型,说明通过特征与蓄积量的相关性优化样本间的距离是一种可行的KNN优化方法。     

Variability in the performance of juvenile Chinook salmon is explained primarily by when and where they resided in estuarine habitats

Estuarine habitats provide rearing opportunities for the juvenile life stage of anadromous fishes. Because survival is positively correlated with juvenile performance, these estuarine habitats play an important role in population abundance and productivity. To provide information for the recovery of several depressed stocks of Chinook salmon in the Columbia River Basin, we sought to identify the factors that explain variability in performance. Using otolith‐derived estimates of juvenile somatic growth rate as an index of recent performance, we observed a negative nonlinear relationship between growth rate and day of year, and a decreasing and increasing trend of growth rate over the 8 years of this study and distance from the river mouth respectively. Using a generalised linear modelling approach, we found that variability in juvenile somatic growth rate was best explained by where and when individuals were collected, their body size, contaminant loads, stock of origin, and whether a fish was hatchery produced or unmarked. Lastly, we argue that a considerable improvement to the growth rate of juveniles in estuarine habitats is physiologically possible. The results of this 8‐year study provide a baseline of the performance of juvenile Chinook salmon to evaluate habitat restoration programs and to compare against future anthropogenic conditions.     

林木瘿螨

概述林木瘿螨研究现状及其亲缘关系,最后扼要地介绍了林木瘿螨的防治。     

混合土料单独命名的必要性探讨

混合土料是由粗细土颗粒组成的土。作者对混合土料、均匀粗粒土及纯细烂土的颗粒组成与工程性质进行了对比分析。结果表明，混合土料是介于均匀粗粒土和纯细粒土之间的土，它的工程性质有别于均匀粗粒土和纯细粒土，有必要对其单独命名，这为混合土的合理定位与专门研究提供了基础。     

数量化理论Ⅲ在土地质量综合评价中的应用

木文对土地质量综合评价的方法进行了探讨,首次提出将数量化理论Ⅲ应用于土地质量分级。与目前使用的系统聚类、动态聚类方法相比,数量化理论Ⅲ更适合于变量类型为定性变量的土地资源调查资料的分类。它弥补了系统聚类方法和动态聚类方法在土地资源评价中应用的局限性,数量化理论Ⅲ是一种可用于土地质量分级的理想方法。     

北京中山地区非石灰性土壤发生分类的研究

利用剖面形态、微形态、理化分析、粘粘x衍射分析等结果,对北京中山地区土壤的发生过程和分类问题进行了研究。首次提出尘暴降尘物质对土壤发生过程的滞缓作用。若土壤分类上采用pH(KCI),北京中山地区非石灰性土壤应属于暗棕壤。在土壤分类特征上,为在山地普遍应用中避免估算和推测造成混乱,建议采用反映该地区水分和温度状况的植被。     

库存本阅览室与外借库的合并管理

我馆在2005年将中文图书库存本阅览室与中文图书外借库合并成中文书库,进行统一管理。本文结合工作实际,分析了书库合并前分开管理的弊端,阐述了二者合并的意义,提出了合并后的具体管理措施。     

GIS在生态土地分类中的作用

This paper depicted the physiographic landscape features and natural vegetation situation of study area (the eastern Jilin Province), and expatiates the definition, basic characters and its development of Ecological Land Classification (ELC). Based on the combination of relief map, satellite photography for study area and vegetation inventory data of 480 sample sites, a 5-class and a 15-class ecological land type map was concluded according to 4 important factors including slope, aspect, vegetation and elevation. Ecological Classification System (ECS) is a method to identify, characterize, and map ecosystems. The Ecological Land Type (ELT) was examined and applied initially in eastern Jilin Province. Foundation item: This paper was supported by Chinese Academy of Sciences “100 people” project and the Open Research Station of Changbai Mountain Forest Ecosystem. Biography: XIAO Bao-ying (1974-), female, postgraduate in Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, P. R. China Responsible editor: Zhu Hong