Measuring trail users’ perception of crowding in a peri-urban nature park: A best-worst scaling experiment

This paper evaluates the perception of crowding, its determinants and relationship with trail users’ experience in a peri-urban nature park. Existing crowding surveys rely heavily on a single-item 9-point crowding scale which was originally developed for backcountry areas. Receiver operating characteristic (ROC) analysis was used to test the validity and reliability of this measure in detecting crowding issues and formulating visitor capacity limits. Low validity and reliability raised concerns about the applicability of this scale in similar frontcountry areas. Inability of this simple crowding measure to detect a visitor threshold brings to the fore its another important limitation – ignorance of the complexity of crowding phenomenon. The perception of crowding varies with various social, psychological and situational factors, and a best-worst scaling (BWS) experiment was designed to simultaneously evaluate different aspects of crowding in the Medvednica Nature Park, a peri-urban nature park near Zagreb, Croatia. The findings of BWS experiment revealed that occupancy of mountain huts, number of other hikers on the trail and amount of litter along the trail on average contributed most to the trail users’ sense of crowding. A latent class analysis identified a large heterogeneity in the perception of crowding; while one group of trail users (63%) was more disturbed by the direct social impacts, the others (37%) were more disturbed by the secondary impacts of other visitors, especially by the negative externalities from road traffic in the park. Older visitors had a greater tendency to primarily associate crowding with the environmental conditions. A higher impact of trail use level in the perception of crowding, younger age and more frequent use were associated with a more negative evaluation of crowding. The park management should closely monitor road traffic in the park and visitor activity on highly used trails, especially on those popular among younger trail users.     

基于Landsat数据的条件植被温度指数升尺度转换方法

以陕西省关中平原为研究区域,应用点扩散函数、混合像素面积权重法和中值像素变异权重法将基于Landsat卫星遥感数据反演的分辨率为30 m的条件植被温度指数(VTCI)干旱监测结果上推至930 m的干旱监测结果,并与Aqua MODIS数据反演的分辨率为930 m的VTCI干旱监测结果进行对比分析,以期为两种空间尺度的干旱监测结果的综合应用提供技术支持。以MODIS数据反演的VTCI为参考,应用相关系数、均方根误差、半变异函数的估计值和图像纹理特征等对尺度上推的VTCI进行评价。结果表明,点扩散函数和混合像素面积权重法的尺度上推效果均较好,而中值像素变异权重法的尺度上推效果较差,说明点扩散函数和混合像素面积权重法均适用于研究区域VTCI干旱监测结果的尺度转换,且点扩散函数的数据处理过程更为简单。典型样点VTCI的尺度上推结果表明,空间异质性越小,尺度上推的结果越好。     

A model of arctic tundra vegetation derived from topographic gradients

We present a topographically-derived vegetation model (TVM) that predicts the landscape patterns of arctic vegetation types in the foothills of the Brooks Range in northern Alaska. In the Arctic there is a strong relationship between water and plant structure and function and TVM is based on the relationships between vegetation types and slope (tan ) and discharge (), two independent variables that can be easily derived from digital terrain data. Both slope and discharge relate to hydrological similarity within a landscape: slope determines the gravitational hydrological gradient and hence influences flow velocity, whereas discharge patterns are computed based on upslope area and quantify lateral flow amount. TVM was developed and parameterized based on vegetation data from a small 2.2 km² watershed and its application was tested in a larger 22km² region. For the watershed, TVM performed quite well, having a high spatial resolution and a goodness-of-fit ranging from 71–78%, depending on the functions used. For the larger region, the strength of the vegetation types predictions drops somewhat to between 56–59%. We discuss the various sources of error and limitations of the model for purposes of extrapolation.     

基于高光谱与在线序列极限学习机确证大米产地方法

为满足快速无损的大米产地确证需求，采集吉林省梅河口市水稻主产区及松原、大安、辉南等其他水稻产区共990个大米样本的高光谱图像（400~1 000 nm）作为研究对象，利用多元散射校正（MSC）处理方法对光谱进行预处理。采用多层感知机（MLP）、极限学习机(ELM)与在线序列极限学习机(OS-ELM)算法，分别基于全波段高光谱数据以及经多维尺度分析（MDS）方法降维后的数据建立产地确证模型。结果表明，基于全波段高光谱数据的OS-ELM模型分类性能最好，准确率达到98.3%。经MDS处理后，输入的数据变量减少了96.6%，MDS-OS-ELM模型准确率稳定在97.4%。对三种模型的训练时间进行对比分析，OS-ELM训练时间明显优于MLP，在分批次获取数据时训练时间优于ELM。为大米产地确证提供了一种高效、准确、稳定的方法。     

区域尺度土壤入渗特征参数的变异性研究

以杨凌地区为例,进行野外双环入渗试验研究,运用2种常用模型(Kostiakov模型和Philip模型)对土壤入渗参数进行模拟。在分析土壤特征参数,寻求适合区域尺度的最优入渗模型同时,对土壤的状态变量进行标定并研究标定系数的空间变异性,研究结果表明:Philip模型可作为区域最优入渗模型,土壤入渗特征参数存在明显的空间变异性,标定系数aA比as对模型参数的标定效果好,且在较大范围内存在一定的趋势性,有较好的预测效果。因此,可根据标定系数随机模拟得到某一具体时刻的土壤入渗量的空间分布,为定量分析土壤水分运动、研究土壤水分入渗的空间分布提供理论基础。     

强化木材检验管理是提高经济效益的重要手段

本阐述了森工采运企业强化木材检验工作管理的重要性和必要性，尤其是在国家实施“天保”工程中，企业求发展，就必须在木材检验方面入手，从队伍建设、人员素质提高及经济制约责任等抓起，从而使森工企业走向可持续发展之路。     

应用热扩散式探针法对南方红壤丘陵区湿地松人工林耗水量的研究

运用Granier热扩散式探针法对湿地松(Pinus elliottii)树干液流密度进行长期连续测定,并对其周围多个气象要素和土壤要素进行同步测定。湿地松生长旺季不同月份晴天液流密度日变化规律基本一致,但液流启动、到达峰值的时间以及开始升高、开始下降的时间间隔存在差异。样木解析结果表明,处于低龄期的湿地松,整个木质部都可看作边材,边材面积和胸径可用二次函数很好地拟合。方差分析结果表明:不同胸径湿地松树干液流密度不存在显著性差异,与胸径无紧密关系。回归分析结果表明:湿地松日累计液流量与边材面积呈显著的线性相关关系,相关关系的判定系数达0.99。另外,单位边材面积日累计液流量与入选各气象因素的相关性显著,相关程度大小顺序为光合有效辐射>冠层相对湿度>冠层温度。结合边材面积-胸径回归方程和样木胸径调查资料,分别采用2种方法推算整个标准地的耗水量。经比较,2种方法所得结果差别不大,各自适用于一定的范围。     

Tooth brushing inhibits oral bacteria in dogs

In this study, scaling, polishing and daily tooth brushing were performed in 20 beagle dogs, and the number of oral bacteria was determined using a bacterial counter. The dogs were randomized into the scaling (S), scaling + polishing (SP), scaling + tooth daily brushing (SB) and scaling + polishing + tooth daily brushing (SPB) groups. Samples were collected from the buccal surface of the maxillary fourth premolars of the dogs immediately after scaling and every week thereafter from weeks 1 to 8. Throughout the study, the number of bacteria was significantly lower in the SB and SPB groups compared with the S group. The findings suggest that daily tooth brushing inhibited oral bacterial growth in the dogs.     

Analysis of regional variation of height growth and slenderness in populations of six urban tree species using a quantile regression approach

Inventory data of six urban tree species from seven cities across Germany were used to model regional variation of height growth, allometric scaling, and slenderness over a wide range of size and age using a quantile regression approach. Variation within and between species and cities was large. Height did not reach an asymptote but declined at higher ages, presumably because of reduction cuts. Allometric scaling and slenderness varied with wind climate, modulus of elasticity, and coefficient of drag. Our data do not support the use of a threshold value of slenderness in tree risk assessment.