Extending the Encounter–Norm–Crowding Generalization to Angler Evaluations of Other Social and Resource Indicators

Recreationists who encounter more people than their normative tolerance for seeing others usually feel more crowded than those encountering fewer than their norm. This research note extends this observation–norm–evaluation relationship (e.g., encounter–norm–crowding) to other evaluations and indicators. Data were from a survey of anglers on the Gulkana National Wild River in Alaska (n = 288). Respondents who encountered more people than their norm felt more crowded than those encountering fewer than their norm. When impacts from other social indicators (e.g., camping within sight or sound of other groups, fishing area competition) exceeded user norms, crowding was higher and satisfaction with overall trip quality was lower than for those experiencing less than their norms. When impacts from resource indicators (e.g., litter, impacted campsites) exceeded norms, satisfaction with both environmental quality and trip quality were lower than for those experiencing less than their norms. The encounter–norm– crowding generalization, therefore, extended to other indicators and evaluations.     

Stewardship as a Path to Cooperation? Exploring the Role of Identity in Intergroup Conflict Among Michigan Wolf Stakeholders

Post-recovery wolf management remains controversial. In Michigan, dialogue centers on hunting wolves but controversy may be more nuanced than simple pro- or anti-hunting positions. Social identity may cause stakeholders to organize in groups and identity differences may be driving controversy. To explore stakeholder disagreement over wolf management, we conducted semi-structured key informant interviews (n = 21) about identity and stewardship in August–September 2012. Four overarching identity themes emerged regarding: (a) management objectives, (b) focal levels, (c) control methods, and (d) justifications for methods. Themes indicated two main researcher-defined identity groups. Interviewees from both groups identified six common stewardship themes: (a) bequest values, (b) ecosystem health, (c) education, (d) existence values, (e) pride in natural resources, and (f) sustainability. Findings suggest stakeholders may be conflicting over opposing identities vis-à-vis organization affiliation, which may be related to what management strategies individuals oppose. Establishing common stewardship objectives through established participation methods may help alleviate controversy.     

基于卷积神经网络的农作物叶片病害诊断

农作物病害诊断对于及时发现并采取防控措施具有重要意义。本研究针对苹果、玉米、番茄、葡萄等典型农作物的常见叶片病害问题,使用了两种目前使用最广泛的卷积神经网络——VGG16及Resnet50,对典型农作物叶片病害进行识别。使用AI Challenger比赛的农作物叶片病害数据集图像,并对这些图像进行预处理,构建了47285张图片的数据集。分析两种卷积神经网络的性能,实验结果表明:VGG16及Resnet50分别达到了82.57%和86.34%的准确率,且Resnet50收敛速度更快,更适合农作物叶片病害的诊断识别。     

中国苹果产量预测模型比较分析

提出了一种灰色神经网络模型。该模型结合了灰色GM(1,1)预测模型和BP神经网络2种预测模型的优点,并用此模型对我国的苹果产量进行预测。将GM(1,1)预测模型的预测值作为BP神经网络的输入变量,实际值作为输出变量进行神经网络训练。灰色神经网络模型对2004、2005年苹果产量的预测精度分别为98.11%、98.45%,高于单一的灰色GM(1.1)预测模型或BP神经网络。     

流浪犬猫与人群利益冲突的现状分析与思考

流浪犬猫是生存于人类社会、介于宠物犬猫和野生动物之间的一类特殊动物,其生存、活动、繁衍与社区人群的利益有时会产生直接冲突。本文介绍了流浪犬猫福利的特征和内涵,指出了其存在传播狂犬病、易攻击人类、粪便污染、噪声污染等与人群利益的有关冲突,由此提出减少遗弃宠物遗弃,减少食物浪费,加强社区公共管理等人为因素控制措施,以及对流浪犬猫实施安乐死,重新收养以及人工绝育等方式化解两者利益冲突,同时优化管理政策措施,平衡流浪犬猫福利和人群利益的关系。     

Neural networks in climate spatialization and their application in the agricultural zoning of climate risk for sunflower in different sowing dates

ABSTRACT

Sunflower is a species that is sensitive to local climate conditions. However, studies that use artificial neural networks (ANNs) to evaluate this influence and create tools such as agricultural zoning of climate risk (ZARC) have not been conducted for this species. Due to the importance of sunflower as a human food source and for biodiesel production, and also the necessity of conducting research to evaluate the suitability of this oleaginous species under different climatic conditions. Thus, we seek to construct a ZARC for sunflower in Brazil simulating sowing on different dates and using meteorological elements spatialized by ANNs. Climate data were used: air temperature (T), rainfall (P), relative air humidity (UR), solar radiation (MJ_m^?2_d^?1) and wind velocity (U²). Climatic regions considered suitable for the cultivation of sunflower had average annual values for T between 20 and 28°C, P between 500 and 1.500 mm per cycle, and soil water deficit (DEF) below 140 mm per cycle. A neural network is an efficient tool that can be used in spatialization of climate variables quickly and accurately. Sunflower sowing in the spring and summer are the ones that provide the largest suitable areas in southeastern Brazil, with 58.13 and 64.36% of suitable areas, respectively.     

基于神经网络方法的土壤流失量预测研究

生产建设项目土壤流失量的预测直接关系到建设项目的水土保持分析、评价和防治措施体系的布局,目前常用的预测方法因其局限性、不合理性以及精度差等问题往往难以实现准确预测。将人工神经网络的BP算法引入到土壤流失量预测中,将降雨侵蚀力、土壤可蚀性、坡长、坡度、水土保持措施作为影响土壤流失量的主要因子,并以17个生产建设项目水土保持监测实例作为学习样本和检测样本,建立了基于神经网络方法的土壤流失量预测模型。预测结果表明,该模型拟合和预测精度高,具有很强的应用价值,能够满足工程应用需要。     

焦作市绿色廊道景观组成与格局分析

绿色廊道是城市生态体系的重要组成部分,在城市空间分隔,维持景观格局稳定,促进物质能量的迁移和更新等方面发挥着重要的作用.以焦作市为例,在对绿色廊道分类、归纳的基础上,利用ENVI 4.5结合ArcGIS 9.2软件对焦作市遥感影像进行了处理,并结合实地调查对绿色廊道结构与体系进行了分析评价.结果表明,焦作市的绿色道路、河流和绿带廊道分别为24,7和2条.城区绿色廊道表现为群落结构简单,物种单一,建设率低;部分水系和道路为裸露的混凝土阶地,城区绿色廊道密度为2.86,绿色廊道建设率为0.48,网络交点为65个,连通度为0.17;焦作市绿色廊道密度、建设率和连通度等指标过低,整体上处于不合理和不健康的状态.未来绿色廊道建设除了加大绿色廊道长度、宽度,提高绿带的比例外,应重点加强各廊道间的生态联系;构建以绿带廊道为导向,“三横五纵”绿色河流廊道为骨架、绿色道路廊道为网络的绿廊体系.     

苏南河网水体污染控制工程及其效果分析

以武进港流域的跃进河、陈巷浜、西大河浜为例,开展了河网水体污染控制技术研究。在河道中分别实施生态修复技术,缓流纳污河浜原位增氧-动态生态组合工艺处理农村生活污水技术(ODBP)工艺及ET生化与生态系统组合处理工艺,对3个示范工程的运行效果进行了分析比较,研究了适用于流域河网地区的污染控制技术。负荷削减效果分析表明,3种工艺技术对水中氮、磷等污染物质的去除效果均较好,并具有良好的生态景观效果。通过进一步优化,可形成适合于太湖流域河网地区的水环境质量改善和生态修复的关键技术。     

玉米种子活力近红外光谱智能检测方法研究

为了实现玉米种子活力的快速无损检测,提出利用近红外光谱和BP神经网络来建立玉米种子活力智能检测模型。首先通过人工老化将样本按老化程度分为3种级别,采集样本的近红外光谱。分别通过卷积平滑(S-G)和多元散射校正(MSC)及二者组合的方法消除光谱噪声和去除奇异光谱。然后分别用主成分分析(PCA)和离散多带小波变换(DWT)提取光谱特征,作为BP神经网络的输入。依据预处理及特征提取的不同构建出6种BP神经网络种子活力检测模型。试验结果表明,组合预处理方法与主成分分析特征提取结合构建的模型最优,其识别的准确率为95.0%,平均识别时间为26.25ms。研究结果为玉米种子活力的快速无损检测提供了理论依据和实用方法。