1978—2018年中国农村环境管理政策演进特征——基于206份政策文本的量化分析

基于手工搜集的1978—2018年中国政府颁布的206份农村环境管理政策文本，从政策发布年度、政策发布主体、政策发布形式、政策作用对象、政策工具及政策效力6个维度构建分析框架，运用政策文献计量和内容分析方法分析了中国农村环境管理政策的演进特征。结果表明:1978年改革开放以来，中国农村环境管理政策在数量上呈整体持续上升态势；农村环境管理政策经历了探索起步(1978—1989年)、初步形成(1990—2004年)、快速发展(2005—2013年)和全面推进(2014年以后)4个阶段的演进；政策发布主体的行政级别较高且呈现多元化特征，政策联合决策程度高，但政策之间统筹性和协调性较低；政策绝大多数以通知、意见等形式发出，缺乏权威性和规范性；政策的着力点主要在原生态保护层面，对农村人居环境整治的重视程度不够；命令控制型政策是政府最为偏好的农村环境管理政策工具，经济激励型、信息公开型和自愿参与型政策工具使用不足；政策整体效力的提升主要由政策发布数量驱动，政策反馈不足、政策措施较少和政策目标量化程度低是导致政策平均效力较低的主要原因。     

基于能值分析京郊蔬菜不同生产经营方式的生态经济可持续性评价

利用能值理论和经济投入、产出分析方法,对北京郊区农户常规种植、企业常规种植和企业有机种植3种大棚蔬菜的生态经济可持续性进行研究。结果表明:在能值评价方面,企业有机种植模式能值年总投入为6.81×10~(16)sej/hm~2,低于农户常规种植模式(1.19×10~(17)sej/hm~2)和企业常规种植模式(8.53×10~(16)sej/hm~2);能值投资率为44.20,分别是农户常规种植和企业常规种植模式的2.41和3.81;环境负载率为2.14,低于农户常规种植模式(3.76)与企业常规种植模式(6.29);可持续发展指数为0.48,高于农户常规种植模式的0.28和企业常规种植模式的0.19。在经济方面,企业有机种植模式的利润(1.45×10~6元/hm~2)高于农户常规种植模式(3.34×10~5元/hm~2)和企业常规种植模式(负利润)。综合能值与经济2个方面,企业有机种植模式是京郊大棚蔬菜的3种模式中生态经济可持续性最优的模式。     

提高烟叶委托分选质量的管理措施

为确保委托方烟叶原料分选质量的稳定性，针对复烤企业承担品牌原料均质化加工要求，积极探索在管理过程中提高烟叶委托分选质量的有效途径,切实加强烟叶分选质量的全程控制，提升复烤企业为委托方品牌烟叶挑选的服务水平。     

冀南地区巨峰葡萄高产高效管理规程

本文针对冀南防寒地区巨峰葡萄管理方式进行了调研统计,根据葡萄的产量和表现,系统地对巨峰葡萄高产、优质、高效的管理技术进行了研究,总结了一套高产高效的管理规程,主要包括秋季剪枝、冬季防寒填埋等栽培管理、养分管理、病虫害防治等方面内容,以期为种植户提供参考。     

校园网络舆情视域下高职院校学生党员教育管理体系构建研究

高职院校学生党员思想培养是校园党务工作者的重要任务。随着互联网的快速发展,高职院校学生党员成为网络阵地的新生力量。新媒体下网络舆情因其自由性、隐秘性、多样性等特点,因此党务工作也应与时俱进,重视校园网络舆情,构建合理的管理体系,进而强化对学生党员的教育管理工作。     

贵州省易地扶贫搬迁的动力机制调查研究——以织金县和思南县为例

易地扶贫搬迁工作已顺利开展多年，贵州省农民因此受益，但搬迁后如何保障农民生计问题变得尤为重要。通过分析贵州省牛场镇和塘头镇易地扶贫搬迁的实战经验，发现贵州易地扶贫搬迁中存在多动力协调推进、动力主体多元化、扶贫方式多样化、配套措施及时落实的动力机制，两地在搬迁中的共性为:选址科学、发展特色经济、推进配套政策。     

Changing how we approach fisheries: A first attempt at an operational framework for ecosystem approaches to fisheries management

The increasing need to account for the many factors that influence fish population dynamics, particularly those external to the population, has led to repeated calls for an ecosystem approach to fisheries management (EAFM). Yet systematically and clearly addressing these factors, and hence implementing EAFM, has suffered from a lack of clear operational guidance. Here, we propose 13 main factors (shift in location, migration route or timing, overfishing (three types), decrease in physiology, increase in predation, increase in competition, decrease in prey availability, increase in disease or parasites and a decline in habitat quality or habitat quantity) that can negatively influence fish populations via mechanisms readily observable in ~20 population features. Using these features as part of a diagnostic framework, we develop flow charts that link probable mechanism(s) underlying population change to the most judicious management actions. We then apply the framework for example case studies that have well‐known and documented population dynamics. To our knowledge, this is the first attempt to provide a clearly defined matrix of all the probable responses to the most common factors influencing fish populations, and to examine possible diagnostics simultaneously, comparatively and relatively in an attempt to elucidate the most probable mechanisms responsible. The framework we propose aims to operationalize EAFM, thereby not only better diagnosing factors influencing fish populations, but also suggesting the most appropriate management interventions, and ultimately leading to improved fisheries. We assert the framework proposed should result in both better use of limited analytical and observational resources and more tailored and effective management actions.     

Evolution of marine fisheries management in China from 1949 to 2019: How did China get here and where does China go next?

China is the world’s biggest fishing nation and a major player in the global seafood trade. Its fisheries development can decisively influence the global seafood trade, food security and marine conservation. In recent years, significant changes have taken place in China’s fisheries management priorities, policies and regulations. In this paper, we review the evolving fisheries management practices in China to delineate changes in the management policies, methods and their performances from 1949 to 2019. We determined that the following issues impede the development, implementation and enforcement of fisheries policies and regulations, namely the large size of the fishing fleet, large and poorly organized fisheries population, the “hidden” fishing capacity, uniform management approaches that sometimes fail to account for local conditions, lack of clearly defined and allocated fishing rights, limited data quality and availability, insufficient fisheries monitoring programmes, absence of a robust scientific input framework and insufficient stakeholder involvement. Combining those problems with China’s current management initiatives, we propose recommendations for China’s future fisheries reforms. We hope this paper can inform China’s marine fisheries policies and provide valuable references for further researches related to China’s sustainable fisheries management.     

生态放养鸡饲养管理技术

我国农业经济快速发展,养殖工作的重要性变得更为突出,其中以生态放养鸡的饲养管理工作最为重要。但是在生态放养鸡的饲养管理工作开展过程中,却发现存在一定的问题,这些问题来自于人为及自然等2个方面,导致生态放养鸡的饲养管理技术没有从根本上得到最大程度的提升。养殖者应对生态放养鸡饲养管理工作的开展予以全面化重视,只有确保相关的技术要点得到实现,才能提升生态鸡的养殖水平。     

A novel approach to estimating the competitive ability of Cirsium arvense in cereals using unmanned aerial vehicle imagery

Eight experiments were carried out in Denmark to determine the yield loss of spring barley due to Cirsium arvense in farmers' fields and to suggest and evaluate a novel approach for quantifying C. arvense infestation in large plots. Literature about the competitive ability of C. arvense is old, scattered and inconclusive, and existing models for estimating crop yield loss are based on data from North America. This study showed that C. arvense coverage could be quantified from unmanned aerial vehicle imagery using a manual image analysis procedure. This gave similar results as scoring the coverage. Yield loss of spring barley due to C. arvense infestation assessed at harvest was given by Y = 100·(1−exp(−0.00170·X)) where Y is the percentage of crop yield loss and X is the percentage of C. arvense coverage. The yield loss was much lower than estimates from models that have been developed in North America. It is speculated that the main reason for this is the later emergence of C. arvense than the crop due to lower soil temperatures in spring. Grain moisture increased linearly with C. arvense coverage: M = 0.0310·X where M is the proportional (%) increase in grain moisture and X is the proportion (%) of C. arvense coverage. Automated image analysis procedures are needed to estimate C. arvense coverage on field scales, and further experiments are needed to reveal whether the low competitive ability of C. arvense found in this study is representative for Northern Europe.