草地划区轮牧饲养原则及设计

为了推进北方草地可持续集约放牧饲养管理,促进完善划区轮牧实验设计及目的,本文总结了放牧国际划区轮牧的10条原则:单位时间的产草量确定载畜率,拔节期指示春季放牧开始时间,开始恢复再生的时间决定放牧时间天数,放牧间隔日数决定放牧频次,计算确定区块数及区块面积,满足牲畜采食行为,充分利用饲草质量和营养,保证牲畜饮水充足,环境友好、易执行、可操作、有弹性。在此基础上,设计了1个划区轮牧实践参考方案,并论述了划区轮牧目标及管理评价标准,讨论了1条北方草地可持续集约养羊畜牧业的发展途径。     

基于GF-1与Landsat8 OLI影像的作物种植结构与产量分析

作物种植结构监测和估产是精准农业遥感的重点领域,其研究对于指导作物种植结构和制定农业政策具有重要意义。该文以黑龙江省北安市为研究区,以2015年的Landsat8 OLI和多时相GF-1为遥感数据源,基于物候信息和光谱特征确定的农作物识别关键时期和特征参数,构建面向对象的决策树分类模型,开展作物种植结构监测研究;综合植被光谱指数和地面采样数据,采用逐步回归方法建立产量遥感估算模型。结果表明:多源与多时相的遥感数据可以反映不同农作物的季相特征,应用本文所构建的决策树分类模型,作物分类效果较好,总体精度达87.54%,Kappa系数为0.8115;2015年,北安市的主要作物类型为大豆、玉米、水稻和小麦,面积分别为2204、1955、122和19 km~2,其中大豆的种植面积最大,占作物种植面积的51.24%。基于NDVI、EVI和GNDVI构建的多元回归模型为北安市大豆和玉米产量估算最优模型(R~2=0.823 7,均方根误差135.45 g/m~2,精度80.55%);北安市玉米高产区集中分布在西部,大豆的高产区主要分布在东部;2015年北安市玉米和大豆的单产分别为8 659、2 846 kg/hm~2,总产量分别为16.93×10~8、6.27×10~8 kg。利用作物关键物候期的多源多时相遥感数据能够精确高效地提取作物种植结构,构建的产量估算多元回归模型,为精准农业科学发展提供参考。     

Comparing the carbon sequestration capacity of temperate deciduous forests between urban and rural landscapes in central Japan

Urbanisation is increasing tremendously in some parts of the world. Consequently, many rural forests may become depleted, although many opportunities exist for urban forests to increase. However, few studies have quantified the carbon (C) sequestration capacities of urban and rural forests in specific climatic zones. The present study compared carbon sequestration in two temperate deciduous forests located in Nagoya and Toyota, central Japan. The Nagoya University forest represented an urban forest, and a site in Toyota represented a rural forest. The urban forest at Nagoya University had comparatively smaller areas of green space and larger areas of buildings and roads. Land uses for building and road, which are typical of urban areas, result in smaller diurnal temperature ranges but higher air temperature, vapour pressure deficit, and atmospheric carbon dioxide (CO₂) concentration. The urban forest in this study exhibited higher gross ecosystem exchange (GEE), especially in the active growing season from May to September, suggesting the possible effect of CO₂ fertilisation. However, higher air temperatures caused comparatively smaller net ecosystem exchange (NEE) because of higher ecosystem respiration (RE). Although both forests functioned as CO₂ sinks at annual time scales, the rural Toyota forest site (5.43 t C ha^–1 yr^–1) had 36% higher net ecosystem production (NEP=–NEE; the negative sign indicates uptake by the forest ecosystem from the atmosphere) than that at the urban forest. The higher normalised respiration (i.e., RE/GPP ratio; GPP=–GEE where GPP represents gross primary production) at the Nagoya University forest might be attributable to factors associated with the degree of urbanisation. Thus, in temperate forests, factors associated with urbanisation may reduce the atmospheric carbon sink function by accelerating respiration. This is an issue of global interest, as many countries are experiencing rapid urbanisation.     

补光和寡糖添加处理对罗汉松苗木生长的影响

以罗汉松当年生实生苗为对象,通过人工补光延长每天育苗的光照时间,施肥时添加寡糖处理,翌年在控制条件下对越冬苗木进行模拟倒春寒处理,取样调查苗木春季生长和干物质。结果表明,添加寡糖处理对苗高、地径和新生根系数量无影响。添加寡糖、延长光照处理地径和当年生叶长分别提高17%和79%,补光对促进苗高的生长和新生根数量的增加具显著影响;延长光照和添加寡糖对地上部和地下根系的干物质积累均有显著促进,补光并添加寡糖处理的茎干干物质较少,根系干物质较大;添加寡糖、延长光照处理的苗木质量提高。     

黄河三角洲典型潮滩湿地土壤硝态氮和铵态氮的空间分布特征

运用地统计学方法研究了黄河口滨岸潮滩湿地土壤中硝态氮和铵态氮的空间分布格局。结果表明,潮滩湿地土壤NO3--N和NH4+-N的水平变异性在不同土层差异较大,较高的水平变异性主要与其在潮滩湿地良好水分条件下较为活跃的物理运移特性有关;潮滩湿地表层土壤NO3--N的水平分布具有明显的空间结构,符合高斯模型,并具有中等程度的空间相关性;自然结构因素在引起NO3--N空间异质性中的贡献占优,随机因素的影响相对较小;表层土壤NO3--N的空间变异性以向低潮滩延伸且受潮汐涨落影响较大的方向最大;潮滩湿地表层土壤的NO3--N具有明显的空间分布格局,表现出向低潮滩延伸方向形成明显斑块低值区,边缘则形成斑块高值区的特征。微地貌特征和潮汐微域物理扰动强度是导致空间异质性的两个重要随机因素,而水盐条件、土壤类型和潮汐物理扰动是3个重要结构因素。     

关于玉米种植密度的思考与讨论

基于前人的研究成果,结合多年来开展的有关田间试验及生产调研工作,对玉米种植密度及其相关问题进行分析与探讨。研究结果表明,玉米不同性状对种植密度变化的响应存在明显差异,一般越是发育与建成较晚的器官(性状)对密度变化的反应越是敏感。除了玉米品种本身耐密性等因素以外,产量环境是种植密度高低的决定性因素。玉米品种的耐密性应从性状角度予以认识与评判,抗倒伏性和结实性是评判品种耐密性最为重要的两个(类)性状。在玉米新组合初、中级测试时,要设置尽可能偏高的密度。在新育成玉米品种推广之前,应设置多环境×多密度互作试验,以测试出新品种在不同产量环境下的耐密性,明确新品种在每一个具体产量环境类型中的安全生产密度。     

Home gardening in Singapore: A feasibility study on the utilization of the vertical space of retrofitted high-rise public housing apartment buildings to increase urban vegetable self-sufficiency

In land-scarce cities, high-rise apartment buildings may provide vertical spaces for natural-light home gardening along corridors, rooftops, balconies as well as façades. The vertical space can improve not only urban environmental sustainability but also food security. Using an experimental approach, we investigated the food production potential of a high-rise public housing apartment building based on different gardening systems, food crops, and sunlight availability. A gardening prototype system for building corridors was shown to increase the unit area yield of corridor gardening by fivefold compared to a commercial trough planter system. Additionally, this commercial trough planter system was mainly for leafy vegetable production, whereas the gardening prototype system for corridors is also suitable for climbing crops, such as legumes and cucurbits. Nevertheless, because of the limited space along corridors of the apartment building and the relatively low-light levels on average, corridor gardening was estimated to meet only 0.5 % of the demand for vegetables of the residents living in the apartment building. Rooftop gardening with shallow growing medium (depth < 15 cm) was estimated to meet 3 % of demand, and façade gardening 43 %, given the larger space available. Although the vegetable production potential in this study was estimated based on a particular typology of public housing apartment buildings in Singapore, our results showed that vegetable production in public housing apartment buildings is feasible, and home gardening can produce a substantial amount of vegetables for consumption if well deployed. Governments of highly urbanized cities may wish to invest in better home garden designs for high-rise public housing apartment buildings and encourage residents’ participation in home gardening, which would increase high-rise greenery coverage and improve urban food system resilience. Future studies should also investigate the environmental sustainability and food safety aspects of home gardening in highly urbanized cities.     

Perceptions of cultural ecosystem services of tree-based green infrastructure: A focus group participatory mapping in Zagreb,Croatia

Urban green infrastructure provides city dwellers numerous benefits. Among them, cultural ecosystem services (CES) are distinguished by being easily perceived and essential for people and their well-being. However, not all CES are equally easy to perceive, resulting with some of the CES categories being weakly explored. Research on CES also rarely considers elements of urban green infrastructure other than parks and forests. Therefore, there is a lack of research on different components of urban green infrastructure, especially tree-based, perceived in relation to CES. This paper presents the results of focus group participatory mapping implemented with citizens in the city districts of Zagreb on the perception of five selected CES categories in various types of urban green infrastructure. Our results show that participants perceived 13 different types of tree-based urban green infrastructure as providers of CES. We also distinguish patterns in the perception of CES categories and their connection with types of tree-based urban green infrastructure. Tree lines are perceived as providers of aesthetical experiences. Furthermore, forests and park forests are perceived in relation to place attachment and recreational activities, while parks are versatile and provide all explored CES. Other types that emerged as important were greenways, greenery around residential buildings and educational institutions, which provokes rethinking of a careful planning of the entire repertoire of urban green infrastructure.     

Monthly composites from Sentinel-1 and Sentinel-2 images for regional major crop mapping with Google Earth Engine

Rapid and accurate access to large-scale, high-resolution crop-type distribution maps is important for agricultural management and sustainable agricultural development. Due to the limitations of remote sensing image quality and data processing capabilities, large-scale crop classification is still challenging. This study aimed to map the distribution of crops in Heilongjiang Province using Google Earth Engine(GEE) and Sentinel-1 and Sentinel-2 images. We obtained Sentinel-1 and Sentinel-2 images from all the covered study areas in the critical period for crop growth in 2018(May to September), combined monthly composite images of reflectance bands, vegetation indices and polarization bands as input features, and then performed crop classification using a Random Forest(RF) classifier. The results show that the Sentinel-1 and Sentinel-2 monthly composite images combined with the RF classifier can accurately generate the crop distribution map of the study area, and the overall accuracy(OA) reached 89.75%. Through experiments, we also found that the classification performance using time-series images is significantly better than that using single-period images. Compared with the use of traditional bands only(i.e., the visible and near-infrared bands), the addition of shortwave infrared bands can improve the accuracy of crop classification most significantly, followed by the addition of red-edge bands. Adding common vegetation indices and Sentinel-1 data to the crop classification improved the overall classification accuracy and the OA by 0.2 and 0.6%, respectively, compared to using only the Sentinel-2 reflectance bands. The analysis of timeliness revealed that when the July image is available, the increase in the accuracy of crop classification is the highest. When the Sentinel-1 and Sentinel-2 images for May, June, and July are available, an OA greater than 80% can be achieved. The results of this study are applicable to large-scale, high-resolution crop classification and provide key technologies for remote sensing-based crop classification in small-scale agricultural areas.