黑龙江省国有林区脆弱异质性家庭对停伐政策的态度及影响因素研究

基于2016年黑龙江省重点国有林区348户家庭的微观调查数据,实证分析黑龙江省国有林区脆弱异质性家庭对停伐政策的态度及影响因素。采用因子分析与综合评价法将348户职工家庭分为脆弱性家庭和非脆弱性家庭,描述性分析2组样本家庭对停伐政策的态度及认知情况,利用多元有序logit模型分析脆弱性与非脆弱性家庭对停伐政策态度的影响因素。结果表明:非脆弱性家庭对停伐政策的了解程度及执行情况的评价均高于脆弱性家庭,脆弱性家庭相对非脆弱性家庭对停伐政策的认可度较高,但是应对风险冲击的能力相对较低。脆弱性家庭和非脆弱性家庭对停伐政策的态度受户主特征、家庭特征以及政策认知特征变量的显著影响,但脆弱性家庭变量参数估计绝对值相对更大,因而停伐政策对脆弱性家庭有着更为敏感和强烈的冲击。     

黄土低山丘陵及坨甸草原区风蚀规律的研究

本文通过对黄土低山丘陵及坨甸草原区248个风蚀图斑资料的分析,运用线性模型理论,对此地区的风蚀规律进行了研究。获得了下垫面各因素与风蚀量关系的数学模型。找出了影响风蚀的主导因素,并系统阐述了植被覆盖度和土地利用类型对风蚀量大小的影响,且与水蚀规律进行了比较分析。     

Ⅳ索12型林业索道在采石场的应用

将Ⅳ索１２型索道应用于狭长工作面的采石场的石材搬运和装车作业。该索道系统中闽林７２１绞盘机的摩擦卷筒、跑车及游动滑车都进行了改装设计使其达到４倍增力起重、双向牵引，最大起重量可达９ｔ。实践表明在特殊困难地形将林业索道用于采石场作业有明显效益。     

七星瓢虫幼虫空间分布型及抽样技术研究

采用颍次分布X~2检验、Iwao平均拥挤度m~*=a+βx和Taylor幂法则S~2=am~b等8种方法,分析了七块麦田中七星瓢虫幼虫的空间分布型,认为其分布型为负二项分布,且聚集的原因是由于个体之间存在着相互吸引,并确定了代表性较强的棋盘式抽样技术,最佳抽样数量为:Q=28.7088/+0.7552。     

基于果实相关性状的桃品种初级核心种质取样策略研究

以国家种质资源圃(北京)编目的558份桃品种的18个形态学和农艺学性状为基本数据,研究了桃品种初级核心种质构建的取样策略,包括总体取样比例的确定及取样方案的选择,以获得最佳的初级核心种质。本试验共设10%～90%9个总体取样比例;取样方案研究包括分组原则和组内取样比例的确定。结果表明,桃初级核心种质的适宜总体取样比例为10%;按品种类群分组结合多样性比例取样为构建桃初级核心种质的最佳取样方案;利用此取样策略从558份桃品种中提取56份作为核心样本,对其代表性进行检测表明所构建的初级核心种质能够很好地代表桃原始种质的遗传多样性。     

Spatio-temporal modelling of broad scale heterogeneity in soil moisture content: a basis for an ecologically meaningful classification of soil landscapes

We describe the classification of landscapes characterised bymineral soil using a model that calculates soil moisture availability on amonthly basis. Scotland is used as a case study area. The model uses potentialsoil moisture deficit, estimated using broad scale (40 × 40 km)climate patterns, in conjunction with meteorological station measurements toobtain finer scale values of climatic soil moisture deficit. Point estimates ofsoil available water are obtained for soil characteristics using appropriatepedotransfer functions, and geostatistical techniques are used to upscale theresults and interpolate to a 1-km grid. Known heterogeneityin soil physical characteristics is used to provide local corrections to thepotential soil moisture deficit, estimated using the climatic variables above.Temporal profiles of monthly water content are modelled for each1-km location and classified into six classes usingunsupervised cluster analysis. The spatial distribution of these classesreflects regional variations in the availability of moisture and energy, onwhich finer-grained topographic patterns are superimposed. In the case study,the broad scale spatial heterogeneity of heathlands and grasslands on mineralsoils in Scotland is shown to be strongly related to the soil moistureclassification. The results can be used in studies investigating the patternsofdistribution of communities at the landscape and regional scale.This revised version was published online in May 2005 with corrections to the Cover Date.     

基于生物量的冬小麦穗部主要形态参数模型

冬小麦穗部形态结构模型是功能–结构小麦模型的重要研究内容。以济麦22、泰农18和鲁原502为材料,于2013—2014和2014—2015年度开展了品种和施氮试验。结合2013—2014年数据,分析穗部主要形态参数与器官生物量的定量关系及形态参数间的内在联系,构建了冬小麦穗部主要形态结构模型。经2014—2015年小麦生长数据检验,除穗长模型精度略低外,穗宽、穗厚、颖壳长、颖壳宽、颖壳厚、籽粒长、籽粒宽和籽粒厚模型精度均较高,所建模型可较好模拟不同品种与施氮水平冬小麦穗部主要形态结构。     

基于SEPLS模型的GIAHS恢复力评估框架及其在保护成效评估中的应用

由联合国粮农组织认定的全球重要农业文化遗产(GIAHS)是一类典型的社会生态生产景观(SEPLS),在传统知识传承保护、粮食与食物安全保障、农业生物多样性保护、气候变化应对等诸多方面具有重要意义。为了更好、更有效地开展GIAHS保护及管理工作,本文在分析GIAHS评估重要性和恢复力概念的基础上,以联合国大学(UNU)等团队开发的社会生态生产景观恢复力评估框架(SEPLS模型)为基础,构建了GIAHS恢复力评估框架(GIAHS-RAF),明确了其评估及计算过程。并以中国第1个GIAHS项目——浙江青田稻鱼共生系统(Qingtian Rice-Fish Culture System in Zhejiang Province, RFC)为例,通过对核心保护区——龙现村在2004年(GIAHS项目授牌前)和2016年(GIAHS授牌11年)的恢复力状况进行评估,探讨模型在GIAHS保护成效评估中的适用性。研究结果显示:1)2016年龙现村恢复力整体状况相对较弱,各项资本评估得分为:物质资本(0.75)经济资本(0.63)人类资本(0.61)社会资本(0.57)自然资本(0.38);2)虽然农户收入来源多样且社会经济基础设施能较好地满足社区需求,但是遗产地内部农业物种较少,农户对于系统提供的粮食多样性尚不是非常满意; 3)相较于2004年,经过11年的保护工作,研究区恢复力有所提高,说明GIAHS项目的实施对该遗产的恢复力有积极影响,尤其是物质资本和经济资本两方面。评估结果与该区域相关研究结果及实地调查情况一致,说明所构建的GIAHS恢复力评估框架可以很好地应用于对GIAHS项目及其他相关农业文化遗产的保护成效评估工作。     

Performance of DSSAT-Nwheat across a wide range of current and future growing conditions

Crop models are widely used in agricultural impact studies. However, many studies have reported large uncertainties from single-model-based simulation analyses, suggesting the need for multi-model simulation capabilities. In this study, the APSIM-Nwheat model was integrated into the Decision Support System for Agro-technology (DSSAT), which already includes two wheat models, to create multi-model simulation capabilities for wheat cropping systems analysis. The new model in DSSAT (DSSAT-Nwheat) was evaluated using more than 1000 observations from field experiments of 65 treatments, which included a wide range of nitrogen fertilizer applications, water supply (irrigation and rainout shelter), planting dates, elevated atmospheric CO₂ concentrations, temperature variations, cultivars, and soil types in diverse climatic regions that represented the main wheat growing areas of the world.DSSAT-Nwheat reproduced the observed grain yields well with an overall root mean square deviation (RMSD) of 0.89 t/ha (13%). Nitrogen applications, water supply, and planting dates had large effects on observed biomass and grain yields, and the model reproduced these crop responses well. Crop total biomass and nitrogen uptake were reproduced well despite relatively poor simulations of observed leaf area measurements during the growing season. The low sensitivity of biomass simulations to poor simulations of leaf area index (LAI) were due to little changes in intercepted solar radiation at LAI >3 and water and nitrogen stress often limiting photosynthesis and growth rather than light interception at low LAI.The responses of DSSAT-Nwheat to temperature variations and elevated atmospheric CO₂ concentrations were close to observed responses. When compared with the two other DSSAT-wheat models (CERES and CROPSIM), these responses were similar, except for the responses to hot environments, due to different approaches in modeling heat stress effects.The comprehensive evaluation of the DSSAT-Nwheat model with field measurements, including a comparison with two other DSSAT-wheat models, created a multi-model simulation platform that allows the quantification of model uncertainties in wheat impact assessments.