冬瓜和节瓜种质资源遗传多样性的RAPD分析

采用RAPD分子标记技术对41份冬瓜和节瓜种质资源进行遗传多样性分析。从455条随机引物中筛选出23条能产生稳定多态性扩增谱带的引物用于RAPD分析,共产生143条扩增谱带,其中多态性谱带81条,多态性检测率为56.6%,表明冬瓜和节瓜种质资源在分子水平上具有丰富的遗传多样性。用NTSYSpc软件处理RAPD数据,41份材料间的遗传相似系数在0.60～0.99之间。聚类分析结果可将供试材料分为6大类群9个亚类,主坐标分析可将供试材料分为6大类群10个亚类。两种分类方法的结果基本一致。     

9个品种桑果营养、香气成分与抗氧化活性评价

【目的】为了科学、合理利用果桑品种资源,比较不同桑椹品种间营养、香气成分和抗氧化活性的差异,筛选出适宜深度开发的北方果桑品种。【方法】以河北省主栽的9个品种果桑的果实为材料,采用紫外分光光度法、固相微萃取联合气相色谱-质谱联用法、酶标仪法,对每个品种桑椹的营养、香气成分和抗氧化指标进行检测,并运用SPSS 23.0软件对测定结果进行差异分析及主成分分析(Principal Component Analysis,PCA)。【结果】桂花出汁率(76.754%)和含水率(85.105%)最高,蒙桑可溶性固形物含量(w,后同)(20.383%)、总酸含量(21.365 mg·g^-1)、还原糖含量(68.844%)以及抗坏血酸含量(89.488 mg·g^-1)最高,安椹的总黄酮含量(26.468 mg·g^-1)、总多酚含量(25.190 mg·g^-1)、DPPH清除能力(25.202 mg·g^-1Vc当量)和ABTS清除能力(51.778 mg·g^-1Vc当量)均显...     

黄金宝树幼龄木枝系构型特征及影响因素

为分析黄金宝树(Melaleuca bracteata)幼龄木不同生长高度的枝系构型特征及影响因素,通过统计分析不同高度阶段的枝系构型指标,并采用主成分分析法分析影响枝系构型的因素。结果表明:随着高度的增加,树高、地径、冠幅均值、树冠体积、逐步分枝率1,2与枝径均值对枝系构型的影响趋于上升;总体分枝率、逐步分枝率2,3、逐步分枝率3,4与枝条倾角均值对枝系构型的影响则增减不一。第1主成分的贡献率在23.61%~60.32%间,当高度小于60 cm时,树冠体积、枝径均值及冠幅均值是影响枝系构型的主要影响因素;高度在60~80 cm时,树冠体积和冠幅均值是主要影响因素;高度在80~100cm时,逐步分枝率1,2和总体分枝率是该阶段的主要影响因素;高度在100~120 cm时,逐步分枝率1,2、冠幅均值及枝径均值为主要影响因素。高度超过120 cm时,逐步分枝率1,2的绝对值最大,说明其为该阶段影响枝系构型的主要因素。     

瓠瓜种质资源主要果实性状的主成分与聚类分析

对119份瓠瓜种质的8个主要果实性状进行了主成分分析与聚类分析。结果表明,119份瓠瓜种质的ShannonWeaver多样性信息指数在0.394 8~2.063 6之间,8个果实性状存在较广泛的遗传多样性,其中以果实形状、皮色和单瓜质量的多样性最丰富。主成分分析结果表明,第一、第二、第三、第四主成分的贡献率分别为37.24%、23.33%、14.71%、9.44%,其累计贡献率达到84.72%。聚类分析结果表明,可以将119份瓠瓜种质分为两大类群,分别包含62份和57份种质,其中第一大类群在品质和外观方面均表现较好,可作为瓠瓜育种的基础材料。     

Statistical models of landscape pattern metrics,with applications to regional scale dynamic forest simulations

Forest managers in Canada need to model landscape pattern or spatial configurationoverlarge (100,000 km²) regions. This presents a scalingproblem, as landscape configuration is measured at a high spatial resolution,but a low spatial resolution is indicated for regional simulation. We present astatistical solution to this scaling problem by showing how a wide range oflandscape pattern metrics can be modelled from low resolution data. Our studyarea comprises about 75,000 km² of boreal mixedwoodforest in northeast Alberta, Canada. Within this area we gridded a sample of 84digital forest cover maps, each about 9500 ha in size, to aresolution of 1 ha and used FRAGSTATS to compute a suite oflandscape pattern metrics for each map. We then used multivariate dimensionreduction techniques and canonical correlation analysis to model therelationship between landscape pattern metrics and simpler stand table metricsthat are easily obtained from non-spatial forest inventories. These analyseswere performed on four habitat types common in boreal mixedwood forests: youngdeciduous, old deciduous, white spruce, and mixedwood types. Using only threelandscape variables obtained directly from stand attribute tables (totalhabitatarea, and the mean and standard deviation of habitat patch size), ourstatistical models explained more than 73% of the joint variation in fivelandscape pattern metrics (representing patch shape, forest interior habitat,and patch isolation). By PCA, these five indices captured much of the totalvariability in the rich set of landscape pattern metrics that FRAGSTATS cangenerate. The predictor variables and strengths of association were highlyconsistent across habitat classes. We illustrate the potential use of suchstatistical relationships by simulating the regional, cumulative effects ofwildfire and forest management on the spatial arrangement of forest patches,using non-spatial stand attribute tables.This revised version was published online in May 2005 with corrections to the Cover Date.     

一串红盆栽基质配方筛选正交试验分析

应用正交试验对一串红盆栽生产基质进行了研究,对一串红的13个观测指标进行主成分分析,综合为3个主成分.计算主成分综合得分,作为分析指标进行方差分析.结果表明:泥炭:珍珠岩:蛭石为2:2;2(体积比)为最佳组合.     

Construction and evaluation of a primary core collection of apricot germplasm in China

As the origin center of apricots, China has the richest apricot germplasm resources. The establishment of core collections is very important for a better evaluation and utilization of apricot germplasm. In this study, 1501 apricot accessions from the initial collections in China were used to sample and establish a primary core collection. Data of 18 traits including both quantitative and qualitative were collected and used to design sampling strategy. The overall sampling strategy includes principles for grouping, sampling proportion within group and sampling method from each group. Three sampling proportions 5%, 10% and 15% were used in the study. Our results suggest that 10% was the best entire sampling ratio for primary core collection of apricots. With 10% entire sampling ratio, the optimal sampling strategy was to group samples based on their growing regions, in combination with logarithmic sampling proportion within each group. Using this sampling strategy, we have established a primary core collection with 150 accessions, and the primary core collection can well represent the genetic diversities of the entire collection. The genetic diversity of the apricot primary core collection was further analyzed using Simple Sequence Repeats (SSRs) molecular marker technique. A total of 22 polymorphic specific primers were developed and 196 alleles were detected. The average number of alleles in each locus was 8.9, suggesting that there were very rich genetic variances among the prime core collection. This also confirms that our primary core collection is a good representation of the genetic diversities of the whole collections at DNA level.     

Environmental,historical, and contextual determinants of vegetation cover: a landscape perspective

We formulated and tested models of relationships among determinants of vegetation cover in two agroforested landscapes of eastern North America (Haut Saint-Laurent, Quebec, Canada) that differed by the spatial arrangement of their geomorphic features and intensity of agricultural activities. Our landscape model compared the woody plots of each landscape in terms of the relative influence of environmental attributes, land use history (1958 – 1997), and spatial context (i.e., proximity of similar or contrasting land cover). Our vegetation model evaluated the relative contribution of the same sets of variables to the distributions of herbs, trees, and shrubs. Relationships were assessed using partial Mantel tests and path analyses. Significant environmental and contextual differences were found between the vegetation plots of the two landscapes, but disturbance history was similar. Our vegetation model confirms the dominant effect of historical factors on vegetation patterns. Whereas land-use history overrides environmental and contextual control for trees, herbaceous and shrub species are more sensitive to environmental conditions. Context is determinant only for understory species in older, less-disturbed plots. Results are discussed in relevance to vegetation dynamics in a landscape perspective that integrates interactions between environmental and human influences.     

Spatial and Seasonal Patterns of Cattle Habitat use in a Mountain Wooded Pasture

Management-oriented models of cattle habitat use often treat grazing pressure as a single variable summarizing all cattle activities. This paper addresses the following questions: How does the spatial pattern of cattle effects vary between cattle activities in a highly heterogeneous landscape? Do these patterns change over the grazing season as forage availability decreases? What are the respective roles of natural and management-introduced structures? We estimated the intensity of herbage removal, dung deposition and trampling after each of three grazing periods on a grid of 25 m ×25 m cells covering an entire paddock in the Swiss Jura Mountains. We found no significant positive correlations between cattle effects. Spatial patterns weakened through the season for grazing and trampling, whereas dunging patterns changed little between grazing periods. Redundancy analysis showed that different cattle effects were correlated with different environmental variables and that the importance of management-introduced variables was highest for herbage removal. Autocorrelograms and partial redundancy analyses using principal coordinates of neighbour matrices suggested that dunging patterns were more coarse-grained than the others. Systematic differences in the spatial and seasonal patterns of cattle effects may result in complex interactions with vegetation involving feedback effects through nutrient shift, with strong implications for ecosystem management. In heterogeneous environments, such as pasture-woodland landscapes, spatially explicit models of vegetation dynamics need to model cattle effects separately.     

Effects of changing landscape pattern and U. S. G. S. land cover data variability on ecoregion discrimination across a forest-agriculture gradient

We examined the use of coarse resolution land cover data (USGS LUDA) to accurately discriminate ecoregions and landscape-scale features important to biodiversity monitoring and management. We used land cover composition and landscape indices, correlation and principal components analysis, and comparison with finer-grained Landsat TM data, to assess how well LUDA data discriminate changing patterns across an agriculture-forest gradient in Minnesota, U.S.A. We found LUDA data to be most accurate at general class levels of agriculture and forest dominance (Anderson Level I), but in consistent and limited in ecotonal areas of the gradient and within forested portions of the study region at finer classes (Anderson Level II). We expected LUDA to over-represent major (matrix) cover types and under-represent minor types, but this was not consistent with all classes. 1) Land cover types respond individualistically across the gradient, changing landscape grain as well as their spatial distribution and abundance. 2) Agriculture is not over-represented where it is the dominant land cover type, but forest is over-represented where it is dominant. 3) Individual forest types are under-represented in an open land matrix. 4) Within forested areas, mixed deciduous-coniferous forest is over-represented by several orders of magnitude and the separate conifer and hardwood types under-represented. Across gradual, transitional agriculture-forest areas, LUDA cover class dominance changes abruptly in a stair-step fashion. In general, rare cover types that are discrete, such as forest in agriculture or wetlands or water in forest, are more accurately represented than cover classes having lower contrast with the matrix. Northward across the gradient, important changes in the proportions of conifer and deciduous forest mixtures occur at scales not discriminated by LUDA data. Results suggest that finer-grained data are needed to map within-state ecoregions and discriminate important landscape characteristics. LUDA data, or similar coarse resolution data sources, should be used with caution and the biases fully understood before being applied in regional landscape management. This revised version was published online in July 2006 with corrections to the Cover Date.