琼岛杨一年生播种苗生长节律研究

于2019年5月6日到12月25日对海南省琼岛杨Populus qiongdaoensis一年生播种苗的苗高、地径生长量进行定期观测,采用Logistic方程进行生长进程拟合,研究琼岛杨的苗期生长节律。结果表明,琼岛杨苗高和地径生长都呈现"慢—快—慢"的"S"形生长规律,且苗高、地径生长量与Logistic方程的回归相关性达到极显著水平,其相关系数分别达0.994和0.996。苗高生长速生期约119 d,占生长期的39.67%,占苗高年总生长量的63.77%;地径生长速生期约125 d,占生长期的45.42%,占地径年总生长量的66.15%。     

考虑降雨量不确定的稻麦收割机多类型配置优化

针对降雨量不确定性导致农机合作社配置收割机的数量和类型较为困难的问题,以蚌埠市的一个农机合作社覆盖的稻麦轮作区域为研究对象,拟合降雨量和潮湿耕地(只能由履带式收割机进行收割的耕地)比例的函数关系,采用1987—2016年每年10月份研究地区的降雨量数据仿真新的降雨量,并利用蒙特卡洛仿真方法优化收割机的配置方案,分析降雨不确定情形下农机合作社的收割机类型与数量的最优配置。结果表明:该区域的降雨量与潮湿耕地比例呈现Logistic分布,收割机的最优配置为,履带收割机和轮式收割机的数量均为14辆,最小收割总成本为725.57万元;随着履带收割机价格的降低,农机合作社应对降雨量不确定的能力显著增加。据此认为不同稻麦轮作区域有必要对降雨量和潮湿耕地比例的函数关系进行估算,同时针对该地区水稻收割期降雨量的特点制定合理的农机补助策略,从而帮助农机合作社应对潜在风险。     

Composite site-productivity functions for Northeastern Ontario black spruce

Data from 122 northeastern Ontario plots were used to develop composite site-productivity functions for black spruce (Picea mariana [Mill.] B.S.P.). A logistic model produced the best fit to the data. The resulting equations produce sets of polymorphic site-productivity curves with subsets of three curves, one for each of Ontario's Forest Ecosystem Classification Operational Groups (FEC OGs) 11, 12 and 14. For direct estimates of site productivity, site index was expressed as a function of stand height, age and FEC OG by employing the reciprocal of the logistic model. Application of the resulting equations and tables is demonstrated in an example. The procedures employed may be used to develop ecologically based site-productivity functions for other areas.     

渔场鱼量模型的建立

微分方程的平衡点可分为稳定和不稳定两种。当轻轻扰动平衡点时，系统状态就会剧烈变化。若新的状态决不会回到原平衡点，此点就是不稳定的；相反，如果一个系统在稳定平衡点附近受到干扰，它总是企图回到平衡点，那么此点就是稳定的。用这一数学工具可以解决诸如渔场鱼量等一系列实际问题。     

Analysis of downy mildew data on field pea: an empirical comparison of two logistic models

In the years 2002–2005, special trials concerning the level of infection of pea varieties by downy mildew were performed in Poland. In these trials, the large number of varieties were tested in many locations (environments), separately on reach and light soils. Obtained trial data are unique because of the large scale of the performed investigations and also for the fact that all the observations were made by the same observer. In a paper, two methods of statistical analysis of such (ordered) data are compared.

Several models have been proposed for the statistical interpretation of ordinal data. One of the most popular is the cumulative-type fixed logistic model. In the present work, using two field pea data sets, we considered whether adding random effects to the simple logistic model can improve inference. It was investigated whether there is any difference between the decisions concerning varieties resulting from the simple logistic model and the proposed mixed logistic model. The two models were also compared in terms of goodness of fit. According to two applied goodness-of-fit statistics, the mixed model performed better in all the cases. Statistical analysis (what is important for practical agriculture) enabled identification of the most resistant and the most susceptible variety from the analyzed set of cultivars.     

Methods to interpolate soil categorical variables from profile observations: Lessons from Iran

The paper compares semi-automated interpolation methods to produce soil-class maps from profile observations and by using multiple auxiliary predictors such as terrain parameters, remote sensing indices and similar. The Soil Profile Database of Iran, consisting of 4250 profiles, was used to test different soil-class interpolators. The target variables were soil texture classes and World Reference Base soil groups. The predictors were 6 terrain parameters, 11 MODIS EVI images and 17 physiographic regions (polygon map) of Iran. Four techniques were considered: (a) supervised classification using maximum likelihoods; (b) multinominal logistic regression; (c) regression-kriging on memberships; and (d) classification of taxonomic distances. The predictive capabilities were assessed using a control subset of 30% profiles and the kappa statistics as criterion. Supervised classification and multinominal logistic regression can lead to poor results if soil-classes overlap in the feature space, or if the correlation between the soil-classes and predictors is low. The two other methods have better predictive capabilities, although both are computationally more demanding. For both mapping of texture classes and soil types, the best prediction was achieved using regression-kriging of indicators/memberships (κ = 45%, κ = 54%). In all cases kappa was smaller than 60%, which can be explained by the preferential sampling plan, the poor definition of soil-classes and the high variability of soils. Steps to improve interpolation of soil-class data, by taking into account the fuzziness of classes directly on the field are further discussed.     

重大线性工程建设下山区乡村聚落空间演变

区域重大线性工程建设对传统山区乡村聚落的发展带来深刻的影响，乡村聚落发展步伐被打断或加快，驱动乡村聚落发展演变与重构，对这一影响和演变过程研究，有助于进一步理解区域重大线性工程与社会经济对传统山区乡村发展产生的外部性，为山区乡村振兴政策制定与发展策略选择提供参考。该研究以河北省赤城县大海陀乡为研究对象，基于1999、2009、2019年3期遥感影像数据，结合空间分析、景观格局指数、Voronoi图及Logistic回归模型，科学识别重大线性工程驱动下乡村聚落空间格局演变规律。结果表明：1）大海陀乡的乡村聚落在高速公路建设前后两个阶段表现出散乱式的斑块数量增长型扩张、集聚式的斑块面积增大型扩张的空间格局演变特征，重大线性工程建设加快了乡村聚落的扩张速度，促进了村庄聚落的内部集聚。2）重大线性工程的建设为构建聚落环境提供社会经济支撑，具有瞬时性与外界强干扰性，驱使大海陀乡乡村聚落从自然资源依附到经济社会依附的演变，形成跨域式的影响效应。3）大海陀乡乡村聚落呈现出"要素-结构-功能"的循环演变机制，内外因素的作用下主体行为的多元模式、自然发展演变与外界力量冲击下三生系统的耦合关系是乡村聚落演变的主要驱动力。京津冀一体化背景下，重大线性工程建设是加强城乡要素流通与转变村民生产生活观念的基石，需统筹城乡资源，加强规划引导与整治措施，促进村镇体系重构。     

施肥量对温室滴灌番茄干物质累积、产量及水肥利用的影响

为研究日光温室秋冬茬番茄生育时期干物质生产动态规律,探索高产高效的科学施肥模式,以标准冲施肥(含N量16%,含P_2O_5量5%,含K_2O量19%)为施肥种类,施肥量以N素为基准分为4个肥料处理水平,即F1(高肥)、F2(中肥)、F3(低肥)、F4(不追肥),分析了不同施肥量对日光温室番茄干物质累积、产量和水肥利用的影响。结果表明,番茄产量和水分利用效率(WUE)与施肥量呈"抛物线"关系,当N施量为290.6 kg/hm2(F2)时达到最高值,分别为67 776.93 kg/hm2和49.27 kg/m3,说明适量施肥可提高产量及水分利用效率。但肥料生产效率(PFP)在施肥量为(N)41.4~539.9 kg/hm2范围内呈现负指数降低趋势。植株干物质累积量表现出F2处理F1处理F3处理F4处理。果实干物质累积进程符合logistic函数轨迹,中肥处理比高肥、低肥处理提前进入快速累积期,使快速累积期持续时间比其他处理长1~8 d。全株总干物质转移量对果实贡献率为1.97%~6.96%,说明果实干物质高达90%以上依靠株体自身光合作用填充。因此,番茄结果期加强水肥的供给是必要的。