温度与昆虫内禀增长率关系模型的比较

数学模型可用于反映温度对昆虫生长速率的动态变化,为选择一个对害虫发生预测具有重要意义的通用性模型,选择Beta、Briére、Ratkowsky和Lobry-Rosso-Flandrois(LRF)4个非线性模型分别对8组不同温度下昆虫和螨类内禀增长率数据集进行拟合,并比较模型拟合效果的优劣。结果表明:Ratkowsky模型对8组数据的拟合优度总体表现最好,其次为LRF模型和Beta模型,而Briére模型表现欠佳;Ratkowsky模型对低温阈值和高温阈值的估计较其它3个模型更为可靠。Ratkowsky模型不仅可以用于描述温度对细菌种群增长速率的影响,还可应用于描述温度对昆虫和螨类内禀增长率的影响。     

Validation of predictive empirical weed emergence models of Abutilon theophrasti Medik based on intercontinental data

Good weed management relies on the proper timing of weed control practices in relation to weed emergence dynamics. Therefore, the development of models that predict the timing of emergence may help provide growers with tools to make better weed management decisions. The aim of this study was to validate and compare two previously published predictive empirical thermal time models of the emergence of Abutilon theophrasti growing in maize with data sets from the USA and Europe, and test the hypothesis that a robust and general weed emergence model can be developed for this species. Previously developed Weibull and Logistic models were validated against new data sets collected from 11 site-years, using four measures of validation. Our results indicated that predictions made with the Weibull model were more reliable than those made with the Logistic model. However, Weibull model results still contained appreciable biases that prevent its use as a general model of A. theophrasti emergence. Our findings highlight the need to develop more accurate models if the ultimate goal is to make more precise predictions of weed seedling emergence globally to provide growers with universally consistent tools to make better weed management decisions.     

The Validation of Pesticide Leaching Models

The validation of pesticide leaching models presents particular problems where the number of model predictions is far in excess of the observed data. Normally, however, there are more frequent field observations for other parameters (notably the site hydrology) than for pesticide concentrations in either water or soil. A five-stage validation procedure which takes advantage of the most frequently available observations and which tests each of the components of the model in a cumulative way, is thus advocated: Stage 1: Parameterisation of the model using only independently measured parameters. Stage 2: Hydrological validation: the validation of the predictions of water movement and water content of the soil. Stage 3: Solute movement validation: where field data are available for solutes other than pesticide, the model should first be validated for them, especially if they are more abundant than the pesticide observations. Conserved solutes such as chloride or bromide are preferred, although nitrate may be used for short periods. Stage 4: Pesticide fate in the soil: models should use parameters of pesticide fate derived from independent studies. Stage 5: Pesticide leaching: only in the last stage are the relatively small number of pesticide observations compared with the model predictions with respect to patterns and orders of magnitude of occurrence. With this scheme, the results of each stage are carried forward to the next, and confidence in the model is built with each stage. This is illustrated using the CRACK-P model and hydrological, nitrate and pesticide data from the Brimstone Farm Experiment Oxfordshire, UK.     

Simulation of damage in winter wheat caused by the grain aphid Sitobion avenae. 3. Calculation of damage at various attainable yield levels

A dynamic, process-based simulation model is used to evaluate the effect of injury bySitobion avenae F. on yield of winter wheat at a range of attainable yield levels. The attainable yield is defined as the yield in the absence of pests and diseases, at the prevailing temperature and radiation and the available amount of soil nitrogen. Water limitation is not taken into account. Only the period from flowering to ripeness is considered. Aphid infestation intensity is expressed in aphid-days, the integral of aphid density (tiller^–1) over time (day). The calculations show that damage per aphid-day decreases from flowering to ripeness because damage caused by honey-dew decreases with advancing crop development stage while damage caused by aphid feeding is about constant. Damage per aphid-day during a particular period of crop development increases in a nearly linear fashion with the attainable yield level. At attainable yield levels over approximately 9000 kg ha^–1 and until crop development stage early milky ripe (DC 73), however, damage per aphid-day increases at a higher rate with the attainable yield level as compared to lower yield levels. The crop-physiological causes are discussed.Regression models are constructed that relate simulated aphid damage both during various periods of crop development and averaged over the entire post-anthesis phase, to the simulated attainable yield level. The accuracy of these simulation-based regression models and five published models of damage in winter wheat caused byS. avenae is evaluated using 21 data sets, obtained in experiments carried out between 1973 and 1984 in the Netherlands. Attention is focussed on two aspects of model accuracy: the agreement between predicted and measured damage and the size of the error in model predictions. In both aspects the simulation-based regression models are as good as the best published empirical models.     

Modeling temporal progress of plant diseases

A model for describing temporal progress of plant diseases is presented. The model (termed a ‘mixed’ model) coincides in two special cases with the logistic and the monomolecular models introduced by Vanderplank. The mixed model is implemented using some data available on the spread of zucchini yellow mosaic virus (ZYMV) from a field experiment in Israel.     

植物病理学中常见数据的统计分析方法

 数据统计分析不充分或不正确,是导致中国科研工作者在国际期刊投稿中遭拒的主要原因之一。过去20年,统计方法学及计算机软件在统计应用方面已有重大进展。但是,大多数中国植物病理学家仍然使用传统的方差分析或普通的分析方法去分析一些数据,而这些数据其实可用更合适的方法分析。本文简要介绍一些适于植物病理学常见数据的统计分析方法,希望对广大科研工作者有所帮助,也希望加强与应用统计学家的科研合作。     

基于4种生态位模型的长芒苋潜在适生区预测

恶性入侵杂草长芒苋Amaranthus palmeri S.Watson对农业生产和生物多样性造成严重威胁。预测其潜在适生区对粮食安全和生物多样性保护至关重要。不同模型由于算法不同对长芒苋潜在适生区的预测结果存在差异。本研究综合4种生态位模型(MaxEnt、GARP、BIOCLIM和DOMAIN)预测长芒苋在我国的潜在适生区以提高预测准确性。结果表明,4种模型的平均AUC值均大于0.85。MaxEnt和DOMAIN的平均Kappa值大于0.81;BIOCLIM和GARP的平均Kappa值大于0.69。MaxEnt的预测精度和稳定性要略胜一筹。BIOCLIM和MaxEnt的预测结果较为收敛,DOMAIN和GARP预测的适生区范围较广,由此预测的长芒苋潜在适生区分别占我国陆地总面积的20.66%和32.38%,48.39%和49.76%。综合预测结果,长芒苋在我国的适生区主要集中在中东部地区,西北和东北地区则是长芒苋存在的边缘环境地区。     

Monte-carlo与NNBR模型结合在年降水量预测中的应用

以内蒙古五原气象站近40 a的降水资料为例,从降水发生的随机性、统计规律性和统计相似性入手,将蒙特卡罗方法(Monte-carlo)和最近邻抽样回归模型(NNBR)结合,对降水量进行预报。Monte-carlo方法的预报结果虽能很好地体现研究区降水发生的随机性和统计的规律性,但却不能准确反映出降水序列之间的排列顺序,使预报序列具有多解性。利用NNBR模型对Monte-carlo的预报序列依据最相似理论重新排列,确定预报序列中各个成员之间的排列次序,从而实现预报序列不仅能体现出研究区内降水序列的统计规律性和相似性,同时也能反映出单一个体出现的随机性。通过检验证明模型具有合理性和较好的适用性。     

应用陆面模式进行干旱监测的过程和实现

在我国,应用陆面模式准实时监测干旱是一种正在发展的监测方法。从模式强迫资料生成,模式运行及结果后处理和干旱监测产品生成3方面,阐述应用CABLE陆面模式进行干旱监测的过程和实现方法。首先,详述了生成强迫资料所需的各种资料及其插值和订正方法。其次,介绍了应用陆面模式干旱监测的等级判断方法,概述了通过Shell语言和NCO(Net CDF Operator)软件实现干旱监测的自动化运行过程。通过对比模式与自校正帕尔默指数(sc_PDSI)对我国北方1997/1998年干旱监测的效果,发现模式监测干旱的起止时间优于sc_PDSI,发生范围较sc_PDSI更加准确,与实际土壤湿度观测资料结果更为一致。研究表明,陆面模式结果能够反映土壤湿度对于历史同一时期的相对干旱程度,是对土壤湿度长时间观测资料不足的有效补充。研究还发现,应用sc_PDSI监测我国南方干旱时,应当进行参数的本地化订正。     

景观生态学中的干扰问题小议

干扰是景观生态学中的重要概念,本文探讨了干扰的定义,认为:干扰是在目标尺度内,改变景观生态过程和生态现象的不连续事件。或者说在目标尺度内,造成生态不整合的不连续事件。同时探讨了干扰的一些基本性质和理论,如干扰-尺度原理、干扰-异质性原理、干扰-稳定性原理和干扰-层系原理等。最后,就尚未成熟的干扰的模型提出一些见解,这可能会成为研究干扰的一种途径。     

作物生产潜力模型研究进展

系统介绍了作物生产潜力的研究方法,评述了该领域在国内外的发展历史及研究现状,探讨了作物生产潜力经验模型和物理模型的优缺点及在应用中存在的问题.在此基础上提出今后作物生产潜力研究的发展方向,认为作物生产潜力研究将从单纯考虑自然因素转向自然因素与社会经济技术因素相结合;机理模型的完善还需要大量相关数据库的组建及相关技术的支持.随着研究工作的不断深入,作物生产潜力研究将在农业生产中发挥更大作用.     

干旱区土壤盐渍化信息遥感建模

以新疆塔里木盆地北缘的渭干河-库车河三角洲绿洲为研究区,利用GF~(-1)与Landsat8 OLI影像数据作为基本数据源,从影像上提取15个盐分指数和5个光谱植被指数,通过灰度关联分析法,对0~10 cm表层土壤含盐量与影像光谱指数进行分析和筛选,确定出与土壤含盐量相关性较高的综合光谱指数,采用多元线性回归,偏最小二乘法回归,支持向量机回归三种方法分别对GF~(-1)与Landsat8 OLI影像构建基于实测数据和影像数据的综合指数土壤含盐量估算模型,并选出最优模型。结果表明:(1)在20个光谱指数中,相关性较好的光谱指数是SR、CSRI、SI、BI、S6、ARVI、SAVI、NDSI,关联系数均达到0.7以上,并基于这8个光谱指数构建综合光谱指数。(2)3种估算模型:基于GF~(-1)多元线性回归模型决定系数R~2为0.6856,高于决定系数R2为0.5142的Landsat8 OLI;偏最小二乘回归模型1~8个主成分,GF~(-1)决定系数2个3个1个,其中2个主成分最高可达0.6104,Landsat决定系数4个3个2个,其中4个主成分最高可达0.549;支持向量机模型3种函数,GF~(-1)决定系数RBFPolynomialLinear,其中RBF函数最高可达0.7969,Landsat决定系数PolynomialRBFLinear,其中Polynomial函数最高可达0.7154。对比3种模型可知,支持向量机回归模型的R2最高,因此该模型相对于多元线性回归和偏最小二乘回归更适于土壤盐渍化估算。     

古气候研究中气候模式的发展与应用

气候模拟是利用模式研究气候演变的学科.根据气候研究的实际需要,产生和发展了大批模式,主要包括大气环流模式(GCMs)、地球系统模式(EMICs)和简单气候模式.3类模式在模拟的时-空尺度和能力上表现出各自的特点,适用的研究领域也有一些差异.运用上述模式分析过去气候变化原因及机理、进一步认识气候系统以及气候政策的制定都发挥了重大作用.各类气候模式在模拟应用过程中都有相应的局限性,应该根据实际应用情况选择合适的模式进行研究应用.     

球孢白僵菌对东亚飞蝗和梨冠网蝽侵染的温湿度效应

环境的温湿度变化对昆虫病原真菌侵染害虫造成直接的影响。本文研究了在不同温湿度变化下,球孢白僵菌Bb2352对梨网蝽和东亚飞蝗侵染率的变化动态与趋势。结果表明,在1.0×10⁷孢子/mL悬浮液接种、25℃饲养条件下,2种不同昆虫的死亡率均随着湿度的增加而增加。经检验湿度效应对死亡率的数量影响吻合时间-剂量-死亡率模型（TDM模型）,拟合得到的新的时间-湿度-死亡率（THM）模型能准确地描述球孢白僵菌Bb2352侵染的湿度效应。THM模型显示,当相对湿度达到85%以上时,梨冠网蝽的死亡率增速明显快于蝗虫;梨冠网蝽死亡率随湿度变化的时间效应参数γ在第8 d（γ8）达到最大,而东亚飞蝗死亡率随湿度变化的时间效应参数γ在第11 d（γ11）达到最大,显示出球孢白僵菌Bb2352侵染不同昆虫的湿度效应有所差异。在温度效应研究中,当环境相对湿度>95%时,菌株Bb2352侵染2种目标昆虫的累计死亡率均在25℃达到最大,增加或降低温度均会降低菌株Bb2352的侵染效率。Logistic模型拟合显示该模型能准确反映球孢白僵菌Bb2352侵染目标害虫的温度效应。本文中湿度THM模型和温度Logistic模型的构建是数学描述昆虫病原真菌对害虫侵染温湿度效应的有益尝试。     

土壤传递函数模型的研究进展

研究评述了线性回归、非线性回归、神经网络等方法构建土壤传递函数模型的优缺点,介绍了传递函数模型及其应用不确定性分析中常用的Bootstrap analysis、改进的Monte Carlo、最小二乘法等方法,探讨了输入数据、模型结构和参数对传递函数及其应用不确定性的影响,并指出今后可借鉴分析法里的格林函数法和耦合去耦等方法开展土壤传递函数及其预测不确定性的研究,明确传递函数模型不确定性的主要来源,提高模型的应用效率。     

Applicability of five models to simulate water infiltration into soil with added biochar

As a soil amendment, biochar can reduce soil bulk density, increase soil porosity, and alter soil aggregates and thus affect the infiltration. Researchers have proposed and revised several theoretical models to describe the process of soil infiltration. Although these models have been successfully used to evaluate the soil infiltration in different scenarios in agricultural fields, little effort has been devoted to assess their performances in arid and semi-arid soils after the addition of biochar. A laboratory experiment was performed to study the infiltration characteristics of two typical Loess Plateau soils at three particle sizes(2–1, 1–0.25, and 0.25 mm) and five biochar application amounts(0, 10, 50, 100, and 150 g/kg). The performance of five models(i.e., the Philip model, Kostiakov model, Mezencev model, USDA-NRCS model, and Horton model) in simulating the infiltration process was then evaluated based on the adjusted coefficient of determination and a reduced Chi-Square test. Results indicated that the Horton model best simulated the water-infiltration process in an aeolian sandy soil with added biochar. However, the Mezencev model best simulated the infiltration process in a loamy clay soil(Eum-Orthic Anthrosol). The three-parameter model, i.e., Mezencev and Horton models can better describe the relationship between cumulative infiltration and infiltration time. In conclusion, biochar reduced the soil infiltration capacity of the aeolian sandy soil and increased that of the Eum-Orthic Anthrosol.     

林芝地区小麦条锈菌与气象因子的关系及流行动态模型的构建

为了解西藏林芝地区气象因子对小麦条锈病的影响及其流行动态,2016年采用五点取样法对林芝地区小麦条锈病的发病情况进行监测,通过相关性分析、逐步回归C(p)统计法和线性回归等方法,分析了病情指数与气象因子的关系,并结合时间和病情指数建立了病害预测模型。结果表明,在林芝地区,温度X_1、湿度X_2均与小麦条锈病病情指数Y呈极显著相关,降雨量X_3与病情指数Y呈显著相关;线性回归方程为:Y=-482.5991+19.7494X1+3.7974X2-0.8439X3。根据模拟情况选择的病害流行动态方程为Y=1/e~((0.914t+0.385)),决定系数为0.952,模型的拟合效果较好,表明该模型能够为林芝地区小麦条锈病的预测预报提供有效的参考依据。     

绿洲土地利用变化未来趋势预测及其调控研究

土地利用/覆盖变化(LUCC)是全球变化研究的重要核心问题之一,基于区域和地方尺度的绿洲土地覆盖变化信息的定量提取与模拟预测在干旱区生态环境演变研究中具有重要的价值,也是对全球变化研究的重要补充。选择干旱区典型绿洲新疆于田地区为研究靶区,对于田绿洲过去近17年土地利用/覆盖动态变化定量研究基础上,利用马尔柯夫—CA模型模拟土地利用的动态演变过程,定量分析其演变的特点和预测其未来的演变趋势,以便为未来绿洲区域人口、资源与环境可持续发展,进行合理化调控奠定基础。     

新疆防沙林带优化模式的研究

在定位观测和调查基础上,本文研究了不同结构和类型防沙林带的防阻沙效能和特点,应用数量化理论公式,采用林带结构、疏透度、树种组成、带高、带宽和沙源等6个参数,经电算得出单带式防沙林带的阴积沙量、形成的沙丘高度和宽度三个预测模型。采用方差分析和新复极差法(LSR),得出不同结构和类型防沙林带阻沙效能的差异排序为:林草结合单带或多带式——窄带多带式和片林——紧密结构单带式——稀疏结构单带式——通风结构单带式。根据自然条件、流沙危害的程度和水资源特点,提出了准噶尔盆地南缘、塔里木盆地南缘和吐鲁番盆地等3个不同风沙生态区防沙林带的优化模式。