Dew amount and its long-term variation in the Kunes River Valley,Northwest China

Dew is an essential water resource for the survival and reproduction of organisms in arid and semi-arid regions. Yet estimating the dew amount and quantifying its long-term variation are challenging. In this study, we elucidate the dew amount and its long-term variation in the Kunes River Valley, Northwest China, based on the measured daily dew amount and reconstructed values (using meteorological data from 1980 to 2021), respectively. Four key results were found: (1) the daily mean dew amount was 0.05 mm during the observation period (4 July-12 August and 13 September-7 October of 2021). In 35 d of the observation period (i.e., 73% of the observation period), the daily dew amount exceeded the threshold (>0.03 mm/d) for microorganisms; (2) air temperature, relative humidity, and wind speed had significant impacts on the daily dew amount based on the relationships between the measured dew amount and meteorological variables; (3) for estimating the daily dew amount, random forest (RF) model outperformed multiple linear regression (MLR) model given its larger R² and lower MAE and RMSE; and (4) the dew amount during June-October and in each month did not vary significantly from 1980 to the beginning of the 21^st century. It then significantly decreased for about a decade, after it increased slightly from 2013 to 2021. For the whole meteorological period of 1980-2021, the dew amount decreased significantly during June-October and in July and September, and there was no significant variation in June, August, and October. Variation in the dew amount in the Kunes River Valley was mainly driven by relative humidity. This study illustrates that RF model can be used to reconstruct long-term variation in the dew amount, which provides valuable information for us to better understand the dew amount and its relationship with climate change.     

黑河中游临泽地区夏季露水的生成

对于降雨稀少的内陆干旱区,露水具有重要的生态学意义.在黑河中游的张掖市临泽县平川镇,于2008年6～9月利用人造面板法对露水进行了连续90d的观测,发现:①只有当露水收集板的温度低于露点时,露水才能生成;②观测期间河岸带共生成露水52次,总生成量为4.26 nn,绿洲内共生成34次,总生成量为1.52 mm,戈壁共生成...     

Effects of shrub species and microhabitats on dew formation in a revegetation-stabilized desert ecosystem in Shapotou,northern China

Dew is an important supplement water source in arid and semi-arid areas. In order to determine the dew formation on different kinds of soils associated with various shrub species and microhabitats, we performed measurement of accumulated dew formation amount and duration in October 2009 in a revegetation-stabilized arid desert ecosystem in Shapotou area, northern China. The results indicated that the accumulated dew formation amount was four times larger at open spaces as compared to under the canopy, and it was nearly twice as much under living Artemisia ordosica plants（L.A.） as compared to under living Caragana korshinskii plants（L.C.）. The opposite characteristics were found for dew duration between different microhabitats. Dew amounts at different vertical heights around the shrub stands were in the order of 50 cm above the canopy〉the canopy edge〉under the canopy. Dew amount continued to increase after dawn, and the proportion of average accumulated dew amount after dawn accounting for the average maximum amount increased from above the canopy to under the canopy. Dew formation duration after sunrise accounted for more than 50% of the total formation duration during the day time. Contrary to the distribution characteristics of dew amount, dew duration after dawn and total dew formation duration during the day time were both highest under the canopy, followed by at the canopy edge and then at 50 cm above the canopy. The portion of dew duration after dawn accounting for the total dew duration during the day time increased from above the canopy to under the canopy. From these results, we may conclude that dew availability as a supplemental water resource for improving the microhabitats in water-limited arid ecosystems is position dependent especially for the plant microhabitats at different stands layers.     

Prediction of stem rust infection favorability, by means of degree-hour wetness duration, for perennial ryegrass seed crops

ABSTRACT A weather-based infection model for stem rust of perennial ryegrass seed crops was developed and tested using data from inoculated bioassay plants in a field environment with monitored weather. The model describes favorability of daily weather as a proportion (0.0 to 1.0) of the maximum possible infection level set by host and inoculum. Moisture duration and temperature are combined in one factor as wet degree-hours (DH(w)) (i.e., degree-hours > 2.0 degrees C summed only over time intervals when) moisture is present). Degree-hours are weighted as a function of temperature, based on observed rates of urediniospore germination. The pathogen Puccinia graminis subsp. graminicola requires favorable conditions of temperature and moisture during the night (dark period) and also at the beginning of the morning (light period), and both periods are included in the model. There is a correction factor for reduced favorability if the dark wet period is interrupted. The model is: proportion of maximum infection = 1 - e((-0.0031) (DHw Index)), where DH(w) Index is the product of interruption-adjusted overnight weighted DH(w) multiplied by morning (first 2 h after sunrise) weighted DH(w). The model can be run easily with measurements from automated dataloggers that record temperature and wetness readings at frequent time intervals. In tests with three independent data sets, the model accounted for 80% of the variance in log(observed infection level) across three orders of magnitude, and the regression lines for predicted and observed values were not significantly different from log(observed) = log(predicted). A simpler version of the model using nonweighted degree hours (>2.0 degrees C) was developed and tested. It performed nearly as well as the weighted-degree-hour model under conditions when temperatures from sunset to 2 h past sunrise were mostly between 4 and 20 degrees C, as is the case during the growing season in the major U.S. production region for cool-season grass seed. The infection model is intended for use in combination with measured or modeled estimates of inoculum level, to derive estimates of daily infection.     

Dew measurement and estimation of rain-fed jujube (Zizyphus jujube Mill) in a semi-arid loess hilly region of China

Dew is an important water source for plants in arid and semi-arid regions. However, information on dew is scarce in such regions. In this study, we explored dew formation, amount, and duration of rain-fed jujube(Zizyphus jujube Mill) trees in a semi-arid loess hilly region of China(i.e., Mizhi County). The data included dew intensity and duration, relative humidity, temperature, and wind speed measured from 26 July to 23 October, 2012 and from 24 June to 17 October, 2013 using a micro-climate system(including dielectric leaf wetness sensors, VP-3 Relative Humidity/Temperature Sensor, High Resolution Rain Gauge, and Davis Cup Anemometer). The results show that atmospheric conditions of relative humidity of 78% and dew point temperature of 1°C–3°C are significantly favorable to dew formation. Compared with the rainfall, dew was characterized by high frequency, strong stability, and long duration. Furthermore, heavy dew accounted for a large proportion of the total amount. The empirical models(i.e., relative humidity model(RH model) and dew point depression model(DPD model)) for daily dew duration estimation performed well at 15-min intervals, with low errors ranging between 1.29 and 1.60 h, respectively. But it should be noted that the models should be calibrated firstly by determining the optimal thresholds of relatively humidity for RH model and dew point depression for DPD model. For rain-fed jujube trees in the semi-arid loess hilly regions of China, the optimal threshold of relative humidity was 78%, and the optimal upper and lower thresholds of dew point depression were 1°C and 5°C, respectively. The study further demonstrates that dew is an important water resource that cannot be ignored for rain-fed jujube trees and may affect water balance at regional scales.     

Simulation of damage in winter wheat caused by the grain aphid Sitobion avenae. 2. Construction and evaluation of a simulation model

To evaluate the relative importance of various components of damage caused by grain aphid (Sitobion avenae F.) populations in winter wheat, a simulation model of crop growth and development is combined with a model of aphid injury. The model applies to the time interval from flowering to ripeness which constitutes the main period of grain aphid immigration and development in winter wheat in the Netherlands. The crop model describes crop growth and development as a function of the prevailing weather and the available amount of soil nitrogen and consists of sink-source relations and distribution functions for carbohydrates and nitrogen. Injury byS. avenae affects crop growth both directly and indirectly. Direct effects on growth are due to aphid feeding. Indirect effects are caused by the aphid excretion product honeydew which affects leaf net carbon dioxide assimilation. Alternative hypotheses on the nature of the direct effects are formulated. Inputs to the model are average daily temperature, daily global radiation, the amount of nitrogen in the soil and the density of the aphid population. The major output is grain weight.The accuracy of the model is assessed by visual and statistical comparison to field data. The accuracy of both crop and damage model is satisfactory except for the final part of the growing season. Then, insufficient information on processes involved in leaf death and the termination of phloem transport to the grains results in overestimation of the rate of grain filling.The consequences of the lack of detailed information on the relation between environmental factors and the effect of honeydew on leaf carbon dioxide assimilation are assessed in a sensitivity analysis.     

Modelling the spatiotemporal dynamics of Phytophthora infestans at a regional scale

Potato late blight caused the Irish Potato Famine and still causes billions of dollars of annual crop damage. Tracking and predicting its spread remains problematic. Growers overspray potato fields with fungicide as a precaution, irrespective of the prevalence or actual risk of the disease. This study created a new weather‐based mathematical model for the spread of late blight at a regional scale using empirical data, and validated it using a novel approach for presence‐only data. The model was tested using a contrapositive ‘proof’ by comparing predicted to actual weather patterns to examine its accuracy. The model was then used to create risk maps showing the likelihood of future outbreaks in the region. Such risk maps can help growers optimize late blight suppression and fungicide use by alerting them to the most probable day at which they are at the most risk, using real‐time weather data from the previous few days. These risk maps would be updated daily to account for conditions needed for sporulation. Overall, this work offers a methodology to understand and model a disease's spread in time and space.     

东北三省春玉米旱灾动态风险评估

干旱演变趋势的不确定性决定了旱灾风险的动态变化特征,如何采用有效的方法探究风险随时间的变化是评估旱灾动态风险的关键。由于干旱发生发展缓慢,长时间尺度数值预报产品精度较低,用于干旱预报有一定的局限性。本研究选用天气发生器随机生成未来逐日气象数据的大量样本预测干旱演变趋势,驱动作物模型评估不同趋势下作物产量因旱损失及动态风险。选取东北三省为研究区,在2012—2017年田间试验数据的基础上,率定及验证APSIM作物模型,利用BCC/RCG-WG天气发生器随机生成未来气象数据,驱动APSIM作物模型模拟春玉米产量因旱损失,计算期望产量因旱损失率,以典型干旱年2000年为例,实时动态评估东北三省春玉米生育期内（5月1日—9月18日）旱灾动态风险。结果表明：（1）APSIM作物模型模拟春玉米播种到开花日数、生育期日数以及产量与试验观测结果决定系数R²均大于0.5,标准均方根误差NRMSE均在10%以下,表明APSIM模型在东北三省模拟春玉米生长效果较好;BCC/RCG-WG天气发生器生成100个气象要素样本与1961—2020年各气象数据年均值R²均在...     

Preinoculation Effects of Light Quantity on Infection Efficiency of Puccinia striiformis and P. triticina on Wheat Seedlings

ABSTRACT In a previous study under controlled conditions, a model was developed to predict the infection efficiency for the wheat leaf and stripe rust fungi based on temperature and dew period during the 24 h after inoculation. The two pathogens differed in their maximum infection efficiency under controlled conditions for temperature and dew period, the infection efficiency was 12 times greater for Puccinia triticina than for P. striiformis. In the present study, the model was validated by field results to predict P. triticina infection efficiency as a function of temperature and dew period only. However, this model failed to predict infection efficiency caused by P. striiformis in the field. The model was adapted to include the effects of light quantity on infection efficiency. Wheat seedlings, grown in climate-controlled rooms and exposed to various regimes of light duration and intensity for 24 h in either field or controlled conditions, were inoculated and incubated in climate-controlled rooms under optimal dew and temperature conditions. Quantity of natural or artificial light (light intensity x duration) received by the plants prior to inoculation enhanced infection efficiency of wheat seedlings inoculated by P. striiformis. Infection efficiency increased from 0.4 to 36% depending on the light quantity according to a Richards' function. For stripe rust, three environmental variables, preinoculation light quantity received by the plants, postinoculation temperature, and postinoculation dew period, were used for fitting a model for infection efficiency measured in the field.     

Characteristics of dew events in an arid artificial oasis cropland and a sub-humid cropland in China

Dew is an important source of water which significantly influences the physiological status of vegetation and the microclimate environment. For quantifying the characteristics of dew events and analyzing the underlying mechanism of dew formation in different ecosystems, we measured, based on the flux-profile method, the amount, frequency and duration of dew events in two croplands, an arid artificial oasis cropland in Zhangye, Gansu province and a sub-humid cropland in Luancheng, Hebei province in China. The results showed that dew events were observed in a total of 69 days in Zhangye, which accounted for 59% of the growing season(from 28 May to 21 September, 2012), while 128 days in Luancheng, which accounted for 79% of the growing season(from 5 April to 13 September, 2008). The frequencies of dew events were 2.8 and 2.4 times of those of precipitation in Zhangye and Luancheng, respectively. In addition, the dew amount reached up to 9.9 and 20.2 mm in Zhangye and Luancheng, which accounted for 9.5% and 4.1% of precipitation, respectively. The average amount of dew was 0.14 and 0.16 mm/night in Zhangye and Luancheng, respectively and the duration of dew events ranged from 0.5 to 12.0 h in the two study sites. Dew amounts were associated with the gradient of atmospheric water vapor concentration and dew duration(P<0.001) in both the two sites. The result implies that dew events play a more important role in crop growth in arid areas in comparison to sub-humid areas considering the dew occurrence frequency and the amount per night.     

毛乌素沙地凝结水动态变化及其影响因子的研究

基于2002年5~10月间运用直接称重法对毛乌素沙地臭柏(Sabina vulgaris Ant.)群落林间空地的0-1.5cm表层土壤凝结水连续观测资料,分析讨论了凝结水的日变化和季节变化特征以及影响凝结水形成的环境因子。结果表明:毛乌素沙地天然臭柏群落内各月均有凝结水发生,并且可从午后持续至翌日清晨,但各月间凝结水量和凝结持续时间有所不同。5月份凝结水持续时间最短,凝结水量也最少;而9月份凝结水持续时间最长,凝结水量也最多。影响毛乌素沙地凝结水形成的主要环境因子有风速、大气相对湿度、气-地温差及其相互作用。其中,风速与凝结量间存在较高相关性,而气温能否趋近或降至露点产生土壤凝结水是决定夜间水分凝结量的一个关键因素。     

Development of ZWIPERO, A Model Forecasting Sporulation and Infection Periods of Onion Downy Mildew based on Meteorological Data

The weather-based forecasting model ZWIPERO was developed by the German Weather Service and determines the risk of sporulation and infection of Peronospora destructor quantitatively based on actual as well as predicted weather data (temperature, relative humidity, leaf wetness, precipitation). The model allows precise planning of disease monitoring and infection-related application of fungicides. ZWIPERO is a more complex mathematical model than the previously published models for downy mildew. In order to operate ZWIPERO independently of the actual field location and season, the time of sunrise and sunset of the location are exactly determined by a subroutine. Another subroutine provides simulated microclimatic input variables based on local production data as well as actual and hourly predicted (up to 4 days) standard weather data. Starting at the time of 'sunrise + 7 h', ZWIPERO calculates the number of sporangia produced, the time of onset of sporangia release, as well as the number of infections possible and the number of sporangia which may survive the day for each 24-h time step. Field evaluations of sporulation periods of downy mildew showed that the simulated micrometeorological input variables are reliable. As the actual plant development, the susceptibility and the disease incidence in the field are not taken into account, ZWIPERO has to be considered primarily as a decision support system for extension services and growers.     

Simulation of apparent infection rate to predict severity of soybean rust using a fuzzy logic system

ABSTRACT Few biologically based models to assess the risk of soybean rust have been developed because of difficulty in estimating variables related to infection rate of the disease. A fuzzy logic system, however, can estimate apparent infection rate by combining meteorological variables and biological criteria pertinent to soybean rust severity. In this study, a fuzzy logic apparent infection rate (FLAIR) model was developed to simulate severity of soybean rust and validated using data from field experiments on two soybean cultivars, TK 5 and G 8587. The FLAIR model estimated daily apparent infection rate of soybean rust and simulated disease severity based on population dynamics. In weekly simulation, the FLAIR model explained >85% of variation in disease severity. In simulation of an entire epidemic period, the FLAIR model was able to predict disease severity accurately once initial values of disease severity were predicted accurately. Our results suggest that a model could be developed to determine apparent infection rate and an initial value of disease severity in advance using forecasted weather data, which would provide accurate prediction of severity of soybean rust before the start of a season.     

黄土高原作物生长模型DSSAT3数据库组建

介绍了DSSAT3模型的结构与功能，组建了黄土高原地区DSSAT3模型气象、土壤和作物品种参数数据库，包含了28个气象台站逐日气象资料数据、60种主要农耕土壤土种特性数据和7个作物136个品种的遗传特性数据，覆盖了黄土高原不同生态类型区。还特别介绍了CERES-小麦和CERES-玉米模型品种遗传特性参数的确定方法与取值范围，为DSSAT3模型在黄土高原地区应用奠定了基础。     

农作物有害生物疫情地理信息系统研究初报

农作物疫情地理信息系统是基于2001、2002年全国农作物有害生物疫情普查开发的。该系统包括空间数据库和属性数据库两部分。空间数据库包括全国1:250 000地图数据和全国范围720个气象站点位置数据。属性数据包括2001、2002年在全国1 300个县约1 000种有害生物调查数据,194个气象站点从1950年到2001年的气象数据。利用地理信息系统软件平台MapInfo及其开发语言MapBasic开发了菜单、对话框等用户界面,可简单方便地完成查询有害生物信息,绘制有害生物发生范围专题图、插值图、每日温度、月均温、害虫年发生世代数估计及有害生物可能分布范围的估计等操作。     

南疆沙漠腹地地温变化特征

利用塔中气象站三年的气象数据,分析了塔中地温的变化特征。结果显示:塔中0～40cm地温年变化规律显著,温度自1月开始迅速上升,在7月达到最高值,达30℃以上,其后又持续下降,冬季最低;80cm以下地温变化平缓,最高、最低温度出现月份逐渐后延,年振幅渐小;在典型晴天、阴天、沙尘天气时,表层地温都是日出前后最低,日出后迅速上升,至午后16时左右达最大值,其后迅速下降,于日落时降至一低值,并在夜间继续缓慢下降;四季0～80cm各层地温夏季﹥秋季﹥春季﹥冬季;天气对地温的影响主要体现在地表温度和浅层地温,至40cm及以下各层几乎无影响,日变化与典型晴天规律相同;阴天和浮尘对地温的影响较小,扬沙和沙尘暴天气对地温影响较大,其影响随深度增加而渐小;各层地温的平均日变化曲线近于正弦曲线,随深度增加地温特征线趋于平缓,极值出现时间逐渐后延。塔中地温的年际、日内变化的逐层性,与沙漠表面风成沙的物理属性有关。     

基于CROPWAT模型的非充分灌溉研究

为验证FAO的CROPWAT模型在非充分灌溉中的适用性和精确性,将民勤棉花和春小麦非充分灌溉的试验方案及当地气象资料输入模型,分析CROPWAT模型在模拟作物蒸发蒸腾量和非充分灌溉对产量影响的模拟效果。结果显示,棉花各生育期日平均蒸发蒸腾量的模拟值和实测值表现出相同的分布规律,但模拟值整体高于实测值0.15~1 mm;模拟非充分灌溉对棉花和春小麦产量的影响时,模拟值和实测值显示出一致的变化规律,将结果进行统计分析,棉花和春小麦的RMSE、EF、CRM分别为20.62%和10.35%、0.98和0.856、-0.00051和-0.0155,说明CROPWAT模型总体模拟效果较好,但模型的执行值较实测值偏高。模拟结果表明,模型在非充分灌溉的研究中有着较好的适用性,但为了使模拟结果更准确,使用前需根据当地实测资料对Kc、Ky等参数进行校正。     

A simple model of pea (Pisum sativum) growth affected by Mycosphaerella pinodes

The effect of epidemics of Mycosphaerella pinodes on crop growth, radiation interception efficiency (RIE) and radiation use efficiency (RUE) was studied in field conditions and the growth of diseased crop was modelled. Natural epidemics were simulated in field plots by dispersion on the ground of barley grains colonized by the fungus. Growth and leaf area index (LAI) were measured in healthy and diseased plots during the growth season. Epidemics affected crop growth mainly by decreasing RUE, with a slight decrease in RIE. This was probably due to the strong effect of M. pinodes on leaf photosynthesis and the lateness of Mycosphaerella blight epidemics on spring pea, which became serious when the canopy was already formed, thus decreasing RIE only by accelerating the senescence of leaves. The data were used to evaluate the performance of a crop growth model for diseased pea crops. The model comprised the decrease in photosynthesis rate in the leaves, the vertical gradient of disease intensity and the differences in photosynthetic function of the various layers of the canopy. This model, validated over 2 years in the field, accurately simulated the crop growth in diseased plots. Thus the decrease in RUE may be accounted for solely by photosynthesis losses in diseased leaves. This simple model may be used for disease management, defining damage thresholds for chemical application and criteria for tolerant variety selection.     

Modelling the effects of weeds on crop production

In most quantitative studies on interplant competition, static regression models are used to describe experimental data. However, the generality of these models is limited. More mechanistic models for interplant competition, which simulate growth and production of species in mixtures on the basis of the underlying physiological processes, have been developed in the past decade. Recently, simulation models for competition between species for light and water were improved and a detailed version was developed for sugarbeet and fat hen (Chenopodium album L.). The model was validated with data sets of five field experiments, in which the effect of fat hen on sugarbeet production was analysed. About 98% of the variation in yield loss between the experiments (which ranged from –6 to 96%) could be explained with the model. Further analysis with the model showed that the period between crop and weed emergence was the main factor causing differences in yield loss between the experiments. Sensitivity analysis showed a strong interaction between the effect of the variables weed density and the period between crop and weed emergence on yield reduction. Different quantitative approaches to crop-weed competition are discussed in view of their practical applicability. Simulations of experiments, where both the weed density and the period between crop and weed emergence were varied over a wide range, showed a close relation between relative leaf cover of the weeds shortly after crop emergence and yield loss. This relation indicates that relative leaf cover of the weeds accounts for both the effect of weed density and the period between crop and weed emergence. This relation has the potential to be developed into a powerful tool for weed-control advisory systems.     

Modelling crop:weed interactions in wheat with ALMANAC

ALMANAC is a dynamic model for plant growth, water balance and soil nitrogen dynamics that can simulate on a daily basis two or more competing species. The simulation of competition for light is based on Beer's law, allowing a different extinction coefficient ( k ) for each species. Light is partitioned between species based on k -values, leaf area index and plant heights. Total hiomass is simulated with radiation use efficiency and grain yield with a harvest index approach, sensitive to water stress. The model simulates competition for water and nutrients based on each species current rooting zone and demand by each species. The effect of crop management on the competition issue can he simulated. The model was evaluated in Dijon (France) using 4 years of experimental data on wheat:oat mixtures, differing in oat ( Avena sativa L.) densities, the period of oat emergence, the date of weed suppression by herbicides and the wheat ( Triticun aestivum L.) genotype. Additional data on oilseed rape ( Brassica nupus L.) and vetch ( Vilcia sauiva L.) competition in spring wheat were also used. The wheat grain yield was reasonably simulated with a root mean square error (RMSE) of 0.10-0.35 t ha^-1. Corresponding values for oats were 0.10-0.55 t ha^-1. The competitiveness of oats, oilseed rape and vetch was correctly simulated. The model appears as a reasonable tool for estimating damage thresholds in integrated weed control programmes.