人类活动影响下科尔沁沙地沙漠化动态的敏感性分析及灰色预测

利用90年代1◊25万和1◊50万的TM遥感影像及GIS获得的数据,结合该区70、80年代遥感调查数据,分析了科尔沁地区6个县的土地覆盖类型和潜在沙漠化动态及敏感因子。结果表明,1980～1990年该区的沙化面积从53%扩大到70%,林地下降10.7%,草地增加8.38%,主要为低覆盖草地。由于10年来人口密度增加了10人·km^-2,耕地平均增加了7%,人口增加和活动是土地覆盖变化的敏感性因子。分析该区沙漠化的自然因素表明气候变化导致沙漠化的正逆过程,人类活动是近代该区沙漠化加剧的直接原因。灰色预测表明该地区2000年以后人口增加,而沙漠化呈增加和减少两种趋势.     

稻飞虱预报模型及防治技术

应用回归分析法,对江苏省高邮市１９８３～１９９７年共１５年稻飞虱发生程度的历史观测资料和气象资料进行了分析,建立了中、短期预测模型,经历史资料回验,符合率８５％以上。并提出规范化药剂防治策略及技术。     

Use of Growth Indices in Markov Chain Models for Crop Yield Forecasting

An improved Markov chain model has been developed for forecasting of sugarcane yields in which growth indices of biometrical characters based on data from two stages simultaneously have been utilised. Comparisons were also made with the models in use viz. the regression model and the first order Markov chain model.     

Modelling the effects of temperature and wetness on the polycyclic phase of Stemphylium vesicarium,the pathogen causing purple spot on asparagus (Asparagus officinalis L.)

The polycyclic phase of Stemphylium vesicarium is the key factor for the forecast and integrated control of purple spot on asparagus. The annual dynamics of airborne conidia were determined under field conditions by conidia traps. From 2013 to 2015, conidia became airborne at the earliest at mid‐July, but the number trapped was considerably enhanced only after mid‐August, early September. The cumulative percentage of trapped conidia was best described using a logistic function depending on the daily temperature sum (base 0°C) accumulated only on days with >0.2 mm of rainfall (R² = .81). The germination of conidia was modelled by a generalized beta‐modified Chapman Richards function, and the germ tube length was modelled by a generalized beta‐power function. Conidia germinated in a wide temperature range, with an optimum at 23.3°C, whereas germ tube length had a narrow nearly optimum temperature range around 28.7°C, which indicates that infection by conidia is more restricted by germ tube growth than by germination. The effect of temperature on the number of lesions produced by two strains on green asparagus spears had the narrowest optimum range (optimum at 21.9°C) of all parts of the polycyclic phase. In plant tissue, the spread of the fungus depends on the mycelium growth. The mycelium growth of the four strains, which was modelled with data from a petri dish experiment, had an optimum temperature at 24.7°C.     

起伏型时间序列分析方法在害虫测报上的应用

介绍了起伏型时间序列（analysisforwavetypetimeseries）害虫预测方法。对安徽省凤阳县稻纵卷叶螟四（2）代蛾主峰高峰日进行建模预测,对历史资料的拟合和1989、1990两年的试报,结果令人满意。这是一种新的时间序列分析法。     

玉米生长条件下农田土壤水分动态预报方法的研究

依据理论分析和田间实测资料,提出了玉米生长条件下农田土壤水分动态预报模型,论述了模型中参数的测取方法,经初步应用结果表明,该模型预报玉米土壤水分动态具有较高的精度。     

莎车巴旦姆物候期对气象条件的响应及花期预测模型

利用莎车县农业气象试验站2008—2013年巴旦姆物候期和同期气象观测资料,分析了巴旦姆物候期的变化特征以及气温、日照时数对物候期的影响.结果表明：巴旦姆花期之前的物候期始日之间均呈正相关,与花期之后的物候期始日的相关性大多较小,花芽膨大早迟与休眠期、生长期天数分别呈极显著的正相关和负相关.以果实成熟期为界,气温对之前、之后物候期间隔日数的影响分别为负相关和正相关,日照时数与物候期间隔日数大多为正相关.果实成熟 叶变色始期间隔日数对平均最高气温以及花序出现 开花末期、叶变色始期 落叶末期间隔日数对日照时数存在明显的响应.当巴旦姆休眠期符合日平均气温-3.0～-7.5 ℃的天数满30 d后,经过17～28 d将进入花芽萌动期.花芽萌动期、开花始期、叶变色始期和落叶末期的始日分别与首个候平均气温≥4 ℃且候平均最高气温≥12 ℃、春季侯平均气温≥14 ℃且侯平均最高气温≥22 ℃、秋季首个侯平均气温≤10 ℃且侯平均最高气温≤18 ℃和冬季首个侯平均气温≤1.9 ℃的候序一一对应.利用偏最小二乘法回归分析,建立巴旦姆盛花期始日预测模型,经过检验模型效果较好.     

稻飞虱迁飞种群的上灯行为节律研究

【目的】明确稻飞虱迁飞种群的上灯行为节律,以指导其大田迁入种群和迁出种群的发生预测与灾变预警。【方法】本研究运用逐时自动灯诱装置对2010和2011连续两年稻飞虱迁飞种群的上灯行为节律进行了系统研究。【结果】灰飞虱Laodelphax striatellus迁飞种群上灯始见期和灯诱虫量年际间差异不明显,白背飞虱Sogatella furcifera和褐飞虱Nilaparvata lugens迁飞过境种群上灯始见期和灯诱虫量年际间差异较大。此外,灰飞虱迁飞种群的特大高峰期和高峰期逐时灯诱虫量百分比与一般上灯期和零星上灯期相比突出了晨暮双峰型中的暮峰型上灯行为特点;白背飞虱迁飞种群特大高峰期逐时灯诱虫量百分比与高峰期和一般期相比突出了晨暮双峰型中的晨峰型生物学特性。【结论】稻飞虱迁飞种群的上灯行为节律存在种的特异性,这一行为节律除了受环境因素的影响外主要与其生物学特性有关。     

Why less complexity produces better forecasts: an independent data evaluation of kelp habitat models

Understanding how species are distributed in the environment is increasingly important for natural resource management, particularly for keystone and habitat – forming species, and those of conservation concern. Habitat suitability models are fundamental to developing this understanding; however their use in management continues to be limited due to often‐vague model objectives and inadequate evaluation methods. Along the Northeast Pacific coast, canopy kelps (Macrocystis pyrifera and Nereocystis luetkeana) provide biogenic habitat and considerable primary production to nearshore ecosystems. We investigated the distribution of these species by examining a series of increasingly complex habitat suitability models ranging from process‐based models based on species’ ecology to complex generalised additive models applied to purpose‐collected survey data. Seeking empirical limits to model complexity, we explored the relationship between model complexity and forecast skill, measured using both cross‐validation and independent data evaluation. Our analysis confirmed the importance of predictors used in models of coastal kelp distributions developed elsewhere (i.e. depth, bottom type, bottom slope, and exposure); it also identified additional important factors including salinity, and potential interactions between exposure and salinity, and slope and tidal energy. Comparative results showed how cross‐validation can lead to over‐fitting, while independent data evaluation clearly identified the appropriate model complexity for generating habitat forecasts. Our results also illustrate that, depending on the evaluation data, predictions from simpler models can out‐perform those from more complex models. Collectively, the insights from evaluating multiple models with multiple data sets contribute to the holistic assessment of model forecast skill. The continued development of methods and metrics for evaluating model forecasts with independent data, and the explicit consideration of model objectives and assumptions, promise to increase the utility of model forecasts to decision makers.