Sporulation of Pyrenopeziza brassicae (light leaf spot) on oilseed rape (Brassica napus) leaves inoculated with ascospores or conidia at different temperatures and wetness durations

In controlled environment experiments, sporulation of Pyrenopeziza brassicae was observed on leaves of oilseed rape inoculated with ascospores or conidia at temperatures from 8 to 20°C at all leaf wetness durations from 6 to 72 h, except after 6 h leaf wetness duration at 8°C. The shortest times from inoculation to first observed sporulation ( l ₀), for both ascospore and conidial inoculum, were 11–12 days at 16°C after 48 h wetness duration. For both ascospore and conidial inoculum (48 h wetness duration), the number of conidia produced per cm² leaf area with sporulation was seven to eight times less at 20°C than at 8, 12 or 16°C. Values of Gompertz parameters c (maximum percentage leaf area with sporulation), r (maximum rate of increase in percentage leaf area with sporulation) and l ₃₇ (days from inoculation to 37% of maximum sporulation), estimated by fitting the equation to the observed data, were linearly related to values predicted by inserting temperature and wetness duration treatment values into existing equations. The observed data were fitted better by logistic equations than by Gompertz equations (which overestimated at low temperatures). For both ascospore and conidial inoculum, the latent period derived from the logistic equation (days from inoculation to 50% of maximum sporulation, l ₅₀) of P. brassicae was generally shortest at 16°C, and increased as temperature increased to 20°C or decreased to 8°C. Minimum numbers of spores needed to produce sporulation on leaves were ≈25 ascospores per leaf and ≈700 conidia per leaf, at 16°C after 48 h leaf wetness duration.     

Simulating evolution of glyphosate resistance in Lolium rigidum II: past, present and future glyphosate use in Australian cropping

Glyphosate is a key component of weed control strategies in Australia and worldwide. Despite widespread and frequent use, evolved resistance to glyphosate is rare. A herbicide resistance model, parameterized for Lolium rigidum has been used to perform a number of simulations to compare predicted rates of evolution of glyphosate resistance under past, present and projected future use strategies. In a 30‐year wheat, lupin, wheat, oilseed rape crop rotation with minimum tillage (100% shallow depth soil disturbance at sowing) and annual use of glyphosate pre‐sowing, L. rigidum control was sustainable with no predicted glyphosate resistance. When the crop establishment system was changed to annual no‐tillage (15% soil disturbance at sowing), glyphosate resistance was predicted in 90% of populations, with resistance becoming apparent after between 10 and 18 years when sowing was delayed. Resistance was predicted in 20% of populations after 25–30 years with early sowing. Risks of glyphosate resistance could be reduced by rotating between no‐tillage and minimum‐tillage establishment systems, or by rotating between glyphosate and paraquat for pre‐sowing weed control. The double knockdown strategy (sequential full rate applications of glyphosate and paraquat) reduced risks of glyphosate and paraquat resistance to <2%. Introduction of glyphosate‐resistant oilseed rape significantly increased predicted risks of glyphosate resistance in no‐tillage systems even when the double knockdown was practised. These increased risks could be offset by high crop sowing rates and weed seed collection at harvest. When no selective herbicides were available in wheat crops, the introduction of glyphosate‐resistant oilseed rape necessitated a return to a minimum‐tillage crop establishment system.     

Predicting effective doses for the joint action of two fungicide applications

A function was derived to predict fungicide efficacy when more than one application of a single active ingredient is made to a crop, given parameters describing the dose–response curves of the component single-spray applications. In the function, a second application is considered to act on that proportion of the total pathogen population which was uncontrollable at the time of the first application (represented by the lower asymptote of the dose–response curve for the first treatment), plus any additional part of the population which survived the first application as a result of a finite dose being applied. Data to estimate the single-spray dose–response curve parameters and validate predictions of two-spray programme efficacy were obtained from separate subsets of treatments in four field experiments. A systemic fungicide spray was applied to wheat at a range of doses, at one or both of two times (t₁ and t₂), in all dose combinations. Observed values of the area under the disease progress curve (AUDPC) for septoria leaf blotch (Mycosphaerella graminicola) were used to construct response surfaces of dose at t₁ by dose at t₂ for each culm leaf layer. Parameters were estimated from single-spray and zero-dose treatment data only. The model predicted a high proportion (R² = 71–95%) of the variation in efficacy of the two-spray programmes. AUDPC isobols showed that the dose required at t₂ was inversely related to the dose at t₁, but the slope of the relationship varied with the relative timings of t₁ and t₂ in relation to culm leaf emergence. Isobols were curved, so the effective dose – the total dose required to achieve a given level of disease suppression – was lower when administered as two applications.     

Modelling Plant Disease Epidemics

An epidemic is the progress of disease in time and space. Each epidemic has a structure whose temporal dynamics and spatial patterns are jointly determined by the pathosystem characteristics and environmental conditions. One of the important objectives in epidemiology is to understand such spatio-temporal dynamics via mathematical and statistical modelling. In this paper, we outline common methodologies that are used to quantify and model spatio-temporal dynamics of plant diseases, with emphasis on developing temporal forecast models and on quantifying spatial patterns. Several examples of epidemiological models in cereal crops are described, including one for Fusarium head blight.     

桃品种需冷量评价模式的探讨

 通过1986～2001年对450余份桃品种需冷量的7．2℃模式、0～7．2℃模式(不包括0℃)和犹它模式比较分析，归纳出桃品种需冷量的评价模式为：以秋季日平均温度稳定低于7．2~C的日期为需冷量测定的起点，以0～7．2℃累积低温值作为需冷量的评价标准比较适宜；犹它模式在中需冷量和长需冷量范围内能有效预测休眠的结束，而不适宜低需冷量品种的测定；7．2℃模式不适宜作为需冷量的评价模式。品种的需冷量与叶芽开放和始花期的相关系数分别为0．52和0．58，均达到极显著水平。提出了桃品种需冷量评价的系列标准参照品种。     

The effect of populations of Xanthomonas campestris pv. phaseoli in bean reproductive tissues on seed infection of resistant and susceptible bean genotypes

Surface and internal populations of Xanthomonas campestris pv. phaseoli, causal agent of common bacterial blight of bean, on and in flower buds, blossoms and pods of seven bean (Phaseolus vulgaris) genotypes were studied. Bean plants were grown in the field and artificially inoculated at the seedling stage (18 days old). The pathogen was recovered in high numbers from flower buds, blossoms, pods and seed of both resistant and susceptible bean genotypes. Significant differences (P = 0.05) in population levels of X. c. pv. phaseoli between stages of reproductive tissue development were observed. Infected seed from resistant bean genotypes had no visible symptoms. Such seed may play an important role in the epidemiology of common bacterial blight because they are difficult to detect and may occur at low frequency in seed lots, as was the case in the current study.     

新疆冬小麦农田蒸散估算模型的研究

本文在田间试验资料的基础上，综合考虑了影响冬小麦农田蒸散的气象、生物学特性和土壤水分等因素，选用蒸发力、冬小麦的叶面积指数和相对有效土壤湿度建立了新疆冬小麦农田蒸散估算模型，并且检验了该模型的计算效果。     

景观生态学原理与方法在荒漠化研究中应用的理论分析

荒漠化发生发展的过程实际上是指在自然和人为因素的作用下，生态系统结构遭受破坏、功能过程受阻和演变发生异化的过程，其防治的根本措施是恢复和重建健康的生态系统。所以，景观生态学理念在荒漠化的研究和防治中有着重要的意义。本文从荒漠化与生态系统结构、功能变化、荒漠化与生物多样性、荒漠化生态系统的物质循环和能量流动以及荒漠化生态系统的稳定性等方面论述了景观生态学理念在荒漠化研究中应用的可行性，并重点分析了景观生态学关于景观格局变化的评价指标与荒漠化土地动态变化之间的关系。     

稻曲病侵染时期和流行因素研究

分期接种试验的结果表明,稻曲病对水稻的侵染时期,主要在孕穗末期至破口期,病菌侵入籽粒在水稻开花前。3a的系统调查和对比分析结果说明,水稻穗期最高气温>32℃的天数少,降雨量大,有利病菌的侵入和发展流行,品种间抗(耐)病性差异显著。近年来稻曲病发生严重的主要原因是单季晚稻的大面积种植,穗期气候条件适宜病害发生流行。     

Functional heterogeneity in resources within landscapes and herbivore population dynamics

Large mammalian herbivores are notorious for their propensity towards population irruptions and crashes, yet many herbivore populations remain relatively stable. I explore how resource heterogeneity within landscapes dampens population instability, using a metaphysiological modelling approach considering patch state distributions. Resource heterogeneity is functionally stabilizing through spreading consumption away from preferred resources before these become critically depleted. Lower-quality resources act as a buffer against starvation during critical periods of the seasonal cycle. Enriching resource quality is destabilizing, even if patch diversity is maintained, because food quantity then becomes the limitation. The potential consequences of landscape fragmentation are explored using the Serengeti ecosystem, characterised by broadscale resource gradients, as a hypothetical example. Further insights provided by the model are illustrated with specific examples concerning the effects of patch scales and waterpoint distribution. A metaphysiological modelling approach enables the basic consequences of landscape heterogeneity to be distinguished from further effects that may arise from specific patch scales and configurations, without the distracting detail of spatially explicit models.