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。     

基于生态位模型的番荔枝实蝇潜在适生性分布预测(英文)

番荔枝实蝇Ceratitis anonae(Graham)是一种重要的外来入侵性检疫害虫。在广东口岸,其幼虫连续从入境旅客所携带的水果中被检出。目前关于番荔枝实蝇潜在适生性分布的研究进行得很少,但对于我国的生物生态安全却有重要意义。本研究中,我们使用3种生态位模型(ENFA模型,马氏典型性模型和Maxent模型)对番荔枝实蝇在中国以及全球范围内的潜在适生性分布区域进行了预测分析。结果显示:Maxent模型拥有最好的预测精确度,马氏典型性模型次之,而ENFA模型的预测精确度最差;Maxent模型和马氏典型性模型的预测精确度无显著性差异;根据Maxent模型的预测结果,番荔枝实蝇在中国的潜在适生区主要是广西、广东、海南以及云南的少部分地区。分析结果显示,番荔枝实蝇从境外传入中国南部地区并最终在上述地区定殖的风险可能性存在,但风险较小。另外,折刀法(Jackknife)分析显示,6种环境因子,例如地面霜冻频率、年平均降雨量、十月降雨量、四月降雨量、年最低温度以及蒸气压,对于番荔枝实蝇在全球和局部地区的分布模式有显著的影响。     

基于CLIMEX的苜蓿籽象甲在中国的适生区分析

苜蓿籽象甲(Tychius medicaginis Bris.)在我国主要分布于新疆的北疆地区和甘肃,是新疆北疆苜蓿种子田重要害虫.本研究综合运用CLIMEX 3.0与ArcGIS 9.3对苜蓿籽象甲在我国目前以及未来气候条件下的潜在地理分布进行了研究.结果显示:目前气候条件下,苜蓿籽象甲在我国的适生区主要分布于新疆、甘肃、内蒙古等苜蓿主要种植地区.基于中国未来气候的预测结果显示,2020年,其中高度适生区范围由20.25％增加至23.88％,增加了3.63％;非适生区有所减少,由21.32％降至13.99％,减少了7.33％.可以看出,未来气候条件将更适宜首蓿籽象甲的生存.鉴于首蓿籽象甲在我国的适生性研究结果,建议进一步完善监测预警预报体系,采取相应有效的防控策略,加强对苜蓿籽象甲的防治措施,严防该虫的进一步传播扩散.     

Modelling the establishment,spread and distribution shifts of pests

Abstract

During the last century increasing human trade networks have interacted with other global changes – such as land use and climate change – to accelerate the range expansion of pest species worldwide. In this special issue, we present a series of articles that model the risk of establishment and spread of non-native harmful species, as well as shifts in the distribution of native pest species. We also provide a state-of the art review of the available literature on species distribution models for pests, weeds, and pathogens. Recent advances in modelling approaches have allowed us to significantly improve our abilities to predict changes in species distribution, and these tools have been widely used to enhance biosecurity planning and pest management. We expect that this special issue contributes toward and integration of the scientific knowledge and the development of novel approaches to model pest species distribution, as well as to better understand the factors that influence their expansion in the context of a rapidly changing world.     

基于GARP的欧洲大蚊在中国的适生性分析

欧洲大蚊(Tipula paludosa)的幼虫可危害多种植物,尤其偏好禾本科植物。该虫原产于欧洲,后传入北美地区,在当地造成重大的经济损失,在中国尚未有分布的报道。搜集欧洲大蚊在欧洲的已知分布数据,利用GARP生态位模型结合ArcGIS对其在中国的潜在分布进行了预测。结果表明:欧洲大蚊在我国有较为广泛的适生区域,包括21个省、市(区)。其中,吉林、辽宁、河北、山东、河南、陕西、江苏和天津的大部分地区都适生。据此提出了针对欧洲大蚊的风险管理措施。     

Common vole (Microtus arvalis) ecology and management: implications for risk assessment of plant protection products

Common voles (Microtus arvalis) are common small mammals in some European landscapes. They can be a major rodent pest in European agriculture and they are also a representative generic focal small herbivorous mammal species used in risk assessment for plant protection products. In this paper, common vole population dynamics, habitat and food preferences, pest potential and use of the common vole as a model small wild mammal species in the risk assessment process are reviewed. Common voles are a component of agroecosystems in many parts of Europe, inhabiting agricultural areas (secondary habitats) when the carrying capacity of primary grassland habitats is exceeded. Colonisation of secondary habitats occurs during multiannual outbreaks, when population sizes can exceed 1000 individuals ha^?1. In such cases, in‐crop common vole population control management has been practised to avoid significant crop damage. The species' status as a crop pest, high fecundity, resilience to disturbance and intermittent colonisation of crop habitats are important characteristics that should be reflected in risk assessment. Based on the information provided in the scientific literature, it seems justified to modify elements of the current risk assessment scheme for plant protection products, including the use of realistic food intake rates, reduced assessment factors or the use of alternativee focal rodent species in particular European regions. Some of these adjustments are already being applied in some EU member states. Therefore, it seems reasonable consistently to apply such pragmatic and realistic approaches in risk assessments for plant protection products across the EU. © 2013 Society of Chemical Industry     

The application of artificial neural networks in plant protection*

Artificial neural networks are powerful predictive tools that have the ability to detect and approximate non‐linear relationships from the data. In an explorative analysis, artificial neural networks were used to predict the geographic distribution of groups of polyphagous plant pests. Using climate variables as predictors, artificial neural network models were compared with binary logistic models for predicting insect distribution. Using bootstrapping, artificial neural networks were shown to predict insect presence and absence significantly better than the binary logistic regression models. Results from the study suggest that artificial neural networks have the potential for application in many areas of plant protection and biosecurity.     

Selectivity of chlorantraniliprole to parasitoid wasps

BACKGROUND: Chlorantraniliprole is a novel anthranilic diamide insecticide registered for use in vegetables, fruits, grains and turf against a variety of insect pests. The objective of this article is to summarize results of acute toxicity testing of chlorantraniliprole on seven species of parasitic wasps with wide geographic distribution and relevance to different crops and integrated pest management (IPM) programmes. RESULTS: Tier‐1, worst‐case laboratory studies evaluated wasp survival and reproduction following different exposure concentrations and scenarios to chlorantraniliprole (i.e. fresh‐dried spray deposits on glass plates, direct contact, ingestion, egg card, dipped leaf residue bioassays, sprayed mummies). No statistically significant effects on adult survival, percentage parasitism or emergence were observed following exposures to chlorantraniliprole compared with controls. CONCLUSION: Chlorantraniliprole was harmless to the parasitoid wasp species tested according to IOBC classification criteria (<30% effects) and may be a useful tool in IPM programmes. Copyright © 2010 Society of Chemical Industry     

一种基于多Agent和GIS的麦蚜种群动态模拟方法研究初报

利用Agent模型对昆虫及其寄主、环境之间的关系进行计算机模拟,比传统种群模型更为直观的体现三者之间的信息交互过程。本文建立了麦长管蚜(Sitobionavenae)、小麦(Triticumaestivum L.)、天敌组合、环境4种类型Agent对象,观察了多种组合下的对象行为。以北京地区的历史日值均温、湿度、降雨量数据为主要环境数据,进行了区域模拟验证,与北京地区实际调查数据进行了对比研究。在GIS平台上,以小麦生长季节的气象数据对宁夏、陇东、陕西3个地区进行了模拟,以环境数据进行驱动的4类Agent对象运行,得到了初步模拟结果。     

外来有害生物适生性研究方法及需要注意的若干问题

在分析利用生态位技术结合气候统计学方法及利用试验数据建立预测模型评估开展有害生物适生性研究的大量文献的基础上,本文详细讨论了在有害生物适生性研究中涉及的有关有害生物生物学资料的评估与分析、有害生物分布点的选择及预测结果的准确性等问题。认为有害生物的生物学特性及地理学的资料在研究有害生物适生性方面具有十分重要的作用。从统计学角度探讨了提高适生性预测结果正确性的途径。     

The role of population and quantitative genetics and modern sequencing technologies to understand evolved herbicide resistance and weed fitness

Evolution of resistance to multiple herbicides with different sites of action and of nontarget site resistance (NTSR) often involves multiple genes. Thus, single‐gene analyses, typical in studies of target site resistance, are not sufficient for understanding the genetic architecture and dynamics of NTSR and multiple resistance. The genetics of weed adaptation to varied agricultural environments is also generally expected to be polygenic. Recent advances in whole‐genome sequencing as well as bioinformatic and statistical tools have made it possible to use population and quantitative genetics methods to expand our understanding of how resistance and other traits important for weed adaptation are genetically controlled at the individual and population levels, and to predict responses to selection pressure by herbicides and other environmental factors. The use of tools such as quantitative trait loci mapping, genome‐wide association studies, and genomic prediction will allow pest management scientists to better explain how pests adapt to control tools and how specific genotypes thrive and spread across agroecosystems and other human‐disturbed systems. The challenge will be to use this knowledge in developing integrated weed management systems that inhibit broad resistance to current and future weed‐control methods. © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

Exploiting the high‐resolution JRC‐MARS European climatic dataset for pest risk mapping

Climatic data with a high temporal and spatial resolution are invaluable when modelling the potential distribution of non‐native pests. The European Commission Joint Research Centre Monitoring Agricultural ResourceS (MARS) programme provides a unique source of European daily climatic data. Available from 1975 to 2015 and updated annually, the data are interpolated from over 5000 weather stations to 25‐km grid cells. All geographical Europe is included, plus Mediterranean areas of the Middle East and North Africa. The climatic parameters available include temperature (daily minima and maxima), solar radiation, rainfall and relative humidity. As well as the potential for use in simple pest models, selected parameters can be imported into more complex models, such as CLIMEX, for more detailed analyses. Case studies showing how the MARS data have been used by the UK in pest risk analyses are presented for three insect pests: Thaumetopoea pityocampa, Hyphantria cunea (both Lepidoptera) and Popillia japonica (Coleoptera). The case studies illustrate some methods of representing uncertainty where thresholds are lacking in the published literature, there are conflicting data and only air temperature data are available to model a soil‐dwelling organism.     

Patterns of loss of biodiversity associated with invasion by Chrysanthemoides monilifera subsp. monilifera (boneseed) across a large geographic region

To investigate the impact of invasion by Chrysanthemoides monilifera ssp. monilifera (boneseed) on plant communities, sites that were invaded and uninvaded were surveyed across Tasmania, South Australia and Victoria, Australia. Above‐ground cover abundance was estimated and samples of the seed bank from invaded and uninvaded sites in each state were collected and germinated in the glasshouse. We compared species richness and composition between invaded and uninvaded sites for both above‐ground and below‐ground samples. Across this broad geographic area, C. monilifera invaded sites had 25% fewer species than uninvaded sites and twice as many exotic species. Most growth forms showed reduced richness in invaded sites. There were no differences in the composition of native species communities between invaded and uninvaded sites in most regions, except South Australia. The composition of the seed bank differed from the above‐ground vegetation, but was similar within each state. Herbs and grasses were most abundant. The species composition of the seed bank was different in invaded sites only in Victoria, suggesting that invasion may negatively influence the capacity of the seed bank to restore vegetation in some areas. However, the underlying mechanisms for the observed patterns were not tested in this study. The capacity of all sites to regenerate effectively from the seed bank was limited and, in order to ensure the conservation of biodiversity into the future, monitoring of species richness at smaller scales, particularly those where management of C. monilifera has occurred, will be needed to ensure management can facilitate the establishment of missing species. This study suggests that C. monilifera impacts a range of functional groups and different species across its distribution and is therefore non‐selective in how it influences changes in communities.     

Insecticide‐induced hormesis and arthropod pest management

Ecological backlashes such as insecticide resistance, resurgence and secondary pest outbreaks are frequent problems associated with insecticide use against arthropod pest species. The last two have been particularly important in sparking interest in the phenomenon of insecticide‐induced hormesis within entomology and acarology. Hormesis describes a biphasic dose–response relationship that is characterized by a reversal of response between low and high doses of a stressor (e.g. insecticides). Although the concept of insecticide‐induced hormesis often does not receive sufficient attention, or has been subject to semantic confusion, it has been reported in many arthropod pest species and natural enemies, and has been linked to pest outbreaks and potential problems with insecticide resistance. The study of hormesis remains largely neglected in entomology and acarology. Here, we examined the concept of insecticide‐induced hormesis in arthropods, its functional basis and potential fitness consequences, and its importance in arthropod pest management and other areas. © 2013 Society of Chemical Industry     

Phenology modelling of major insect pests in fruit orchards from biological basics to decision support: the forecasting tool SOPRA*

The forecasting tool SOPRA has been developed with the objective of optimizing timing of monitoring, management and control measures of insect pests in fruit orchards in Switzerland. Applying time‐varying distributed delay approaches, phenology‐models were developed driven by solar radiation, air temperature and soil temperature on hourly basis. Relationships between temperature and stage‐specific development rates for relevant stages of the life cycles were established under controlled laboratory conditions for Dysaphis plantaginea, Hoplocampa testudinea, Cydia pomonella, Grapholita lobarzewskii, Cacopsylla pyri, Rhagoletis cerasi, Anthonomus pomorum and Adoxophyes orana. The implementation of body temperatures in the models is based on habitat selection and biophysical modelling of habitat conditions. In order to validate modelling, phenology predictions were compared with several years of independent field observations. On the basis of local weather data, the age structure of the pest populations is simulated and crucial events for management activities are announced. Through a web interface, the simulation results are made available to consultants and growers ( http://www.sopra.info ) and the latter can be applied as a decision support system for the eight major insect pests of fruit orchards in the alpine valleys and north of the Alps on local and regional scale.     

Drosophila suzukii (Diptera: Drosophilidae) distribution modelling improves our understanding of pest range limits

Abstract

Spatial distributions models (SDM) are often used in invasive pest management to understand current and potential distribution. Using data on the well-studied spotted wing drosophila as a model, we compared distribution patterns of the range-limit with commonly applied correlative and mechanistic models. Correlative models risk underestimation whereas simple mechanistic models provide overestimated range predictions, although using both approaches for the spotted wing drosophila improved range-limit predictions. Model choice when dealing with pests is central to the accurate identification of invasive species limit range and consequently for the deployment of monitoring and early detection programs.     

The population dynamics of disease on short and long time-scales

Observational evidence is scarce concerning the distribution of plant pathogen population sizes or densities as a function of time-scale or spatial scale. For wild pathosystems we can only get indirect evidence from evolutionary patterns and the consequences of biological invasions. We have little or no evidence bearing on extermination of hosts by pathogens, or successful escape of a host from a pathogen. Evidence over the last couple of centuries from crops suggest that the abundance of particular pathogens in the spectrum affecting a given host can vary hugely on decadal time-scales. However, this may be an artefact of domestication and intensive cultivation. Host-pathogen dynamics can be formulated mathematically fairly easily–for example as SIR-type differential equation or difference equation models, and this has been the (successful) focus of recent work in crops. “Long-term” is then discussed in terms of the time taken to relax from a perturbation to the asymptotic state. However, both host and pathogen dynamics are driven by environmental factors as well as their mutual interactions, and both host and pathogen co-evolve, and evolve in response to external factors. We have virtually no information about the importance and natural role of higher trophic levels (hyperpathogens) and competitors, but they could also induce long-scale fluctuations in the abundance of pathogens on particular hosts. In wild pathosystems the host distribution cannot be modelled as either a uniform density or even a uniform distribution of fields (which could then be treated as individuals). Patterns of short-term density-dependence and the detail of host distribution are therefore critical to long-term dynamics. Host density distributions are not usually scale-free, but are rarely uniform or clearly structured on a single scale. In a (multiply structured) metapopulation with co-evolution and external disturbances it could well be the case that the time required to attain equilibrium (if it exists) based on conditions stable over a specified time-scale is longer than that time-scale. Alternatively, local equilibria may be reached fairly rapidly following perturbations but the meta-population equilibrium be attained very slowly. In either case, meta-stability on various time-scales is a more relevant than equilibrium concepts in explaining observed patterns.     

Applying weather index insurance to agricultural pest and disease risks

In this paper, we explore the application of weather index insurance to plant pest and disease management strategies using two distinct models: (1) insuring crop loss due to disease incidence (“Crop Insurance”) and (2) insuring the use of pesticides (“Pesticide Insurance”). We find that despite the seeming ease of applying weather-based pest incidence models to an insurance product, insuring plant disease incidence models is presently unsuitable for the insurance market for both scientific and behavioral reasons. However, derivative-like applications of weather index insurance to insure pesticide use offer a means to introduce financial leverage into pesticide usage decisions. Risk management with weather index insurance would thus function as a complement to existing risk management strategies using pesticides, and offer a market-based mechanism for pesticide abatement. We conclude that more interdisciplinary collaboration is needed to develop weather index insurance for remuneration of losses due to plant pests and diseases, but weather index insurance offers a potential mechanism to reduce inefficiencies and negative externalities in agricultural markets if pesticide expenditures are insured instead of crop losses.