Risk maps for targeting exotic plant pest detection programs in the United States

In the United States, pest risk maps are used by the Cooperative Agricultural Pest Survey for spatial and temporal targeting of exotic plant pest detection programs. Methods are described to create standardized host distribution, climate and pathway risk maps for the top nationally ranked exotic pest targets. Two examples are provided to illustrate the risk mapping process: late wilt of corn (Harpophora maydis) and the giant African land snail (Achatina fulica). Host risk maps were made from county‐level crop census and USDA Forest Inventory and Analysis data, respectively. Climate risk maps were made using the North Carolina State University–USDA APHIS Plant Pest Forecasting System (NAPPFAST), which uses a web‐based graphical user interface to link climatic and geographic databases with interactive templates for biological modelling. Pathway risk maps were made using freight flow allocation data sets to move commodities from 7 world regions to 3162 US urban areas. A new aggregation technique based on the Pareto dominance principle was used to integrate maps of host abundance, climate and pathway risks into a single decision support product. The maps are publicly available online ( http://www.nappfast.org ). Key recommendations to improve the risk maps and their delivery systems are discussed.     

A quantitative interpretation of the entry section of the EPPO decision‐support scheme for pest risk analysis

The development of methods to combine components of risk and their associated uncertainty in Pest Risk Analysis (PRA) has received attention in a number of recent European projects. Many of the risk components distinguished in the EPPO Decision‐support scheme (DSS) for PRA are usually difficult to quantify, but when there is detailed knowledge of the pest and pathway, quantification may be possible to a limited extent for the pest entry section of the scheme. The European Food Safety Authority has recently commissioned a project to investigate approaches to quantitative pathway analysis for pests of commodities entering and moving within the EU (QPA‐Food); a sister project concerns non‐food commodities. This paper illustrates the potential for a quantitative pathway model based closely on the Entry Section of the EPPO DSS for PRA, where existing quantitative definitions of rating categories have been used as a basis to estimate the proportion and number of infested lots on a pathway. Such quantification may provide additional insights without requiring substantial changes to the information elicited via the DSS.     

A decision‐support scheme for mapping endangered areas in pest risk analysis*

This paper describes a decision‐support scheme (DSS) for mapping the area where economically important loss is likely to occur (the endangered area). It has been designed by the PRATIQUE project to help pest risk analysts address the numerous risk mapping challenges and decide on the most suitable methods to follow. The introduction to the DSS indicates the time and expertise that is needed, the data requirements and the situations when mapping the endangered areas is most useful. The DSS itself has four stages. In stage 1, the key factors that influence the endangered area are identified, the data are assembled and, where appropriate, maps of the key factors are produced listing any significant assumptions. In stage 2, methods for combining these maps to identify the area of potential establishment and the area at highest risk from pest impacts are described, documenting any assumptions and combination rules utilised. When possible and appropriate, Stage 3 can then be followed to show whether economic loss will occur in the area at highest risk and to identify the endangered area. As required, Stage 4, described elsewhere, provides techniques for producing a dynamic picture of the invasion process using a suite of spread models. To illustrate how the DSS functions, a maize pest, Diabrotica virgifera virgifera, and a freshwater invasive alien plant, Eichhornia crassipes, have been used as examples.     

Potential spread of kiwifruit bacterial canker (Pseudomonas syringae pv. actinidiae) in Europe

Pest risk analyses (PRAs) are conducted to determine whether an organism is a pest and whether and how it should be regulated. Estimation of the potential area of establishment and pest spread are key factors of this analysis. Tools for modelling and mapping of these key factors have to be quick and easily applicable for a wide variety of organisms with limited data for parameterization. For this purpose, a dispersal kernel model based on a 2Dt‐distribution had been developed in a European Union project (PRATIQUE). The aim of the present study was the evaluation of this spread model hitherto tested on insects, plants, fungi and nematodes in order to determine its applicability to bacterial pests. Therefore, the potential distribution and spread of kiwifruit bacterial canker Pseudomonas syringae pv. actinidiae in Europe was investigated based on climatic suitability and host plant availability. The results of the modelling were compared with the spread history of the pest in Europe. It is shown that this generic spread model can also be applied to a bacterial pest.     

Consistency in pest risk analysis – how can it be achieved and what are the benefits?*

This paper describes the efforts in the PRATIQUE EU project to increase consistency that were integrated into the revised EPPO Decision‐support scheme (DSS) for Pest Risk Analysis (PRA). The establishment section is used here to illustrate the changes and improvements of the DSS, as it has undergone the most comprehensive changes with reformulation and restructuring of many questions and detailed rating guidance. When revising the establishment section of the EPPO DSS for PRA, there were three principal objectives that influenced the revision: (i) to focus the assessment on the most relevant factors influencing establishment; (ii) to identify the area where establishment is possible before assessing the suitability of that area, and (iii) to enhance the consistency of the establishment section by providing rating guidance with sub‐questions and examples. To simplify the process, some questions were rephrased as closed questions (answer is either yes or no). Clearer notes were provided to explain what information is needed to answer the questions. Furthermore, consistency has been enhanced by developing tools to help assessors when deciding on an appropriate overall risk rating and uncertainty score by providing a visual summary of the risk ratings and uncertainty scores (‘Visualizer’) and a method for integrating all the responses to the questions to provide a summary score for each major section and an overall assessment of risk (‘Rule based matrix model’).     

Climatic Zoning and Plant Disease Potential – Examples from the Near and Middle East1

Actual plant disease and pest occurrence depends on many genetic and environmental factors, and frequently obscures the basic suitability of a given location to support or prevent epidemic development. In order to allow the demarcation of climatic zones related to the potential of disease or pest occurrence, we have used long-term average climatic data, especially monthly average temperatures and monthly average rainfall. If applied to sugar beet leaf pathogens such as Cercospora beticola and Erysiphe betae in the Near and Middle Eastern region, some interesting zoning became possible, which could be verified by extended field studies. Other examples that have been analysed in the region are apple scab, Venturia inaequalis, and downy mildew of grapes, Plasmopara viticola. A recent and ongoing analysis of the factors controlling chickpea anthracnose caused by Ascochyta rabiei indicates that the same principle may be applied for very different pathogens. Large-scale planning and control strategies as tried by the International Agricultural Research Centers should therefore be based on careful climatic zoning for plant pest and disease potential, to avoid waste of the limited genetic and financial resources available.     

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.     

The Potential Geographic Range of Pyrenophora semeniperda

ABSTRACT There is no evidence that Pyrenophora semeniperda, the causal agent of leaf spotting in many annual and perennial grasses, currently occurs in Europe or Asia. However, there is potential phytosanitary concern that the importation of infected commodities could result in the introduction of this fungus into Eurasia, putting crops at risk and possibly resulting in economic losses. To assist in assessing the risk of geographic range extension of P. semeniperda, an analysis was undertaken to estimate the potential global distribution of this species, based on climatic suitability. Geographic distribution data for P. semeniperda in part of its current range were used to fit parameter values in a CLIMEX pest risk assessment model, and the remaining distribution data were used to validate the model. The CLIMEX model correctly predicts that virtually all locations where P. semeniperda has been found are climatically suitable. Only five locations worldwide where the fungus was recorded present are predicted as being unsuitable. These "outliers" may have been transient populations occurring during a favorable season and then dying out. Exploratory adjustments of the model to accommodate these records created unsatisfactory distortions in the projected climatic suitability surfaces, extending the suitable climatic zone beyond well-established traditional range boundaries. We are therefore confident that the model is credibly predicting the potential distribution of P. semeniperda worldwide. The CLIMEX model suggests that P. semeniperda could potentially extend its range throughout Europe and temperate regions of Asia, Africa, and South America. Our heavy reliance upon geographic data to build this CLIMEX model departs from most previous published examples in plant pathology, which have depended primarily upon experimentally derived physiological data to estimate model parameters. The use of geographic data to infer climate parameters is popular in CLIMEX models of weeds and arthropod pests and can provide decision-makers with early risk assessments of potential pathogen invasions, particularly where the pathogens have long, or difficult-to-study, lifecycles.     

河北省棉花气候适宜度及其时空变化趋势分析

棉花为河北省重要的经济作物,与其它作物相比对气候比较敏感.选取河北省25个棉花县,对棉花各个发育期气候适宜度及其时空分布进行分析计算.结果表明:棉花从播种到吐絮降水适宜度比温度、日照适宜度明显偏小,尤以播种期和吐絮期最小,且变异系数最大.日照适宜度从播种到吐絮变化不大,较温度和降水适宜度高.多年适宜度的变化趋势为:温度适宜度缓慢上升,降水适宜度缓慢下降,日照适宜度在明显下降,气候综合适宜度同降水一致,在缓慢下降.降水适宜度高值区分布在北部棉区,低值区分布在黑龙港流域的部分地区;温度适宜度低值区在唐山大部,高值区在黑龙港流域;日照适宜度低值区在西部太行山丘陵棉区,高值区在东部棉区.     

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.     

东北地区玉米气候适宜评价指标的确定与验证

为科学、定量地评价气象条件对玉米生长发育及产量形成的影响,以东北地区为例,利用模糊数学原理,在考虑了玉米生物学特性的基础上,结合农业气象业务服务指标,构建了东北区温度、水分、日照适宜度模型,采用几何平均法计算了玉米气候适宜度。考虑到不同发育期气候条件对玉米产量形成影响程度的客观差异,运用相关系数法设定玉米生育期内各旬对产量的权重,采用加权平均法构建了玉米播种至任意时段的气候适宜指数。利用各时段历史气候适宜指数最大值、平均值、最小值,确定了不同等级的气候适宜评价指标。基于该指标将1993—2011年玉米全生育期气候适宜指数划分为气候适宜、较适宜、较不适宜和不适宜4个等级,并将该指标进行验证。检验结果表明:东北地区玉米气候适宜等级与生育期内气象条件的优劣具有很好的一致性,播种~拔节、播种~乳熟、播种~成熟3个阶段的气候适宜等级与产量增减幅度的相关性十分显著(P≤0.05),且越接近成熟期,相关性越明显;气候适宜等级能够较准确地反映出玉米生育期内气象条件的优劣变化及逐年、典型灾害年产量的实际情况。     

东北春玉米全生育期气候适宜度评价

适宜的气候要素是保障东北春玉米健康生长和高产稳产的基本条件。依据温、光、水气候要素对春玉米生长的影响,分别构建温度、日照和降水适宜度模型,引入有效降水提高模型精度,再基于有效降水和实际降水将三种气候要素耦合建立综合气候适宜度模型Ⅰ和模型Ⅱ,并利用1994—2013年有效气象、物候数据和2003—2010年像元尺度大田玉米生长状况时序遥感监测信息对海伦和泰来两个典型东北农业台站进行模型测试检验,将最适用模型应用于东北三省玉米典型种植区以估算2008与2009年25个站点不同生育期各气候要素适宜度。检验结果表明,“基于有效降水的模型Ⅰ”所估算的全生育期综合气候适宜度与NDVI、EVI的相关系数(0.58、0.29)均优于“基于实际降水的模型Ⅱ”(0.52、0.18),融合有效降水信息的模型Ⅰ更能有效捕获气候要素对春玉米生长胁迫现象。应用结果显示,模型Ⅰ估算的2008和2009年东北春玉米全生育期综合气候适宜度分别为0.67和0.56,与该地区2008年春玉米实际产量高于2009年表现一致;两年间东北三省春玉米各气候要素适宜度总体表现为温度>日照>有效降水;辽宁与吉林的温度、有效...     

Report of a rapid pest risk analysis for Lambdina fiscellaria (Guenée, [1858]) (Lepidoptera: Geometridae) for the island of Ireland

The hemlock looper, Lambdina fiscellaria (Guenée), is a serious forest pest in North America with three subspecies that vary in their geographical range and larval host preferences. Both broadleaved and coniferous trees are infested, though the largest impacts are on coniferous forestry where trees can be completely defoliated and killed. The pest was identified as a potential threat to forestry on the island of Ireland during a horizon‐scanning exercise to identify pests of Picea sitchensis (Bong.) Carr. (Sitka spruce) and was subject to a rapid pest risk analysis (PRA). Though judged to be unlikely, pathways identified were uncontrolled wood commodities and mosses and lichens harvested from forests in North America and exported for use in ornamental displays. Lambdina fiscellaria is found in a range of climate types, and is likely to be able to complete its lifecycle in the Irish climate – although there is uncertainty concerning its ability to adapt to European trees. Lambdina fiscellaria has only a limited capacity for spread, as virgin females are burdened by their eggs and are poor fliers. This was judged to reduce potential impacts in the PRA area – as the slow rate of spread would provide time to develop monitoring and control methods well ahead of the pest reaching its maximum extent on the island of Ireland. The pest still poses a considerable risk to coniferous forestry not only on the island of Ireland but across the EPPO region where climate is suitable for the pest to establish. Regulation and implementation of phytosanitary measures prevent introduction of the pest should be considered.     

林业小蠹类昆虫在中国的适生性分析综合比较研究

小蠹类昆虫是重要的林业害虫类群,严重威胁我国的林业生产和生态安全,具有重要的经济意义。综合比较中国林业小蠹类昆虫的适生性分析方法,有助于把握林业小蠹类昆虫物种分布模型的研究动向。该文归纳整理中国林业小蠹类昆虫的适生性分析文献,统计文献所使用的模型、适生性等级划分标准以及文献来源等信息,并对小蠹类昆虫适生性分析未来发展进行展望,以期为林业有害生物防控提供参考。     

Assessing the potential distribution of insect pests: case studies on large pine weevil (Hylobius abietis L) and horse‐chestnut leaf miner (Cameraria ohridella) under present and future climate conditions in European forests

Forest insect pests represent a serious threat to European forests and their negative effects could be exacerbated by climate change. This paper illustrates how species distribution modelling integrated with host tree species distribution data can be used to assess forest vulnerability to this threat. Two case studies are used: large pine weevil (Hylobius abietis L) and horse‐chestnut leaf miner (Cameraria ohridella Deschka & Dimi?) both at pan‐European level. The proposed approach integrates information from different sources. Occurrence data of insect pests were collected from the Global Biodiversity Information Facility (GBIF), climatic variables for present climate and future scenarios were sourced, respectively, from WorldClim and from the Research Program on Climate Change, Agriculture and Food Security (CCAFS), and distributional data of host tree species were obtained from the European Forest Data Centre (EFDAC), within the Forest Information System for Europe (FISE). The potential habitat of the target pests was calculated using the machine learning algorithm of Maxent model. On the one hand, the results highlight the potential of species distribution modelling as a valuable tool for decision makers. On the other hand, they stress how this approach can be limited by poor pest data availability, emphasizing the need to establish a harmonised open European database of geo‐referenced insect pest distribution data.     

The current and future potential distribution of Melaleuca quinquenervia

Melaleuca quinquenervia (broad-leaved paperbark) is a tree native to Australia, Papua New Guinea and New Caledonia that has become moderately to highly invasive in a number of countries over the last century. Although a synoptic view of the invasion would be of considerable use in devising appropriate control strategies, little effort has been applied to investigate the potential distribution of this invasive species. A climate suitability analysis was undertaken in this study, to assess the risk of geographic range expansion of M . quinquenervia under current climate and how this distribution will be modified by climate change during the 2080s. CLIMEX™ was used to infer the climatic requirements of M . quinquenervia from observations in both the native and exotic range. The accuracy of the developed model was assessed using independent naturalised observations of the species in Asia, Africa, Oceania and the Caribbean. Projections of climatic suitability indicate considerable scope for further invasion, with the most suitable areas occurring adjacent to existing populations in south-east Asia, the Caribbean, Central and South America and the Gulf coast in southern USA. Under future climates, model projections indicate there will be a marked contraction of suitable habitat in most regions and a slight poleward range expansion within south-eastern China, southern Europe and northern New Zealand.     

Predicting the distribution of harmful species and their natural enemies in agricultural,livestock and forestry systems: an overview

Abstract

Predicting the potential distribution of harmful species to agriculture, livestock and forestry is decisive to prevent their impacts, especially when these are expanding their range due to global change. Recent advances in species distribution modelling (SDM) have made these tools widely used for biosecurity studies. We reviewed the available literature of SDM for pest, weeds, pathogen species and biological-control agents, with the aims of synthesizing and quantifying the available information, and identifying gaps in the knowledge and future perspectives. SDMs for 420 species were collected from 220 publications. Insect pests were the most frequently studied organisms. CLIMEX and MaxEnt were the most commonly used modelling tools, while pure mechanistic approaches were rarely applied. Most studies covered broad scales, and focused on predicting the distribution of invasive species and/or the effects of climate change. The challenge remains for models to include disturbance, resource availability, and biotic factors, as well as to better quantify uncertainty. This future directions will be fundamental to improve the predictive power of SDMs for productive systems in the context of a rapidly changing World.     

悬铃木方翅网蝽在浙江的风险分析及防控对策

悬铃木方翅网蝽是浙江新发现的一种林业危险性害虫。采用国际植物检疫措施实施标准（ISPM）的有害生物风险分析（PRA）程序,对悬铃木方翅网蝽的风险分析进行定性和定量分析,得出悬铃木方翅网蝽的风险值R为1.95,在我国属于中度危险的有害生物。结合本省悬铃木属寄主植物的资源状况及气候特点,对悬铃木方翅网蝽在浙江的潜在危险性进行了分析,结果表明,悬铃木方翅网蝽在浙江大部分区域具有定殖、扩散的可能性。据此,作者提出了检疫管理及防范对策。     

河北省冬小麦气候适宜度动态模型的建立及应用

运用模糊数学理论结合前人研究成果,建立了冬小麦温度、降水、日照隶属度模型和气候适宜度模型,分别计算了河北省冬小麦1960～2005历年全生育期和各发育期的温度隶属度、降水隶属度、日照的隶属度和气候适宜度.结果表明,河北省冬小麦温度隶属度和日照隶属度较大,光热资源一般条件下能够满足冬小麦生长发育要求,降水隶属度较小,降水条件是冬小麦产量形成的限制因素.冬小麦气候适宜度为下降趋势,10年下降速率为0.012.冬小麦各发育期气候适宜度以分蘖期、返青期、拔节期变化幅度较大,这与河北省的天气特点是一致的.     

进口植物及植物产品有害生物风险分析

本文从经济、生态和人及人类社会3个方面阐述了外来有害生物的风险;根据国际标准中制订的有害生物风险分析流程,定性地描述了有害生物风险分析的方法;并从入侵种特性研究、适生区预测研究和风险分析模型3个方面阐述了有关有害生物风险分析的理论研究进展,这些理论研究有助于为有害生物风险定量分析提供科学依据。