A suite of models to support the quantitative assessment of spread in pest risk analysis

Effect of temperature on in vitro germination and growth of Colletotrichum fioriniae, a new emerging pathogen of olive fruits

Olive anthracnose induced by different Colletotrichum species causes dramatic losses of fruit yield and oil quality. The increasing incidence of Colletotrichum fioriniae (Colletotrichum acutatum species complex) as causal agent of olive anthracnose in Italy, is endorsing new studies on its biology, ecology, and environmental factors such as temperature. Five isolates from different sampling sites in Lazio region (Central Italy) were studied under controlled laboratory conditions aiming to better understand the differences of thermal development among the isolates and to lay the foundations of a future mathematical model able to describe the key aspects of the pathogen's life cycle. The mycelial growth rate and the conidial germination rate were assessed at seven different constant temperatures (5, 10, 15, 20, 25, 30, and 35°C) and fixed relative humidity (100% RH). The obtained dataset was analysed to estimate the parameters of mathematical functions that connect the mycelial growth rate and the spore germination with the environmental temperature. The parameters set provided as the result of this study constitute a key step forward in the biological knowledge of the species and the basis for future formulations of mathematical models that might be the core of decision support systems in an integrated pest management framework.

Forest Landscape Effects on Dispersal of Spruce Budworm Choristoneura fumiferana (Clemens, 1865) (Lepidoptera, Tortricidae) and Forest Tent Caterpillar Malacosoma disstria Hübner, 1820 (Lepidoptera, Lasiocampidae) Female Moths in Alberta, Canada

Leaf-rollers and tent caterpillars, the families Torticidae and Lasiocampidae, represent a significant component of the Lepidoptera, and are well-represented in the forest insect pest literature of North America. Two species in particular-spruce budworm (Choristoneura fumiferana (Clem.)) and forest tent caterpillar (Malacosoma disstria Hbn.)-are the most significant pests of the Pinaceae and Salicacae, respectively, in the boreal forest of Canada, each exhibiting periodic outbreaks of tremendous extent. Dispersal is thought to play a critical role in the triggering of population eruptions and in the synchronization of outbreak cycling, but formal studies of dispersal, in particular studies of long-range dispersal by egg-bearing adult females, are rare. Here, it is shown in two independent studies that adult females of both species tend to disperse away from sparse or defoliated forest, and toward intact or undefoliated forest, suggesting that long-range dispersal during an outbreak peak is adaptive to the species and an important factor in their population dynamics, and hence their evolutionary biology.

An Integrated Biosecurity Risk Assessment Model (IBRAM) For Evaluating the Risk of Import Pathways for the Establishment of Invasive Species

An important aspect of analyzing the risk of unwanted organisms establishing in an area is understanding the pathways by which they arrive. Evaluating the risks of these pathways requires use of data from multiple sources, which frequently are uncertain. To address the needs of agencies responsible for biosecurity operations, we present an Integrated Biosecurity Risk Assessment Model (IBRAM) for evaluating the risk of establishment and dispersal of invasive species along trade pathways. The IBRAM framework consists of multiple linked models which describe pest entry into the country, escape along trade pathways, initial dispersal into the environment, habitat suitability, probabilities of establishment and spread, and the consequences of these invasions. Bayesian networks (BN) are used extensively to model these processes. The model includes dynamic BN components and geographic data, resulting in distributions of output parameters over spatial and temporal axes. IBRAM is supported by a web-based tool that allows users to run the model on real-world pest examples and investigate the impact of alternative risk management scenarios, to explore the effect of various interventions and resource allocations. Two case studies are provided as examples of how IBRAM may be used: Queensland fruit fly (Bactrocera tryoni) (Diptera: Tephritidae) and brown marmorated stink bug (Halyomorpha halys) (Hemiptera: Pentatomidae) are unwanted organisms with the potential to invade Aotearoa New Zealand, and IBRAM has been influential in evaluating the efficacy of pathway management to mitigate the risk of their establishment in the country.

Network Models and Simulation Analytics for Multi-scale Dynamics of Biological Invasions

Globalization and climate change facilitate the spread and establishment of invasive species throughout the world via multiple pathways. These spread mechanisms can be effectively represented as diffusion processes on multi-scale, spatial networks. Such network-based modeling and simulation approaches are being increasingly applied in this domain. However, these works tend to be largely domain-specific, lacking any graph theoretic formalisms, and do not take advantage of more recent developments in network science. This work is aimed toward filling some of these gaps. We develop a generic multi-scale spatial network framework that is applicable to a wide range of models developed in the literature on biological invasions. A key question we address is the following: how do individual pathways and their combinations influence the rate and pattern of spread? The analytical complexity arises more from the multi-scale nature and complex functional components of the networks rather than from the sizes of the networks. We present theoretical bounds on the spectral radius and the diameter of multi-scale networks. These two structural graph parameters have established connections to diffusion processes. Specifically, we study how network properties, such as spectral radius and diameter are influenced by model parameters. Further, we analyze a multi-pathway diffusion model from the literature by conducting simulations on synthetic and real-world networks and then use regression tree analysis to identify the important network and diffusion model parameters that influence the dynamics.

EU-Trees4F, a dataset on the future distribution of European tree species

We present "EU-Trees4F", a dataset of current and future potential distributions of 67 tree species in Europe at 10 km spatial resolution. We provide both climatically suitable future areas of occupancy and the future distribution expected under a scenario of natural dispersal for two emission scenarios (RCP 4.5 and RCP 8.5) and three time steps (2035, 2065, and 2095). Also, we provide a version of the dataset where tree ranges are limited by future land use. These data-driven projections were made using an ensemble species distribution model calibrated using EU-Forest, a comprehensive dataset of tree species occurrences for Europe, and driven by seven bioclimatic parameters derived from EURO-CORDEX regional climate model simulations, and two soil parameters. "EU-Trees4F", can benefit various research fields, including forestry, biodiversity, ecosystem services, and bio-economy. Possible applications include the calibration or benchmarking of dynamic vegetation models, or informing forest adaptation strategies based on assisted tree migration. Given the multiple European policy initiatives related to forests, this dataset represents a timely and valuable resource to support policymaking.

Potential global distribution of Aleurocanthus woglumi considering climate change and irrigation

Citrus blackfly, Aleurocanthus woglumi Ashby (Hemiptera: Aleyrodidae), is an important agricultural quarantine pest, causing substantial economic losses to citrus and many other cultivated crops. Aleurocanthus woglumi is found in tropical and subtropical regions but is presently unknown in Europe and the Mediterranean Basin. We used CLIMEX to model the potential distribution of A. woglumi under an historical climate scenario (centred on 1995), including a spatially explicit irrigation scenario. We found that A. woglumi could potentially invade the Mediterranean Basin, and south-east Asia, including Australia. There is potential for it to invade most of sub-Saharan Africa. Irrigation is revealed as an important habitat factor affecting the potential distribution of A. woglumi, increasing its potential range by 53% in Asia. Under a future climate scenario for 2050, its potential distribution increased across all continents except Africa, where potential range expansion due to relaxation of cold stresses was limited, and was offset by range decrease due to lethal heat or dry stress. As global climates warm, Europe is likely to face a substantial increase in the area at risk of establishment by A. woglumi (almost doubling under the 2050 irrigation scenario). The biosecurity threat from A. woglumi is significant in current citrus production areas and poses a challenge to biosecurity managers and risk analysts.

Effects of straw return with N fertilizer reduction on crop yield, plant diseases and pests and potential heavy metal risk in a Chinese rice paddy: A field study of 2 consecutive wheat-rice cycles

Understanding the comprehensive effect on crop production and quality, soil acidification, and Cd accumulation and distribution for wheat-rice rotation under N fertilization and continuous straw return is important for proper contaminated agricultural soil management. A 2-year paddy field experiment was conducted to study the effects of above factors change in the Zhejiang province, China. Fertilization treatments included: conventional N fertilizer application (N3), 20% reduction of N application (N2), 40% reduction of N application (N1), combined with three portions of straw incorporation: all straws retention (N3), half of the straws into the fields (S2), 20% straws retention(S1). The N1 treatments significantly decreased crop yields compared to N2 and N3 treatments. Except for C2-wheat, soil pH generally decreased with increasing N fertilizer input in the order of N1>N2>N3, regardless of how many straws was amended. Moreover, we found that straw addition plus N fertilization had a intersystem impacts on Cd accumulation, distribution and availability. Although total Cd had different trends among 4 experimental seasons, when the N reduced 20% applied, the DTPA-Cd contents were lowest among 3 out of four experimental seasons, except for that of C2-wheat, where N2 treatments ranked the second lower contents. For most seasons, Cd contents in straws were higher than soils and lowest in grains, and S2N2 treatment performed an intermediate value among all treatments. Furthermore, our study demonstrated that S2 or N2 treatments or S2N2 reduced the potential risk of plant diseases and pests with lower disease index, disease cluster rate. Notably, the relative outbreak of pests was remarkably suppressed under S2 treatments, especially S2N2. Thus, these findings demonstrated that in wheat-rice rotation reducing 20% N fertilization with 50% straw returning may be a win-win practice in this region for the equilibrium between agricultural productivity, quality and low Cd polluted risk.

Global risk of invasion by Bactrocera zonata: Implications on horticultural crop production under changing climatic conditions

The peach fruit fly Bactrocera zonata (Saunders) (Diptera: Tephritidae) is an important invasive species causing substantial losses to the horticulture industry worldwide. Despite the severe economic impact caused by this pest in its native and invaded range, information on its potential range expansion under changing climate remains largely unknown. In this study, we employed maximum entropy (MaxEnt) modeling approach to predict the global potential climatic suitability of B. zonata under current climate and four Representative Concentration Pathways (RCPs) for the year 2050. Outputs from MaxEnt were merged with Spatial Production Allocation Model. A natural dispersal model using Gaussian dispersal kernel was developed. The Areas Under Curves generated by MaxEnt were greater than 0.92 for both current and future climate change scenarios, indicating satisfactory performances of the models. Mean temperature of the coldest quarter, precipitation of driest month and temperature seasonality significantly influenced the potential establishment of B. zonata. The models indicated high climatic suitability in tropical and subtropical areas in Asia and Africa, where the species has already been recorded. Suitable areas were predicted in West, East and Central Africa and to a lesser extent in Central and South America. Future climatic scenarios models, RCP 4.5 and 8.5 show significant potential range expansion of B. zonata in Western Sahara, while RCP 4.5 highlighted expansion in Southern Africa. Contrarily, RCP 2.6 showed considerable decrease in B. zonata range expansion in Central, East and West Africa. There was increased climatic suitability of B. zonata in Egypt and Middle East under RCP 6.0. The dispersal model revealed that B. zonata could spread widely within its vicinity with decreasing infestation rates away from the source points. Our findings can help to guide biosecurity agencies in decision-making and serve as an early warning tool to safeguard against the pest invasion into unaffected areas.

Models of Diabrotica Populations: Demography, Population Genetics, Geographic Spread, and Management

Simple Summary

Two beetles that are serious pests of maize, Diabrotica virgifera virgifera and Diabrotica barberi, have caused problems for farmers in the USA and Europe for many years. Because both species have developed resistance to several management tactics, including insecticides and crop rotation, mathematical modeling has been used to evaluate their life cycles for weaknesses and new tactics for value. This review highlights lessons learned from the past 35 years. Some models have focused on the probability of the beetles spreading across regions. Other models have been developed to estimate the risk of the evolution of resistance. These models are thoroughly reviewed with respect to the biological attributes incorporated in these models and the impact of those attributes on the evolution of resistance.

Abstract

Both Diabrotica virgifera virgifera LeConte and D. barberi Smith and Lawrence are among the most damaging insects impacting corn in North America. D. virgifera virgifera has also invaded Europe and has become an important pest in that region. Computer models have become an important tool for understanding the impact and spread of these important pests. Over the past 30 years, over 40 models have been published related to these pests. The focus of these models range from occupancy models (particularly for Europe), impact of climate change, range expansion, economics of pest management, phenology, to the evolution of resistance to toxins and crop rotation. All of these models share characteristics. We elaborate on the methods in which modelers have incorporated the biology of these pests, including density-dependence, movement, fecundity and overwintering mortality. We discuss the utility of both spatially-explicit, complex models and spatially-implicit, generational models and where each might be appropriate. We review resistance models that either explain past evolution to crop rotation, insecticides or insecticidal traits or attempt to predict the consequences of resistance management strategies.

Modelling for risk and biosecurity related to forest health

Modelling the invasion and emergence of forest pests and pathogens (PnPs) is necessary to quantify the risk levels for forest health and provide key information for policy makers. Here, we make a short review of the models used to quantify the invasion risk of exotic species and the emergence risk of native species. Regarding the invasion process, models tackle each invasion phase, e.g. pathway models to describe the risk of entry, species distribution models to describe potential establishment, and dispersal models to describe (human-assisted) spread. Concerning the emergence process, models tackle each process: spread or outbreak. Only a few spread models describe jointly dispersal, growth, and establishment capabilities of native species while some mechanistic models describe the population temporal dynamics and inference models describe the probability of outbreak. We also discuss the ways to quantify uncertainty and the role of machine learning. Overall, promising directions are to increase the models’ genericity by parameterization based on meta-analysis techniques to combine the effect of species traits and various environmental drivers. Further perspectives consist in considering the models’ interconnection, including the assessment of the economic impact and risk mitigation options, as well as the possibility of having multi-risks and the reduction in uncertainty by collecting larger fit-for-purpose datasets.

Modeling Commodity Flow in the Context of Invasive Species Spread: Study of Tuta absoluta in Nepal

Trade and transport of goods is widely accepted as a primary pathway for the introduction and dispersal of invasive species. However, understanding commodity flows remains a challenge owing to its complex nature, unavailability of quality data, and lack of systematic modeling methods. A robust network-based approach is proposed to model seasonal flow of agricultural produce and examine its role in pest spread. It is applied to study the spread of Tuta absoluta, a devastating pest of tomato in Nepal. Further, the long-term establishment potential of the pest and its economic impact on the country are assessed. Our analysis indicates that regional trade plays an important role in the spread of T. absoluta. The economic impact of this invasion could range from USD 17-25 million. The proposed approach is generic and particularly suited for data-poor scenarios.

A Model to Predict the Expansion of Trioza erytreae throughout the Iberian Peninsula Using a Pest Risk Analysis Approach

Simple Summary

The African citrus psyllid Trioza erytreae is a natural vector of Candidatusliberibacter spp., the causal agent of the “citrus greening disease”. Citrus greening has not yet been detected in Europe; however, it represents a serious threat to citrus production. In this work, we parameterize a series of models to predict the expected spread of T. erytreae in the Iberian Peninsula since its introduction in 2014. Although T. erytreae was first detected in northwestern Spain, its detection and rapid spread around Porto (in Portugal) shortly afterward suggests a second entry point or transport of infested plant material from Spain. Among the developed models, the one that covered the known spread of T. erytreae best after 5 years was the kernel model with two simultaneous entry points. The invaded area predicted beyond the observed spread strongly suggests a physical and/or bioclimatic barrier preventing further spread of T. erytreae. Further development and refinement of models are crucial to accurately predicting the potential future spread of T. erytreae throughout the Iberian Peninsula. Accurate models will aid the development of successful management and regulatory programs.

Abstract

Assessing the potential of spread of an introduced crop pest in a new country is crucial to anticipating its effects on crop production and deriving phytosanitary management toward reducing potential negative effects. Citrus production represents a key agricultural activity throughout the Mediterranean basin. The African citrus psyllid Trioza erytreae (del Guercio, 1918) (Hemiptera: Triozidae) is a natural vector of Candidatusliberibacter spp., the causal agent of the harmful disease huanglongbing (HLB) or “citrus greening disease”. In continental Europe, T. erytreae was detected for the first time in northwestern Spain in 2014. Pest risk analysis (PRA) approaches, such as modeling, consider both time and space components to predict the potential distribution of pests in a given region. In this work, we aim to parameterize a model able to predict the expected spread of T. erytreae in the Iberian Peninsula using three types of PRA models. The kernel model with two hypothetical entry points accurately predicted the distribution of T. erytreae with respect to latitude. This model should be further refined and validated to support decision-makers in the adoption of timely and successful management and regulatory measures against the spread of T. erytreae to other citrus-producing areas in Europe.

Arthropod Invasions Versus Soybean Production in Brazil: A Review

Soybean production in Brazil has been markedly affected by invasions of non-native arthropod species that feed on the crop, severely impacting biodiversity, food security, health, and economic development. Data on soybean production losses and increase in insecticide usage over the last two decades have not been explored in association with past invasion events, and the dynamics underlying the recent blitz of invasive species into Brazil remain largely unclear. We provide a review of arthropod invasions in the Brazilian soybean agroecosystem since 1990, indicating that the introductions of Bemisia tabaci (Gennadius) MEAM1 (Hemiptera: Aleyrodidae), Tetranychus urticae (Koch) (Acari: Tetranychidae), and Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) are likely correlated with periods of increase in insecticide usage for soybean production. Using these three cases as examples, we review factors that could lead to increased likelihood of future invasions by particular pests, outlining four possible criteria to evaluate potential invasiveness of non-native arthropods: likelihood of entry, likelihood of establishment, biological features of the species, and availability of control measures. Spodoptera litura (F.) (Lepidoptera: Noctuidae) and Aphis glycines (Matsumura) (Hemiptera: Sternorrhynca) are examples of highly damaging soybean pests, related to one or more of these factors, that could be introduced into Brazil over the next years and which could lead to problematic scenarios. Melanagromyza sojae (Zehnter) (Diptera: Agromyzidae) also meets these criteria and has successfully invaded and colonized Brazilian soybean fields in recent years. Our review identifies current issues within soybean pest management in Brazil and highlights the need to adopt management measures to offset future costs and minimize lost revenue.

Pathologists and entomologists must join forces against forest pest and pathogen invasions

The world’s forests have never been more threatened by invasions of exotic pests and pathogens, whose causes and impacts are reinforced by global change. However, forest entomologists and pathologists have, for too long, worked independently, used different concepts and proposed specific management methods without recognising parallels and synergies between their respective fields. Instead, we advocate increased collaboration between these two scientific communities to improve the long-term health of forests.

Our arguments are that the pathways of entry of exotic pests and pathogens are often the same and that insects and fungi often coexist in the same affected trees. Innovative methods for preventing invasions, early detection and identification of non-native species, modelling of their impact and spread and prevention of damage by increasing the resistance of ecosystems can be shared for the management of both pests and diseases.

We, therefore, make recommendations to foster this convergence, proposing in particular the development of interdisciplinary research programmes, the development of generic tools or methods for pest and pathogen management and capacity building for the education and training of students, managers, decision-makers and citizens concerned with forest health.

Impact of Xylella fastidiosa subspecies pauca in European olives

Xylella fastidiosa is the causal agent of plant diseases that cause massive economic damage. In 2013, a strain of the bacterium was, for the first time, detected in the European territory (Italy), causing the Olive Quick Decline Syndrome. We simulate future spread of the disease based on climatic-suitability modeling and radial expansion of the invaded territory. An economic model is developed to compute impact based on discounted foregone profits and losses in investment. The model projects impact for Italy, Greece, and Spain, as these countries account for around 95% of the European olive oil production. Climatic suitability modeling indicates that, depending on the suitability threshold, 95.5 to 98.9%, 99.2 to 99.8%, and 84.6 to 99.1% of the national areas of production fall into suitable territory in Italy, Greece, and Spain, respectively. For Italy, across the considered rates of radial range expansion the potential economic impact over 50 y ranges from 1.9 billion to 5.2 billion Euros for the economic worst-case scenario, in which production ceases after orchards die off. If replanting with resistant varieties is feasible, the impact ranges from 0.6 billion to 1.6 billion Euros. Depending on whether replanting is feasible, between 0.5 billion and 1.3 billion Euros can be saved over the course of 50 y if disease spread is reduced from 5.18 to 1.1 km per year. The analysis stresses the necessity to strengthen the ongoing research on cultivar resistance traits and application of phytosanitary measures, including vector control and inoculum suppression, by removing host plants.

Many unreported crop pests and pathogens are probably already present

Invasive species threaten global biodiversity, food security and ecosystem function. Such incursions present challenges to agriculture where invasive species cause significant crop damage and require major economic investment to control production losses. Pest risk analysis (PRA) is key to prioritize agricultural biosecurity efforts, but is hampered by incomplete knowledge of current crop pest and pathogen distributions. Here, we develop predictive models of current pest distributions and test these models using new observations at subnational resolution. We apply generalized linear models (GLM) to estimate presence probabilities for 1,739 crop pests in the CABI pest distribution database. We test model predictions for 100 unobserved pest occurrences in the People's Republic of China (PRC), against observations of these pests abstracted from the Chinese literature. This resource has hitherto been omitted from databases on global pest distributions. Finally, we predict occurrences of all unobserved pests globally. Presence probability increases with host presence, presence in neighbouring regions, per capita GDP and global prevalence. Presence probability decreases with mean distance from coast and known host number per pest. The models are good predictors of pest presence in provinces of the PRC, with area under the ROC curve (AUC) values of 0.75-0.76. Large numbers of currently unobserved, but probably present pests (defined here as unreported pests with a predicted presence probability >0.75), are predicted in China, India, southern Brazil and some countries of the former USSR. We show that GLMs can predict presences of pseudoabsent pests at subnational resolution. The Chinese literature has been largely inaccessible to Western academia but contains important information that can support PRA. Prior studies have often assumed that unreported pests in a global distribution database represent a true absence. Our analysis provides a method for quantifying pseudoabsences to enable improved PRA and species distribution modelling.

Many unreported crop pests and pathogens are probably already present

Invasive species threaten global biodiversity, food security and ecosystem function. Such incursions present challenges to agriculture where invasive species cause significant crop damage and require major economic investment to control production losses. Pest risk analysis (PRA) is key to prioritize agricultural biosecurity efforts, but is hampered by incomplete knowledge of current crop pest and pathogen distributions. Here, we develop predictive models of current pest distributions and test these models using new observations at subnational resolution. We apply generalized linear models (GLM) to estimate presence probabilities for 1,739 crop pests in the CABI pest distribution database. We test model predictions for 100 unobserved pest occurrences in the People's Republic of China (PRC), against observations of these pests abstracted from the Chinese literature. This resource has hitherto been omitted from databases on global pest distributions. Finally, we predict occurrences of all unobserved pests globally. Presence probability increases with host presence, presence in neighbouring regions, per capita GDP and global prevalence. Presence probability decreases with mean distance from coast and known host number per pest. The models are good predictors of pest presence in provinces of the PRC, with area under the ROC curve (AUC) values of 0.75-0.76. Large numbers of currently unobserved, but probably present pests (defined here as unreported pests with a predicted presence probability >0.75), are predicted in China, India, southern Brazil and some countries of the former USSR. We show that GLMs can predict presences of pseudoabsent pests at subnational resolution. The Chinese literature has been largely inaccessible to Western academia but contains important information that can support PRA. Prior studies have often assumed that unreported pests in a global distribution database represent a true absence. Our analysis provides a method for quantifying pseudoabsences to enable improved PRA and species distribution modelling.

Effects of land use on infestation and parasitism rates of cabbage seed weevil in oilseed rape

BACKGROUND

This study investigated how infestation rates of an important oilseed rape pest, the cabbage seed weevil (Ceutorhynchus obstrictus) and rates of parasitization by its parasitoids are affected by land use, up to 1000 m from 18 focal fields.

RESULTS

The mean proportion of C. obstrictus-infested pods per plant was 8% (2-19.5%). Infestation rates were higher if the adjacent habitat was a herbaceous semi-natural habitat than if it was either another crop or a woody habitat. Infestation rates were positively related to the area of herbaceous semi-natural vegetation, permanent grassland and wheat (which followed oilseed rape in the crop rotation) at a spatial scale of at least 1 km. The mean parasitism rate of C. obstrictus larvae was 55% (8.3-87%), sufficient to provide efficient biocontrol. Parasitism rates were unrelated to adjacent habitats, however, they were positively related to the presence of herbaceous linear elements in the landscape and negatively related to permanent grasslands at a spatial scale of 200 m.

CONCLUSION

Proximity of herbaceous elements increased both infestation rates and parasitism, while infestation was also related to landscape factors at larger distances. The findings provide an empirical basis for designing landscapes that suppress C. obstrictus, at both field and landscape scales. © 2018 Society of Chemical Industry.

Guidance on quantitative pest risk assessment

This Guidance describes a two-phase approach for a fit-for-purpose method for the assessment of plant pest risk in the territory of the EU. Phase one consists of pest categorisation to determine whether the pest has the characteristics of a quarantine pest or those of a regulated non-quarantine pest for the area of the EU. Phase two consists of pest risk assessment, which may be requested by the risk managers following the pest categorisation results. This Guidance provides a template for pest categorisation and describes in detail the use of modelling and expert knowledge elicitation to conduct a pest risk assessment. The Guidance provides support and a framework for assessors to provide quantitative estimates, together with associated uncertainties, regarding the entry, establishment, spread and impact of plant pests in the EU. The Guidance allows the effectiveness of risk reducing options (RROs) to be quantitatively assessed as an integral part of the assessment framework. A list of RROs is provided. A two-tiered approach is proposed for the use of expert knowledge elicitation and modelling. Depending on data and resources available and the needs of risk managers, pest entry, establishment, spread and impact steps may be assessed directly, using weight of evidence and quantitative expert judgement (first tier), or they may be elaborated in substeps using quantitative models (second tier). An example of an application of the first tier approach is provided. Guidance is provided on how to derive models of appropriate complexity to conduct a second tier assessment. Each assessment is operationalised using Monte Carlo simulations that can compare scenarios for relevant factors, e.g. with or without RROs. This document provides guidance on how to compare scenarios to draw conclusions on the magnitude of pest risks and the effectiveness of RROs and on how to communicate assessment results.

Evidence-based economic analysis demonstrates that ecosystem service benefits of water hyacinth management greatly exceed research and control costs

Invasive species management can be a victim of its own success when decades of effective control cause memories of past harm to fade and raise questions of whether programs should continue. Economic analysis can be used to assess the efficiency of investing in invasive species control by comparing ecosystem service benefits to program costs, but only if appropriate data exist. We used a case study of water hyacinth (Eichhornia crassipes (Mart.) Solms), a nuisance floating aquatic plant, in Louisiana to demonstrate how comprehensive record-keeping supports economic analysis. Using long-term data sets, we developed empirical and spatio-temporal simulation models of intermediate complexity to project invasive species growth for control and no-control scenarios. For Louisiana, we estimated that peak plant cover would be 76% higher without the substantial growth rate suppression (84% reduction) that appeared due primarily to biological control agents. Our economic analysis revealed that combined biological and herbicide control programs, monitored over an unusually long time period (1975-2013), generated a benefit-cost ratio of about 34:1 derived from the relatively modest costs of $124 million ($2013) compared to the $4.2 billion ($2013) in benefits to anglers, waterfowl hunters, boating-dependent businesses, and water treatment facilities over the 38-year analysis period. This work adds to the literature by: (1) providing evidence of the effectiveness of water hyacinth biological control; (2) demonstrating use of parsimonious spatio-temporal models to estimate benefits of invasive species control; and (3) incorporating activity substitution into economic benefit transfer to avoid overstating benefits. Our study suggests that robust and cost-effective economic analysis is enabled by good record keeping and generalizable models that can demonstrate management effectiveness and promote social efficiency of invasive species control.

A modeling framework for the establishment and spread of invasive species in heterogeneous environments

Natural and human-induced events are continuously altering the structure of our landscapes and as a result impacting the spatial relationships between individual landscape elements and the species living in the area. Yet, only recently has the influence of the surrounding landscape on invasive species spread started to be considered. The scientific community increasingly recognizes the need for broader modeling framework that focuses on cross-study comparisons at different spatiotemporal scales. Using two illustrative examples, we introduce a general modeling framework that allows for a systematic investigation of the effect of habitat change on invasive species establishment and spread. The essential parts of the framework are (i) a mechanistic spatially explicit model (a modular dispersal framework-MDIG) that allows population dynamics and dispersal to be modeled in a geographical information system (GIS), (ii) a landscape generator that allows replicated landscape patterns with partially controllable spatial properties to be generated, and (iii) landscape metrics that depict the essential aspects of landscape with which dispersal and demographic processes interact. The modeling framework provides functionality for a wide variety of applications ranging from predictions of the spatiotemporal spread of real species and comparison of potential management strategies, to theoretical investigation of the effect of habitat change on population dynamics. Such a framework allows to quantify how small-grain landscape characteristics, such as habitat size and habitat connectivity, interact with life-history traits to determine the dynamics of invasive species spread in fragmented landscape. As such, it will give deeper insights into species traits and landscape features that lead to establishment and spread success and may be key to preventing new incursions and the development of efficient monitoring, surveillance, control or eradication programs.

Achieving Durable Resistance Against Plant Diseases: Scenario Analyses with a National-Scale Spatially Explicit Model for a Wind-Dispersed Plant Pathogen

Genetic resistance in crops is a cornerstone of disease management in agriculture. Such genetic resistance is often rapidly broken due to selection for virulence in the pathogen population. Here, we ask whether there are strategies that can prolong the useful life of plant resistance genes. In a modeling study, we compared four deployment strategies: gene pyramiding, sequential use, simultaneous use, and a mixed strategy. We developed a spatially explicit model for France and parameterized it for the fungal pathogen Puccinia striiformis f. sp. tritici (causing wheat yellow rust) to test management strategies in a realistic spatial setting. We found that pyramiding two new resistance genes in one variety was the most durable solution only when the virulent genotype had to emerge by mutation. Deploying single-gene-resistant varieties concurrently with the pyramided variety eroded the durability of the gene pyramid. We found that continuation of deployment of varieties with broken-down resistance prolonged the useful life of simultaneous deployment of four single-gene-resistant varieties versus sequential use. However, when virulence was already present in the pathogen population, durability was low and none of the deployment strategies had effect. These results provide guidance on effective strategies for using resistance genes in crop protection practice.

Development of a pathway model to assess the exposure of European pine trees to pine wood nematode via the trade of wood

Pine wood nematode (PWN), Bursaphelenchus xylophilus, is a threat for pine species (Pinus spp.) throughout the world. The nematode is native to North America, and invaded Japan, China, Korea, and Taiwan, and more recently Portugal and Spain. PWN enters new areas through trade in wood products. Once established, eradication is not practically feasible. Therefore, preventing entry of PWN into new areas is crucial. Entry risk analysis can assist in targeting management to reduce the probability of entry. Assessing the entry of PWN is challenging due to the complexity of the wood trade and the wood processing chain. In this paper, we develop a pathway model that describes the wood trade and wood processing chain to determine the structure of the entry process. We consider entry of PWN through imported coniferous wood from China, a possible origin of Portuguese populations, to Europe. We show that exposure increased over years due to an increase in imports of sawn wood. From 2000 to 2012, Europe received an estimated 84 PWN propagules from China, 88% of which arose from imported sawn wood and 12% from round wood. The region in Portugal where the PWN was first reported is among those with the highest PWN transfer per unit of imported wood due to a high host cover and vector activity. An estimated 62% of PWN is expected to enter in countries where PWN is not expected to cause the wilt of pine trees because of low summer temperatures (e.g., Belgium, Sweden, Norway). In these countries, PWN is not easily detected, and such countries can thus serve as potential reservoirs of PWN. The model identifies ports and regions with high exposure, which helps targeting monitoring and surveillance, even in areas where wilt disease is not expected to occur. In addition, we show that exposure is most efficiently reduced by additional treatments in the country of origin, and/or import wood from PWN-free zones. Pathway modelling assists plant health managers in analyzing risks along the pathway and planning measures for enhancing biosecurity.

Altitudinal Barrier to the Spread of an Invasive Species: Could the Pyrenean Chain Slow the Natural Spread of the Pinewood Nematode?

Mountain ranges may delimit the distribution of native species as well as constitute potential barriers to the spread of invasive species. The invasive pinewood nematode, Bursaphelenchus xylophilus, is a severe forest pest inducing pine wilt disease. It is vectored in Europe by a native long-horned beetle, Monochamus galloprovincialis. This study explored the potential of the Pyrenean chain to slow or prevent the natural spread of nematode-infested beetles from the Iberian Peninsula, where the nematode is established and is expanding its range, towards France and the rest of Europe. An analysis of the genetic structure and migration patterns of the beetle populations throughout the Pyrenean mountain range was combined with a spread model simulating the potential movements of nematode-infested beetles across it. The central part of the Pyrenees, which corresponds to the highest elevation zone, was shown to prevent gene flow between the French and Spanish populations of M. galloprovincialis on each side of the mountains. Conversely, strong admixture was detected between populations located on both sides of low elevation hills, and especially at the east and west extremities of the mountain range. Simulations of the spread of nematode-infested beetles under various thresholds of beetle survival and pine wilt disease expression gave results consistent with the variation in genetic make-up, suggesting that western and eastern hillsides may represent corridors favoring natural spread of the nematode from the Iberian Peninsula to France. Simulations also showed that temperature rise due to climate change may significantly reduce the extent of the barrier formed by highest elevations. Our results support the hypothesis that the Pyrenean chain represents a partial barrier to the natural spread of nematode-infested beetles. These results, which have to be considered together with potential human-assisted long-distance spread of the nematode, highlight priority zones for future pest monitoring and management programs. More generally, such an integrated approach could be used to assess the role of mountain chains in the potential spread of other invasive pests.

Sharka epidemiology and worldwide management strategies: learning lessons to optimize disease control in perennial plants

Many plant epidemics that cause major economic losses cannot be controlled with pesticides. Among them, sharka epidemics severely affect prunus trees worldwide. Its causal agent, Plum pox virus (PPV; genus Potyvirus), has been classified as a quarantine pathogen in numerous countries. As a result, various management strategies have been implemented in different regions of the world, depending on the epidemiological context and on the objective (i.e., eradication, suppression, containment, or resilience). These strategies have exploited virus-free planting material, varietal improvement, surveillance and removal of trees in orchards, and statistical models. Variations on these management options lead to contrasted outcomes, from successful eradication to widespread presence of PPV in orchards. Here, we present management strategies in the light of sharka epidemiology to gain insights from this worldwide experience. Although focused on sharka, this review highlights more general levers and promising approaches to optimize disease control in perennial plants.

Range-expanding pests and pathogens in a warming world

Crop pests and pathogens (CPPs) present a growing threat to food security and ecosystem management. The interactions between plants and their natural enemies are influenced by environmental conditions and thus global warming and climate change could affect CPP ranges and impact. Observations of changing CPP distributions over the twentieth century suggest that growing agricultural production and trade have been most important in disseminating CPPs, but there is some evidence for a latitudinal bias in range shifts that indicates a global warming signal. Species distribution models using climatic variables as drivers suggest that ranges will shift latitudinally in the future. The rapid spread of the Colorado potato beetle across Eurasia illustrates the importance of evolutionary adaptation, host distribution, and migration patterns in affecting the predictions of climate-based species distribution models. Understanding species range shifts in the framework of ecological niche theory may help to direct future research needs.

Long-range dispersal, stochasticity and the broken accelerating wave of advance

Rare long distance dispersal events are thought to have a disproportionate impact on the spread of invasive species. Modelling using integrodifference equations suggests that, when long distance contacts are represented by a fat-tailed dispersal kernel, an accelerating wave of advance can ensue. Invasions spreading in this manner could have particularly dramatic effects. Recently, various authors have suggested that demographic stochasticity disrupts wave acceleration. Integrodifference models have been widely used in movement ecology, and as such a clearer understanding of stochastic effects is needed. Here, we present a stochastic non-linear one-dimensional lattice model in which demographic stochasticity and the dispersal regime can be systematically varied. Extensive simulations show that stochasticity has a profound effect on model behaviour, and usually breaks acceleration for fat-tailed kernels. Exceptions are seen for some power law kernels, K(l)∝|l|^-β with β<3, for which acceleration persists despite stochasticity. Such kernels lack a second moment and are important in 'accelerating' phenomena such as Lévy flights. Furthermore, for long-range kernels the approach to the continuum limit behaviour as stochasticity is reduced is generally slow. Given that real-world populations are finite, stochastic models may give better predictive power when long-range dispersal is important. Insights from mean-field models such as integrodifference equations should be applied with caution in such circumstances.