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Evidence Project Final Report

 Note In line with the Freedom of Information Project identification Act 2000, Defra aims to place the results of its completed research projects in the public domain wherever possible. 1. Defra Project code FFG1207 The Evidence Project Final Report is designed to capture the information on 2. Project title the results and outputs of Defra-funded Adding tree health value to UK monitoring networks research in a format that is easily publishable through the Defra website An Evidence Project Final Report must be completed for all projects. 3. Contractor Plymouth University  This form is in Word format and the organisation(s) boxes may be expanded, as appropriate.

 ACCESS TO INFORMATION The information collected on this form will be stored electronically and may be sent 54. Total Defra project costs £29878 to any part of Defra, or to individual researchers or organisations outside (agreed fixed price) Defra for the purposes of reviewing the project. Defra may also disclose the 5. Project: start date ...... 1 December 2012 information to any outside organisation acting as an agent authorised by Defra to 31 March 2013 process final research reports on its end date ...... behalf. Defra intends to publish this form on its website, unless there are strong reasons not to, which fully comply with exemptions under the Environmental Information Regulations or the Freedom of Information Act 2000. Defra may be required to release information, including personal data and commercial information, on request under the Environmental Information Regulations or the Freedom of Information Act 2000. However, Defra will not permit any unwarranted breach of confidentiality or act in contravention of its obligations under the Data Protection Act 1998. Defra or its appointed agents may use the name, address or other details on your form to contact you in connection with occasional customer research aimed at improving the processes through which Defra works with its contractors.

EVID4 Evidence Project Final Report (Rev. 06/11) Page 1 of 37 6. It is Defra‟s intention to publish this form. Please confirm your agreement to do so...... YES X NO (a) When preparing Evidence Project Final Reports contractors should bear in mind that Defra intends that they be made public. They should be written in a clear and concise manner and represent a full account of the research project which someone not closely associated with the project can follow. Defra recognises that in a small minority of cases there may be information, such as intellectual property or commercially confidential data, used in or generated by the research project, which should not be disclosed. In these cases, such information should be detailed in a separate annex (not to be published) so that the Evidence Project Final Report can be placed in the public domain. Where it is impossible to complete the Final Report without including references to any sensitive or confidential data, the information should be included and section (b) completed. NB: only in exceptional circumstances will Defra expect contractors to give a "No" answer. In all cases, reasons for withholding information must be fully in line with exemptions under the Environmental Information Regulations or the Freedom of Information Act 2000. (b) If you have answered NO, please explain why the Final report should not be released into public domain

Executive Summary 7. The executive summary must not exceed 2 sides in total of A4 and should be understandable to the intelligent non-scientist. It should cover the main objectives, methods and findings of the research, together with any other significant events and options for new work. Project Rationale The frequency with which invasive tree pests have become established in the UK has increased in recent years. One interpretation of this observation is that, against a background of changes to global trade patterns, current pest surveillance systems are no longer sufficient to deliver biosecurity by themselves. This project considered the potential for introducing an additional level of surveillance, using existing monitoring networks.

Project Objectives 1. review existing monitoring and sampling schemes (professional and amateur) and evaluate their potential to contribute to enhanced plant health surveillance; 2. evaluate a wide range of trapping and sampling methods (e.g. canopy entomology) targeted at the major insect orders and pests included in the EPPO A1 and A2 lists,in particular; 3. assess the potential for using new technologies (e.g. next generation sequencing) to resolve detection and identification issues anticipated to arise when adapting existing monitoring and sampling methods; 4. identify existing and potential mathematical modelling approaches that can support the cost-effective design of surveillance systems (similar to those used for the Defra Phytophthora programme); 5. consider the process of data recording and timely delivery of information about potential threats

Project Activities A desk study was undertaken to identify and evaluate existing insect and other monitoring schemes. A total of 287 such networks were identified. In addition, a meeting was held with Tim Elliot of the Meteorological Office to consider the potential of utilising

EVID4 Evidence Project Final Report (Rev. 06/11) Page 2 of 37 the well-established network of volunteers contributing to the Climate Network.

The EPPO A1 and A2 pest lists were critically examined and evaluated for their potential risk to UK trees. Additional species of concern to the Forestry Commission were also incorporated to provide a working „risk register‟ for this project. A total of 73 species spanning five insect orders were identified as potential threats. Of these, 57 had records of some form of attractant having been identified and specific traps were reported for 39 species.

The species on the risk register were used to evaluate the range of potential insect trap types.

We explored the potential for next generation sequencing to provide timely information about species presence and spread, and the possibilities for mathematical modelling to be used in deciding how many and where traps should be located, through meetings with experts.

A critical constraint in any monitoring system is the delivery of timely information and problems relating to location and identification of target organisms that appear at low frequency in large multi-species trap catches often represents a significant time-limiting step. A meeting was held with the sequencing and bioinformatics groups at The Genomic Analysis Centre (TGAC) in Norwich to evaluate the potential of next generation sequencing and metagenomics for resolving this issue.

The requirements for mathematical modelling to support the design of surveillance systems were discussed in meetings with the Gilligan laboratory (Cambridge University) and the van den Bosche group at Rothamsted.

A workshop was held on 20 March 2013 to consider and test ideas emerging from the project and confirm identified research gaps.

Project Conclusions 1. No suitable network exists for straightforward adaptation to provide an additional level of biosecurity surveillance. 2. Most insect trapping methods are tailored to specific taxa. There is some evidence that combining characteristics of different trap types increases the diversity of captured but only suction traps are known to be taxonomically neutral with respect to the species that they catch. 3. Next generation technologies are capable of determining (rapidly and cost- effectively) if a known species is present within a mixed species sample. 4. Sample preparation rather than processing is the greater constraint for DNA-based methods; a turnaround time of one week from receipt is feasible. 5. Epidemiological models developed to forecast the spread of pests and diseases can be adapted to support additional biosecurity surveillance by forecasting insect dispersal, and hence be used to examine permutations of trapping networks. 6. The concept of a new national monitoring network, complimenting existing Plant Health procedures by providing timely information about the presence or absence of targeted pest species, is scientifically and technically viable.

Research Gaps In order to test the feasibility of a new national pest monitoring network, the following research requirements have been identified:

1. Development of a simple, robust and functional multi-taxa insect trap.

EVID4 Evidence Project Final Report (Rev. 06/11) Page 3 of 37 2. Testing and demonstration that specific sequences can be detected from whole trap catch DNA extraction. 3. Determination of characteristics associated with volunteers operating long-term, sustainable scientific networks. 4. Mathematical models to optimise the geographic location of traps. 5. Optimisation of species-specific trapping methods for all targets on a national risk register. 6. Evaluation of multi-species lure mixtures to potentiate traps for risk register species.

Project Report to Defra

Project consortium

The consortium brought together expertise in plant health (Walters), national insect surveillance (Harrington), and insect spatial ecology/dispersal and the functioning of trapping systems (Blackshaw). The participants have over 100 years combined experience studying pests and their management.

Dr Keith Walters is Senior Research Fellow at Imperial College London. His personal research interests, developed during the last 25 years, have been focused on two programmes of multidisciplinary collaborative work. The first addresses issues at the science/policy interface, investigating the consequences for the natural environment, agriculture and forestry, of globalisation of the world trade in plants and plant products. It concentrates on the biology, impact and policy options for quarantine pests and diseases and has led to collaborative projects involving a range of discipline specialists. The second centres on sustainable agricultural production and the mitigation of environmental damage resulting from xenobiotics in the agri-environment. His research has benefited in recent years from experience gained through the leadership of a large Plant Health disease management programme (The Defra Phytophthora programme), including strategic planning, coordination and integration of surveillance and management activities, integration/application of research outputs and public awareness/behavioural change activities. Recent work has included the use of mathematical modelling techniques for containment and eradication of pests and diseases of quarantine importance (with Univ. Cambridge), development/integration of novel approaches/techniques to reduce establishment frequency of quarantine pests (with Univ.

EVID4 Evidence Project Final Report (Rev. 06/11) Page 4 of 37 Warwick), and stakeholder/volunteer engagement in national surveillance and containment campaigns/networks for quarantine organisms. He currently also sits on the SETAC group developing European-wide monitoring approaches (with special remit for terrestrial ).

Dr Richard Harrington leads the Rothamsted Insect Survey, a BBSRC-support National Capability. A suction trap network and a light trap network have been assembling daily data on aphids and moths since the mid-sixties and both networks have recorded many insects which threaten plant health, including invasives. Richard‟s main research interests are provision of data to help decision making in pest control and in conservation strategy, and the impacts of climate change on pest and beneficial insects.

Professor Rod Blackshaw is currently the Director of the Centre for Agricultural and Rural Sustainability (CARS) at Plymouth University and leads a multidisciplinary research group addressing issues that directly affect food security and environmental sustainability of agricultural systems. Within CARS and relevant to this proposal is a canopy research group. His personal research involves the development of new mathematical methods to interpret trap catches (with Leicester University), the dispersal and trapping of adult stages of root herbivores (with Agriculture and AgFood Canada), the development of sequence-based identification methods for cryptic genera (with Innsbruck (Austria) and Simon Fraser (Canada) universities) and the deployment of stable isotope technologies to investigate soil food webs and nutrient cycling (with Rothamsted, North Wyke).

Contract Objectives

This project aimed to establish the potential of existing sampling programmes to form the basis of a new national surveillance network and to identify the research requirements that would be necessary to adapt existing systems. Specific objectives were to:

1. review existing insect monitoring and sampling schemes (professional and amateur) and evaluate their potential to contribute to enhanced plant health surveillance; 2. evaluate a wide range of trapping and sampling methods (e.g. canopy entomology) targeted at the major insect orders and pests included in the EPPO A1 and A2 lists in particular; 3. assess the potential for using new technologies (e.g. next generation sequencing) to resolve; detection and identification issues anticipated to arise when adapting existing monitoring and sampling methods; 4. identify existing and potential mathematical modelling approaches that can support the cost-effective design of surveillance systems (similar to those used for the Defra Phytophthora programme); 5. consider the process of data recording and timely delivery of information about potential threats

Extent to which the aims and objectives have been met All objectives were addressed during the course of the project. Our expected outcomes were: 1. recommendations for the extension of one or more monitoring networks to deliver value- added plant health surveillance ; 2. recommendations for the adaptation of such networks (prioritised by estimated cost) to ensure fitness for purpose; 3. identification of research requirements needed to make networks operational; 4. assembly of new consortia to prepare research proposals for Phase 2.

EVID4 Evidence Project Final Report (Rev. 06/11) Page 5 of 37 In practice, it became apparent that no existing network was fit for our purpose and so outcomes 1 and 2 were extended to incorporate use of the knowledge gained to enable us to conceptualise the scope and potential structure of a biosecurity surveillance network and to define the research necessary to test and evaluate the proposals.

Methods We approached this as a desk study, using the primary literature to understand the biological attributes of pest species wherever possible and supplementing this with internet searches for other information. Over 250 peer-reviewed references were considered.

The desk studies were supplemented by interviews with key experts. The requirements for mathematical modelling to support the design of surveillance systems were discussed in meetings with the Gilligan laboratory (Cambridge University), the van den Bosche group at Rothamsted, and the Petrovskii laboratory at Leicester University. The potential for next generation technologies was discussed with the Sequencing and Bioinformatics groups at The Genome Analysis Centre, Norwich. Discussions with Tim Elliot (Meteorological Office) were valuable in understanding the long-term sustainability of the Climate Network and how characteristics of their volunteers may not be typical of citizen scientists.

The three members of the project consortium attended several workshops run by other Phase 1 projects. This provided further input into our thinking. We tested the ideas about a new approach to pest surveillance we developed during the course of this project in a workshop (organised by the project consortium) at Rothamsted on 20 March 2013.

Results 287 existing biological networks were evaluated during the course of the study. We concluded that none of these could form the foundation for a robust and sustainable tree health surveillance network. Individual reasons for this varied but generally included one or more of poor geographic coverage, intermittent sampling, focus on specific taxa or too few participants. Discussions with the Meteorological Office about their Climate Network revealed that although it was not directly suitable for this purpose because of inadequate geographic coverage, volunteers delivering data were committed and reliable. The instance of one site being operated over three generations indicated that these volunteers might have distinctive characteristics when compared to other citizen scientists.

By evaluating the detailed biological information of insect pest species on the A1 and A2 lists together with those identified by the Forestry Commission as being of particular concern we produced a „risk register‟ of 73 species. These spanned five insect orders. Of these, 57 had records of some form of attractant having been identified and specific traps were reported for 39 species. Details are provided in Appendix 1.

This risk register was then used to consider the potential of different insect trapping methods to detect invasive pests. Generally, traps are predominantly useful for selected taxa. There has been relatively little research into developing traps targeted at insect biodiversity per se, rather they reflect the primary interests of the entomologists who operate them. The only type that reliably catches a wide range of taxa is a suction trap. Here though, the network of suction traps operated by the Rothamsted Insect Survey is too small to provide adequate geographic coverage and the fact that samples are used to create an archive of specimens also prevents a functional extension of its use for biosecurity monitoring. The potential usefulness of suction traps is confirmed by unpublished data from Plymouth University that shows that these traps detect the presence of a wider range of insect species in tree canopies than other types.

EVID4 Evidence Project Final Report (Rev. 06/11) Page 6 of 37 Key to any operational network is the need to be able to rapidly determine if a potential pest threat has been discovered. Experience with the Rothamsted Insect Survey has shown that conventional taxonomic approaches are too resource intensive to identify more than a small portion of the captured species within the real-time requirements of the proposed surveillance network. Linked to this is the UK national shortage of taxonomic expertise. Thus, traditional approaches are not able to deliver a cost-effective monitoring system.

Sequencing is increasingly used to identify closely related species that are morphologically similar. A selected region of the genome, such as CO1, usually provides sufficient information to identify a species by reference to an international resource such as the Biodiversity of Life Database (BOLD). These methods have so far been used to a) separate difficult species and b) confirm identifications. Whilst knowledge of the sequences from risk register species is an essential precursor for any application of DNA methodologies to monitoring pest arrival and spread, there needs to be a paradigm shift in the way that this is approached. In some respects, eukaryote lags behind prokaryote research. For example, microbiologists will determine the diversity of communities by establishing the number of instances of which a specific sequence is detected (number of „reads‟). Each distinct sequence is known as an operational taxonomic unit (OTU) and the number of these defines biodiversity. Furthermore, the presence of functional genes of interest can also be determined.

These approaches have been made possible by the development of next generation sequencing technologies. We considered whether these could be applied to the taxonomic/identification outlined above. In any surveillance network, the traps that are used will capture a wide range of insects and will need to catch reasonable numbers if invasive pests are to be detected at an earlier point in the colonisation process than at present. The objective is to detect a known sequence – previously determined for risk register insects - against a background of sequences from the pool of sampled insects. We concluded that the objective is achievable but with the caveat that difficulties related to the presence of introgression (whereby the target sequence is very similar to that of an indigenous species) may need to be overcome. In these circumstances, deploying a second sequence can resolve the problem and so an hierarchical process would be an option.

Following confirmation of the technical feasibility of using sequencing technology, we next gave consideration to whether timely information can be delivered. The consensus that emerged was that a turnaround from receipt of a sample in the laboratory to delivery of results within a week could be achieved. To do this, robotic systems would have to be deployed but the technology exists for this.

Development of appropriate bioinformatics to support this is an essential component. In theory, we can also „train‟ the system to deliver other knowledge. For example, individual OTU profiles for traps can be used to provide a measure of biodiversity and be compared, even if the species present are unknown. Over time, therefore, it should be possible to „establish‟ which OTUs belong to native species (i.e. they appear regularly in the results) and hence increase the possibility of detecting invasive species that have not been previously defined as a threat. Where sequences of indigenous species are known, it would be possible to identify them.

This approach to insect monitoring is future-proof. A changing threat picture can be accommodated by adding new sequences to those of interest. Furthermore, this potential is not restricted to tree health but has broader application to plant biosecurity generally.

Whilst it does not form part of this project‟s remit, it is clear that a strategic, long-term national goal should be to sequence all common UK insects (about 24,000 species) so that the presence of any non-natives can be quickly determined. The data collected by the proposed network will contribute to this goal.

EVID4 Evidence Project Final Report (Rev. 06/11) Page 7 of 37

A range of mathematical models that describe and forecast the spread of invasive organisms (both pests and diseases) are available and have been used by authoprities in a range of countries to answer practical Plant Health questions. Our consultations indicated that the disease epidemiological models developed for Phytophthora (and some insect species) could be adapted if suitable biological data were available for target species. Reference to the literature indicates that such data has been published for many species on the projects‟ risk register. Similarly, there are programmes of research directed towards understanding insect dispersal using, for example, individual-based movement models, advection/diffusion models etc. Such models can be used to estimate the probabilities of detection with differing trap densities and spatial siting patterns.

Whilst it has been shown that models for single species are tractable a greater task is to optimise trap locations for multi-species trapping through development of a more generalized approach. This will present considerable intellectual challenge but is an essential component of surveillance and risk management.

Conceptualising a new insect pest surveillance system As a result of our review, we have conceptualised a nested surveillance programme that compliments and operates alongside existing Plant Health measures. The surveillance and response has three levels: 1. Primary level - a system of single multi-taxa traps with sufficient national geographic coverage to significantly increase the probability of intercepting a threat. Location of the traps would be optimised using epidemiological and behavioural modelling, and they would be operated on a weekly basis during the risk period. DNA from collected insects will be recovered and sequenced to reveal if any target species are present. (See Fig. 1). 2. Secondary level - a positive sequence find triggers this level and a response based on current Plant Health contingency plans initiated. In addition suitable species-specific trapping systems would be deployed to determine the geographic extent of the invasion. Identifications will again be confirmed by sequencing. It is likely that conventional sampling will also be undertaken as per existing approaches. In order to gain time to implement control measures through retarding population growth, mating disruption could be attempted using pheromones/kairomones. 3. Tertiary level - evaluation of success of interventions and re-examination of geographic invasive spread using species-specific trapping. Identification of need to apply further control measures as outlined in Plant Health contingency plans.

Future research to develop a new surveillance network

We have identified five inter-linked areas where research is required to evaluate the feasibility of this approach to reinforcing existing Plant Health approaches to biosecurity:

1. Development of a cost-effective and functional multi-taxa trap that reflects the biodiversity of threats and is capable of deployment by volunteers; 2. Integration of single species sequence knowledge into a detection tool using next generation sequencing and developing supporting bioinformatics; 3. Understanding the characteristics of volunteers who are capable of sustained commitment to operating monitoring traps, and the identification of rewards and incentives for them; 4. Mathematical models to understand how changes in spatial arrays of traps influence detection probabilities

EVID4 Evidence Project Final Report (Rev. 06/11) Page 8 of 37 5. Identification of species-specific lures for „risk register‟ species and the development of multi-taxa lures to potentiate traps.

Fig 1 Schematic of the operation of a new tree health insect surveillance system.

Action arising from the research

As a direct result of this project, a consortium was formed to take forward a proposal under Phase 2 of the Tree Health and Plant Biosecurity Initiative.

EVID4 Evidence Project Final Report (Rev. 06/11) Page 9 of 37 Appendix 1 The risk register of insect threats used in the project.

Table 1. Taxonomic grouping of selected insect species from the EPPO A1 and EPPO A2 lists of species recommended for regulation as quarantine pests, and of insect species identified as being of specific current concern to UK forestry in the status summaries published on the Forestry Commission web site. Species selected from the EPPO A1 and A2 lists were considered to pose a threat to tree health in the UK through their potential to establish in the UK natural environment and interact with the natural ecology of the area. Those from the FC Status Summaries were identified by their Tree Health Expert Group as either “Pests established in the UK”, “Pests newly arrived in the UK”, “Pests in the EU posing a threat to the UK”, or “Other pest threats globally”

Taxonomic Group EPPO A1 List: EPPO A2 List: FC Status Summaries: No. Species No. Species No. Species Coleoptera: Buprestidae 1 1 2 Cerambycidae 3 6 2 6 1 1 Scarabaeidae 1 Scolytidae 15 4 2

Diptera: Anthomyidae 1 Tephritidae 3 2

Homoptera: Cicadellidae 1 Diaspididae 2

Hymentoptera: Cynipidae 1 1 Siricidae 1

Lepidoptera: Carposinidae 1 Lasiocampidae 2 3 1 Lymantriidae 1 1 Noctuidae 1 Notodontidae 1 Tortricidae 8 2 1

EVID4 Evidence Project Final Report (Rev. 06/11) Page 10 of 37 Table 2. Species represented in the EPPO A1, EPPO A2 lists or identified as being of specific current concern to UK forestry by the FC Tree Health Expert Group. Species that appear in FC Status Summaries are classified as: (A) Pests established in the UK; (B) Pests newly arrived in the UK; (C) Pests in the EU posing a threat to the UK; or (D) Other pest threats globally.

Taxonomic EPPO A1 List EPPO A2 List FC Status Summaries Group

Coleoptera:

Buprestidae Agrilus anxius Agrilus anxius (D)

Agrilus planipennis Agrilus plannipennis (D)

Cerambycidae Anoplophora Anoplophora glabripennis glabripennis (C)

Monochamus spp (as disease vectors)

Saperda candida

Aeolesthes sarta

Anoplophora chinensis Anoplophora chinensis (C)

Hesperophanes campestris

Tetropium gracilicorne

Xylotrechus altaicus

Xylotrechus namanganensis

Curculionidae Conotrachelus nenuphar

Pissodes nemorensis

Pissodes strobe

Pissodes terminalis

Pseudopityophthorus minutissimus (as a disease vector)

Pseudopityophthorus pruinosus (as a disease vector)

Megaplatypus mutatus

EVID4 Evidence Project Final Report (Rev. 06/11) Page 11 of 37 Hylobius abietus (A)

Scarabaeidae Popillia japonica

Scolytidae Dryocoetes confuses

Gnathotrichus sulcatus

Ips calligraphus

Ips confuses

Ips paraconfusus

Ips grandicollis

Ips lecontei

Ips pini

Ips plastographus

Dendroctonus adjunctus

Dendroctonus brevicomis

Dendroctonus frontalis

Dendroctonus ponderosae

Dendroctonus pseudotsugae

Dendroctonus rufipennis

Ips cembrae

Ips hauseri

Ips subelongatus

Scolytus morawitzi

Dendroctonus micans (A)

Ips typographus (C)

Diptera:

Anthomyidae Strobilomyia viaria

Tephritidae Rhagoletis fausta

EVID4 Evidence Project Final Report (Rev. 06/11) Page 12 of 37 Rhagoletis indifferens

Rhagoletis pomonella

Ceratitis capitata

Rhagoletis cingulata

Homoptera:

Cicadellidae Scaphoideus luteolus (as a disease vector)

Diaspididae Lepidosaphes ussuriensis

Quadraspidiotus perniciosus

Hymentoptera: Dryocosmus kuriphilus (D) Cynipidae Dryocosmus kuriphilus

Siricidae Sirex ermak

Lepidoptera:

Carposinidae Carposina niponensis

Lasiocampidae Malacosoma americanum

Malacosoma disstria

Dendrolimus sibiricus

Dendrolimus superans

Malacosoma parallela Dendrolimus pini (B)

Lymantriidae Orgyia pseudotsugata

Lymantria mathura

Noctuidae Erschoviella musculana Thaumetopoea Notodontidae processionea (B)

Tortricidae Acleris gloverana

Acleris variana

EVID4 Evidence Project Final Report (Rev. 06/11) Page 13 of 37

Choristoneura conflictana Choristoneura fumiferana Choristoneura (D) fumiferana

Choristoneura occidentalis

Choristoneura rosaceana

Cydia packardi

Cydia prunivora

Cacoecimorpha pronubana

Cydia inopinata

EVID4 Evidence Project Final Report (Rev. 06/11) Page 14 of 37

Table 3. Characterisation of attractants or pheromones and development of lures or traps for the species represented in the EPPO A1, EPPO A2 or FC Tree Health Expert Group lists. (M) = Multiple attractants identified

Taxonomic Group Species Attractant or pheromone Lure or trap available characterised

Coleoptera:

Buprestidae Agrilus anxius Yes

Agrilus planipennis Yes (M)

Cerambycidae Aeolesthes sarta

Anoplophora chinensis Yes

Anoplophora Yes (M) glabripennis

Hesperophanes campestris

Monochamus spp (as Yes (M) Yes disease vectors)

Saperda candida

Tetropium gracilicorne

Xylotrechus altaicus

Xylotrechus namanganensis

Curculionidae Conotrachelus nenuphar Yes (M) Yes

Hylobius abietus Yes (M) Yes

Megaplatypus mutatus Yes

Pissodes nemorensis Yes (M) Yes

Pissodes strobe Yes (M) Yes

Pissodes terminalis

Pseudopityophthorus Yes minutissimus (as a disease vector)

Pseudopityophthorus pruinosus (as a disease

EVID4 Evidence Project Final Report (Rev. 06/11) Page 15 of 37 vector)

Scarabaeidae Popillia japonica Yes (M) Yes

Scolytidae Dendroctonus adjunctus Yes (M) Yes

Dendroctonus Yes (M) Yes brevicomis

Dendroctonus frontalis Yes (M) Yes

Dendroctonus micans Yes

Dendroctonus Yes (M) Yes ponderosae

Dendroctonus Yes pseudotsugae

Dendroctonus rufipennis Yes (M) Yes

Dryocoetes confuses Yes (M)

Gnathotrichus sulcatus Yes (M) Yes

Ips calligraphus Yes (M) Yes

Ips cembrae Yes (M)

Ips confuses Yes (M)

Ips grandicollis Yes (M) Yes

Ips hauseri

Ips lecontei Yes

Ips paraconfusus Yes (M)

Ips pini Yes (M) Yes

Ips plastographus Yes

Ips subelongatus Yes

Ips typographus Yes (M) Yes

Scolytus morawitzi

Diptera:

Anthomyidae Strobilomyia viaria

Tephritidae Ceratitis capitata Yes (M) Yes

EVID4 Evidence Project Final Report (Rev. 06/11) Page 16 of 37 Rhagoletis cingulata Yes (M) Yes

Rhagoletis fausta Yes Yes

Rhagoletis indifferens Yes Yes

Rhagoletis pomonella Yes (M) Yes

Homoptera:

Cicadellidae Scaphoideus luteolus (as a disease vector)

Diaspididae Lepidosaphes ussuriensis

Quadraspidiotus Yes (M) Yes perniciosus

Hymentoptera:

Cynipidae Dryocosmus kuriphilus

Siricidae Sirex ermak

Lepidoptera:

Carposinidae Carposina niponensis Yes (M) Yes

Lasiocampidae Dendrolimus pini Yes

Dendrolimus sibiricus Yes (M) Yes

Dendrolimus superans Yes (M) Yes

Malacosoma Yes (M) Yes americanum

Malacosoma disstria Yes (M) Yes

Malacosoma parallela

Lymantriidae Lymantria Mathura Yes (M) Yes

Orgyia pseudotsugata Yes (M) Yes

Noctuidae Erschoviella musculana

Notodontidae Thaumetopoea Yes (M) Yes processionea

Tortricidae Acleris gloverana Yes Yes

Acleris variana Yes Yes

EVID4 Evidence Project Final Report (Rev. 06/11) Page 17 of 37 Cacoecimorpha Yes (M) Yes pronubana

Choristoneura Yes (M) Yes conflictana

Choristoneura Yes (M) Yes fumiferana

Choristoneura Yes (M) Yes occidentalis

Choristoneura rosaceana Yes (M) Yes

Cydia inopinata Yes

Cydia packardi Yes Yes

Cydia prunivora Yes (M) Yes

EVID4 Evidence Project Final Report (Rev. 06/11) Page 18 of 37

EVID4 Evidence Project Final Report (Rev. 06/11) Page 19 of 37

References to published material 9. This section should be used to record links (hypertext links where possible) or references to other published material generated by, or relating to this project. .

Alfaro, R.I., Pierce, H.D., Jr., Borden, J.H., and Oehlschlager, A.C. (1980). Role of volatile and nonvolatile components of Sitka spruce bark as feeding stimulants for Pissodes strobi Peck (Coleoptera: Curculionidae). Can. J. Zool. 58: 626-632.

Alford, A.R., Silk, P.J., McClure, M., Gibson, C., and Fitzpatrick, J. (1983). Behavioural effects of secondary components of the sex pheromone of the eastern spruce budworm, Choristoneura fumiferana (Lepidoptera: Tortricidae). Can. Entomol. 115: 1053-1058.

Alford, A.R., and Silk, P.J. (1984). Behavioral effects of secondary components of sex pheromone of western spruce budworm (Choristoneura occidentalis) Free. J. Chem. Ecol. 10: 265-270.

Allison, J.D., Borden, J.H., McIntosh, R.L., De Groot, P., and Gries, R. (2001). Kairomonal response by four Monochamus species (Coleoptera: Cerambycidae) to bark pheromones. J. Chem. Ecol. 27, 633-646.

Anderson, R.J., Gieselmann, M.J., Chinn, H.R., Adams, K.G., Henrick, C.A., Rice, R.E., and Roelofs, W.L. (1981). Synthesis and identification of a third component of the San Jose scale sex pheromone. J. Chem. Ecol. 7: 695-706.

Ando, T., Yoshida, S., Tatsuki, S., and Takahashi, N. (1977). Sex attractants for male Lepidoptera. Agric. Biol. Chem. 41: 1485-1492.

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