Report on the methodology applied by EFSA to provide a quantitative assessment of pest‐related criteria required to rank candidate priority pests as defined by Regulation (EU) 2016/2031

European Food Safety Authority (EFSA); Richard Baker; Gianni Gilioli; Carsten Behring; Denise Candiani; Andrey Gogin; Tomasz Kaluski; Mart Kinkar; Olaf Mosbach‐Schulz; Franco Maria Neri; Riccardo Siligato; Giuseppe Stancanelli; Sara Tramontini

doi:10.2903/j.efsa.2019.5731

. 2019 Jun 5;17(6):e05731. doi: 10.2903/j.efsa.2019.5731

Report on the methodology applied by EFSA to provide a quantitative assessment of pest‐related criteria required to rank candidate priority pests as defined by Regulation (EU) 2016/2031

European Food Safety Authority (EFSA), Richard Baker, Gianni Gilioli, Carsten Behring, Denise Candiani, Andrey Gogin, Tomasz Kaluski, Mart Kinkar, Olaf Mosbach‐Schulz, Franco Maria Neri, Riccardo Siligato, Giuseppe Stancanelli, Sara Tramontini

PMCID: PMC7009284 PMID: 32626353

Abstract

In agreement with Article 6(2) of the Regulation (EU) 2016/2031 on protective measures against pests of plants, the European Commission has been tasked by the Council and European Parliament to establish a list of Union quarantine pests which qualify as priority pests. The prioritisation is based on the severity of the economic, social and environmental impact that these pests can cause in the Union territory. The Commission's Joint Research Centre (JRC) is in charge of developing a methodology based on a multi‐criteria decision analysis and composite indicators. In this context, EFSA has provided technical and scientific data related to these pests, in particular: (i) the potential host range and distribution of each of these pests in the Union territory at the level of NUTS2 regions; (ii) parameters quantifying the potential consequences of these pests, e.g. crop losses in terms of yield and quality, rate of spread and time to detection. Expert knowledge elicitation methodology has been applied by EFSA in order to provide those parameters in a consistent and transparent manner.

Keywords: control, detection, host plants, potential distribution, quality loss, spread, yield loss

1. Introduction

1.1. Background and Terms of Reference as provided by the requestor

Pursuant to Article 31 of Regulation (EC) No 178/20021, the Directorate‐General of Health and Food Safety (DG SANTE) of the European Commission requested EFSA for technical assistance in the field of plant health as regards a list of regulated harmful organisms qualifying as priority pests under Regulation (EU) 2016/20312.

More particularly, the Commission has been empowered by the Council and European Parliament to adopt a delegated act, establishing a list of Union quarantine pests which qualify as priority pests, as by Article 6(2) of the Regulation (EU) 2016/2031 on protective measures against pests of plants (hereinafter ‘the new Plant Health Law’). Pests will be listed as priority according to Article 6(1) of the new Plant Health Law, taking into account the severity of the economic, social and environmental impact that they can cause in the Union territory. That list shall be adopted by the Commission by the end of 2019 at the latest.

As regards the initial analysis of the criteria included in Section 2 of Annex I of Regulation (EU) 2016/2031, covering multiple dimensions (i.e. economic, social and environmental) each of the described by multiple impacts (i.e. crop losses in terms of yield and quality, costs of control measures, significant effects on biodiversity, employment, food security and safety and cultural heritage), the methodology should be built on the multi‐criteria decision analysis (MCDA) and composite indicators.

Given the expertise in this domain, DG SANTE is in the process of contracting out to the Commission's Joint Research Centre (JRC), a 2 year project with the aim to develop the methodology which would support DG SANTE in the preparation of such a list of priority pests. That methodology will be applied by the JRC on a sample of indicative list of Union quarantine pests qualifying as potential priority pests. The indicative, non‐binding, list is available in Appendix A and could still be further refined.

EFSA is therefore requested to support the JRC with the extrapolation of technical and scientific data related to those pests, based on current scientific knowledge, and related to the criteria listed in Section 2 of Annex I of Regulation (EU) 2016/2031.

More specifically, EFSA is requested to provide an indication of the potential capacity of establishment of each of those pests in the Union territory at the level of NUTS2 regions. Available data on the potential consequences of those pests should also be provided, taking into account their economic and environmental impact (e.g. crop losses in terms of yield and quality, needs for additional control measures, in particular, when data are available, the need for any significant and long‐term increases of the use of plant protection products).

Such information should be made available at appropriate times during the course of the 2 year project which will start in June 2017. More specifically, the JRC project will consist of three tasks and EFSA inputs will be requested for Task 1 on Methodology development, identification of indicators, and alternative weights for each of the criteria, Task 2 on Application of the methodology to two pilot pests, which will be defined at the onset of the project based on data promptly available, while covering different types of pests, and for Task 3 Extension of the application of the methodology to the remaining potential candidate priority pests.

As some of the potential candidate priority pests may be already included in the mandate on pest categorisation (Ares(2017)1111340), it is also requested that the categorisation of these plant pests are prioritised so that their results can also be applied to this project.

1.2. Interpretation of the Terms of Reference

The current mandate asked EFSA to contribute to the three following tasks

Task 1: Methodology development and identification of indicators
Task 2: Application of the methodology to two pilot pests
Task 3: Extension of the application of the methodology to the remaining potential candidate priority pests.

Task 1 was performed by developing the specific methodology proposed in the current EFSA Scientific Report (from now on ‘Methodology Report’). The methodology has been developed ad hoc taking into account the tiered approach proposed in the EFSA guidance on quantitative pest risk assessment (EFSA PLH Panel, 2018a). The setting of the methodology went through a series of steps and adjustments as a consequence of: (i) the lesson learnt from its testing on the pilot pests; (ii) the feedbacks provided by JRC as final user of the EFSA outputs; (iii) the feedbacks provided by Member States during the regular meetings of the Expert Group on Plant Health Legislation, Discussion of the Delegated Act on Priority Pests of the European Commission, and by written procedure; and (iv) the experience gained by the EFSA Working Group (WG) testing the methodology on the full list of pests provided with the mandate (Appendix A).

Task 2 was conducted applying the methodology on the two pilot pests Agrilus anxius and Tilletia indica with the ‘permanent group of experts’ only. Agrilus anxius was then repeated at a later stage with a different expert group composition, as indicated in Appendix B: this allowed a test of the reliability of the approach (in terms of the stability of the results) and to update the assessment with the most recent findings presented at the international conference ‘Preparing Europe for invasion by the beetles emerald ash borer and bronze birch borer, two major tree‐killing pests’ (1–4 October 2018, BFW Austrian Research Centre for Forests, Vienna, Austria). Tilletia indica was also updated and its completeness improved with the support provided by the hearing expert Pierluigi Meriggi. A third pest, Xanthomonas citri, could also be considered as a pilot study, as it was the first pest on which the methodology was tested with ‘external’ experts; that is experts who did not participate to the development of the methodology, but then applied it on the pest.

Task 3 was completed during the second year of activity, involving for each of the remaining pests’ different groups of experts (Appendix B). All the 28 pests of the list (Appendix A) were assessed. The list of the candidate pests was reviewed and updated during the second year. A large part of the 28 pest species was at the same period subject of at least another type of EFSA evaluation: pest categorisation (e.g. Popillia japonica, EFSA PLH Panel, 2018b), pest risk assessment (e.g. Spodoptera frugiperda, EFSA PLH Panel, 2018c), survey card (e.g. Synchytrium endobioticum, EFSA, 2019). In order to connect the different outputs and harmonise their content, the different EFSA WGs planned to synchronise their outputs, whenever possible. In case of Xylella fastidiosa, the assessment was performed as part of the activity of the WG dedicated to the ‘Update of the Scientific Opinion on the risks to plant health posed by X. fastidiosa in the EU territory’ (EFSA PLH Panel, 2019a).

In Task 3 common templates for the Pest Reports and Pest Datasheets were developed; their regular update was mainly dedicated to improving clarity, and therefore usability, of the final outputs by JRC and any other external user.

1.2.1. Final outputs

The Methodology Report is the reference document for the methodology applied to all the other outputs produced under the mandate: for each of the 28 pests, in fact, EFSA produced a specific report (from now on ‘Pest Report’) and a datasheet (from now on ‘Pest Datasheet’) provided to JRC. Pest Reports and Pest Datasheets are not published on the EFSA Journal but are uploaded on Zenodo3 from which they are freely accessible. The use of this platform should simplify the process of publication of the Pest Reports and Pest Datasheets in case more pests will be submitted for assessment as candidate priority pests or existing reports require to be updated in line with the most recent findings. In case of multiple versions of the same document, Zenodo provides a DOI that represents all versions, and will always resolve to the latest one (Appendix C).

For each of the 28 pests, an interactive version of the map of area of potential distribution at NUTS24 spatial resolution is available on ArcGIS Online.

1.2.2. Working Group composition

The WG is composed by:

Ten members from the EFSA staff, with different tasks and coming from different units and teams
Two members who are external experts regularly involved in all the activities of the WG (‘permanent member’ in the Table of Appendix B)
Forty experts, across Members and Hearing Experts, involved ad hoc to the pest specific assessment according to their knowledge (ad hoc expert groups, Section 1.2.2.1). Some of the Members were also invited to review Pest Reports produced by other groups (Appendix B).
Two Peer‐Reviewers who reviewed the Methodology Report.

1.2.2.1. Ad hoc expert groups

For each pest specific assessment, an ad hoc group of experts was created. The group was designed to include:

at least one of the WG members who defined the methodology in order to ensure consistency in the approach and application of the methods;
at least one internationally recognised expert on the pest;
one expert on agricultural/forestry practices relevant to the specific hosts under consideration.

A good combination of experts and resource availability meant that the ad hoc groups were generally composed of 4–5 people, very rarely by less than 3 or more than 6.

PLH Panel members were selected if their expertise covered points (ii) and/or (iii).

2. Data and methodologies

For each pest, EFSA has provided the JRC with data sets including the following components:

•
The area of potential distribution at least at the NUTS2 level for each Member State (MS)
•
Host lists: (i) a preliminary list of main hosts obtained from a variety of sources; (ii) a full host list obtained by combining the host lists from the CABI Crop Protection Compendium datasheet and the EPPO Global database; and (iii) a final list of hosts for which the expert knowledge elicitation (EKE) on yield and quality losses was performed
•
Expected change in the use of plant protection products
•
Additional potential effects other than direct yield and quality losses (mycotoxin production and vector of a plant pathogen)
•
Data on parameters related to the potential consequences of pest establishment:
1. Yield and quality losses
2. Spread rate
3. Time between establishment and first detection of the pest.

In order to produce the data set, EFSA estimated uncertainty distributions for each of the parameters using the literature and data sets available and, where sufficient evidence was lacking, EKEs with groups composed of risk assessors and pest experts.

The full process undergone for the preparation of the Pest Reports and Pest Datasheets is summarised in Appendix D and described in detail in the following sections.

2.1. Selection of information and data

The Pest Reports summarise the key information on which the assessment is conducted based on the most complete, up‐to‐date, pest categorisation(s) and/or pest risk assessment(s) by EFSA, EPPO, other European or non‐European institutions.

Additional information and data were obtained via literature search and complemented by expert contributions to ensure that data relevant to the estimation of the parameters and the most recent research findings were taken into account.

When a reference had been collected and screened for relevance, a.pdf of the full article was stored in the EFSA internal document management system (DMS).

2.2. Structure and content of the Pest Report

Each Pest Report has five sections:

1
Introduction for the user on the structure of the document
2
Background information relevant to support the EKE process and its results, in particular
- o
  biology and taxonomy
- o
  host plants
- o
  area of potential distribution
- o
  expected change in the use of plant protection products
- o
  additional potential effects
3
Report of the EKE
- o
  yield and quality losses: structured expert judgement and elicited values
- o
  spread rate: structured expert judgement and elicited values
- o
  time to detection: structured expert judgement and elicited values
4
Conclusions
5
References.

In addition, Appendices on the host list and summary tables on the evidence provided to the EKE complete the document.

2.2.1. Summary of the biology and taxonomy

This introductory section provides the reader with general information on the pest, any taxonomic or nomenclature issues and the type of damages caused. This section is short and only includes information directly relevant to the assessment.

2.2.2. Host plants

A full list of host plants was compiled merging the information from the most recent pest risk assessments, the CABI Crop Protection Compendium (CABI, online) and the EPPO Global Database (EPPO, online). Hosts from the CABI list classified as ‘Unknown’ as well as hosts from the EPPO list classified as ‘Alternate’, ‘Artificial’ or ‘Incidental’ were excluded from the list. The full list of host plants is reported in Appendix A of the Pest Report.

From the full list, host plants of economic or environmental importance to the EU (agricultural crops, ornamental, forest species, etc.) were identified to assist with the process of selecting the plant species, for which yield and quality losses should be elicited. These are based on published reports of the pest causing economic impacts and a review of the hosts listed as ‘major’ in the EPPO Global Database and ‘main’ in the CABI Crop Protection Compendium.

One or more of the following criteria were used to decide which hosts to include in the estimation of yield and quality losses:

The availability of data on the distribution of the host(s) in the EU and production statistics.
The type of damage caused by the pest on the specific host or category of hosts.
The economic and environmental importance of the plant species in the EU (e.g. whether it is a major crop in the area of potential distribution).
Host plant preferences of the pest under assessment.
The impact caused by the pest on the host.

Once the species to be included for the estimation of yield and quality losses had been identified, experts were asked to decide on:

The grouping of host plants for each EKE, especially for polyphagous pests.
The level of aggregation (genus/species/subspecies) of the hosts.

In the case of polyphagous pests, the host plants were grouped by taking into account similarities in one or more of the following criteria:

The level of susceptibility of the hosts or the host preferences of the pest within the same taxonomic group (e.g. family, genus, species) or crop category (e.g. EUROSTAT categories).
The production systems (e.g. row crops, greenhouse crops, orchards, forest plants).
The final use of the product (e.g. forage crop, grain crop, fresh consumption).

2.2.2.1. Natura 2000 sites

For assessing the environmental impact, the number of Natura 20005 sites and their area where potential hosts of the pest are mentioned as ‘protected’ or ‘important’ species were considered. The impact was assessed as follows:

Number of Natura 2000 sites with at least one potential host were counted.
Number of Natura 2000 sites impacted by the pest (i.e. with at least one host within the area of potential distribution) were counted.
Total area (ha) of Natura 2000 sites with at least one potential host was calculated.
Total area (ha) of Natura 2000 sites impacted by the pest (i.e. with at least one host within the area of potential distribution) was calculated.
Percentage of the area of Natura 2000 sites impacted by the pest was calculated as the ratio between number 3 and 4.

For those Natura 2000 sites whose area is only partially included in the area of potential establishment, the full size of the site was used.

2.2.3. Area of potential distribution

The area of potential distribution includes both the area of potential establishment and the area where the pest may only have transient populations. Combining transient populations with established populations to form the area of potential distribution is in agreement with the International Standard for Phytosanitary Measures (ISPM) No 8. (Determination of Pest Status in an Area) since it is stated here that ‘seasonally present’, i.e. transience, is included in the term ‘distribution’.

In order to identify the area of potential distribution for a given pest in the EU, information on host availability and climate suitability were used. The results of any relevant models describing the area of potential establishment were evaluated. The area of potential distribution in the EU was then reported in a map.

The areas where the pest has been present with transient populations can be included in the assessment if needed (for details on the criteria for assessment of transient populations, see Section 2.2.3.3).

Since it is assumed that glasshouses are favourable habitats for the establishment of the pest, they were considered as part of the area of potential establishment, even if they are far from the areas where the pest can establish outdoors.

2.2.3.1. Area of current distribution

This is generally represented by a map of the pest's global distribution usually extracted from the EPPO Global Database.

2.2.3.2. Area of potential establishment

In order to define the area of potential establishment, the availability of suitable hosts and the suitability of the environment, particularly the climate, has been assessed. Where appropriate, published maps have been reproduced or new maps have been generated to support the assessments.

In order to identify the area of host distribution the following databases were consulted:

EUROSTAT: for crop distributions, although in many cases the information is available at national level only or for groups of crops and not at the species level – http://ec.europa.eu/eurostat/data/database
JRC – Natura 2000 database – https://www.eea.europa.eu/data-and-maps/data/natura-9
European atlas of forest tree species – http://forest.jrc.ec.europa.eu/european-atlas-of-forest-tree-species/atlas-download-page/
JRC Yearly Modelled crop area at grid level – http://agri4cast.jrc.ec.europa.eu/DataPortal/RequestDataResource.aspx?idResource=32&o=d
Previous EFSA opinions: where specific data sets are available (e.g. citrus distribution from CBS opinions: data collected from MSs)
Corine Land Cover 2012: https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012

Priority was given to the data set which provided the highest level of spatial resolution. The minimum level is the information on presence/absence at NUTS2 level (in the data set 0 = absent and 1 = present).

When the pest is polyphagous and data were available, maps provide the distribution of the hosts (see Section 2.2.2).

Whenever available, priority was given to models for the estimation of potential pest distributions published in previous EFSA opinions or other scientific publications. When models were not available or considered to be flawed, maps of pest potential distribution were generated taking into account the most relevant biological parameters for the pest to establish in a given area. For meteorological and climatic data, the following data sets were used:

JRC Gridded Agro‐Meteorological data http://agri4cast.jrc.ec.europa.eu/DataPortal/RequestDataResource.aspx?idResource=7&o=d
Köppen‐Geiger climate classification: http://koeppen-geiger.vu-wien.ac.at/

Maps are provided with the highest level of spatial resolution based on meteorological and climatic data available. The minimum level of resolution is the information on the climate suitable/not suitable for establishment at NUTS2 level (in the data set 0 = not suitable and 1 = suitable).

For harmonisation purposes, the climatic suitability may be aggregated up to NUTS0 level. In such cases, the data sets include the weighted average of the NUTS2 regions based on production volumes or production areas. If host specific data were not available, the land area of the NUTS2 regions was used to weight the average.

The area of potential establishment could be smaller than the area where the main hosts occur, due to due to climate or other ecological factors preventing the establishment.

Within the area of potential establishment, the mean abundance of the pest, the main driver of the pest impact, was considered as: (i) the same throughout the assessment area or (ii) not equally distributed across the assessment area, in which case patterns of population abundance or of any of the proxies that could be considered (e.g. number of generations, thermal sums) are described. In case (ii), zones or gradients were described and the impact on yield and quality loss assessed in each zone or along the gradient.

2.2.3.3. Transient populations

In areas outside the area of potential establishment, yield/quality losses could still occur due to the presence of transient populations. The impacts of these transient populations on the yield/quality losses estimated in the area of potential establishment can be scaled by factors (i.e. coefficients) specific to the areas where transience can occur. These scaling factors account for: (i) the heterogeneity both in time and space in the occurrence of the transient populations and (ii) differences in the abundance of these transient populations compared to the population abundance in the area of potential establishment.

It was assumed that transient populations only occur when the species has a specific adaptation facilitating long‐distance dispersal involving both active (e.g. the species is a strong flyer) and/or passive (e.g. the species can be transported by wind) methods of spread. We set a threshold for identifying the cases where transient populations are taken into account. This only occurs if the species has a maximum spread rate (99% percentile of the spread rate) greater than 100 km. For the species that satisfied this criterion, the yield/quality loss outside the area of potential establishment was calculated as follows:

The area of potential distribution was defined by extending the border of the area of potential establishment based on the additional distance covered by the pest (a distance equal to 99% percentile of the spread rate).
A variable was defined that provides a proxy for the abundance to be used for assessing the amount of impact caused by the transient population (e.g. the number of generations, thermal sums).
The scaling factor for the impact was calculated as the ratio between the value of the variable defined in point 2) in each point and the maximum value of that variable in the area of potential establishment.
The yield/quality loss caused by transient populations at a location outside the area of potential establishment was calculated by multiplying the estimated maximum yield/quality loss in the area of potential establishment by the scaling factor computed at that location.

2.2.4. Expected change in the use of plant protection products

The WG found that it was not possible to identify one parameter that correctly reflects whether pest presence will result in the ‘need for any significant and long‐term increases of the use of plant protection products’ as mentioned in the DG SANTE mandate letter. Since the JRC protocol considers this aspect in terms of ‘undesired effects of control measures’, EFSA has proposed a three‐level score (Table 1) to reflect the extent to which there is likely to be an increase in the use of Plant Protection Products (PPPs) without quantifying the likely number of additional treatments. This is based on four cases (A–D) as outlined in Table 1.

Table 1.

Expected changes in the use of Plant Protection Products (PPPs) following pest establishment in the EU in relation to four cases (A–D) and three‐level score (0–2) for the expected change in the use of PPPs

Expected change in the use of PPPs	Case	PPPs indicator
PPPs effective against the pest are not available/feasible in the EU	A	0
PPPs applied against other pests in the risk assessment area are also effective against the pest, without increasing the amount/number of treatments	B	0
PPPs applied against other pests in the risk assessment area are also effective against the pest but only if the amount/number of treatments is increased	C	1
A significant increase in the use of PPPs is not sufficient to control the pest: only new integrated strategies combining different tactics are likely to be effective	D	2

Category		Potential priority pests
Insects	1.	Agrilus anxius a
	2.	Agrilus planipennis
	3.	Anastrepha ludens
	4.	Anoplophora chinensis
	5.	Anoplophora glabripennis
	6.	Anthonomus eugenii
	7.	Aromia bungii
	8.	Bactericera cockerelli
	9.	Bactrocera dorsalis (including Bactrocera invadens)
	10.	Bactrocera zonata
	11.	Conotrachelus nenuphar
	12.	Dendrolimus sibiricus
	13.	Popillia japonica
	14.	Rhagoletis pomonella (Tephritidae (non‐European))
	15.	Spodoptera frugiperda
	16.	Thaumatotibia leucotreta
	17.	Thrips palmi
Bacteria	18.	Candidatus Liberibacter spp. (citrus greening)
	19.	Clavibacter michiganensis subsp. sepedonicus
	20.	Ralstonia solanacearum
	21.	Xylella fastidiosa
	22.	Xanthomonas citri a
	23.	Grapevine flavescence dorée
Nematodes	24.	Bursaphelenchus xylophilus
Fungi	25.	Ceratocystis fagacearum
	26.	Phyllosticta citricarpa
	27.	Synchytrium endobioticum
	28.	Tilletia indica a

Species with effect on yield of cereals			Percentiles of the proportion of yield loss [%]
Class	Species	EPPO code/host	1%	5%	10%	17%	25%	33%	50%	67%	75%	83%	90%	95%	99%
INSECTS	Spodoptera frugiperda	LAPHFR/sweet corn	0.8%	2.5%	4.2%	6.3%	8.8%	11.4%	16.9%	23.6%	27.9%	33.3%	39.5%	46.8%	60.3%
INSECTS	Thaumatotibia leucotreta	ARGPLE/sweet corn	2.2%	4.4%	6.2%	8.1%	10.1%	12.1%	16.0%	20.5%	23.4%	27.0%	31.1%	36.0%	45.6%
INSECTS	Spodoptera frugiperda	LAPHFR/grain maize	0.3%	1.0%	1.7%	2.7%	3.8%	5.1%	7.8%	11.4%	13.7%	16.9%	20.6%	25.4%	35.1%
INSECTS	Spodoptera frugiperda	LAPHFR/rice	0.4%	1.3%	2.1%	3.0%	4.0%	5.1%	7.2%	9.8%	11.4%	13.5%	15.9%	18.9%	25.1%
INSECTS	Thaumatotibia leucotreta	ARGPLE/grain for feed	0.5%	0.5%	0.7%	0.9%	1.4%	2.1%	4.0%	6.8%	8.4%	10.4%	12.3%	13.9%	15.4%
INSECTS	Spodoptera frugiperda	LAPHFR/forage maize	0.3%	0.7%	1.1%	1.6%	2.2%	2.7%	3.8%	5.1%	6.0%	7.0%	8.2%	9.7%	12.8%
INSECTS	Popillia japonica	POPIJA/soya, maize	0.1%	0.4%	0.7%	1.1%	1.5%	2.0%	3.0%	4.2%	4.9%	6.0%	7.2%	8.7%	12.0%
FUNGI	Tilletia indica	NEOVIN/wheat	0.00%	0.01%	0.01%	0.02%	0.03%	0.03%	0.05%	0.08%	0.10%	0.13%	0.19%	0.27%	0.54%

High spread species			Percentiles of the spread rate [km/y]
Class	Species	EPPO code	1%	5%	10%	17%	25%	33%	50%	67%	75%	83%	90%	95%	99%
INSECTS	Spodoptera frugiperda	LAPHFR	254.45	379.05	474.62	572.65	674.77	765.67	931.66	1093.67	1178.63	1271.45	1356.94	1436.66	1533.07
BACTERIA	Candidatus Liberibacter spp. (citrus greening)	LIBEXX	0.90	3.21	5.55	8.34	11.58	14.66	20.61	26.55	29.61	32.82	35.58	37.88	40.12
INSECTS	Anastrepha ludens	ANSTLU	1.71	3.08	4.08	5.11	6.23	7.29	9.45	12.00	13.62	15.76	18.28	21.49	28.42
INSECTS	Bactrocera zonata	DACUZO	1.26	2.44	3.28	4.14	5.08	5.97	7.86	10.36	12.17	14.91	18.83	25.34	48.71
INSECTS	Bactrocera dorsalis	DACUDO	1.05	1.83	2.46	3.17	4.02	4.91	6.95	9.87	12.02	15.25	19.67	26.41	45.84
BACTERIA	Xylella fastidiosa	XYLEFA	0.42	1.10	1.69	2.34	3.07	3.77	5.18	6.81	7.82	9.10	10.57	12.35	15.94
NEMATODES	Bursaphelenchus xylophilus	BURSXI	0.16	0.59	1.03	1.57	2.24	2.92	4.43	6.34	7.59	9.27	11.25	13.80	19.26

	Name	Role	Performed tasks
1.	AKOTSEN‐MENSAH Clement	Hearing Expert	EKE on Conotrachelus nenuphar
2.	BAKER Richard	Permanent Member	EKE on Anthonomus eugenii, Bactericera cockerelli, Bursaphelenchus xylophilus, Candidatus Liberibacter spp., Ceratocystis fagacearum, Conotrachelus nenuphar, Dendrolimus sibiricus, Phyllosticta citricarpa, Popillia japonica, Spodoptera frugiperda, Thaumatotibia leucotreta, Thrips palmi, Tilletia indica, Xanthomonas citri Review on Agrilus anxius, Agrilus planipennis, Xylella fastidiosa
3.	BALI Elma	Hearing Expert	EKE on Anastrepha ludens, Bactrocera dorsalis, Bactrocera zonata, Rhagoletis pomonella
4.	BEHRING Carsten	Member from EFSA	Supporting information to the quantitative analysis (data and maps management)
5.	BIONDI Antonio	Hearing Expert	EKE on Anthonomus eugenii
6.	BOSCIA Donato	Member	EKE on Xylella fastidiosa Review on Candidatus Liberibacter
7.	BOSIO Giovanni	Hearing Expert	EKE on Popillia japonica
8.	CANDIANI Denise	Member from EFSA	Elicitor for the EKE on Candidatus Liberibacter (rapporteur), Phyllosticta citricarpa (rapporteur), Ralstonia solanacearum (impact on Solanaceae other than potato), Synchytrium endobioticum (preliminary assessment), Tilletia indica (rapporteur), Xanthomonas citri (rapporteur)
9.	CIAMPITTI Mariangela	Hearing Expert	EKE on Aromia bungii, Popillia japonica
10.	CUBERO Jaime	Member	EKE on Candidatus Liberibacter spp., Xanthomonas citri Review on Phyllosticta citricarpa
11.	DALMAU Vicente	Hearing Expert	EKE on Conotrachelus nenuphar, Xylella fastidiosa
12.	DEHNEN‐SCHMUTZ Katharina	Peer Reviewer	Peer‐Review of the report on the methodology
13.	EVANS Hugh	Member	EKE on Agrilus anxius, Agrilus planipennis, Bursaphelenchus xylophilus Review on Anoplophora chinensis, Anoplophora glabripennis
14.	FACCOLI Massimo	Hearing Expert	EKE on Anoplophora chinensis, Anoplophora glabripennis
15.	FOISSAC Xavier	Member	EKE on grapevine flavescence dorée
16.	GILIOLI Gianni	Permanent Member	EKE on Anoplophora chinensis, Anoplophora glabripennis, Aromia bungii, Candidatus Liberibacter spp., Clavibacter michiganensis subsp. Sepedonicus, grapevine flavescence dorée, Phyllosticta citricarpa, Ralstonia solanacearum, Spodoptera frugiperda, Synchytrium endobioticum, Thaumatotibia leucotreta, Tilletia indica, Xanthomonas citri, Xylella fastidiosa Elicitor for the EKE on Bactericera cockerelli, Bursaphelenchus xylophilus, Ceratocystis fagacearum, Conotrachelus nenuphar, Popillia japonica
17.	GOGIN Andrey	Member from EFSA	Supporting information to the quantitative analysis (data and maps management)
18.	GREGOIRE Jean Claude	Member	EKE on Anoplophora chinensis, Anoplophora glabripennis, Dendrolimus sibiricus Review on grapevine flavescence dorée
19.	HOPPE Bjoern	Hearing Expert	EKE on Aromia bungii
20.	HRUSKA Allan	Member	EKE on Spodoptera frugiperda
21.	JACQUES Marie Agnes	Member	EKE on Ralstonia solanacearum, Xylella fastidiosa Review on Xanthomonas citri
22.	JAQUES MIRET Josep Anton	Member	EKE on Anastrepha ludens, Bactrocera dorsalis, Bactrocera zonata, Rhagoletis pomonella Review on Anthonomus eugenii, Conotrachelus nenuphar
23.	JEGER Michael John	Peer Reviewer	Peer‐review of the report on the methodology
24.	KALUSKI Tomasz	Member from EFSA	Support to experts and JRC, rapporteur during EKEs
25.	KINKAR Mart	Member from EFSA	Support to experts and JRC, rapporteur during EKEs
26.	LOOMANS Antoon	Hearing Expert	EKE on Anthonomus eugenii, Thrips palmi
27.	MACLEOD Alan	Member	EKE on Thrips palmi Review on Spodoptera frugiperda
28.	MACQUARRIE Christian	Member	EKE on Agrilus anxius, Agrilus planipennis Review on Popillia japonica, Aromia bungii
29.	MAGNUSSON Sven Christer	Member	EKE on Bursaphelenchus xylophilus Review on Ceratocystis fagacearum
30.	MALUMPHY Chris	Hearing Expert	EKE on Bactericera cockerelli
31.	MARZACHI Cristina	Member	EKE on grapevine flavescence dorée
32.	MCCULLOUGH Deborah	Member	EKE on Agrilus anxius, Agrilus planipennis
33.	MERIGGI Pierluigi	Hearing Expert	Information on cereals production
34.	MILONAS Panagiotis	Member	EKE on Bactericera cockerelli Review on Bactrocera dorsalis, Bactrocera zonata
35.	MOSBACH‐SCHULZ Olaf	Member from EFSA	Elicitor during most of the EKEs
36.	NERI Franco Maria	Member from EFSA	Support to experts and JRC, rapporteur during EKEs
37.	PAPADOPOULOS Nikolaos	Member	EKE on Anastrepha lundens, Bactrocera dorsalis, Bactrocera zonata, Rhagoletis pomonella Review on Thrips palmi
38.	PAPANASTASSIOU Stella	Hearing Expert	EKE on Anastrepha lundens, Bactrocera dorsalis, Bactrocera zonata, Rhagoletis pomonella
39.	RAFOSS Trond	Hearing Expert	EKE on Candidatus Liberibacter spp., Clavibacter michiganensis subsp. sepedonicus, Dendrolimus sibiricus, Phyllosticta citricarpa, Ralstonia solanacearum, Synchytrium endobioticum, Tilletia indica, Xanthomonas citri
40.	RAVN Hans Peter	Member	EKE on Agrilus anxius, Agrilus planipennis
41.	RUTLEDGE Claire	Member	EKE on Agrilus anxius, Agrilus planipennis Review on Dendrolimus sibiricus
42.	SILIGATO Riccardo	Member from EFSA	Support to experts and JRC, rapporteur during EKEs
43.	STANCANELLI Giuseppe	Member from EFSA	Chair of the Working Group in the preliminary phase
44.	TRAMONTINI Sara	Member from EFSA	Chair of the Working Group, support to experts and JRC, rapporteur during EKEs
45.	UREK Gregor	Member	EKE on Clavibacter michiganensis subsp. Sepedonicus, Ralstonia solanacearum, Synchytrium endobioticum Review on Bursaphelenchus xylophilus
46.	VAN DER GAAG Dirk Jan	Member	EKE on Clavibacter michiganensis subsp. Sepedonicus, Popillia japonica, Ralstonia solanacearum, Synchytrium endobioticum Review on Anastrepha ludens, Rhagoletis pomonella
47.	VAN DER STRATEN Marja	Member	EKE on Spodoptera frugiperda, Thaumatotibia leucotreta
48.	VERNIERE Christian	Member	EKE on Candidatus Liberibacter spp., Phyllosticta citricarpa, Xanthomonas citri Review on Ralstonia solanacearum
49.	VETTRAINO Anna Maria	Member	EKE on Ceratocystis fagacearum Review on Tilletia indica
50.	VICENT Antonio	Member	EKE on Candidatus Liberibacter spp., Phyllosticta citricarpa, Xanthomonas citri, Xylella fastidiosa
51.	VILA Lluis	Hearing Expert	EKE on Conotrachelus nenuphar
52.	YEMSHANOV Denys	Member	EKE on Agrilus anxius, Agrilus planipennis
53.	YUEN Jonathan	Member	EKE on Ralstonia solanacearum Review on Clavibacter michiganensis subsp. sepedonicus, Synchytrium endobioticum
54.	ZAPPALA’ Lucia	Member	EKE on Thrips palmi Review on Bactericera cockerelli, Thaumatotibia leucotreta

	Pest species	EFSA Question number	Doi on Zenodo	Concept Doi on Zenodo	EFSA Output number
1.	Agrilus anxius	EFSA‐Q‐2018‐00376	https://doi.org/10.5281/zenodo.2784731	https://doi.org/10.5281/zenodo.2784730	EN‐1633
2.	Agrilus planipennis	EFSA‐Q‐2018‐00377	https://doi.org/10.5281/zenodo.2784060	https://doi.org/10.5281/zenodo.2784059	EN‐1634
3.	Anastrepha ludens	EFSA‐Q‐2018‐00378	https://doi.org/10.5281/zenodo.2785521	https://doi.org/10.5281/zenodo.2785520	EN‐1635
4.	Anoplophora chinensis	EFSA‐Q‐2018‐00379	https://doi.org/10.5281/zenodo.2785767	https://doi.org/10.5281/zenodo.2785766	EN‐1636
5.	Anoplophora glabripennis	EFSA‐Q‐2018‐00380	https://doi.org/10.5281/zenodo.2786190	https://doi.org/10.5281/zenodo.2786189	EN‐1637
6.	Anthonomus eugenii	EFSA‐Q‐2018‐00381	https://doi.org/10.5281/zenodo.2786324	https://doi.org/10.5281/zenodo.2786323	EN‐1638
7.	Aromia bungii	EFSA‐Q‐2018‐00406	https://doi.org/10.5281/zenodo.2786516	https://doi.org/10.5281/zenodo.2786515	EN‐1639
8.	Bactericera cockerelli	EFSA‐Q‐2018‐00382	https://doi.org/10.5281/zenodo.2786698	https://doi.org/10.5281/zenodo.2786697	EN‐1640
9.	Bactrocera dorsalis	EFSA‐Q‐2018‐00383	https://doi.org/10.5281/zenodo.2786922	https://doi.org/10.5281/zenodo.2786921	EN‐1641
10.	Bactrocera zonata	EFSA‐Q‐2018‐00384	https://doi.org/10.5281/zenodo.2787209	https://doi.org/10.5281/zenodo.2787208	EN‐1642
11.	Bursaphelenchus xylophilus	EFSA‐Q‐2018‐00385	https://doi.org/10.5281/zenodo.2788667	https://doi.org/10.5281/zenodo.2788666	EN‐1643
12.	Candidatus Liberibacter	EFSA‐Q‐2018‐00386	https://doi.org/10.5281/zenodo.2788905	https://doi.org/10.5281/zenodo.2788904	EN‐1644
13.	Ceratocystis fagacearum	EFSA‐Q‐2018‐00387	https://doi.org/10.5281/zenodo.2789117	https://doi.org/10.5281/zenodo.2789116	EN‐1645
14.	Clavibacter michiganensis	EFSA‐Q‐2018‐00388	https://doi.org/10.5281/zenodo.2789277	https://doi.org/10.5281/zenodo.2789276	EN‐1646
15.	Conotrachelus nenuphar	EFSA‐Q‐2018‐00389	https://doi.org/10.5281/zenodo.2789435	https://doi.org/10.5281/zenodo.2789434	EN‐1647
16.	Dendrolimus sibiricus	EFSA‐Q‐2018‐00390	https://doi.org/10.5281/zenodo.2789555	https://doi.org/10.5281/zenodo.2789554	EN‐1648
17.	Grapevine flavescence dorée	EFSA‐Q‐2018‐00393	https://doi.org/10.5281/zenodo.2789595	https://doi.org/10.5281/zenodo.2789594	EN‐1649
18.	Phyllosticta citricarpa	EFSA‐Q‐2018‐00396	https://doi.org/10.5281/zenodo.2789635	https://doi.org/10.5281/zenodo.2789634	EN‐1650
19.	Popillia japonica	EFSA‐Q‐2018‐00398	https://doi.org/10.5281/zenodo.2789676	https://doi.org/10.5281/zenodo.2789675	EN‐1651
20.	Ralstonia solanacearum	EFSA‐Q‐2018‐00399	https://doi.org/10.5281/zenodo.2789713	https://doi.org/10.5281/zenodo.2789712	EN‐1652
21.	Rhagoletis pomonella	EFSA‐Q‐2018‐00400	https://doi.org/10.5281/zenodo.2789749	https://doi.org/10.5281/zenodo.2789748	EN‐1653
22.	Spodoptera frugiperda	EFSA‐Q‐2018‐00401	https://doi.org/10.5281/zenodo.2789779	https://doi.org/10.5281/zenodo.2789778	EN‐1654
23.	Synchytrium endobioticum	EFSA‐Q‐2018‐00402	https://doi.org/10.5281/zenodo.2789811	https://doi.org/10.5281/zenodo.2789810	EN‐1655
24.	Thaumatotibia leucotreta	EFSA‐Q‐2018‐00403	https://doi.org/10.5281/zenodo.2789844	https://doi.org/10.5281/zenodo.2789843	EN‐1656
25.	Thrips palmi	EFSA‐Q‐2018‐00404	https://doi.org/10.5281/zenodo.2789876	https://doi.org/10.5281/zenodo.2789875	EN‐1657
26.	Tilletia indica	EFSA‐Q‐2018‐00405	https://doi.org/10.5281/zenodo.2789904	https://doi.org/10.5281/zenodo.2789903	EN‐1658
27.	Xanthomonas citri	EFSA‐Q‐2018‐00407	https://doi.org/10.5281/zenodo.2789946	https://doi.org/10.5281/zenodo.2789945	EN‐1659
28.	Xylella fastidiosa	EFSA‐Q‐2018‐00408	https://doi.org/10.5281/zenodo.2789978	https://doi.org/10.5281/zenodo.2789977	EN‐1660

		Fruits													Vegetables, legumes							Cereals				Other				Forest
		Pears	Apples	Peach and nectarine	Apricot	Plum	Cherry	Almond	Olive	Grape	Citrus	Avocado	Other exotic fruit	Berries (small fruit)	Potato	Tomato	Pepper	Eggplant	Cucurbits	Lettuce	Soybean	Durum wheat	Rice	Sorghum	Sweet corn	Grain maize	Forage maize/Biofuel	Turf	Ornamentals(cut flowers)/potted plants)	Birch	Ash	Oak	Fir	Pine	Other conifers	Other broadleaves
BACTERIA	Candidatus Liberibacter spp. (citrus greening)										Y
	Xanthomonas citri										YQ
	Grapevine flavescence dorée									Y
	Xylella fastidiosa							Y	Y	Y	Y
	Clavibacter michiganensis subsp. sepedonicus														Y
	Ralstonia solanacearum														YQ	Y	Y	Y
FUNGI	Synchytrium endobioticum														Y
	Ceratocystis fagacearum																															Y
	Phyllosticta citricarpa										YQ
	Tilletia indica																					YQ
INSECTS	Anastrepha ludens			Y							Y		Y
	Bactrocera zonata			Y							Y		Y
	Bactrocera dorsalis			Y							Y		Y
	Rhagoletis pomonella		Y
	Anthonomus eugenii																Y
	Conotrachelus nenuphar	Y	Y	Y	Y	Y	Y
	Spodoptera frugiperda																						Y	Y	Y	Y	Y
	Thaumatotibia leucotreta			Y							Y	Y	Y				Y	Y							Y	Y
	Popillia japonica		Y	Y	Y	Y	Y			Y				Y							Y				Y	Y		Y
	Thrips palmi																YQ	YQ	YQ	Y									Y
	Bactericera cockerelli														Y	Y	Y	Y
	Aromia bungii			Y	Y	Y	Y	Y																												YU
	Anoplophora chinensis	Y	Y	Y	Y	Y	Y	Y			Y																									YU
	Anoplophora glabripennis																																			YU
	Agrilus anxius																													Y
	Agrilus planipennis																														Y
	Dendrolimus sibiricus																																Y	Y	Y
NEM	Bursaphelenchus xylophilus																																	Y

Species with effect on ornamentals or similar			Percentiles of the proportion of yield loss [%]
Class	Species	EPPO code/host	1%	5%	10%	17%	25%	33%	50%	67%	75%	83%	90%	95%	99%
INSECTS	Anoplophora chinensis	ANOLCN/urban trees	5.0%	6.8%	8.6%	10.6%	12.9%	15.2%	20.2%	26.1%	29.9%	34.7%	40.1%	46.6%	58.7%
INSECTS	Anoplophora glabripennis	ANOLGL/urban trees	4.4%	5.5%	6.6%	8.0%	9.8%	11.6%	15.7%	20.8%	24.1%	28.5%	33.6%	39.8%	51.9%
INSECTS	Aromia bungii	AROMBU/ornamentals	1.4%	3.2%	4.7%	6.2%	7.8%	9.3%	12.3%	15.6%	17.6%	20.1%	22.9%	26.2%	32.7%
INSECTS	Popillia japonica	POPIJA/turf	0.5%	1.4%	2.2%	3.1%	4.1%	5.1%	7.0%	9.4%	10.8%	12.7%	14.8%	17.4%	22.7%
INSECTS	Thrips palmi	THRIPL/ornamentals	0.0%	0.1%	0.2%	0.3%	0.5%	0.6%	1.0%	1.6%	1.9%	2.4%	3.1%	3.9%	5.9%

Species with effect on yield of potatoes			Percentiles of the proportion of yield loss [%]
Class	Species	EPPO code/host	1%	5%	10%	17%	25%	33%	50%	67%	75%	83%	90%	95%	99%
INSECTS	Bactericera cockerelli	PARZCO/potatoes	0.9%	2.0%	2.9%	3.8%	4.9%	6.0%	8.2%	10.9%	12.7%	15.0%	17.9%	21.5%	29.6%
BACTERIA	Clavibacter michiganensis subsp. sepedonicus	CORBSE/ware potatoes	2.0%	2.3%	2.5%	2.6%	2.7%	2.9%	3.1%	3.3%	3.5%	3.7%	3.9%	4.2%	4.7%
FUNGI	Synchytrium endobioticum	SYNCEN/potatoes	0.09%	0.22%	0.34%	0.46%	0.60%	0.73%	0.99%	1.29%	1.47%	1.70%	1.96%	2.28%	2.92%
BACTERIA	Ralstonia solanacearum	RALSSO/ware potatoes	0.05%	0.07%	0.09%	0.10%	0.12%	0.14%	0.17%	0.21%	0.24%	0.28%	0.33%	0.39%	0.56%
BACTERIA	Clavibacter michiganensis subsp. sepedonicus	CORBSE/seed potatoes	0.002%	0.007%	0.011%	0.015%	0.020%	0.025%	0.035%	0.047%	0.055%	0.065%	0.076%	0.090%	0.118%
BACTERIA	Ralstonia solanacearum	RALSSO/seed potatoes	0.000%	0.000%	0.000%	0.000%	0.001%	0.001%	0.003%	0.007%	0.010%	0.014%	0.020%	0.028%	0.050%

Species with effect on yield of potatoes			Percentiles of the proportion of yield loss [%]
Class	Species	EPPO code/host	1%	5%	10%	17%	25%	33%	50%	67%	75%	83%	90%	95%	99%
INSECTS	Bactericera cockerelli	PARZCO/potatoes	0.9%	2.0%	2.9%	3.8%	4.9%	6.0%	8.2%	10.9%	12.7%	15.0%	17.9%	21.5%	29.6%
BACTERIA	Clavibacter michiganensis subsp. sepedonicus	CORBSE/ware potatoes	2.0%	2.3%	2.5%	2.6%	2.7%	2.9%	3.1%	3.3%	3.5%	3.7%	3.9%	4.2%	4.7%
FUNGI	Synchytrium endobioticum	SYNCEN/potatoes	0.09%	0.22%	0.34%	0.46%	0.60%	0.73%	0.99%	1.29%	1.47%	1.70%	1.96%	2.28%	2.92%
BACTERIA	Ralstonia solanacearum	RALSSO/ware potatoes	0.05%	0.07%	0.09%	0.10%	0.12%	0.14%	0.17%	0.21%	0.24%	0.28%	0.33%	0.39%	0.56%
BACTERIA	Clavibacter michiganensis subsp. sepedonicus	CORBSE/seed potatoes	0.002%	0.007%	0.011%	0.015%	0.020%	0.025%	0.035%	0.047%	0.055%	0.065%	0.076%	0.090%	0.118%
BACTERIA	Ralstonia solanacearum	RALSSO/seed potatoes	0.000%	0.000%	0.000%	0.000%	0.001%	0.001%	0.003%	0.007%	0.010%	0.014%	0.020%	0.028%	0.050%

Species with effect on yield of citrus fruits			Percentiles of the proportion of yield loss [%]
Class	Species	EPPO code/host	1%	5%	10%	17%	25%	33%	50%	67%	75%	83%	90%	95%	99%
BACTERIA	Candidatus Liberibacter spp. (citrus greening)	LIBEXX/citrus	17.7%	29.8%	37.7%	45.0%	52.0%	57.8%	67.8%	76.7%	81.1%	85.7%	89.8%	93.5%	97.6%
INSECTS	Thaumatotibia leucotreta	ARGPLE/citrus	7.4%	11.5%	14.1%	16.7%	19.3%	21.7%	26.2%	31.0%	33.8%	37.4%	41.2%	45.8%	54.3%
BACTERIA	Xanthomonas citri	XANTCI/high impact citrus	1.8%	3.1%	4.2%	5.5%	7.0%	8.5%	12.2%	17.4%	21.3%	27.2%	35.2%	47.6%	83.6%
BACTERIA	Xylella fastidiosa	XYLEFA/citrus	0.1%	0.7%	1.5%	2.8%	4.5%	6.4%	10.9%	16.2%	19.4%	23.1%	26.7%	30.2%	34.4%
INSECTS	Bactrocera dorsalis	DACUDO/citrus	0.6%	1.6%	2.5%	3.5%	4.7%	5.9%	8.6%	11.9%	14.2%	17.2%	20.9%	25.7%	36.4%
INSECTS	Anoplophora chinensis	ANOLCN/citrus	2.5%	3.5%	4.3%	5.0%	5.8%	6.6%	8.3%	10.3%	11.7%	13.6%	16.0%	19.3%	27.4%
INSECTS	Bactrocera zonata	DACUZO/citrus	0.4%	1.2%	2.0%	2.9%	4.0%	5.0%	7.3%	9.9%	11.7%	13.9%	16.5%	19.8%	26.5%
FUNGI	Anastrepha ludens	ANSTLU/citrus, peaches	0.9%	1.5%	1.9%	2.4%	3.0%	3.6%	4.9%	6.8%	8.1%	10.0%	12.5%	16.3%	26.7%
BACTERIA	Xanthomonas citri	XANTCI/medium impact citrus	0.2%	0.7%	1.2%	1.8%	2.6%	3.3%	4.9%	6.8%	8.1%	9.8%	11.8%	14.3%	19.5%
FUNGI	Phyllosticta citricarpa	GUIGCI/citrus	0.1%	0.2%	0.4%	0.7%	1.0%	1.3%	2.1%	3.1%	3.9%	4.9%	6.2%	7.8%	11.7%

PERMALINK

Report on the methodology applied by EFSA to provide a quantitative assessment of pest‐related criteria required to rank candidate priority pests as defined by Regulation (EU) 2016/2031

Richard Baker

Gianni Gilioli

Carsten Behring

Denise Candiani

Andrey Gogin

Tomasz Kaluski

Mart Kinkar

Olaf Mosbach‐Schulz

Franco Maria Neri

Riccardo Siligato

Giuseppe Stancanelli

Sara Tramontini

Abstract

1. Introduction

1.1. Background and Terms of Reference as provided by the requestor

1.2. Interpretation of the Terms of Reference

1.2.1. Final outputs

1.2.2. Working Group composition

1.2.2.1. Ad hoc expert groups

2. Data and methodologies

2.1. Selection of information and data

2.2. Structure and content of the Pest Report

2.2.1. Summary of the biology and taxonomy

2.2.2. Host plants

2.2.2.1. Natura 2000 sites

2.2.3. Area of potential distribution

2.2.3.1. Area of current distribution

2.2.3.2. Area of potential establishment

2.2.3.3. Transient populations

2.2.4. Expected change in the use of plant protection products

Table 1.

2.2.5. Additional potential effects

2.3. Finalisation of section 2 of the Pest Report

2.4. Experts knowledge elicitation

2.4.1. Yield and quality losses

2.4.1.1. Scenario assumptions

2.4.1.2. Yield loss

2.4.1.3. Quality loss

2.4.1.4. Handling of nurseries

2.4.1.5. Translate impacts from NUTS2 to NUTS0 level

2.4.2. Spread rate and time to detection

2.4.2.1. Scenario assumptions

2.4.2.2. Spread rate

2.4.2.3. Time for detection after entry

2.4.3. Compilation of the pest datasheet

3. Summary of results

Table A.1.

Figure 1.

Figure 2.

3.1. Comparison of pests

3.1.1. Comparison of yield loss for different host categories

Table 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Figure 9.

Figure 10.

Table 10.

Figure 11.

Table 11.

Figure 12.

3.1.1.1. Cereals

3.1.1.2. Potatoes

Table 3.

3.1.1.3. Vegetables

Table 4.

3.1.1.4. Citrus

Table 5.

3.1.1.5. Pome fruits

Table 6.

3.1.1.6. Stone fruits

Table 7.

3.1.1.7. Grapes

Table 8.

3.1.1.8. Other fruits (e.g. exotic, small)