Tackling ash dieback

Develop a spatially explicit model of the spread of ADB and EAB at UK scale suitable to assess large-scale surveillance and predict the effect of control measures. The model structure will be able to represent the distribution of the host and will capture the important epidemiological and landscape characteristics that affect EAB and ADB, and potential points of entry for EAB.

Sub-objective 1.1:  Gather data on

• host distribution in the UK
• current status of ADB infection
• data on the spread of EAB in the USA and Russia.

From this we shall map the host distribution and infection status of the ash in the UK and analyse spread characteristics of EAB. 

Sub-objective 1.2:  Develop epidemiological models of the spread of EAB and ADB for UK climatic conditions, and accounting for interaction between these two threats to ash trees. Our models will include the efficacy of different forms of surveillance and types of control. We will then validate our models with data gathered in 1.1. 

Carry out extensive social scientific exploration of stakeholder values, actions and acceptability of EAB management options in order to develop an agent-based model of the behaviour of landscape-managers. This model will be based on the data gathered in 2.1 of how landscape-managers’ attitudes and behaviours influence how they act in the face of the spread and establishment of multiple biotic threats (including diseases and insect pests).

Sub-objective 2.1: Conduct a rapid evidence review and stakeholder mapping.

Sub-objective 2.2: Develop and undertake structured surveys and interviews to determine

• the values of stakeholders with respect to ash
• the stakeholders’ current tree management activities and
• the likely social acceptability of EAB surveillance and control measures.

In this context stakeholders include tree and land managers and the industry.

Sub-objective 2.3: Develop a model of the stakeholder behaviour in relation to the take-up of surveillance measures and the management of ash in the face of multiple threats.

Sub-objective 2.4: Develop and deliver participatory and deliberative workshops aiming to derive parameter values for the sociological model. 

Link the epidemiological model (Objective 1) to the model of stakeholder behaviour (Objective 2) to develop a socio-epidemic model and use this to elucidate the factors that make robust surveillance networks and sustainable strategies for the management of ash trees.

Sub-objective 3.1: Identify the key biological and sociological factors that determine the success of a national surveillance programme for the early detection of EAB under the known and widespread presence of ADB. This will account for the spatial variation in the threat to ash health resulting from EAB and ADB, the accuracy of available surveillance methods and the ability and willingness of stakeholders (incl. volunteer networks) to implement them.

Sub-objective 3.2:  Identify the key biological and sociological factors that determine the successful management of ash treescapes, including replanting strategies, that are infected by EAB and/or ADB. This will account for the epidemiology of EAB and ADB and how they interact, the efficacy of available control methods and the ability and willingness of stakeholders to implement them.

Delivery of research results.

Sub-objective 4.1: Derive recommendations for policy makers and stakeholders on how to

• set up and maintain effective surveillance networks for the detection of multiple threats to ash (i.e. EAB and ADB). This may Include recommendations related to the how citizen science might aid surveillance. exploitation of citizen science.
• manage ash-treescapes under threat from ADB and EAB in the UK.