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NE GCN Modelling Tender. Closes 10th Jan 2014.

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Ewan View Drop Down

Joined: 14 Jul 2003
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    Posted: 12 Dec 2013 at 12:54pm


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Am posting this for info and not on behalf of NE - contact them not me!


 Specification for understanding modelling of the Great Crested Newt in England


 This purpose of the contract is intended to improve our understanding of statistical and spatial modelling of Great Crested Newt (GCN) in England. The intelligence provided will inform our future investment in GCN data and modelling, allowing us to secure value for money by developing a measured programme of field work and model development. This will aid us in taking evidence based decisions to benefit GCN.


 The Great Crested Newt (GCN) is strictly protected under the European Habitats Directive. The Directive requires understanding of the species’ status across its range. Knowledge of GCN distribution at a local level is required to both comply with the strict protection requirements afforded to this species under the Habitats Regulations and to plan positive conservation actions for this species. The ecology and widespread distribution of the GCN render extensive survey for national use and detailed surveillance for local purposes across Great Britain prohibitively expensive. Different types of models have been used or tested at a GB/national scale, with varying levels of success, to predict pond and 1km2 occupancy, broad distribution, and trends in occurrence of the GCN. The country agencies, working with Amphibian and Reptile Conservation(ARC), have developed a spatial modelling approach, most advanced in Wales, using Maximum Entropy (MaxEnt) models to predict GCN occurrence at a local scale. Additional modelling work using least cost paths to interpret connectivity between populations has been developed and is being used to guide developers and conservation planners, and to aid Welsh licensing authorities in making derogation decisions. Such modelled outputs could also help to target both development compensation and conservation actions.

 Details of the Habitats Directive surveillance requirements and the modelling work referred to above are listed in Appendix 1.

 In order to secure better outcomes for GCN across GB the Secretary of State has established the Defra GCN Task Force. This group has representation from across Government departments and agencies alongside non-government organisations.


 Natural England is letting this contract to deliver the below requirements to help inform the next steps to progress this area of work in England. It will also form part of Natural England’s contribution to the Task Force. The contract will run in tandem with a Memorandum of Agreement between Natural England and Amphibian and Reptile Conservation who have developed the most detailed GCN models to date, including those currently being effectively deployed in North Wales. The successful contractor will need to work closely with ARC on this project. 



Requirement 1: Review existing modelling work

 Undertake a review exercise to test the rationale behind the existing modelling (details of which will be provided to the successful contractor on contract award), working with ARC to test the type of modelling, logic, parameters and statistics employed. While MaxEnt is widely accepted as the foremost software for modelling species distribution, the contractor is required to consider if other options might be more appropriate. The contractor should suggest improvements to the existing MaxEnt approach. ARC has c.60 separately funded staff days assigned to modelling evaluation and improvements.

 In completing this objective, the contractor will be expected to assess the following, with reasoning:

 ·        Soundness of the current rationale.

·        Predictive power of the current approach, including an assessment of sensitivity to different parameters, geographies and scalability.

·        Limitations of the current approach and the likely impact on predictive power

·        Comparison to alternative modelling approaches (i.e. different techniques).

·        Suggest improvements that can be made.

·        Ground-truthing requirements.

·        Requirements, such as future field survey, for keeping model(s) up to date.

Requirement 2: Scoping analysis of future model investments.

 Undertake an analysis of the data and model development requirements, and the associated initial and ongoing costs, to provide useful modelled outputs at a series of scales:


·        Local (e.g. one or more Local Planning Authority or an English County)

·        Biogeographical (e.g. multi-county such as the South East England GCN ‘hot spot’, perhaps using National Character Areas)

·        Country (England)


Compare the cost, predictive power and confidences of different scenarios to achieve national coverage (e.g. 30 models, 16 models, 7 models, a single model). Describe the expected returns on investment in new data, including a point of diminishing returns if applicable, and the value of updates.

Requirement 3: Using model outputs.

Provide technical guidance on the interpretation of models. This should include any conversions of model outputs necessary to ensure comparability between models if more than one is needed to achieve national coverage.

Working with the project officer, who will advise on relevant scenarios with the input of NE staff, the contractor will be expected to present illustrated examples of ways in which model outputs could potentially be applied in real-world scenarios. Scenarios are likely to include:

 ·        Local decision making on land use planning and licensing

·        Targeting conservation and compensation mitigation measures at a sub-national scale

·        Estimating impacts on local conservation status from developments and conservation activity.

Requirement 4: Presentation of findings

 The reports produced in requirements 1 – 3 to be presented at the final meeting to the steering group at the end of the contract in a Power Point Presentation format.  Detailed arrangements of this meeting by mutual agreement. Location likely to be London.

Ewan Shilland
Contract Research Scientist
Environmental Change Research Centre
University College London
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