Modelling dutch elm disease on the isle of man

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Identifying Dutch elm disease (DED) ‘danger-spots’ on the Isle of Man (IoM) with an agent-based model. Bruce Mitchell, Joana Barros & Daniel WendelThe paper presents a summary of an MSc GISc dissertation ( Mitchell ). It proposes a 2.5D / 3D spatial analytical agent-based-model (ABM) approach to identifying DED ‘danger-spots’ – locations on the IoM where outbreaks of DED might lead to the greatest mortality among the Isle’s elm population.

Transcript of Modelling dutch elm disease on the isle of man

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Identifying Dutch elm disease ‘danger-spots’ on the Isle of Manwith an agent-based model

Bruce Mitchell a, Joana Barros b, Daniel Wendel c

Email a: bruce.birkbeck@ntlworld.comb: j.barros@bbk.ac.uk c: djwendel@gmail.com

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Suffolk, 1984

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StarLogo TNG - code blocks

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The Isle of Man in TNG SpaceLand

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Objective

Is there a relationship between where a beetle cluster originates and the number of agent elms that die?

If so, might that relationship be used to map the island to reveal locations where an infestation might potentially be more or less damaging?

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Isle of Man - Relief

• Scolytus beetles can only thrive where elms prosper

• Landscape determines elm habitats

• On Man, there is an ‘elm-line’ of ca. 160 metres a.s.l..

• Two ranges of hills exceed this elevation, restricting the flow of the disease across the island

• In the model, a ‘beetle-line’ was set at an arbitrary 25 % higher (200m) than the elm-line.

The combination of DEM, elm-line and beetle-line places elevation at the model’s centre.

• Beetles operating out of any given disease epicentre will find some areas accessible, others out of range.

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A single model run …Sets up tree, beetle, forester, bird

agents‘Infects’ up to 1.5% of elms with beetlesRuns an elm census at game turn (GT) 0Generates a single beetle clusterRuns a beetle census at GT 60Continues to GT 1,000Exports results to .csv fileResets to GT 0 and introduces next run

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Model agent flow chart

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The agents

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Model system flow chart

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SL-TNG OutputFor each run:

◦cluster originates in random location;◦number of elms surviving to GT1000

varies.csv run results ported to MapInfo

and SPSS for processing, then transferred to ArcGIS Spatial Analyst

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RCNS Calculation – step one

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RCNS Calculation – step two

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RCNS zones and regions

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Data processing flowchart

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Frequency of cell inclusion

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Cluster median centres and elm survival

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Modelled danger-spots

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Identifying Dutch elm disease ‘danger-spots’ on the Isle of Manwith an agent-based model 

Bruce MitchellData Visualisation CentreMethodology DirectorateOffice for National Statistics bruce.mitchell@ons.gov.uk

Joana Barros Department of Geography, Environment and Development Studies, Birkbeck, University of London, Malet Street, London, WC1E 7HX j.barros@bbk.ac.uk

Daniel WendelLead StarLogo TNG DeveloperScheller Teacher Education Program Massachusetts Institute of TechnologyBoston, MA, USA djwendel@gmail.com 

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