Tick ecology data and risk maps, 2007-2010 - RELU Assessing and communicating animal disease risks for countryside users

This dataset consists of tick sampling and microclimate data from Exmoor, Richmond and New Forest study sites; as well as ARCGIS risk maps that model tick abundance driven by climate surfaces and host abundance. Tick sampling data (91 files, each representing a day of sampling) indicate tick abundance (distinguishing larvae, nymphs, adult males and adult females), vegetation height, soil moisture, temperature and relative humidity. Static risk map files indicate modeled tick abundance: 251 landcover files for the three sites, as well as 36 ArcView map files. The study is part of the NERC Rural Economy and Land Use (RELU) programme. Many people take pleasure from activities in forests and wild lands in the UK and others are being encouraged to participate. Unfortunately, there are risks and one of the most insidious is the possibility (albeit tiny) of acquiring a disease from wild animals; for example, ticks can be vectors of the bacterial infection leading to Lyme Disease. Both diagnosis and treatment can be problematic so prevention of acquiring such disease is highly desirable. Surprisingly little is known about how best to warn countryside users about the potential for disease without scaring them away or spoiling their enjoyment. Answering such questions was the goal of this project, and required the integration of a diverse set of scientific skills, and an understanding of the views of those who manage countryside, those who have contracted zoonotic diseases and those who access the land. This project combined knowledge from three strands of work, namely risk assessment, risk perception and communication, and scenario analysis. The study sites were selected to provide a range of environmental conditions and countryside use. Peri-urban parkland, accessible lowland forest and heath and remote upland forest were chosen as represented by Richmond Park on the fringe of Greater London, the New Forest in Southern England, and Exmoor in South West England. The following additional data from this same research project are available at the UK Data Archive under study number 6892 (see online resources): Lyme disease risk perception data resulting from tick imagery vignette experiments, Lyme disease patient interviews and surveys, residents and countryside staff focus groups, forest manager interviews, and multiple scoring procedures of animal social representation; as well as Lyme and tick risk communication data resulting from interviews with organisations and content analysis of risk warning information leaflets, Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).

Publication date: 2013-07-25

Where/When

Study area
Temporal extent
2007-09-01    to    2010-11-30

Supplemental information

Other useful information regarding this dataset:

Project information, publications and outputs accessible via the Relu Knowledge Portal
Data collection record for social science data resulting from the same research project

Provenance & quality

Research funded by Economic and Social Research Council, Natural Environment Research Council and Biotechnology and Biological Sciences Research Council. Award Number: RES-229-25-0007 Tick sampling data (91 files, each representing a day of sampling) indicate tick abundance (distinguishing larvae, nymphs, adult males and adult females), vegetation height, soil moisture, temperature and relative humidity. Static risk map files indicate modeled tick abundance: 251 landcover files for the three sites, as well as 36 ArcView map files.

Correspondence/contact details

Moseley, Darren
Forest Research
Edinburgh
darren.moseley@forestry.gsi.gov.uk

Authors

Moseley, Darren
Forest Research
Marcu, Afrodita
University of Surrey
Marzano, Mariella
Forest Research
O'Brien, Liz
Forest Research

Other contacts

Custodian
Environmental Information Data Centre
Owner
Randolph, Sarah
University of Oxford
Owner
Uzell, David
University of Surrey
Owner
Barnett, Julie
Brunel University

Spatial

Spatial representation type
Vector
Spatial reference system
WGS 84

Tags

Topic categories
Biota , Environment , Health
INSPIRE Theme
Human health and safety
Species distribution
Keywords
Assessing and communicating animal disease risks for countryside users,  Countryside,  great Britain,  health risks,  leisure time activities,  lyme disease,  national parks,  nature reserves,  Rural Economy and Land Use Programme,  tourism,  zoonotic diseases