Geostatistical models using remotely-sensed data predict savanna tsetse decline across the interface between protected and unprotected areas in Serengeti, Tanzania-Reference-Cited by-同舟云学术

Geostatistical models using remotely-sensed data predict savanna tsetse decline across the interface between protected and unprotected areas in Serengeti, Tanzania

Published:2018-02-13 Issue:4 Volume:55 Page:1997-2007
ISSN:0021-8901
Container-title:Journal of Applied Ecology
language:en
Short-container-title:J Appl Ecol

Author:

Lord Jennifer S.¹^ORCID,Torr Stephen J.¹,Auty Harriet K.²,Brock Paddy M.³,Byamungu Mechtilda⁴,Hargrove John W.⁵,Morrison Liam J.⁶,Mramba Furaha⁴,Vale Glyn A.⁵⁷,Stanton Michelle C.¹

Affiliation:

1. Department of Vector Biology; Liverpool School of Tropical Medicine; Liverpool UK

2. Epidemiology Research Unit; SRUC; Inverness UK

3. Institute of Biodiversity, Animal Health and Comparative Medicine; College of Medical, Veterinary and Life Sciences; University of Glasgow; Glasgow UK

4. Vector and Vector-Borne Diseases Research Institute; Tanga Tanzania

5. SACEMA; University of Stellenbosch; Stellenbosch South Africa

6. Roslin Institute; Royal (Dick) School of Veterinary Studies; University of Edinburgh; Midlothian UK

7. Natural Resources Institute; University of Greenwich; Chatham UK

Funder

Zoonosis and Emerging and Livestock Systems (ZELS) programme

UNICEF

Biotechnology and Biological Sciences Research Council

Department for International Development

The Economic and Social Science Research Council

Natural Environment Research Council

International Development Research Centre

Seventh Framework Programme

ICONZ (Integrated Control of Neglected Zoonoses)

Publisher

Wiley

Subject

Ecology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/1365-2664.13091/fullpdf

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4. Trypanosome diversity in wildlife species from the Serengeti and Luangwa valley ecosystems ed J.M. Ndung'u;Auty;PLoS Neglected Tropical Diseases,2012

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