Vegetation phenology and habitat discrimination : impacts for E.multilocularis transmission host modelling

Marston, CG; Giraudoux, P; Armitage, RP; Danson, FM; Reynolds, SC; Wang, Q; Qiu, J; Craig, PS

Abstract

Echinococcus multilocularis (Em), a parasitic tapeworm, is responsible for a significant burden of human disease across continental Asia. Here, we use a time-series of MODIS 16-day 250 m Enhanced Vegetation Index (EVI) satellite data to quantify the seasonal vegetation dynamics across a study area in Serxu County, Sichuan Province, China, in relation to the presence of the Em intermediate host Ochotona curzoniae (plateau pika) and Ochotona cansus (Gansu pika) (here merged to Ochotona spp.). A series of derived phenological metrics are analysed using the random forests statistical method to determine the relative importance of seasonal vegetation characteristics. Results indicate negative relationships between Ochotona spp. presence and EVI showing a preference for low-biomass habitats. However, EVI values during green-up and senescence periods are also shown to be important, potentially resulting from improved detectability of low-biomass grassland habitats at these times. Improved detection of Ochotona spp. preferred habitats via time-series EVI imagery offers better understanding of the distributions of this Em host, and the potential for monitoring the changes in Ochotona spp. optimal habitat distributions resulting from landscape change. This could aid the identification of villages at increased risk of infection, enabling preventive strategies to be adopted.

Citation

Marston, C., Giraudoux, P., Armitage, R., Danson, F., Reynolds, S., Wang, Q., …Craig, P. (2016). Vegetation phenology and habitat discrimination : impacts for E.multilocularis transmission host modelling. Remote Sensing of Environment, 176, 320-327. https://doi.org/10.1016/j.rse.2016.02.015

• Journal Article Type: Article
• Acceptance Date: Feb 5, 2016
• Online Publication Date: Feb 16, 2016
• Publication Date: Apr 1, 2016
• Deposit Date: Feb 22, 2016
• Publicly Available Date: May 3, 2023
• Journal: Remote Sensing of Environment
• Print ISSN: 0034-4257
• Publisher: Elsevier
• Volume: 176
• Pages: 320-327
• DOI: https://doi.org/10.1016/j.rse.2016.02.015
• Publisher URL: http://dx.doi.org/10.1016/j.rse.2016.02.015
• Related Public URLs: http://www.sciencedirect.com/science/journal/00344257
• Additional Information: Grant Number: 094325/Z/10/Z; Grant Number: EID TW001565-01 & 05