Soenen Karen1,Vercruysse J.1, De Roeck E.2,Van Coillie F.2, De Wulf R.2,
Hantson W.3, Ducheyne E.3, Hendrickx G.3, Charlier J.1
Towards farm specific risk maps for Fasciola hepatica:
Which factors determine snail abundance?
Potential habitats of G. truncatula are classified into five small water body types
Why?
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Fasciola hepatica in cattle costs € 1.5 billion a year in Europe (€ 8 million a year in Belgium)
No decrease in prevalence despite increased awareness
Current low resolution risk maps cover large regions
Farm specific risk maps that predict Galba truncatula occurrence may improve pasture management and targeted use of fasciolicids
Monthly snail searching during grazing season (April-November) by transect analysis in small water bodies in 2012
Moist area
Trench
Snail abundance is driven by:
(P-value < 0.05)
(Fencing, mowing,
Climatological factors
type cattle)
(min/max/mean temperature,
Mul%variate Analysis
rainfall, …)
Abundance G. truncatula
Negative Binomial Regression Model
with robust standard errors
Small water body type
Micro-environmental factors
(Abiotic: pH & temperature of soil and
small water body)
(Biotic: Occurrence of indicator plants (Juncus sp.
Ranunculus sp., grass-like sp.
(Phragmites sp.,Typha sp.))
Small water body type
Trench> Pond/Furrow/Moist area > Ditch
Total monthly rainfall (+)
Agricultural region
Addi%onal Univariate Analysis
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Furrow
Output
Management
4 farms in two distinct agricultural regions in Belgium
Ditch
Modelling
Data-collection
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Pond
Soil pH (+)
Water & mean air temperature (-)
Vegetation: Ranunculus sp. (+) and grass-like sp. (-)
Mowing (-)
Conclusion
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Small water body type, agricultural region and rainfall drive G. truncatula abundance
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Taking into account micro-environmental variables such as soil pH, vegetation and water temperature may further improve predictions of G. truncatula abundance
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Classification of small water bodies using very high resolution imagery combined with rainfall and soil maps is likely to enhance the accuracy of small scale risk maps
[email protected] - Laboratory of Parasitology, Ghent University, Belgium (1)
2Laboratory
of Forest Management and Spatial Information Techniques, Ghent University, Belgium
3Avia-GIS
– Agriculture and Veterinary Information and Analysis, Zoersel, Belgium
The SATHELI project is funded by the Belgian Science Policy Office in the frame of the STEREO II programme (SR/00/155)
