Abstract. The visualization of vector occurrence in space and time is an important aspect of studying vector-borne diseases. Detailed maps of possible vector habitats provide valuable information for the prediction of infection risk zones but are currently lacking for most parts of the world. Nonetheless, monitoring vector habitats from the finest scales up to farm level is of key importance to refine currently existing broad-scale infection risk models. Using Fasciola hepatica, a parasite liver fluke as a case in point, this study illustrates the potential of very high resolution (VHR) optical satellite imagery to efficiently and semi-automatically detect detailed vector habitats. A WorldView2 satellite image capable of <5m resolution was acquired in the spring of 2013 for the area around Bruges, Belgium, a region where dairy farms suffer from liver fluke infections transmitted by freshwater snails. The vector thrives in small water bodies (SWBs), such as ponds, ditches and other humid areas consisting of open water, aquatic vegetation and/or inundated grass. These water bodies can be as small as a few m 2 and are most often not present on existing land cover maps because of their small size. We present a classification procedure based on object-based image analysis (OBIA) that proved valuable to detect SWBs at a fine scale in an operational and semi-automated way. The classification results were compared to field and other reference data such as existing broad-scale maps and expert knowledge. Overall, the SWB detection accuracy reached up to 87%. The resulting fine-scale SWB map can be used as input for spatial distribution modelling of the liver fluke snail vector to enable development of improved infection risk mapping and management advice adapted to specific, local farm situations.

BackgroundThe trematode parasite Fasciola hepatica causes important economic losses in ruminants worldwide. Current spatial distribution models do not provide sufficient detail to support farm-specific control strategies. A technology to reliably assess the spatial distribution of intermediate host snail habitats on farms would be a major step forward to this respect. The aim of this study was to conduct a longitudinal field survey in Flanders (Belgium) to (i) characterise suitable small water bodies (SWB) for Galba truncatula and (ii) describe the population dynamics of G. truncatula.MethodsFour F. hepatica-infected farms from two distinct agricultural regions were examined for the abundance of G. truncatula from the beginning (April 2012) until the end (November 2012) of the grazing season. Per farm, 12 to 18 SWB were selected for monthly examination, using a 10 m transect analysis. Observations on G. truncatula abundance were coupled with meteorological and (micro-)environmental factors and the within-herd prevalence of F. hepatica using simple comparison or negative binomial regression models.ResultsA total of 54 examined SWB were classified as a pond, ditch, trench, furrow or moist area. G. truncatula abundance was significantly associated with SWB-type, region and total monthly precipitation, but not with monthly temperature. The clear differences in G. truncatula abundance between the 2 studied regions did not result in comparable differences in F. hepatica prevalence in the cattle. Exploration of the relationship of G. truncatula abundance with (micro)-environmental variables revealed a positive association with soil and water pH and the occurrence of Ranunculus sp. and a negative association with mowed pastures, water temperature and presence of reed-like plant species.ConclusionsFarm-level predictions of G. truncatula risk and subsequent risk for F. hepatica occurrence would require a rainfall, soil type (representing the agricultural region) and SWB layer in a geographic information system. While rainfall and soil type information is easily accessible, the recent advances in very high spatial resolution cameras carried on board of satellites, planes or drones should allow the delineation of SWBs in the future.

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Question: What are the main pathways of long-term stand development in forest ecosystems on oligotrophic and acidic sandy soils? Location: Nine forest reserves at different locations in The Netherlands; all ageing Pinus sylvestris forests that are no longer managed and where massive regeneration of broadleaved species is often reported. Methods: Agglomerative cluster analysis was used to define structural classes from forest reserve data. Sequences of structural classes, representing different trajectories of stand development, were constructed with the aid of a process based gap model. Results: Four main pathways of stand development could be distinguished. Three pathways are linked to gap dynamics, and lead towards dominance of Betula, Quercus or Fagus. They differ in light availability for regeneration and/or seed tree availability. The fourth pathway comprises of development patterns after major disturbances. Conclusions: The new methodological approach, combining the empirical strength of forest reserve data with the predictive ability of a process based model, made it possible to detail and quantify insights into structure and dynamics of forests on poor sandy soils. Some factors not included in the study can substantially influence pathways, especially those where Quercus and Fagus potentially play an important role.Abbreviations: Be = Betula pendula and Betula pubescens; Fa = Fagus sylvatica; MP p = Model prediction for a simulation plot p; OV p,t = output vector at time t of MP p ; Pi = Pinus sylvestris; Qu = Quercus robur and/or Q. petraea; SC = Structural class; SCO = Structural class object.Nomenclature: De Langhe et al. (1988).

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