Identification and characterization of the farmers’ named crop varieties cultivated around the world is a major issue for conservation and sustainable use of plant genetic resources. Intraspecific diversity is strongly determined by farmers’ socio-cultural environment, but this has little been documented. In this paper, we tested, on a contact zone among three ethnolinguistic groups located on the Mount Kenya region, whether farmers’ socio-cultural differences have an impact on the morphological characteristics of the farmers’ named sorghum varieties. Eighteen qualitative morphological traits of the panicles were measured. We first compared the morphological diversity of the named varieties among ethnolinguistic groups using multivariate analysis of homogeneity of groups’ dispersion and tested their differentiation using permutational multivariate analysis of variance. Discriminant analysis of principal components was then used to categorize the morphological diversity without a priori, and this classification was compared with farmers’ local taxonomy (vernacular names) in the three ethnolinguistic groups. Our results show that some morphotypes are peculiar to some ethnolinguistic groups and that a morphotype can bear different variety names while the same variety name can be used to identify different morphotypes. Morphological differentiation that was explained by ethnolinguistic groups was higher for local landraces than for improved varieties. Our findings imply that socio-cultural diversity of farmers and the criteria they use to identify and maintain landraces need to be considered in studying and sampling crop diversity for in situ as well as for ex situ conservation.

To advance our restricted knowledge on mosquito biodiversity and distribution in Belgium, a national inventory started in 2007 (MODIRISK) based on a random selection of 936 collection points in three main environmental types: urban, rural and natural areas. Additionally, 64 sites were selected because of the risk of importing a vector or pathogen in these sites. Each site was sampled once between May and October 2007 and once in 2008 using Mosquito Magnet Liberty Plus traps. Diversity in pre-defined habitat types was calculated using three indices. The association between species and environmental types was assessed using a correspondence analysis. Twenty-three mosquito species belonging to traditionally recognized genera were found, including 21 indigenous and two exotic species. Highest species diversity (Simpson 0.765) and species richness (20 species) was observed in natural areas, although urban sites scored also well (Simpson 0.476, 16 species). Four clusters could be distinguished based on the correspondence analysis. The first one is related to human modified landscapes (such as urban, rural and industrial sites). A second is composed of species not associated with a specific habitat type, including the now widely distributed Anopheles plumbeus. A third group includes species commonly found in restored natural or bird migration areas, and a fourth cluster is composed of forest species. Outcomes of this study demonstrate the effectiveness of the designed sampling scheme and support the choice of the trap type. Obtained results of this first country-wide inventory of the Culicidae in Belgium may serve as a basis for risk assessment of emerging mosquito-borne diseases.

The Statistical Feed-Forward Control Model (SFFCM) relies on a sequence of specification adjustments made on subsets of a population to counter the influence of the long time component of the variation. The difficulty strives in finding a proper estimate for the measure of the central tendency of each subset to minimize the number of the required adjustments. By means of simulating the assembly of two components having high dimensional variation, forty experiments were designed to compare the individual influence of different factors such as the number of adjustments, the sampling strategy and two measures of central tendency: the sample mean and the cumulative de-noised average. Simulation results showed that, regardless of the sampling strategy but keeping the inspection rate at 20%, the use of the cumulative de-noised average instead of the sample mean made possible to reduce the number of adjustments by 20%. Thus, while the shift mean of the resulting assembly was decreased by 90%; the standard deviation was reduced by 15%. Hence, the selection of a proper central tendency measure is crucial when modeling the long time variation. The cumulative de-noised average proved to be a valid alternative.