Contrasted optimal environmental windows for both sardinella species in Senegalese waters

We investigate Sardinella aurita and Sardinella maderensis recruitment success relative to the variability of oceanographic conditions in Senegalese waters using generalized additive models (GAM). Results show that recruitment of both species is marked by a strong intra‐annual (seasonal) variation with minimum and maximum in winter and summer, respectively. Their interannual variations are synchronous until 2006 (recruitment decreasing), while from 2007 there is no synchrony. The model developed shows that sardinella recruitment variability is closely related to the tested environmental variables in the study area. However, the key environmental variables influencing the recruitment success are different for both species: the Coastal Upwelling Index and the sea surface temperature for S. aurita and S. maderensis, respectively. We report that recruitment success of S. aurita and S. maderensis are associated with distinct ranges of sea surface temperature, upwelling intensity, wind‐induced turbulence, concentration of chlorophyll‐a and north Atlantic oscillation index. Considering food security and socio‐economic importance of both stocks, we recommend that consideration is given to the environmental variability in the small pelagic fish national management plans, particularly in the context of climate change.     

Effect of environmental conditions on the seasonal and inter‐annual variability of small pelagic fish abundance off North‐West Africa: The case of both Senegalese sardinella

The objective of this study was to assess the effect of environmental variations on the abundance of Sardinella aurita and Sardinella maderensis in Senegalese waters in the upwelling system. Monthly data indicating the abundance of sardinella were first estimated from commercial statistics, using Generalized Linear Model from 1966 to 2011. Abundance indices (AIs) were then compared with environmental indices, at the local scale, a Coastal Upwelling Index (CUI) and a coastal Sea Surface Temperature (SST) index, and on a large scale, the North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO) and the Multivariate El Niño Southern Oscillation Index (MEI), using correlations and times series analyses. The results showed that the abundance of sardinella is determined by a strong seasonal pattern and inter‐annual fluctuations. The abundance of S. aurita peaked in spring and in autumn, whereas that of S. maderensis peaked in the warm season (July–September). The trend of the sardinella abundance was significantly correlated with the CUI, especially in autumn and spring. Interannual fluctuations of S. maderensis and S. aurita abundance are, respectively, driven by the precocity and the duration of the upwelling season that is attributed to distinct migration patterns. Both sardinella species also respond with a delay of around 4 years to the winter NAO index and the autumn CUI, and the AMO index, respectively, both related to migration patterns. The wide variations in sardinella biomass are caused by variations in environmental conditions, which should be considered in the implementation of an ecosystem‐based approach in sardinella stocks management.     

Porcine colon explants in the study of innate immune response to Entamoeba histolytica

Human amebiasis is caused by the protozoan Entamoeba histolytica. This protozoan is responsible for muco-hemorrhagic diarrhoea and liver abscess in affected populations. E. histolytica can be asymptomatic commensally confined to the intestinal lumen or can result in invasion of the colonic mucosa leading to ulceration and/or liver abscesses. Recently, human colonic explants have been identified as valuable in the study of host-parasite interactions. Here we investigated the potential of porcine colonic explants as an alternative to human tissues which are far less available. Porcine colonic explants were cultured with two strains of E. histolytica, one virulent (HM1:IMSS) and one avirulent (Rahman). Results from histopathological and real-time PCR analysis showed that porcine explants cultured with virulent ameba trophozoites react similarly to their human counterparts with an invasion of the tissue by the trophozoites and the triggering of typical innate immune response against the parasite. On the contrary, explants cultured with avirulent ameba trophozoites were preserved. The study open the way to the use of porcine colonic explants in the study of the complex interactions between the parasite and the host.     

Do Sardinella aurita spawning seasons match local retention patterns in the Senegalese–Mauritanian upwelling region?

Sardinella aurita is the most abundant small pelagic fish in the Senegalese–Mauritanian region. The success of its reproduction crucially depends on the local circulation as this determines whether larvae reach coastal nursery areas favorable to their survival or are dispersed into the open ocean. As a first step towards evaluating sardinella vulnerability to climate‐driven hydrodynamical changes, this study aims at underpinning how transport pathways drive optimal spatial and seasonal patterns for sardinella reproduction. We have used two estimates of the Senegalese–Mauritanian coastal seasonal circulation simulated by two hydrodynamical model configurations that differ in their forcing and topography. Nursery areas are determined by evaluating coastal retention with a Lagrangian individual‐based model that accounts for processes such as diel vertical migration and mortality as a result of lethal temperature exposure. Our results suggest that the shelf zones located at the Arguin Bank (19.5°N–21°N) and south of Senegal (12°N–14.75°N) are highly retentive. We find maximum retention rates in July–August and November–December over the Arguin Bank; from February–July and November–December over the southern Senegalese shelf; and lower retention rates over the central region (14.75°N–19.5°N) that are locally maximum in June–July when the upwelling weakens. These retention areas and their seasonality are in agreement with previously reported spawning patterns, suggesting that the Sardinella aurita spawning strategy may result from a trade‐off between retention patterns associated with the seasonal circulation and food availability. Exposure to lethal temperatures, although not well studied, could be a further limiting factor for spawning. The Lagrangian analysis reveals important connectivity between sub‐regions within and south of the system and hence underlines the importance for joint management of the Sardinella aurita stock.     

A Bayesian zero-truncated approach for analysing capture-recapture count data from classical scrapie surveillance in France

Capture-recapture (CR) methods are used to study populations that are monitored with imperfect observation processes. They have recently been applied to the monitoring of animal diseases to evaluate the number of infected units that remain undetected by the surveillance system. This paper proposes three bayesian models to estimate the total number of scrapie-infected holdings in France from CR count data obtained from the French classical scrapie surveillance programme. We fitted two zero-truncated Poisson (ZTP) models (with and without holding size as a covariate) and a zero-truncated negative binomial (ZTNB) model to the 2006 national surveillance count dataset. We detected a large amount of heterogeneity in the count data, making the use of the simple ZTP model inappropriate. However, including holding size as a covariate did not bring any significant improvement over the simple ZTP model. The ZTNB model proved to be the best model, giving an estimation of 535 (CI(95%) 401-796) infected and detectable sheep holdings in 2006, although only 141 were effectively detected, resulting in a holding-level prevalence of 4.4‰ (CI(95%) 3.2-6.3) and a sensitivity of holding-level surveillance of 26% (CI(95%) 18-35). The main limitation of the present study was the small amount of data collected during the surveillance programme. It was therefore not possible to build complex models that would allow depicting more accurately the epidemiological and detection processes that generate the surveillance data. We discuss the perspectives of capture-recapture count models in the context of animal disease surveillance.     

A capture-recapture analysis in a challenging environment: assessing the epidemiological situation of foot-and-mouth disease in Cambodia

We performed a two-source capture-recapture analysis for estimating the true number of villages that experienced clinical cases of foot-and-mouth disease (FMD) in 2009 in Svay Rieng province, Cambodia, and assessing the completeness of the official case-reporting procedure. As a first source, we used the 2009 official dataset made up of the 15 FMD-infected villages that were reported to the provincial authorities, and enlarged this list by assuming that all the villages located at less than 4 km from one of these villages also experienced clinical cases in 2009. In addition, we created a retrospective detection protocol using participatory tools cross-checked against a serological survey that detected 13 infected villages. The capture-recapture analysis of these two detection sources led us to the conclusion that 315 (CI(95%) 117-514) villages experienced clinical cases of foot-and-mouth disease in Svay Rieng province in 2009, corresponding to a village-level annual prevalence rate of 0.46 (CI(95%) 0.17-0.74). The official reporting rate to provincial authorities could therefore be evaluated at 0.05 (CI(95%) 0.03-0.13). An analysis of the sensitivity of the estimation of the number of cases to the radius used for enlargement of Source 1 was performed, indicating its low influence. This study clearly highlights the highly enzootic situation of Cambodia regarding foot-and-mouth disease and the substantial underreporting of clinically affected villages to veterinary authorities. We propose explanations for this low notification rate, stress the importance of accurate reporting procedures and, finally, discuss the potential of capture-recapture techniques as a tool for the quantitative evaluation of animal disease surveillance systems.     

The calibration of a phytoplankton growth model using batch culture data

The feasibility of applying nonlinear parameter estimation techniques to data from batch culture of phytoplankton is studied using simulated data. A Monod-type model for nutrient uptake and growth in phytoplankton is used for the simulation. A parameter estimation procedure is applied to these data before and after they are noise-corrupted, to obtain back-calculated values of the parameter in the model. The results indicate that nonlinear parameter estimation is well suited fpr analytical interpretation of batch-culture data.