Temporal modelling of Lymnaea natalensis (Krauss, 1848) in tropical aquatic habitats.

Lymnaea natalensis is the only snail intermediate host of Fasciola gigantica, the causative agent of fascioliasis, in Nigeria. The species also serves as intermediate host for many other African trematode species of medical and veterinary importance, and it is found throughout the country. However, there is no detailed information on the factors that influence its distribution and seasonal abundance in the tropical aquatic habitats in Nigeria. This study used the geographic information system and remotely sensed data to develop models for predicting the distribution of L. natalensis in South-Western Nigeria. Both land surface temperature (LST) and normalised difference vegetation index (NDVI) were extracted from Landsat satellite imagery; other variables (slope and elevation) were extracted from a digital elevation model (DEM) while rainfall data were retrieved from the European Meteorology Research Programme (EMRP). These environmental variables were integrated into a geographic information system (GIS) to predict suitable habitats of L. natalensis using exploratory regression. A total of 1410 L. natalensis snails were collected vis-à-vis 22 sampling sites. Built-up areas recorded more L. natalensis compared with farmlands. There was no significant difference in the abundance of snails with season (p  0.05). The regression models showed that rainfall, NDVI, and slope were predictors of L. natalensis distribution. The habitats suitable for L. natalensis were central areas, while areas to the north and south were not suitable for L. natalensis.Contribution: The predictive risk models of L. natalensis in the study will be useful in mapping other areas where the snail sampling could not be conducted.

Models for predicting bulinids species habitats in southwestern Nigeria.

Background: Schistosomiasis prevalence is high in southwestern Nigeria and planorbids of the genus Bulinus had been implicated in the transmission of the disease in the area. The knowledge of species distribution in relation to environmental variables will be auspicious in planning control strategies. Methods: Satellite imagery and geographic information system (GIS) were used to develop models for predicting the habitats suitable for bulinid species. Monthly snail sample collection was done in twenty-three randomly selected water contact sites using the standard method for a period of two years. Remotely sensed variables such as Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) were extracted from Landsat TM, ETM+; Slope and Elevation were obtained from digital elevation model (DEM) while Rainfall was retrieved from European Meteorology Research Program. These environmental factors and snail species were integrated into QGIS to predict the potential habitats of different bulinid species using an exploratory regression model. Results: The following environmental variables: flat-moderate slope (0.01-15.83), LST (21.1 °C-23.4 °C), NDVI (0.19-0.52), rainfall (> 1569.34 mm) and elevation (1-278 m) contributed to the model used in predicting habitat suitable for bulinids snail intermediate hosts. Exploratory regression models showed that LST, NDVI and slope were predictors of Bulinus globosus and Bulinus jousseaumei; elevation, LST, rainfall and slope were predictors of Bulinus camerunensis; rainfall, NDVI and slope were predictors of B. senegalensis while NDVI and slope were predictors of Bulinus forskalii in the area. Bulinids in the forskalii group showed clustering in middle belt and south. The predictive risk map of B. jousseaumei was similar to the pattern described for B. globosus, but with a high R-square value of 81%. Conclusion: The predictive risk models of bulinid species in this study provided a robust output for the study area which could be used as base-line for other areas in that ecological zone. It will be useful in appropriate allocation of scarces resources in the control of schistosomiasis in that environment.

Land use/land cover change, physico-chemical parameters and freshwater snails in Yewa North, Southwestern Nigeria.

The management of ecosystem has been a major contributor to the control of diseases that are transmitted by snail intermediate hosts. The ability of freshwater snails to self-fertilize, giving rise to thousands of hatchlings, enables them to contribute immensely to the difficulty in reducing the endemicity of some infections in the world. One of the effects of land use/land cover change (LU/LCC) is deforestation, which, in turn, leads to the creation of suitable habitats for the survival of freshwater snails. This study was aimed at studying the land use/land cover change, physico-chemical parameters of water bodies and to understand the interplay between them and freshwater snails in an environment where a new industrial plant was established. Landsat TM, 1984, Landsat ETM+ 2000 and Operational land Imager (OLI) 2014 imageries of the study area were digitally processed using ERDAS Imagine. The land use classification includes settlement, water bodies, wetlands, vegetation and exposed surface. Dissolved oxygen, water temperature, pH, total dissolved solids and conductivity were measured with multipurpose digital meters. Snail sampling was done at each site for 30 minutes along the littoral zones, using a long-handled scoop (0.2mm mesh size) net once every month for 24 months. Independent t-test was used to determine the variation between seasons, Spearman's rank correlation coefficient was used to test the relationship between physico-chemical parameters and snail species while regression was used to analyze the relationship between LU/LCC and freshwater snails. Species' richness, diversity and evenness were examined using Margalef, Shannon Weiner and Equitability indexes. Snail species recovered include: Bulinus globosus, Bulinus jousseaumei, Bulinus camerunensis, Bulinus senegalensis, Bulinus forskalii, Amerianna carinatus, Ferrissia spp., Segmentorbis augustus, Lymnaea natalensis, Melanoides tuberculata, Physa acuta, Gyraulus costulatus, Indoplanorbis exuxtus and Gibbiella species. Out of the total snails recovered, M. tuberculata (2907) was the most abundant, followed by Lymnaea natalensis (1542). The highest number of snail species was recovered from Iho River while the least number of snails was recovered from Euro River. The mean and standard deviation of physico-chemical parameters of the water bodies were DO (2.13±0.9 mg/L), pH (6.80±0.4), TDS (50.58±18.8 mg/L), Temperature (26.2±0.9°C) and Conductivity (74.00±27.5 µS/cm). There was significant positive correlation between pH and B. globosus (r = 0.439; P<0.05). Dissolved oxygen showed significant positive correlation with B. globosus (r = 0.454; P<0.05) and M. tuberculata (r = 0.687; P<0.01). There was a positive significant relationship between LULCC and B. camerunensis (p<0.05). The positive relationship between LULCC and the abundance of B. globosus, B. jousseaumei was not significant. The area covered by water bodies increased from 3.72 to 4.51 kilometers; this indicates that, more suitable habitats were being created for the multiplication of freshwater snails. We therefore conclude that, increase in areas suitable for the survival of freshwater snails could lead to an increase in water-borne diseases caused by the availability of snail intermediate hosts.