Spatial Clustering of Porcine Cysticercosis in Mbulu District, Northern Tanzania

Taenia solium is a tapeworm that causes two different disease conditions. In its adult stage, it inhabits the small intestine of human, a condition known as taeniosis, which is characterised by mild symptoms including abdominal disconfort. In the larval stage, T. solium can infect humans and various animal species, mainly pigs, causing cysticercosis. Taeniosis is acquired through consumption of inadequately cooked infected meat, while cysticercosis is acquired through ingestion of tapeworm eggs in foodstuffs contaminated with faeces from a human tapeworm carrier. Cysticercosis of human central nervous tissues (neurocysticercosis) causes serious syndromes such as epilepsy. Transmission of T. solium is facilitated by several factors such as presence of tapeworm carriers, poor sanitation and poor pig husbandry, which allow pigs to access human faeces. Nevertheless, the role of these factors in parasite transmission may vary with different cultural settings. Following an incidence and a prevalence studies in a rural area of northern Tanzania, there was a significant spatial clustering of porcine cysticerocis, suggesting focal distribution of transmission risk factors, which could be targeted for interventions. The study also revealed that despite the low sensitivity of the lingual examination method to detect porcine cysticercosis, it could highlight the potential ‘hotspots’ of the infection

Prediction of Soil Moisture-Holding Capacity with Support Vector Machines in Dry Subhumid Tropics

Soil moisture-holding capacity data are required in modelling agrohydrological functions of dry subhumid environments for sustainable crop yields. However, they are hardly sufficient and costly to measure. Mathematical models called pedotransfer functions (PTFs) that use soil physicochemical properties as inputs to estimate soil moisture-holding capacity are an attractive alternative but limited by specificity to pedoenvironments and regression methods. This study explored the support vector machines method in the development of PTFs (SVR-PTFs) for dry subhumid tropics. Comparison with the multiple linear regression method (MLR-PTFs) was done using a soil dataset containing 296 samples of measured moisture content and soil physicochemical properties. Developed SVR-PTFs have a tendency to underestimate moisture content with the root-mean-square error between 0.037 and 0.042 cm3·cm−3 and coefficients of determination (R2) between 56.2% and 67.9%. The SVR-PTFs were marginally better than MLR-PTFs and had better accuracy than published SVR-PTFs. It is held that the adoption of the linear kernel in the calibration process of SVR-PTFs influenced their performance

Integrated assessment of forest cover change and above-ground carbon stock in Pugu and Kazimzumbwi forest reserves, Tanzania

A study was conducted to estimate the forest cover change, quantify and map tree above-ground carbon stock using Re- mote sensing and GIS techniques together with forest inventory. Landsat images of 1980, 1995 and 2010 acquired dur- ing dry season were used in the estimation of cover changes. Supervised image classification using Maximum Likeli- hood Classifier was performed in ERDAS Imagine software to analyze the images and further analysis was performed in Arc GIS 9.3 software. Stratified sampling procedure was used to select concentric inventory plots in Pugu Forest Re- serve (PFR) and Kazimzumbwi Forest Reserve (KFR). Plots were laid according to NAFORMA, and the tree parame- ters in each sampling plot were collected. A Microsoft Excel spreadsheet was used to compute the above-ground bio- mass for each plot using an empirical equation relating wood basic density and tree height. The above-ground carbon was calculated using a conversion factor of 0.49. Geostatistical method in ArcGIS was used to analyze and map carbon. Results revealed that for the periods 1980-1995 and 1995-2010, Closed Forest in PFR decreased by 4.5% and 25.3% respectively, while for KFR, Closed Forest decreased by 11.9% and 31.3% respectively. The mean carbon density for PFR and KFR were respectively 5.72 tC/ha and 0.98 tC/ha while carbon stocks were 14 730.41 tC and 7 206.46 tC re- spectively. The revealed low carbon densities were attributable to decline in area under Closed Forest in the two Forest Reserves. The study recommends concerted efforts to enhance proper management of the forests so that the two forest reserves may contribute to REDD initiatives.this article is also available at http://coastalforests.tfcg.org/pubs/Japhet%20et%20al%202013.%20Integrated%20assesment%20of%20forest%20cover%20change%20in%20Tanzania.pdfThis research was supported by a NORAD funded re- search programme—Climate Change Impacts, Adapta- tion and Mitigation (CCIAM) of the Sokoine University of Agricultur

Advances in Remote Sensing

ABSTRACT A study was conducted to estimate the forest cover change, quantify and map tree above-ground carbon stock using Remote sensing and GIS techniques together with forest inventory. Landsat images of 1980, 1995 and 2010 acquired during dry season were used in the estimation of cover changes. Supervised image classification using Maximum Likelihood Classifier was performed in ERDAS Imagine software to analyze the images and further analysis was performed in Arc GIS 9.3 software. Stratified sampling procedure was used to select concentric inventory plots in Pugu Forest Reserve (PFR) and Kazimzumbwi Forest Reserve (KFR). Plots were laid according to NAFORMA, and the tree parameters in each sampling plot were collected. A Microsoft Excel spreadsheet was used to compute the above-ground biomass for each plot using an empirical equation relating wood basic density and tree height. The above-ground carbon was calculated using a conversion factor of 0.49. Geostatistical method in ArcGIS was used to analyze and map carbon. Results revealed that for the periods 1980-1995 and 1995-2010, Closed Forest in PFR decreased by 4.5% and 25.3% respectively, while for KFR, Closed Forest decreased by 11.9% and 31.3% respectively. The mean carbon density for PFR and KFR were respectively 5.72 tC/ha and 0.98 tC/ha while carbon stocks were 14 730.41 tC and 7 206.46 tC respectively. The revealed low carbon densities were attributable to decline in area under Closed Forest in the two Forest Reserves. The study recommends concerted efforts to enhance proper management of the forests so that the two forest reserves may contribute to REDD initiatives

Deforestation in an African biodiversity hotspot: extent, variation and the effectiveness of protected areas

The Eastern Arc Mountains of Tanzania show exceptional endemism that is threatened by high anthropogenic pressure leading to the loss of natural habitat. Using a novel habitat conversion model, we present a spatially explicit analysis of the predictors of forest and woodland conversion in the Eastern Arc over 25years. Our results show that 5% (210km) of evergreen forest and 43% (2060km) of miombo woodland was lost in the Eastern Arc Mountains between 1975 and 2000. Important predictors of habitat conversion included distance to natural habitat edge, topography and measures of remoteness. The main conservation strategy in these mountains for the past 100years has been to develop a network of protected areas. These appear to have reduced rates of habitat loss and most remaining evergreen forest is now within protected areas. However, the majority of miombo woodland, an important source of ecosystem services, lies outside formal protected areas, where additional conservation strategies may be needed