Vertical Assessment of Public Global Digital Elevation Models Including 1"SRTM Generally, and in Eight Sample Land Covers and Terrains of Tanzania

Recent public global digital elevation models (GDEMs) include, ,  and . GDEMs have many useful applications in many areas.  Many developing countries are not in position to determine their own reliable digital elevation models (GDEMs). Often a resort is to search for public GDEM that suits its purpose better. The search for a suitable DEM for Tanzania has been going on for more than a decade. In this paper, a review of search for a better GDEM for Tanzania in the past five years through vertical assessment of public GDEMs is given.  The method used is the statistical assessment of the differences of GDEM and GPS control point heights relative to EGM96 geoid model. The assessment used between 127 and 222 GPS control points scattered over Tanzania. Always two GDEMs were compared and validated, often was one of the GDEMs. In 2012 and 2013, the comparison and assessment was general over the whole country. In 2014, in addition to the general assessment, three representative land covers and terrains were also involved. In 2015, the representative land covers and terrains were increased to six and in 2016 they were eight. The other public GDEMs involved are ,  and.  and  proved in their first assessments to be much inferior to  and . The overall fit of to the GPS controls is about 7m while for the  and  is around 10m.  is close to the two 3-arc seconds GDEMs by about 6m.Performance of is the best in flat and almost bare land where STD is 1.5m and RMS is 2.4m, and is the worst in rough, mountainous and forested terrain where the STD is 10m and RMS is 10.5m.  performance is superior to all the GDEMs validated until 2016 and therefore the best DEM for Tanzania.

Assessing the genetic diversity of farmed and wild Rufiji tilapia (Oreochromis urolepis urolepis) populations using ddRAD sequencing

Rufiji tilapia (Oreochromis urolepis urolepis) is an endemic cichlid in Tanzania. In addition to its importance for biodiversity conservation, Rufiji tilapia is also attractive for farming due to its high growth rate, salinity tolerance, and the production of all-male hybrids when crossed with Nile tilapia (Oreochromis niloticus). The aim of the current study was to assess the genetic diversity and population structure of both wild and farmed Rufiji tilapia populations in order to inform conservation and aquaculture practices. Double-digest restriction-site-associated DNA (ddRAD) libraries were constructed from 195 animals originating from eight wild (Nyamisati, Utete, Mansi, Mindu, Wami, Ruaha, Kibasira, and Kilola) and two farmed (Bwawani and Chemchem) populations. The identified single nucleotide polymorphisms (SNPs;n = 2,182) were used to investigate the genetic variation within and among the studied populations. Genetic distance estimates (F-st) were low among populations from neighboring locations, with the exception of Utete and Chemchem populations (F-st = 0.34). Isolation-by-distance (IBD) analysis among the wild populations did not detect any significant correlation signal (r = .05;p-value = .4) between the genetic distance and the sampling (Euclidean distance) locations. Population structure and putative ancestry were further investigated using both Bayesian (Structure) and multivariate approaches (discriminant analysis of principal components). Both analysis indicated the existence of three distinct genetic clusters. Two cross-validation scenarios were conducted in order to test the efficiency of the SNP dataset for discriminating between farmed and wild animals or predicting the population of origin. Approximately 95% of the test dataset was correctly classified in the first scenario, while in the case of predicting for the population of origin 68% of the test dataset was correctly classified. Overall, our results provide novel insights regarding the population structure of Rufiji tilapia and a new database of informative SNP markers for both conservation management and aquaculture activities

Effect of Salinity on the Survival and Growth of Rufiji Tilapia (Oreochromis urolepis urolepis) Fry

AbstractSurvival and growth of Rufiji tilapia (Oreochromis urolepis urolepis) fry were determined under controlled salinity conditions of 5, 15, 25 and 35 ppt for 56 days. Experiments were carried out in 12 concrete tanks of 1 m3 volume each with three replicates for each treatment. Data was recorded at fourteen days intervals where weight measurements (g) of fry were recorded to the nearest 0.01 g. One Way Analysis of Variance (ANOVA) was used for data analysis. Results showed significant differences in the final body weight, specific growth rate, weight gain and daily growth rate at different salinity levels. The fry reared at a salinity of 25 ppt had the highest final body weight, specific growth rate, weight gain and daily growth rate, while the lowest was recorded at the salinity of 5 ppt. There was no significant difference in survival rate among the fry reared at different salinity levels. Dissolved oxygen (DO) was significantly different at different levels of salinity but temperature and pH showed no significant differences. The results suggest that under proper management, Rufiji tilapia can be farmed in brackish and sea water by coastal communities along the coast.

USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODEL

There exist a number of methods for approximating the local geoid surface and studies carried out to determine a local geoid. In this study, performance of geoid by PSO method in modeling local geoid was presented and analyzed. The ellipsoidal heights (h), derived from GPS observations, and known orthometric heights from first-order bench marks were first used to create local geometric geoid model, then the PSO method was used to convert ellipsoidal heights into orthometric heights (H). The resulting values were used to compare between the spirit leveling and GPS methods. The adopted PSO method can improve the fitting of local geometric geoid by quadratic surface fitting method, which agrees with the known orthometric heights within ±1.02cmthe Cartography produced: General Map, Partial Maps, Profile, Cross Sections and others