Genetic structure of the savannah elephant population ( Loxodonta africana (Blumenbach 1797)) in the Kavango-Zambezi Transfrontier Conservation Area

Earlier studies investigated the genetic structure of fragmented or isolated elephant populations by comparing the genetic characteristics of pre-defined populations. This study aimed to determine if there was genetic evidence for spatial structuring in a continuous elephant population in the Kavango-Zambezi Transfrontier Conservation Area (KAZA-TFCA).;There were three significantly differentiated mtDNA sub-populations (Fst = 0.787), and two nDNA sub-populations that were not significantly differentiated (Fst = -0.02; Rst = -0.045), implying obstructed mtDNA, but high nDNA gene flow across the study region. Also, gene flow was apparent between Chobe and Kafue National Parks, where telemetry data has as of yet not recorded inter-population movements between these parks.;The three mtDNA sub-populations were geographically differentiated and followed political boundaries as apparent sub-populations in Botswana, Zambia and Zimbabwe. The differences between mtDNA and nDNA genetic structuring may be explained by i) historical events that shaped the current genetic structure (e.g. through founder-effects and persistent poaching hotspots) and ii) intrinsic variables that influence genetic structure at a local scale (e.g. through resource dependencies and social behaviour). The KAZA elephant population has a genetic diversity (mtDNA diversity as the pairwise number of differences (th) = 2.59; nDNA diversity as the mean alleles/locus and He = 7.5, 0.71) higher than other southern African populations, and inter-population movements may be responsible for maintaining this genetic diversity.;I recommend continued support for conservation initiatives that aim at maintaining and restoring connectivity between populations through landscape linkages, which in so doing may ensure inter-population gene flow and uphold the current genetic state of the KAZA-TFCA elephant population.;I sequenced one mtDNA gene region for 88 individuals and genotyped 100 individuals for 10 nuclear microsatellite loci. Bayesian Clustering Algorithms incorporated in the program Geneland were used to identify groups of genetically similar individuals. An Analysis of Molecular Variance (AMOVA) determined if these groups (henceforth referred to as subpopulations) were significantly differentiated. I used a Geographic Information System (GIS) landscape genetic toolbox to identify areas in the landscape with high genetic divergence between individual samples to determine if there were identifiable genetic barriers in the landscape.