Habitat loss and fragmentation is a crisis affecting wildlife worldwide. In Tanzania, East Africa, a dramatic and recent (<80 years) expansion in human settlement and agriculture threatens to reduce gene flow among protected areas for many species of large mammals. Wildlife linkages can mitigate population isolation, but linkage designs lacking empirical justification may be controversial and ineffective. Connectivity conservation requires an understanding of how biogeographic factors shaped gene flow prior to habitat loss or fragmentation, however the history of interaction among populations is rarely known. The goal of my study was to provide context for connectivity conservation in central and southern Tanzania by identifying landscape features that have shaped gene flow for three ungulate species with different dispersal capabilities. I investigated historical patterns of connectivity for Maasai giraffe (Giraffa camelopardalis tippelskirchi), impala (Aepyceros melampus), and eland (Tragelaphus oryx) by estimating genetic structure among four to eight protected areas per species. Genetic structure changes very slowly among large populations and thus is likely to reflect historical processes instead of recent anthropogenic influences. I collected noninvasive DNA samples and generated microsatellite genotypes at 8 to 15 loci per species, then estimated genetic diversity metrics (allelic richness, AR, and expected heterozygosity, H[subscript E]) for each population (defined by reserve). I also calculated genetic distance (F[subscript ST] and Nei's unbiased genetic distance, D[subscript hat]) and an estimate of gene flow (Nm) between all population pairs for each species. To elucidate the possible causes of genetic structure between these populations, I tested for isolation by distance and isolation by resistance based on a suite of biogeographic factors hypothesized to affect gene flow. To do this, I created GIS-based resistance surfaces that assigned different costs of movement to landscape features. I created one or more resistance surfaces for each hypothesis of landscape effect. I used circuit theory to estimate the cumulative resistance between each pair of reserves for each weighting scheme, and then performed Mantel tests to calculate the correlation between these resistances and the observed population pairwise genetic distances (D[subscript hat]). I chose the optimal resistance model for each species as the model that was most highly correlated with observed genetic patterns. To verify that the correlation of resistance models with genetic distance was not an artefact of geographic distance, I performed partial Mantel tests to calculate correlation while controlling for the effect of geographic distance. Finally, I compared historical gene flow patterns to the distribution of contemporary human activity to predict areas that are at risk of a loss of connectivity. Indices of genetic diversity were moderate for all three species and comparable to previously reported values for other savannah ungulates. Diversity (both H[subscript E] and A[subscript R]) was highest in eland and lowest in giraffe for these populations, and was not consistently correlated with reserve size as has been reported for other species in East Africa. Although patterns in genetic distance were broadly similar across all three species there were also striking differences in connectivity, highlighting the importance of cross-species comparisons in connectivity conservation. At this scale, resistance models based on slope strongly predicted population structure for all three species; distance to water was also highly correlated with genetic distance in eland. For all three species, the greatest genetic distances occurred between populations separated by the Eastern Arc Mountains, suggesting that the topography of this area has long acted as a barrier to gene flow, but this effect is present in varying degrees for each species. I observed high levels of historical gene flow between centrally located populations (Ruaha National Park and Rungwa Game Reserve) and those in the southwest (Katavi National Park and Rukwa Game Reserve). Although human settlement in this area has been low relative to other areas, the connection between the Katavi/Rukwa and Ruaha ecosystems may be threatened by increased human activity and warrants conservation. High levels of historical gene flow were also seen between reserves in the northeast (Tarangire National Park, Swagaswaga Game Reserve) and the central and southwest populations. These connections appear highly threatened due to current land use practices, and may have already suffered a loss of gene flow. Field surveys in the lands surrounding the northeastern reserves are needed to quantify current levels of connectivity and determine whether corridors could be established to maintain or restore gene flow with other reserves. / Graduation date: 2012

Thesis (M.S.)--University of Tennessee, Knoxville, 2009. / Title from title page screen (viewed on Mar. 8, 2010). Thesis advisor: Frank T. van Manen. Vita. Includes bibliographical references.

Doctorat en Sciences / info:eu-repo/semantics/nonPublished

It has been assumed that the considerable dispersal ability of many marine species would prevent genetic divergence in the absence of geographic isolation. However, recent work has shown that many marine species often develop differentiation among areas within their known dispersal range. This 'paradox' of marine divergence is particularly important among marine mammal species where behavior can restrict gene flow. To investigate genetic substructure within such a species, I used tissue samples collected from 63 stranded Pacific harbor seals (Phoca vitulina richardsi) in Washington and Oregon between 2006 and 2010 for population stock analysis. DNA was extracted from frozen tissues, and a 551 bp fragment of mtDNA control region sequence and eight microsatellite loci were amplified to investigate localized genetic structure. Minimum spanning network and haplotype frequency analyses of mtDNA sequences indicated that while haplotype lineages are not isolated within a sampling region, there is some evidence of regional differentiation. On the other hand, microsatellite data suggest a lack of substructure among the animals sampled, with only a weak signal of limited gene flow between Puget Sound and coastal areas. Biased dispersal among age classes was also suggested, with juveniles showing less differentiation among areas than adults. Regardless of the historical scenario which has led to this complex pattern of genetic structure in Pacific harbor seals across the Pacific Northwest, my results suggest higher levels of exchange among areas than previously suspected, and will have important consequences for future management considerations for these stocks.