This research utilized population genetic analyses (protein starch-gel electrophoresis and DNA sequencing of the cytochrome b mtDNA gene), host-parasite specificity (lice coevolution), remote sensing of satellite data, and geographic information systems (GIS) to characterize newly discovered populations of pocket gophers (genus: Geomys) in Arkansas. These populations are isolated and occur in seemingly unsuitable habitat in the Ozark Mountains of Arkansas. Analyses of electrophoretic and ectoparasite data suggested the populations in the Ozark Mountains represented isolates allied to Geomys bursarius, a species not known to occur in Arkansas. Comparison of mitochondrial DNA sequence data of the cytochrome b gene with that of other taxa and morphometric analyses confirmed that these populations are most closely allied to G. bursarius occurring to the north in Missouri. Moreover, these mtDNA sequence analyses indicated a degree of differentiation typical of that between other subspecies of pocket gophers. Therefore, these populations represent a distinct genetic entity in an intermediate stage of speciation and should be designated as a new subspecies, Geomys bursarius ozarkensis. Molecular clock analysis revealed a time of lineage divergence for this new subspecies as approximately 511,000 YBP. Due to the isolated nature and limited distribution of this subspecies, an evaluation of critical habitat needs was initiated. Remote sensing and GIS technologies were used to identify and describe suitable habitat Computerized classification of satellite imagery of suitable vegetation, integrated with ancillary digital information on soil associations, roads, and water systems, revealed that human activity had played a positive role in the establishment and dispersal of pocket gophers in this area. This research represents an initial combination of classical systematic tools with remote sensing and GIS to investigate biogeographic patterns and evolution. This project establishes a framework for using an interdisciplinary approach to studying organisms with limited distributions, determining evolutionary status, and providing recommendations for conservation.

A mechanistic model is developed to determine the habitat needs of drift-feeding stream salmonids from the direct cause-and- effect relationships of environmental and physiological variables on net energy intake (NEI). The model determines NEI by subtracting energy costs (basal metabolism , swimming cost, digestion cost) and losses (egestion and excretion) from the gross energy intake obtained as a result of simulated prey capture. The prey capture portion of the model utilizes components o f the predation model of C.S. Holling and the prey capture model of N.F. Hughes and L.M. Dill to determine the rate of prey capture (gross energy intake) as a function of fish size, water velocity, water depth, water temperature, and the amount of drift. Physiological input parameters for the model are estimated from the literature. Two separate validation tests of the model's ability to predict stream habitat use of trout, primarily cutthroat trout (Oncorhynchus clarki), in St. Charles Creek, Idaho, are presented. In both cases, the NEI model closely predicts the stream habitat that different size classes of fish utilize. The validation tests provide strong evidence that drift-feeding fish utilize stream habitats that provide high rates of NEI as determined by the model. Sensitivity and simulation analyses of the model are used to identify the most important input parameters and to illustrate in terms of energetics why drift-feeding fish utilize various habitats. Model simulations explain why fish utilize deeper and faster habitats as they get larger and why they utilize slower habitats in the winter. In addition, it is shown that streams with high drift rates should theoretically provide more usable salmonid habitat than similar streams with lower drift rates.