Operator and organizational maintenance manual : loader, scoop type, pneu-tired, diesel engine driven, hinged frame steer with 2 1/2 cu yd multi-purpose bucket, Allis-Chalmers model 645M, FSN 3805-051-9359.

"July 1968."

Direct and general support and depot maintenance repair parts and special tools lists [microform] : loader, scoop type, diesel engine, 4 wheel drive, rear wheel steerable pneumatic tires, 2 1/2 cu yd, w/multi-segment bucket (Frank G. Hough model H-90CM), FSN 3805-995-3236.

"November 1967."

Operator's, organizational and direct support maintenance manual : air conditioner, wall or base mounted, self-contained, multi-package, standard weight, air cooled, 6,000 BTU/hr cooling, 4,000 BTU/hr heating, class 1, 115 volt, single phase, 2-wire, 50/60 hertz, model CE-6A-60, Keco model F6000-7, NSN 4120-01-066-9677.

"21 November 1980."

Organizational and direct support maintenance repair parts and special tools list : air conditioner, wall or base mounted, self-contained, multi-package, standard weight, air cooled, 6,000 BTU/hr cooling, 4,500 BTU/hr heating, class 1, 115 volt, single phase, 2-wire, 50/60 Hertz, model CE-6A-60, Keco model F6000-7, NSN 4120-01-066-9677.

Includes index.

Operator, organizational, direct and general support maintenance manual : heater, space, multi-fuel, with blower, 60,000 BTU/hr, (Hunter model UH-68[[D), FSN 4520-114-1055.

"June 1969."

Operator's, organizational, direct and general support maintenance manual : heater, space, multi-fuel, with blower, 60,000 BTU/HR, (Hunter model UH-68F), NSN 4520-01-050-5628.

Includes index.

Direct and general support and depot maintenance manual : generator set, diesel engine, 200 kw, 60 cycle, AC, 120/208 V, 240/416 V, 3 phase, convertible to 167 kw, 50 cycle, 120/208 V, 240/416 V, 3 phase, multi-purpose, portable, skid mounted (military design model SF-200-MD/CIED) ...

"February 1968."

Operator, organizational, direct support, and general support maintenance manual : bath unit, portable, automated, Multi-head model PBU100, NSN 4510-01-139-4973.

"6 July 1984."

Genetic variation and inference of demographic histories in non-model species

Both long-term environmental changes such as those driven by the glacial cycles and more recent anthropogenic impacts have had major effects on the past demography in wild organisms. Within species, these changes are reflected in the amount and distribution of neutral genetic variation. In this thesis, mitochondrial and microsatellite DNA was analysed to investigate how environmental and anthropogenic factors have affected genetic diversity and structure in four ecologically different animal species. Paper I describes the post-glacial recolonisation history of the speckled-wood butterfly (Pararge aegeria) in Northern Europe. A decrease in genetic diversity with latitude and a marked population structure were uncovered, consistent with a hypothesis of repeated founder events during the postglacial recolonisation. Moreover, Approximate Bayesian Computation analyses indicate that the univoltine populations in Scandinavia and Finland originate from recolonisations along two routes, one on each side of the Baltic. Paper II aimed to investigate how past sea-level rises affected the population history of the convict surgeonfish (Acanthurus triostegus) in the Indo-Pacific. Assessment of the species’ demographic history suggested a population expansion that occurred approximately at the end of the last glaciation. Moreover, the results demonstrated an overall lack of phylogeographic structure, probably due to the high dispersal rates associated with the species’ pelagic larval stage. Populations at the species’ eastern range margin were significantly differentiated from other populations, which likely is a consequence of their geographic isolation. In Paper III, we assessed the effect of human impact on the genetic variation of European moose (Alces alces) in Sweden. Genetic analyses revealed a spatial structure with two genetic clusters, one in northern and one in southern Sweden, which were separated by a narrow transition zone. Moreover, demographic inference suggested a recent population bottleneck. The inferred timing of this bottleneck coincided with a known reduction in population size in the 19th and early 20th century due to high hunting pressure. In Paper IV, we examined the effect of an indirect but well-described human impact, via environmental toxic chemicals (PCBs), on the genetic variation of Eurasian otters (Lutra lutra) in Sweden. Genetic clustering assignment revealed differentiation between otters in northern and southern Sweden, but also in the Stockholm region. ABC analyses indicated a decrease in effective population size in both northern and southern Sweden. Moreover, comparative analyses of historical and contemporary samples demonstrated a more severe decline in genetic diversity in southern Sweden compared to northern Sweden, in agreement with the levels of PCBs found.

Mixed model formulations for multi-environment trials

When studying genotype X environment interaction in multi-environment trials, plant breeders and geneticists often consider one of the effects, environments or genotypes, to be fixed and the other to be random. However, there are two main formulations for variance component estimation for the mixed model situation, referred to as the unconstrained-parameters (UP) and constrained-parameters (CP) formulations. These formulations give different estimates of genetic correlation and heritability as well as different tests of significance for the random effects factor. The definition of main effects and interactions and the consequences of such definitions should be clearly understood, and the selected formulation should be consistent for both fixed and random effects. A discussion of the practical outcomes of using the two formulations in the analysis of balanced data from multi-environment trials is presented. It is recommended that the CP formulation be used because of the meaning of its parameters and the corresponding variance components. When managed (fixed) environments are considered, users will have more confidence in prediction for them but will not be overconfident in prediction in the target (random) environments. Genetic gain (predicted response to selection in the target environments from the managed environments) is independent of formulation.