Factors influencing the seasonal changes in primary productivity of the photosynthetic bacteria of Crawford Lake, Ontario

A naturally occurring population of photosynthetic bacteria, located in the meromictic Crawford Lake, was examined during two field seasons (1979-1981). Primary production, biomass, light intensity, lake transparency, pH and bicarbonate concentration were all monitored during this period at selected time intervals. Analysis of the data indicated that (l4C) bacterial photosynthesis was potentially limited by the ambient bicarbonate concentration. Once a threshold value (of 270 mg/l) was reached a dramatic (2 to 10 fold) increase in the primary productivity of the bacteria was observed. Light intensity appeared to have very little effect on the primary productivity of the bacteria, even at times when analyses by Parkin and Brock (1980a) suggested that light intensity could be limiting (i.e., 3.0-5.0 ft. candles). Shifts in the absorption maxima at 430 nrn of the .bacteriochlorophyll spectrum suggested that changes in the species or strain composition of the photosynthetic bacteria had occurred during the summer months. It was speculated that these changes might reflect seasonal variation in the wavelength of light reaching the bacteria. Chemocline erosion did not have the same effect on the population size (biomass) of the photosynthetic bacteria in Crawford Lake (this thesis) as it did in Pink Lake (Dickman, 1979). In Crawford Lake the depth of the chemocline was lowered with no apparent loss in biomass (according to bacteriochlorophyll data). A reverse current was. proposed to explain the observation. The photosynthetic bacteria contributed a significant proportion (10-60%) of the lake1s primary productivitya Direct evidence was obtained with (14C) labelling of the photosynthetic bacteria, indica.ting that the zooplankton were grazing the photosynthetic bacteria. This indicated that some of the photosynthetic bacterial productivity was assimilated into the food chain of the lake. Therefore, it was concluded that the photosynthetic bacteria made a significant contribution to the total productivity of Crawford Lake.

Starvation Induces Expression of the Plant-Adhesin Gene, Mad2, of the Entomopathogenic Fungus Metarhizium robertsii.

Metarhizium robertsii is an entomopathogenic fungus that is additionally plant rhizosphere competent. Two adhesin-encoding gens, Mad1 and Mad2, are involved in insect pathogenesis or plant root colonization, respectively. This study examined differential expression of the Mad genes for M robertsii grown on a variety of insectand plant-related substrates. Mad1 was up regulated in response to insect cuticles and up regulation of Mad2 resulted from root exudates, tomato stems and non-preferred carbohydrates. A time course analysis that compared water, minimal media, and nutrient rich broth revealed Mad2 gene expression increased as nutrient availability decreased. The regulation of Mad2 compared to known stress-related genes (Hsp30, Hsp70 and ssgA) under various stresses (nutrient, pH, osmotic, oxidative, temperature) revealed Mad2 to be generally up regulated by nutrient starvation only. Examination of the Mad2 promoter region revealed two copies of a stress-response element (S TRE) known to be regulated under the general stress response pathway.

Characterizing Dynamic Optimization Benchmarks for the Comparison of Multi-Modal Tracking Algorithms

Population-based metaheuristics, such as particle swarm optimization (PSO), have been employed to solve many real-world optimization problems. Although it is of- ten sufficient to find a single solution to these problems, there does exist those cases where identifying multiple, diverse solutions can be beneficial or even required. Some of these problems are further complicated by a change in their objective function over time. This type of optimization is referred to as dynamic, multi-modal optimization. Algorithms which exploit multiple optima in a search space are identified as niching algorithms. Although numerous dynamic, niching algorithms have been developed, their performance is often measured solely on their ability to find a single, global optimum. Furthermore, the comparisons often use synthetic benchmarks whose landscape characteristics are generally limited and unknown. This thesis provides a landscape analysis of the dynamic benchmark functions commonly developed for multi-modal optimization. The benchmark analysis results reveal that the mechanisms responsible for dynamism in the current dynamic bench- marks do not significantly affect landscape features, thus suggesting a lack of representation for problems whose landscape features vary over time. This analysis is used in a comparison of current niching algorithms to identify the effects that specific landscape features have on niching performance. Two performance metrics are proposed to measure both the scalability and accuracy of the niching algorithms. The algorithm comparison results demonstrate the algorithms best suited for a variety of dynamic environments. This comparison also examines each of the algorithms in terms of their niching behaviours and analyzing the range and trade-off between scalability and accuracy when tuning the algorithms respective parameters. These results contribute to the understanding of current niching techniques as well as the problem features that ultimately dictate their success.