Thesis (M. Env. Sc.)--University of Adelaide, Mawson Graduate Centre for Environmental Studies, 1999. / Includes bibliographical references (leaves 124-134).

Recently, it was reported that humans treat animals that they perceive as aesthetically attractive unequally to the "ugly" ones, turning more attention to them and setting more conservation programs for their protection. The aim of this thesis was to investigate the issue focusing around animal beauty in more detail by examining human preferences towards one of the most popular animal taxon, the birds. In three subsequent studies, we assessed human preferences towards selected bird species: all members of the order of parrots, randomly selected representatives of all non- passerine bird families, and all members of the vividly colored passerine family Pittidae. The first study revealed that the preferred parrots were kept in zoos in higher numbers, regardless of their conservation priority (IUCN status). We discussed possible consequences of this finding and the benefits that may arise in the light of animal conservation if this bias in species preferences was to be considered by conservation specialists. We also found that people preferred long-tailed parrots possessing blue and yellow colors over green ones, which were probably perceived as dull and uninteresting as the majority of the parrots are fully or partially green. In the next two studies, we found that shape, pattern, and overall...

Thesis (Ph. D.)--University of Nevada, Reno, 2007. / "December 2007." Includes bibliographical references. Online version available on the World Wide Web.

No / A species conservation technique takes inspiration from the field of ecology, in which the population is divided into several species according to their similarity. Based on this technique, a Species Conservation Genetic Algorithms (SCGA) was established and had been proved to be very effective in finding multiple solutions of multimodal optimisation problems, including some problems known to be deceptive for genetic algorithms (GAs). In this paper, the SCGA is introduced to engineering structure design, and two structure designs are used to demonstrate the performances of the SCGA and how the choice of a meaningful measure of similarity will help in exploration of significant designs.

The main goal of a scheduling process is to decide when and how to execute each of the project’s activities. Despite large variety of researched scheduling problems, the majority of them can be described as generalisations of the resource-constrained project scheduling problem (RCPSP). Because of wide applicability and challenging difficulty, RCPSP has attracted vast amount of attention in the research community and great variety of heuristics have been adapted for solving it. Even though these heuristics are structurally different and operate according to diverse principles, they are designed to obtain only one solution at a time. In the recent researches on RCPSPs, it was proven that these kind of problems have complex multimodal fitness landscapes, which are characterised by a wide solution search spaces and presence of multiple local and global optima. The main goal of this thesis is twofold. Firstly, it presents a variation of the RCPSP that considers optimisation of projects in an uncertain environment where resources are modelled to adapt to their environment and, as the result of this, improve their efficiency. Secondly, modification of a novel evolutionary computation method Cuckoo Search (CS) is proposed, which has been adapted for solving combinatorial optimisation problems and modified to obtain multiple solutions. To test the proposed methodology, two sets of experiments are carried out. First, the developed algorithm is applied to a real-life software development project. Second, performance of the algorithm is tested on universal benchmark instances for scheduling problems which were modified to take into account specifics of the proposed optimisation model. The results of both experiments demonstrate that the proposed methodology achieves competitive level of performance and is capable of finding multiple global solutions, as well as prove its applicability in real-life projects.

No / This paper introduces a new technique called species conservation for evolving paral-lel subpopulations. The technique is based on the concept of dividing the population into several species according to their similarity. Each of these species is built around a dominating individual called the species seed. Species seeds found in the current gen-eration are saved (conserved) by moving them into the next generation. Our technique has proved to be very effective in finding multiple solutions of multimodal optimiza-tion problems. We demonstrate this by applying it to a set of test problems, including some problems known to be deceptive to genetic algorithms.

The main goal of a scheduling process is to decide when and how to execute each of the project's activities. Despite large variety of researched scheduling problems, the majority of them can be described as generalisations of the resource-constrained project scheduling problem (RCPSP). Because of wide applicability and challenging difficulty, RCPSP has attracted vast amount of attention in the research community and great variety of heuristics have been adapted for solving it. Even though these heuristics are structurally different and operate according to diverse principles, they are designed to obtain only one solution at a time. In the recent researches on RCPSPs, it was proven that these kind of problems have complex multimodal fitness landscapes, which are characterised by a wide solution search spaces and presence of multiple local and global optima. The main goal of this thesis is twofold. Firstly, it presents a variation of the RCPSP that considers optimisation of projects in an uncertain environment where resources are modelled to adapt to their environment and, as the result of this, improve their efficiency. Secondly, modification of a novel evolutionary computation method Cuckoo Search (CS) is proposed, which has been adapted for solving combinatorial optimisation problems and modified to obtain multiple solutions. To test the proposed methodology, two sets of experiments are carried out. Firstly, the developed algorithm is applied to a real-life software development project. Secondly, the performance of the algorithm is tested on universal benchmark instances for scheduling problems which were modified to take into account specifics of the proposed optimisation model. The results of both experiments demonstrate that the proposed methodology achieves competitive level of performance and is capable of finding multiple global solutions, as well as prove its applicability in real-life projects.

Understanding dispersal and gene flow in human-modified landscapes is crucial for effective conservation. Seed dispersal governs colonization, recruitment, and distribution of plant species, whereas both pollen and seed dispersal determine gene flow among populations. This PhD thesis tests the effect of rotational shepherding on seed dispersal and gene flow in fragmented calcareous grasslands. Calcareous grasslands (Gentiano-Koelerietum pyramidatae vegetation) in Central Europe are semi-natural communities traditionally used for rotational grazing that experienced a decline of plant species during the 20th century due to abandonment of shepherding. This PhD profits from a management project started in 1989 in Bavaria, Germany to reconnect previously abandoned calcareous grasslands in three non-overlapping shepherding systems. Two vegetation surveys in 1989 and 2009 revealed colonizations in previously abandoned grasslands reconnected by shepherding. First, I propose a comprehensive approach to identify determinants of community-level patch colonization rates based on 48 habitat specialist plants by testing competing models of pre-dispersal and dispersal effects and accounting for post-dispersal effects. Mean source patch species occupancy in 1989, and structural elements in focal patches related to establishment explained community-level patch colonization rates. Secondly, by adapting the community analysis to all 31 individual species of the same community with sufficient data, I corroborate the role of shepherding to support dispersal for a range of species, even if they lack seed morphological traits related to zoochory. Thirdly, for the habitat specialist Dianthus carthusianorum, I genotyped 1,613 individuals from 64 populations at eleven microsatellites to test the effect of dispersal by sheep on spatial genetic structure at the landscape scale. Genetic distances between grazed patches of the same herding system were related to distance along herding routes, whereas ungrazed patches showed isolation by geographic distance. Lastly, within individual grassland patches, shepherding significantly decreases the degree of relatedness among neighboring individuals (kinship structure) and increases genetic diversity. My thesis contributes towards understanding the effects of zoochory on spatial dynamics in plant populations across scales.

Understanding dispersal and gene flow in human-modified landscapes is crucial for effective conservation. Seed dispersal governs colonization, recruitment, and distribution of plant species, whereas both pollen and seed dispersal determine gene flow among populations. This PhD thesis tests the effect of rotational shepherding on seed dispersal and gene flow in fragmented calcareous grasslands. Calcareous grasslands (Gentiano-Koelerietum pyramidatae vegetation) in Central Europe are semi-natural communities traditionally used for rotational grazing that experienced a decline of plant species during the 20th century due to abandonment of shepherding. This PhD profits from a management project started in 1989 in Bavaria, Germany to reconnect previously abandoned calcareous grasslands in three non-overlapping shepherding systems. Two vegetation surveys in 1989 and 2009 revealed colonizations in previously abandoned grasslands reconnected by shepherding. First, I propose a comprehensive approach to identify determinants of community-level patch colonization rates based on 48 habitat specialist plants by testing competing models of pre-dispersal and dispersal effects and accounting for post-dispersal effects. Mean source patch species occupancy in 1989, and structural elements in focal patches related to establishment explained community-level patch colonization rates. Secondly, by adapting the community analysis to all 31 individual species of the same community with sufficient data, I corroborate the role of shepherding to support dispersal for a range of species, even if they lack seed morphological traits related to zoochory. Thirdly, for the habitat specialist Dianthus carthusianorum, I genotyped 1,613 individuals from 64 populations at eleven microsatellites to test the effect of dispersal by sheep on spatial genetic structure at the landscape scale. Genetic distances between grazed patches of the same herding system were related to distance along herding routes, whereas ungrazed patches showed isolation by geographic distance. Lastly, within individual grassland patches, shepherding significantly decreases the degree of relatedness among neighboring individuals (kinship structure) and increases genetic diversity. My thesis contributes towards understanding the effects of zoochory on spatial dynamics in plant populations across scales.

The main goal of a scheduling process is to decide when and how to execute each of the project’s activities. Despite large variety of researched scheduling problems, the majority of them can be described as generalisations of the resource-constrained project scheduling problem (RCPSP). Because of wide applicability and challenging difficulty, RCPSP has attracted vast amount of attention in the research community and great variety of heuristics have been adapted for solving it. Even though these heuristics are structurally different and operate according to diverse principles, they are designed to obtain only one solution at a time. In the recent researches on RCPSPs, it was proven that these kind of problems have complex multimodal fitness landscapes, which are characterised by a wide solution search spaces and presence of multiple local and global optima. The main goal of this thesis is twofold. Firstly, it presents a variation of the RCPSP that considers optimisation of projects in an uncertain environment where resources are modelled to adapt to their environment and, as the result of this, improve their efficiency. Secondly, modification of a novel evolutionary computation method Cuckoo Search (CS) is proposed, which has been adapted for solving combinatorial optimisation problems and modified to obtain multiple solutions. To test the proposed methodology, two sets of experiments are carried out. Firstly, the developed algorithm is applied to a real-life software development project. Secondly, the performance of the algorithm is tested on universal benchmark instances for scheduling problems which were modified to take into account specifics of the proposed optimisation model. The results of both experiments demonstrate that the proposed methodology achieves competitive level of performance and is capable of finding multiple global solutions, as well as prove its applicability in real-life projects.