Resources that can optimize survival are distributed unevenly across landscapes. I assumed that the distribution of these resources is reflected by landscape heterogeneity and that selection for areas with relatively high heterogeneity reflects on selection for resources. I therefore hypothesized that landscape heterogeneity determines variability in elephant home range location and size. I evaluated home range sizes for elephants living in the Etosha National Park (n = 6), Khaudum Game Reserve (n = 6) and Ngamiland District 11 (n = 4) during two wet and two dry seasons. I used raster grid landscape maps, which were based on structural classes, to superimpose elephant home ranges and to generate randomly located ranges. I then used the FRAGSTATS programme to calculate five landscape metrics that measure aspects of heterogeneity within elephant and randomly located ranges. I compared landscape heterogeneity of the three study areas using the landscape metrics calculated for the randomly located ranges. Assuming that higher values of Patch density, Lanscape shape index and Shannon diversity index, and lower values of Largest patch index and Contagion implies selection for heterogeneity, I qualitatively compared the distribution and the mean of the landscape metric values for the elephant home ranges with those for the randomly located ranges. The influence of season on selection for the landscape metrics was also evaluated. I searched for relationships between home range size and landscape metrics for the three study areas and searched for a possible relationship between home range size and water point density for elephants in Etosha and Khaudum. Khaudum was consistently more heterogeneous than Etosha and NG11, while the latter was the least heterogeneous. Within these study areas, at least some of the landscape metrics may explain the location of elephant home ranges. The consistent apparent selection for areas with relatively higher values of Landscape shape index and Shannon diversity index and lower values of Largest patch index and Contagion across both wet and/or dry seasons by elephants in Etosha and NG11 suggests that landscape heterogeneity can explain landscape selection by elephants. This did not hold for elephants in Khaudum where elephants inconsistently selected for Largest patch index and Landscape shape index. This study further suggested that landscape heterogeneity did not determine home range size. However, water was a strong determinant of home range size and may therefore explain the lack of selection for heterogeneity in Khaudum. Heterogeneity is an inherent characteristic of landscapes and seems to reflect on the availability of resources that may subsequently influence the way elephants use space. My study supported the concept that increasing space, while promoting heterogeneity for elephants may enhance range expansion. The management of elephants should therefore be directed at optimising the availability of heterogeneous landscapes when setting land aside for their conservation. Management also should reconsider water distribution policies since the availability of water influences landscape use and conceivably potential impact on vegetation. / Dissertation (MSc)--University of Pretoria, 2008. / Zoology and Entomology / unrestricted

Abstract Senecio is one of the largest genera in the Asteraceae family with 28 Senecio species in New Zealand and over 1200 species worldwide. Native Senecio in the Canterbury region are typically naturally uncommon and exhibit extreme fluctuations in population size. Contrary to native Senecio, exotic Senecio in the Canterbury region are thriving. Why some exotic species thrive in a novel environment while native species decline has been an area of intense study since the era of Darwin. However, despite extensive study, we are still unsure about the underlying mechanisms of this phenomenon. This thesis looks at several hypotheses that have been proposed to explain differences in success between native and exotic species including four that have been frequently mentioned in the literature: phylogenetics, natural enemy release and biotic resistance, allopolyploidy and habitat modification. In order to determine if phylogenetic relatedness influences the abundance and distribution of Senecio species in Canterbury, DNA phylogenies of New Zealand’s Senecio were constructed using nuclear (ITS, ETS) and plastid (trnL, trnL-F and psbA-trnH) DNA sequences. The resulting cladograms were used to determine the areas of origin of New Zealand’s Senecio lineages, the identity of their closest relatives and lineages and species that are of allopolyploid origin. The data provided by the phylogenetic analyses was to provide context for analyses of ecological data of 86 native and exotic Senecio populations from the Canterbury region. My results indicate that phylogenetic relatedness is a poor predictor of the amount of folivory experienced by Senecio, although some natural enemies of native and exotic Senecio displayed a positive preference for Senecio depending on their clade. The strongest effects on Senecio and the occurrences of their natural enemies came from the surrounding land use which influenced the amount of folivory and the abundances of natural enemies on Senecio. Enemy release and biotic resistance were land use specific within Canterbury and by themselves cannot explain the variance in folivory when applied to a landscape scale. According to my results, the biggest factor influencing Senecio folivory, abundance and distribution in the Canterbury region is change in the surrounding land use.

The brown bear (Ursus arctos) is a generalist omnivore that occupies diverse habitats and displays high levels of behavioral plasticity. Plasticity in foraging behavior can result in variable diets across a population, and allow individuals to use a greater variety of resources. The distribution of food in space and time may also be an important factor in determining brown bear resource selection as it can greatly influence foraging efficiency. Our objectives were to determine if seasonal brown bear home ranges were influenced by temporal availability and spatial distribution of resources and if deviation from an optimal diet influenced brown bear body condition. Understanding how the spatial and temporal distribution of food influences brown bear space use and the relationships between behavioral plasticity and the ability of populations to persist in dynamic environments could provide additional insights into the eco-evolutionary advantages of variable foraging behavior and ultimately population resilience.

Biological invasions are devastating ecosystems and economies world-wide, while many native species' survival depends on their ability to track climate change. Characterising the spread of biological populations is therefore of utmost importance, and can be studied with spatially explicit, discrete-time integro-difference equations (IDEs), which reflect numerous species' processes of demography and dispersal. While spatial variation has often been ignored when implementing IDE models, real landscapes are rarely spatially uniform and environmental variation is crucial in determining biological spread. To address this, we use novel methods to characterise population spread in heterogeneous landscapes. Asymptotic analysis is used for highly fragmented landscapes, where habitat patches are isolated and smaller than the dispersal scale, and in landscapes with low environmental variation, where the ecological parameters vary by no more than a small factor from their mean values. We find that the choice of dispersal kernel determines the effect of landscape structure on spreading speed, indicating that accurately fitting a kernel to data is important in accurately predicting speed. For the low-variation case, the spreading speeds in the heterogeneous and homogeneous landscapes differ by ϵ², where ϵ governs the degree of variation, suggesting that in many cases, a simpler homogeneous model gives similar spread rates. For irregular landscapes, analytical methods become intractable and numerical simulation is needed to predict spread. Accurate simulation requires high spatial resolution, which, using existing techniques, requires prohibitive amounts of computational resources (RAM, CPU etc). We overcome this by developing and implementing a novel algorithm that uses adaptive mesh refinement. The approximations and simulation algorithm produce accurate results, with the adaptive algorithm providing large improvements in efficiency without significant losses of accuracy compared to non-adaptive simulations. Hence, the adaptive algorithm enables faster simulation at previously unfeasible scales and resolutions, permitting novel areas of scientific research in species spread modelling.

The dynamics of ecological populations and communities are predominantly governed by three ecological processes, environmental filtering, species interactions and dispersal, and these processes may vary with heterogeneity of the environment. In my PhD research, I investigated how ecologists conceptualize landscape heterogeneity, and how these three ecological processes may vary with spatial and temporal environmental heterogeneity. I conducted my empirical work in Alliaria petiolata, a non-native invasive species in North America, at the Koffler Scientific Reserve at Joker’s Hill in Ontario, Canada. The thesis contains six chapters, where chapters 2 – 5 are structured as stand-alone manuscripts. In chapter 2, I conducted a quantitative review to link the metacommunity concept (which combines the above-mentioned three processes) with different conceptual models of landscape spatial heterogeneity. I found that 78% of metacommunity studies were not explicit about the underlying model of landscape heterogeneity, though there was a significant association between the implied model of landscape heterogeneity and the observed metacommunity model. In chapter 3, I quantified dispersal of Alliaria petiolata, assessed the spatial structure of rosette and adult density, and compared the effects of the different processes on rosette and adult density. Seed dispersal followed a lognormal distribution (μ = 0.01, σ = 0.65). Both adults and rosettes exhibited significant spatial structure up to 2 m. Propagule pressure and interactions among life stages were significant processes shaping rosette density, whereas propagule pressure was the only important process shaping adult density. In chapter 4, I investigated patterns, determinants and demographic consequences of herbivory in A. petiolata. I found that patterns, determinants and demographic consequences of herbivory may vary between life stages and habitat types. One striking finding was that herbivory incidence in A. petiolata may strongly depend on plant life stage, possibly due to a defense–fitness trade off. In chapter 5, I tested whether intra-specific interactions in A. petiolata shift with temporal environmental heterogeneity (seasonality). I found significant negative density-dependent survival in summer and positive density-dependent survival over winter. I suggested that predictions of the stress gradient hypothesis at the intra-specific level are applicable to seasonal variation in environmental stress.

The dynamics of ecological populations and communities are predominantly governed by three ecological processes, environmental filtering, species interactions and dispersal, and these processes may vary with heterogeneity of the environment. In my PhD research, I investigated how ecologists conceptualize landscape heterogeneity, and how these three ecological processes may vary with spatial and temporal environmental heterogeneity. I conducted my empirical work in Alliaria petiolata, a non-native invasive species in North America, at the Koffler Scientific Reserve at Joker’s Hill in Ontario, Canada. The thesis contains six chapters, where chapters 2 – 5 are structured as stand-alone manuscripts. In chapter 2, I conducted a quantitative review to link the metacommunity concept (which combines the above-mentioned three processes) with different conceptual models of landscape spatial heterogeneity. I found that 78% of metacommunity studies were not explicit about the underlying model of landscape heterogeneity, though there was a significant association between the implied model of landscape heterogeneity and the observed metacommunity model. In chapter 3, I quantified dispersal of Alliaria petiolata, assessed the spatial structure of rosette and adult density, and compared the effects of the different processes on rosette and adult density. Seed dispersal followed a lognormal distribution (μ = 0.01, σ = 0.65). Both adults and rosettes exhibited significant spatial structure up to 2 m. Propagule pressure and interactions among life stages were significant processes shaping rosette density, whereas propagule pressure was the only important process shaping adult density. In chapter 4, I investigated patterns, determinants and demographic consequences of herbivory in A. petiolata. I found that patterns, determinants and demographic consequences of herbivory may vary between life stages and habitat types. One striking finding was that herbivory incidence in A. petiolata may strongly depend on plant life stage, possibly due to a defense–fitness trade off. In chapter 5, I tested whether intra-specific interactions in A. petiolata shift with temporal environmental heterogeneity (seasonality). I found significant negative density-dependent survival in summer and positive density-dependent survival over winter. I suggested that predictions of the stress gradient hypothesis at the intra-specific level are applicable to seasonal variation in environmental stress.

It has been argued that organic farming sustains a higher biodiversity than conventional farming. This might promote the ecosystem services that exist in agricultural landscapes such as pollination and pest control. Here, I examined the effect of farming system (organic vs. conventional) with respect to the time since farming system transition, landscape heterogeneity and plant richness on pollinating and predatory insects. In total, data from 30 farms were used, of which 20 were organic and 10 were conventional. The data were analyzed using general linear models and model averaging. The results show that insect groups responded differently to various factors. Pollinators were more sensitive to landscape complexity, showing an increase of abundance and species richness with an increased heterogeneity. Predators on the other hand reacted to farming system, where there was an increase in abundance and species richness on organic farms.

The recent increase in large fires in southwestern forests has prompted concern regarding their ecological consequences. Recognizing the importance of spatial patterns in influencing successional processes, I asked: (1) How do large fires change plant communities?; (2) What are the implications of these changes for ponderosa pine forests?; and (3) What is the relationship of fire severity to gradients of climate, fuels, and topography? To address the first two questions, I studied succession in the woody plant community at two sites that burned in high-severity fire: La Mesa fire in northern New Mexico (1977) and Saddle Mountain in northern Arizona (1960). After large fires, abiotic conditions, associated prefire plant distributions, and spatial patterns of burning interacted to result in particular successional outcomes. Variation in abundance and diversity of species that spread from a refuge of seed sources remaining after the fire followed the model of wave-form succession. I investigated the implications of large fires for ponderosa pine by examining the influence of spatial patterns of burning on regeneration. Tree density corresponded most closely with particular scales of seed dispersal kernel and neighborhood severity metrics. Spatial patterns of burning remained influential even after consideration of variables describing subsequent burning and the physical and biotic environment. Age structure of young forests indicated that populations spread in a moving front and by long-distance dispersal. To explore the relationship between fire severity and climate, I investigated how the spatial heterogeneity of high-severity patches varied among 20 fires across gradients in fire size and climate. The largest fires generally occurred during cool dry La Niña climates, however, several fires deviated from this trend. Some spatial properties of severity did not correspond to fire size or to changes in climate. Characteristics of fuels and topography altered spatial patterns of severity, but interactions with extreme burning conditions may have disrupted these local influences in both La Niña and El Niño fires. Spatial patterns of fire severity are central to understanding ecological dynamics following large fires in southwestern forests. Moreover, simplistic assumptions regarding the relation of fire severity to fire size and climate should be viewed with caution.

I studied habitat preferences of three common endemic butterflies in the Bamenda Highlands, Cameroon. Assuming that the life history traits of taxa with limited geographic distribution reflect past habitat conditions within their ranges, the history and conservation of West African mountain landscape is discussed.

Landscapes are inherently heterogeneous. However, some portions of a landscape are more heterogeneous than others and are therefore not equally suitable for resource extraction by elephants. Elephants have large energy demands to meet and should spend the majority of their time in areas where they are able to forage optimally. Identifying the determinants of home range location and area may therefore provide insight into aspects of landscape utilization by elephants. Using vegetation structure as a surrogate, I investigated whether landscape heterogeneity explains the variability home range size and location of elephants occurring in the mesic savannas of Zambia and Malawi. I developed a landscape map for each of five study areas. Using these maps, I applied four FRAGSTATS metrics to quantify different aspects of landscape heterogeneity within the study areas, as well as elephant home ranges and randomly located ranges delineated using a 95% Kernel estimation. I placed similar study areas into comparable groups for each of the landscape heterogeneity metrics. Elephant home range size was not a function of landscape heterogeneity metrics and may therefore be explained by other factors. Landscape complexity and diversity of elephant home ranges varied within groups of similar study areas, suggesting that these metrics were important descriptors of home range location. Within study areas, with the exception of patch density, landscape heterogeneity metrics supported the expectation that wet season ranges would be more heterogeneous than those of the dry season. In addition, female ranges were more heterogeneous than those of males during the wet seasons with respect to both patch density and landscape diversity. In most cases, greater landscape heterogeneity within home ranges was only shown during the wet season and this suggests that water requirements preclude selection for more heterogeneous landscapes during the dry season. However, elephants of the Zambian study areas, besides Kafue, selected for metrics indicative of landscape complexity and diversity during both dry and wet seasons. I therefore concluded that elephants favoured complex landscapes with more vegetation types in irregularly arranged patches and landscape heterogeneity therefore determines the location of elephant home ranges. At a regional scale, a landscape comprises habitats of varying suitability to elephants. In a metapopulation framework, such areas may form sources or sinks and therefore contribute to driving elephant movements. The ability to identify areas of importance to elephant range utilization is therefore an essential tool to apply within the megaparks for metapopulations conservation framework. / Dissertation (MSc (Zoology))--University of Pretoria, 2007. / Zoology and Entomology / unrestricted