Bacillus anthracis is the causal agent of anthrax which primarily affects ungulates, occasionally carnivores and less frequently humans. The endospores of this soil-borne bacterium are highly resistant to extreme conditions, and under ideal conditions, anthrax spores can survive for many years in the soil. The bacterium is generally found in soil at sites where infected animals have died. When these spores are exposed, they have the potential to be ingested by a mammalian species which could lead to an anthrax outbreak. Anthrax is almost never transmitted directly from host to host, but is rather ingested by herbivores while drinking, grazing or browsing in a contaminated environment, with the exception of scavengers and carnivores consuming infected prey. Anthrax is known to be endemic in the northern part of Kruger National Park (KNP) in South Africa (SA), with occasional epidemics spreading southward into the non-endemic areas. The aim of this study is to identify and map areas that are ecologically suitable for the harbouring of B. anthracis spores within the KNP. Anthrax surveillance data and selected environmental variables were used as inputs to the maximum entropy (Maxent) species distribution modelling method. Five-hundred and ninety-seven anthrax occurrence records, dating from the year 1988 to 2011, were extracted from the Skukuza State Veterinary Office’s database. A total of 40 environmental variables were used and their relative contribution to predicting suitability for anthrax occurrence was evaluated using Maxent software (version 3.3.3k). Variables showing the highest gain were then used for subsequent, refined model iterations until the final model parameters were established. The environmental variables that contributed the most to the occurrence of anthrax were soil type, normalized difference vegetation index (NDVI), land type and precipitation. A map was created using a geographic information system (GIS) that illustrates the sites where anthrax spores are most likely to occur throughout the Park. This included the known endemic Pafuri region as well as the low lying soils along the Shingwedzi-Phugwane-Bubube rivers and the Letaba-Olifants river drainage area. The outputs of this study could guide future targeted surveillance efforts to focus on areas predicted to be highly suitable for anthrax, especially since the KNP uses passive surveillance to detect anthrax outbreaks. Knowing where to look can improve sampling efficiency and lead to increased understanding of the ecology of anthrax within the KNP. / Dissertation (MMedVet)--University of Pretoria, 2013. / Production Animal Studies / unrestricted

La mise en place d'objectifs de conservation adéquats repose sur la définition d'états de référence appropriés pour la distribution et l'abondance des espèces. Cependant, l'étendue des impacts cumulés de l'homme sur les écosystèmes est aujourd'hui largement sous-estimée. Dans ce projet, je m'intéresse aux opportunités qu'offre l'utilisation de données historiques combinées à différentes méthodes analytiques pour définir ces états de référence ainsi qu'aux défis posés par ce type d'approche. Des données de présence ont été recueillies pour sept espèces de cétacés et trois espèces de pinnipèdes à partir de sources archéologiques, historiques et industrielles, révélant des réductions dans la distribution et l'abondance des espèces depuis la préhistoire à nos jours. Des modèles de distribution d'espèces ont été développés pour cinq espèces de cétacés, combinant des données de chasse baleinière du 19ème siècle à des variables environnementales afin d'estimer la distribution historique des espèces avant qu'elles n'aient été chassées. J'ai obtenu pour la baleine franche de l'Atlantique Nord (Eubalena glacialis) une estimation détaillée de sa distribution et de son abondance avant qu'elle ne soit exploitée, en extrapolant des connaissances sur la distribution et l'abondance d'une espèce congénérique, la baleine franche du Pacifique Nord (E. japonica). Ces résultats suggèrent que la baleine franche de l'Atlantique Nord occupe une portion réduite de sa distribution historique, et que son abondance actuelle ne représente qu'une infime portion (<5%) de son abondance passée. Plus généralement, ces résultats soulignent l'importance de considérer des données historiques pour comprendre le niveau d'impact par l'homme sur les espèces, évaluer leur niveau de déplétion et renseigner leur potentiel de rétablissement dans l'avenir. / Relevant baselines on the historical distribution and abundance of species are needed to support appropriate conservation targets for depleted species, but the full scale of cumulative human impacts on ecosystems is highly underestimated. In this project, I investigated the challenges and opportunities of combining historical data with analytical methods to improve these historical baselines. Occurrence data from archaeological, historical and industrial sources were reviewed for seven cetacean and three pinniped species, revealing range contractions and population depletions from prehistorical times to today. For five whale species, I used species distribution modelling to combine 19th Century whaling records with environmental data, to estimate pre-whaling distributions. For the highly depleted North Atlantic right whale, (Eubalaena glacialis), I obtained a detailed estimate of pre-whaling distribution and abundance by inferring from the historical distribution and abundance of its congeneric North Pacific right whale (E. japonica). These results suggest that the North Atlantic right whale occupies a small fraction of its historical range and that its current population represents <5% of its historical abundance, with implications for the management, monitoring and conservation targets of this species. More generally, these results emphasize the utility of considering historical data to understand the extent to which species have been impacted by humans, assess their current level of depletion, and inform the options available for their future recovery.

The dissertation builds a bridge from the social-philosophical works of Hobbes, Rousseau, and Smith to current game theoretical models explaining social order to two empirical applications in a rural region of Guinea. The work focuses on the central role of natural resources for human societies and uses two empirical studies to test general hypotheses on the drivers of the sustainable exploitation and the equitable distribution of natural resources. The work strictly follows a quantitative empirical approach. After discussing the methodological foundations of statistical causal analysis in a first step, the various approaches are evaluated in a simulation study. Finally, the most successful of these approaches finds its application in the analysis of the empirical data, which was collected during field research in Guinea. In the observational study, socioeconomic data are combined with environmental data to model the influence of humans on the occurrence of wild species that are exploited for economic purposes in the study area. In the experimental study, socioeconomic data is linked to experimental data from a resource distribution game to identify factors affecting the people’s behavior when sharing a common natural resource. Both the exploitation of wild species and the sharing of a natural resource show that the social context is crucial for the understanding of human behavior, as postulated by Hobbes, Rousseau, and Smith: reputation, market integration, inequality and homogeneity of the population, as well as the salience of moral norms and property rights are essential dimensions. / Die Dissertation widmet sich der zentralen Rolle von natürlichen Ressourcen für menschliche Gesellschaften. Anhand zweier empirischer Studien werden allgemeine Hypothesen zu den Determinanten der nachhaltigen Ausbeutung und gerechten Verteilung von natürlichen Ressourcen getestet. Dabei wird in der Arbeit eine Brücke von den Werken der Sozialphilosophen Hobbes, Rousseau und Smith, über aktuelle spieltheoretische Modelle zur Erklärung sozialer Ordnung, hin zu zwei empirischen Anwendungen in einer ländlichen Region Guineas geschlagen. Die Arbeit folgt strikt einem empirischen quantitativen Ansatz. Nach der Erörterung der methodischen Grundlagen der statistischen Kausalanalyse werden die verschiedenen Ansätze im Rahmen einer Simulationsstudie evaluiert. Schließlich findet der erfolgreichste dieser Ansätze in der Auswertung der Daten, die bei der Feldforschung in Guinea erhoben wurden, Anwendung. In der Beobachtungsstudie werden sozioökonomische Daten mit ökologischen Daten verknüpft, um den Einfluss der Menschen auf das Vorkommen von wilden Arten, die zu ökonomischen Zwecken ausgebeutet werden, im Untersuchungsgebiet zu modellieren. In der Experimentalstudie werden sozioökonomische Daten mit Experimentaldaten aus einem Ressourcenverteilungsspiel verknüpft, um Faktoren zu identifizieren, welche sich auf das Verhalten von Menschen beim Teilen einer gemeinsamen natürlichen Ressource auswirken. Sowohl für die Ausbeutung der wilden Arten, wie auch für das gemeinsame Teilen einer natürlichen Ressource gilt, dass der soziale Kontext für das Verhalten der Menschen von großer Relevanz ist, wie von Hobbes, Rousseau und Smith postuliert: Reputation, Marktintegration, Ungleichheit und Homogenität der Bevölkerung sowie die Salienz moralischer Normen und Eigentumsrechte sind entscheidende Dimensionen.

Large-scale land-use change across the tropics has led to the decline of animal populations and their habitat. With large investments into mining, hydropower dams and industrial agriculture this trend is likely to continue. Consequently, there is a need for systematic land-use planning to set aside areas for protection and allocate scarce conservation funding effectively. Even though primates are relatively well studied, data-driven systematic planning is still rarely implemented. The overall aim of this dissertation was to investigate population parameters needed for evidence-based conservation planning for the critically endangered western chimpanzee (Pan troglodytes verus) in West Africa. To this end, I compiled density datasets covering the entire geographic range of this taxon from the IUCN SSC A.P.E.S. database and modeled chimpanzee densities as a function of 20 social-ecological variables. I found that western chimpanzees seemingly persist within three social-ecological configurations: rainforests with a low degree of anthropogenic threats, steep areas that are less likely to be developed and are harder to access by humans, and areas with a high prevalence of cultural taboos against hunting chimpanzees. The third configuration of reduced hunting pressure is not yet reflected in commonly implemented conservation interventions, suggesting a need for designing new approaches aimed at reducing the threat of hunting. Based on the modeled density distribution, I estimated that 52,811 (95% CI 17,577-96,564) western chimpanzees remain in West Africa, and identified areas of high conservation value to which conservation interventions should be targeted. These results can be used to inform the expansion of the protected area network in West Africa, to quantify the impact of planned industrial projects on western chimpanzees, and to guide the systematic allocation of conservation funding. In addition, this thesis highlights the unique position of taxon-specific databases of providing access to high-resolution data at the scale needed for conservation planning. Data-driven conservation planning has the potential to enable conservationists to respond more proactively to current and emerging threats, and ultimately improve conservation outcomes.

This dissertation presents research on the value of using different sources of data to explore the factors determining invasiveness of introduced species. The research draws upon the availability of data on the historical trial plantings of alien species and other sources. The focus of the study is on Australian Acacia species as a taxon introduced into southern Africa (Lesotho, South Africa and Swaziland). The first component of the study focused on understanding the factors determining introduction outcome of species in historical trial plantings and invasion success of Australian Acacia species using Species Distribution Models (SDMs) and classification tree techniques. SDMs were calibrated using the native range occurrence records (Australia) and were validated using results of 150 years of South African government forestry trial planting records and invaded range data from the Southern African Plant Invaders Atlas. To understand factors associated with survival (‘trial success’) or failure to survive (‘trial failure’) of species in historical trial plantings, classification and regression tree analysis was used. The results indicate climate as one of the factors that explains introduction and/or invasion success of Australian Acacia species in southern Africa. However, the results also indicate that for ‘trial failures’ there are factors other than climate that could have influenced the trial outcome. This study emphasizes the need to integrate data on whether the species has been recorded to be invasive elsewhere with climate matching for invasion risk assessment. The second component of the study focused on understanding the distribution patterns of Australian Acacia species that are not known as invasive in southern Africa. The specific aims were to determine which species still exist at previously recorded sites and determine the current invasion status. This was done by collating data from different sources that list species introduced into southern Africa and then conducting revisits. For the purpose of this study, revisits means conducting field surveys based on recorded occurrences of introduced species. The known occurrence data for species on the list were obtained from different data sources and various invasion biology experts. As it was not practical to do revisits for all species on the list, three ornamental species (Acacia floribunda, A. pendula and A. retinodes) were selected as part of the pilot study for the conducted revisits in this study. Acacia retinodes trees were not found during the revisits. The results provided data that could be used to characterize species based on the Blackburn et al., (2011) scheme. However, it is not clear whether observed Acacia pendula or A. floribunda trees will spread away from the sites hence the need to continuously monitor sites for spread. The methods used in this research establish a protocol for future work on conducting revisits at known localities of introduced species to determine their population dynamics and thereby characterize the species according to the scheme for management purposes. / Dissertation (MSc)--University of Pretoria, 2014. / National Research Foundation (NRF) / Zoology and Entomology / MSc (Zoology) / Unrestricted

The Nile monitor (Varanus niloticus) is a large, carnivorous lizard that has become a notorious invasive species in Florida, USA. Initially released in the 1980s from the pet trade, the species has since established at least three breeding populations and spread throughout much of southern Florida. While current control efforts have failed to eradicate V. niloticus, it is important to attain a better understanding of its invasive dynamics to guide and inform better control strategies. In this study, available georeferenced records of V. niloticus in Florida were compiled and linked to a habitat classification map to evaluate ecotype preferences. Factored with bioclimatic data, the regional spread of V. niloticus was modelled for contemporary and projected (i.e., in the year 2050) presence using Maxent and Mahalanobis Distance models. Study results indicate that V. niloticus maintains a strong presence in eastern Lee County on the southwestern coast. Populations in Palm Beach and Miami-Dade counties on the southeastern coast may be interconnected, contrary to current descriptions that they are separated from each another. Model forecasts of conditions for the year 2050 identify widespread expansion of V. niloticus in Florida, particularly northward with the establishment of a new population center in Pasco County in the western central peninsula. This is the first known modelling study of V. niloticus in Florida and identifies regions at greater risk for future population expansion.

No description available.

The genus Psilochalcis, of the Family Chalcididae, was originally described in 1905 by Kieffer. Mainly considered an Old-World taxon, the first North American Psilochalcis were not identified until 1981 by Grissell and Schauff. Little is known about the species distributions, biologies and ecological relationships of these parasitic wasps. This dissertation describes research conducted in central Utah setting arrays of Malaise traps in 4 different habitat types common to the Great Basin at three separate locations. A result of this sampling revealed a high abundance of multiple species of Psilochalcis wasps, particularly from one location and two habitat types. Chapter 1 describes three new species of Psilochalcis wasps namely; P. adenticulata Petersen, P. minuta Petersen, and P. quadratis Petersen. A review of all North American Psilochalcis species explains their distribution in Utah and throughout the surrounding western United States. A taxonomic key for all North American Psilochalcis species is given. Chapter 2 examines the seasonal abundance of P. minuta and P. quadratis and their associations with two common Great Basin habitat types. Both species show their highest abundance from late June through early August. Their peak abundance is shown to change dependent on the environmental conditions of temperature and precipitation. Psilochalcis minuta is significantly associated with pinyon/juniper (Pinus edulis or P. monophylla and Juniperus osteosperma) and P. quadratis is significantly associated with cheatgrass (Bromus tectorum). Chapter 3 describes the building of species distribution models for P. minuta and P. quadratis using a maximum entropy (Maxent) approach. Ten environmental variables were used to predict areas of optimal suitable habitat for each species. Multiple predicted sites were field sampled to test each model's effectiveness. Psilochalcis minuta occurred at nearly 90% of predicted sites, and P. quadratis occurred at 50% of predicted sites. Both species occurred at some non-predicted sites in other habitat types. Model analyses and field-testing results show the P. minuta model to be reliable in predicting areas of probable species occurrence, while the P. quadratis model is much less reliable in doing so. Aspect and fire disturbance show the highest percent contribution to both species' models. Slight differences in variable percent contribution between models suggest these species have sympatric distributions. Soil and slope are more important predictors of optimal suitable habitat for each species. Maintaining integrity between model predictions and field testing gave insights into other factors contributing to probable occurrence of Psilochalcis species.

Monitoring the heterogeneous aquatic environment such as the Stormwater Treatment Areas (STAs) located at the northeast of the Everglades is extremely important in understanding the land processes of the constructed wetland in its capacity to remove nutrient. Direct monitoring and measurements of ecosystem evolution and changing velocities at every single part of the STA are not always feasible. Integrated remote sensing, monitoring, and modeling technique can be a state-of-the-art tool to estimate the spatial and temporal distributions of flow velocity regimes and ecological functioning in such dynamic aquatic environments. In this presentation, comparison between four computational intelligence models including Extreme Learning Machine (ELM), Genetic Programming (GP) and Artificial Neural Network (ANN) models were organized to holistically assess the flow velocity and direction as well as ecosystem states within a vegetative wetland area. First the local sensor network was established using Acoustic Doppler Velocimeter (ADV). Utilizing the local sensor data along with the help of external driving forces parameters, trained models of ELM, GP and ANN were developed, calibrated, validated, and compared to select the best computational capacity of velocity prediction over time. Besides, seasonal images collected by French satellite Pleiades have been analyzed to address the seasonality effect of plant species evolution and biomass changes in the constructed wetland. The key finding of this research is to characterize the interactions between geophysical and geochemical processes in this wetland system based on ground-based monitoring sensors and satellite images to discover insight of hydraulic residence time, plant species variation, and water quality and improve the overall understanding of possible nutrient removal in this constructed wetland.

Aim: The abundances and distributions of some species are more closely matched to variations in climate than others. Species traits that might influence how well the distribution and abundance of a species are matched to climatic variation include life history (e.g., body size and dispersal ability), ecology (e.g., habitat specialization and territoriality) and demography (e.g., population size). Here, we used a survey of bird abundances across the USA to assess the extent to which species abundances and distributions are predicted by climate (i.e., climate matching) and how species traits relate to interspecific variation in climate matching. Location: USA. Time period: 1983–2018. Major taxa studied: Birds. Methods: Species abundances were obtained from the North American Breeding Bird Survey. Climate matching was estimated as the predictive performance of species–climate models fitted using boosted regression trees and generalized additive models and modelled as a function of species traits. Results: Species traits explained 56% of the variation in climate matching among species. Intermediate-sized species were more well matched to climate than smaller or larger species, as were species that lived primarily in forested compared with open habitats, species that were locally more abundant and species that were more territorial. Alternatively, species that were more specialized or had high variability in abundance among sites were less well matched to climate. We also found that species classified as “near threatened” were more well matched to climate, suggesting that these species might be more vulnerable to climate change. However, species classified as “vulnerable” were more decoupled from climate than those of “least concern”, possibly owing to ecological drift associated with progressive population declines. Main conclusions: Our findings provide an ecological basis for understanding the extent to which species abundances and distributions match broad climatic gradients, which can provide the groundwork to improve our ability to predict distributions under global change.