No description available.

Invasive weeds inflict significant harm on native species, ecosystem processes, and natural disturbance regimes. When managing these weed threats, some of the most useful tools are the outputs of predictive distribution models. As they supplement existing distribution data to assess where in the landscape is most susceptible to weed invasion, they allow for more efficient weed management because the areas most suited to weed species may be targeted for control. This research develops a habitat suitability model for the weed lantana (Lantana camara L. sensu lato) in a portion of the Greater Blue Mountains World Heritage Area at present and under forecast warmer climates. A generalised additive model (GAM) is used, which fits the regression curve used for prediction to the calibration data themselves and allows for an exploration of which environmental conditions favour lantana as well as where in the landscape is most suitable for the weed. Temperature was positively correlated with suitable habitat and explained over 90% of the variation in lantana presence predicted by the model. 15% of the study area was found to be suitable for lantana at present, with this figure reaching 58% after a simulated 3??C rise in temperature. Mapping habitat suitability across the study area allowed for the identification of five distinct pathways for lantana to further invade the Blue Mountains. Responding to calls for the integration of weed management with biodiversity conservation, the research also integrates the habitat suitability model with information regarding the distribution of vegetation communities and endangered species in the Blue Mountains. Thirteen native vegetation communities were found to have more than 20% suitable habitat for lantana at present, and an additional three contained more than 80% suitable habitat after a simulated 3??C rise in temperature. Five of these communities are listed as threatened under relevant legislation and harbour at least 27 endangered species, placing additional urgency on their conservation. This research has successfully used modelling techniques to identify areas for targeted weed management integrated with biodiversity conservation. The methods are easily adaptable to other weeds and regions and could thus be used to illustrate the comprehensive threat weeds pose to Australia???s biodiversity.

Invasive weeds inflict significant harm on native species, ecosystem processes, and natural disturbance regimes. When managing these weed threats, some of the most useful tools are the outputs of predictive distribution models. As they supplement existing distribution data to assess where in the landscape is most susceptible to weed invasion, they allow for more efficient weed management because the areas most suited to weed species may be targeted for control. This research develops a habitat suitability model for the weed lantana (Lantana camara L. sensu lato) in a portion of the Greater Blue Mountains World Heritage Area at present and under forecast warmer climates. A generalised additive model (GAM) is used, which fits the regression curve used for prediction to the calibration data themselves and allows for an exploration of which environmental conditions favour lantana as well as where in the landscape is most suitable for the weed. Temperature was positively correlated with suitable habitat and explained over 90% of the variation in lantana presence predicted by the model. 15% of the study area was found to be suitable for lantana at present, with this figure reaching 58% after a simulated 3??C rise in temperature. Mapping habitat suitability across the study area allowed for the identification of five distinct pathways for lantana to further invade the Blue Mountains. Responding to calls for the integration of weed management with biodiversity conservation, the research also integrates the habitat suitability model with information regarding the distribution of vegetation communities and endangered species in the Blue Mountains. Thirteen native vegetation communities were found to have more than 20% suitable habitat for lantana at present, and an additional three contained more than 80% suitable habitat after a simulated 3??C rise in temperature. Five of these communities are listed as threatened under relevant legislation and harbour at least 27 endangered species, placing additional urgency on their conservation. This research has successfully used modelling techniques to identify areas for targeted weed management integrated with biodiversity conservation. The methods are easily adaptable to other weeds and regions and could thus be used to illustrate the comprehensive threat weeds pose to Australia???s biodiversity.

Invasive weeds inflict significant harm on native species, ecosystem processes, and natural disturbance regimes. When managing these weed threats, some of the most useful tools are the outputs of predictive distribution models. As they supplement existing distribution data to assess where in the landscape is most susceptible to weed invasion, they allow for more efficient weed management because the areas most suited to weed species may be targeted for control. This research develops a habitat suitability model for the weed lantana (Lantana camara L. sensu lato) in a portion of the Greater Blue Mountains World Heritage Area at present and under forecast warmer climates. A generalised additive model (GAM) is used, which fits the regression curve used for prediction to the calibration data themselves and allows for an exploration of which environmental conditions favour lantana as well as where in the landscape is most suitable for the weed. Temperature was positively correlated with suitable habitat and explained over 90% of the variation in lantana presence predicted by the model. 15% of the study area was found to be suitable for lantana at present, with this figure reaching 58% after a simulated 3??C rise in temperature. Mapping habitat suitability across the study area allowed for the identification of five distinct pathways for lantana to further invade the Blue Mountains. Responding to calls for the integration of weed management with biodiversity conservation, the research also integrates the habitat suitability model with information regarding the distribution of vegetation communities and endangered species in the Blue Mountains. Thirteen native vegetation communities were found to have more than 20% suitable habitat for lantana at present, and an additional three contained more than 80% suitable habitat after a simulated 3??C rise in temperature. Five of these communities are listed as threatened under relevant legislation and harbour at least 27 endangered species, placing additional urgency on their conservation. This research has successfully used modelling techniques to identify areas for targeted weed management integrated with biodiversity conservation. The methods are easily adaptable to other weeds and regions and could thus be used to illustrate the comprehensive threat weeds pose to Australia???s biodiversity.

Medical cartography can provide valuable insights into the epidemiology and ecology of infectious diseases, providing a quantitative representation of the distribution of these pathogens. Such methods therefore provide a key step in informing public health policy decisions ranging from prioritising sites for further investigation to identifying targets for interventions. By increasing the resolution at which risk is defined, policymakers are provided with an increasingly informed approach for considering next steps as well as evaluating past progress. In spite of their benefits however, global maps of infectious disease are lacking in both quality and comprehensiveness. This thesis sets out to investigate the next steps for medical cartography and details the use of species distribution models in evaluating global distributions of a variety of zoonotic diseases of public health importance. Chapter 2 defines a methodology by which global targets for infectious disease mapping can be quantitatively assessed by comparing the global burden of each disease with the demand from national policymakers, non-governmental organisations and academic communities for global assessments of disease distribution. Chapter 3 introduces the use of boosted regression trees for mapping the distribution of a group of vector-borne diseases identified as being a high priority target, the leishmaniases. Chapter 4 adapts these approaches to consider Ebola virus disease. This technique shows that the West African outbreak was ecologically consistent with past infections and suggests a much wider area of risk than previously considered. Chapter 5 investigates Marburg virus disease and considers the variety of different factors relating to all aspects of the transmission cycle that must be considered in these analyses. Chapters 6 and 7 complete the mapping of the suite of viral haemorrhagic fevers by assessing the distribution of Crimean-Congo haemorrhagic fever and Lassa fever. Finally, Chapter 8 considers the risk that these viral haemorrhagic fevers present to the wider African continent, quantifying potential risk of spillover infections, local outbreaks and more widespread infection. This thesis addresses important information gaps in global knowledge of a number of pathogens of public health importance. In doing so, this work provides a template for considering the global distribution of a number of other zoonotic diseases.

Conservation of biodiversity and sustainable resource use are central aims within ecology. This thesis focuses on the current data and environmental frameworks used to support these aims across different states in Europe. In particular, it examines the impact of geo-political boundaries on data-use, funding and planning for temporal movement of species in response to climate change. It also examines the current environmental framework agreements in Europe and their capacity to deal with trans-boundary aspects of biodiversity change. Through examination of European biodiversity datasets, undertaking species distribution modelling of forest taxa, examining economic data, palaeo-ecological data, and assessing international environmental framework agreements, this thesis identifies a number of important knowledge gaps. Probably unsurprisingly, the distribution of biodiversity in Europe mostly does not match political entities, all of which have individual aims, financial resources, and biodiversity management regimes in place. All have a significant impact on biodiversity conservation planning because i) the use of geo-politically truncated data influences modelling predictions, ii) financial commitment to biodiversity conservation varies between countries influencing success outcomes, iii) biodiversity persistence in current and future climate change does not recognise geo-political boundaries, and iv) many of the key environmental frameworks are implemented within countries and do not considering trans-boundary issues. Overall these findings significantly improve the understanding of conservation and resource management in Europe and fill a number of important knowledge gaps. They highlight the importance of appropriate trans-boundary ecological datasets and the need for more consistency across Europe in financial resources for biodiversity conservation. They also highlight the need for appreciation of areas of high-persistent biodiversity regardless of geo-political boundaries and environmental framework agreements that support cross-border conservation measures.

Biodiversity is a complex concept incorporating genes, species, ecosystems, composition, structure and function. The global scientific and political community has recognized the importance of biodiversity for human well-being, and has set goals and targets for its conservation, sustainable use, and benefit sharing. Monitoring biodiversity will help meet conservation goals and targets, yet observations collected in-situ are limited in space and time, which may bias interpretations and hinder conservation. Remote sensing can provide complementary datasets for monitoring biodiversity that are spatially comprehensive and repeatable. However, further research is needed to demonstrate, for various spatial scales and regions, how remotely sensed datasets represent different aspects of biodiversity. The overall goal of this dissertation is to advance the mapping and monitoring of biodiversity indicators, globally and within Canada, through the use of remote sensing. This research produced maps that were rich with spatially explicit, spatially continuous data, filling gaps in the availability and spatial resolution or scalability of information regarding ecosystem function (primary productivity) at global scales, tree species composition at regional scales (Saskatchewan, Canada), and ecosystem structure at local scales (coastal British Columbia, Canada). Further, the remotely sensed indicator datasets proposed and tested in each of the research chapters are repeatable, ecologically meaningful, translate to specific biodiversity targets globally and within Canada, and are calculable at multiple spatial scales. Challenges and opportunities for fully implementing these or similar remotely sensed biodiversity indicators and indicator datasets at a national level in Canada are discussed, contributing to the advancement of biodiversity monitoring science. / Graduate

Thesis (PhD)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: Large-scale human-mediated movements of organisms promote the establishment of species outside their native ranges and a very small proportion of these species become invasive. Invasive species management typically assumes that introduced species are single, static evolutionary units that are genetically analogous to their native counterparts. However, studies have shown that native and introduced populations of a number of introduced plants differ vastly in their genetic composition. These differences may negatively affect the overall success of control and management programmes, particularly for species that are intra-specifically diverse. The influence of intra-specific diversity on the invasion process was tested in two widely exported tree species that are native to Western Australia, Acacia saligna (three subspecies) and Paraserianthes lophantha (two subspecies). Climate matching between the native and introduced range (using species distribution models, SDM) is widely used to forecast future invasion risks, however, it is unknown if SDMs can detect intra-specific niche differences in invasive plants. The SDMs I developed for the subspecies of A. saligna detected intra-specific differences within the native range, but did not predict the full invasive distribution in South Africa. Unsurprisingly, SDMs agreed with genetic analyses (based on nuclear microsatellites, nuclear DNA, and chloroplast DNA) and did not assign South African populations to any subspecies of A. saligna. South African populations were assigned to a novel genetic entity likely produced by human cultivation practices. A global phylogeny identified this cultivated genotype in introduced populations in eastern Australia and Portugal, while the remaining introduced populations differed markedly in their genetic composition. Overall, A. saligna‘s high intra-specific diversity and complex introduction history generated a variety of genetic patterns across the current global distribution of the taxon. Global populations of P. lophantha were processed using a similar approach to that used for A. saligna, and aimed to determine if the same pathways and modes of introduction produced analogous genetic patterns in a closely related species. Diverse arrays of genotypes were identified in introduced populations of P. lophantha, suggesting inconsistent sampling of a variety of native sources. Further work is however needed to clarify the morphological and genetic differences (if any) between the intra-specific entities, and identify exactly which P. lophantha subspecies were introduced outside of their native range, The variation in the global distribution of genetic diversity observed in A. saligna and P.lophantha demonstrated that intra-specific genetic variation, human usage, and the pathway and manner of introduction interact during several phases of the invasion process and collectively determine the introduced genetic patterns. The dissimilarity in the distribution of genotypes in both species suggests that they might not behave the same way throughout their introduced range. Consequently, management insights might not be transferrable between regions. More generally, my findings provide an important contribution to the debate whether (and how quickly) introduced and native populations should be treated as fundamentally different entities. / AFRIKAANSE OPSOMMING: Grootskaalse menslike verskuiwing van organismes bevorder die vestiging van spesies buite hul natuurlike voorkomsareas en 'n klein hoeveelheid van hierdie spesies word indringers. Tydens die bestuur van indringerspesies word dit tipies aanvaar dat ingevoerde indringerspesies enkele, statiese evolusionêre eenhede is wat analoog is aan hul inhmeemse eweknieë. Studies het egter getoon dat inheemse en uitheemse populasies van 'n aantal ingevoerde plante aansienlik verskil in hul genetiese samestelling. Hierdie verskille kan 'n negatiewe invloed op die algehele sukses van beheer- en bestuursprojekte hê, veral vir die spesies wat intra-spesifiek divers is. Die invloed van intra-spesifieke diversiteit op die indringingsproses is getoets aan twee boomspesies, inheems aan Wes-Australië, wat wyd uitgevoer word: Acacia saligna (drie subspesies) en Paraserianthes lophantha (twee subspesies). Vergelyking van klimaatstoestande tussen n spesie se in- en uitheemse voorkomsareas word wyd gebruik om toekomstige indringingsrisiko te voorspel. Dit was voor hierdie navorsing onduidelik of spesie verspreiding modelle (SVMs) intra-spesifieke nis-verskille in indringerplante kan uitwys. SVMs wat vir die subspesies van A. saligna ontwikkel is, kon intra-spesifieke verskille in Wes-Australië uitwys, maar het nie die volle verspreiding van die spesies in Suid-Afrika voorspel nie. Onverbasend, is geen Suid-Afrikaanse populasies deur genetiese analise (gebaseer op die kern mikrosatelliete, kern-DNS, en chloroplas-DNS) toegewys aan 'n subspesie van A. Saligna nie. Suid-Afrikaanse populasies het 'n nuwe genetiese entiteit wat waarskynlik gekweek is deur menslike verbouingspraktyke. 'n Globale filogenie het hierdie verboude genotipe in addisionele ingevoerde populasies in die ooste van Australië en Portugal geïdentifiseer. Mikrosatelliet genotipes van uitheemse populasies wêreldwyd in Oos-Australië, Israel, Italië, Nieu-Seeland, Portugal, Suid-Afrika, Spanje en die VSA verskil merkbaar in hul genetiese samestelling. A. saligna se hoë intra-spesifieke diversiteit en komplekse geskiedenis van invoer (wat verbouing, wye verspreiding en hoë ―propagule druk betrek), het 'n verskeidenheid van genetiese patrone oor die huidige globale verspreiding van die takson gegenereer. Om te bepaal of 'n globale uiteenlopende genetiese patroon binne nouverwante spesies bestaan, is globale bevolkings van Paraserianthes lophantha verwerk deur gebruik te maak van 'n soortgelyke benadering as wat vir A. saligna gebruik is. Globale populasies van beide studie-spesies bestaan uit 'n diverse verskeidenheid van genotipes. Resultate dui daarop dat P. lophantha van 'n verskeidenheid inheemse bronne ingevoer is. Om te identifiseer watter P. lophantha subspesies buite hul natuurlike voorkomsarea versprei is, word verdere werk benodig om die morfologiese en genetiese verskille (indien enige) tussen die intra-spesifieke entiteite vas te stel. In hierdie tesis het ek gewys dat intra-spesifieke genetiese variasie, menslike gebruik en invoering-geskiedenis saam werk om genetiese patrone in uitheemse populasies te vorm. Verder het ek die waarde van die gebruik van verskillende molekulêre benaderings om indringing geskiedenis te verstaan, gedemonstreer. Die verskil in die verspreiding van die genotipes van A. saligna en P. lophantha dui daarop dat hulle moontlik nie op dieselfde manier dwarsdeur hul uitheemse verspreidingsarea mag optree nie. Bestuursinsigte mag gevolglik nie oordraagbaar wees tussen streke nie. Meer algemeen, bied my bevindings 'n belangrike bydrae tot die debat of (en hoe vinnig) inheemse en ingevoerde populasies behandel moet word as fundamenteel verskillende entiteite.

In this thesis, I have assessed and modelled invasion of alien plant species in the forest of the southeastern United States. There are over 380 recognized invasive plants in southeastern forests and grasslands with 53 ranked as high-to-medium risk to natural communities. I have focused on ten of these: Chinese lespedeza, tall fescue, Japanese honeysuckle, Chinese privet, autumn olive, princesstree, silktree, chinaberry, tree of heaven, tallowtree. Assessing them at differing scales, locally (Chapter 2 and 3), eco-regionally (Chapter 4 and 5) and regionally (Chapters 6 and 7), using field based measurements integrated with remotely sensed and digital datasets, and applying both parametric and non-parametric modelling approaches. Data from field based measurements as well as digitally available sources was evaluated, bringing together freely available data with time consuming, intensively collected data. Once models were developed application to assessing long term impacts was done by integrating potential climate change scenarios. At the local level Chinese lespedeza and Japanese Honeysuckle were the most prevalent, with models at the local level dominated by remotely sensed variables. At an eco-regional level Japanese honeysuckle was the most prevalent with models primarily dominated by environmental variables. At a regional level, where only trees were assessed, potential distributions of the invasive species ranged from 12 to 33 percent of the southeastern forests under current conditions with this dramatically increasing for chinaberry and tallowtree under most climate change scenarios, up as high as 66 percent of southeastern forest sites. In this thesis information on anthropogenic factors added some value to the models, however it was rarely dominant. Roads and land use (proportion of forest or distance to forest) were the most useful anthropogenic variables. In all models evaluated, only six times did any one anthropogenic variable represent more than 25 percent of the models, four of these were at the local scale. At the regional and eco-regional level, roads had a greater than 25 percent contribution to the silktree models, at a local level, distance to forest and distance roads contributed more than 25 percent to three of the species evaluated, sawtooth oak, Japanese honeysuckle and privet. Human activities have the most influence on invasion progression through dispersal (movement and introduction rate) and disturbance of the landscape (increased resource availability). Anthropogenic variables such as roads are likely to be a mechanism of spread, thus the more a model is driven by anthropogenic variables, the more likely the invasive plant is to be in the early stages of invasion process. Thus our results suggest that many of these species have moved through the first stages of invasion. Environmental characteristics play an important role in determining a site’s vulnerability to invasion. At an eco-region and regional scale, environmental characteristics dominated (>50%) all but one model (silktree at the regional scale). At the eco-region level elevation was the dominant variable, and at a regional level minimum temperature was the dominant variable. These have some correlation, with higher elevation often relating to lower temperatures, particularly at a smaller scale. This confirms the validity of matching the climate ranges of native species with the range of potential invasion, and the approach of integrating elevation, latitude and longitude to estimate potential distribution. It also suggests that climate change will influence the distribution and that variation in climate should be integrated into models. Two different modelling approaches, logistic regression and maximum entropy, were used throughout my thesis, and applied to the same data. Agreement between different modelling types adds strength to conclusions, while disagreement can assist in asking further questions. The inclusion in the models of similar variables with the same direction of relationships gives confidence to any inference about the importance of these variables. The geographical agreement between models adds confidence to the probability of occurrence in the area. Alternatively using the same model but different datasets can give you similar information. Overall for all models created by both logistic regression and MaxEnt, the logistic regression had slightly better omission rates and the MaxEnt model had better AUC’s. Logistic regression models also often predicted larger geographical areas of occurrences when the threshold of maximum sensitivity plus specificity was used, thus the lower omission rates is related to the less stringent model that predicts a larger area. The selection of appropriate data to answer the question was shown to be fundamental in Chapter 7. When data were used outside of the area of interest it generalized the models and increased the potential for invasion significantly. There was more value in the intensive surveyed data but this was less dramatic than in using the defined areas of interest to select the data for models.

This research project has investigated the mechanical behaviour of artificial turf surface systems used for sports under a range of real player movements, and the contribution of component layers to the overall system response by developing advanced measurement systems and methods. Artificial turf surface systems are comprised of a number of different materials and commonly with several layers, all of which contribute to their composite behaviour. During sports movements a player loads the surface, resulting in deformation that can change the surface behaviour, which in turn modifies the player biomechanical response. Improving the understanding of surface response to actual player loading is important for developing enhanced products for improving play performance. Likewise, by improving knowledge of surface effects on players, the understanding of injury risk can be improved. However, there is currently no published research to measure and analyse the behaviour of artificial turf system during real player locomotion. This research was undertaken to address this current lack of knowledge within the interaction between player and sports surface regarding the effects of player loading on the mechanical behaviour of artificial turf systems. In addition to support player loading regime, mechanical behaviour of hockey and third generation artificial turf surface systems and their component shockpad layers (a rubber shreds bonded shockpad and a polyurethane foam shockpad) was examined through dynamic cyclic compressive loading using an advanced material testing machine in laboratory environment. Each layer and carpet-shockpad system was subjected to controlled loading designed with previous biomechanical data at various loading frequencies (0.9 Hz, 3.3 Hz and 10 Hz) and under two different contact areas (50 mm and 125 mm diameter) to simulate aspects of player walking, running and sprinting. All layers and surface systems tested showed nonlinear stress-strain behaviour with hysteresis. Increasing the contact area resulted in reduced surface vertical deflection and more linear response. Increasing the loading frequency led to stiffer response in the lower stress range (< 400 kPa) for all surface systems. The third generation artificial turf systems showed also an increase in stiffness at higher stress range ( > 600 kPa) and a decrease in maximum strain as the loading frequency increased. Hysteresis loops obtained at different loading frequencies indicated that the amount of energy lost at the same peak load of 1900 N in each surface system decreased with an increase in loading rate. Player loading regime was performed to quantify the load/stress and the resulting surface deformation/strain under subject loading. Measurement systems including motion capture system, force plate and high speed were developed to characterise the response behaviour in a novel way. The mechanical behaviour of artificial turf surface systems under three player movement patterns (heel-toe walking, forefoot running and forefoot single leg landing) was measured. Boot-surface contact area of each movement varied during the stance. The heel-toe walking results indicated that the maximum applied stress and surface strain occurred in very early stance (first 10%) when the boot-surface contact area was small. For forefoot running and landing, the peak surface strain occurred around mid-stance concurrent with the time of peak applied stress. The maximum strain measured under running was smaller than under landing. A thin-film pressure sensing mat was used in both mechanical and player loading regimes and proved to be a useful tool for evaluating the pressure distributions and contact areas at different interfaces of the surface system. The applied stress on surface was observed to greatly reduce with depth over increasing contact area through the surface systems. Although the average pressure was reduced, pressure distribution contour showed directly under the surface load area the pressure at depth was still relatively large and that outside of this area the pressure was much lower. A comparison of the mechanical behaviour of artificial turf systems in terms of compressive strain, modulus of elasticity, stress distribution and energy loss under mechanical and player loading was evaluated. Key loading parameters in different loading regimes and their influence on surface system response were determined. The structure and material intrinsic properties of shockpad were considered to further explain the observed surface system behaviour. Two mathematical models were used to fit through the experimental data and found to be able to describe the loading behaviour. A breakthrough in understanding of the effects of real player loading on the mechanical behaviour response of artificial turf systems, and the contribution of the components to the whole system response has been achieved through the development of advanced measurement techniques.