In recent years a push to establish pulpwood plantation forestry in Sarawak, East Malaysia with Acacia mangium has been identified as a means to relieve pressure on the State’s diminishing natural forest resource whilst providing 1) economic wealth for a developing economy 2) community development, and 3) biodiversity conservation outside the protected area network. In a specially designated 504,000 hectare Planted Forest Zone (PFZ) a range of broad-scale landscape planning initiatives have been implemented in an attempt to conserve a representative sample of biodiversity across the plantation landscape. The effects of forest modification and fragmentation have been widely reported in the literature for mammals, and in this study, non-volant small mammals were fitted with tracking spools and/or radio collars and released into small forest remnants outside of their home ranges to measure response to unfamiliar habitats, forest edges and various scales of habitat fragmentation during simulated dispersal events. Medium sized patches exhibited the greatest species diversity and abundance, whereas the largest forest areas hosted the largest population of brown spiny rat (Maxomys rajah); a species that is identified as vulnerable across its natural range. Small forest patches of c.1.00 ha that had been exempt from clearing during plantation establishment are likely to be species poor and host small populations of extant species only. All species were found to make extensive use of downed woody debris for movement, and showed varied responses to a range of habitat edges including forest roads, acacia plantation compartments, old haul trails, clearings and riparian areas. Two species of treeshrew; long-footed treeshrew (Tupaia longipes) and painted treeshrew (T. picta) were shown to be able to move between the forest patch and the acacia forest while the same edges were shown to pose barriers to the brown spiny rat (M. rajah) and large treeshew (T. tana) illustrating the different ways that species may perceive and use habitat features such as corridors. Despite T. picta being common in the PFZ, comparatively little has been published on its ecology and behaviour compared with the other Bornean tupaiids. Therefore this study also reports on the movement and behaviour of this species within its own home territory as revealed from both radio telemetry and spool-and-line tracking. Home range size, dimension, average daily movement distances and nest site construction was found to be similar to other Tupaiids studied in secondary forests in Sabah, and home ranges were found to be dictated by anthropogenic landscape features such as forest roads and open areas across which no movement was recorded. Painted treeshrews were found to favour logs and fallen woody debris as movement substrates and spend the large majority of their movement at ground level. Camera trapping revealed possible interspecific nest sharing between the painted treeshrew and the three-striped ground squirrel (Lariscus insignis), fuelling the debate on whether or not treeshrews construct their own nests or use nests constructed by squirrels.

Master of Science / Department of Electrical and Computer Engineering / William H. Hsu / Caterina M. Scoglio / Early detection of livestock diseases and development of cost optimal mitigation strategies are becoming a global necessity. Foot and Mouth Disease (FMD) is considered one of the most serious livestock diseases owing to its high rate of transmission and extreme economic consequences. Thus, it is imperative to improve parameterized mathematical models for predictive and preventive purposes. In this work, a meta-population based stochastic model is implemented to assess the FMD infection dynamics and to curb economic losses in countries with underdeveloped livestock disease surveillance databases. Our model predicts the spatio-temporal evolution of FMD over a weighted contact network where the weights are characterized by the effect of wind and movement of animals and humans. FMD incidence data from countries such as Turkey, Iran and Thailand are used to calibrate and validate our model, and the predictive performance of our model is compared with that of baseline models as well. Additionally, learning-based prediction models can be utilized to detect the time of onset of an epidemic outbreak. Such models are computationally simple and they may be trained to predict infection in the absence of background data representing the dynamics of disease transmission, which is otherwise necessary for predictions using spatio-temporal models. Thus, we comparatively study the predictive performance of our spatio-temporal against neural networks and autoregressive models. Also, Bayesian networks combined with Monte-Carlo simulations are used to determine the gold standard by approximation. Next, cost-effective mitigation strategies are simulated using the theoretical concept of infection network fragmentation. Based on the theoretical reduction in the total number of infected animals, several simulative mitigation strategies are proposed and their cost-effectiveness measures specified by the percentage reduction in the total number of infected animals per million US dollars, are also analyzed. We infer that the cost-effectiveness measures of mitigation strategies implemented using our spatio-temporal predictive model have a narrower range and higher granularity than those for mitigation strategies formulated using learning-based prediction models. Finally, we coin optimal mitigation strategies using Fuzzy Dominance Genetic Algorithms (FDGA). We use the concept of hierarchical fuzzy dominance to minimize the total number of infected animals, the direct cost incurred due to the implementation of mitigation strategies, the number of animals culled, and the number of animals vaccinated to mitigate an epidemic. This method has the potential to aid in economic policy development for countries that have lost their FMD-free status.

As drivers of biogeochemical cycles and nutrient recycling, such as carbon turnover, the microbial community is essential in sustaining functioning ecosystems. Together with the metazoan community, the microbial community constitute the majority of all life in the benthos. Environmental change in biotic and abiotic factors may influence the dynamics of these communities, for example through a sorting or driving effect on the community structure through assembly processes. Environmental change, e.g. change in dissolved oxygen concentration, salinity and temperature, can directly or indirectly affect community composition. How, in what way, and to what extent, benthic bacterial and meiofaunal community composition in the eutrophied, brackish benthic environments, in the Baltic Sea sub-basin the Baltic Proper, respond to environmental change is understudied, both at local and seascape scale. This thesis aimed to study and understand the effects of environmental variation on the diversity and biogeographic patterns of Baltic Sea sediment bacterial and meiofaunal communities. A further aim was to understand the links between the different community levels by studying the interaction between meiofaunal- and macrofaunal communities in relation to environmental variation. Community diversity was analysed along a latitudinal transect of national environmental monitoring stations in the Baltic Proper using a framework of metapopulation and metacommunity theory. The analyses were based on environmental genomics, with high-throughput sequencing, bioinformatics and statistics. The total community genome was analysed using phylogenetic marker gene fragments as a proxy for taxonomic diversity, to investigate diversity, community structure and dynamics. Salinity and oxygen were found to be the main abiotic environmental drivers of benthic community composition and alpha- and beta-diversity patterns. Furthermore, macrofauna-meiofauna interactions were significantly more complex in higher salinity environments. Results also showed that both enhanced environmental gradients and dispersal following a major inflow of saline and oxygenated water from the Atlantic Ocean, influenced the composition of sediment bacterial communities at the seascape scale of the Baltic Sea, as shown by a reduced beta-diversity and increased alpha-diversity, and the development of a significant distance-decay of community similarity. This study also identified strong metapopulation dynamics of the benthic sediment bacterial communities with many satellite and a few core taxa. The outcomes from this study contribute to the understanding of how environmental variation and environmental change relate to changes in Baltic Sea benthic community diversity and composition, and important factors and processes governing community dynamics.

MSc (Zoology) / Department of Zoology / Mopane worm (Gonimbrasia belina Westwood) is an indigenous edible insect that periodically has population eruptions in Mopane tree (Colosphermum mopane) dominated vegetation. This insect is a valuable source of food and has become an economic commodity for commercial harvesters. Despite its importance, little is known of the population dynamics of mopane worm. Considerable attention has been paid to the nutritional and social dimensions of mopane worm consumption. However, anecdotal evidence suggests there is a decline in the spatial extent of their distribution due to unsustainable utilization, land transformation, and commercialization. This is paralleled with a decrease of harvest yield, thereby affecting local communities, commercial harvesting operations, and market product availability. Partial domestication of this species may be a way of ensuring sustainable and reliable utilization of this edible insect because it improves natural survival rates. Here I explore mopane worm ecology by mainly focusing on understanding spatial structuring and the role of domestication in the development of sustainable harvest techniques of Mopane worms (G. belina). Spatial structuring of mopane worms was investigated at both a fine (10m x 10m) and medium-scale (1 km2) at sites with and without commercial harvesting. Mopane worm populations were experimentally treated through transplant experiments and manipulating access of predators to 1st – 3rd instar larvae. The role of tree characteristics (height, canopy volume and number of stems) on both spatial and experimental treatments were explored using generalized linear mixed models. Moran’s Eigenvector Maps (MEM’s) were used to represent spatial structures at various scales and the role of soil. Relative to control, seeding of worms was successful in establishing new populations in unoccupied areas while transplant and application of sleeve nets had no significant effect on larval survival. Populations at sites where no harvesting takes place were spatially structured, while this was not true where commercial harvesting takes place. Canopy volume also accounted for egg packets distribution although the relationship was ambiguous. The density of larvae increased with an increase in sodium concentration in soil. Seeding of the population provides a viable option for the sustainable utilization of mopane worms and educating people on how to domesticate mopane worms. This study also highlights that populations of mopane worms are not only clumped in time but also in space and at various spatial scales. / NRF

In under 6 decades dengue has emerged from South East Asia to become the most widespread arbovirus affecting human populations. Recent dramatic increases in epidemic dengue fever have mainly been attributed to factors such as vector expansion and ongoing ecological, climate and socio-demographic changes. The failure to control the virus in endemic regions and prevent global spread of its mosquito vectors and genetic variants, underlines the urgency to reassess previous research methods, hypotheses and empirical observations. This thesis comprises a set of studies that integrate currently neglected and emerging epidemiological, ecological and evolutionary factors into unified mathematical frameworks, in order to better understand the contemporary population biology of the dengue virus. The observed epidemiological dynamics of dengue are believed to be driven by selective forces emerging from within-host cross-immune reactions during sequential, heterologous infections. However, this hypothesis is mainly supported by modelling approaches that presume all hosts to contribute equally and significantly to the selective effects of cross-immunity both in time and space. In the research presented in this thesis it is shown that the previously proposed effects of cross-immunological reactions are weakened in agent-based modelling approaches, which relax the common deterministic and homogeneous mixing assumptions in host-host and host-pathogen interactions. Crucially, it is shown that within these more detailed models, previously reported universal signatures of dengue's epidemiology and population genetics can be reproduced by demographic and natural stochastic processes alone. While this contrasts with the proposed role of cross-immunity, it presents demographic stochasticity as a parsimonious mechanism that integrates, for the first time, multi-scale features of dengue's population biology. The implications of this research are applicable to many other pathogens, involving challenging new ways of determining the underlying causes of the complex phylodynamics of antigenically diverse pathogens.