The ecology and evolution of invasive Potamopyrgus antipodarum in Australia

The spread of invasive organisms is one of the greatest threats to ecosystems and biodiversity worldwide. Understanding the evolutionary and ecological factors responsible for the transport, introduction, establishment and spread of invasive species will assist the development of control strategies. The New Zealand mudsnail, Potamopyrgus antipodarum (Gray 1843) (Gastropoda: Hydrobiidae), is a global freshwater invader, with populations established in Europe, Asia, the Americas and Australia. While sexual and asexual P. antipodarum coexist in the native range, invasive populations reproduce by parthenogenesis, producing dense populations that compete for resources with native species. Potamopyrgus antipodarum is a natural model system for the study of evolutionary and ecological processes underlying invasion. This thesis assesses the invasion history, genetic diversity and ecology of P. antipodarum in Australia, with particular focus on: a) potential source populations, b) distribution and structure of populations, and c) species traits related to the establishment, persistence and spread of invasive P. antipodarum. Genetic analyses were carried out on specimens collected for this study from New Zealand and Australia, along with existing museum samples. In combination with published data, the analyses revealed low genetic diversity among and within invasive populations in south-eastern Australia, relative to New Zealand populations. Phylogenetic relationships inferred from mitochondrial sequences indicated that the Australian populations belong to clades dominated by parthenogenetic haplotypes that are known to be present in Europe and the US. These ‘invasive clades’ are likely to originate from the North Island of New Zealand, and suggest a role for selection in determining genetic composition of invasive populations. The genotypic diversity of Australian P. antipodarum was low, with few, closely related clones distributed across south-eastern Australia. The pattern of clone distribution was not consistent with any assessed geographical or abiotic factors; instead a few, widely-distributed clones were present in high frequencies at most sites. Differences in clone frequencies were found, which may indicate differential success of clonal lineages. A range of traits have been proposed as facilitators of invasion success, and within-species variation in these traits can promote differential success of genotypes. Using laboratory-based experiments, the performance of the three most common Australian clones was tested across a suite of invasion-relevant traits. Ecologically-relevant variation in traits was found among the clones. These differences may have determined the spatial distribution of clones, and may continue to do so into the future. This thesis found that the P. antipodarum invasion of Australia is the result of few introductions of a small number of globally-invasive genotypes that vary in ecologically-relevant traits. From a source of considerable genetic diversity in the native range, very few genotypes have become invasive. Those that are invasive appear to be very successful at continental scales. These findings highlight a capacity in asexual invaders to successfully invade, and potentially adapt to, a broad range of ecosystems. The P. antipodarum invasion system is amenable to research using combinations of field-based studies, molecular and laboratory approaches, and is likely to yield significant, broadly-applicable insights into invasion.

Vision-based tracking for sports performance analysis

With the world of professional sports shifting towards employing better sport analytics, the demand for vision-based performance analysis is growing increasingly in recent years. In addition, the nature of many sports does not allow the use of any kind of sensors or other wearable markers attached to players for monitoring their performances during competitions. This provides a potential application of systematic observations such as tracking information of the players to help coaches to develop their visual skills and perceptual awareness needed to make decisions about team strategy or training plans. My PhD project is part of a bigger ongoing project between sport scientists and computer scientists involving also industry partners and sports organisations. The overall idea is to investigate the contribution technology can make to the analysis of sports performance on the example of team sports such as rugby, football or hockey. A particular focus is on vision-based tracking, so that information about the location and dynamics of the players can be gained without any additional sensors on the players. To start with, prior approaches on visual tracking are extensively reviewed and analysed. In this thesis, methods to deal with the difficulties in visual tracking to handle the target appearance changes caused by intrinsic (e.g. pose variation) and extrinsic factors, such as occlusion, are proposed. This analysis highlights the importance of the proposed visual tracking algorithms, which reflect these challenges and suggest robust and accurate frameworks to estimate the target state in a complex tracking scenario such as a sports scene, thereby facilitating the tracking process. Next, a framework for continuously tracking multiple targets is proposed. Compared to single target tracking, multi-target tracking such as tracking the players on a sports field, poses additional difficulties, namely data association, which needs to be addressed. Here, the aim is to locate all targets of interest, inferring their trajectories and deciding which observation corresponds to which target trajectory is. In this thesis, an efficient framework is proposed to handle this particular problem, especially in sport scenes, where the players of the same team tend to look similar and exhibit complex interactions and unpredictable movements resulting in matching ambiguity between the players. The presented approach is also evaluated on different sports datasets and shows promising results. Finally, information from the proposed tracking system is utilised as the basic input for further higher level performance analysis such as tactics and team formations, which can help coaches to design a better training plan. Due to the continuous nature of many team sports (e.g. soccer, hockey), it is not straightforward to infer the high-level team behaviours, such as players’ interaction. The proposed framework relies on two distinct levels of performance analysis: low-level performance analysis, such as identifying players positions on the play field, as well as a high-level analysis, where the aim is to estimate the density of player locations or detecting their possible interaction group. The related experiments show the proposed approach can effectively explore this high-level information, which has many potential applications.