Adaptive strategies in reef-building corals

One of the major goals of ecology is to identify metrics of assemblage structure that are easy to obtain and that enable accurate predictions of how assemblages respond to disturbance and environmental change. One recent approach, termed Universal Adaptive Strategy Theory (UAST), has been hypothesised to apply to all creatures on the tree of life. However, previous attempts to classify reef-building corals according to UAST have been inconclusive, perhaps because they have not chosen species traits according to the principles set out in the theory. In addition, the utility of the approach for predicting the response of coral assemblages to disturbance has not been effectively tested. This aims of my thesis was to test whether UAST applies to reef-building corals and whether or not adaptive strategy grouping are useful for predicting the response of taxa to disturbance. In Chapter 2, I first classify coral species into groups using the principles of UAST and a comprehensive database of coral traits. Next, in Chapter 3, I test the ability of adaptive strategy groups to predict the response of coral taxa to disturbance using a long-term dataset from inshore reefs on the Great Barrier Reef (GBR). Finally, in Chapter 4, I test for variation in the relative abundance of adaptive strategy groups in coral assemblages along the 1600 km latitudinal or environmental gradient that is the GBR. I found that UAST does not apply to corals and the analyses suggests only two groups of species rather than the three predicted by the theory. I also found that adaptive strategy groups do not accurately predict how a taxa will respond to disturbance nor do these groups respond in a predictable way along an environmental gradient. In conclusion, it is much more tractable and informative to explore traits directly, rather than looking for groups based on traits

A functional approach to the structural complexity of coral assemblages based on colony morphological features

Colony morphological features is among the best predictor of the scleractinian coral's function in reef ecosystems. However, morphological traits are categorical and to convert this information into a quantitative value as well as estimate their influence on ecosystem process remain a challenge. Here, we propose a trait-based approach to quantify morphological diversity and assess the structural complexity of the habitat provided by corals. We used a previously published dataset that is related to a bleaching event that affected the coral reef off Tikus Island in Indonesia in 1983. We found clear signs of recovery of the coral assemblage's complexity toward pre El Niño conditions five years after the event. Independent of the change observed in species richness, this return in structural complexity was accompanied by a global decrease in species number associated with each particular morphological entity (Functional Redundancy) and an increase in the number of single-species entities (Functional Vulnerability). Together with species loss, we show an overall functional erosion of the coral assemblage and suggest that the role of the coral reef habitat could be strongly imperiled under repeated or synergistic disturbances. This approach offers an opportunity for a better understanding of coral responses to natural and anthropogenic disturbances

Identifying the attack sources of botnets for a renewable energy management system by using a revised locust swarm optimisation scheme

Distributed denial of service (DDoS) attacks often use botnets to generate a high volume of packets and adopt controlled zombies for flooding a victim’s network over the Internet. Analysing the multiple sources of DDoS attacks typically involves reconstructing attack paths between the victim and attackers by using Internet protocol traceback (IPTBK) schemes. In general, traditional route-searching algorithms, such as particle swarm optimisation (PSO), have a high convergence speed for IPTBK, but easily fall into the local optima. This paper proposes an IPTBK analysis scheme for multimodal optimisation problems by applying a revised locust swarm optimisation (LSO) algorithm to the reconstructed attack path in order to identify the most probable attack paths. For evaluating the effectiveness of the DDoS control centres, networks with a topology size of 32 and 64 nodes were simulated using the ns-3 tool. The average accuracy of the LS-PSO algorithm reached 97.06 for the effects of dynamic traffic in two experimental networks (number of nodes = 32 and 64). Compared with traditional PSO algorithms, the revised LSO algorithm exhibited a superior searching performance in multimodal optimisation problems and increased the accuracy in traceability analysis for IPTBK problems