ORCID Profile
0000-0001-9718-4464
Current Organisations
Queensland University of Technology
,
James Cook University
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Aquaculture | Fish Pests and Diseases | Fisheries Sciences | Fish Physiology and Genetics
Aquaculture Prawns | Aquaculture Fin Fish (excl. Tuna) | Fisheries - Aquaculture not elsewhere classified |
Publisher: Wiley
Date: 30-10-2012
Publisher: Inter-Research Science Center
Date: 24-08-2023
DOI: 10.3354/MEPS14362
Abstract: Studies focused on understanding drivers of coral mortality often examine reef- or ecosystem-scale stressors and/or pulse events such as mass bleaching or disease outbreaks. While such work provides valuable information about large-scale changes to reef ecosystems, how stressors interact at the in idual colony level across non-disturbance years is less understood. In this study, we tracked the fate of 400 plating Acropora coral colonies from 2 mid- and 2 outer-shelf reefs for 18 mo and examined (1) temporal changes in the prevalence of stressors, (2) how stressors affected the survival of in idual colonies, and (3) survival rates of colonies after contracting disease. We found that 35.5% of all colonies died within the 18 mo observation period, a period free from acute disturbances (e.g. cyclones, mass bleaching, crown-of-thorns starfish [CoTS] outbreaks). Despite its low prevalence, predation (by Drupella spp. or CoTS) led to the greatest risk of complete mortality compared to corals that experienced no stressors (over 10-fold increased risk). Similarly, experiencing disease and physical injury (fragmentation, dislodgement) also increased the risk of complete mortality (~4-fold and ~2-fold, respectively). In contrast, while compromised health (i.e. bleaching, algal overgrowth) was common, this did not significantly increase the risk of colony mortality. Survival analysis of colonies with white syndrome showed that colonies exposed to stressors prior to contracting disease were 3 times more likely to die compared to colonies with disease alone. Our results highlight the complex interactions that occur among multiple stressors on coral reefs, even in non-disturbance years, and quantify the increased risk of mortality for colonies experiencing accumulated stressors.
Publisher: Elsevier BV
Date: 12-2016
Publisher: Springer Science and Business Media LLC
Date: 18-01-2018
DOI: 10.1007/S10393-017-1309-Y
Abstract: Understanding environmental factors driving spatiotemporal patterns of disease can improve risk mitigation strategies. Hendra virus (HeV), discovered in Australia in 1994, spills over from bats (Pteropus sp.) to horses and thence to humans. Below latitude - 22°, almost all spillover events to horses occur during winter, and above this latitude spillover is aseasonal. We generated a statistical model of environmental drivers of HeV spillover per month. The model reproduced the spatiotemporal pattern of spillover risk between 1994 and 2015. The model was generated with an ensemble of methods for presence-absence data (boosted regression trees, random forests and logistic regression). Presences were the locations of horse cases, and absences per spatial unit (2.7 × 2.7 km pixels without spillover) were s led with the horse census of Queensland and New South Wales. The most influential factors indicate that spillover is associated with both cold-dry and wet conditions. Bimodal responses to several variables suggest spillover involves two systems: one above and one below a latitudinal area close to - 22°. Northern spillovers are associated with cold-dry and wet conditions, and southern with cold-dry conditions. Biologically, these patterns could be driven by immune or behavioural changes in response to food shortage in bats and horse husbandry. Future research should look for differences in these traits between seasons in the two latitudinal regions. Based on the predicted risk patterns by latitude, we recommend enhanced preventive management for horses from March to November below latitude 22° south.
Publisher: Springer Science and Business Media LLC
Date: 14-01-2017
Publisher: Authorea, Inc.
Date: 30-03-2022
DOI: 10.22541/AU.164865054.47757006/V1
Abstract: Understanding connectivity of marine species is crucial for their management. This connectivity, however, is difficult to quantify propagules of marine species are typically small, numerous, and can travel large distances. Consequently, oceanographic models are often used to simulate larval dispersal. To avoid high computational costs, these models typically use, pooled or cross-sectional data and fixed biological parameters. Here we explore how temporal and spatial variation in current velocities, and pelagic larval duration and buoyancy can alter patterns of marine connectivity of Crown-of-Thorns starfish on Australia’s Great Barrier Reef. Our results reveal highly variable reef connectivity in space and time mediated by all three factors. No in idual reef acted consistently as a population source or sink. It is, therefore, important to consider many factors concurrently when estimating connectivity for understanding these population dynamics, especially where such estimates are relied on for evidence-based decision making.
Publisher: MDPI AG
Date: 21-09-2017
DOI: 10.3390/D9040041
Publisher: Wiley
Date: 30-10-2012
Publisher: Springer Science and Business Media LLC
Date: 19-03-2009
DOI: 10.1007/S00439-009-0652-7
Abstract: Migraine is a painful disorder for which the etiology remains obscure. Diagnosis is largely based on International Headache Society criteria. However, no feature occurs in all patients who meet these criteria, and no single symptom is required for diagnosis. Consequently, this definition may not accurately reflect the phenotypic heterogeneity or genetic basis of the disorder. Such phenotypic uncertainty is typical for complex genetic disorders and has encouraged interest in multivariate statistical methods for classifying disease phenotypes. We applied three popular statistical phenotyping methods-latent class analysis, grade of membership and grade of membership "fuzzy" clustering (Fanny)-to migraine symptom data, and compared heritability and genome-wide linkage results obtained using each approach. Our results demonstrate that different methodologies produce different clustering structures and non-negligible differences in subsequent analyses. We therefore urge caution in the use of any single approach and suggest that multiple phenotyping methods be used.
Publisher: MDPI AG
Date: 22-08-2017
DOI: 10.20944/PREPRINTS201708.0076.V1
Abstract: Research on the coral-eating crown-of-thorns starfish (CoTS) has waxed and waned over the last few decades, mostly in accordance with the occurrence of population outbreaks at key locations, such as Australia& rsquo s Great Barrier Reef. This review considers advances in our understanding of the biology and ecology of CoTS based on the latest resurgence of research interest, which culminated in this current special issue on the Biology, Ecology and Management of Crown-of-Thorns Starfish. More specifically, this review considers progress against 41 specific research questions posed in the seminal review by P. Moran 30 years ago, as well as exploring new directions for CoTS research. Despite the plethora of research on CoTS (& ,200 research articles), there are persistent knowledge gaps that constrain effective management of outbreaks. Although directly addressing some of these questions will be extremely difficult, there have been considerable advances in understanding the biology of CoTS, if not the proximal and ultimate cause(s) of outbreaks. Moving forward, researchers need to embrace new technologies and opportunities to advance understanding of CoTS biology and behaviour, with focus given to key questions that will improve effectiveness of management to reduce the frequency and likelihood of future outbreaks, if not preventing them altogether.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2011
DOI: 10.1109/TCBB.2011.46
Publisher: Elsevier BV
Date: 11-2017
Publisher: Springer Science and Business Media LLC
Date: 10-05-2023
DOI: 10.1007/S11750-023-00656-6
Abstract: Autonomous vehicles create new opportunities as well as new challenges to dynamic vehicle routing. The introduction of autonomous vehicles as information-collecting agents results in scenarios, where dynamic nodes are found by proximity. This paper presents a novel dynamic vehicle-routing problem variant with proximity-dependent nodes. Here, we introduced a novel variable, detectability , which determines whether a proximal dynamic node will be detected, based on the sight radius of the vehicle. The problem considered is motivated by autonomous weed-spraying vehicles in large agricultural operations. This work is generalisable to many other autonomous vehicle applications. The first step to crafting a solution approach for the problem is to decide when reoptimisation should be triggered. Two reoptimisation trigger strategies are considered—exogenous and endogenous. Computational experiments compared the strategies for both the classical dynamic vehicle routing problem as well as the introduced variant. Experiments used extensive standardised vehicle-routing problem benchmarks with varying degrees of dynamism and geographical node distributions. The results showed that for both the classical problem and the novel variant, an endogenous trigger strategy is better in most cases, while an exogenous trigger strategy is only suitable when both detectability and dynamism are low. Furthermore, the optimal level of detectability was shown to be dependent on the combination of trigger, degree of dynamism, and geographical node distribution, meaning practitioners may determine the required detectability based on the attributes of their specific problem.
Publisher: Microbiology Society
Date: 06-2015
DOI: 10.1099/VIR.0.000073
Publisher: Proceedings of the National Academy of Sciences
Date: 14-01-2010
Publisher: Springer Science and Business Media LLC
Date: 24-04-2009
DOI: 10.1007/S00439-009-0671-4
Abstract: Definition of disease phenotype is a necessary preliminary to research into genetic causes of a complex disease. Clinical diagnosis of migraine is currently based on diagnostic criteria developed by the International Headache Society. Previously, we examined the natural clustering of these diagnostic symptoms using latent class analysis (LCA) and found that a four-class model was preferred. However, the classes can be ordered such that all symptoms progressively intensify, suggesting that a single continuous variable representing disease severity may provide a better model. Here, we compare two models: item response theory and LCA, each constructed within a Bayesian context. A deviance information criterion is used to assess model fit. We phenotyped our population s le using these models, estimated heritability and conducted genome-wide linkage analysis using Merlin-qtl. LCA with four classes was again preferred. After transformation, phenotypic trait values derived from both models are highly correlated (correlation = 0.99) and consequently results from subsequent genetic analyses were similar. Heritability was estimated at 0.37, while multipoint linkage analysis produced genome-wide significant linkage to chromosome 7q31-q33 and suggestive linkage to chromosomes 1 and 2. We argue that such continuous measures are a powerful tool for identifying genes contributing to migraine susceptibility.
Publisher: Public Library of Science (PLoS)
Date: 19-04-2017
Publisher: Springer Science and Business Media LLC
Date: 19-03-2018
Publisher: PeerJ
Date: 12-06-2017
DOI: 10.7717/PEERJ.3438
Abstract: Seawater temperature anomalies associated with warming climate have been linked to increases in coral disease outbreaks that have contributed to coral reef declines globally. However, little is known about how seasonal scale variations in environmental factors influence disease dynamics at the level of in idual coral colonies. In this study, we applied a multi-state Markov model (MSM) to investigate the dynamics of black band disease (BBD) developing from apparently healthy corals and/or a precursor-stage, termed ‘cyanobacterial patches’ (CP), in relation to seasonal variation in light and seawater temperature at two reef sites around Pelorus Island in the central sector of the Great Barrier Reef. The model predicted that the proportion of colonies transitioning from BBD to Healthy states within three months was approximately 57%, but 5.6% of BBD cases resulted in whole colony mortality. According to our modelling, healthy coral colonies were more susceptible to BBD during summer months when light levels were at their maxima and seawater temperatures were either rising or at their maxima. In contrast, CP mostly occurred during spring, when both light and seawater temperatures were rising. This suggests that environmental drivers for healthy coral colonies transitioning into a CP state are different from those driving transitions into BBD. Our model predicts that (1) the transition from healthy to CP state is best explained by increasing light, (2) the transition between Healthy to BBD occurs more frequently from early to late summer, (3) 20% of CP infected corals developed BBD, although light and temperature appeared to have limited impact on this state transition, and (4) the number of transitions from Healthy to BBD differed significantly between the two study sites, potentially reflecting differences in localised wave action regimes.
Start Date: 09-2021
End Date: 08-2026
Amount: $4,996,503.00
Funder: Australian Research Council
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