ORCID Profile
0000-0002-6495-3535
Current Organisation
University of Western Australia
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Photogrammetry and Remote Sensing | Physical Oceanography | Geophysical Fluid Dynamics | Oceanography
Expanding Knowledge in the Earth Sciences | Physical and Chemical Conditions of Water in Marine Environments | Marine Oceanic Processes (excl. climate related) |
Publisher: International Ocean Colour Coordinating Group (IOCCG)
Date: 2019
DOI: 10.25607/OBP-691
Publisher: Elsevier BV
Date: 11-2023
Publisher: Wiley
Date: 10-2019
DOI: 10.1002/AQC.3068
Publisher: Elsevier BV
Date: 2018
Publisher: MDPI AG
Date: 19-01-2018
DOI: 10.3390/RS10010147
Publisher: Elsevier BV
Date: 06-2011
DOI: 10.1016/J.MARPOLBUL.2011.03.040
Abstract: The large green-tide events that occurred in the Yellow Sea in 2008 (3489km(2)) and 2009 (4994km(2)) are shown to be novel events preceded only once by a much smaller event in 2007 (82km(2)). The blooms originated in the coastal area of Jiangsu province and spread north-east towards the Shandong Peninsula. The blooms grew at different rates and mesoscale variability in surface winds explained the differences in the spatial and temporal patterns of blooms in 2008 and 2009. The 2009 bloom was tracked to its origin immediately offshore of extensive intertidal flats between Yancheng and Nantong where recent rapid expansion of Porphyra aquaculture has occurred. We review published hypotheses which have been advanced to explain the occurrence of blooms and in light of our findings, we conclude that the accumulation and disposal of waste Ulva prolifera from Porphyra aquaculture rafts is the most likely cause of the blooms.
Publisher: Wiley
Date: 29-08-2021
DOI: 10.1111/DDI.13400
Abstract: Forecasting the influence of climate change on coral bio ersity and reef functioning is important for informing policy decisions. Dominance shifts, tropicalization and local extinctions are common responses of climate change, but uncertainty surrounds the reliability of predicted coral community transformations. Here, we use species distribution models (SDMs) to assess changes in suitable coral habitat and associated patterns in bio ersity across Western Australia (WA) under present‐day and future climate scenarios (RCP 2.6 and RCP 8.5). Coral reef systems and communities in WA. We developed SDMs with model prediction uncertainty analyses, using specimen‐based occurrence records of 188 hermatypic scleractinian coral species and seven variables to estimate present‐day and future changes to coral species distribution and bio ersity patterns in WA under climate change conditions. We found that suitable habitat is predicted to increase across all regions in WA under , and scenarios with all tropical and subtropical regions remaining coral bio ersity strongholds. Under the extreme scenario, however, a clear tropicalization trend could be observed with coral species expanding their range to mid‐high latitude regions, while a substantial drop in coral species richness was predicted at low latitude tropical coral reefs, such as the inshore Kimberley and offshore NW reefs. Despite the predicted expansion south, we identified a net decline in coral bio ersity across the WA coastline. Results from the models predicted higher net coral bio ersity loss at low latitude tropical regions compared with net gains at mid‐high latitude regions under . These results are likely to be representative of latitudinal trends across the Southern Hemisphere and highlight that increases in habitat suitability at higher latitudes may not lead to equivalent bio ersity benefits. Urgent action is needed to limit climate change to prevent spatial erosion of tropical coral communities, extinction events and loss of tropical ecosystem services.
Publisher: American Geophysical Union (AGU)
Date: 2013
DOI: 10.1029/2012JC008292
Publisher: Optica Publishing Group
Date: 09-2020
DOI: 10.1364/OE.405306
Abstract: Corrections for equations in our recently published paper [ Opt. Express 27 , A1350 ( 2019 ) ] are presented.
Publisher: Coastal Education and Research Foundation
Date: 03-03-2016
DOI: 10.2112/SI75-258.1
Publisher: Elsevier BV
Date: 10-2017
Publisher: Public Library of Science (PLoS)
Date: 25-02-2015
Publisher: MDPI AG
Date: 02-10-2015
DOI: 10.3390/RS71013157
Publisher: Wiley
Date: 10-2014
Publisher: Inter-Research Science Center
Date: 21-03-2016
DOI: 10.3354/MEPS11657
Publisher: American Association for the Advancement of Science (AAAS)
Date: 2021
Abstract: With the advancement of Lidar technology, bottom depth ( H ) of optically shallow waters (OSW) can be measured accurately with an airborne or space-borne Lidar system ( H Lidar hereafter), but this data product consists of a line format, rather than the desired charts or maps, particularly when the Lidar system is on a satellite. Meanwhile, radiometric measurements from multiband imagers can also be used to infer H ( H imager hereafter) of OSW with variable accuracy, though a map of bottom depth can be obtained. It is logical and advantageous to use the two data sources from collocated measurements to generate a more accurate bathymetry map of OSW, where usually image-specific empirical algorithms are developed and applied. Here, after an overview of both the empirical and semianalytical algorithms for the estimation of H from multiband imagers, we emphasize that the uncertainty of H imager varies spatially, although it is straightforward to draw regressions between H Lidar and radiometric data for the generation of H imager . Further, we present a prototype system to map the confidence of H imager pixel-wise, which has been lacking until today in the practices of passive remote sensing of bathymetry. We advocate the generation of a confidence measure in parallel with H imager , which is important and urgent for broad user communities.
Publisher: Elsevier BV
Date: 09-2018
Publisher: Springer Science and Business Media LLC
Date: 16-05-2019
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 05-2014
Publisher: Elsevier BV
Date: 12-2020
Location: United States of America
Start Date: 04-2022
End Date: 04-2026
Amount: $707,971.00
Funder: Australian Research Council
View Funded Activity