Data

Adaptive monitoring of coral health at Scott Reef where data exhibit nonlinear and disturbed trends over time

Name: Adaptive monitoring of coral health at Scott Reef where data exhibit nonlinear and disturbed trends over time
Published: 2026

Australian Institute of Marine Science

Australian Institute of Marine Science (AIMS)

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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25845/asfw-dz73&rft.title=Adaptive monitoring of coral health at Scott Reef where data exhibit nonlinear and disturbed trends over time&rft.identifier=https://doi.org/10.25845/asfw-dz73&rft.publisher=Australian Institute of Marine Science (AIMS)&rft.description=Time series data are often observed in ecological monitoring. Frequently such data exhibit nonlinear trends over time potentially due to complex relationships between observed and auxiliary variables, and there may also be sudden declines over time due to major disturbances. This poses substantial challenges for modelling such data and also for model-based adaptive monitoring. We propose novel methods for finding adaptive designs for monitoring when historical data show such nonlinear patterns and sudden declines over time. This work is motivated by a coral reef monitoring program that has been established at Scott Reef; a coral reef off the Western coast of Australia. Data collected for monitoring the health of Scott Reef are considered, and semiparametric and interrupted time series modelling approaches are adopted to describe how these data vary over time. New methods are then proposed that enable adaptive monitoring designs to be found based on such modelling approaches. These methods are then applied to find future monitoring designs at Scott Reef and form a set of recommendations for future monitoring.Through applying the proposed methods, it was found that future in formation gain is expected to be similar across a variety of different sites, suggesting that no particular location needed to be prioritised at Scott Reef for the next monitoring phase. In addition, it was found that omitting some sampling sites/reef locations was possible without substantial loss in expected information gain, depending upon the disturbances that were observed. The resulting adaptive designs are used to provide recommendations for future monitoring in this region, and for reefs where changes to the current monitoring practices are being sought. Furthermore, as the methods used and developed throughout this study are generic in nature, this research has the potential to improve ecological monitoring more broadly where complex 28 data are being collected over time.Maintenance and Update Frequency: notPlannedStatement: See file: SCOTT_REEF_Data_Description.txt&rft.creator=Australian Institute of Marine Science (AIMS) &rft.date=2026&rft.coverage=westlimit=121.67303463444115; southlimit=-14.232739153937622; eastlimit=122.07952869124712; northlimit=-13.598723675422956&rft.coverage=westlimit=121.67303463444115; southlimit=-14.232739153937622; eastlimit=122.07952869124712; northlimit=-13.598723675422956&rft_rights=Creative Commons Attribution-NonCommercial 3.0 Australia License http://creativecommons.org/licenses/by-nc/3.0/au/&rft_rights=Use Limitation: All AIMS data, products and services are provided as is and AIMS does not warrant their fitness for a particular purpose or non-infringement. While AIMS has made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. AIMS make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, AIMS exclude all liability to any person arising directly or indirectly from the use of the data, products and services.&rft_rights=Attribution: Format for citation of metadata sourced from Australian Institute of Marine Science (AIMS) in a list of reference is as follows: Australian Institute of Marine Science (AIMS). (2022). Adaptive monitoring of coral health at Scott Reef where data exhibit nonlinear and disturbed trends over time. https://doi.org/10.25845/asfw-dz73, accessed[date-of-access].&rft_subject=oceans&rft.type=dataset&rft.language=English Access the data

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http://creativecommons.org/licenses/by-nc/3.0/au/

Use Limitation: All AIMS data, products and services are provided "as is" and AIMS does not warrant their fitness for a particular purpose or non-infringement. While AIMS has made every reasonable effort to ensure high quality of the data, products and services, to the extent permitted by law the data, products and services are provided without any warranties of any kind, either expressed or implied, including without limitation any implied warranties of title, merchantability, and fitness for a particular purpose or non-infringement. AIMS make no representation or warranty that the data, products and services are accurate, complete, reliable or current. To the extent permitted by law, AIMS exclude all liability to any person arising directly or indirectly from the use of the data, products and services.

Attribution: Format for citation of metadata sourced from Australian Institute of Marine Science (AIMS) in a list of reference is as follows: "Australian Institute of Marine Science (AIMS). (2022). Adaptive monitoring of coral health at Scott Reef where data exhibit nonlinear and disturbed trends over time. https://doi.org/10.25845/asfw-dz73, accessed[date-of-access]".

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Time series data are often observed in ecological monitoring. Frequently such data exhibit nonlinear trends over time potentially due to complex relationships between observed and auxiliary variables, and there may also be sudden declines over time due to major disturbances. This poses substantial challenges for modelling such data and also for model-based adaptive monitoring. We propose novel methods for finding adaptive designs for monitoring when historical data show such nonlinear patterns and sudden declines over time. This work is motivated by a coral reef monitoring program that has been established at Scott Reef; a coral reef off the Western coast of Australia. Data collected for monitoring the health of Scott Reef are considered, and semiparametric and interrupted time series modelling approaches are adopted to describe how these data vary over time. New methods are then proposed that enable adaptive monitoring designs to be found based on such modelling approaches. These methods are then applied to find future monitoring designs at Scott Reef and form a set of recommendations for future monitoring.

Through applying the proposed methods, it was found that future in formation gain is expected to be similar across a variety of different sites, suggesting that no particular location needed to be prioritised at Scott Reef for the next monitoring phase. In addition, it was found that omitting some sampling sites/reef locations was possible without substantial loss in expected information gain, depending upon the disturbances that were observed. The resulting adaptive designs are used to provide recommendations for future monitoring in this region, and for reefs where changes to the current monitoring practices are being sought. Furthermore, as the methods used and developed throughout this study are generic in nature, this research has the potential to improve ecological monitoring more broadly where complex 28 data are being collected over time.

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Maintenance and Update Frequency: notPlanned

Statement: See file: SCOTT_REEF_Data_Description.txt

Notes

Credit
Thilan AWLP. Queensland University of Technology (QUT), Australian Research Council Centre of Excellence for Mathematical andStatistical Frontiers (ACEMS) & University of Ruhuna, Sri Lanka

Credit
Fisher R. Australian Institute of Marine Science (AIMS), Oceans Institute, University of Western Australia (UWA) & Western Australian Marine Science Institution (WAMSI)

Credit
Thompson H. QUT & ACEMS

Credit
Menendez, P. Monash University & AIMS

Credit
Gilmour, J. AIMS & Oceans Institute (UWA)

Credit
McGree, JM. QUT & ACEMS

Modified: 06 11 2026

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text: westlimit=121.67303463444115; southlimit=-14.232739153937622; eastlimit=122.07952869124712; northlimit=-13.598723675422956

Subjects

oceans |

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Other Information

SCOTT_REEF.csv

url : https://api.aims.gov.au/data-v2.0/4cffe92a-1b58-4bc9-8f7c-a41ffdf18cdb/files/SCOTT_REEF.csv External Link

SCOTT_REEF_Data_Description

url : https://api.aims.gov.au/data-v2.0/4cffe92a-1b58-4bc9-8f7c-a41ffdf18cdb/files/SCOTT_REEF_Data_Description.txt External Link

Abeysiri Wickrama Liyanaarachchige, Pubudu Thilan. (2021). Scott Reef Survey Design. Zenodo. [Software] https://doi.org/10.5281/zenodo.4586187

doi : https://doi.org/10.5281/zenodo.4586187 DOI Link

Identifiers

global : 4cffe92a-1b58-4bc9-8f7c-a41ffdf18cdb