Alan Pearse | ARC Centre of Excellence for Mathematical and Statistical Frontiers

Research assistant

Queensland University of Technology

I am a research assistant for Dr Erin Peterson. I have a passion for environmental and ecological statistics, and my specialities are GIS, scientific programming, and experimental design.

Research Interests:

Adaptive survey design

Environmental monitoring

GIS

Modelling of biological and environmental systems

Qualifications:

Bachelor of Science (Earth Science), Bachelor of Mathematics (Statistical Science)

Projects

Monitoring through many eyes: Integrating datasets to improve monitoring of the Great Barrier Reef

Enormous effort is invested in monitoring the Great Barrier Reef (GBR), but data collection is currently fragmented over dozens of publicly and privately funded organisations, with data collected using different methods and for different purposes. As a result, the data are rarely analysed together.

Rapid spatial risk modelling for management of early weed invasions: balancing ecological complexity and operational needs

Invasive weeds can threaten native biodiversity and negatively impact on agriculture. A group of researchers at QUT and CSIRO, including an ACEMS member, designed and implemented a new framework for rapidly modelling the invasion risk of weeds using Bayesian belief networks.

Publications

Invited talks, refereed proceedings and other conference outputs

2018

Pearse, A. R., McGree J., Som N., & Peterson E. (2018). SSNdesign: an R package for pseudo-Bayesian optimal and adaptive design on stream networks. UseR!2018.

Journal Articles

2018

Peterson, N., Hamilton G. S., Almany G., Pita J., Choat J. Howard, Hamilton R. J., et al. (2018). Giant coral reef fishes display markedly different susceptibility to night spearfishing. Ecology and Evolution. 8(20), 10247 - 10256. doi: 10.1002/ece3.4501

2017

Peterson, E., & Pearse A. R. (2017). IDW-Plus: An ArcGIS Toolset for Calculating Spatially Explicit Watershed Attributes for Survey Sites. JAWRA Journal of the American Water Resources Association. 53(5), 1241-1249. doi: 10.1111/1752-1688.12558

Mengersen, KL., Peterson E., Clifford S., Ye N., Kim J., Bednarz T., et al. (2017). Modelling imperfect presence data obtained by citizen science. Environmetrics. 28(5), e2446. doi: 10.1002/env.2446

Publicly available softwares

2018

Lee, S. A., Lumley T., & Pearse A. R. (2018). rwalkable.

Welcome to the ACEMS Reportal

All contributors should enter data on all of the Centre’s reportable key performance indicators (KPIs).

Mr Alan Pearse

Projects

Monitoring through many eyes: Integrating datasets to improve monitoring of the Great Barrier Reef

Rapid spatial risk modelling for management of early weed invasions: balancing ecological complexity and operational needs

Publications

2018

2018

2017

2018

Research links

Links

ARC Centre of Excellence for Mathematical & Statistical Frontiers

Welcome to the ACEMS Reportal

All contributors should enter data on all of the Centre’s reportable key performance indicators (KPIs).

Mr Alan Pearse

2018

2018

2017

2018

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Links

ARC Centre of Excellence for Mathematical & Statistical Frontiers