Adj Assoc Prof Erin Peterson

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PhD (Colorado State University)

Dr. Erin Peterson joined QUT in 2015 as an Associate Professor/Principal Research Fellow (100% Research) in the Institute for Future Environments and the ARC Centre for Excellence in Mathematical and Statistical Frontiers (ACEMS). Erin’s educational background and experience allow her to work at the interface of landscape ecology, geographic information science, and environmental statistics. Her research relates to broad-scale modelling, regional monitoring program design and assessment, and the development of methods that better represent the spatial location, configuration, and connectivity in statistical models. Erin is also committed to software tool development, which helps to ensure that the methods she develops are accessible other scientists and natural resource managers.

Erin received her B.S. in Conservation Forestry from Michigan State University, her M.S. in Forestry from Colorado State University, and her Ph.D. in Earth Resources from Colorado State University. Prior to coming to QUT, Erin worked as a Postdoctoral Research Fellow, Research Scientist, and Senior Research Scientist at CSIRO in Brisbane. From 2012-2014 she also led the Environmental & Agricultural Informatics, Monitoring and Indicator Analysis team. These roles provided her with extensive experience engaging and collaborating with natural resource management agenci, industry representatives, and scientists from national and international government agencies and universities.

Erin has obtained funding for research grants (~$6.64M), led, and contributed to many spatially distributed, inter-agency, and interdisciplinary research teams. These projects include, but are not limited to:

  • 2017-2018: Bonneville Power Authority Automated Fish Density Tool. Collaborators: US Forest Service, US NOAA. Funding Body: US Department of Energy. Project Leader
  • 2016-2017: A generic IntelliSensing software platform to support spatio-temporal analytics. Funding Body: QUT Institute for Future Environments. Project Leader
  • 2016-2019: Improving Our Predictive Capabilities of Stream Health. Funding Body: Southeast Queensland Healthy Land & Water. Project Leader
  • 2016-2019: Improving the ability of the Australian cotton industry to report its sustainability performance. Funding Body: Cotton Research & Development Corporation. Project Leader
  • 2015-2016: Monitoring Through Many Eyes: Spatially Enabling People to Protect the Great Barrier Reef. Collaborators: Australian Institute of Marine Science, University of Queensland Global Change Institute and the Remote Sensing Research Centre, Reef Check Australia. Funding Bodies: CRC for Spatial Information and the Queensland Department of Natural Resources and Mines. Chief Investigator.
  • 2014-2016: National Stream Internet to Facilitate Accurate, High-Resolution Status and Trend Assessments for Water Quality Parameters and Aquatic Biotas. Collaborators: US Forest Service, US NOAA, US Geological Survey. Funding Body: US National Landscape Conservation Cooperative. Chief Investigator.
  • 2011-2016: A Regional Stream Temperature Model for Mapping Thermal Habitats and Understanding Vulnerability of Aquatic Species to Climate Change across the Great Northern LCC. Collaborators: US Forest Service, US NOAA, US Geological Survey, Trout Unlimited. Funding Body: US Great Northern Landscape Conservation Cooperative. Chief Investigator.

For a list of current publications, please see Erin’s Google Scholar page.


Additional information

Dr. Erin Peterson’s research focuses on the development of interdisciplinary approaches and tools used to account for multi-scale, ecological and spatio-temporal relationships in environmental and agricultural ecosystems. From a theoretical perspective, this research area provides a rich set of challenges to work on, related to capturing and quantifying spatio-temporal heterogeneity at multiple scales within a statistical modeling framework. However, Erin is also deeply committed to applied research, where real management questions create the need for innovative solutions. In addition, she is committed to software and tool development, which helps to ensure that complex statistical methodologies are accessible to non-statisticians.

Erin also has a broad set of skills related to monitoring program design, assessment, and reporting. Her PhD research was part of the Space-Time Aquatic Resources Modeling and Analysis Program (STARMAP), which involved the development of new statistical methods for aquatic resources, as well as the transfer of statistical expertise to natural resource managers. At CSIRO, Erin was involved in the development of a wide range of monitoring-related methods including survey design, indicator selection, indicator aggregation, regionalisation, spatial prediction, uncertainty estimation, and environmental report-card development. She has a particular interest in the use of large, spatio-temporal datasets collected using new technologies (e.g. in situ sensors, remote sensing) for predictive modelling and uncertainty estimation, within an adaptive monitoring framework.

Erin has worked on projects ranging from the:

  • Spatial statistical modeling on stream networks;
  • Acoustic monitoring of bats in cotton systems;
  • Estimating resistance parameters in landscape genetic models using spatial statistical models;
  • Modelling citizen-science data on the Great Barrier Reef;
  • Using virtual reality to elicit information for conservation modeling;
  • Modelling jaguar encounters using imperfect presence-only data obtained by citizen science;
  • Development of an integrated report card for the Great Barrier Reef catchments;
  • Estimating annual pollutant loads from monitoring data;
  • Assessing the ecological response to altered flow regimes;
  • Broad-scale prediction of stream temperature to improve the efficiency of monitoring and facilitate species vulnerability assessments under different climate-change scenarios; and the
  • Development of an agroecosystem health assessment framework that can be used assess industry-specific environmental impacts.
Agri-Intelligence in Cotton Production Systems - Stage 1
Primary fund type
CAT 1 - Australian Competitive Grant
Project ID
Start year
Agriculture Cybernetics;Digital Agriculture;In-Farm Decision Support Systems;Management of Inputs in Agriculture;Value Chain of Cotton Crops
Improving the ability of the Australian cotton industry to report its sustainability performance
Primary fund type
CAT 1 - Australian Competitive Grant
Project ID
Start year
Agriculture;Agroecosystem Health;Natural Resource Management