Adjunct Associate Professor
Erin Peterson

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.