Dr Erin Peterson
Principal Research Fellow
Erin Peterson is a Principle Research Fellow in the Queensland University of Technology Institute for Future Environments and the ARC Centre for Excellence in Mathematical and Statistical Frontiers (ACEMS), in Brisbane, Australia. 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, assessment, and reporting; and the development of methods that better represent the spatial location, configuration, and connectivity of features in statistical models. Her transdisciplinary work has been published in top-tier journals, including the Journal of the American Statistical Association and Ecology Letters. She was also part of a multidisciplinary team awarded the 2016 US Forest Service Rise to the Future Award for the successful knowledge transfer of statistical methods that have become standard-practice for aquatic resource management. Erin is currently a Regional Representative of The International Environmetrics Society (TIES).
Research Interests:
Environmental monitoring assessment and reporting
Spatial networks
Spatial statistics
Qualifications:
B.S. Forest Conservation, Michigan State University (1995)
M.S. Forestry, Colorado State University (2001)
Ph.D. Earth Resources, Colorado State University (2005)
Projects
Publications
Invited talks, refereed proceedings and other conference outputs
(2019). Estimating parameters of landscape resistance using spatial autoregressive models.
The 10th International Association for Landscape Ecology World Congress.
(2019). Virtual Reef Diver.
International Workshop on Spatial Statistics.
(2019). Combining citizen science and professional monitoring data to conserve and sustainably use marine resources.
62nd ISI World Statistics Congress.
(2019). Optimisation of coral reef monitoring using Bayesian adaptive design methods.
Bayes on the Beach 2019.
(2018). SSNdesign: an R package for pseudo-Bayesian optimal and adaptive design on stream networks.
UseR!2018.
(2017). Environmental and Biological Monitoring in the Era of Big Data.
62nd RBRAS and 17th Annual SEAGRO joint meeting.
(2017). Monitoring Through Many Eyes.
62nd RBRAS and 17th Annual SEAGRO joint meeting.
(2016). Monitoring through many eyes.
International Statistical Ecology Conference.
(2016). Elicitation of expert information for conservation.
The International Environmetrics Society.
(2016). Virtual reality for conservation.
Web3D 2016: 21st International Conference on Web3D Technology. 177–178. doi: 10.1145/2945292.2945319
(2016). Virtual reality for conservation.
Web3D 2016. doi: 10.1145/2945292.2945319
Journal Articles
(2019). The sound of management: Acoustic monitoring for agricultural industries.
Ecological Indicators. 96(Part 1), 739-746. doi: 10.1016/j.ecolind.2018.09.029
(2018). Spatial Autoregressive Models for Statistical Inference from Ecological Data.
Ecological Monographs. 88(1), 36-59. doi: 10.1002/ecm.1283
(2018). A framework for automated anomaly detection in high frequency water-quality data from in situ sensors.
arXiv preprints.
(2018). Riparian restoration offsets predicted population consequences of climate warming in a threatened headwater fish.
Aquatic Conservation: Marine and Freshwater Ecosystems. 28(3), 575 - 586. doi: 10.1002/aqc.2864
(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). 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
(2017). Modelling imperfect presence data obtained by citizen science.
Environmetrics. 28(5), e2446. doi: 10.1002/env.2446
(2017). Thermal habitat restricts patterns of occurrence in multiple life-stages of a headwater fish.
Freshwater Science. 36(2), 402 - 414. doi: 10.1086/691553
(2017). An assessment framework for measuring agroecosystem health.
Ecological Indicators. 79, 265 - 275. doi: 10.1016/j.ecolind.2017.04.002
(2017). The NorWeST Summer Stream Temperature Model and Scenarios for the Western U.S.: A Crowd-Sourced Database and New Geospatial Tools Foster a User Community and Predict Broad Climate Warming of Rivers and Streams.
Water Resources Research. doi: 10.1002/2017WR020969
(2017). Scalable population estimates using spatial-stream-network (SSN) models, fish density surveys, and national geospatial database frameworks for streams.
Canadian Journal of Fisheries and Aquatic Sciences. 74(2), 147-156. doi: 10.1139/cjfas-2016-0247
(2016). To aggregate or not? Capturing the spatio-temporal complexity of the thermal regime.
Ecological Indicators. 67, 39-48. doi: 10.1016/j.ecolind.2016.02.014
(2016). Spatial and temporal variation of water temperature regimes on the Snoqualmie river network.
JAWRA Journal of the American Water Resources Association. 52(3), 769-787. doi: 10.1111/1752-1688.12423
(2016). Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity.
Proceedings of the National Academy of Sciences. 113(16), 4374-4379. doi: 10.1073/pnas.1522429113
(2015). Validation and comparison of geostatistical and spline models for spatial stream networks.
Environmetrics. 26(5), 327-338. doi: 10.1002/env.2340
Technical reports and unrefereed outputs
(2016). Monitoring Through Many Eyes:Spatially enabling people to protect the Great Barrier Reef.
