Dr Erin Peterson
Principal Research Fellow
Dr Erin Peterson is the owner of EP Consulting in Brisbane, where she leads a small team of scientists working at the interface of natural resource management, geographic information science (GIS), and environmental statistics. Erin has over 20 years of experience as a government and academic research scientist, and independent consultant. Her research and consulting work is primarily focused on the next generation of environmental monitoring in terrestrial, marine, and river ecosystems using new technologies. This includes innovative methods of data capture; the analysis of near real-time data collected using in situ sensors; and accounting for data quality and uncertainty when combining different data sources, including citizen-science data. The results of these projects have been used by government, industry, and NGOs to support condition and trend assessments, spatial prioritization of management actions, evaluations of the effectiveness of management actions, and natural and anthropogenic impact assessments under current and future land-use and climate scenarios.
Research Interests:
Environmental monitoring assessment and reporting
Spatial networks
Spatial statistics
Projects
Publications
Invited talks, refereed proceedings and other conference outputs
(2021). Data Science meets Citizen Science: how to trust people.
1st International Symposium on the Science of Data Science (ISSDS 2021), Switzerland.
(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.
(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.
(2018). SSNdesign: an R package for pseudo-Bayesian optimal and adaptive design on stream networks.
UseR!2018.
(2017). Monitoring Through Many Eyes.
62nd RBRAS and 17th Annual SEAGRO joint meeting.
(2017). Environmental and Biological Monitoring in the Era of Big Data.
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.
International Conference on Web3D Technology. 177–178. doi: 10.1145/2945292.2945319
Journal Articles
(2021). Understanding links between water-quality variables and nitrate concentration in freshwater streams using high-frequency sensor data.
arXiv. arXiv:2106.01719v1.
(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). 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
(2018). Spatial Autoregressive Models for Statistical Inference from Ecological Data.
Ecological Monographs. 88(1), 36-59. doi: 10.1002/ecm.1283
(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
(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
(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.
Research links
