PLOS’ environmental science journals cover a broad range of topics, from agriculture and ecosystems, to the effects of environmental change on health…
For this behind the paper post, we caught up with the authors of a new article in PLOS Water “Daily stream temperature predictions for free-flowing streams in the Pacific Northwest, USA,” Jared Siegel, Aimee Fullerton, Alyssa FitzGerald, Damon Holzer, and Chris Jordan. In their paper, the authors describe a new statistical model for more accurately predicting water temperatures in rivers and streams across broad geographic regions, taking into account complex factors like topography and seasonal changes.
Congratulations on your recent publication in PLOS Water!
To begin, can you share a little about your study? What motivated you to explore the topic, and how did you come up with the idea for this modeling approach?
As NOAA Fisheries scientists, we are charged with identifying environmental factors that contribute to the well-being of Pacific salmon so that we can identify potential conservation and management actions to support healthy populations and to recover imperiled populations.
Stream temperature is one of the most important controls on fish growth and survival. Stream temperature is something we can influence, for example by reconnecting rivers with their floodplains and ensuring adequate riparian shade. Research on stream temperature has progressed quickly, but we lacked daily predictions of stream temperature in rivers across the range of salmon in the Pacific Northwest, USA. Therefore, we decided to take it on ourselves to build a model to give us predictions that we could use to support fish management decisions.
Our modeling approach was motivated by previous stream temperature modeling works (i.e., Isaak et al. 2017, Jackson et al. 2018, Siegel and Volk 2019, FitzGerald et al. 2021) that were so useful, but daily stream temperature was still unavailable over a vast spatial extent. We really wanted our model to be an easy-to-interpret, easy-to-use approach that relied on straightforward statistics, intuitive relationships with covariates, and freely available data that anyone could apply to best suit the needs specific to their region.
Did you learn anything that surprised you along the way?
Sometimes statistical models can feel a little bit like magic. It is one thing to have a theory of what data might be useful in predicting stream temperature. But, it is another to actually have that data available, processed, and brought together in a modeling framework. Our covariates come from a number of different sources and they themselves represent impressive works from other scientists. Without these previous efforts, our work would not have been possible. It is a testament to how science can build upon itself to continue to achieve new accomplishments.
There is a feeling of excitement and magic when in the end all these disparate parts come together and actually work as envisioned.
What do you hope your readers will gain from this work? How do you think it may be applied in the field going forward?
Our primary intention was to provide a resource to readers in the form of the daily stream temperature predictions we produced that will be immediately useful in a variety of applications. But, we also hope that readers will find our modeling tool useful, and that they will continue to improve on what we did, fine-tuning the code and covariates to make even better predictions.
Why did you choose to submit to PLOS Water? How was the experience?
We wanted our research to be visible to a broad audience, including water resource scientists, managers, and conservation practitioners. We hope that by choosing a well-respected, Open Access, international journal, our approach will be applied in new parts of the world. The experience was very comfortable: the process was very fast, all staff were professional and kind, and reviews were constructive.
When you submitted to PLOS Water, you opted-in to have your manuscript posted as a preprint on EarthArXiv as well. How was the preprinting process? Did you receive any feedback from readers?
In previewing our work, there was a high demand for our stream temperature predictions. We knew that people were eager to see what we had done and to have something to cite informally while our paper proceeded through the review process. We therefore really appreciated having this preprint opportunity to share our work and to get feedback. The process was seamless and very straightforward. We did receive feedback, but not specifically from preprint readers.
What comes next—what further research would you like to see in this area?
There are many new directions this research could take, including a better way to represent predictions downstream of large dams, inclusion of how fire shapes the landscape over time (and alters covariates like riparian cover and flow pathways), and an improved representation of the interaction between surface and groundwater. It would also be great to have reliable sources of remotely-sensed data (e.g., snowpack, air temperature) and modeled streamflow with daily or finer temporal resolution. We hope that readers will continue to forge ahead with these and other improvements. Additionally, we hope that our modeling approach will be applied to other geographic regions inhabited by Pacific salmon, e.g., California, Alaska, and western Canada.
Thank you so much for taking the time to share your research story with us!
Thank you for the opportunity to communicate with you and readers!
FitzGerald, A. M., S. N. John, T. M. Apgar, N. J. Mantua, and B. T. Martin. 2021. Quantifying thermal exposure for migratory riverine species: Phenology of Chinook salmon populations predicts thermal stress. Glob Chang Biol 27:536-549.
Isaak, D. J., S. J. Wenger, E. E. Peterson, J. M. Ver Hoef, D. E. Nagel, C. H. Luce, S. W. Hostetler, J. B. Dunham, B. B. Roper, S. P. Wollrab, G. L. Chandler, D. L. Horan, and S. Parkes-Payne. 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 WR020969.
Jackson, F. L., R. J. Fryer, D. M. Hannah, C. P. Millar, and I. A. Malcolm. 2018. A spatio-temporal statistical model of maximum daily river temperatures to inform the management of Scotland’s Atlantic salmon rivers under climate change. Science of the Total Environment 612:1543-1558.
Siegel, J. E., and C. J. Volk. 2019. Accurate spatiotemporal predictions of daily stream temperature from statistical models accounting for interactions between climate and landscape. PeerJ 7:e7892.
About the authors
Beyond predicting stream temperature, Jared Siegel is interested in examining the interaction between environmental and human factors that impact the life history and survival of Pacific salmon. He currently works on fish passage projects with PACE Engineers.
Aimee Fullerton works for NOAA’s Northwest Fisheries Science Center, researching how to best support recovery of Pacific salmon, with a focus on freshwater ecosystems. She is also very interested in how science can improve decision-making.
Alyssa FitzGerald is an Assistant Project Scientist at the University of California, Santa Cruz, and a NOAA Southwest Fisheries Science Center affiliate. FitzGerald’s research focuses on the impacts of water temperature and other environmental factors on Pacific salmon survival, with the goal of reducing mortality induced by anthropogenic causes, such as climate change and non-native predators.
Damon Holzer works for NOAA’s Northwest Fisheries Science Center, focusing on the application of spatial sciences for salmon recovery and habitat restoration efforts. He is particularly interested in devising creative and practical strategies for utilizing geospatial data in habitat modeling, analysis, and visualization projects.
Chris Jordan works for NOAA’s Northwest Fisheries Science Center, researching the physical and biological processes that form and maintain healthy riverscapes. Chris’s work focuses on supporting natural resource management decision making around freshwater habitat restoration for ESA listed salmonids across salmon country.