Data from: Statistical stream temperature modelling with SSN and INLA: an introduction for conservation practitioners
Data files
Jan 23, 2024 version files 1.28 MB
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bnp_data_June2022_V5.csv
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bnp_data_preds_June2022_V5.csv
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edges_buffer_100m.zip
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lsn.ssn.zip
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README.md
Abstract
Statistical stream temperature models can predict the fine-scale spatial distribution of water temperatures and guide species recovery and habitat restoration efforts. However, stream temperature modelling is complicated by spatial autocorrelation arising from non-independence data collected within dendritic networks. We used data from miniature sensors deployed in Canadian Rocky Mountain streams to develop and validate two statistical stream temperature modelling techniques that account for spatial autocorrelation. The first was based on spatial steam network models (SSNs) specifically developed to account for spatial autocorrelation in dendritic stream networks. The second used integrated nested Laplace approximation (INLA) that accounts for spatial autocorrelation but was not designed to address anisotropic stream network data. We evaluated the best-fitted SSN and INLA models using leave-one-out cross validation from the data collected along the stream network. Both modelling techniques had similar RMSE and MAE (near 1oC) and r2 (> 0.6) values, and proved flexible with respect to implementation; however, the SSN models required more preprocessing steps before incorporating spatially correlated random errors. We provide practical advice and open-access data and r-script to help non-experts develop statistical stream temperature models of their own.
README: Reference Information
Provenance for this README
- File name: README_Dataset-AugStreamTempBanff_v0.1.0.txt
- Authors: Daniel P. Struthers
- Other contributors: Lee F.G. Gutowsky, Tim C.D. Lucas, Neil J. Mochnacz; Christopher M. Carli, Mark K. Taylor
- Date created: 2024-01-23
- Date modified: 2024-01-23
Dataset Version and Release History
Current Version:
- Number: 1.0.0
- Date: 2024-01-23
- Persistent identifier: DOI: 10.5061/dryad.5bk4c
- Summary of changes: n/a
Embargo Provenance: n/a
- Scope of embargo: n/a
- Embargo period: n/a
Dataset Attribution and Usage
Dataset Title: Data for the article "Statistical stream temperature modelling with SSN and INLA: an introduction for conservation practitioners"
Persistent Identifier: https://doi.org/10.5061/dryad.5bk4c
Dataset Contributors:
- Creators: Daniel P. Struthers, Mark K. Taylor
Date of Issue: 2024-01-23
Publisher: Parks Canada, Banff National Park
License: Use of these data is covered by the following license:
- Title: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
- Specification: https://creativecommons.org/publicdomain/zero/1.0/; the authors respectfully request to be contacted by researchers interested in the re-use of these data so that the possibility of collaboration can be discussed.
Suggested Citations:
- Dataset citation: > Struthers, D.P., and Taylor, M.K. 2023. Data for the article "Statistical stream temperature modelling with SSN and INLA: an introduction for conservation practitioners"", Dryad, Dataset, https://doi.org/10.5061/dryad.crjdfn391
- Corresponding publication: > Struthers, D.P., Gutowsky, L.F.G., Lucas, T.C.D., Mochnacz, N.J., Carli, C.M., and Taylor, M.K. 2023. Statistical stream temperature modelling with SSN and INLA: an introduction for conservation practitioners. Canadian Journal of Fisheries and Aquatic Science. IN REVIEW.
Contact Information
Name: Daniel P. Struthers
Affiliations: Parks Canada Agency, Banff National Park, Banff, AB, Canada
ORCID ID: https://orcid.org/0009-0009-8075-493X
Email: dan.struthers@pc.gc.ca
Alternate Email: danstruthers88@gmail.com
Address: e-mail preferred
Alternative Contact: Mark K. Taylor
- Name: Mark Taylor
- Affiliations: Parks Canada Agency, Banff National Park, Banff, AB, Canada
- ORCID ID: https://orcid.org/0000-0003-0655-4197
- Email: <mark.taylor@pc.gc.ca>
- Address: e-mail preferred
Contributor ORCID IDs:
- Daniel P. Struthers: https://orcid.org/0009-0009-8075-493X
- Lee F.G. Gutowsky: https://orcid.org/0000-0003-1244-9465
- Tim C.D. Lucas: https://orcid.org/0000-0003-4694-8107
- Neil J. Mochnacz: https://orcid.org/0000-0002-3052-0301
- Christopher M. Carli:https://orcid.org/0000-0001-6304-8755
- Mark K. Taylor: https://orcid.org/0000-0003-0655-4197
Additional Dataset Metadata
Dates and Locations
Dates of data collection: Field data collected in August 2018
Geographic locations of data collection: Fieldwork conducted in Banff National Park, Alberta, Canada (see publication for more details)
Methodological Information
- Methods of data collection/generation: see manuscript for details
Data and File Overview
Summary Metrics
- File count: 6
- Total file size: 1345 kB
- Range of individual file sizes: 13kB - 883 kB
- File formats: .csv, .ssn, .R, .shp
Table of Contents
- lsn.ssn.zip
- bnp_data_June2022_V5.csv
- bnp_data_preds_June2022_V5.csv
- edges_buffer_100m.zip
- INLA_R-Script.R
- SSN_R-Script.R
Setup
Unpacking instructions: unzip .zip folders to working directory (e.g., C: drive)
Recommended software/tools: RStudio Version 1.4.1717, R version 4.1.0
File/Folder Details
Details for: lsn.ssn.zip
Description: The .ssn object contains multiple objects to store the spatial, attribute, and topological information of the landscape networtk (LSN) in order to fit SSN models to these data. There are three shapefiles - edges, sites, and preds - to store the spatial, attribute, and topological relationships. The netID1.dat object provides the location information of each edge (rid) within the stream network (binaryID). The lsn.ssn is imported into R enviornemnt to fit spatial stream network (SSN) models (see SSN_R-Script.R file)
Format(s): .ssn
Size(s): 364 kB
Details for: bnp_data_June2022_V5.csv
Description: a comma-delimited file containing the August Mean Stream Temperature (AugTw) recorded in Banff National Park in 2018. The .csv file was exported from R while fitting SSN models. The .csv file can be imported back into R to fit INLA models (see INLA_R-script.R file).
Format(s): .csv
Size(s): 13 kB
Dimensions: 110 rows x 15 columns
Variables:
- ID: Unique Object ID for each sample point generated when importing these data into ArcGIS
- LoggerID: Unique ID for each temperature logger installed in the project area
- S_N: Manufacturer serial number of the temperature logger
- Easting: UTM grid coordinates expressed as a distance in meters to the east (UTM Zone: 11U)
- Northing: UTM grid coordinates expressed as a distance in meters to the North (UTM Zone: 11U)
- WSf: Name of the fourth-order watershed that the temperature logger was installed in.
- Waterbody: Name of the watercourse that the temperature logger was installed in.
- Year_: Installation year for the temperature logger
- WaterTemp: August mean stream temperature (AugTw) measured at each temperature logger site in 2018.
- LE: Lake effect (0 = no, 1 = yes)
- Elev: elevation (meters) at location of temperature sensor
- RSlope: Reach Slope (%) of rid
- h2oAreaKm2: upstream watershed conbributing area (square km)
- logRCA: upstream watershed conbributing area (square km) - log-10 transformed
- HUC10: hydrologic unit code level-10 watershed scale
Details for: bnp_data_preds_June2022_V5.csv
Description: a comma-delimited file containing the points spaced at 1-km intervals along the stream network where predictions were made using the SSN and INLA models (see INLA_R-script.R file).
Format(s): .csv
Size(s): 158 kB
Dimensions: 642 rows x 13 columns
Variables:
- ID: Unique Object ID for each prediction point populated in ArcGIS when creating the shapefile.
- Elev: point elevation (meters) at location of prediction point
- RSlope: Reach Slope (%) of stream segment that the point coincides with.
- WSf: Name of the fourth-order watershed that the prediction point is located in.
- Easting: UTM grid coordinates expressed as a distance in meters to the east (UTM Zone: 11U)
- Northing: UTM grid coordinates expressed as a distance in meters to the North (UTM Zone: 11U)
- LE: Lake effect (0 = no, 1 = yes)
- h2oAreaKm2: upstream watershed conbributing area (square km)
- logRCA: upstream watershed conbributing area (square km) - log-10 transformed
- HUC10: hydrologic unit code level-10 watershed scale
- locID: location ID
- netID: network identifier assigned to the edges, sites, and preds attribue tables.
- pid: point ID
Details for: edges_buffer_100m.zip
Description: a shapefile containing the 100-m buffer polygon generated from the stream network. This polygon is used to fit a barrier model with INLA (see INLA_R-Script.R file).
Format(s): .shp
Size(s): 830.29 kB
Details for: INLA_R-Script.R
Description: an R-script used to fit INLA models to the AugTw observations recorded in Banff National Park.
Format(s): .R
Size(s): 32.84 kB
Details for: SSN_R-Script.R
Description: an R-script used to fit SSN models to the AugTw observations recorded in Banff National Park.
Format(s): .R
Size(s): 16.06 kB
END OF README
Methods
Please see the README document ("README_Dataset-AugStreamTempBanff_v0.1.0.md") and the accompanying peer-reviewed article: Struthers, D.P., Gutowsky, L.F.G., Lucas, T.C.D., Mochnacz, N.J., Carli, C.M., and Taylor, M.K. 2023. Statistical stream temperature modelling with SSN and INLA: an introduction for conservation practitioners. Canadian Journal of Fisheries and Aquatic Science. IN REVIEW.