DOI: 10.5061/dryad.crjdfn391
title: Data from: Statistical stream temperature modelling with SSN and INLA: An introduction for conservation practitioners

description: 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 (&gt;
 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.
description: # 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](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/](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: &gt; 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](https://doi.org/10.5061/dryad.crjdfn391) * Corresponding publication: &gt; 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, 81(4), 417-232. ## 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](https://orcid.org/0009-0009-8075-493X) * Email: [dan.struthers@pc.gc.ca](mailto:dan.struthers@pc.gc.ca) * Alternate Email: [danstruthers88@gmail.com](mailto: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](https://orcid.org/0000-0003-0655-4197) * Email: [mark.taylor@pc.gc.ca](mailto:mark.taylor@pc.gc.ca) * Address: e-mail preferred * Contributor ORCID IDs: * Daniel P. Struthers: [https://orcid.org/0009-0009-8075-493X](https://orcid.org/0009-0009-8075-493X) * Lee F.G. Gutowsky: [https://orcid.org/0000-0003-1244-9465](https://orcid.org/0000-0003-1244-9465) * Tim C.D. Lucas: [https://orcid.org/0000-0003-4694-8107](https://orcid.org/0000-0003-4694-8107) * Neil J. Mochnacz: [https://orcid.org/0000-0002-3052-0301](https://orcid.org/0000-0002-3052-0301) * Christopher M. Carli:[https://orcid.org/0000-0001-6304-8755](https://orcid.org/0000-0001-6304-8755) * Mark K. Taylor: [https://orcid.org/0000-0003-0655-4197](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 * r-script can be found on zenodo: click [here](https://zenodo.org/records/7942855) ## 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 * r-script can be found on zenodo: click [here](https://zenodo.org/records/7942855) --- END OF README