This documentation file was generated on 2024-01-24 by Katie A. Wampler ------------------- # GENERAL INFORMATION ------------------- 1. Title of Dataset Data and scripts describing dissolved organic carbon concentrations across a stream network in Oregon following the 2020 Holiday Farm Wildfire 2. Creator Information Name: Katie A. Wampler Institution: Oregon State University College, School or Department: Forest Engineering, Resources and Management Address: 380 Peavy Hall, Oregon State University, Corvallis, OR 97333 Email: katie.wampler@oregonstate.edu ORCID: 0000-0002-5584-7554 Role: Data processing, data collection and curation, formal analysis Name: Kevin D. Bladon Institution: Oregon State University College, School or Department: Forest Engineering, Resources and Management Address: 321 Richardson Hall, Oregon State University, Corvallis, OR 97333 Email: kevin.bladon@oregonstate.edu ORCID: 0000-0002-4182-6883 Role: Funding acquisition, resources, supervision Name: Allison Myers-Pigg Institution: Pacific Northwest National Lab College, School or Department: Marine and Coastal Research Laboratory Address: 1529 W Sequim Bay Rd, Sequim, WA 98382 Email: allison.myers-pigg@pnnl.gov Role: Funding acquisition, resources, supervision 4. Contact Information Name: Katie A. Wampler Institution: Oregon State University College, School or Department: Forest Engineering, Resources and Management Address: 380 Peavy Hall, Oregon State University, Corvallis, OR 97333 Email: katie.wampler@oregonstate.edu ORCID: 0000-0002-5584-7554 Name: Kevin D. Bladon Institution: Oregon State University College, School or Department: Forest Engineering, Resources and Management Address: 321 Richardson Hall, Oregon State University, Corvallis, OR 97333 Email: kevin.bladon@oregonstate.edu ORCID: 0000-0002-4182-6883 5. Publisher Oregon State University ------------------- CONTEXTUAL INFORMATION ------------------- 1. Abstract for the dataset In 2020, the Holiday Farm Wildfire burned ~18 % of the McKenzie sub-basin in Oregon, USA. To investigate the impact of the wildfire on in-stream dissolved organic carbon (DOC) concentrations, we collected water samples from 129 stream sites within the McKenzie sub-basin stream network over four distinct seasonal wetness conditions (wetting, wet, drying, dry) between November 2022 and September 2023. This data was used to create spatial network models to model DOC concentrations across the stream network. This data package consists of (1) a spreadsheet spreadsheet containing DOC concentrations, landscape characteristics, and site information for the stream sites within the McKenzie sub-basin, OR, USA. (2) A spatial stream network (SSN) object developed for the McKenzie sub-basin from the proceeding DOC and landscape data. (3) Scripts written in R used to process, analyze, and report our findings from this data. This data package is associated with the publication "The influence of burn severity on dissolved organic carbon concentrations across a stream network differs based on seasonal wetness conditions post-fire" submitted to Biogeosciences (Wampler et al. 2024). 2. Date of data collection: 2022-11-01 to 2023-09-11 3. Geographic location of data collection: The McKenzie sub-basin (HUC 17090004), Oregon, USA (44.508, 43.859, -123.106, -121.768) 4. Funding sources that supported the collection of the data: Funding to support collection of this data set was provided by the U.S. Forest Service agreement numbers 22-JV-11261952-071 and 23-JV-11261954-057 and from the US Department of Energy, Office of Science, Biological and Environmental Research, as part of the Environmental System Science (ESS) Program to the River Corridors Science Focus Area at the Pacific Northwest National Laboratory (PNNL). PNNL is operated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data This work is licensed under a Creative Commons Attribution - NonCommerical 4.0 International License 2. Links to publications related to the dataset: Wampler, K. A., Bladon, K. D., & Myers-Pigg, A. N. (2024). The influence of burn severity on dissolved organic carbon concentrations across a stream network differs based on seasonal wetness conditions post-fire. EGUsphere, 1–40. https://doi.org/10.5194/egusphere-2024-273. 3. Recommended citation for the data: Wampler, K.A.; Bladon, K.D.; Myers-Pigg, A. (2024) Data and scripts describing dissolved organic carbon concentrations across a stream network in Oregon following the 2020 Holiday Farm Wildfire [Data set]. Oregon State University. 4. Dataset Digital Object Identifier (DOI) https://doi.org/10.7267/zc77sz60m -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Dissolved Organic Carbon Data Collection- We selected 129 stream sites: 65 sites upstream of the Holiday Farm fire, 54 sites within the burn perimeter, and 10 sites downstream of the fire. To facilate spatial stream network modeling, we chose sites near confluences where we could sample upstream and downstream from a tributary. We aimed to sample each site four times across the year, during four distinct seasonal wetness conditions. We sampled on 2022-11-01 during one of the first storms of the hydrologic year as the basin was rewetting (wetting), on 2023-03-13 during the winter as the basin was relatively wet (wet), on 2023-06-11 during early summer as the basin was starting to dry (drying), and on 2023-09-11 at the end of the summer when the basin was quite dry (dry). However, due to access and timing constraints, not every site was sampled during each sampling campaign. Samples were analyzed for dissolved organic carbon within a month of collection using a Shimadzu TOC-VCSH Combustion Analyzer. 2. Landscape Characteristics Collection- To link our sites to landscape characteristics we used USGS streamstats batch processor to generate the watershed contributing area polygons for each site. Those polygons were then used in R with landscape raster files to find the average value across the watershed area for each site. See below for citations for specific landscape characteristics. 3. Spatial Stream Network Object- A spatial stream network model object for the McKenzie stream network was created in ArcMap using the STARS tool (Peterson, E., & Ver Hoef, J. M. (2014). STARS: An ArcGIS Toolset Used to Calculate the Spatial Information Needed to Fit Spatial Statistical Models to Stream Network Data. Journal of Statistical Software, 56, 1–17. https://doi.org/10.18637/jss.v056.i02). We use the stream network from the National Stream Internet Project to start (Nagel, D. E., Wollrab, S., Parkes-Payne, S., Peterson, E., Isaak, D., & Ver Hoef, J. M. (n.d.). National Stream Internet hydrography datasets for spatial-stream-network (SSN) analysis. [dataset]. Rocky Mountain Research Station, U.S. Forest Service Data Archive. https://www.fs.usda.gov/rm/boise/AWAE/projects/NationalStreamInternet/NSI_network.html). --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: McKenzie_DOC_SiteData_2022_2023.csv Short description: A table containing information about the sites sampled with the McKenzie sub-basin for dissolved organic carbon (DOC) including the DOC results, landscape characteristics of each site used in spatial stream network modeling. B. Filename: lsn.ssn.zip Short description: A zip file containing the raw .ssn file used to build the spatial stream network models in R. Contained within the zip file are 5 shape files: (1) edges.shp - the stream network, (2) sites.shp - the sampling locations and landscape attributes, (3) preds.shp - a set of prediction points along the stream network at a 1 km resolution, (4) preds_gate.shp - a set of prediction points along Gate Creek tributary at a 100 m resolution, (5) preds_quartz.shp - a set of prediction points along Quartz Creek tributary at a 100 m resolution. For additonal information about the .ssn file structure see Ver Hoef et al. 2014 (Ver Hoef, J. M., Peterson, E., Clifford, D., & Shah, R. (2014). SSN: An R Package for Spatial Statistical Modeling on Stream Networks. Journal of Statistical Software, 56, 1–45. https://doi.org/10.18637/jss.v056.i03). C. Filename: McKenzie_DOC_SSN_Code.R Short description: An R script containing all the code used to generate the results reported in Wampler et al. (2024). 2. Relationship between files: Both McKenzie_DOC_SiteData_2022_2023.csv and lsn.ssn.zip are the required datasets to run McKenzie_DOC_SSN_Code.R 3. Formats .csv, .zip/.ssn (Ver Hoef, J. M., Peterson, E., Clifford, D., & Shah, R. (2014). SSN: An R Package for Spatial Statistical Modeling on Stream Networks. Journal of Statistical Software, 56, 1–45. https://doi.org/10.18637/jss.v056.i03), .R ----------------------------------------- TABULAR DATA-SPECIFIC INFORMATION FOR: McKenzie_DOC_SiteData_2022_2023.csv ----------------------------------------- 1. Number of variables: 22 2. Number of cases/rows: 416 3. Missing data codes: There are no missing data in the table 4. Variable List A. Name: Site Data Type: character Description: The unique identifier for each sampling location in the McKenzie sub-basin within the study, takes the form of "MCSN###" B. Name: Stream Data Type: character Description: The name of the stream associated with the site number, used to help identify the correct sampling location. C. Name: Lat Data Type: numeric Description: The latitude of the sampling location (UTM Zone 10N, WGS 84) D. Name: Long Data Type: numeric Description: The longitude of the sampling location (UTM Zone 10N, WGS 84) E. Name: BurnSev Data Type: character Description: The burn severity group of the site. This was determined based on the average dNBR value across each site's upstream contributing area and the burn severity thresholds determined by monitoring trends in burn severity (MTBS, https://www.mtbs.gov/) for the 2020 Holiday Farm Wildfire. The thresholds are unburned: <=40, low: 40-320, moderate: 320-660, high: >660. F. Name: PerBurn Data Type: numeric Description: An estimated percentage of each site's upstream area that burned in the 2020 Holiday Farm Wildfire. Data is based on the burn severity maps from MTBS (https://www.mtbs.gov/) G. Name: Date Data Type: date Description: The date the sample was collected on. H. Name: TimePST Data Type: time Description: The time the water sample was collected at using a 24h clock in Pacific Standard Time. I. Name: AREA Data Type: numeric Description: The area up the upstream contributing area in km2 for each site. Calculated using basin delination from USGS streamstats (U.S. Geological Survey. (2019). The StreamStats program [Computer software]. https://streamstats.usgs.gov/ss/). J. Name: SEASON Data Type: character Description: The season the sample was collected during (wetting, wet, drying, dry). K. Name: DOC_mgL Data Type: numeric Description: The measured dissolved organic carbon (DOC) concentration measured at the site on the specified date. DOC was determined via Shimadzu TOC-VCSH Combustion Analyzer. L. Name: DNBR Data Type: numeric Description: The average difference in normalized burn ratio (dNBR) across each site's upstream contributing area. dNBR data was obtained from MTBS (MTBS Project. (2021). MTBS Data Access: Fire Level Geospatial Data. USDA Forest Service/U.S. Geological Survey. http://mtbs.gov/direct-download). M. Name: ARIDITY Data Type: numeric Description: Average aridity index (Precipitation/Evapotranspiration) across each site's basin area. Raster data was sourced from Trabucco, A., & Zomer, R. (2019). Global Aridity Index and Potential Evapotranspiration (ET0) Climate Database v2 [dataset]. https://doi.org/10.6084/m9.figshare.7504448.v3. N. Name: AWC Data Type: numeric Description: The depth averaged average amount (cm/cm) of water the soils across each site's basin area can store that is available for plants. Raster data was sourced from USDA NRCS. (2016). Oregon SSURGO STATSGO Soils Compilation [dataset]. https://spatialdata.oregonexplorer.info/geoportal/details;id=668a7a8824e5456797bec858cc14ca74. O. Name: BFI Data Type: numeric Description: The average percentage of streamflow attributed to groundwater discharge averaged across each site's basin area. Raster data sourced from U.S. Geological Survey. (2003). Base-flow index grid for the conterminous United States [dataset]. https://water.usgs.gov/GIS/metadata/usgswrd/XML/bfi48grd.xml. P. Name: ELEV Data Type: numeric Description: The average elevation averaged across each site's basin area in meters. Raster data sourced from U.S. Geological Survey. (2000). Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global [dataset]. https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-shuttle-radar-topography-mission-srtm-1-arc?qt-science_center_objects=0#qt-science_center_objects. Q. Name: FOREST Data Type: numeric Description: The percent of the basin area classified as deciduous, evergreen, or mixed forest. Raster data sourced from Dewitz, J. (2021). National Land Cover Database (NLCD) 2019 Products [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P9KZCM54. R. Name: PRECIP Data Type: numeric Description: Average annual precipitation (mm) across each site's basin area, based on 30-year normals. Raster data sourced from PRISM Climate Group. (2012). 30-Year Normals [dataset]. Oregon State University. http://prism.oregonstate.edu. S. Name: CLAY Data Type: numeric Description: Depth averaged weight percentage of clay particles in soil averaged across each site's basin area. Raster data sourced from Oregon SSURGO STATSGO Soils Compilation [dataset]. https://spatialdata.oregonexplorer.info/geoportal/details;id=668a7a8824e5456797bec858cc14ca74. T. Name: SOIL_OM Data Type: numeric Description: Depth averaged weight percentage of decomposed plant and animal residue in the soil averaged across each site's basin area. Raster data sourced from Oregon SSURGO STATSGO Soils Compilation [dataset]. https://spatialdata.oregonexplorer.info/geoportal/details;id=668a7a8824e5456797bec858cc14ca74. U. Name: SOIL_PH Data Type: numeric Description: Depth averaged pH of the soil determined using the 1:1 soil-water ratio method averaged across each site's basin area. Raster data sourced from Oregon SSURGO STATSGO Soils Compilation [dataset]. https://spatialdata.oregonexplorer.info/geoportal/details;id=668a7a8824e5456797bec858cc14ca74. V. Name: TWI Data Type: numeric Description: A function of contributing area and slope describing the topographic controls on wetness averaged across each site's basin area. Raster data sourced from U.S. Geological Survey. (2000). Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global [dataset]. https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-shuttle-radar-topography-mission-srtm-1-arc?qt-science_center_objects=0#qt-science_center_objects. W. Name: TIME_HR Data Type: numeric Description: The time of day (decimal hours) when the sample was collected from the stream using a 24h clock. ----------------------------------------- CODE-SPECIFIC INFORMATION: ----------------------------------------- 1. Installation Install R and R Studio here: https://posit.co/download/rstudio-desktop/ 2. Requirements The code requires a number of libraries linked at the beginning of the script. Of note is a package that's required, but not available on CRAN, "thorloki", a package written by Katie A. Wampler with functions to aid in SSN analysis. This package can be installed using the line: install_github("katiewampler/thorloki") in R. This package also depends on an additional non-CRAN package "displease" which can be downloaded by running: install_github("coolbutuseless/displease"). This package also relies on the "SSN" package which since the time of analysis has been replaced by the SSN2 package. To install the "SSN" package it's recommended to install via the CRAN archive or using: install_github("jayverhoef/SSN"). 3. Usage This code is used to generate the results reported in Wampler et al. 2024. 4. Runtime requirements While the majority of the lines in the script run quite quickly, there's a single function, "best_var_str", which can take several hours to run and is best run overnight.