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        <parTitl xml:lang="en">Myrstener et al. (2025) Downstream temperature effects of boreal forest clearcutting vary with riparian buffer width - Data and Code</parTitl>
        <IDNo agency="SND">doi-10-17045-sthlmuni-27188004-0</IDNo>
        <IDNo agency="DOI">https://doi.org/10.17045/STHLMUNI.27188004</IDNo>
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        <producer xml:lang="en" abbr="SND">Swedish National Data Service</producer>
        <producer xml:lang="sv" abbr="SND">Svensk nationell datatjänst</producer>
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      <holdings URI="https://doi.org/10.17045/STHLMUNI.27188004">Landing page</holdings>
    </citation>
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    <citation>
      <titlStmt>
        <titl xml:lang="sv"></titl>
        <parTitl xml:lang="en">Myrstener et al. (2025) Downstream temperature effects of boreal forest clearcutting vary with riparian buffer width - Data and Code</parTitl>
        <IDNo agency="SND">doi-10-17045-sthlmuni-27188004-0</IDNo>
        <IDNo agency="DOI">https://doi.org/10.17045/STHLMUNI.27188004</IDNo>
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        <AuthEnty xml:lang="en" affiliation="Stockholm University">Greiser, Caroline</AuthEnty>
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        <distrbtr xml:lang="en" abbr="SND" URI="https://snd.se">Swedish National Data Service</distrbtr>
        <distrbtr xml:lang="sv" abbr="SND" URI="https://snd.se">Svensk nationell datatjänst</distrbtr>
        <distDate xml:lang="en" date="2025-02-17" />
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      <abstract xml:lang="en" contentType="abstract">Please read the readme.txt !

This depository contains raw and clean data (.csv),
as well as the R-scripts (.r) that process the data, create the plots and the models.

We recommend to go through the R-scripts in their chronological order.

Code was developed in the R software:

R version 4.4.1 (2024-06-14 ucrt) -- "Race for Your Life"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64


****** List of files ********************************

- Data

---raw

72 files from 72 Hobo data loggers

names: site_position_medium.csv

example: "20_20_down_water.csv" (site = 20, position = 20 m downstream, medium = water)

---clean

site_logger_position_medium.csv list of all sites, their loggers, their position and medium in which they were placed

loggerdata_compiled.csv all raw logger data (see above) compiled into one dataframe, for column names see below

Daily_loggerdata.csv all data aggregated to daily mean, max and min values, for column names see below

CG_site_distance_pairs.csv all logger positions for each stream and their pairwise geographical distance in meters

Discharge_site7.csv Discharge data for the same season as logger data from a reference stream

buffer_width_eniro_CG.csv measured and averaged buffer widths for each of the studied streams (in m)

- Scripts

01_compile_clean_loggerdata.r

02_aggregate_loggerdata.r

03_model_stream_temp_summer.r

03b_model_stream_temp_autumn.r

04_calculate_warming_cooling_rates_summer.r

04b_calculate_warming_cooling_rates_autumn.r

05_model_air_temp_summer.r

05b_model_air_temp_autumn.r

06_plot_representative_time_series_temp_discharge.r

****** Column names ********************************

Most column names are self explaining, and are also explained in the R code.

Below some detailed info on two dataframes (.csv)
- the column names are similar in other csv files

File "loggerdata_compiled.csv" [in Data/clean/ ]

"Logger.SN" Logger serial number

"Timestamp" Datetime, YYYY-MM-DD HH:MM:SS

"Temp" temperature in °C

"Illum" light in lux

"Year" YYYY

"Month" MM

"Day" DD

"Hour" HH

"Minute" MM

"Second" SS

"tz" time zone

"path" file path

"site" stream/site ID

"file" file name

"medium" "water" or "air"

"position" one of 6 positions along the stream: up, mid, end, 20, 70, 150

"date" YYYY-MM-DD

File "Daily_loggerdata.csv" [in Data/clean/ ]

"date" ... (see above)

"Logger.SN" Logger serial number

"mean_temp" mean daily temperature

"min_temp" minimum daily temperature

"max_temp" maximum daily temperature

"path" ...

"site" ...

"file" ...

"medium" ...

"position" ...

"buffer" one of 3 buffer categories: no, thin, wide

"Temp.max.ref" maximum daily temperature of the upstream reference logger

"Temp.min.ref" minimum daily temperature of the upstream reference logger

"Temp.mean.ref" mean daily temperature of the upstream reference logger

"Temp.max.dev" max. temperature difference to upstream reference

"Temp.min.dev" min. temperature difference to upstream reference

"Temp.mean.dev" mean temperature difference to upstream reference

Paper abstract:

Clearcutting increases temperatures of forest streams, and in temperate zones, the effects can extend far downstream. Here, we studied whether similar patterns are found in colder, boreal zones and if riparian buffers can prevent stream water from heating up. We recorded temperature at 45 locations across nine streams with varying buffer widths. In these streams, we compared upstream (control) reaches with reaches in clearcuts and up to 150 m downstream. In summer, we found daily maximum water temperature increases on clearcuts up to 4.1 °C with the warmest week ranging from 12.0 to 18.6 °C. We further found that warming was sustained downstream of clearcuts to 150 m in three out of six streams with buffers &lt; 10 m. Surprisingly, temperature patterns in autumn resembled those in summer, yet with lower absolute temperatures (maximum warming was 1.9 °C in autumn). Clearcuts in boreal forests can indeed warm streams, and because these temperature effects are propagated downstream, we risk catchment-scale effects and cumulative warming when streams pass through several clearcuts. In this study, riparian buffers wider than 15 m protected against water temperature increases; hence, we call for a general increase of riparian buffer width along small streams in boreal forests.</abstract>
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    </method>
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      <useStmt>
        <restrctn xml:lang="en">Access to data through an external actor. </restrctn>
        <restrctn xml:lang="sv">Åtkomst till data via extern aktör. </restrctn>
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    </dataAccs>
    <othrStdyMat />
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