Major changes in fish thermal habitat diversity in Canada’s Arctic lakes due to climate change

Gillis, Daniel1 ; Minns, Charles1; Campana, Steven2; Shuter, Brian1

Published Feb 26, 2024 on Dryad. https://doi.org/10.5061/dryad.cvdncjt8g

Cite this dataset

Gillis, Daniel; Minns, Charles; Campana, Steven; Shuter, Brian (2024). Major changes in fish thermal habitat diversity in Canada’s Arctic lakes due to climate change [Dataset]. Dryad. https://doi.org/10.5061/dryad.cvdncjt8g

Abstract

Climate warming is a major disruptor of fish community structure globally. We use large-scale geospatial analyses of 447,077 Canadian Arctic lakes to predict how climate change would impact lake thermal habitat diversity across the Arctic landscape. Increases in maximum surface temperature (+2.4–6.7 °C), ice-free period (+14–38 days), and thermal stratification presence (+4.2–18.9%) occur under all climate scenarios. Lakes, currently fishless due to deep winter ice, open up; many thermally uniform lakes become thermally diverse. Resilient coldwater habitat supply is predicted; however, thermally diverse lakes shift from providing almost exclusively coldwater habitat to providing substantial coolwater habitat and previously absent warmwater habitat. Across terrestrial ecozones, most lakes exhibit major shifts in thermal habitat. The prevalence of thermally diverse lakes more than doubles, providing refuge for coldwater taxa. Ecozone-specific differences in the distribution of thermally diverse and thermally uniform lakes require different management strategies for adapting fish resource use to climate change.

README

This README file was generated on 2024-02-09 by Daniel P. Gillis.

GENERAL INFORMATION

Title of Dataset: Major changes in fish thermal habitat diversity in Canada’s Arctic lakes due to climate change
Author Information
A. Corresponding Author:
Name: Daniel P. Gillis
Institution: 1) University of Toronto, Toronto, ON, Canada 2) Fisheries and Oceans Canada, Vancouver, BC
Email: daniel.gillis@mail.utoronto.ca
B. Co-Author 1:
Name: Charles K. Minns
Institution: University of Toronto, Toronto, ON, Canada
C. Co-Author 2:
Name: Steven E. Campana
Institution: University of Iceland, Reykjavik, Iceland
D. Co-Author 3:
Name: Brian J. Shuter
Institution: University of Toronto, Toronto, ON, Canada
Geographical location: Canadian Arctic. Focus of analysis is on areas at least 60 degrees N latitude.
Funding sources:
A. This work was supported by grants from the Canadian Network for Aquatic Ecosystems Services and the Discovery Grant program of the Natural Sciences and Engineering Research Council of Canada.
B. Gerald Black played a crucial role in developing the Arctic lake database. His work was supported by the Nunavut Wildlife Management Board, Fisheries and Oceans Canada, US National Science Foundation grant OCE-9985884 and the University of Iceland.
Recommended citation for this dataset: Gillis, D. G., Minns, C. K., Campana, S. E., Shuter, B. J. (2024). Data from: Major changes in fish thermal habitat diversity in Canada’s Arctic lakes due to climate change. Dryad Digital Repository. https://doi.org/10.5061/dryad.cvdncjt8g

SHARING/ACCESS INFORMATION

Licenses/restrictions placed on the data: CC0 1.0 Universal (CC0 1.0) Public Domain
Links to publications that cite or use the data:

Gillis, D. G., Minns, C. K., Campana, S. E., Shuter, B. J. (2024). Major changes in fish thermal habitat diversity in Canada’s Arctic lakes due to climate change. Communications Earth & Environment.

Links to other publicly accessible locations of the data: None
Links/relationships to ancillary data sets: Yes, see ##DATA & FILE OVERVIEW
Was data derived from another source? Yes, see ##DATA & FILE OVERVIEW
A. If yes, list source(s):
see ## Sharing/Access information, Arctic GIS lake database

##DATA & FILE OVERVIEW

Script, file and output list and their relationships:

Each script is introduced by name, in order. They are numbered in the order in which they are intended to be used
Each file is listed, in order of appearance. They are labelled by a number, indicating the script that it was first involved in, followed by a capital letter, which indicates the place in the sequence which it appears (e.g., file 1B is the second file that appears in script 1)
Each file is listed, in order of appearance. They are labelled by a number, indicating the script that it was first involved in, followed by a lowercase letter, which indicates the place in the sequence which it appears (e.g., output 1b is the second output that appears in script 1)
Each file is included in the Dryad repository: these are files that are not created by the scripts, they are the data that form the basis of the analysis
Each output is not included in the Dryad repository: these outputs can be created by running the scripts in order. The following information highlights the dependencies among scripts to complete the analysis
External files (prefaced with "external: ") for which they may not be compatible with the CC0 licence type required by Dryad are indicated by their filename. Additionally, they may be easily accessible online and thus sharing in the repository would be duplicitive. See Sharing/Access Information section for more information on external dataset access. Filenames in the scripts are listed under the appropriate section (e.g., geomet-climate-DCS.TM.HISTO.ENS.ABS_PCTL50_1986_01_to_1994_05.tif is the filename of Government of Canada climate data)
If a file or script is used in a second, third, or subsequent script, it is indented with the hyphen "-" symbol the number of times it has appeared (e.g., one hyphen indent "-" for its second appearance, two hyphen indents "--" for its third)
When a file or output is used for a subsequent script, it retains the alphanumerical label, which indicates the script that it first appears in (the number) and what order in that script it appeared in (the letter) (e.g., "rlakes3pt1km_latlong_zmean.csv" is created in script ##1 and appears again in script ##3. Therefore, in script ##3, it appears intended with one hyphen, as follows "-1a) rlakes3pt1km_latlong_zmean.csv")
The scripts that figures and tables are created in are listed below the files and outputs for clarity (see "##Figures, tables, and their relationships to scripts, in the order that they are created"")
Files and outputs that are included in the repository are preceded by an asterisk *

Files, outputs, and their relationships to scripts
##1_Arctic_Proj_Lake_Dataset_Config.R
*1A) rlakes3pt1km.csv
*1B) lakeslatlong.csv
1a) rlakes3pt1km_latlong_zmean.csv

##2_Arctic_Proj_Lake_Morphometry_Ground_Truthed.R
2A) external: Ground_Truthed_Lake_Morphometry.csv
*2B) external: Ground_Truthed_Lake_Morphometry_Prelim_Eco.csv
2a) external: Ground_Truthed_Lake_Morphometry_Eco_Cleaned.csv

##3_Arctic_Proj_Lake_Morphometry_Config.R
-1a) rlakes3pt1km_latlong_zmean.csv
*3A) lakesmeandepth.csv
-2a) external: Ground_Truthed_Lake_Morphometry_Eco_Cleaned.csv
*3B) rlakes3pt1km_lat_long_zmean_ECO.csv
3a) rlakes3pt1km_latlong_zmean_pred_final.csv

##4_Arctic_Proj_Climate_Temp_Precip_Wind_Extraction_GeoTIFF.R
-3a) rlakes3pt1km_latlong_zmean_pred_final.csv
4A) external: geomet-climate-DCS.TM.HISTO.ENS.ABS_PCTL50_1986_01_to_1994_05.tif
4B) external: geomet-climate-DCS.TM.HISTO.ENS.ABS_PCTL50_1994_06_to_2002_09.tif
4C) external: geomet-climate-DCS.TM.HISTO.ENS.ABS_PCTL50_2002_10_to_2005_12.tif
4a) TM_HISTO.csv
4D) external: geomet-climate-DCS.TM.RCP45.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
4E) external: geomet-climate-DCS.TM.RCP45.ENS.ABS_PCTL50_2100_01_to_2100_12.tif
4b) TM_RCP45_2050.csv
4c) TM_RCP45_2100.csv
4F) external: geomet-climate-DCS.TM.RCP85.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
4G) external: geomet-climate-DCS.TM.RCP85.ENS.ABS_PCTL50_2100_01_to_2100_12.tif
4d) TM_RCP85_2050.csv
4e) TM_RCP85_2100.csv
4H) external: geomet-climate-DCS.PR.HISTO.ENS.ABS_PCTL50_1986_01_to_1994_05.tif
4I) external: geomet-climate-DCS.PR.HISTO.ENS.ABS_PCTL50_1994_06_to_2002_09.tif
4J) external: geomet-climate-DCS.PR.HISTO.ENS.ABS_PCTL50_2002_10_to_2005_12.tif
4f) PR_HISTO.csv
4K) external: geomet-climate-DCS.PR.RCP45.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
4L) external: geomet-climate-DCS.PR.RCP45.ENS.ABS_PCTL50_2100_01_to_2100_12.tif
4g) PR_RCP45_2050.csv
4h) PR_RCP45_2100.csv
4M) external: geomet-climate-DCS.PR.RCP85.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
4N) external: geomet-climate-DCS.PR.RCP85.ENS.ABS_PCTL50_2100_01_to_2100_12.tif
4i) PR_RCP85_2050.csv
4j) PR_RCP85_2100.csv
4O) external: geomet-climate-CMIP5.SFCWIND.HISTO.ENS.ABS_PCTL50_1986_01_to_2005_11.tif
4k) SFCWIND_HISTO.csv
4P) external: geomet-climate-CMIP5.SFCWIND.RCP45.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
4Q) external: geomet-climate-CMIP5.SFCWIND.RCP45.ENS.ABS_PCTL50_2100_01_to_2100_12.tif
4l) SFCWIND_RCP45_2050.csv
4m) SFCWIND_RCP45_2100.csv
4R) external: geomet-climate-CMIP5.SFCWIND.RCP85.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
4S) external: geomet-climate-CMIP5.SFCWIND.RCP85.ENS.ABS_PCTL50_2100_01_to_2100_12.tif
4n) SFCWIND_RCP85_2050.csv
4o) SFCWIND_RCP85_2100.csv

##5_Arctic_Proj_CRU_Lakes_To_Grids.R
5A) external: cru_ts4.01.2001.2010.tmp.dat.nc
--3a) rlakes3pt1km_latlong_zmean_pred_final.csv
5a) AllLakeGridsrlakes3pt1km_latlong_zmean_pred_final.csv
5b) UniqueGridsrlakes3pt1km_latlong_zmean_pred_final.csv

##6_Arctic_Proj_CRU_Add_Cld_to_Grids.R
-5b) UniqueGridsrlakes3pt1km_latlong_zmean_pred_final.csv
6A) external: cru_ts4.01.1981.1990.cld.dat.nc
6B) external: cru_ts4.01.1991.2000.cld.dat.nc
6C) external: cru_ts4.01.2001.2010.cld.dat.nc
6a) UGrlakes3pt1km_latlong_zmean_pred_final.cru_ts4.01.cld.1981.2010.csv
6b) CRU_cld.csv

##7_Arctic_Proj_CRU_Add_Elev_to_Grids.R
--5b) UniqueGridsrlakes3pt1km_latlong_zmean_pred_final.csv
7A) external: etopo1.nc
7a) UniqueGridsElevsrlakes3pt1km_latlong_zmean_pred_final.csv

##8_Arctic_Proj_CRU_Add_Rad_RadCld_to_Grids.R
-7a) UniqueGridsElevsrlakes3pt1km_latlong_zmean_pred_final.csv
-6b) CRU_cld.csv
8a) CRU_crad.csv

##9_Arctic_Proj_CRU_Add_Climate_Metrics_to_GridYears.R
-4a) TM_HISTO.csv
9a) TM_HISTO_added_temp_metrics.csv
-4b) TM_RCP45_2050.csv
9b) TM_RCP45_2050_added_temp_metrics.csv
-4c) TM_RCP45_2100.csv
9c) TM_RCP45_2100_added_temp_metrics.csv
-4d) TM_RCP85_2050.csv
9d) TM_RCP85_2050_added_temp_metrics.csv
-4e) TM_RCP85_2100.csv
9e) TM_RCP85_2100_added_temp_metrics.csv

##10_Arctic_Proj_Dataset_Assembly.R
---3a) rlakes3pt1km_latlong_zmean_pred_final.csv
--4a) TM_HISTO.csv
--4b) TM_RCP45_2050.csv
--4c) TM_RCP45_2100.csv
--4d) TM_RCP85_2050.csv
--4e) TM_RCP85_2100.csv
-4f) PR_HISTO.csv
-4g) PR_RCP45_2050.csv
-4h) PR_RCP45_2100.csv
-4i) PR_RCP85_2050.csv
-4j) PR_RCP85_2100.csv
-4k) SFCWIND_HISTO.csv
-4l) SFCWIND_RCP45_2050.csv
-4m) SFCWIND_RCP45_2100.csv
-4n) SFCWIND_RCP85_2050.csv
-4o) SFCWIND_RCP85_2100.csv
-9a) TM_HISTO_added_temp_metrics.csv
-9b) TM_RCP45_2050_added_temp_metrics.csv
-9c) TM_RCP45_2100_added_temp_metrics.csv
-9d) TM_RCP85_2050_added_temp_metrics.csv
-9e) TM_RCP85_2100_added_temp_metrics.csv
-5a) AllLakeGridsrlakes3pt1km_latlong_zmean_pred_final.csv
-8a) CRU_crad.csv
*10a) rlakes3pt1km_assembled.csv

##11_Arctic_Proj_Wind_atlas_weibull.R
11A) external: 60_243 10 time scale.xls
11B) external: 60_261 10 min time scale.xls
11C) external: 62_238 10 min time scale.xls
11D) external: 66_255 10 min time scale.xls
11E) external: 68_232 10 min time scale.xls
11F) external: Dan Sites 10 min time scale.xls
*11a) median_shape_1hr_df.csv

##12_Arctic_Proj_Projections.R
-*10a) rlakes3pt1km_assembled.csv
*12A) rlakes3pt1km_assembled_sample.csv
-*11a) median_shape_1hr_df.csv
12B) external: Gorham and Boyce 1989 Figure 1 5 groups.csv
12C) external: Gorham and Boyce 1989 Figure 1 Lake Points.csv
12a) rlakes3pt1km_projections.csv

##13_Arctic_Proj_Analysis_A_Batches.R
-12a) rlakes3pt1km_projections.csv
13a) A_rlakes3pt1km_projections.csv
13b) B_rlakes3pt1km_projections.csv
13c) C_rlakes3pt1km_projections.csv
13d) D_rlakes3pt1km_projections.csv
13e) E_rlakes3pt1km_projections.csv
13f) F_rlakes3pt1km_projections.csv
13g) G_rlakes3pt1km_projections.csv
13h) H_rlakes3pt1km_projections.csv
13i) I_rlakes3pt1km_projections.csv
13j) J_rlakes3pt1km_projections.csv
13k) K_rlakes3pt1km_projections.csv
13l) L_rlakes3pt1km_projections.csv
13m) M_rlakes3pt1km_projections.csv
13n) N_rlakes3pt1km_projections.csv
13o) O_rlakes3pt1km_projections.csv
13p) P_rlakes3pt1km_projections.csv
13q) Q_rlakes3pt1km_projections.csv
13r) R_rlakes3pt1km_projections.csv
13s) S_rlakes3pt1km_projections.csv
13t) T_rlakes3pt1km_projections.csv

##14_Arctic_Proj_Analysis_Lake_Volume_Cals.R
-13a) A_rlakes3pt1km_projections.csv
-13b) B_rlakes3pt1km_projections.csv
-13c) C_rlakes3pt1km_projections.csv
-13d) D_rlakes3pt1km_projections.csv
-13e) E_rlakes3pt1km_projections.csv
-13f) F_rlakes3pt1km_projections.csv
-13g) G_rlakes3pt1km_projections.csv
-13h) H_rlakes3pt1km_projections.csv
-13i) I_rlakes3pt1km_projections.csv
-13j) J_rlakes3pt1km_projections.csv
-13k) K_rlakes3pt1km_projections.csv
-13l) L_rlakes3pt1km_projections.csv
-13m) M_rlakes3pt1km_projections.csv
-13n) N_rlakes3pt1km_projections.csv
-13o) O_rlakes3pt1km_projections.csv
-13p) P_rlakes3pt1km_projections.csv
-13q) Q_rlakes3pt1km_projections.csv
-13r) R_rlakes3pt1km_projections.csv
-13s) S_rlakes3pt1km_projections.csv
-13t) T_rlakes3pt1km_projections.csv
14a) rlakes3pt1km_projections_with_volume.csv

##15_Arctic_Proj_HydroComp.R
15A) external: HydroLAKES_ECO_Spreadsheet.csv
-14a) rlakes3pt1km_projections_with_volume.csv
--2a) Ground_Truthed_Lake_Morphometry_Eco_Cleaned.csv
----3a) rlakes3pt1km_latlong_zmean_pred_final.csv

##16_Arctic_Proj_Daily_Water_Temps.R
--13a) A_rlakes3pt1km_projections.csv
16a) A_Daily_lake_temps_HISTO.csv
16b) A_Daily_lake_temps_RCP45_2050.csv
16c) A_Daily_lake_temps_RCP45_2100.csv
16d) A_Daily_lake_temps_RCP85_2050.csv
16e) A_Daily_lake_temps_RCP85_2100.csv
--13b) B_rlakes3pt1km_projections.csv
16f) B_Daily_lake_temps_HISTO.csv
16g) B_Daily_lake_temps_RCP45_2050.csv
16h) B_Daily_lake_temps_RCP45_2100.csv
16i) B_Daily_lake_temps_RCP85_2050.csv
16j) B_Daily_lake_temps_RCP85_2100.csv
--13c) C_rlakes3pt1km_projections.csv
16k) C_Daily_lake_temps_HISTO.csv
16l) C_Daily_lake_temps_RCP45_2050.csv
16m) C_Daily_lake_temps_RCP45_2100.csv
16n) C_Daily_lake_temps_RCP85_2050.csv
16o) C_Daily_lake_temps_RCP85_2100.csv
--13d) D_rlakes3pt1km_projections.csv
16p) D_Daily_lake_temps_HISTO.csv
16q) D_Daily_lake_temps_RCP45_2050.csv
16r) D_Daily_lake_temps_RCP45_2100.csv
16s) D_Daily_lake_temps_RCP85_2050.csv
16t) D_Daily_lake_temps_RCP85_2100.csv
--13e) E_rlakes3pt1km_projections.csv
16u) E_Daily_lake_temps_HISTO.csv
16v) E_Daily_lake_temps_RCP45_2050.csv
16w) E_Daily_lake_temps_RCP45_2100.csv
16x) E_Daily_lake_temps_RCP85_2050.csv
16y) E_Daily_lake_temps_RCP85_2100.csv
--13f) F_rlakes3pt1km_projections.csv
16z) F_Daily_lake_temps_HISTO.csv
16aa) F_Daily_lake_temps_RCP45_2050.csv
16bb) F_Daily_lake_temps_RCP45_2100.csv
16cc) F_Daily_lake_temps_RCP85_2050.csv
16dd) F_Daily_lake_temps_RCP85_2100.csv
--13g) G_rlakes3pt1km_projections.csv
16ee) G_Daily_lake_temps_HISTO.csv
16ff) G_Daily_lake_temps_RCP45_2050.csv
16gg) G_Daily_lake_temps_RCP45_2100.csv
16hh) G_Daily_lake_temps_RCP85_2050.csv
16ii) G_Daily_lake_temps_RCP85_2100.csv
--13h) H_rlakes3pt1km_projections.csv
16jj) H_Daily_lake_temps_HISTO.csv
16kk) H_Daily_lake_temps_RCP45_2050.csv
16ll) H_Daily_lake_temps_RCP45_2100.csv
16mm) H_Daily_lake_temps_RCP85_2050.csv
16nn) H_Daily_lake_temps_RCP85_2100.csv
--13i) I_rlakes3pt1km_projections.csv
16oo) I_Daily_lake_temps_HISTO.csv
16pp) I_Daily_lake_temps_RCP45_2050.csv
16qq) I_Daily_lake_temps_RCP45_2100.csv
16rr) I_Daily_lake_temps_RCP85_2050.csv
16ss) I_Daily_lake_temps_RCP85_2100.csv
--13j) J_rlakes3pt1km_projections.csv
16tt) J_Daily_lake_temps_HISTO.csv
16uu) J_Daily_lake_temps_RCP45_2050.csv
16vv) J_Daily_lake_temps_RCP45_2100.csv
16ww) J_Daily_lake_temps_RCP85_2050.csv
16xx) J_Daily_lake_temps_RCP85_2100.csv
--13k) K_rlakes3pt1km_projections.csv
16yy) K_Daily_lake_temps_HISTO.csv
16zz) K_Daily_lake_temps_RCP45_2050.csv
16aaa) K_Daily_lake_temps_RCP45_2100.csv
16bbb) K_Daily_lake_temps_RCP85_2050.csv
16ccc) K_Daily_lake_temps_RCP85_2100.csv
--13l) L_rlakes3pt1km_projections.csv
16ddd) L_Daily_lake_temps_HISTO.csv
16eee) L_Daily_lake_temps_RCP45_2050.csv
16fff) L_Daily_lake_temps_RCP45_2100.csv
16ggg) L_Daily_lake_temps_RCP85_2050.csv
16hhh) L_Daily_lake_temps_RCP85_2100.csv
--13m) M_rlakes3pt1km_projections.csv
16iii) M_Daily_lake_temps_HISTO.csv
16jjj) M_Daily_lake_temps_RCP45_2050.csv
16kkk) M_Daily_lake_temps_RCP45_2100.csv
16lll) M_Daily_lake_temps_RCP85_2050.csv
16mmm) M_Daily_lake_temps_RCP85_2100.csv
--13n) N_rlakes3pt1km_projections.csv
16nnn) N_Daily_lake_temps_HISTO.csv
16ooo) N_Daily_lake_temps_RCP45_2050.csv
16ppp) N_Daily_lake_temps_RCP45_2100.csv
16qqq) N_Daily_lake_temps_RCP85_2050.csv
16rrr) N_Daily_lake_temps_RCP85_2100.csv
--13o) O_rlakes3pt1km_projections.csv
16sss) O_Daily_lake_temps_HISTO.csv
16ttt) O_Daily_lake_temps_RCP45_2050.csv
16uuu) O_Daily_lake_temps_RCP45_2100.csv
16vvv) O_Daily_lake_temps_RCP85_2050.csv
16www) O_Daily_lake_temps_RCP85_2100.csv
--13p) P_rlakes3pt1km_projections.csv
16xxx) P_Daily_lake_temps_HISTO.csv
16yyy) P_Daily_lake_temps_RCP45_2050.csv
16zzz) P_Daily_lake_temps_RCP45_2100.csv
16aaaa) P_Daily_lake_temps_RCP85_2050.csv
16bbbb) P_Daily_lake_temps_RCP85_2100.csv
--13q) Q_rlakes3pt1km_projections.csv
16cccc) Q_Daily_lake_temps_HISTO.csv
16dddd) Q_Daily_lake_temps_RCP45_2050.csv
16eeee) Q_Daily_lake_temps_RCP45_2100.csv
16ffff) Q_Daily_lake_temps_RCP85_2050.csv
16gggg) Q_Daily_lake_temps_RCP85_2100.csv
--13r) R_rlakes3pt1km_projections.csv
16hhhh) R_Daily_lake_temps_HISTO.csv
16iiii) R_Daily_lake_temps_RCP45_2050.csv
16jjjj) R_Daily_lake_temps_RCP45_2100.csv
16kkkk) R_Daily_lake_temps_RCP85_2050.csv
16llll) R_Daily_lake_temps_RCP85_2100.csv
--13s) S_rlakes3pt1km_projections.csv
16mmmm) S_Daily_lake_temps_HISTO.csv
16nnnn) S_Daily_lake_temps_RCP45_2050.csv
16oooo) S_Daily_lake_temps_RCP45_2100.csv
16pppp) S_Daily_lake_temps_RCP85_2050.csv
16qqqq) S_Daily_lake_temps_RCP85_2100.csv
--13t) T_rlakes3pt1km_projections.csv
16rrrr) T_Daily_lake_temps_HISTO.csv
16ssss) T_Daily_lake_temps_RCP45_2050.csv
16tttt) T_Daily_lake_temps_RCP45_2100.csv
16uuuu) T_Daily_lake_temps_RCP85_2050.csv
16vvvv) T_Daily_lake_temps_RCP85_2100.csv

##17_Arctic_Proj_Daily_Water_Temps_Bind.R
-16a) A_Daily_lake_temps_HISTO.csv
-16f) B_Daily_lake_temps_HISTO.csv
-16k) C_Daily_lake_temps_HISTO.csv
-16p) D_Daily_lake_temps_HISTO.csv
-16u) E_Daily_lake_temps_HISTO.csv
-16z) F_Daily_lake_temps_HISTO.csv
-16ee) G_Daily_lake_temps_HISTO.csv
-16jj) H_Daily_lake_temps_HISTO.csv
-16oo) I_Daily_lake_temps_HISTO.csv
-16tt) J_Daily_lake_temps_HISTO.csv
-16yy) K_Daily_lake_temps_HISTO.csv
-16ddd) L_Daily_lake_temps_HISTO.csv
-16iii) M_Daily_lake_temps_HISTO.csv
-16nnn) N_Daily_lake_temps_HISTO.csv
-16sss) O_Daily_lake_temps_HISTO.csv
-16xxx) P_Daily_lake_temps_HISTO.csv
-16cccc) Q_Daily_lake_temps_HISTO.csv
-16hhhh) R_Daily_lake_temps_HISTO.csv
-16mmmm) S_Daily_lake_temps_HISTO.csv
-16rrrr) T_Daily_lake_temps_HISTO.csv
17a) Daily_lake_temps_HISTO.csv
-16b) A_Daily_lake_temps_RCP45_2050.csv
-16g) B_Daily_lake_temps_RCP45_2050.csv
-16l) C_Daily_lake_temps_RCP45_2050.csv
-16q) D_Daily_lake_temps_RCP45_2050.csv
-16v) E_Daily_lake_temps_RCP45_2050.csv
-16aa) F_Daily_lake_temps_RCP45_2050.csv
-16ff) G_Daily_lake_temps_RCP45_2050.csv
-16kk) H_Daily_lake_temps_RCP45_2050.csv
-16pp) I_Daily_lake_temps_RCP45_2050.csv
-16uu) J_Daily_lake_temps_RCP45_2050.csv
-16zz) K_Daily_lake_temps_RCP45_2050.csv
-16eee) L_Daily_lake_temps_RCP45_2050.csv
-16jjj) M_Daily_lake_temps_RCP45_2050.csv
-16ooo) N_Daily_lake_temps_RCP45_2050.csv
-16ttt) O_Daily_lake_temps_RCP45_2050.csv
-16yyy) P_Daily_lake_temps_RCP45_2050.csv
-16dddd) Q_Daily_lake_temps_RCP45_2050.csv
-16iiii) R_Daily_lake_temps_RCP45_2050.csv
-16nnnn) S_Daily_lake_temps_RCP45_2050.csv
-16ssss) T_Daily_lake_temps_RCP45_2050.csv
17b) Daily_lake_temps_RCP45_2050.csv
-16c) A_Daily_lake_temps_RCP45_2100.csv
-16h) B_Daily_lake_temps_RCP45_2100.csv
-16m) C_Daily_lake_temps_RCP45_2100.csv
-16r) D_Daily_lake_temps_RCP45_2100.csv
-16w) E_Daily_lake_temps_RCP45_2100.csv
-16bb) F_Daily_lake_temps_RCP45_2100.csv
-16gg) G_Daily_lake_temps_RCP45_2100.csv
-16ll) H_Daily_lake_temps_RCP45_2100.csv
-16qq) I_Daily_lake_temps_RCP45_2100.csv
-16vv) J_Daily_lake_temps_RCP45_2100.csv
-16aaa) K_Daily_lake_temps_RCP45_2100.csv
-16fff) L_Daily_lake_temps_RCP45_2100.csv
-16kkk) M_Daily_lake_temps_RCP45_2100.csv
-16ppp) N_Daily_lake_temps_RCP45_2100.csv
-16uuu) O_Daily_lake_temps_RCP45_2100.csv
-16zzz) P_Daily_lake_temps_RCP45_2100.csv
-16eeee) Q_Daily_lake_temps_RCP45_2100.csv
-16jjjj) R_Daily_lake_temps_RCP45_2100.csv
-16oooo) S_Daily_lake_temps_RCP45_2100.csv
-16tttt) T_Daily_lake_temps_RCP45_2100.csv
17c) Daily_lake_temps_RCP45_2100.csv
-16d) A_Daily_lake_temps_RCP85_2050.csv
-16i) B_Daily_lake_temps_RCP85_2050.csv
-16n) C_Daily_lake_temps_RCP85_2050.csv
-16s) D_Daily_lake_temps_RCP85_2050.csv
-16x) E_Daily_lake_temps_RCP85_2050.csv
-16cc) F_Daily_lake_temps_RCP85_2050.csv
-16hh) G_Daily_lake_temps_RCP85_2050.csv
-16mm) H_Daily_lake_temps_RCP85_2050.csv
-16rr) I_Daily_lake_temps_RCP85_2050.csv
-16ww) J_Daily_lake_temps_RCP85_2050.csv
-16bbb) K_Daily_lake_temps_RCP85_2050.csv
-16ggg) L_Daily_lake_temps_RCP85_2050.csv
-16lll) M_Daily_lake_temps_RCP85_2050.csv
-16qqq) N_Daily_lake_temps_RCP85_2050.csv
-16vvv) O_Daily_lake_temps_RCP85_2050.csv
-16aaaa) P_Daily_lake_temps_RCP85_2050.csv
-16ffff) Q_Daily_lake_temps_RCP85_2050.csv
-16kkkk) R_Daily_lake_temps_RCP85_2050.csv
-16pppp) S_Daily_lake_temps_RCP85_2050.csv
-16uuuu) T_Daily_lake_temps_RCP85_2050.csv
17d) Daily_lake_temps_RCP85_2050.csv
-16e) A_Daily_lake_temps_RCP85_2100.csv
-16j) B_Daily_lake_temps_RCP85_2100.csv
-16o) C_Daily_lake_temps_RCP85_2100.csv
-16t) D_Daily_lake_temps_RCP85_2100.csv
-16y) E_Daily_lake_temps_RCP85_2100.csv
-16dd) F_Daily_lake_temps_RCP85_2100.csv
-16ii) G_Daily_lake_temps_RCP85_2100.csv
-16nn) H_Daily_lake_temps_RCP85_2100.csv
-16ss) I_Daily_lake_temps_RCP85_2100.csv
-16xx) J_Daily_lake_temps_RCP85_2100.csv
-16ccc) K_Daily_lake_temps_RCP85_2100.csv
-16hhh) L_Daily_lake_temps_RCP85_2100.csv
-16mmm) M_Daily_lake_temps_RCP85_2100.csv
-16rrr) N_Daily_lake_temps_RCP85_2100.csv
-16www) O_Daily_lake_temps_RCP85_2100.csv
-16bbbb) P_Daily_lake_temps_RCP85_2100.csv
-16gggg) Q_Daily_lake_temps_RCP85_2100.csv
-16llll) R_Daily_lake_temps_RCP85_2100.csv
-16qqqq) S_Daily_lake_temps_RCP85_2100.csv
-16vvvv) T_Daily_lake_temps_RCP85_2100.csv
17e) Daily_lake_temps_RCP85_2100.csv

##18_Arctic_Proj_Analysis_Thermal_Hab_Cals.R
---13a) A_rlakes3pt1km_projections.csv
---13b) B_rlakes3pt1km_projections.csv
---13c) C_rlakes3pt1km_projections.csv
---13d) D_rlakes3pt1km_projections.csv
---13e) E_rlakes3pt1km_projections.csv
---13f) F_rlakes3pt1km_projections.csv
---13g) G_rlakes3pt1km_projections.csv
---13h) H_rlakes3pt1km_projections.csv
---13i) I_rlakes3pt1km_projections.csv
---13j) J_rlakes3pt1km_projections.csv
---13k) K_rlakes3pt1km_projections.csv
---13l) L_rlakes3pt1km_projections.csv
---13m) M_rlakes3pt1km_projections.csv
---13n) N_rlakes3pt1km_projections.csv
---13o) O_rlakes3pt1km_projections.csv
---13p) P_rlakes3pt1km_projections.csv
---13q) Q_rlakes3pt1km_projections.csv
---13r) R_rlakes3pt1km_projections.csv
---13s) S_rlakes3pt1km_projections.csv
---13t) T_rlakes3pt1km_projections.csv
-17a) Daily_lake_temps_HISTO.csv
-17b) Daily_lake_temps_RCP45_2050.csv
-17c) Daily_lake_temps_RCP45_2100.csv
-17d) Daily_lake_temps_RCP85_2050.csv
-17e) Daily_lake_temps_RCP85_2100.csv
*18a) rlakes3pt1km_projections_thermal_hab.csv
*18A) external: FEOW_ID_ArcticLakeid.csv
18B) external: ne_10m_lakes.shp
*18b) polys_sf_trans_cropped.gpkg

##19_Arctic_Proj_Testing_Lake_Temp_Thermocline_Models_Vital_Alexie_Toolik.R
*19A) Vital_Lake_Temperature_Data.csv
*19B) Alexie_Lake_Temperature_Data.csv
*19C) Copy of reference lake subset for Shuter - Vital Alexie Yearly subset - climate Secchi.csv
19D) external: Arctic_LTER_Lake_Specific_Data_Lake_Morpho.csv
19E) external: Arctic_LTER_Lake_Temperature_Data.csv
19F) external: Arctic_LTERUG20190426.cru_ts4.01.tmp.1971.2016.csv
19G) external: Arctic_LTERUG20190426.cru_ts4.01.pre.1971.2016.csv
19H) external: Arctic_LTERUG20190426.cru_ts4.01.crad.1971.2016.csv
19I) external: Arctic_LTERUG20190426.cru_ts4.01.cld.1971.2016.csv
19J) external: Arctic_LTERUG20190426.added_temp_metrics.1971.2016.csv
19K) external: Arctic_LTERUG20190524.wspd.10m.mon.mean.1971.2016.csv
19L) external: Arctic_LTER_ESRLAllLakeGrids20190524.csv
19M) external: Arctic_LTER_Lake_Year_Data.csv
-*18a) rlakes3pt1km_projections_thermal_hab.csv
--*11a) median_shape_1hr_df.csv
19N) external: CMIP5.SFCWIND.HISTO.SUMMER.ABS_PCTL50.csv

##20_Arctic_Proj_Lake_Morphometry_Ecozone_FWEcoregion.R
--*18a) rlakes3pt1km_projections_thermal_hab.csv
-*18A) FEOW_ID_ArcticLakeid.csv

##Figures, tables, key results, and their relationships to scripts, in the order that they are created
##2_Arctic_Proj_Lake_Morphometry_Ground_Truthed.R
Supplementary Table 14

##3_Arctic_Proj_Lake_Morphometry_Config.R
Supplementary Table 13
Supplementary_Figure_6.png
Supplementary_Figure_7.png
Supplementary_Figure_3.png
Supplementary_Figure_4.png
Supplementary_Figure_5.png
Supplementary Table 12

##11_Arctic_Proj_Wind_atlas_weibull.R
Supplementary_Table_15.csv

##12_Arctic_Proj_Projections.R
Supplementary Table 16
Supplementary Table 17
Supplementary_Figure_11.png
Supplementary_Figure_12.png

##15_Arctic_Proj_HydroComp.R
Supplementary_Figure_9.png
Supplementary_Figure_8.png
Supplementary Table 11

##18_Arctic_Proj_Analysis_Thermal_Hab_Cals.R
Results_Lake_Temperature_and_Ice_Projections.csv
Supplementary_Table_1.csv
Results - Lake Temperature and Ice Projections cont'd
Figure_3a.png
Figure_4_Eco_1.png
Figure_4_Eco_2.png
Figure_4_Eco_3.png
Figure_4_Eco_4.png
Figure_4_Eco_5.png
Figure_4_Eco_9.png
Figure_4_Eco_11.png
Figure_4_Eco_12.png
Supplementary_Table_4.csv
Figure_3b.png
Supplementary_Table_2.csv
Supplementary_Table_3.csv
Figure_6all.png
Supplementary_Table_7.csv
Supplementary_Table_8.csv
Results - Lake Thermal Habitat Projections
Supplementary_Table_9.csv
Figure_5_all.png
Figure_5_Eco_1.png
Figure_5_Eco_2.png
Figure_5_Eco_3.png
Figure_5_Eco_4.png
Figure_5_Eco_5.png
Figure_5_Eco_9.png
Figure_5_Eco_11.png
Figure_5_Eco_12.png
Figure_7_all.png
Figure_7_Eco_1.png
Figure_7_Eco_2.png
Figure_7_Eco_3.png
Figure_7_Eco_4.png
Figure_7_Eco_5.png
Figure_7_Eco_9.png
Figure_7_Eco_11.png
Figure_7_Eco_12.png
Supplementary_Figure_14_All.png
Supplementary_Figure_14_FEOW_101.png
Supplementary_Figure_14_FEOW_102.png
Supplementary_Figure_14_FEOW_103.png
Supplementary_Figure_14_FEOW_104.png
Supplementary_Figure_14_FEOW_105.png
Supplementary_Figure_14_FEOW_106.png
Supplementary_Figure_14_FEOW_111.png
Supplementary_Figure_14_FEOW_112.png
Supplementary_Figure_14_FEOW_113.png
Supplementary_Table_5.csv
Supplementary_Table_6.csv
Figure_6_Eco_1.png
Figure_6_Eco_2.png
Figure_6_Eco_3.png
Figure_6_Eco_4.png
Figure_6_Eco_5.png
Figure_6_Eco_9.png
Figure_6_Eco_11.png
Figure_6_Eco_12.png
Supplementary_Figure_1A.png
Results - Lake Thermal Habitat Projections
Supplementary_Figure_1B_all.png
Supplementary_Figure_1B_Eco_1.png
Supplementary_Figure_1B_Eco_2.png
Supplementary_Figure_1B_Eco_3.png
Supplementary_Figure_1B_Eco_4.png
Supplementary_Figure_1B_Eco_5.png
Supplementary_Figure_1B_Eco_9.png
Supplementary_Figure_1B_Eco_11.png
Supplementary_Figure_1B_Eco_12.png
Supplementary_Figure_1C_all.png
Supplementary_Figure_1C_Eco_1.png
Supplementary_Figure_1C_Eco_2.png
Supplementary_Figure_1C_Eco_3.png
Supplementary_Figure_1C_Eco_4.png
Supplementary_Figure_1C_Eco_5.png
Supplementary_Figure_1C_Eco_9.png
Supplementary_Figure_1C_Eco_11.png
Supplementary_Figure_1C_Eco_12.png
Supplementary_Figure_1D_All.png
Supplementary_Figure_1D_Eco_1.png
Supplementary_Figure_1D_Eco_2.png
Supplementary_Figure_1D_Eco_3.png
Supplementary_Figure_1D_Eco_4.png
Supplementary_Figure_1D_Eco_5.png
Supplementary_Figure_1D_Eco_9.png
Supplementary_Figure_1D_Eco_11.png
Supplementary_Figure_1D_Eco_12.png
Supplementary_Figure_17.png
Supplementary_Figure_20.png
Supplementary_Figure_19.png
Supplementary_Figure_18.png
Supplementary_Figure_21.png
Supplementary_Figure_26.png
Supplementary_Figure_27.png
Supplementary_Figure_29.png
Supplementary_Figure_31.png
Supplementary_Figure_30.png
Supplementary_Figure_28.png
Supplementary_Figure_32.png
Supplementary_Figure_24.png
Supplementary_Figure_22.png
Supplementary_Figure_23.png
Supplementary_Figure_25.png
Supplementary_Figure_15.png
Supplementary_Figure_16.png

##19_Arctic_Proj_Testing_Lake_Temp_Thermocline_Models_Vital_Alexie_Toolik.R
Supplementary_Figure_10A.png
Supplementary_Figure_10B.png
Supplementary_Figure_10C.png

##20_Arctic_Proj_Lake_Morphometry_Ecozone_FWEcoregion.R
Supplementary_Table_18.csv
Supplementary_Figure_13_pt3.png
Supplementary_Figure_13_pt4.png
Supplementary_Figure_13_pt1.png
Supplementary_Figure_13_pt2.png
Supplementary_Table_19.csv
Supplementary Table 20

Description of the scripts, data, and file structure

The following information summarizes the essential points related to the scripts, data, and files used for the study.

##1_Arctic_Proj_Lake_Dataset_Config.R
SCRIPT PURPOSE: Configuring the Arctic Lake Dataset with latitude, longitude, and correct mean depth values

#########################################################################

DATA-SPECIFIC INFORMATION FOR: rlakes3pt1km.csv

Number of variables: 52
Number of cases/rows: 481784
Variable list:

*...1: duplicate of id (below)

* id: lake ID

* name: another lake ID

* n_id: unknown, not used in analyses, relic from Campana et al. 2020

* nts: The National Topographic System or NTS, or the system used by Natural Resources Canada for topographic maps of Canada. This shows the NTS grid cell that the lake is in.

* area_sq_km: lake area in square kilometres

* perimeter_km: lake perimeter in kilometres

* mean_depth_m: lake mean depth in metres

* max_depth_m: lake maximum depth in metres

* is_included: all are TRUE. Shows if the lake is included in the dataset (they all are). Relic from Campana et al. 2020

* is_lake: all are TRUE. Shows if the row is a lake, which they all are. Relic from Campana et al. 2020.

* definition: unknown, not used in analyses, relic from Campana et al. 2020

* prov: province that the lake is in

* elevation_m: lake elevation in metres

* dwms_max_depth_m: lake maximum depth in metres (determined using alternate method, see Campana et al. 2020)

* dwms_mean_depth_m: lake mean depth in metres (determined using alternate method, see Campana et al. 2020)

* dwms_elevation_m: lake elevation in metres (determined using alternate method, see Campana et al. 2020)

*degree_days_above_zero, days_above_zero, daily_avg_temp, precipitation_mm: climate variables used in Campana et al. 2020 and not in the present study

* community_distance_km: distance to nearest community (see Campana et al. 2020)

* cgndb_key: key (abbreviation) for nearest community, from Canadian Geographical Names Database of non-abandoned communities

* daily_avg_temp_jan - daily_avg_temp_dec: climate variables used in Campana et al. 2020 and not in the present study

* water_temp: modelled water temperature, not used in the present study (see Campana et al. 2020)

* elevation_weather_stns_m: nearest weather station elevation

* daily_avg_tempele: lake-specific air temperature based on 1981-2010 data (see Campana et al. 2020)

* rcp_45_2006 - rcp_85_2100: lake-specific air temperature under different projected future climate scenarios (used in Campana et al. 2020 and not in the present study)

* fetch_km: lake fetch (maximum length) in kilometres

* wat_temp_rcp_45_2006ele - wat_temp_rcp_85_2100ele: lake-specific modelled water temperature under different projected future climate scenarios (used in Campana et al. 2020 and not in the present study)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
See Campana et al. (2020) (full citation below) for information on geospatial methods for estimating lake depths.

#########################################################################

DATA-SPECIFIC INFORMATION FOR: lakeslatlong.csv

Number of variables: 10
Number of cases/rows: 481784
Variable list:

*...1: duplicate of id (below)

* id: lake ID

* name: another lake ID

* nts: The National Topographic System or NTS, or the system used by Natural Resources Canada for topographic maps of Canada. This shows the NTS grid cell that the lake is in.

* area_sq_km: lake area in square kilometres

* perimeter_km: lake perimeter in kilometres

* mean_mean_depth_m: lake mean depth in metres, the one that is used in the study (the mean of both geospatial methods used in Campana et al. 2020)

* max_depth_m: lake maximum depth in metres

* longitude: lake longitude (decimal degrees)

* latitude: lake latitude (decimal degrees)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
See Campana et al. (2020) (full citation below) for information on geospatial methods for estimating lake depths.

#########################################################################

DATA-SPECIFIC INFORMATION FOR: rlakes3pt1km_latlong_zmean.csv

*Output from script, not included in Dryad repository

Number of variables: 54
Number of cases/rows: 481784
Variable list:

*Same as rlakes3pt1km.csv (above) but with mean_mean_depth_m, longitude, and latitude (see lakeslatlong.csv above)
Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
See Campana et al. (2020) (full citation below) for information on geospatial methods for estimating lake depths.

##2_Arctic_Proj_Lake_Morphometry_Ground_Truthed.R
SCRIPT PURPOSE: Analyzing ground-truthed morphometry values for validating the Arctic Lakes GIS database

#########################################################################

DATA-SPECIFIC INFORMATION FOR: Ground_Truthed_Lake_Morphometry.csv

*External, not included in Dryad repository

Number of variables: 8
Number of cases/rows: 229
Variable list:

*Group: which dataset the lake belongs to:

* CLAM = lakes from the Canadian Lakes Assessment Model (CLAM) database. Minns, C. K., Moore, J. E., Shuter, B. J. & Mandrak, N. E. A preliminary national analysis of some key characteristics of Canadian lakes. Can. J. Fish. Aquat. Sci. 65, 1763–1778 (2008).

* Sharma = lakes from Sharma et al. 2007. Sharma, S., Jackson, D. A., Minns, C. K. & Shuter, B. J. Will northern fish populations be in hot water because of climate change? Glob. Chang. Biol. 13, 2052–2064 (2007).

* Campana = lakes from Campana et al. (2020). Campana, S. E. et al. Arctic freshwater fish productivity and colonization increase with climate warming. Nat. Clim. Chang. 10, 428–433 (2020). Available at https://doi.org/10.5063/F1ZP44F1 under the Creative Commons Universal 1.0 Public Domain Dedication

* CIMP = lakes from the Cumulative Impact Monitoring Program (CIMP). Murdoch, A. et al. Drivers of fish biodiversity in a rapidly changing permafrost landscape. Freshw. Biol. 66, 2301–2321 (2021).

* FishoutDB = lakes from the Fisheries and Oceans Canada fishout database. Samarasin, P., Minns, C. K., Shuter, B. J., Tonn, W. M. & Rennie, M. D. Fish diversity and biomass in northern Canadian lakes: Northern lakes are more diverse and have greater biomass than expected based on species–energy theory. Can. J. Fish. Aquat. Sci. 72, 226–237 (2014).

* Lake: lake name

* Latitude: lake latitude (decimal degrees)

* Longitude: lake longitude (decimal degrees)

* Lake_area_km2: lake area (square kilometres)

* Max_depth_m: lake maximum depth in metres

* Mean_depth_m: lake mean depth in metres

* Area_Flag: 1 = lake is below 0.01 square kilometres, cutoff for inclusion in the study and Campana et al. 2020, 0 = lake is greater than or equal to 0.01 square kilometres

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
External dataset. Comprised of data from a variety of sources that may not necessarily comply with CC0 licence requirements. See Group variable for sources, references, and licence information and links where datasets are available under CC0 compliant licence.

#########################################################################

DATA-SPECIFIC INFORMATION FOR: Ground_Truthed_Lake_Morphometry_Prelim_Eco.csv

Number of variables: 7
Number of cases/rows: 229
Variable list:

*Group: which dataset the lake belongs to:

* CIMP = lakes from the Cumulative Impact Monitoring Program (CIMP). Murdoch, A. et al. Drivers of fish biodiversity in a rapidly changing permafrost landscape. Freshw. Biol. 66, 2301–2321 (2021).

* Lake: lake name

* ECOREGION_: Ecoregion, signified by its numerical ID, that the lake is in according to Ricketts et al. (1999). Ricketts, T. A. et al. Terrestrial Ecoregions of North America - A conservation assessment. (Island Press Books, 1999).

* ECOZONE_ID: Ecozone, signified by its numerical ID,that the lake is in according to Ricketts et al. (1999). Ricketts, T. A. et al. Terrestrial Ecoregions of North America - A conservation assessment. (Island Press Books, 1999).

* ECOPROVINC: Ecoprovince, signified by its numerical ID, that the lake is in according to Ricketts et al. (1999). Ricketts, T. A. et al. Terrestrial Ecoregions of North America - A conservation assessment. (Island Press Books, 1999).

* ECOREGION1: Ecoregion, signified by its name, that the lake is in according to Ricketts et al. (1999). Ricketts, T. A. et al. Terrestrial Ecoregions of North America - A conservation assessment. (Island Press Books, 1999).

* ECOREGIO_1: Ecoregion, signified by its French name, that the lake is in according to Ricketts et al. (1999). Ricketts, T. A. et al. Terrestrial Ecoregions of North America - A conservation assessment. (Island Press Books, 1999).

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
External dataset. Does not contain specific data about the lakes that are proprietary to the datasets that they belong to, only the ecozones (etc.) that the lakes, which are named, belong to. The full lake datasets (Ground_Truthed_Lake_Morphometry.csv, above) come from a variety of sources that may not necessarily comply with CC0 licence requirements. See Group variable for sources, references, and licence information and links where datasets are available under CC0 compliant licence.

#########################################################################

DATA-SPECIFIC INFORMATION FOR: Ground_Truthed_Lake_Morphometry_Eco_Cleaned.csv

*Output from script and external dataset, not included in Dryad repository

Number of variables: 17
Number of cases/rows: 167
Variable list:

*Join and subset of columns from each of Ground_Truthed_Lake_Morphometry.csv and Ground_Truthed_Lake_Morphometry_Eco_Cleaned.csv. 167 instead of 229 rows because it was filtered for lakes with Area_Flag = 0 (greater than or equal to 10 0.01 square kilometres surface area)

*Group: which dataset the lake belongs to:

* CIMP = lakes from the Cumulative Impact Monitoring Program (CIMP). Murdoch, A. et al. Drivers of fish biodiversity in a rapidly changing permafrost landscape. Freshw. Biol. 66, 2301–2321 (2021).

* Lake: lake name

* Latitude: lake latitude (decimal degrees)

* Longitude: lake longitude (decimal degrees)

* area_sq_km: lake area (square kilometres)

* max_depth_m: lake maximum depth in metres

* mean_depth_m: lake mean depth in metres

* Area_Flag: 1 = lake is below 0.01 square kilometres, cutoff for inclusion in the study and Campana et al. 2020, 0 = lake is greater than or equal to 0.01 square kilometres

* ECOREGION_ID: Ecoregion, signified by its numerical ID, that the lake is in according to Ricketts et al. (1999). Ricketts, T. A. et al. Terrestrial Ecoregions of North America - A conservation assessment. (Island Press Books, 1999).

* ECOPROVINCE_ID: Ecoprovince, signified by its numerical ID, that the lake is in according to Ricketts et al. (1999). Ricketts, T. A. et al. Terrestrial Ecoregions of North America - A conservation assessment. (Island Press Books, 1999).

* ECOREGION_NAME_EN: Ecoregion, signified by its name, that the lake is in according to Ricketts et al. (1999). Ricketts, T. A. et al. Terrestrial Ecoregions of North America - A conservation assessment. (Island Press Books, 1999).

* ECOREGION_NAME_FR: Ecoregion, signified by its French name, that the lake is in according to Ricketts et al. (1999). Ricketts, T. A. et al. Terrestrial Ecoregions of North America - A conservation assessment. (Island Press Books, 1999).

* Lake_Group: Lake column and Group column strings combined

* max_depth_m_log: log-transformed max_depth_m

* mean_depth_m_log: log-transformed mean_depth_m

* area_sq_km_log: log-transformed area_sq_km

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
External dataset. Comprised of data from a variety of sources that may not necessarily comply with CC0 licence requirements. See Group variable for sources, references, and licence information and links where datasets are available under CC0 compliant licence. Also a script output, so not included in repository anyway.

##3_Arctic_Proj_Lake_Morphometry_Config.R
SCRIPT PURPOSE: Configuring lake morphometry to be used in the final analyses

#########################################################################

DATA-SPECIFIC INFORMATION FOR: lakesmeandepth.csv

Number of variables: 9
Number of cases/rows: 481784
Variable list:

* id: lake ID

* area_sq_km: lake area in square kilometres

* perimeter_km: lake perimeter in square kilometres

* mean_depth_m: lake mean depth in metres

* dwms_mean_depth_m: lake mean depth in metres (determined using alternate method, see Campana et al. 2020)

* mean_mean_depth_m: lake mean depth in metres, the one that is used in the study (the mean of both geospatial methods used in Campana et al. 2020)

* average: average value of mean_depth_m and dwms_mean_depth_m

* max_depth_m: lake maximum depth in metres

* dwms_max_depth_m: lake maximum depth in metres (determined using alternate method, see Campana et al. 2020)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
See Campana et al. (2020) (full citation below) for information on geospatial methods for estimating lake depths.

#########################################################################

DATA-SPECIFIC INFORMATION FOR: rlakes3pt1km_lat_long_zmean_ECO.csv

Number of variables: 5
Number of cases/rows: 481784
Variable list:

* id: lake ID

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
See Campana et al. (2020) (full citation below) for information on geospatial methods for estimating lake depths.

#########################################################################

DATA-SPECIFIC INFORMATION FOR: rlakes3pt1km_latlong_zmean_pred_final.csv

Number of variables: 89
Number of cases/rows: 481782
Variable list:

* Variables 1-54 (variable X to wat_temp_rcp_85_2100ele) are the same as rlakes3pt1km_latlong_zmean.csv (see above under ##1_Arctic_Proj_Lake_Dataset_Config.R). The additional variables are as follows.

* average_mean_depth_m: the average value of the lake mean depths in metres derived using alternate methods (see Campana et al. 2020)

* ln_max_depth_m: lake maximum depth in metres, transformed by the natural logarithm (ln)

* ln_mean_depth_m: lake mean depth in metres, transformed by the natural logarithm (ln)

* ln_area_sq_km: lake surface area in square kilometres, transformed by the natural logarithm (ln)

* ln_max_depth_m_pred: lake maximum depth in metres, transformed by the natural logarithm (ln), predicted by a linear regression equation predicting ln-max depth from ln-mean depth using the ground-truthed morphometry dataset

* max_depth_m_pred: lake maximum depth in metres, predicted by a linear regression equation predicting ln-max depth from ln-mean depth using the ground-truthed morphometry dataset, and then exponentiated to transform from ln metres to metres

* ln_mean_depth_m_pred: lake mean depth in metres, transformed by the natural logarithm (ln), predicted by a linear regression equation predicting ln-mean depth from ln-max depth using the ground-truthed morphometry dataset

* mean_depth_m_pred: lake mean depth in metres, predicted by a linear regression equation predicting ln-mean depth from ln-max depth using the ground-truthed morphometry dataset, and then exponentiated to transform from ln metres to metres

* ln_max_depth_m_pred_area: lake maximum depth in metres, transformed by the natural logarithm (ln), predicted by a linear regression equation predicting ln-max depth from ln-surface area using the ground-truthed morphometry dataset

* max_depth_m_pred_area: lake maximum depth in metres, predicted by a linear regression equation predicting ln-max depth from ln-surface area depth using the ground-truthed morphometry dataset, and then exponentiated to transform from ln metres to metres

* ln_mean_depth_m_pred_area: lake mean depth in metres, transformed by the natural logarithm (ln), predicted by a linear regression equation predicting ln-mean depth from ln-surface area using the ground-truthed morphometry dataset

* mean_depth_m_pred_area: lake mean depth in metres, predicted by a linear regression equation predicting ln-mean depth from ln-surface area depth using the ground-truthed morphometry dataset, and then exponentiated to transform from ln metres to metres

* dwms_mean_depth_m_edit: dwms_mean_depth_m, edited so that values less than 0.1 metres are converted to NA

* mean_depth_m_edit: mean_depth_m, edited so that values equal to 0 metres are converted to NA

* average_mean_depth_m_edit: average value of mean_depth_m_edit and dwms_mean_depth_m_edit

* max_depth_m_edit: max_depth_m, edited so that values equal to 0 metres are converted to NA

* mean_depth_m_final_flag_max_pred: if average_mean_depth_m_edit is NA and max_depth_m_edit is not NA, then the value is TRUE, if not, it is FALSE

* ln_mean_depth_m_final: if average_mean_depth_m_edit is NA, and max_depth_m_edit is not NA, then this column equals ln_mean_depth_m_pred, if not, it equals average_mean_depth_m_edit

* mean_depth_m_final_flag_area_pred: if ln_mean_depth_m_final is NA, the value is TRUE, if not, it is FALSE

* ln_max_depth_m_pred_2: using values from average_mean_depth_m_edit, the prediction of maximum depth from mean depth using a linear regression equation predicting ln-maximum depth from ln-mean depth using the ground-truthed morphometry dataset

* max_depth_m_final_flag_mean_pred: if max_depth_m_edit is NA, and ln_max_depth_m_pred_2 is not NA, then the value is TRUE, if not, it is FALSE

* ln_max_depth_m_final: if max_depth_m_edit is NA, then this column equals ln_max_depth_m_pred_2, if not, then it equals ln-transformed max_depth_m_edit

* max_depth_m_final_flag_area_pred: if ln_max_depth_m_final is NA, then the value is TRUE, if not, it is FALSE

* ln_max_depth_m_final: if ln_max_depth_m_final is NA, then this column is equal to ln_max_depth_m_pred_area, if not, it is equal to ln_max_depth_m_final

* max_depth_m_final_flag_area_pred: if ln_max_depth_m_final is NA, then the value is TRUE, if not, it is FALSE

* max_depth_m_final: ln_max_depth_m_final exponentiated to get the value in metres

* ln_max_depth_m_pred_deeper: for lakes with max_depth_m_final values smaller than the mean_depth_m_final values, lake maximum depth in metres, transformed by the natural logarithm (ln), predicted by a linear regression equation predicting ln-max depth from ln-mean depth using the ground-truthed morphometry dataset

* max_depth_m_pred_deeper: ln_max_depth_m_pred_deeper exponentiated to get the value in metres

* max_depth_m_final_flag_mean_deeper: if mean_depth_m_final is greater than max_depth_m_final, then the value is TRUE, if not, it is FALSE

* fetch_km_flag_1: a column flagging whether a lake's geometry values (surface area and fetch) are potentially in conflict

* fetch_km_flag_2: another column flagging whether a lake's geometry values (surface area and fetch) are potentially in conflict

* fetch_km_estimate: for lakes that were flagged as potentially having incorrect geometries in fetch_km_flag_1, fetch is estimated using the mean of lake surface area from lakes with similar suface areas

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
See Campana et al. (2020) (full citation below) for information on geospatial methods for estimating lake depths.

##4_Arctic_Proj_Climate_Temp_Precip_Wind_Extraction_GeoTIFF.R
SCRIPT PURPOSE: Extracting temperature, precipitation, and wind data for Arctic lakes

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
geomet-climate-DCS.TM.HISTO.ENS.ABS_PCTL50_1986_01_to_1994_05.tif
geomet-climate-DCS.TM.HISTO.ENS.ABS_PCTL50_1994_06_to_2002_09.tif
geomet-climate-DCS.TM.HISTO.ENS.ABS_PCTL50_2002_10_to_2005_12.tif
geomet-climate-DCS.TM.RCP45.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
geomet-climate-DCS.TM.RCP45.ENS.ABS_PCTL50_2100_01_to_2100_12.tif
geomet-climate-DCS.TM.RCP85.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
geomet-climate-DCS.TM.RCP85.ENS.ABS_PCTL50_2100_01_to_2100_12.tif

*External dataset, not included in Dryad repository

Number of variables: 1 (excluding dimension variables)
Number of cases/rows:
geomet-climate-DCS.TM.HISTO.ENS.ABS_PCTL50_1986_01_to_1994_05.tif: 510 * 1068 * 101 = 55012680 elements
geomet-climate-DCS.TM.HISTO.ENS.ABS_PCTL50_1994_06_to_2002_09.tif: 510 * 1068 * 100 = 54468000 elements
geomet-climate-DCS.TM.HISTO.ENS.ABS_PCTL50_2002_10_to_2005_12.tif: 510 * 1068 * 39 = 55012680 elements
geomet-climate-DCS.TM.RCP45.ENS.ABS_PCTL50_2050_01_to_2050_12.tif: 510 * 1068 * 12 = 6536160 elements
geomet-climate-DCS.TM.RCP45.ENS.ABS_PCTL50_2100_01_to_2100_12.tif: 510 * 1068 * 12 = 6536160 elements
geomet-climate-DCS.TM.RCP85.ENS.ABS_PCTL50_2050_01_to_2050_12.tif: 510 * 1068 * 12 = 6536160 elements
geomet-climate-DCS.TM.RCP85.ENS.ABS_PCTL50_2100_01_to_2100_12.tif: 510 * 1068 * 12 = 6536160 elements
The 510 rows represent the number of latitude grid demarcations, 1068 columns represent the number of longitude grid demarcations, and the number of cells (39 and 101) represent the number of months across the years (e.g., 101 months from January 1986 to May 1994)
Variable list:

* example of variable names - geomet.climate.DCS.TM.HISTO.ENS.ABS_PCTL50_1986_01_to_1994_05.101:

* geomet-climate-DCS: downscaled climate scnearios
* TM = mean air temperature (degrees Celsius)
* HISTO = Historical (1986-2005)
* HISTO may also be replaced with a future climate scenario, described below
* RCP45 = Representative Concentration Pathy 4.5 (climate change scenario)
* RCP85 = Representative Concentration Pathy 8.5 (climate change scenario)
* ENS: climate model ensemble
* ABS: actual values (as opposed to anomolies)
* PCTL50: ensemble percentile (50th percentile)
* 1986_01_to_1994_05: the whole geotiff file that this variable is in spans January 1986 to May 1994
* .101: corresponds to the 101st cell in the geotiff, which is the final month in the time series (May 1994 in this case)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
External dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Government of Canada Climate data Extraction tool (See more info below under ## Sharing/Access information)

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
TM_HISTO.csv
TM_RCP45_2050.csv
TM_RCP45_2100.csv
TM_RCP85_2050.csv
TM_RCP85_2100.csv

*Output from script, not included in Dryad repository

Number of variables: 25
Number of cases/rows: 481782
Variable list:

* X: a lake ID column

* nts: The National Topographic System or NTS, or the system used by Natural Resources Canada for topographic maps of Canada. This shows the NTS grid cell that the lake is in.

* latitude: lake latitude (decimal degrees)

* longitude: lake longitude (decimal degrees)

* ID: row number

* nts2: nts without the letter code (a broader level)

*TM_Jan_HISTO, TM_Feb_HISTO,...TM_Dec_HISTO: mean monthly air temperature (degrees Celsius)

*TM_DJF_HISTO, TM_MAM_HISTO, TM_JJA_HISTO, TM_SON_HISTO: mean seasonal air temperature (degrees Celsius)

*TM_Ann_HISTO: mean annual air temperature (degrees Celsius)

*nts_mean_flag: if 1, it means that the lake had a zero/NA for the cliamte value, and therefore it needed to be imputed by neighbouring lakes in its NTS

Missing data codes: NA
Specialized formats or other abbreviations used:
DJF: December, January, February
MAM: March, April, May
JJA: June, July, August
SON: September, October, November
Notes:
External dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Government of Canada Climate data Extraction tool (See more info below under ## Sharing/Access information)

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
geomet-climate-DCS.PR.HISTO.ENS.ABS_PCTL50_1986_01_to_1994_05.tif
geomet-climate-DCS.PR.HISTO.ENS.ABS_PCTL50_1994_06_to_2002_09.tif
geomet-climate-DCS.PR.HISTO.ENS.ABS_PCTL50_2002_10_to_2005_12.tif
geomet-climate-DCS.PR.RCP45.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
geomet-climate-DCS.PR.RCP45.ENS.ABS_PCTL50_2100_01_to_2100_12.tif
geomet-climate-DCS.PR.RCP85.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
geomet-climate-DCS.PR.RCP85.ENS.ABS_PCTL50_2100_01_to_2100_12.tif

*External dataset, not included in Dryad repository

Number of variables: 1 (excluding dimension variables)
Number of cases/rows:
geomet-climate-DCS.PR.HISTO.ENS.ABS_PCTL50_1986_01_to_1994_05.tif: 510 * 1068 * 101 = 55012680 elements
geomet-climate-DCS.PR.HISTO.ENS.ABS_PCTL50_1994_06_to_2002_09.tif: 510 * 1068 * 100 = 54468000 elements
geomet-climate-DCS.PR.HISTO.ENS.ABS_PCTL50_2002_10_to_2005_12.tif: 510 * 1068 * 39 = 55012680 elements
geomet-climate-DCS.PR.RCP45.ENS.ABS_PCTL50_2050_01_to_2050_12.tif: 510 * 1068 * 12 = 6536160 elements
geomet-climate-DCS.PR.RCP45.ENS.ABS_PCTL50_2100_01_to_2100_12.tif: 510 * 1068 * 12 = 6536160 elements
geomet-climate-DCS.PR.RCP85.ENS.ABS_PCTL50_2050_01_to_2050_12.tif: 510 * 1068 * 12 = 6536160 elements
geomet-climate-DCS.PR.RCP85.ENS.ABS_PCTL50_2100_01_to_2100_12.tif: 510 * 1068 * 12 = 6536160 elements
The 510 rows represent the number of latitude grid demarcations, 1068 columns represent the number of longitude grid demarcations, and the number of cells (39 and 101) represent the number of months across the years (e.g., 101 months from January 1986 to May 1994)
Variable list:

* example of variable names - geomet.climate.DCS.PR.HISTO.ENS.ABS_PCTL50_1986_01_to_1994_05.101:

* geomet-climate-DCS: downscaled climate scnearios
* PR = total precipitation (millimetres)
* HISTO = Historical (1986-2005)
* HISTO may also be replaced with a future climate scenario, described below
* RCP45 = Representative Concentration Pathy 4.5 (climate change scenario)
* RCP85 = Representative Concentration Pathy 8.5 (climate change scenario)
* ENS: climate model ensemble
* ABS: actual values (as opposed to anomolies)
* PCTL50: ensemble percentile (50th percentile)
* 1986_01_to_1994_05: the whole geotiff file that this variable is in spans January 1986 to May 1994
* .101: corresponds to the 101st cell in the geotiff, which is the final month in the time series (May 1994 in this case)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
External dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Government of Canada Climate data Extraction tool (See more info below under ## Sharing/Access information)

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
PR_HISTO.csv
PR_RCP45_2050.csv
PR_RCP45_2100.csv
PR_RCP85_2050.csv
PR_RCP85_2100.csv

*Output from script, not included in Dryad repository

Number of variables: 25
Number of cases/rows: 481782
Variable list:

* X: a lake ID column

* nts: The National Topographic System or NTS, or the system used by Natural Resources Canada for topographic maps of Canada. This shows the NTS grid cell that the lake is in.

* latitude: lake latitude (decimal degrees)

* longitude: lake longitude (decimal degrees)

* ID: row number

* nts2: nts without the letter code (a broader level)

*PR_Jan_HISTO, PR_Feb_HISTO,...PR_Dec_HISTO: total monthly precipitation (millimetres)

*PR_DJF_HISTO, PR_MAM_HISTO, PR_JJA_HISTO, PR_SON_HISTO: total seasonal precipitation (millimetres)

*PR_Ann_HISTO: total annual precipitation (millimetres)

*nts_mean_flag: if 1, it means that the lake had a zero/NA for the cliamte value, and therefore it needed to be imputed by neighbouring lakes in its NTS

Missing data codes: NA
Specialized formats or other abbreviations used:
DJF: December, January, February
MAM: March, April, May
JJA: June, July, August
SON: September, October, November
Notes:
External dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Government of Canada Climate data Extraction tool (See more info below under ## Sharing/Access information)

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
geomet-climate-CMIP5.SFCWIND.HISTO.ENS.ABS_PCTL50_1986_01_to_2005_11.tif
geomet-climate-CMIP5.SFCWIND.RCP45.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
geomet-climate-CMIP5.SFCWIND.RCP45.ENS.ABS_PCTL50_2100_01_to_2100_12.tif
geomet-climate-CMIP5.SFCWIND.RCP85.ENS.ABS_PCTL50_2050_01_to_2050_12.tif
geomet-climate-CMIP5.SFCWIND.RCP85.ENS.ABS_PCTL50_2100_01_to_2100_12.tif

*External dataset, not included in Dryad repository

Number of variables: 1 (excluding dimension variables)
Number of cases/rows:
geomet-climate-CMIP5.SFCWIND.HISTO.ENS.ABS_PCTL50_1986_01_to_2005_11.tif: 46 * 105 * 239 = 1154370 elements
geomet-climate-CMIP5.SFCWIND.RCP45.ENS.ABS_PCTL50_2050_01_to_2050_12.tif: 46 * 105 * 12 = 57960 elements
geomet-climate-CMIP5.SFCWIND.RCP45.ENS.ABS_PCTL50_2100_01_to_2100_12.tif: 46 * 105 * 12 = 57960 elements
geomet-climate-CMIP5.SFCWIND.RCP85.ENS.ABS_PCTL50_2050_01_to_2050_12.tif: 46 * 105 * 12 = 57960 elements
geomet-climate-CMIP5.SFCWIND.RCP85.ENS.ABS_PCTL50_2100_01_to_2100_12.tif: 46 * 105 * 12 = 57960 elements
The 46 rows represent the number of latitude grid demarcations, 105 columns represent the number of longitude grid demarcations, and the number of cells (239 and 12) represent the number of months across the years (e.g., 239 months from January 1986 to November 2005)
Variable list:

* example of variable names - geomet-climate-CMIP5.SFCWIND.HISTO.ENS.ABS_PCTL50_1986_01_to_2005_11.239:

* geomet-climate-DCS: downscaled climate scnearios
* SFCWIND = mean near surface wind speed (metres per second)
* HISTO = Historical (1986-2005)
* HISTO may also be replaced with a future climate scenario, described below
* RCP45 = Representative Concentration Pathy 4.5 (climate change scenario)
* RCP85 = Representative Concentration Pathy 8.5 (climate change scenario)
* ENS: climate model ensemble
* ABS: actual values (as opposed to anomolies)
* PCTL50: ensemble percentile (50th percentile)
* 1986_01_to_2005_11: the whole geotiff file that this variable is in spans January 1986 to November 2005
* .239: corresponds to the 239th cell in the geotiff, which is the final month in the time series (November 2005 in this case)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
External dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Government of Canada Climate data Extraction tool (See more info below under ## Sharing/Access information)

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
SFCWIND_HISTO.csv
SFCWIND_RCP45_2050.csv
SFCWIND_RCP45_2100.csv
SFCWIND_RCP85_2050.csv
SFCWIND_RCP85_2100.csv

*Output from script, not included in Dryad repository

Number of variables: 25
Number of cases/rows: 481782
Variable list:

* X: a lake ID column

* nts: The National Topographic System or NTS, or the system used by Natural Resources Canada for topographic maps of Canada. This shows the NTS grid cell that the lake is in.

* latitude: lake latitude (decimal degrees)

* longitude: lake longitude (decimal degrees)

* ID: row number

* nts2: nts without the letter code (a broader level)

*SFCWIND_Jan_HISTO, SFCWIND_Feb_HISTO,...SFCWIND_Dec_HISTO: mean monthly near surface wind speed (metres per second)

*SFCWIND_DJF_HISTO, SFCWIND_MAM_HISTO, SFCWIND_JJA_HISTO, SFCWIND_SON_HISTO: mean seasonal near surface wind speed (metres per second)

*SFCWIND_Ann_HISTO: mean annual near surface wind speed (metres per second)

*nts_mean_flag: if 1, it means that the lake had a zero/NA for the cliamte value, and therefore it needed to be imputed by neighbouring lakes in its NTS

Missing data codes: NA
Specialized formats or other abbreviations used:
DJF: December, January, February
MAM: March, April, May
JJA: June, July, August
SON: September, October, November
Notes:
External dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Government of Canada Climate data Extraction tool (See more info below under ## Sharing/Access information)

##5_Arctic_Proj_CRU_Lakes_To_Grids.R
SCRIPT PURPOSE: Using Climatic Research Unit Climate data to assign 0.5 degree latitude and longitude grids to each lake

#########################################################################

DATA-SPECIFIC INFORMATION FOR: cru_ts4.01.2001.2010.tmp.dat.nc

*External dataset, not included in Dryad repository

Number of variables: 2 (excluding dimension variables)
Number of cases/rows: lon (longitude) 720 * lat (latitude) 360 * time 120 = 31104000 elements
Variable list:

* tmp[lon,lat,time]: near-surface temperatre (degrees Celsius)

* stn[lon,lat,time]: number of stations contributing to each datum

Missing data codes: NA
Specialized formats or other abbreviations used:
filename:
- cru = Climatic Research Unit
- ts = time series
- 4.01 = version of the dataset
- 2001.2010 = years covered by the dataset (2001-2010)
- tmp.dat = air temperature data
Notes:
External dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Climatic Research Unit (See more info below under ## Sharing/Access information).

#########################################################################

DATA-SPECIFIC INFORMATION FOR: AllLakeGridsrlakes3pt1km_latlong_zmean_pred_final.csv

*Output from script, not included in Dryad repository

Number of variables: 90
Number of cases/rows: 481782
Variable list:

* same as rlakes3pt1km_latlong_zmean_pred_final.csv (described in ##3_Arctic_Proj_Lake_Morphometry_Config.R above), but with a few changes to variable names to conform with this script, and a few additional variables

* Group: added Group column and set to Arctic to conform with script

* Lake_ID: equivalent to X, a lake ID column

* LatitudeDD: equivalent to latitude, renamed to conform to script

* LongitudeDD: equivalent to longitude, renamed to conform to script

* id - max_depth_m_final_flag_mean_deeper: same as rlakes3pt1km_latlong_zmean_pred_final.csv

* Flag: flag for whether longitude or latitude is NA, indicated by a zero

* Dist_km: distance in kilometres of the lake to the grid centre

* GridID: the 0.5 degree latitude * longitude grid cell that the lake corresponds to closest (e.g., a lake with GridID of Grid_51.25*-78.25 is closest to the grid where the centroid is at 51.25 degrees N latitude, and -78.25 degrees W longitude)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

#########################################################################

DATA-SPECIFIC INFORMATION FOR: UniqueGridsrlakes3pt1km_latlong_zmean_pred_final.csv

*Output from script, not included in Dryad repository

Number of variables: 6
Number of cases/rows: 4314
Variable list:

GridID: one of the 0.5 degree latitude * longitude grid cells that is in AllLakeGridsrlakes3pt1km_latlong_zmean_pred_final.csv. This dataset contains all of the unique grids across all of the lakes in the dataset (e.g., a lake with GridID of Grid_51.25-78.25 is closest to the grid where the centroid is at 51.25 degrees N latitude, and -78.25 degrees W longitude)

* Count: how many lakes corresponded to that grid cell

* ilo: longitude used for computing look-up coordinates for the 0.5 degree grid

* ila: latitude used for computing look-up coordinates for the 0.5 degree grid

* Glat: Grid cell latitude (decimal degrees)

* Glon: Grid cell longitude (decimal degrees)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

##6_Arctic_Proj_CRU_Add_Cld_to_Grids.R
SCRIPT PURPOSE: Using Climatic Research Unit Climate data to generated by grid and year tables of monthly, seasonal, and annual cloud cover metrics

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
cru_ts4.01.1981.1990.cld.dat.nc
cru_ts4.01.1991.2000.cld.dat.nc
cru_ts4.01.2001.2010.cld.dat.nc

*External dataset, not included in Dryad repository

Number of variables: 2 (excluding dimension variables)
Number of cases/rows: lon (longitude) 720 * lat (latitude) 360 * time 120 = 31104000 elements
Variable list:

* cld[lon,lat,time]: cloud cover (percentage)

* stn[lon,lat,time]: pre-2003, size of station pool from which three are used for each datum); 2003 onwards, number of stations contributing to each datum

Missing data codes: NA
Specialized formats or other abbreviations used:
filename:
- cru = Climatic Research Unit
- ts = time series
- 4.01 = version of the dataset
- 1981.1990, 1991.2000, 2001.2010 = years covered by the dataset (e.g., 2001-2010)
- cld.dat = cloud cover data
Notes:
External dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Climatic Research Unit (See more info below under ## Sharing/Access information).

#########################################################################

DATA-SPECIFIC INFORMATION FOR: UGrlakes3pt1km_latlong_zmean_pred_final.cru_ts4.01.cld.1981.2010.csv

*Output from script, not included in Dryad repository

Number of variables: 17
Number of cases/rows: 129420
Variable list:

GridID: one of the 0.5 degree latitude * longitude grid cells that is in AllLakeGridsrlakes3pt1km_latlong_zmean_pred_final.csv. This dataset contains all of the unique grids across all of the lakes in the dataset (e.g., a lake with GridID of Grid_51.25-78.25 is closest to the grid where the centroid is at 51.25 degrees N latitude, and -78.25 degrees W longitude)

* Year: year corresponding to the data in that row

*cldJan, cldFeb,... cldDec: mean monthly cloud cover (percent cover)

*cldAnn: mean annual cloud cover (percent cover)

*cldSum: mean summer cloud cover (June, July, August; percent cover)

*cldSpr: mean spring cloud cover (March, April, May; percent cover)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

#########################################################################

DATA-SPECIFIC INFORMATION FOR: CRU_cld.csv

*Output from script, not included in Dryad repository

Number of variables: 17
Number of cases/rows: 4314
Variable list:

GridID: one of the 0.5 degree latitude * longitude grid cells that is in AllLakeGridsrlakes3pt1km_latlong_zmean_pred_final.csv. This dataset contains all of the unique grids across all of the lakes in the dataset (e.g., a lake with GridID of Grid_51.25-78.25 is closest to the grid where the centroid is at 51.25 degrees N latitude, and -78.25 degrees W longitude)

*cldJan, cldFeb,... cldDec: mean monthly cloud cover (percent cover)

*cldAnn: mean annual cloud cover (percent cover)

*cldSum: mean summer cloud cover (June, July, August; percent cover)

*cldSpr: mean spring cloud cover (March, April, May; percent cover)

*na_flag: if cldAnn is NA, the value is 1, if not it is 0
Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

##7_Arctic_Proj_CRU_Add_Elev_to_Grids.R
SCRIPT PURPOSE: Using ncdf with 0.5degree gridded elevation data to obtain site elevation with the ETOPO1 dataset

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DATA-SPECIFIC INFORMATION FOR:
etopo1.nc

*External dataset, not included in Dryad repository

Number of variables: 2 (excluding dimension variables)
Number of cases/rows: lon (longitude) 6901 * lat (latitude) 3301 = 22780201 elements
Variable list:

* crs[]: CRS definition

* Band1[lon,lat]: GDAL Band Number 1 (this is the elevation)

Missing data codes: -32767
Specialized formats or other abbreviations used:
- GDAL (Geospatial Data Abstraction Library), a geospatial computer software library.
Notes:
External dataset. Accessible online at https://www.ncei.noaa.gov/products/etopo-global-relief-model (NOAA; See more info below under ## Sharing/Access information).

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
UniqueGridsElevsrlakes3pt1km_latlong_zmean_pred_final.csv

*Output from script, not included in Dryad repository

Number of variables: 10
Number of cases/rows: 4314
Variable list:

* Same as UniqueGridsrlakes3pt1km_latlong_zmean_pred_final.csv with a few additional variables

GridID: one of the 0.5 degree latitude * longitude grid cells that is in AllLakeGridsrlakes3pt1km_latlong_zmean_pred_final.csv. This dataset contains all of the unique grids across all of the lakes in the dataset (e.g., a lake with GridID of Grid_51.25-78.25 is closest to the grid where the centroid is at 51.25 degrees N latitude, and -78.25 degrees W longitude)

* Count: how many lakes corresponded to that grid cell

* ilo: longitude used for computing look-up coordinates for the 0.5 degree grid

* ila: latitude used for computing look-up coordinates for the 0.5 degree grid

* Glat: Grid cell latitude (decimal degrees)

* Glon: Grid cell longitude (decimal degrees)

* Flag: flag for whether longitude or latitude is NA, indicated by a zero

* Dist_km: distance in kilometres of the lake to the grid centre

* ElevMneto1: mean elevation within the grid cell, rounded to one significant digit

* ElevSDeto1: standard deviation of elevation within the grid cell, rounded to one significant digit

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

##8_Arctic_Proj_CRU_Add_Rad_RadCld_to_Grids.R
SCRIPT PURPOSE: Using Unique Grids set compute ground level Radiation without and with cloud cover

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DATA-SPECIFIC INFORMATION FOR:
CRU_crad.csv

*Output from script, not included in Dryad repository

Number of variables: 17
Number of cases/rows: 4314
Variable list:

GridID: one of the 0.5 degree latitude * longitude grid cells that is in AllLakeGridsrlakes3pt1km_latlong_zmean_pred_final.csv. This dataset contains all of the unique grids across all of the lakes in the dataset (e.g., a lake with GridID of Grid_51.25-78.25 is closest to the grid where the centroid is at 51.25 degrees N latitude, and -78.25 degrees W longitude)

*cradJan, cradFeb,... cradDec: mean monthly solar radiation, corrected for cloud cover cloud cover (Watts per metres squared)

*cradAnn: mean annual cloud cover (Watts per metres squared)

*cradSum: mean summer cloud cover (June, July, August; Watts per metres squared)

*cradSpr: mean spring cloud cover (March, April, May; Watts per metres squared)

*na_flag: if cradAnn is NA, the value is 1, if not it is 0
Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

##9_Arctic_Proj_CRU_Add_Climate_Metrics_to_GridYears.R
SCRIPT PURPOSE: Using Unique Grids by Year compute additional climate metrics

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DATA-SPECIFIC INFORMATION FOR:
TM_HISTO_added_temp_metrics.csv
TM_RCP45_2050_added_temp_metrics.csv
TM_RCP45_2100_added_temp_metrics.csv
TM_RCP85_2050_added_temp_metrics.csv
TM_RCP85_2100_added_temp_metrics.csv

*Output from script, not included in Dryad repository

Number of variables: 26
Number of cases/rows: 481782
Variable list:

* X: a lake ID column

* nts: The National Topographic System or NTS, or the system used by Natural Resources Canada for topographic maps of Canada. This shows the NTS grid cell that the lake is in.

* latitude: lake latitude (decimal degrees)

* longitude: lake longitude (decimal degrees)

* ID: row number

* nts2: nts without the letter code (a broader level)

* nts_mean_flag: if 1, it means that the lake had a zero/NA for the cliamte value, and therefore it needed to be imputed by neighbouring lakes in its NTS

* distinct_clim: a column indicating the ID of each unique set of temperature values

* J_Spr0: day of year following the last spring day when the 30-day running mean daily air temperature <0 °C

* J_Spr4: day of year following the last spring day when the 30-day running mean daily air temperature <4 °C

* J_Aut0: day of year following the last fall day when the 30-day running mean daily air temperature >0 °C

* J_Aut4: day of year following the last fall day when the 30-day running mean daily air temperature >4 °C

* T_Spr0: mean air temperature for the three-month period where the central month contains J_Spr0.

* T_Aut0: mean air temperature for the three-month period where the central month contains J_Aut0.

* tmpDecM, tmpJanP: Estimate missing Dec and Jan tmp values at beginning and end respect of each GridID time series

* YY_Spr0: fixed year at 2010 for the purposes of streamlining code, this is for the historical period, so the year is irrelevant

* MM_Spr0: month that contains J_Spr0 represented by a number between 1 and 12

* DD_Spr0: day within the month that contains J_Spr0 represented by the number within that month

* YY_Aut0: fixed year at 2010 for the purposes of streamlining code, this is for the historical period, so the year is irrelevant

* MM_Aut0: month that contains J_Aut0 represented by a number between 1 and 12

* DD_Aut0: day within the month that contains J_Aut0 represented by the number within that month

* S40WR: air warming rate °C/day from J_Spr0 to J_Spr4

* A40CR: air cooling rate °C/day from J_Aut4 to J_Aut0

* Ang_Spr0: angular elevation of the sun above the horizon at noon on J_Spr0

Missing data codes: NA
Specialized formats or other abbreviations used:
DD: Day
MM: Month
YY: Year
WR: warming rate
CR: cooling rate
Ang: angle
Spr: spring
Aut: fall/autumn
T: mean air temperature
J: day of year
Notes:
Output from an external dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Government of Canada Climate data Extraction tool (See more info below under ## Sharing/Access information)

##10_Arctic_Proj_Dataset_Assembly.R
SCRIPT PURPOSE: Assembling the necessary lake and climate data to conduct ice break-up/freeze-up/thickness, thermocline depth, and surface temperature estimates for Historical, RCP4.5, and RCP8.5 conditions (2050 and 2100)

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
rlakes3pt1km_assembled.csv

*Output from script, but included in Dryad repository for convenience because it is an important intermediate dataset

Number of variables: 76
Number of cases/rows: 481782
Variable list:

* X: a lake ID column

* id: lake ID

* name: another lake ID

* n_id: unknown, not used in analyses, relic from Campana et al. 2020

* nts: The National Topographic System or NTS, or the system used by Natural Resources Canada for topographic maps of Canada. This shows the NTS grid cell that the lake is in.

* latitude: lake latitude (decimal degrees)

* longitude: lake longitude (decimal degrees)

* area_sq_km: lake area in square kilometres

* perimeter_km: lake perimeter in square kilometres

* fetch_km: lake fetch (maximum length) in kilometres

* is_included: all are TRUE. Shows if the lake is included in the dataset (they all are). Relic from Campana et al. 2020

* is_lake: all are TRUE. Shows if the row is a lake, which they all are. Relic from Campana et al. 2020.

* definition: unknown, not used in analyses, relic from Campana et al. 2020

* prov: province that the lake is in

* elevation_m: lake elevation in metres

* mean_depth_m_final: lake mean depth in metres, the final version to be used in the analysis

* max_depth_m_final: lake maximum depth in metres, the final version to be used in the analysis

* lake_size_class: area_sq_km binned into one of five categories - 0.1 - 1 km^2, 1 - 10 km^2, 10 - 100 km^2, 100 - 1000 km^2, >= 1000 km^2

* ID: row number

* nts2: nts without the letter code (a broader level)

* TM_Jul_HISTO: mean July air temperature (degrees Celsius), historical climate period (HISTO; 1986-2005)

* TM_JJA_HISTO: mean summer air temperature (June, July, August; degrees Celsius), historical climate period (HISTO; 1986-2005)

* TM_Ann_HISTO: mean annual air temperature (degrees Celsius), historical climate period (HISTO; 1986-2005)

* TM_Jul_RCP45_2050, TM_Jul_RCP45_2100, TM_Jul_RCP85_2050, TM_Jul_RCP85_2100: mean July air temperature (degrees Celsius), projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* TM_JJA_RCP45_2050, TM_JJA_RCP45_2100, TM_JJA_RCP85_2050, TM_JJA_RCP85_2100: mean summer air temperature (June, July, August; degrees Celsius), projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* TM_Ann_RCP45_2050, TM_Ann_RCP45_2100, TM_Ann_RCP85_2050, TM_Ann_RCP85_2100: mean annual air temperature (degrees Celsius), projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* PR_Aug_HISTO: total August precipitation (millimetres), historical climate period (HISTO; 1986-2005)

* PR_Aug_RCP45_2050, PR_Aug_RCP45_2100, PR_Aug_RCP85_2050, PR_Aug_RCP85_2100: total August precipitation (millimetres), projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* SFCWIND_Jul_HISTO: mean July near surface wind speed (metres per second), historical climate period (HISTO; 1986-2005)

* SFCWIND_Jul_RCP45_2050, SFCWIND_Jul_RCP45_2100, SFCWIND_Jul_RCP85_2050, SFCWIND_Jul_RCP85_2100: mean July near surface wind speed (metres per second), projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* SFCWIND_JJA_HISTO: mean Summer near surface wind speed (metres per second), historical climate period (HISTO; 1986-2005)

* SFCWIND_JJA_RCP45_2050, SFCWIND_JJA_RCP45_2100, SFCWIND_JJA_RCP85_2050, SFCWIND_JJA_RCP85_2100: mean Summer near surface wind speed (June, July, August; metres per second), projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* J_Aut0_HISTO: day of year following the last fall day when the 30-day running mean daily air temperature >0 °C, historical climate period (HISTO; 1986-2005)

* T_Aut0_HISTO: mean air temperature for the three-month period where the central month contains J_Aut0, historical climate period (HISTO; 1986-2005)

* J_Spr0_HISTO: day of year following the last spring day when the 30-day running mean daily air temperature <0 °C, historical climate period (HISTO; 1986-2005)

* Ang_Spr0_HISTO: angular elevation of the sun above the horizon at noon on J_Spr0, historical climate period (HISTO; 1986-2005)

* J_Aut0_RCP45_2050, J_Aut0_RCP45_2100, J_Aut0_RCP85_2050, J_Aut0_RCP85_2100: day of year following the last fall day when the 30-day running mean daily air temperature >0 °C, projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* T_Aut0_RCP45_2050, T_Aut0_RCP45_2100, T_Aut0_RCP85_2050, T_Aut0_RCP85_2100: mean air temperature for the three-month period where the central month contains J_Aut0, projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* J_Spr0_RCP45_2050, J_Spr0_RCP45_2100, J_Spr0_RCP85_2050, J_Spr0_RCP85_2100: day of year following the last spring day when the 30-day running mean daily air temperature <0 °C, projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* Ang_Spr0_RCP45_2050, Ang_Spr0_RCP45_2100, Ang_Spr0_RCP85_2050, Ang_Spr0_RCP85_2100: angular elevation of the sun above the horizon at noon on J_Spr0, projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

*cradJul: mean July solar radiation, corrected for cloud cover cloud cover (Watts per metres squared)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

##11_Arctic_Proj_Wind_atlas_weibull.R
SCRIPT PURPOSE: Get weibull distributions for wind atlas data

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
60_243 10 time scale.xls
60_261 10 min time scale.xls
62_238 10 min time scale.xls
66_255 10 min time scale.xls
68_232 10 min time scale.xls
Dan Sites 10 min time scale.xls

*External dataset, not included in Dryad repository

Number of variables:
60_243 10 time scale.xls - 22
60_261 10 min time scale.xls - 22
62_238 10 min time scale.xls - 23
66_255 10 min time scale.xls - 23
68_232 10 min time scale.xls - 21
Dan Sites 10 min time scale.xls - 12
Number of cases/rows: 13248
Variable list:

* Count: row numer

* hr_blck: increasing intergers in sections of 6 to calculate 1-hour, 8-hour and 24-hour mean winds from the 10-minute wind that is in the original versions of the dataset.

* s1, s2,...s20: wind at one of twenty sites (metres per second), each row corresponds to the mean wind for a ten minute period. The time series is representattive of the 92 days that span June, July, and August (note, Dan Sites 10 min time scale.xls has 9 sites)

* Grp_1hr: groups every six observations by increasing integers (e.g., the first six rows in the dataset have a value of "1", the 7th to 12th rows have "2") in order to calculate the mean 1-hour wind

* Grp_8hr: groups every six observations by increasing integers (e.g., the first 48 rows in the dataset have a value of "1", the 49th to 96th rows have "2") in order to calculate the mean 8-hour wind

* Grp_24hr: groups every six observations by increasing integers (e.g., the first 144 rows in the dataset have a value of "1", the 145th to 288th rows have "2") in order to calculate the mean 24-hour wind

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
External dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Wind Atlas, Government of Canada (See more info below under ## Sharing/Access information).

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
median_shape_1hr_df.csv

*Script output, but included in the Dryad repository for convenience in executing subsequent scripts

Number of variables: 1
Number of cases/rows: 1
Variable list:

* median_shape_1hr: median Weibull shape across all sites for mean 1-hour wind

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

##12_Arctic_Proj_Projections.R
SCRIPT PURPOSE: Making historical and future projections for Arctic lakes, lake temperature, stratification, and ice dynamics

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
rlakes3pt1km_assembled_sample.csv

*Output from script, but included in Dryad repository for convenience because it is an important intermediate dataset

Number of variables: 76
Number of cases/rows: 9623
Variable list:

* same as rlakes3pt1km_assembled.csv, see above under script ##10_Arctic_Proj_Dataset_Assembly.R

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
This dataset is a sample of rlakes3pt1km_assembled.csv, approximately 2% of the dataset.

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
Gorham and Boyce 1989 Figure 1 5 groups.csv

*External dataset, not included in Dryad repository

Number of variables: 66
Number of cases/rows: 3
Variable list:

* X: x-axis value of Gorham and Boyce (1989) Figure 1, lake maximum length (L) in kilometres (i.e., fetch), stratified lakes

* Y: y-axis value of Gorham and Boyce (1989) Figure 1, lake maximum depth (H) in metres, stratified lakes

* Group: the group/geographical location that the lake is a part (e.g., N.W. Ontario = Northwestern Ontario lakes). This dataset just includes 5 groups, those from Northeastern North America.

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
External dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Gorham and Boyce (1989) (See more info below under ## Sharing/Access information).

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
Gorham and Boyce 1989 Figure 1 Lake Points.csv

*External dataset, not included in Dryad repository

Number of variables: 152
Number of cases/rows: 3
Variable list:

* x_L_km: x-axis value of Gorham and Boyce (1989) Figure 1, lake maximum length (L) in kilometres (i.e., fetch), features all stratified lakes in that paper's dataset

* y_H_m: y-axis value of Gorham and Boyce (1989) Figure 1, lake maximum depth (H) in metres, features all stratified lakes in that paper's dataset

* Group: the group/geographical location that the lake is a part (e.g., N.W. Ontario = Northwestern Ontario lakes)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
External dataset. Comprised of data from sources that may not necessarily comply with CC0 licence requirements. Gorham and Boyce (1989) (See more info below under ## Sharing/Access information).

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
rlakes3pt1km_projections.csv

*Output from script, not included in Dryad repository

Number of variables: 202
Number of cases/rows: 481782
Variable list:

* Variables 1-76 (column "X" to "cradJul") are the same as rlakes3pt1km_assembled.csv, see above under script ##10_Arctic_Proj_Dataset_Assembly.R

* IceBU_HISTO, IceBU_RCP45_2050, IceBU_RCP45_2100, IceBU_RCP85_2050, IceBU_RCP85_2100: BU = ice break-up (day of year) under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* IceFU_HISTO, IceFU_RCP45_2050, IceFU_RCP45_2100, IceFU_RCP85_2050, IceFU_RCP85_2100: BU = ice freeze-up (day of year) under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* Icefree_HISTO, Icefree_RCP45_2050, Icefree_RCP45_2100, Icefree_RCP85_2050, Icefree_RCP85_2100: Icefree = ice-free period (days) under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* Icecover_HISTO, Icecover_RCP45_2050, Icecover_RCP45_2100, Icecover_RCP85_2050, Icecover_RCP85_2100: Icecover = ice-cover period (days) under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* Icethick_HISTO, Icethick_RCP45_2050, Icethick_RCP45_2100, Icethick_RCP85_2050, Icethick_RCP85_2100: Icethick = ice thickness (metres) under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* T_Peak_HISTO, T_Peak_RCP45_2050, T_Peak_RCP45_2100, T_Peak_RCP85_2050, T_Peak_RCP85_2100: T_Peak = maximum surface water tempearture (°C), from Sharma et al. (2007) model under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* TMAX_HISTO, TMAX_RCP45_2050, TMAX_RCP45_2100, TMAX_RCP85_2050, TMAX_RCP85_2100: TMAX = maximum surface water tempearture (°C), from Gillis et al. (2021) model under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* T_MEAN_HISTO, T_MEAN_RCP45_2050, T_MEAN_RCP45_2100, T_MEAN_RCP85_2050, T_MEAN_RCP85_2100: mean of T_Peak and TMAX columns

* fetch_m: lake fetch (maximum length) in metres

* density_diff_HISTO, density_diff_RCP45_2050, density_diff_RCP45_2100, density_diff_RCP85_2050, density_diff_RCP85_2100: density_diff = modelled density_diff difference modelled from equation #9 in the accompanying article, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* epi_density_HISTO, epi_density_RCP45_2050, epi_density_RCP45_2100, epi_density_RCP85_2050, epi_density_RCP85_2100: epi_density = epilimnion density based on T_MEAN columns, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* hypo_density_HISTO, hypo_density_RCP45_2050, hypo_density_RCP45_2100, hypo_density_RCP85_2050, hypo_density_RCP85_2100: hypo_density = hypolimnion density based on epi_density columns plus density_diff columns, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* hypo_temperature_HISTO, hypo_temperature_RCP45_2050, hypo_temperature_RCP45_2100, hypo_temperature_RCP85_2050, hypo_temperature_RCP85_2100: hypo_temperature = hypolimnion temperature based on hypo_density columns, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* SFCWIND_JJA_HISTO_Storm, SFCWIND_JJA_RCP45_2050_Storm, SFCWIND_JJA_RCP45_2100_Storm, SFCWIND_JJA_RCP85_2050_Storm, SFCWIND_JJA_RCP85_2100_Storm: mean Summer near surface wind speed under estimated storm conditions (June, July, August; metres per second), under historical climate period (HISTO; 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* CD10_HISTO, CD10_RCP45_2050, CD10_RCP45_2100, CD10_RCP85_2050, CD10_RCP85_2100: CD10 = the drag coefficient for surface winds at 10 m, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* strat_HISTO_morpho, strat_RCP45_2050_morpho, strat_RCP45_2100_morpho, strat_RCP85_2050_morpho, strat_RCP85_2100_morpho: predicted stratification, stratified is 1, mixed is 0, If fetch is greater than or equal to 5 km, and depth is greater than 34 m, then the lake shall be deemed stratified. This prevents massive lakes from being erroneously misclassified as mixed, when the odds of them actually being mixed are quite low since the maximum thermocline depth we are using is 20 m, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* dense_lake_HISTO, dense_lake_RCP45_2050, dense_lake_RCP45_2100, dense_lake_RCP85_2050, dense_lake_RCP85_2100: If a lake doesn't display the minimum density difference, then it is not stratified. Value of 0.0005 (kilograms per metre cubed), under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100. If the lake has a density of less than or equal to 0.0005, there is a value of 1, otherwise it is 0.

* strat_HISTO, strat_RCP45_2050, strat_RCP45_2100, strat_RCP85_2050, strat_RCP85_2100: predicted stratification, stratified is 1, mixed is 0, with Gorham and Boyce (1989) model, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* strat_HISTO_therm, strat_RCP45_2050_therm, strat_RCP45_2100_therm, strat_RCP85_2050_therm, strat_RCP85_2100_therm: for stratified lakes, Incorporate existing stratification state (based on temperature) into subsequent ifelse statements so that this step isn't overwritten, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* cold_lake_HISTO, cold_lake_RCP45_2050, cold_lake_RCP45_2100, cold_lake_RCP85_2050, cold_lake_RCP85_2100: a column to show if the lake has an epilimnetic vs. hypolimnetic temperature difference of 2 degrees Celsius, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* g_prime_HISTO, g_prime_RCP45_2050, g_prime_RCP45_2100, g_prime_RCP85_2050, g_prime_RCP85_2100: density difference between epilimnion and hypolimnion at the time of maximum heat content (kilograms per metres cubed), under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* tau_HISTO, tau_RCP45_2050, tau_RCP45_2100, tau_RCP85_2050, tau_RCP85_2100: wind stress associated with summer storms (i.e., stress associated with the maximum sustained wind strength likely to be experienced by the lake during summer), under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* h_HISTO, h_RCP45_2050, h_RCP45_2100, h_RCP85_2050, h_RCP85_2100: for stratified lakes, modelled thermocline depth in metres using model from Gorham and Boyce (1989), under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* alpha_HISTO, alpha_RCP45_2050, alpha_RCP45_2100, alpha_RCP85_2050, alpha_RCP85_2100: h_HISTO, h_RCP45_2050, h_RCP45_2100, h_RCP85_2050, h_RCP85_2100, each divided by max_depth_m_final, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* Hcrit_HISTO, Hcrit_RCP45_2050, Hcrit_RCP45_2100, Hcrit_RCP85_2050, Hcrit_RCP85_2100: for stratified lakes, modelled critical mixing depth in metres using model from Gorham and Boyce (1989), under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* JM_HISTO, JM_RCP45_2050, JM_RCP45_2100, JM_RCP85_2050, JM_RCP85_2100: date of TMAX, or the maximum surface water temperature (day of year), or the midpoint between the ice break-up and freeze-up dates, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
Gillis, D. P., Minns, C. K. & Shuter, B. J. Predicting open-water thermal regimes of temperate North American lakes. Can. J. Fish. Aquat. Sci. 1–78 (2021) doi:10.1139/cjfas-2020-0140.
Gorham, E. & Boyce, F. M. Influence of lake surface area and depth upon thermal stratification and the depth of the summer thermocline. J. Great Lakes Res. 15, 233–245 (1989).
Sharma, S., Jackson, D. A., Minns, C. K. & Shuter, B. J. Will northern fish populations be in hot water because of climate change? Glob. Chang. Biol. 13, 2052–2064 (2007).

##13_Arctic_Proj_Analysis_A_Batches.R
SCRIPT PURPOSE: Creating batches (subsets of the main dataset) for further analysis

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
A_rlakes3pt1km_projections.csv
B_rlakes3pt1km_projections.csv
C_rlakes3pt1km_projections.csv
D_rlakes3pt1km_projections.csv
E_rlakes3pt1km_projections.csv
F_rlakes3pt1km_projections.csv
G_rlakes3pt1km_projections.csv
H_rlakes3pt1km_projections.csv
I_rlakes3pt1km_projections.csv
J_rlakes3pt1km_projections.csv
K_rlakes3pt1km_projections.csv
L_rlakes3pt1km_projections.csv
M_rlakes3pt1km_projections.csv
N_rlakes3pt1km_projections.csv
O_rlakes3pt1km_projections.csv
P_rlakes3pt1km_projections.csv
Q_rlakes3pt1km_projections.csv
R_rlakes3pt1km_projections.csv
S_rlakes3pt1km_projections.csv
T_rlakes3pt1km_projections.csv

*Output from script, not included in Dryad repository

Number of variables: 202
Number of cases/rows:
A_rlakes3pt1km_projections.csv - 25000
B_rlakes3pt1km_projections.csv - 25000
C_rlakes3pt1km_projections.csv - 25000
D_rlakes3pt1km_projections.csv - 25000
E_rlakes3pt1km_projections.csv - 25000
F_rlakes3pt1km_projections.csv - 25000
G_rlakes3pt1km_projections.csv - 25000
H_rlakes3pt1km_projections.csv - 25000
I_rlakes3pt1km_projections.csv - 25000
J_rlakes3pt1km_projections.csv - 25000
K_rlakes3pt1km_projections.csv - 25000
L_rlakes3pt1km_projections.csv - 25000
M_rlakes3pt1km_projections.csv - 25000
N_rlakes3pt1km_projections.csv - 25000
O_rlakes3pt1km_projections.csv - 25000
P_rlakes3pt1km_projections.csv - 25000
Q_rlakes3pt1km_projections.csv - 25000
R_rlakes3pt1km_projections.csv - 25000
S_rlakes3pt1km_projections.csv - 25000
T_rlakes3pt1km_projections.csv - 6782
Variable list:

* Each dataset is a subset of rlakes3pt1km_assembled.csv, see above under script ##10_Arctic_Proj_Dataset_Assembly.R. They are each 25000 rows, file starting with A is 1-25000, file starting with B is 25001-50000, etc. Each are 25000, except for the last one, which is rows 475001-481782, for 6782. All of the columns are the same

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

##14_Arctic_Proj_Analysis_Lake_Volume_Cals.R
SCRIPT PURPOSE: Adding lake volume to the batches of rlakes3pt1km_projections.csv (A_rlakes3pt1km_projections.csv, B_rlakes3pt1km_projections.csv, etc.)

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
rlakes3pt1km_projections_with_volume.csv

*Output from script, not included in Dryad repository

Number of variables: 203
Number of cases/rows: 481782
Variable list:

* This dataset is the same as rlakes3pt1km_assembled.csv, see above under script ##10_Arctic_Proj_Dataset_Assembly.R, except that it has the following extra column:

* volume_m3: lake volume in cubic metres

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

##15_Arctic_Proj_HydroComp.R
SCRIPT PURPOSE: Comparing HydroLAKES and the Arctic GIS lake database

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
HydroLAKES_ECO_Spreadsheet.csv

*External dataset, not included in Dryad repository

Number of variables: 29
Number of cases/rows: 452927
Variable list:

* See HydroLAKES technical documentation for column name information: https://data.hydrosheds.org/file/technical-documentation/HydroLAKES_TechDoc_v10.pdf. Only essential variables are described below that were added on for the current study.

* ECOZONE: Ecozone, signified by its numerical ID,that the lake is in according to Ricketts et al. (1999). Ricketts, T. A. et al. Terrestrial Ecoregions of North America - A conservation assessment. (Island Press Books, 1999).

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
Messager, M. L., Lehner, B., Grill, G., Nedeva, I. & Schmitt, O. Estimating the volume and age of water stored in global lakes using a geo-statistical approach. Nat. Commun. 7, 1–11 (2016). https://doi.org/10.1038/ncomms13603

##16_Arctic_Proj_Daily_Water_Temps.R
SCRIPT PURPOSE: Calculating daily water temps for Arctic lakes

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
A_Daily_lake_temps_HISTO.csv
A_Daily_lake_temps_RCP45_2050.csv
A_Daily_lake_temps_RCP45_2100.csv
A_Daily_lake_temps_RCP85_2050.csv
A_Daily_lake_temps_RCP85_2100.csv
B_Daily_lake_temps_HISTO.csv
B_Daily_lake_temps_RCP45_2050.csv
B_Daily_lake_temps_RCP45_2100.csv
B_Daily_lake_temps_RCP85_2050.csv
B_Daily_lake_temps_RCP85_2100.csv
...C_, D_, etc....
T_Daily_lake_temps_HISTO.csv
T_Daily_lake_temps_RCP45_2050.csv
T_Daily_lake_temps_RCP45_2100.csv
T_Daily_lake_temps_RCP85_2050.csv
T_Daily_lake_temps_RCP85_2100.csv

*Output from script, not included in Dryad repository

Number of variables: 3
Number of cases/rows: across the 100 subsets, the number of rows ranges from 737920 (T_Daily_lake_temps_HISTO.csv) - 3635844 (O_Daily_lake_temps_RCP85_2100)
Variable list:

* The numeric dataset subsets related to the lakes within each of those described in scripts ##13_Arctic_Proj_Analysis_A_Batches.R and ##14_Arctic_Proj_Analysis_Lake_Volume_Cals.R

* X: a lake ID column

* day: day of year during the open water season

* T_HISTO | T_RCP45_2050 | T_RCP45_2100 | T_RCP85_2050 | T_RCP85_2100: daily lake epilimnetic temperature in degrees Celsius, under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100, depending on the corresponding climate scenario dataset

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

##17_Arctic_Proj_Daily_Water_Temps_Bind.R
SCRIPT PURPOSE: binding together the daily lake temperature dataset batches from script ##16_Arctic_Proj_Daily_Water_Temps.R

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
Daily_lake_temps_HISTO.csv
Daily_lake_temps_RCP45_2050.csv
Daily_lake_temps_RCP45_2100.csv
Daily_lake_temps_RCP85_2050.csv
Daily_lake_temps_RCP85_2100.csv

*Output from script, not included in Dryad repository

Number of variables: 3
Number of cases/rows:
Daily_lake_temps_HISTO.csv - 51604638
Daily_lake_temps_RCP45_2050.csv - 58155550
Daily_lake_temps_RCP45_2100.csv - 60079813
Daily_lake_temps_RCP85_2050.csv - 59922957
Daily_lake_temps_RCP85_2100.csv - 69745034
Variable list:

* X: a lake ID column

* day: day of year during the open water season

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
Daily_lake_temps_HISTO.csv is A_Daily_lake_temps_HISTO.csv, B_Daily_lake_temps_HISTO.csv... etc. T_Daily_lake_temps_HISTO.csv stacked to give the complete dataset of all lakes. The subsequeny future climate scenario datasets are organized accordingly as well (each batches/subset dataset is brought together)

##18_Arctic_Proj_Analysis_Thermal_Hab_Cals.R
SCRIPT PURPOSE: Thermal habitat calculations on Arctic lakes

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
rlakes3pt1km_projections_thermal_hab.csv

*Output from script, but included in Dryad repository for convenience as it is an important intermediate output

Number of variables: 407
Number of cases/rows: 447077
Variable list:

* Columns 1-203 (column "X" to column "volume_3") are the same as rlakes3pt1km_projections_with_volume.csv which is detailed in script ##14_Arctic_Proj_Analysis_Lake_Volume_Cals.R

* epi_volume_HISTO, epi_volume_RCP45_2050, epi_volume_RCP45_2100, epi_volume_RCP85_2050, epi_volume_RCP85_2100, hypo_volume_HISTO, hypo_volume_RCP45_2050, hypo_volume_RCP45_2100, hypo_volume_RCP85_2050, hypo_volume_RCP85_2100: epilimnion (epi) or hypolimnion (hypo) volume under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* T_HISTO_cold_days (column 214) - T_RCP85_2100_warm_days_final (column 258): the number of days/year that the daily surface/epi water temperature is either:

* below the cold upper limit (cold)
* greater than the cold_persist_limit (cold_persist)
* Actual thermal habitat with respect to establishment and persistence. These lakes get "eliminated" if they fail the establishment and persistence criteria (final)
* at or above cool_lower_limit and below cool_upper_limit (cool)
* at or above cool_lower_limit and below cool_upper_limit for lakes that have maximum lake temperatures at or above the cool_estab_limit (cool_estab)
* at or above warm_lower_limit and below warm_upper_limit (warm)
* at or above warm_lower_limit and below warm_upper_limit for lakes that have maximum lake temperatures at or above the warm_estab_limit (warm_estab)
* Normalized to a percentage of the entire year's daily volume supply (e.g., HISTO_cold_volume_days_norm = HISTO_cold_volume_days / 365 / volume_m3 * 100)
* The difference between the normalized volume days in a future climate scenario vs. the historical value (norm_diff) (e.g., HISTO_RCP45_2050_cold_volume_days_norm_diff = RCP45_2050_cold_volume_days_norm - HISTO_cold_volume_days_norm)
* under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* HISTO_cold_volume_days (column 259) - HISTO_RCP85_2100_warm_estab_volume_days_norm_diff (column 396): thermal habitat volume days according to:

* thermal guild (cold, cool, warm)
* coldwater thermal guild volume days just during the Ice-free season (Icefree). This excludes the coldwater habitat that dominates when the lake is covered in ice
* the volume days where coldwater species can persist (persist), and warmwater and coolwater species can establish (estab)
* Actual thermal habitat with respect to establishment and persistence. These lakes get "eliminated" if they fail the establishment and persistence criteria (final)
* under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* lake_size_class_2: if fetch_km is less than 5 kilometres, "Small", if not, "Large"

* h_zmax_ratio_HISTO: h_HISTO (thermocline depth in metres) divided by max_depth_m_final (maximum lake depth in metres)

* lake_fish_class_HISTO, lake_fish_class_RCP45_2050, lake_fish_class_RCP45_2100, lake_fish_class_RCP85_2050, lake_fish_class_RCP85_2100: whether the lake is:

* thermally diverse ("Thermally_Diverse", meaning it is stratified and its ice thickness (metres) is less than or equal to its mean_depth_m_final (mean depth in metres))
* thermally uniform ("Thermally_Uniform", meaning it is not stratified and its ice thickness (metres) is less than or equal to its mean_depth_m_final (mean depth in metres))
* barren ("Barren", meaning that its ice thickness (metres) is greater than its mean_depth_m_final (mean depth in metres))
* under historical climate conditions (HISTO, 1986-2005) and projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2050 or 2100

* T_MEAN_HISTO_RCP85_2100: lake-specific difference between T_MEAN_RCP85_2100 and T_MEAN_HISTO (i.e., T_MEAN_RCP85_2100 minus T_MEAN_HISTO)

* IceBU_HISTO_RCP85_2100: lake-specific difference between IceBU_RCP85_2100 and IceBU_HISTO (i.e., IceBU_RCP85_2100 minus IceBU_HISTO)

* IceFU_HISTO_RCP85_2100: lake-specific difference between IceFU_RCP85_2100 and IceFU_HISTO (i.e., IceFU_RCP85_2100 minus IceFU_HISTO)

* Icefree_HISTO_RCP85_2100: lake-specific difference between Icefree_RCP85_2100 and Icefree_HISTO (i.e., Icefree_RCP85_2100 minus Icefree_HISTO)

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
FEOW_ID_ArcticLakeid.csv

Number of variables: 3
Number of cases/rows: 447079
Variable list:

* V1: row number

* id: lake ID

* FEOW_ID: Freshwater Ecoregions of the World, assigned to each lake, identified by the code. Legend for codes: https://www.feow.org/ecoregions/list

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:
Derived from external dataset, usage notes and licence information below.

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
ne_10m_lakes.shp

*External dataset, not included in Dryad repository

Number of variables: 41 fields
Number of cases/rows: 1355 features
Variable list:

* Coordinates:
min max
x -165.96558 177.15438
y -50.66967 81.95521

* proj4string : [+proj=longlat +datum=WGS84 +no_defs]

* name: lake name in English

* subsequent columns are not described as they are not central to our mapping code. See https://www.naturalearthdata.com/downloads/10m-physical-vectors/10m-lakes/ for more details

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
polys_sf_trans_cropped.gpkg

* Output from script, but included in Dryad repository for convenience because it is an important intermediate dataset

Number of variables: 105 fields
Number of cases/rows: 4374 features
Variable list:

* Geometry type: GEOMETRY

* Dimension: XY

* Bounding box: xmin: -2227185 ymin: 1204291 xmax: 1607910 ymax: 3832041

* Projected CRS: NAD83 / Canada Atlas Lambert

* subsequent columns contain key lake metrics for supplementary figure maps, based on grid cell means of these values. See Supplementary Figures 15–32 for maps showing projected changes in all metrics presented in this study summarized as regional averages represented by 0.5° grid cells. See captions for information on the variables represented in this output.

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

##19_Arctic_Proj_Testing_Lake_Temp_Thermocline_Models_Vital_Alexie_Toolik.R
19M)

19N) external: CMIP5.SFCWIND.HISTO.SUMMER.ABS_PCTL50.csv

SCRIPT PURPOSE: Testing lake temperature and stratification models with Alexie and Vital Water temp data, as well as Toolik lakes

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
Vital_Lake_Temperature_Data.csv
Alexie_Lake_Temperature_Data.csv

Number of variables: 6
Number of cases/rows:
Vital_Lake_Temperature_Data.csv - 610
Alexie_Lake_Temperature_Data.csv - 9039
Variable list:

* group: Arctic (used to distinguish from Toolik lakes in plotting and analyses)

* lake: lake name (Alexie or Vital)

* year: 2013 (remvoed 2012 from Alexie because incomplete)

* jd: day of year (stands for Julian Day), numerical value

* z: water depth of temperature measurement in metres

* tmp: daily water temperature at depth in degrees Celsius

Missing data codes: NA
Specialized formats or other abbreviations used:
Notes:

#########################################################################

DATA-SPECIFIC INFORMATION FOR:
Copy of reference lake subset for Shuter - Vital Alexie Yearly subset - climate Secchi.csv

Number of variables: 161
Number of cases/rows: 3
Variable list:

*Many of the below variables are not used in the analyses but were in the dataset provided.

* Group: Arctic (used to distinguish from Toolik lakes in plotting and analyses)

* Lake_ID: lake name (Alexie or Vital)

* LatitudeDD: latitude (decimal degrees)

* LongitudeDD: longitude (decimal degrees)

* Altitude_m: lake elevation (metres)

* Meandepth_m: lake mean depth (metres)

* Maxdepth_m: lake maximum depth (metres)

* Shoreline_km: lake shoreline length (kilometres)

* fish_diversity: measure of fish diversity (not used in analyses)

* Predicted_F: unknown, not used in analyses

* prov: Province/territory that the lake is in

* n_lake_trout: number of lake trout

* air_degree_days_above_zero: air tempearture (degrees Celsius) degree days above zero

* air_days_above_zero: number of days the air temperature is above zero

* air_daily_avg_temp: daily average air temperature (degrees Celsius)

* precipitation_mm: annual precipitation in millimetres

* community_distance_km: distance to nearest community (see Campana et al. 2020)

* water_temp: water temperature (degrees Celsius)

* elevation_weather_stations_m: nearest weather station elevation in metres

* air_daily_avg_temp_adjusted_for_elevation: daily average air temperature (degrees Celsius) adjusted for elevation

* rcp_45_2006_airtemp, rcp_45_2050, rcp_45_2100, rcp_85_2006, rcp_85_2050, rcp_85_2100: daily average air temperature (degrees Celsius) adjusted for elevation under projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2006, 2050 or 2100

* fetch_km: lake fetch (maximum length) in kilometres

* wat_temp_rcp_45_2006_adjusted_for_elevation, wat_temp_rcp_45_2050ele, wat_temp_rcp_45_2100ele, wat_temp_rcp_85_2006ele, wat_temp_rcp_85_2050ele, wat_temp_rcp_85_2100ele: lake water temperature (degrees Celsius) adjusted for elevation under projected future climate scenarios for Representative Concentration pathway 4.5 (45) or 8.5 (85) for 2006, 2050 or 2100

* Flag: flag for whether longitude or latitude is NA, indicated by a zero

* Dist_km: distance in kilometres of the lake to the grid centre

* Year: year of data, 2013 or 2012

* tmpJan (column 39) - tmpDD5 (column 55): air temperature metrics

* Jan-Dec: mean monthly air temperature (Jan = January, etc.; degrees Celsius)

* Ann: mean annual air temperature (degrees Celsius)

* Sum, Spr: mean summer (June, July, August), and Spring (March, April, May) air temperature (degrees Celsius)

* DD0: degree days that the temperature was above 0 degrees Celsius

* DD5: degree days that the temperature was above 5 degrees Celsius

* preJan (column 56) - preSpr (column 70): precipitation metrics

* Jan-Dec: total monthly precipitation (Jan = January, etc.; millimetres)

* Ann: total annual precipitation (millimetres)

* Sum, Spr: total summer (June, July, August), and Spring (March, April, May) precipitation (millimetres)

* cldJan (column 71) - cldSpr (column 85): cloud cover metrics

* Jan-Dec: mean monthly cloud cover (Jan = January, etc.; percent cloud cover)

* Ann: mean annual cloud cover (percent cloud cover)

* Sum, Spr: mean summer (June, July, August), and Spring (March, April, May) cloud cover (percent cloud cover)

* radJan (column 86) - radSON (column 102): solar radiation metrics

* Jan-Dec: mean monthly solar radiation (Jan = January, etc.; Watts per metre squared)

* Ann: mean annual solar radiation (Watts per metre squared)

* DJF, MAM, JJA, SON: mean summer (June, July, August - JJA), Spring (March, April, May - MAM), winter (December, January, February - DJF), and fall (September, October, November - SON) solar radiation (Watts per metre squared)

* cradJan (column 103) - cradSpr (column 117): cloud cover-corrected solar radiation metrics

* Jan-Dec: mean monthly cloud cover (Jan = January, etc.; Watts per metre squared)

* Ann: mean annual cloud cover (Watts per metre squared)

* Sum, Spr: mean summer (June, July, August), and Spring (March, April, May) cloud cover (Watts per metre squared)

* Leap: shows if the year is a leap year (2012 is, so it is "1", 2013 is not, so it is "0")

* tmpDJF, tmpMAM, tmpJJA, tmpSON: mean summer (June, July, August - JJA), Spring (March, April, May - MAM), winter (December, January, February - DJF), and fall (September, October, November - SON) air temperature (degrees Celsius)