DOI: 10.5061/dryad.cvdncjt8g
title: Major changes in fish thermal habitat diversity in Canada’s Arctic lakes due to climate change

description: 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.
description: <strong>Overview of the Methods Used in This
 Paper</strong>   The
 following is an overview of the methods that we used in this paper. Each
 paragraph has an accompanying sub-section within the Methods section that
 provides more details. To develop the approach used in this paper, we
 applied both empirical and semi-mechanistic methods to build the set of
 predictive models needed to fulfill our primary objective: (i) predicting
 the impacts of climate change on the seasonal progression of thermal
 structure in Canadian Arctic lakes: and (ii) assessing how those impacts
 would change the character and diversity of the fish communities resident
 in those lakes<sup>24,35</sup>. A summary of issues addressed,
 and methods used follows:  
 (i) <em>Ground-Truthing Lake Morphometry:</em> Lake
 shape is a primary determinant of lake thermal structure. We used the
 GIS-based estimates of Canadian Arctic lake morphometry as the basis for
 our study, hereafter the Arctic GIS lake
 database<sup>13</sup>. Our Arctic GIS lake database provides
 the basic information (lake area, mean depth, maximum depth) needed to
 characterize lake shape<sup>13</sup>. We confirmed the
 accuracy of those estimates by comparing them to an empirical database of
 167 Arctic lakes obtained from a variety of sources (see Ground-Truthing
 Lake Morphometry section below) with morphometrics directly measured from
 field surveys.    (ii)
 <em>Lake-Specific Predictions of Ice Cover Phenology and Maximum
 Surface Water Temperature:</em> These are two of the primary
 elements determining the seasonal pattern of a lake’s thermal structure.
 We mobilized published empirical models to predict the impacts of climate
 change on these characteristics of Arctic lakes.
   (iii) <em>Lake-Specific
 Predictions of Thermal Stratification Patterns:</em> Gorham and
 Boyce (1989) developed a semi-mechanistic model linking the character of
 summer thermal stratification in lakes to the following lake-specific
 characteristics: the density difference between surface and bottom waters
 in mid-summer, summer wind strength, and lake
 fetch<sup>25</sup>. Gillis et al. (2021) successfully used
 this model to predict the presence or absence of seasonal lake thermal
 stratification<sup>27</sup>. We mobilized various sets of
 empirical data to ground-truth this model for our set of Arctic lakes. We
 then used it, along with our other models, to forecast the impacts of
 climate change on: which lakes remain
 completely frozen through the winter period and hence cannot support a
 self-sustaining fish community; lakes with winter
 surface ice only. These have the potential to support self-sustaining fish
 communities and fall into two categories. These are lakes that:
 do not stratify during the summer
 open-water period and hence provide a single, thermally uniform habitat to
 support their resident fish communities; stratify
 into warm surface and cold bottom regions and hence provide a set of
 thermally diverse habitats to support their resident fish
 communities. (iv) <em>Regional
 Predictions of the Impact of Climate Change on Stratification Patterns in
 Canadian Arctic Lakes:</em> We accessed spatially explicit datasets
 for historical (1986–2005) climate and projected changes in climate for
 2050 and 2100 under RCP4.5 and RCP8.5 emission scenarios using historical
 and future climate data for each lake from the Government of Canada’s
 climate data extraction tool29 to generate historical and future climate
 conditions for each lake in our Arctic GIS data base. Using these climate
 conditions and lake-specific morphometric data as input to the models
 described above, we estimated historical and future seasonal patterns of
 thermal structuring for each lake. We then summarized these projected
 changes across all lakes in each of the eight terrestrial ecozones
 comprising the Canadian Arctic
 region<sup>30</sup>.  
 (v) <em>Regional Predictions of the Impact of Climate
 Change on Fish Habitat Diversity in Canadian Arctic
 Lakes:</em> North American limnetic fish species can be classified
 into three thermal guilds (cold, cool, warm) based on their thermal
 preferences. We used the historical and projected future patterns of
 thermal structuring for each lake in our Arctic data base to generate
 annual, lake-specific estimates of the supply (the volume-days:
 m<sup>3</sup> days) of habitat suitable for each thermal
 guild. We then summarized projected changes in suitable thermal habitat
 supply across all the lakes found in each of the eight Canadian Arctic
 terrestrial ecozones.  
 <strong>References (as numbered in the
 manuscript)</strong>  
 13. Campana, S. E. et al. Arctic freshwater fish productivity
 and colonization increase with climate warming. Nat. Clim. Chang. 10,
 428–433 (2020). 24. McMeans, B. C. et al. Winter in
 water: differential responses and the maintenance of biodiversity. Ecol.
 Lett. 23, 922–938 (2020). 25. 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). 27. 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. 29. Government of
 Canada. Climate data extraction tool. (2021). 30.
 Ricketts, T. A. et al. Terrestrial Ecoregions of North America - A
 conservation assessment. (Island Press Books, 1999).
 35. Van Zuiden, T. M., Chen, M. M., Stefanoff, S., Lopez, L.
 & Sharma, S. Projected impacts of climate change on three
 freshwater fishes and potential novel competitive interactions. Divers.
 Distrib. 22, 603–614 (2016).
description: Spreadsheet editor to view files (e.g., Microsoft Excel). R to
 execute code.
description: ## This README file was generated on 2024-02-09 by Daniel P. Gillis.
 GENERAL INFORMATION 1. Title of Dataset: Major changes in fish thermal
 habitat diversity in Canada’s Arctic lakes due to climate change 2. 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: 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 3.
 Geographical location: Canadian Arctic. Focus of analysis is on areas at
 least 60 degrees N latitude. 4. 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. 5. 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.
 ## SHARING/ACCESS
 INFORMATION 1. Licenses/restrictions placed on the data: CC0 1.0 Universal
 (CC0 1.0) Public Domain 2. 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. 1. Links to
 other publicly accessible locations of the data: None 2.
 Links/relationships to ancillary data sets: Yes, see ##DATA & FILE
 OVERVIEW 3. 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 1.
 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 1. Number of variables: 52 2. Number of cases/rows: 481784 3. 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) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: See Campana et al. (2020) (full citation below) for information on geospatial methods for estimating lake depths. \######################################################################### DATA-SPECIFIC INFORMATION FOR: lakeslatlong.csv 1. Number of variables: 10 2. Number of cases/rows: 481784 3. 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) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 54 2. Number of cases/rows: 481784 3. Variable list: *Same as rlakes3pt1km.csv (above) but with mean_mean_depth_m, longitude, and latitude (see lakeslatlong.csv above) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 8 2. Number of cases/rows: 229 3. 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 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 1. Number of variables: 7 2. Number of cases/rows: 229 3. 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 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 * 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). 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 17 2. Number of cases/rows: 167 3. 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: * 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 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) * 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). * 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). * 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 1. Number of variables: 9 2. Number of cases/rows: 481784 3. 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) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 1. Number of variables: 5 2. Number of cases/rows: 481784 3. Variable list: * id: lake ID * 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). * 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). * 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). 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 1. Number of variables: 89 2. Number of cases/rows: 481782 3. 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. * 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). * 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). * 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). * 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 1 (excluding dimension variables) 2. 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) 3. 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) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 25 2. Number of cases/rows: 481782 3. 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) * 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). * 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: DJF: December, January, February MAM: March, April, May JJA: June, July, August SON: September, October, November 6. 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 ``` 1. Number of variables: 1 (excluding dimension variables) 2. 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) 3. 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) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 25 2. Number of cases/rows: 481782 3. 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) * 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). * 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: DJF: December, January, February MAM: March, April, May JJA: June, July, August SON: September, October, November 6. 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 ``` 1. Number of variables: 1 (excluding dimension variables) 2. 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) 3. 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) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 25 2. Number of cases/rows: 481782 3. 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) * 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). * 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: DJF: December, January, February MAM: March, April, May JJA: June, July, August SON: September, October, November 6. 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 ``` 1. Number of variables: 2 (excluding dimension variables) 2. Number of cases/rows: lon (longitude) 720 * lat (latitude) 360 * time 120 = 31104000 elements 3. Variable list: * tmp[lon,lat,time]: near-surface temperatre (degrees Celsius) * stn[lon,lat,time]: number of stations contributing to each datum 4. Missing data codes: NA 5. 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 6. 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 ``` 1. Number of variables: 90 2. Number of cases/rows: 481782 3. 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) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: \######################################################################### DATA-SPECIFIC INFORMATION FOR: UniqueGridsrlakes3pt1km_latlong_zmean_pred_final.csv ``` *Output from script, not included in Dryad repository ``` 1. Number of variables: 6 2. Number of cases/rows: 4314 3. 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) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 2 (excluding dimension variables) 2. Number of cases/rows: lon (longitude) 720 * lat (latitude) 360 * time 120 = 31104000 elements 3. 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 4. Missing data codes: NA 5. 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 6. 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 ``` 1. Number of variables: 17 2. Number of cases/rows: 129420 3. 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) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: \######################################################################### DATA-SPECIFIC INFORMATION FOR: CRU_cld.csv ``` *Output from script, not included in Dryad repository ``` 1. Number of variables: 17 2. Number of cases/rows: 4314 3. 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 \######################################################################### DATA-SPECIFIC INFORMATION FOR: etopo1.nc ``` *External dataset, not included in Dryad repository ``` 1. Number of variables: 2 (excluding dimension variables) 2. Number of cases/rows: lon (longitude) 6901 * lat (latitude) 3301 = 22780201 elements 3. Variable list: * crs[]: CRS definition * Band1[lon,lat]: GDAL Band Number 1 (this is the elevation) 4. Missing data codes: -32767 5. Specialized formats or other abbreviations used: * GDAL (Geospatial Data Abstraction Library), a geospatial computer software library. 6. Notes: External dataset. Accessible online at (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 ``` 1. Number of variables: 10 2. Number of cases/rows: 4314 3. 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 \######################################################################### DATA-SPECIFIC INFORMATION FOR: CRU_crad.csv ``` *Output from script, not included in Dryad repository ``` 1. Number of variables: 17 2. Number of cases/rows: 4314 3. 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: \##9_Arctic_Proj_CRU_Add_Climate_Metrics_to_GridYears.R SCRIPT PURPOSE: Using Unique Grids by Year compute additional climate metrics \######################################################################### 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 ``` 1. Number of variables: 26 2. Number of cases/rows: 481782 3. 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) * 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). * 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 &lt;0 °C * J_Spr4: day of year following the last spring day when the 30-day running mean daily air temperature &lt;4 °C * J_Aut0: day of year following the last fall day when the 30-day running mean daily air temperature &gt;0 °C * J_Aut4: day of year following the last fall day when the 30-day running mean daily air temperature &gt;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 4. Missing data codes: NA 5. 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 6. 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 ``` 1. Number of variables: 76 2. Number of cases/rows: 481782 3. 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 * 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). * 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). * 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). * 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, &gt;= 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 &gt;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 &lt;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 &gt;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 &lt;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 *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) *cradJul: mean July solar radiation, corrected for cloud cover cloud cover (Watts per metres squared) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. 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 2. Number of cases/rows: 13248 3. 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 1 2. Number of cases/rows: 1 3. Variable list: * median_shape_1hr: median Weibull shape across all sites for mean 1-hour wind 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 76 2. Number of cases/rows: 9623 3. Variable list: * same as rlakes3pt1km_assembled.csv, see above under script ##10_Arctic_Proj_Dataset_Assembly.R 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 66 2. Number of cases/rows: 3 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. 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 152 2. Number of cases/rows: 3 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) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 202 2. Number of cases/rows: 481782 3. 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 * 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 202 2. 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 3. 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 203 2. Number of cases/rows: 481782 3. 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 29 2. Number of cases/rows: 452927 3. Variable list: * See HydroLAKES technical documentation for column name information: . 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). 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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). \##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 ``` 1. Number of variables: 3 2. 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) 3. 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 3 2. 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 3. Variable list: * 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 407 2. Number of cases/rows: 447077 3. 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) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: \######################################################################### DATA-SPECIFIC INFORMATION FOR: FEOW_ID_ArcticLakeid.csv 1. Number of variables: 3 2. Number of cases/rows: 447079 3. 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: 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 41 fields 2. Number of cases/rows: 1355 features 3. 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 for more details 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 ``` 1. Number of variables: 105 fields 2. Number of cases/rows: 4374 features 3. 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. 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. 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 1. Number of variables: 6 2. Number of cases/rows: Vital_Lake_Temperature_Data.csv - 610 Alexie_Lake_Temperature_Data.csv - 9039 3. 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 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: \######################################################################### DATA-SPECIFIC INFORMATION FOR: Copy of reference lake subset for Shuter - Vital Alexie Yearly subset - climate Secchi.csv 1. Number of variables: 161 2. Number of cases/rows: 3 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 * 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) * 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) * J_Spr0: day of year following the last spring day when the 30-day running mean daily air temperature &lt;0 °C * J_Spr4: day of year following the last spring day when the 30-day running mean daily air temperature &lt;4 °C * J_Aut0: day of year following the last fall day when the 30-day running mean daily air temperature &gt;0 °C * J_Aut4: day of year following the last fall day when the 30-day running mean daily air temperature &gt;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 * ESRLGridID: National Oceanic and Atmospheric Administration Earth System Research Laboratories (ESRL) grid cell ID. * wspdJan (column 141) - wspdDD5 (column 157): wind speed metrics * Jan-Dec: mean monthly wind speed (Jan = January, etc.; metres per second) * Ann: mean annual wind speed (metres per second) * Sum, Spr: mean summer (June, July, August), and Spring (March, April, May) wind speed (metres per second) * DD0: wind on days that the temperature was above 0 metres per second * DD5: wind on days that the temperature was above 5 metres per second * SWS: secondary watersed, from Canadian Lakes Assessment Model protocol * EstZMX: estimated maximum lake depth in metres, from Canadian Lakes Assessment Model * EstZMN: estimated mean lake depth in metres, from Canadian Lakes Assessment Model * EstSECCHI: estimated Secchi depth in metres, from Canadian Lakes Assessment Model 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: Derived from lakes (Vital and Alexie) featured in Campana et al. (2020): \######################################################################### DATA-SPECIFIC INFORMATION FOR: Arctic_LTER_Lake_Specific_Data_Lake_Morpho.csv ``` *External, not included in Dryad repository ``` 1. Number of variables: 32 2. Number of cases/rows: 45 3. Variable list: *Many of the below variables are not used in the analyses but were in the dataset provided. * Lake_ID: lake name (Alexie or Vital) * Group: Arctic_LTER (used to distinguish from Arctic GIS database ground truthing lakes in plotting and analyses) * Glat: latitude (decimal degrees) * Glon: longitude (decimal degrees) * surface_area: lake area (square metres) * zmax: lake maximum depth (metres) * zmean: lake mean depth (metres) * watershed_area: watershed area, NA * shoreline_length: lake shoreline length (metres) * volume: lake volume (cubic metres) * SDF: shoreline development factor (i.e., how close the lake is to a perfect circle) * elevation_source: lake elevation in metres, from the source data * surfaceArea (column 13) - meanDepthCor2.1 (column 28): lake morphometry metrics derived from lakemorpho R package, not used in present study so not detailed here (); Hollister J, Stachelek J (2017). “lakemorpho: Calculating lake morphometry metrics in R.” F1000Research, 6(1718). .; Hollister J, Stachelek J (2023). lakemorpho: Lake Morphometry Metrics. R package version 1.3.2, . * 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) * elevation: lake elevation from ETOPO1 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: External data External dataset. Comprised of data from a variety of sources that may not necessarily comply with CC0 licence requirements. See ## Sharing/Access information for more information \######################################################################### DATA-SPECIFIC INFORMATION FOR: Arctic_LTER_Lake_Temperature_Data.csv ``` *External, not included in Dryad repository ``` 1. Number of variables: 7 2. Number of cases/rows: 23077 3. Variable list: * group: Arctic_LTER (used to distinguish from Toolik lakes in plotting and analyses) * lake: lake name * year: year of lake temperature profile measurement * 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 * tmpFLAG: column to flag suspicous temperatures (all are zero, which is a sign that it is all good) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: External data External dataset. Comprised of data from a variety of sources that may not necessarily comply with CC0 licence requirements. See ## Sharing/Access information for more information \######################################################################### DATA-SPECIFIC INFORMATION FOR: Arctic_LTERUG20190426.cru_ts4.01.tmp.1971.2016.csv Arctic_LTERUG20190426.cru_ts4.01.pre.1971.2016.csv Arctic_LTERUG20190426.cru_ts4.01.crad.1971.2016.csv Arctic_LTERUG20190426.cru_ts4.01.cld.1971.2016.csv Arctic_LTERUG20190426.added_temp_metrics.1971.2016.csv Arctic_LTERUG20190524.wspd.10m.mon.mean.1971.2016.csv ``` *External, not included in Dryad repository ``` 1. Number of variables: Arctic_LTERUG20190426.cru_ts4.01.tmp.1971.2016.csv - 19 Arctic_LTERUG20190426.cru_ts4.01.pre.1971.2016.csv - 17 Arctic_LTERUG20190426.cru_ts4.01.crad.1971.2016.csv - 17 Arctic_LTERUG20190426.cru_ts4.01.cld.1971.2016.csv - 17 Arctic_LTERUG20190426.added_temp_metrics.1971.2016.csv - 24 Arctic_LTERUG20190524.wspd.10m.mon.mean.1971.2016.csv - 19 2. Number of cases/rows:\ Arctic_LTERUG20190426.cru_ts4.01.tmp.1971.2016.csv - 276 Arctic_LTERUG20190426.cru_ts4.01.pre.1971.2016.csv - 276 Arctic_LTERUG20190426.cru_ts4.01.crad.1971.2016.csv - 276 Arctic_LTERUG20190426.cru_ts4.01.cld.1971.2016.csv - 276 Arctic_LTERUG20190426.added_temp_metrics.1971.2016.csv - 276 Arctic_LTERUG20190524.wspd.10m.mon.mean.1971.2016.csv - 138 3. Variable list: Variables in the tmp, pre, crad, cld, and added_temp_metrics datasets: ``` * 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) * Year: year of climate data ``` Variables in the Arctic_LTERUG20190426.cru_ts4.01.tmp.1971.2016.csv dataset: ``` * tmpJan - tmpDD5: 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 ``` Variables in the Arctic_LTERUG20190426.cru_ts4.01.pre.1971.2016.csv dataset: ``` * preJan - preSpr: 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) ``` Variables in the Arctic_LTERUG20190426.cru_ts4.01.crad.1971.2016.csv dataset: ``` * cradJan - cradSpr: 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) ``` Variables in the Arctic_LTERUG20190426.cru_ts4.01.cld.1971.2016.csv dataset: ``` * cldJan - cldSpr: 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) ``` Variables in the Arctic_LTERUG20190426.added_temp_metrics.1971.2016.csv dataset: ``` - 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) * J_Spr0: day of year following the last spring day when the 30-day running mean daily air temperature &lt;0 °C * J_Spr4: day of year following the last spring day when the 30-day running mean daily air temperature &lt;4 °C * J_Aut0: day of year following the last fall day when the 30-day running mean daily air temperature &gt;0 °C * J_Aut4: day of year following the last fall day when the 30-day running mean daily air temperature &gt;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 ``` Variables in the Arctic_LTERUG20190524.wspd.10m.mon.mean.1971.2016.csv dataset: ``` * ESRLGridID: National Oceanic and Atmospheric Administration Earth System Research Laboratories (ESRL) grid cell ID. https://www.esrl.noaa.gov/ * Year: year of climate data * wspdJan - wspdDD5: wind speed metrics - Jan-Dec: mean monthly wind speed (Jan = January, etc.; metres per second) - speedAnn: mean annual wind speed (metres per second) - speedDJF, speedMAM, speedJJA, speedSON: mean winter (December, January, February - DJF), spring (March, April, May - MAM), summer (June, July, August), and fall (September, October, November) wind speed (metres per second) ``` 4\. Missing data codes: NA 1. Specialized formats or other abbreviations used: cru = Climatic Research Unit ts = time serious 4.01 = dataset version tmp = air temperature (degrees Celsius) pre = precipitation (millimeters) crad = cloud-corrected solar radiation (Watts per metre squared) added_temp_metrics = additional temperature metrics wspd = wind speed (metres per second) 2. Notes: External data External dataset. Comprised of data from a variety of sources that may not necessarily comply with CC0 licence requirements. See ## Sharing/Access information for more information \######################################################################### DATA-SPECIFIC INFORMATION FOR: Arctic_LTER_ESRLAllLakeGrids20190524.csv ``` *External, not included in Dryad repository ``` 1. Number of variables: 25 2. Number of cases/rows: 49 3. Variable list: * Group: Arctic_LTER (used to distinguish from Toolik lakes in plotting and analyses) * Lake_ID: lake name * LatitudeDD: latitude (decimal degrees) * LongitudeDD: longitude (decimal degrees) * zmax: lake maximum depth (metres) * zmean: lake mean depth (metres) * surface_area: lake surface area (metres squared) * volume: lake volume (cubic metres) * elevation: lake elevation (metres) * surfaceArea (column 10) - MinorMajorRation (column 22): lake morphometry metrics derived from lakemorpho R package, not used in present study so not detailed here (); Hollister J, Stachelek J (2017). “lakemorpho: Calculating lake morphometry metrics in R.” F1000Research, 6(1718). .; Hollister J, Stachelek J (2023). lakemorpho: Lake Morphometry Metrics. R package version 1.3.2, . * 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 * ESRL_GridID: the 2.5 degree latitude * longitude grid cell that the lake corresponds to closest (e.g., a lake with ESRL_GridID of ESRL_Grid_67.5*-150 is closest to the grid where the centroid is at 67.5 degrees N latitude, and -150 degrees W longitude) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: External data External dataset. Comprised of data from a variety of sources that may not necessarily comply with CC0 licence requirements. See ## Sharing/Access information for more information \######################################################################### DATA-SPECIFIC INFORMATION FOR: Arctic_LTER_Lake_Year_Data.csv ``` *External, not included in Dryad repository ``` 1. Number of variables: 10 2. Number of cases/rows: 504 3. Variable list: * group: Arctic_LTER (used to distinguish from Toolik lakes in plotting and analyses) * lake: lake name * year: year of the lake sampling event * zsecchi: Secchi depth of the lake in metres * DOC_mg_L: lake dissolved organic carbon (milligrams per litre) * TP_uM: lake total phosphorous (mmol/m^3) * TDP_uM: lake total dissolved phosphorous (mmol/m^3) * DOC_uM: lake dissolved organic carbon (mmol/m^3) * chla_V: chlorophyll-a (unknown unit), not used in analysis * chla_ugL: chlorophyll-a (micrograms per litre) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: External data External dataset. Comprised of data from a variety of sources that may not necessarily comply with CC0 licence requirements. See ## Sharing/Access information for more information \######################################################################### DATA-SPECIFIC INFORMATION FOR: CMIP5.SFCWIND.HISTO.SUMMER.ABS_PCTL50.csv ``` *External, not included in Dryad repository ``` 1. Number of variables: 15 2. Number of cases/rows: 106 3. Variable list: * time_1900/2005/P1Y: year * values: wind speed (metres per second) * longitude: longitude in decimal degrees * latitude: latitude in decimal degrees * scenario_en: climate scenario in English * scenario_fr: climate scenarion in French * time_res_en: time resolution English * time_res_fr: time resolution French * value_type_en: value type English (absolute wind value, as opposed to an anomoly value) * value_type_fn: value type French (absolute wind value, as opposed to an anomoly value) * percentile_en: climate ensemble percentile English - 50th percentile of cliamte ensemble * percentile_fr: climate ensemble percentile French - 50th percentile of cliamte ensemble * variable_en: variable English (Near surface wind speed) * variable_fr: variable French (Near surface wind speed) * uom: units of measurement (metres per second) 4. Missing data codes: NA 5. Specialized formats or other abbreviations used: 6. Notes: External dataset. Climate Data Extraction Tool from Government of Canada, wind data for Toolik lakes. Comprised of data from a source that may not necessarily comply with CC0 licence requirements. See ## Sharing/Access information for more information ## Rationale for the file structure \##Files The original Arctic lake morphometry dataset is included (rlakes3pt1km.csv). Scripts can be run to create intermediate analyses and generate intermediate datasets. Arctic lakes assigned to freshwater ecoregions are included (FEOW_ID_ArcticLakeid.csv), as are the empical ground-truthing morphometry lakes' assignments to ecozones (Ground_Truthed_Lake_Morphometry_Prelim_ECO.csv). Some key set-up files are included to aid with assembling the final dataset (lakeslatlong.csv, lakesmeandepth.csv, rlakes3pt1km_lat_long_zmean_ECO.csv). Some lake temperature data for ground truthing is included from Campana et al. (2020) (Alexie_Lake_Temperature_Data.csv, Vital_Lake_Temperature_Data.csv), as is lake morphometry data from Campana et al. (2020) (Copy of reference lake subset for Shuter - Vital Alexie Yearly subset - climate Secchi.csv) \##Script outputs included for convenience The finished product used for the main analyses is included (rlakes3pt1km_projections_thermal_hab.csv). The median Weibull shape parameter is included as well as it appears in multiple scripts (median_shape_1hr_df.csv). The spatial grid file for the supplementary maps 15-32 is included as it can take some time to create in script #20 (polys_sf_trans_cropped.gpkg). An intermediate Arctic lake morphometry dataset (rlakes3pt1km_assembled.csv) is included, as it is the product of the 10th script. If users wish to pick up at script 11, they may do so using this file. A subset of the main dataset (rlakes3pt1km_assembled_sample.csv) is included for convenience and for recreating certain analyses. ## Sharing/Access information Links to other publicly accessible locations of the data: * Arctic GIS lake database: * created by Gerald Black (retired) through Campana et al. 2020. To create the databse, the authors of that study (mainly Gerald Black) downloaded geospatial data from the Canadian Digital Surface Model and Canadian Digital Elevation Model (DEM) (, which included most elements of hydrographic morphometry in northern Canada, including the location of the water body, area, shoreline and surrounding topography. * Licence information of the Canadian Government source data: Contains information licensed under the Open Government Licence - Canada. * citation: Campana, S. E. et al. Arctic freshwater fish productivity and colonization increase with climate warming. Nat. Clim. Chang. 10, 428–433 (2020). * Directly implicated files: * rlakes3pt1km.csv and all files subsequent to this up to rlakes3pt1km_projections_thermal_hab.csv * Original Arctic Lake morphometry database: * link: * citation: Campana, S. E. et al. Arctic freshwater fish productivity and colonization increase with climate warming. Nat. Clim. Chang. 10, 428–433 (2020). * Ground-truthing lake surface water temperature data for Alexie and Vital lakes were also sourced through this study and are provided here as well * Ground-truthing morphometry data was sourced from this study and have been archived at Knowledge Network for Biocomplexity * Licence information: This work is dedicated to the public domain under the Creative Commons Universal 1.0 Public Domain Dedication. To view a copy of this dedication, visit . * Directly implicated files: * Ground_Truthed_Lake_Morphometry.csv * Ground_Truthed_Lake_Morphometry_Prelim_Eco.csv * Ground_Truthed_Lake_Morphometry_Eco_Cleaned.csv * Government of Canada climate data * link (extracted using this interface): * link (GeoTIFF files currently available here): * citation: Government of Canada. Climate data extraction tool. (2021). * Licence information of the Canadian Government source data: contains information licensed under the Open Government Licence - Canada. * Directly implicated files: * 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 * 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 * 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 * CMIP5.SFCWIND.HISTO.SUMMER.ABS_PCTL50.csv * ETOPO Global Relief Model * link: * citation: Amante, C. & Eakins, B. ETOP01 1 arc‐minute global relief model: procedures, data sources and analysis. NOAA Technical Memorandum NESDIS NGDC-24. (2009) doi:10.7289/V5C8276M. NOAA National Centers for Environmental Information. 2022: ETOPO 2022 15 Arc-Second Global Relief Model. NOAA National Centers for Environmental Information. DOI: 10.25921/fd45-gt74. Accessed [2018-12-11]. * Licence information: SPDX License: Creative Commons Zero v1.0 Universal (CC0-1.0) () * Directly implicated files: * etopo1.nc * Climatic Research Unit Data * link: * citation: Harris, I., Jones, P. D., Osborn, T. J. & Lister, D. H. Updated high-resolution grids of monthly climatic observations - the CRU TS3.10 Dataset. Int. J. Climatol. 34, 623–642 (2014). * Licence information: These datasets are made available under the Open Government Licence (). You are free to use this dataset but you must acknowledge the source of the information. Please use the attribution Climatic Research Unit (University of East Anglia) and NCAS. If it is appropriate to give citations and/or website links, then please also cite the relevant publication (see data table above) and/or provide a link to this website. * Directly implicated files: * cru_ts4.01.2001.2010.tmp.dat.nc * cru_ts4.01.1981.1990.cld.dat.nc * cru_ts4.01.1991.2000.cld.dat.nc * cru_ts4.01.2001.2010.cld.dat.nc * Wind Atlas Tool, Environment and Climate Change Canada * link: * Licence information: * Directly implicated files: * 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 * Natural Earth Lakes shapefile for maps (ne_10m_lakes.shp) * link: * Licence information: All versions of Natural Earth raster + vector map data found on this website are in the public domain () * Directly implicated files: ne_10m_lakes.shp * Gorham and Boyce (1989). 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). doi: 10.1016/S0380-1330(89)71479-9 * Licence information: Copyright © 2024 Elsevier B.V., its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. * Directly implicated files: * Gorham and Boyce 1989 Figure 1 5 groups.csv * Gorham and Boyce 1989 Figure 1 Lake Points.csv * HydroLAKES * Citation: 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). * link: * Licence information: The HydroLAKES database is licensed under a Creative Commons Attribution (CC-BY) 4.0 International License. * Directly implicated files: * HydroLAKES_ECO_Spreadsheet.csv * Freshwater Ecoregions of the World (FEOW) * Citation: 67. Abell, R. et al. Freshwater ecoregions of the world: A new map of biogeographic units for freshwater biodiversity conservation. Bioscience 58, 403–414 (2008). * link: * Licence information: Copyright 2008 by The Nature Conservancy and World Wildlife Fund, Inc. All Rights Reserved. Freshwater Ecoregions of the World (FEOW) has been jointly developed by the Conservation Science Program of World Wildlife Fund and by The Nature Conservancy. Some content on this site may be the property of independent authors and contributors, who may be identified in separate copyright notices associated with content provided by them. You may not copy, reproduce, modify, display, republish, upload, post, transmit, distribute, alter, prepare any derivative works of, or otherwise use any material from this web site, including without limitation text, code, software, photographs, and images, without the prior express written consent of The Nature Conservancy or World Wildlife Fund, except as described below. * Directly implicated files: * FEOW_ID_ArcticLakeid.csv * Toolik Field Station lakes, Arctic Long Term Ecological Research (LTER) * Link: , * Licence information: This work is licensed under the Creative Commons Attribution 4.0 International License (CC By - Attribution) * Directly implicated files: * Arctic_LTER_Lake_Specific_Data_Lake_Morpho.csv * Arctic_LTER_Lake_Temperature_Data.csv * Arctic_LTERUG20190426.cru_ts4.01.tmp.1971.2016.csv * Arctic_LTERUG20190426.cru_ts4.01.pre.1971.2016.csv * Arctic_LTERUG20190426.cru_ts4.01.crad.1971.2016.csv * Arctic_LTERUG20190426.cru_ts4.01.cld.1971.2016.csv * Arctic_LTERUG20190426.added_temp_metrics.1971.2016.csv * Arctic_LTERUG20190524.wspd.10m.mon.mean.1971.2016.csv * Arctic_LTER_Lake_Year_Data.csv * National Oceanic and Atmospheric Administration Earth System Research Laboratories (ESRL) grid cell ID. * Wind data for some ground truthing was sourced from this database. * Link: * Citation: Kalnay et al.,The NCEP/NCAR 40-year reanalysis project, Bull. Amer. Meteor. Soc., 77, 437-470, 1996 * Licence information: Usage Restrictions - None * Directly implicated files: * Arctic_LTER_ESRLAllLakeGrids20190524.csv ## Code/Software Scripts are separated into different sections based on their intended purpose. They are meant to be executed in sequence and are numbered accordingly. We conducted all data transformation and analyses in the R statistical environment (R version 4.2.0). \- software citation: R Core Team. R: A language and environment for statistical computing. (2022). Several R packages are necessary to run the scripts. R package versions for each script are reported below the section at the beginning of each script where the packages are loaded (under sessionInfo()).