David Olefeldt University of Alberta Associate Professor

South Academic Building 348D Department of Renewable Resources, University of Alberta Edmonton AB T6G 2G7 Canada

(780) 248 - 1814 olefeldt@ualberta.ca www.caws.ualberta.ca https://orcid.org/0000-0002-5976-1475 Mikael Hovemyr Stockholm University mikael.hovemyr@natgeo.su.se McKenzie Kuhn mckenzie@ualberta.ca https://orcid.org/0000-0003-3871-1548 David Bastviken Linköping University david.bastviken@liu.se https://orcid.org/0000-0003-0038-2152 Theodore Bohn WattIQ ted.j.bohn@gmail.com https://orcid.org/0000-0002-1880-9129 John Connolly Trinity College Dublin john.connolly@tcd.ie https://orcid.org/0000-0002-2897-9711 Patrick Crill Stockholm University patrick.crill@geo.su.se https://orcid.org/0000-0003-1110-3059 Eugénie Euskirchen University of Alaska Fairbanks seeuskirchen@alaska.edu Sarah Finkelstein University of Toronto sarah.finkelstein@utoronto.ca https://orcid.org/0000-0002-8239-399X Hélène Genet University of Alaska Fairbanks hgenet@alaska.edu https://orcid.org/0000-0003-4537-9563 Guido Grosse Alfred Wegener Institute guido.grosse@awi.de https://orcid.org/0000-0001-5895-2141 Lorna Harris University Of Alberta liharris@ualberta.ca https://orcid.org/0000-0002-2637-4030 Liam Heffernan Uppsala University liam.heffernan@ebc.uu.se https://orcid.org/0000-0003-0145-2167 Manuel Helbig Dalhousie University manuel.Helbig@dal.ca https://orcid.org/0000-0003-1996-8639 Gustaf Hugelius Stockholm University gustaf.hugelius@natgeo.su.se https://orcid.org/0000-0002-8096-1594 Ryan Hutchins University of Waterloo hutchins.ryan@gmail.com https://orcid.org/0000-0002-1696-4934 Sari Juutinen University of Helsinki sari.juutinen@helsinki.fi Mark Lara University of Illinois mjlara@illinois.edu https://orcid.org/0000-0002-4670-7031 Avni Malhotra Stanford University avnim@stanford.edu https://orcid.org/0000-0002-7850-6402 Kristen Manies U.S. Geological Survey kmanies@usgs.gov https://orcid.org/0000-0003-4941-9657 David McGuire University of Alaska Fairbanks admcguire@alaska.edu https://orcid.org/0000-0003-4646-0750 Susan Natali Woodwell Climate Research Center snatali@woodwellclimate.org https://orcid.org/0000-0002-3010-2994 Jonathan O'Donnell National Park Service jonathan_o'donnell@nps.gov Frans-Jan Parmentier University of Oslo f.j.parmentier@geo.uio.no https://orcid.org/0000-0003-2952-7706 Aleksi Räsänen University of Helsinki aleksi.rasanen@luke.fi https://orcid.org/0000-0002-3629-1837 Christina Schädel Northern Arizona University Christina.Schaedel@nau.edu https://orcid.org/0000-0003-2145-6210 Oliver Sonnentag Université de Montréal oliver.sonnentag@umontreal.ca Maria Strack University of Waterloo maria.strack@uwaterloo.ca https://orcid.org/0000-0002-8996-7271 Suzanne Tank University Of Alberta suzanne.tank@ualberta.ca https://orcid.org/0000-0002-5371-6577 Claire Treat Alfred Wegener Institute claire.treat@awi.de https://orcid.org/0000-0002-1225-8178 Ryth Varner University of New Hampshire ruth.varner@unh.edu https://orcid.org/0000-0002-3571-6629 Tarmo Virtanen University of Helsinki tarmo.virtanen@helsinki.fi Rebecca Warren Ducks Unlimited Canada r_warren@ducks.ca Jennifer Watts Woodwell Climate Research Center jwatts@woodwellclimate.org 2021 The Boreal and Arctic Wetland and Lake Dataset (BAWLD) provides estimates of fractional land cover of 19 land cover classes within 0.5° ×0.5° grid cells. The total area of the BAWLD domain is 25 500 000 kilometers squared (km2), i.e. 17% of the global land surface. The domain includes the boreal and tundra biomes, as well as areas of rocks and glaciers at greater than 50° North (N). The dataset is comprised of 23,469 0.5° ×0.5° grid cells. Each grid cell includes information on the fractional cover of five wetland classes, seven lake classes, three river classes, along with glacier, rockland, tundra, and boreal forest classes. Estimates of land cover fractional extents are based on an expert assessment, and a subsequent extrapolation to the full study region using random forest analysis. The dataset also includes an assessment of the uncertainty of the fractional cover estimates, represented by the 95% high and low estimates for fractional land cover. Each grid cell is further classified as one of fifteen “wetscapes”, which are defined by a characteristic land cover composition. Aquatic Ecosystems Lakes Wetlands Terrestrial Ecosystems Permafrost Land Use/Land Cover Classification NASA Global Change Master Directory (GCMD) This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. http://doi.org/doi:10.18739/A2C824F9X The land cover dataset covers the northern hemisphere boreal and tundra biomes, along with rock and ice at >50 deg N. -180 180 90 45 2021 David Olefeldt University of Alberta Associate Professor

South Academic Building 348D Department of Renewable Resources, University of Alberta Edmonton AB T6G 2G7 Canada

(780) 248 - 1814 olefeldt@ualberta.ca www.caws.ualberta.ca https://orcid.org/0000-0002-5976-1475 NSF Arctic Data Center support@arcticdata.io http://arcticdata.io Q77285095 The BAWLD domain includes all of the northern boreal and tundra ecoregions, and also areas of rock and ice at latitudes greater than 50°N (Olson et al., 2001). The BAWLD domain thus covers 25.5×10^6 km2, or 17% of the global land surface. A network of 0.5° grid cells, cropped along coasts and at the transition from boreal to temperate ecoregions, was created for the BAWLD domain. Grid cells in BAWLD were populated with data from 15 publicly available spatial datasets, yielding 53 variables with spatial information. Most datasets that were included have data at higher resolution than the 0.5° BAWLD grid cells, hence information was averaged for each grid cell. For datasets where the spatial resolution was coarser or where spatial data were not aligned with the 0.5° grid cells, data was first apportioned into BAWLD grid cells before area-weighted averages were calculated. Climate data from the WorldClim2 (WC2) dataset (Fick and Hijmans, 2017) were averaged for each grid cell, including “mean annual air temperature”, “mean annual precipitation”, and “climate moisture index”. Information on soils and permafrost conditions were summarized as fractional coverage within each grid cell, and included “permafrost extent” from the Permafrost Zonation and Terrain Ruggedness Index (PZI) dataset (Gruber, 2012), permafrost zonation, ground ice content, and overburden thickness from the Circum-Arctic Map of Permafrost and Ground-Ice (CAPG) dataset (Brown et al., 2002), “yedoma ground” from the Ice-Rich Yedoma Permafrost (IRYP) dataset (Strauss et al., 2017), and non-permafrost peat “histosol”, permafrost peat “histel”, and “aqueous” wetland soils from the Northern Circumpolar Soil Carbon Database (NCSCD; hereafter NCS) (Hugelius et al., 2013). Four independent datasets provided information on wetland coverage, although without further differentiation between distinct wetland classes; the “regularly flooded shrub and/or herbaceous cover“ area from the Global Land Cover Database 2000 (GLC2) (Bartholomé and Belward, 2005), the “wetlands” area in the GlobLand30 (GL30) dataset (Chen et al., 2015), and the ‘”inundation and presence of wetlands” area from the Global Wetlands (GWET) dataset (Matthews and Fung, 1987), and the Circumpolar Arctic Vegetation Map (CAVM) dataset (Walker et al., 2005). Two datasets provided information of the extent of forested regions; the GLC2 and the Terrestrial Ecoregions of the World (TEW) dataset (Olson et al., 2001), while three datasets provided information on the extents of tundra vegetation; the CAVM, the GL30, and the TEW. Three datasets provided information on extent of glaciers and permanent snow; the NCS, the GL30, and the TEW. The NCS dataset also provided information about the extents of “rocklands”, while the PZI dataset had extents of topographic ruggedness (“flat”, “undulating”, “hilly”, “mountainous”, and “rugged”). Information on river extents was found in two datasets; the “river area” in the BasinATLAS (BAS) dataset (Linke et al., 2019), and “rivers” in the Global Lakes and Wetland (GLW) dataset which includes 6th order rivers and greater (Lehner and Döll, 2004). Inundation dynamics was provided by two datasets, with “mean annual minimum” and “mean annual maximum” inundation in the Global Inundation Map (GIM) dataset (Fluet-Chouinard et al., 2015), and an analysis of temporal inundation from the Global Surface Water (GSW) dataset (Pekel et al., 2016) where we defined inundation of individual 30 m pixels as being inundated “rarely” (greater than 0 to 5% of all available landsat images), “occasionally” (5 to 50%), “regularly” (50 to 95%), or “permanently” (95 to 100%). Four datasets included information about static extents of open water, including “open water” in NCS, “water bodies” in GL30, “water bodies” in GLC2, and information about lakes in the Hydrolakes (HL) dataset (Messager et al., 2016), where we differentiated between the area of “large lakes” (lakes greater than 10 km2), and “midsize lakes” (lakes between 0.1 and 10 km2). The land cover classification in BAWLD was constructed with the goal to enable upscaling of CH4 fluxes for large spatial extents. As such, we aimed to include as few classes as possible to facilitate for large-scale mapping, while still including classes that allow for separation among ecosystems with distinct hydrology, ecology, biogeochemistry and thus net CH4 fluxes. The BAWLD land cover classification is hierarchical; with five wetland classes, seven lake classes, and three river classes, along with four other classes; glaciers, dry tundra, boreal forest, and rocklands. WETLAND CLASSES Wetlands are defined by having a water table near or above the land surface for sufficient time to cause the development of wetland soils (either mineral soils with redoximorphic features, or organic soils with greater than 40 cm peat), and the presence of plant species with adaptations to wet environments. Wetland classifications for boreal and arctic biomes can focus either on small-scale wetland classes that have distinct hydrological regimes, vegetation composition, and biogeochemistry, or on larger-scale wetland complexes that are comprised of distinct patterns of smaller wetland and open-water classes. While larger-scale wetland complexes are easier to identify through remote sensing techniques (e.g. patterned fens comprised of higher elevation ridges and inundated hollows), our classification focuses on wetland classes due to greater homogeneity of hydrological, ecological, and biogeochemical characteristics that regulate CH4 fluxes. Several boreal countries identify four main wetland classes, differentiated primarily based on hydrodynamic characterization; bogs, fens, marshes, and. The BAWLD classification follows this general framework, but further uses the presence or absence of permafrost as a primary characteristic for classification and excludes a distinct swamp class, yielding five classes; Bogs, Fens, Marshes, Permafrost Bogs, and Tundra Wetlands. The swamp class was omitted due to the wide range of moisture and nutrient conditions of swamps, as well as the limited number of studies of swamp CH4 fluxes. We instead included swamp ecosystems in expanded descriptions of Bogs, Fens, and Marshes. The presence or absence of near-surface permafrost was used as a primary characteristic to distinguish between Permafrost Bogs and Bogs, and to distinguish Tundra Wetlands from Marshes and Fens. The presence or absence of near-surface permafrost is considered key for controlling CH4 emissions given its influence on hydrology, and for the potential of permafrost thaw and thermokarst collapse to cause rapid non-linear shifts to CH4 emissions. Finally, while some classifications include shallow (e.g. 2 m depth), open-water ecosystems within the definition of wetlands, we have included all open-water ecosystems without emergent vegetation within the lake classes (see below) due to the strong influence of emergent vegetation in controlling CH4 emissions. Bogs are described as ombrotrophic peatland ecosystems, i.e. only dependent on precipitation, and snowmelt for water inputs. Peat thickness is at least 40 cm, with maximum thickness greater than 10 m. The peat profile is not affected by permafrost, although in some climatically colder settings there may be permafrost below the peat profile. Bogs are wet to saturated ecosystems, often with small-scale (less than 10 m) microtopographic variability, with stagnant water and a water table that rarely is above the surface or more than 50 cm below the surface. Bogs have low pH (less than 5), low concentrations of dissolved ions, and low nutrient availability resulting from a lack of hydrological connectivity to surrounding mineral soils. Vegetation is commonly dominated by Sphagnum mosses, lichens, and woody shrubs, and can be either treed or treeless. Our description of Bogs also includes what is commonly classified as treed swamps, which generally represent ecotonal transitions between peatlands and upland forests. Fens are described as minerotrophic peatland ecosystems, i.e. hydrologically connected to surrounding mineral soils through surface water or groundwater inputs. A Fen peat profile is at least 40 cm thick, although maximum thickness is generally less than for bogs. The peat profile is not affected by permafrost. Fens are wet to saturated ecosystems, with generally slow-moving water. Fens have widely ranging nutrient regimes and levels of dissolved ions depending on the degree and type of hydrological connectivity to their surroundings, ranging from poor fens to rich fens. Vegetation largely depends on wetness and nutrient availability, where more nutrient poor fens can have Sphagnum mosses, shrubs, and trees, while rich fens are dominated by brown mosses, graminoids (sedges, rushes), herbaceous plants, and sometimes coniferous or deciduous trees (e.g. willows, birch, larch). Our description of Fens also includes what is commonly classified as shrubby swamps, which often are associated with riparian ecotones and lake shorelines. Marshes are minerotrophic wetlands with dynamic hydrology, and often high nutrient availability. Vegetation is dominated by emergent macrophytes, including tall graminoids such as rushes, reeds, grasses and sedges – some of which can persist in settings with greater than 1.5 m of standing water. Marshes are saturated to inundated wetlands, often with highly fluctuating water levels as they generally are located along shorelines of lake or coasts, along streams and rivers, or on floodplains and deltas. It is common for marshes to exhibit both flooded and dry periods. Dry periods facilitate decomposition of organic matter, and can prevent the build-up of peat. As such Marshes generally have mineral soils, although some settings allow for the accumulation of highly humified organic layers – sometimes indicating ongoing succession towards a peatland ecosystem. Salinity can vary depending on water sources, with brackish to saline conditions in some areas of groundwater discharge, or in coastal settings. Permafrost Bogs are peatland ecosystems, although the peat thickness in cold climates is often relatively shallow. Permafrost Bogs have a seasonally thawed active layer that is 30 to 70 cm thick, with the remainder of the peat profile perennially frozen (i.e. permafrost). Excess ground-ice and ice expansion often elevate Permafrost Bogs up to a few meters above their surroundings, and as such they are ombrotrophic and generally the wetland class with the driest soils. Permafrost Bogs have moist to wet soil conditions, often with a water table that follows the base of the seasonally developing thawed soil layer. Ombrotrophic conditions cause nutrient-poor conditions, and the vegetation is dominated by lichens, Sphagnum mosses, woody shrubs, and sometimes stunted coniferous trees. Permafrost Bogs are often interspersed in a fine-scale mosaic (10 to 100 m) with other wetland classes, e.g. Bogs and Fens. Common Permafrost Bog landforms include palsas, peat plateaus, and the elevated portions of high- and low-center polygonal peatlands. Tundra Wetlands are treeless ecosystems with saturated to inundated conditions, most commonly with near surface permafrost. Tundra Wetlands can have either mineral soils or shallow organic soils, and generally receive surface or near-surface waters from its surroundings, as permafrost conditions preclude connectivity to deeper groundwater sources. Vegetation is dominated by short emergent vegetation, including sedges and grasses, with mosses and shrubs in slightly drier sites. Tundra Wetlands have lower maximum depth of standing water than Marshes, due to the shorter vegetation. Tundra Wetlands can be found in basin depressions, in low-center polygonal wetlands, and along rivers, deltas, lake shorelines, and on floodplains in regions of continuous permafrost. Despite the name, limited wetlands with these characteristics (hydrology, permafrost conditions, and vegetation) can also be found within the continuous permafrost zone in boreal and sub-arctic regions. LAKE CLASSES Lakes are in BAWLD considered to include all lentic open-water ecosystems, regardless of surface area and depth of standing water. It is common in ice-rich permafrost lowlands and peatlands for open-water bodies to have shallow depths, often less than two meters, even when surface areas are up to hundreds of km2 in size. While small, shallow open-water bodies often are included in definitions of wetlands, we include them here within the lake classes as controls on net CH4 emissions depend strongly on the presence or absence of emergent macrophytes. Further classification of lakes in BAWLD is based lake size and lake genesis, where lake genesis influences lake bathymetry and sediment characteristics. Previous global spatial inventories of lakes include detailed information on size and location of individual larger lakes, but do not include open-water ecosystems less than 0.1 km2 in size, and do not differentiate between lakes of different genesis (e.g. tectonic, glacial, organic, and yedoma lakes). Small water bodies are disproportionately abundant in some high latitude environments, have high emissions of CH4, and therefore require explicit classification apart from larger water-bodies. Furthermore, lake genesis and sediment type haven been shown to influence net CH4 flux from lakes. In BAWLD we thus differentiate between large (greater than 10 km2), midsize (0.1 to 10 km2) and small (less than 0.1 km2) lake classes, and further differentiate between three lake types for midsize and small lakes; peatland, yedoma, and glacial lakes. Small and Midsize Peatland Lakes are described as lakes with thick organic sediments that are mainly found adjacent to or surrounded by peatlands, or in lowland tundra regions with organic-rich soils. Small Peatland Lakes includes the numerous small pools often found in extensive peatlands and lowland tundra regions, e.g. including the open-water parts of string fens and polygonal peatlands. Peatland Lakes generally form as a result of interactions between local hydrology and the accumulation of peat which can create open water pools and lakes, but can also form in peatlands as a result of permafrost dynamics. As such, these lakes with thick organic sediments are often shallow and have a relatively low shoreline development index. Peatland lakes have dark waters with high concentrations of dissolved organic carbon. Small and Midsize Yedoma Lakes are exclusive to non-glaciated regions of eastern Siberia, Alaska, and the Yukon where yedoma deposits accumulated during the Pleistocene. Yedoma permafrost soils are ice-rich and contain fine-grained, organic-rich loess which was deposited by wind and accumulated upwards in parallel with permafrost aggradation, thus limiting decomposition and facilitating organic matter burial. Notable thermokarst features, including lakes, often develop when yedoma permafrost thaws, causing labile organic matter to become available for microbial mineralization. Small Yedoma lakes typically represent younger thermokarst features, whereas Midsized Yedoma Lakes represent later stages of thermokarst lake development. Small Yedoma Lakes are thus more likely to have actively thawing and expanding lake edges where CH4 emissions can be extremely high, largely driven by high ebullition emissions. Century-scale development of yedoma lakes can shift the main source of CH4 production from yedoma deposits to new organic-rich sediment that accumulate from allochtonous and autochthonous sources – resulting in such lakes here being considered as Peatland Lakes. Small and Midsize Glacial Lakes include all lakes with organic-poor sediments – predominately those formed through glacial or post-glacial processes, e.g. kettle lakes and bedrock depressions. However, due to similarities in CH4 emissions and controls thereof, we also include all other lakes with organic-poor sediments within these classes. Glacial Lakes typically have rocky bottoms or mineral sediments with limited organic content. Lakes in this class are abundant on the Canadian Shield and in Fennoscandia, but can be found throughout the boreal and tundra biomes. Many Glacial Lakes have high shoreline development index, with irregular, elongated shapes. Generally, Glacial Lakes are deeper than lakes in the other classes, when comparing lakes with similar lake area. Large Lakes are greater than 10 km2 in surface area. Most Large Lakes are glacial or structural/tectonic in origin. Lake genesis is not considered for further differentiation within this land cover class. RIVER CLASSES We include three river classes in BAWLD, Large Rivers, Small Organic-Rich Rivers, and Small Organic-Poor Rivers. Large Rivers are described as 6th Strahler order rivers or greater, and generally have river widths greater than ~75 m. Small Organic-Rich Rivers include all 1st to 5th order streams and rivers that drain peatlands or other wetland soils, thus being associated with high concentrations of dissolved organic carbon and high supersaturation of CH4. Conversely, Small Organic-Poor Rivers drain regions with less wetlands and organic-rich soils, and generally have lower concentrations of dissolved organic carbon and dissolved CH4. OTHER CLASSES Four additional classes are included in BAWLD; Glaciers, Rocklands, Dry Tundra, and Boreal Forests. Glaciers include both glaciers and other permanent snow and ice on land. Rocklands include areas with very poor soil formation and where vegetation is largely absent. Rocky outcrops in shield landscapes, slopes of mountains, and high Arctic barren landscapes are included in the class. The Rocklands class also includes artificial surfaces such as roads and towns. Glaciers and Rocklands are largely considered to be neutral with respect to CH4 emissions. The Dry Tundra class includes both lowland arctic tundra and alpine tundra; both treeless ecosystems dominated by graminoid or shrub vegetation. Dry Tundra ecosystems generally have near-surface permafrost, with seasonally thawed active layers between 20 and 150 cm depending on climate, soil texture, and landscape position. Near-surface permafrost in Dry Tundra prevents vertical drainage, but lateral drainage ensures predominately oxic soil conditions. A water table is either absent or close to the base of the seasonally thawing active layer. Dry Tundra is differentiated from Permafrost Bogs by having thinner organic soil (less than 40 cm), and from Tundra Wetlands by their drained soils (average water table position greater than 5 cm below soil surface).. Boreal Forests are treed ecosystems with non-wetland soils. Coniferous trees are dominant, but the class also includes deciduous trees in warmer climates and landscape positions. Boreal Forests may have permafrost or non-permafrost ground, where absence of permafrost often allow for better drainage. The Boreal Forest class also includes the few agricultural/pasture ecosystems within the boreal biome. Expert assessments can be used to inform various environmental assessments, and are particularly useful to assess levels of uncertainty and to provide data which cannot be obtained through other means. We solicited an expert assessment to aid in the modelling of fractional coverage of the 19 land cover classes within each BAWLD grid cell. Researchers associated with the Permafrost Carbon Network (www.permafrostcarbon.org) with expertise from wetland, lake, and/or river ecosystems within the BAWLD domain were invited to participate. We also included a few additional referrals to suitable experts outside the Permafrost Carbon Network. A total of 29 researchers completed the expert assessment, and are included as co-authors of the BAWLD dataset. Each expert was asked to identify a region within the BAWLD domain for which they considered themselves familiar with. Experts were then assigned 10 random cells from their region of familiarity and 10 cells distributed across the BAWLD domain that allowed for an overall balanced distribution of training cells. No cell was assessed more than once, and in total ~3% of the area of the BAWLD domain was included in the expert assessment. Each expert was asked to assess the percent coverage of each of the 19 land cover classes within their 20 training cells. To guide their assessment, each expert was provided step-by-step instructions, plus information on the definitions of each land cover class, and a KML file with the data extracted from available spatial datasets for each grid cell. Experts were asked to use their knowledge of typical wetland and lake classes within specific high-latitude regions, their ability to interpret satellite imagery as provided by Google Earth, and their judgement of the quality and relevance of available spatial datasets to make their assessments of fractional cover. Random forest regression models were created to predict the percent coverage of all 19 individual BAWLD land cover classes, along with three additional models for total wetland, lake, and river coverage. Each land cover class was at first modelled separately, which was followed by minor adjustments, described below, that ensured that the total land cover within each cell added up to 100%. All statistical analysis and modelling were done using R 4.0.2 (R Core Team, 2020), and the packages Boruta (v7.0.0; Miron et al., 2010), caret (v6.0-86; Kuhn, 2020), randomForest (v4.6-14; Liaw and Wiener, 2002), and factoextra (v1.0.7; Kassambara and Mundt, 2020). Prior to running the random forest analyses, we performed an automatic feature selection using a Boruta algorithm, (Miron et al., 2010). The Boruta algorithm completed 150 runs for each land cover class, after which subsets of the 53 possible data variables were deemed important and selected for inclusion in subsequent random forest models. The random forest models (Kuhn 2020, Liaw and Wiener, 2002) then used boot-strapped samples (i.e. the expert assessments of land cover fractional grid cell coverages) to grow 500 decision-trees (ntree), with a subset of randomized data variables as predictors at each tree node (mtry). We used a 10-fold cross-validation with five repetitions providing mtry as a tuneable parameter for model training. The random forest model output included the root mean squared error (RMSE), the percent of the expert assessment variability that was explained (%Var), and relative variable importance. Relative variable importance assigns a 100% importance to the variable with the most influence on the model, and then ranks all other variables relative to the influence of that variable. A bias correction (Song, 2015) was applied to the predicted data of land cover class coverages, as the models were found to overestimate low coverages and underestimate high coverages. After the bias correction, all bias-adjusted predictions less than 0% were set to 0%, while those greater than 100% were set to 100%. Next, we ensured that the combined coverage of all 19 land cover classes within each grid cell added up to 100% by applying a proportional adjustment. In order to estimate the 5th and 95th percentile confidence bounds of the land cover predictions, we repeated the random forest analysis, as outlined above, an additional 20 times for each class. Each new run completely excluded 20% of the expert assessments, and the data were reshuffled four times. Each grid cell thus had 21 predictions of coverage for each of the 19 land cover classes, and for the cumulative wetland, lake, and river coverages, and the variability of these predictions were used to define the 5th and 95th percentile confidence bounds. While each cell in BAWLD has a distinct land cover combination, we were also interested in identifying cells with similarities in their land cover compositions to distinguish between regions of the boreal and arctic domain that represent characteristic landscapes. We carried out a k-means clustering (Kassambara and Mundt, 2020) to group grid cells with similarities in their predicted land cover compositions. The k-means clustering was based on within-cluster sum of squares, and we evaluated resulting maps with between 10 and 20 distinct classes. Using 15 clusters was deemed to balance within-cluster sum of squares and interpretability of the resulting map. 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Linke, S., Lehner, B., Ouellet Dallaire, C., Ariwi, J., Grill, G., Anand, M., Beames, P., Burchard-Levine, V., Maxwell, S., Moidu, H., Tan, F., and Thieme, M.: Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution, 6, 283, https://doi.org/10.1038/s41597-019-0300-6, 2019. Lehner, B. and Döll, P.: Development and validation of a global database of lakes, reservoirs and wetlands, Journal of Hydrology, 296, 1–22, https://doi.org/10.1016/j.jhydrol.2004.03.028, 2004. Fluet-Chouinard, E., Lehner, B., Rebelo, L.-M., Papa, F., and Hamilton, S. K.: Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data, Remote Sensing of Environment, 158, 348–361, https://doi.org/10.1016/j.rse.2014.10.015, 2015. Pekel, J.-F., Cottam, A., Gorelick, N., and Belward, A. S.: High-resolution mapping of global surface water and its long-term changes, 540, 418–422, https://doi.org/10.1038/nature20584, 2016. Messager, M. L., Lehner, B., Grill, G., Nedeva, I., and Schmitt, O.: Estimating the volume and age of water stored in global lakes using a geo-statistical approach, 7, 13603, https://doi.org/10.1038/ncomms13603, 2016. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/, 2020 Miron B. Kursa, Witold R. Rudnicki. Feature Selection with the Boruta Package. Journal of Statistical Software, 36(11), 1-13. URL http://www.jstatsoft.org/v36/i11/, 2010 Kuhn, M. caret: Classification and Regression Training. R package version 6.0-86. https://CRAN.R-project.org/package=caret, 2020 Liaw, A., and Wiener, M. Classification and Regression by randomForest. R News 2(3), 18—22, 2002 Kassambara, A., and Mundt, F. factoextra: Extract and Visualize the Results of Multivariate Data Analyses. R package version 1.0.7. https://CRAN.R-project.org/package=factoextra, 2020. Song, J.: Bias corrections for Random Forest in regression using residual rotation, 2, 321–326, https://doi.org/10.1016/j.jkss.2015.01.003, 2015. Christina Schaedel coPrincipalInvestigator Edward A Schuur principalInvestigator National Science Foundation https://doi.org/10.13039/100000001 1931333 https://www.nsf.gov/awardsearch/showAward?AWD_ID=1931333 BAWLD_V1_kml.kml BAWLD v1 land cover kml file BAWLD_V1_kml.kml 113363113 a9987b11617fce895560fdd8829c8bed application/vnd.google-earth.kml+xml https://cn.dataone.org/cn/v2/resolve/urn:uuid:f6a3fed4-ff14-4529-848e-ad3669cf8b4b Cell_ID Unique cell ID. * Lat Latitude of centre point of grid cell (decimal degrees). In cases where grid cells have been intersected (coast or ecoregion), the center point still indicates the centre of the grid cell prior to intersection. degree real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002130 Long Latitude of centre point of grid cell (decimal degrees). In cases where grid cells have been intersected (coast or ecoregion), the center point still indicates the centre of the grid cell prior to intersection. degree real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002132 Area_Pct The percent of a grid cell that is included in the BAWLD database after intersection with coast and ecoregions (%). percent real Shp_Area Area of grid cell (after intersection, where applicable) (m2). percent real GLA Percent cover of glaciers and permanent snow within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002665 ROC Percent cover of rocklands within grid cell (%) percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002666 TUN Percent cover of dry tundra within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002667 BOR Percent cover of boreal forest within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002668 WET Percent cover of wetlands within grid cell (%). Wetlands include the five wetland sub-classes, permafrost bogs, wet tundra, marsh, bog, and fen. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002669 PEB Percent cover of permafrost bogs within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002670 WTU Percent cover of tundra wetland within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002671 MAR Percent cover of marsh within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002672 BOG Percent cover of bog within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002673 FEN Percent cover of fen within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002674 LAK Percent cover of lakes within grid cell (%). Lakes include the seven lake sub-classes; large lakes (greater than 10 km2), mid-size peatland, yedoma, and glacial lakes (between 10 and 0.1 km2), and small peatland, yedoma, and glacial lakes (less than 0.1 km2). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002675 MPL Percent cover of mid-sized peatland lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002676 MYL Percent cover of mid-sized yedoma lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002677 MGL Percent cover of mid-sized glacial lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002678 SPL Percent cover of small peatland lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002679 SYL Percent cover of small yedoma lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002680 SGL Percent cover of small glacial lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002681 RIV Percent cover of rivers within grid cell (%). Rivers include three river sub-classes: large rivers (6th order or greater), and small organic-rich and organic-poor rivers (less than 6th order). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002682 LAR Percent cover of large rivers within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002683 SRR Percent cover of small organic-rich rivers within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002684 SRP Percent cover of small organic-poor rivers within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002685 GLA_L Percent cover of glaciers and permanent snow within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002665 GLA_H Percent cover of glaciers and permanent snow within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002665 ROC_L Percent cover of rocklands within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002666 ROC_H Percent cover of rocklands within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002666 TUN_L Percent cover of dry tundra within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002667 TUN_H Percent cover of dry tundra within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002667 BOR_L Percent cover of boreal forest within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002668 BOR_H Percent cover of boreal forest within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002668 WET_L Percent cover of wetlands within grid cell (%). Low estimate of 95% confidence interval. Wetlands include the five wetland sub-classes, permafrost bogs, wet tundra, marsh, bog, and fen. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002669 WET_H Percent cover of wetlands within grid cell (%). High estimate of 95% confidence interval. Wetlands include the five wetland sub-classes, permafrost bogs, wet tundra, marsh, bog, and fen. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002669 PEB_L Percent cover of permafrost bogs within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002670 PEB_H Percent cover of permafrost bogs within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002670 WTU_L Percent cover of tundra wetland within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002671 WTU_H Percent cover of tundra wetland within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002671 MAR_L Percent cover of marsh within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002672 MAR_H Percent cover of marsh within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002672 BOG_L Percent cover of bog within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002673 BOG_H Percent cover of bog within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002673 FEN_L Percent cover of fen within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002674 FEN_H Percent cover of fen within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002674 LAK_L Percent cover of lakes within grid cell (%). Low estimate of 95% confidence interval. Lakes include the seven lake sub-classes; large lakes (greater than 10 km2), mid-size peatland, yedoma, and glacial lakes (between 10 and 0.1 km2), and small peatland, yedoma, and glacial lakes (less than 0.1 km2). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002675 LAK_H Percent cover of lakes within grid cell (%). High estimate of 95% confidence interval. Lakes include the seven lake sub-classes; large lakes (greater than 10 km2), mid-size peatland, yedoma, and glacial lakes (between 10 and 0.1 km2), and small peatland, yedoma, and glacial lakes (less than 0.1 km2). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002675 MPL_L Percent cover of mid-sized peatland lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002676 MPL_H Percent cover of mid-sized peatland lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002676 MYL_L Percent cover of mid-sized yedoma lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002677 MYL_H Percent cover of mid-sized yedoma lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002677 MGL_L Percent cover of mid-sized glacial lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002678 MGL_H Percent cover of mid-sized glacial lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002678 SPL_L Percent cover of small peatland lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002679 SPL_H Percent cover of small peatland lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002679 SYL_L Percent cover of small yedoma lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002680 SYL_H Percent cover of small yedoma lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002680 SGL_L Percent cover of small glacial lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002681 SGL_H Percent cover of small glacial lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002681 RIV_L Percent cover of rivers within grid cell (%). Low estimate of 95% confidence interval. Rivers include three river sub-classes: large rivers (6th order or greater), and small organic-rich and organic-poor rivers (less than 6th order). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002682 RIV_H Percent cover of rivers within grid cell (%). High estimate of 95% confidence interval. Rivers include three river sub-classes: large rivers (6th order or greater), and small organic-rich and organic-poor rivers (less than 6th order). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002682 LAR_L Percent cover of large rivers within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002683 LAR_H Percent cover of large rivers within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002683 SRR_L Percent cover of small organic-rich rivers within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002684 SRR_H Percent cover of small organic-rich rivers within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002684 SRP_L Percent cover of small organic-poor rivers within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002685 SRP_H Percent cover of small organic-poor rivers within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002685 WETSCAPE Classification of wetscape. 1 Permafrost Peatlands 2 Sparse Boreal Peatlands 3 Rivers 4 Glaciers 5 Upland Tundra 6 Common Boreal Peatlands 7 Large Lakes 8 Lake-rich wetlands 9 Dominant Boreal Peatlands 10 Wetland-rich Tundra 11 Alpine and Tundra Barrens 12 Wetland and Lake-rich Tundra 13 Lake-rich Shield 14 Upland Boreal 15 Wetland and Lake-rich Yedoma Tundra MultiPolygon North_Pole_Lambert_Azimuthal_Equal_Area BAWLD_V1___Shapefile.zip BAWLD v1 land cover shapefile+zip BAWLD_V1___Shapefile.zip 13590003 570709da76fecc0747169ddd6e7fb8d9 application/vnd.shp+zip https://cn.dataone.org/cn/v2/resolve/urn:uuid:f623f043-d755-4c3a-bf54-cb8d36b0bda3 Cell_ID Unique cell ID. * Lat Latitude of centre point of grid cell (decimal degrees). In cases where grid cells have been intersected (coast or ecoregion), the center point still indicates the centre of the grid cell prior to intersection. degree real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002130 Long Latitude of centre point of grid cell (decimal degrees). In cases where grid cells have been intersected (coast or ecoregion), the center point still indicates the centre of the grid cell prior to intersection. degree real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002132 Area_Pct The percent of a grid cell that is included in the BAWLD database after intersection with coast and ecoregions (%). percent real Shp_Area Area of grid cell (after intersection, where applicable) (m2). percent real GLA Percent cover of glaciers and permanent snow within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002665 ROC Percent cover of rocklands within grid cell (%) percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002666 TUN Percent cover of dry tundra within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002667 BOR Percent cover of boreal forest within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002668 WET Percent cover of wetlands within grid cell (%). Wetlands include the five wetland sub-classes, permafrost bogs, wet tundra, marsh, bog, and fen. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002669 PEB Percent cover of permafrost bogs within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002670 WTU Percent cover of tundra wetland within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002671 MAR Percent cover of marsh within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002672 BOG Percent cover of bog within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002673 FEN Percent cover of fen within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002674 LAK Percent cover of lakes within grid cell (%). Lakes include the seven lake sub-classes; large lakes (greater than 10 km2), mid-size peatland, yedoma, and glacial lakes (between 10 and 0.1 km2), and small peatland, yedoma, and glacial lakes (less than 0.1 km2). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002675 MPL Percent cover of mid-sized peatland lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002676 MYL Percent cover of mid-sized yedoma lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002677 MGL Percent cover of mid-sized glacial lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002678 SPL Percent cover of small peatland lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002679 SYL Percent cover of small yedoma lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002680 SGL Percent cover of small glacial lakes within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002681 RIV Percent cover of rivers within grid cell (%). Rivers include three river sub-classes: large rivers (6th order or greater), and small organic-rich and organic-poor rivers (less than 6th order). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002682 LAR Percent cover of large rivers within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002683 SRR Percent cover of small organic-rich rivers within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002684 SRP Percent cover of small organic-poor rivers within grid cell (%). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002685 GLA_L Percent cover of glaciers and permanent snow within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002665 GLA_H Percent cover of glaciers and permanent snow within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002665 ROC_L Percent cover of rocklands within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002666 ROC_H Percent cover of rocklands within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002666 TUN_L Percent cover of dry tundra within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002667 TUN_H Percent cover of dry tundra within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002667 BOR_L Percent cover of boreal forest within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002668 BOR_H Percent cover of boreal forest within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002668 WET_L Percent cover of wetlands within grid cell (%). Low estimate of 95% confidence interval. Wetlands include the five wetland sub-classes, permafrost bogs, wet tundra, marsh, bog, and fen. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002669 WET_H Percent cover of wetlands within grid cell (%). High estimate of 95% confidence interval. Wetlands include the five wetland sub-classes, permafrost bogs, wet tundra, marsh, bog, and fen. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002669 PEB_L Percent cover of permafrost bogs within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002670 PEB_H Percent cover of permafrost bogs within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002670 WTU_L Percent cover of tundra wetland within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002671 WTU_H Percent cover of tundra wetland within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002671 MAR_L Percent cover of marsh within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002672 MAR_H Percent cover of marsh within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002672 BOG_L Percent cover of bog within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002673 BOG_H Percent cover of bog within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002673 FEN_L Percent cover of fen within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002674 FEN_H Percent cover of fen within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002674 LAK_L Percent cover of lakes within grid cell (%). Low estimate of 95% confidence interval. Lakes include the seven lake sub-classes; large lakes (greater than 10 km2), mid-size peatland, yedoma, and glacial lakes (between 10 and 0.1 km2), and small peatland, yedoma, and glacial lakes (less than 0.1 km2). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002675 LAK_H Percent cover of lakes within grid cell (%). High estimate of 95% confidence interval. Lakes include the seven lake sub-classes; large lakes (greater than 10 km2), mid-size peatland, yedoma, and glacial lakes (between 10 and 0.1 km2), and small peatland, yedoma, and glacial lakes (less than 0.1 km2). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002675 MPL_L Percent cover of mid-sized peatland lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002676 MPL_H Percent cover of mid-sized peatland lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002676 MYL_L Percent cover of mid-sized yedoma lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002677 MYL_H Percent cover of mid-sized yedoma lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002677 MGL_L Percent cover of mid-sized glacial lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002678 MGL_H Percent cover of mid-sized glacial lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002678 SPL_L Percent cover of small peatland lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002679 SPL_H Percent cover of small peatland lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002679 SYL_L Percent cover of small yedoma lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002680 SYL_H Percent cover of small yedoma lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002680 SGL_L Percent cover of small glacial lakes within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002681 SGL_H Percent cover of small glacial lakes within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002681 RIV_L Percent cover of rivers within grid cell (%). Low estimate of 95% confidence interval. Rivers include three river sub-classes: large rivers (6th order or greater), and small organic-rich and organic-poor rivers (less than 6th order). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002682 RIV_H Percent cover of rivers within grid cell (%). High estimate of 95% confidence interval. Rivers include three river sub-classes: large rivers (6th order or greater), and small organic-rich and organic-poor rivers (less than 6th order). percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002682 LAR_L Percent cover of large rivers within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002683 LAR_H Percent cover of large rivers within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002683 SRR_L Percent cover of small organic-rich rivers within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002684 SRR_H Percent cover of small organic-rich rivers within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002684 SRP_L Percent cover of small organic-poor rivers within grid cell (%). Low estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002685 SRP_H Percent cover of small organic-poor rivers within grid cell (%). High estimate of 95% confidence interval. percent real https://bioportal.bioontology.org/ontologies/OBOE#containsMeasurementsOfType http://purl.dataone.org/odo/ECSO_00002685 WETSCAPE Classification of wetscape. 1 Permafrost Peatlands 2 Sparse Boreal Peatlands 3 Rivers 4 Glaciers 5 Upland Tundra 6 Common Boreal Peatlands 7 Large Lakes 8 Lake-rich wetlands 9 Dominant Boreal Peatlands 10 Wetland-rich Tundra 11 Alpine and Tundra Barrens 12 Wetland and Lake-rich Tundra 13 Lake-rich Shield 14 Upland Boreal 15 Wetland and Lake-rich Yedoma Tundra MultiPolygon North_Pole_Lambert_Azimuthal_Equal_Area BAWLD_V1_Data_Info.pdf Data information of the Boreal-Arctic Wetland and Lake Dataset (BAWLD) BAWLD_V1_Data_Info.pdf 367500 870353a792e742035cd1594b5586f775 application/pdf https://cn.dataone.org/cn/v2/resolve/urn:uuid:bc85ad97-f07a-4468-8256-333fda64e586 application/pdf