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Earth Syst. Sci. Data, 14, 4095–4110, 2022
https://doi.org/10.5194/essd-14-4095-2022
Data description paper
Data description paper | 07 Sep 2022
A high spatial resolution soil carbon and nitrogen dataset for the northern permafrost region based on circumpolar land cover upscaling
A high spatial resolution soil carbon and nitrogen dataset for the northern permafrost region based on circumpolar land cover upscaling A high spatial resolution soil carbon and nitrogen dataset for the northern permafrost region... Juri Palmtag et al.
Juri Palmtag1, Jaroslav Obu2, Peter Kuhry3,4, Andreas Richter5, Matthias B. Siewert6, Niels Weiss7, Sebastian Westermann2, and Gustaf Hugelius3,4 Juri Palmtag et al. Juri Palmtag1, Jaroslav Obu2, Peter Kuhry3,4, Andreas Richter5, Matthias B. Siewert6, Niels Weiss7, Sebastian Westermann2, and Gustaf Hugelius3,4
1Department of Human Geography, Stockholm University, Stockholm, Sweden
2Department of Geosciences, University of Oslo, Sem Sælands vei 1, 0316 Oslo, Norway
3Department of Physical Geography, Stockholm University, Stockholm, Sweden
4Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
5Centre for Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria
6Department of Ecology and Environmental Science, Umeå University, Umeå, 901 87, Sweden
7Northwest Territories Geological Survey, Government of the Northwest Territories, Yellowknife NT X1A 1K3, Canada
Correspondence: Juri Palmtag (juri.palmtag@humangeo.su.se)
Received: 05 Jan 2022 – Discussion started: 02 Feb 2022 – Revised: 09 Aug 2022 – Accepted: 23 Aug 2022 – Published: 07 Sep 2022
Soils in the northern high latitudes are a key component in the global carbon cycle; the northern permafrost region covers 22 % of the Northern Hemisphere land surface area and holds almost twice as much carbon as the atmosphere. Permafrost soil organic matter stocks represent an enormous long-term carbon sink which is in risk of switching to a net source in the future. Detailed knowledge about the quantity and the mechanisms controlling organic carbon storage is of utmost importance for our understanding of potential impacts of and feedbacks on climate change. Here we present a geospatial dataset of physical and chemical soil properties calculated from 651 soil pedons encompassing more than 6500 samples from 16 different study areas across the northern permafrost region. The aim of our dataset is to provide a basis to describe spatial patterns in soil properties, including quantifying carbon and nitrogen stocks. There is a particular need for spatially distributed datasets of soil properties, including vertical and horizontal distribution patterns, for modeling at local, regional, or global scales. This paper presents this dataset, describes in detail soil sampling; laboratory analysis, and derived soil geochemical parameters; calculations; and data clustering. Moreover, we use this dataset to estimate soil organic carbon and total nitrogen storage estimates in soils in the northern circumpolar permafrost region (17.9×106 km2) using the European Space Agency's (ESA's) Climate Change Initiative (CCI) global land cover dataset at 300 m pixel resolution. We estimate organic carbon and total nitrogen stocks on a circumpolar scale (excluding Tibet) for the 0–100 and 0–300 cm soil depth to be 380 and 813 Pg for carbon, and 21 and 55 Pg for nitrogen, respectively. Our organic carbon estimates agree with previous studies, with most recent estimates of 1000 Pg (−170 to +186 Pg) to 300 cm depth. Two separate datasets are freely available on the Bolin Centre Database repository (https://doi.org/10.17043/palmtag-2022-pedon-1, Palmtag et al., 2022a; and https://doi.org/10.17043/palmtag-2022-spatial-1, Palmtag et al., 2002b).
Palmtag, J., Obu, J., Kuhry, P., Richter, A., Siewert, M. B., Weiss, N., Westermann, S., and Hugelius, G.: A high spatial resolution soil carbon and nitrogen dataset for the northern permafrost region based on circumpolar land cover upscaling, Earth Syst. Sci. Data, 14, 4095–4110, https://doi.org/10.5194/essd-14-4095-2022, 2022.
Permafrost soils represent a large part of the terrestrial carbon reservoir and form a significant and climate-sensitive component of the global carbon cycle (Hugelius et al., 2014). High-latitude ecosystems are experiencing rapid climate change causing warming of the soil, thawing of permafrost, and fluvial and coastal erosion (Biskaborn et al., 2019; Fritz et al., 2017). Warming enhances the decomposition of organic matter (OM) by microorganisms, which produces carbon dioxide, methane, and nitrous oxide. The release of these greenhouse gases to the atmosphere would in turn generate further climate change, resulting in a positive feedback on global warming (Turetsky et al., 2019). To better predict the magnitude and effect of environmental changes in the permafrost region, improved data on the properties and quantities of carbon and nitrogen stored in these climate vulnerable soils are needed.
In many cases, a lack of observational data for parameterization or evaluation can limit model development or accurate model projections (Flato, 2011). Soil properties such as OM content, soil texture, and soil moisture or their derivatives are commonly used to parametrize, train, or validate models (e.g., Oleson et al., 2010). Yet, the representation of northern soil profiles in global datasets remains limited (Köchy et al., 2015; Batjes, 2016); the northern circumpolar permafrost region (20.6×106 km2) in which permafrost can occur accounts for 22 % of the Northern Hemisphere exposed land area (Obu et al., 2019).
Many previous studies have shown a robust relationship between land cover and soil organic carbon (SOC) distribution, making land cover datasets useful for upscaling estimates from soil profiles to full landscape coverage (e.g., Kuhry et al., 2002; Hugelius, 2012; Palmtag et al., 2015; Siewert et al., 2015; Wojcik et al., 2019). Here we describe the compilation of a harmonized soil dataset for permafrost-affected landscapes derived from 15 different high latitude sites and one high alpine study site in Canada, Greenland, Svalbard, Sweden, and Russia (Fig. 1; Table 1). In total, 651 soil pedons contain information from up to 6529 samples on carbon and nitrogen content, carbon to nitrogen (C/N) ratio, isotopic composition, texture (sand, silt + clay) and coarse fraction content, land cover type, wet and dry bulk density, calculated volumetric contents for ice/water, and volumetric content of organic soil material, mineral soil material, and air. Site data were upscaled to the northern circumpolar permafrost region using the European Space Agency (ESA) Climate Change Initiative (CCI) global land cover dataset at 300 m pixel resolution, which is the very first long-term global land cover time series product.
This study has two main aims. Firstly, the primary aim of this dataset is to provide a harmonized, high resolution, quality controlled, and contextualized soil pedon dataset with a focus on SOC, nitrogen, and other parameters essential to determine the role of northern permafrost region soils in the climate system. Particularly, the extensive metadata on soil properties included for many samples when available (texture, volumetric densities, active layer depth, ice content, isotopic composition, etc.) are of great importance, and can be used to identify and model the processes responsible for the current and future carbon balance. Secondly, we used this soil dataset and an existing spatial product for upscaling to provide a new and independent estimate of the SOC and total nitrogen (TN) storage estimates within the northern circumpolar permafrost region.
Figure 1Overview map with location of the 16 sampling sites (see Table 1). Blue shading indicates permafrost probability (dark hues showing higher permafrost occurrence probability), based on an equilibrium state model for the temperature at the top of the permafrost (TTOP) for the 2000–2016 period (Obu et al., 2019). North Pole Lambert azimuthal equal area projection (datum: WGS 84). Base map: made with Natural Earth.
2.1 Dataset structure
The dataset contains 6529 analyzed samples from 651 soil pedons in 16 different sampling locations across the northern permafrost region (Fig. 1; Table 1) (Palmtag et al., 2022a, b). Each sampled pedon was described and classified according to land cover type. Land cover is defined as the biophysical cover of the Earth's terrestrial surface such as different vegetation types, water, and bare ground.
Table 1Summary of all study sites.
Land cover products are commonly satellite derived and sometimes globally available. We opted for a two-tier approach, where more classes can be used in products with higher thematic or spatial resolution (Table 2). First, we differentiated land cover into five primary tier classes (Tier I) which represent the major land cover types: forest, tundra, wetland, barren, and Yedoma. Although Yedoma is a sedimentary deposit and not a typical land cover class, it was added due to its large areal extent, special soil organic matter (SOM), and ground ice properties, as well as soil characteristics (Strauss et al., 2017; Weiss et al., 2016). Subsequently, Tier I classes were subdivided into 10 Tier II subclasses (Table 2).
Table 2Hierarchical structure of the two-tier land cover class system applied to the pedons based on field observations.
Class definitions of soil pedons to land cover types
All sampling sites were classified with Tier I descriptions using field descriptions and, where possible, assigned a more detailed (Tier II) description. The forest class was used for sparse to dense forests, further separated into three different Tier II classes: deciduous broadleaf, evergreen needleleaf, and deciduous needleleaf forest. Tundra is separated in Tier II to shrub tundra (dominated by erect shrubs >50 cm height) and graminoid/forb tundra (with low growth heath vegetation or graminoid dominated). Wetland includes terrain that is saturated with water for sufficient time of the year to promote aquatic soil processes with low oxygen conditions and occurrence of vegetation fully adapted to these conditions, as well as all types of peatlands. Areas that met the National Wetlands Working Group (1997) definition of a wetland were classified as such. The permafrost status within the top 2 m of a site was used to distinguish in Tier II the permafrost wetlands and the non-permafrost wetlands. Although a substantial part of the northern circumpolar permafrost region is classified as water (0.98×106 km2) or permanent snow/ice (0.06×106 km2), no soil sample or pedon data from these classes are included in the database. The Tibetan permafrost region was also excluded from our estimates as none of the sampling sites originated from that area. The class barren includes land cover types, such as exposed bedrock, boulder fields, talus slopes, debris cones, and rock glaciers, where soil is either almost completely absent, or occurs only in minor patches (<10 % area) or in between boulders. The land cover class Yedoma is defined as areas in Siberia, Alaska, and Yukon underlain by late Pleistocene ice-rich syngenetic permafrost deposits. We used the spatial extent for the Yedoma domain from Strauss et al. (2017) which occupied an area of 570 000 km2 from the used ESA CCI land cover product. Tier II divides the Yedoma domain into Yedoma tundra and Yedoma forest.
2.2 Soil sampling
Field soil sampling took place in summer months (late June to early September) between 2006 and 2019, most frequently in August or September in order to capture the maximum seasonal thaw (active layer) depth at each site. Active layer thickness was measured at each location using a graduated steel probe or measuring tape in excavated soil pits. A stratified sampling scheme consisting of linear transects with predefined equidistant intervals of typically 100 to 200 m across all major landscape elements was used to retrieve soil pedons (n=582), with on average 37 sampling sites per study area. To ensure that this sampling scheme covered all representative landscape units and types, maps (including vegetation, surficial geology) and remote sensing products (including air photos, satellite imagery, and elevation models) were assessed prior to fieldwork. Detailed field reconnaissance involving visual observation of the manageable study area was conducted before establishing transects. Sampling sites were located and marked at the exact position based on distance to the first sampling point and compass bearing using a handheld GPS device. This ensured an unbiased location of individual sampling sites. When sufficient time was available in the field, additional sampling (n=69) using a random or stratified random distribution of sampling points was used. Following the field sampling protocol (Fig. S1 in the Supplement), a site description, soil, and, in several cases, phytomass sampling was conducted at each sampling point.
For each pedon, the organic layer and the active layer was sampled from an open soil pit excavated to the bottom of the active layer to the bedrock, or, when this was not possible, to a depth of at least 50 cm (Fig. 2). Deeper unfrozen soil layers were sampled using a steel pipe (see permafrost sampling below). The organic layer sample was cut out as a block using a pair of scissors or a knife (removing living vegetation), and the block volume was measured in the field. The active layer samples were collected using 100 cm3 soil sampling rings inserted horizontally into the soil profile. Sampling of the active layer was performed in fixed depth intervals (5–10 cm) or along soil horizon boundaries. For non-permafrost wetland sites, a Russian peat corer with a 50 cm long chamber was used. After extraction, the core was subdivided into smaller increments (generally 5 cm) which resulted typically in about 5–15 samples per sampling site depending on the reached depth.
The permafrost section of the soil profile and very deep unfrozen soil layers were sampled using a steel pipe that was hammered into the ground in short (5 to 10 cm) depth increments. The pipe was pulled out after each sampled increment using large pipe wrenches, and the sample was pushed out of the pipe using a steel rod. At several locations (n=18), permafrost samples were also collected from exposures along lake shores or river valleys where the steel pipe was hammered in horizontally. These steel pipes are industry standardized with an outer diameter of 42.2 mm (1.25 inches), affordable and widely available even in remote locations. At several locations (n=5), soil cores were collected using a handheld motorized rotational Earth auger (Stihl BT 121) with a 50 cm core barrel and 52 mm outside diameter. Samples were split lengthwise into two halves: one half was analyzed to determine sediment characteristics, volumetric ice content, and gravimetric water content. Disturbance material was removed from the core surface by repeated scraping with a razor blade. The other half of each core was kept as a frozen archive to be used in the event of laboratory error. Since the accurate determination of soil bulk density (BD) is crucial when calculating SOC, special attention was paid to accurate soil volume estimation during field sampling. The target depth for soil cores was 100 cm, or until bedrock or massive ground ice (e.g., ice wedges) was reached. Pedons were often extended beyond 100 cm depth (n=313), in particular to assess full peat depth and organic/mineral transition in organic soils.
Wet or frozen samples were described and placed in double bags to assure no soil water was lost in transport. For each sampled soil profile, pictures and notes were taken to describe land cover type, landform, elevation, slope and aspect, surface moisture, and surface features. Specific observations regarding the collected sample depths, such as excess ground ice (visual estimate, %), occurrence of large stones (visual estimate, %), color (general description or using a Munsell scale), and soil structure including signs of cryoturbation, roots, and rooting depth were noted. Samples with cryoturbated soil material were marked or rated on a scale from 1 to 3 according to the relative amount of cryoturbated soil material. Soil texture, which refers to particle size and relative content of mineral components (sand, silt + clay), is of importance as it affects the physical and chemical properties of a soil, including cryoturbation (Palmtag and Kuhry, 2018). Soil texture was estimated for most samples using manipulation tests and assessment by hand in the field under varying weather conditions. To avoid misinterpretation, we decided to combine silt and clay, and refer to them as one fine-grained soil texture class. In case of permafrost samples, subsamples were thawed, analyzed, and returned back to the sample bag. The land cover and vegetation community were described at all sites. For many sites, vegetation cover was described in terms of relative plant functional type coverage per square meter. Beyond assigning the profiles to land cover, vegetation data are not included in this database and not further discussed.
Figure 2A three-dimensional field sampling protocol with typical soil layers in permafrost ground (reprinted from Weiss, 2017, p. 12). The orange shapes represent the different sampling techniques for organic surface layer (block), active layer sample from an excavated pit (fixed volume cylinder), and permafrost sampling (steel pipe).
2.3 Laboratory analysis
In the laboratory, soil samples (n=5315) were weighed before and after oven-drying at 60–70 ∘C for at least 24 h (or until no further weight change was observed) to determine field-moist mass (mws) and the oven-dried mass (md), thus permitting the calculation of wet bulk density (BDw) and dry bulk density (BD, g cm−3) using the known sample volume. To ensure that there was no remaining water in the organic rich and/or fine grained samples (n=3684), subsamples of ∼10 g were dried again at 105 ∘C to verify the oven-dried weights. After drying, samples were homogenized and sieved to determine the concentration of coarse mineral fragments (CF, >2 mm, %). For a subset of samples, particle size analysis was performed using a Malvern Mastersizer 3000 laser particle size analyzer (Malvern Instruments Ltd, Malvern, UK), which can analyze particles in the range of 0.01–3500 µm in diameter. It measures the intensity of light scattered as a laser beam passes through a dispersed particulate sample. A detailed description of these samples is given in Palmtag et al. (2018). Out of 5331 samples where OC % data are available, subsamples from 4471 samples were heated to 550 ∘C for 5 h to obtain organic matter content through loss on ignition (LOI; Heiri et al., 2001), and about half of the samples (n=2960) were heated to 950 ∘C for 2 h to determine carbonate content (for details, see Palmtag et al., 2015, 2016). To determine the elemental content of carbon and nitrogen (TOC and TN) and their isotopic composition, 2674 samples were analyzed using an elemental analyzer (EA). If LOI950 following Heiri et al. (2001) indicated presence of inorganic carbon >1 %, samples were acid treated (Abisko, Sweden; Ny Ålesund, Norway; Aktru, Altai Mountains, Russia) with hydrochloric acid prior to determination of TOC. To estimate the organic carbon % (OC %) for samples where only LOI was available (44 %), a polynomial regression model (R2=95 %) was performed between LOI550 and OC % from EA on samples for which both analyses were available at study-area level.
2.4 SOC/TN stock calculations and upscaling
Dry and wet bulk density (g cm−3), sample volume (cm3), and % carbon was used to calculate the volumetric contents of water, organic soil material, mineral soil material, and air for each sample. The soil organic carbon content (kg C m−2) was calculated for each sample separately based on dry bulk density (BD, g cm−3), percentage organic C in the sample (OC %), sample thickness T (cm), and coarse fraction correction (CF) (Eq. 1). Equation (1) was also used to calculate the TN content, in which OC % was replaced with N %.
(1) SOC g C cm - 2 = BD ⋅ OC % ⋅ 1 - CF ⋅ T .
SOC content for each pedon was calculated by summing up individual samples on 1 cm resolution until the maximum sampling depth was reached. The pedons were assigned to a specific land cover class and the SOC content averaged for different depth intervals (0–30, 30–50, 50–100, 100–200, 200–300 cm, and summed to 0–100 and 0–300 cm). In areas with large stones in the soil column (e.g., alpine areas) or areas with massive ice bodies (e.g., Yedoma deposits), it is also important to deduct the volume of stones or massive ice from the calculations. These additional variables are not included in Eq. (1), but were accounted for in the SOC calculations at the pedon level. If bedrock was encountered at any point, a SOC content of 0 kg C m−2 was assigned for the remaining part down to 300 cm depth at that specific sampling site. In pedons where some increments were missing or the full sampling depth was not reached, the nearest samples from the same pedon for BD and OC % were interpolated or extrapolated. To avoid overestimation of the SOC storage, such extrapolations were only used where field notes showed that the deposits were homogeneous and bedrock was not reached.
Masses of soil components (water (mw, g), organic matter (mOM, g), and mineral component (mmin, g)) were calculated based on the laboratory analysis for all the individual samples. The mass of water was calculated as a difference between field-moist mass and oven-dried mass. Organic matter mass was calculated from the OC % and dry sample weight and multiplied by 2, which is a standard conversion factor between SOC and SOM (Pribyl, 2010). The mass of the mineral fraction was calculated as a difference between dry sample mass and organic matter mass.
Volumetric fractions of soil components were calculated by dividing the volume of the component with the total sample volume (V). We calculated component volumes from mass by assuming the following densities: 1 g cm−3 for water, 0.91 g cm−3 for ice, 1.3 g cm−3 for organic matter (Farouki, 1981), and 2.65 g cm−3 mineral component. The volumetric fraction of air was calculated as 1 minus the sum of the other fractions.
All profiles were assigned to land cover class based on field descriptions. Dry bulk density, SOC density, TN density, and the volumetric contents of mineral and organic matter and water and air were averaged according to land cover classes for depths until 3 m using Python scripting language and pandas library (McKinney, 2011). Soil parameters were assigned to pedon sample depth ranges and these were grouped according to land cover classes yielding means and standard deviations for each centimeter of depth. Fractions of soil texture classes (sand and silt + clay) were created using the same procedure by counting occurrences of texture classes within pedons. Typical soil stratigraphies were generated for each class which can be used as input for permafrost modeling and mapping (e.g., Westermann et al., 2013, 2017; Czekirda et al., 2019).
For the upscaling, we used the land cover map from the global ESA land cover Climate Change Initiative (CCI) (2017) project at 300 m spatial resolution (http://maps.elie.ucl.ac.be/CCI/viewer/index.php, last access: 2 September 2022). The overall classification accuracy, based on 3167 random sampling cases, is stated as 73 % (Defourny et al., 2008). The land cover class dataset for upscaling was generated from ESA CCI land cover yearly products from period 2006 to 2015 (corresponding to the sampling period) by identifying prevailing land cover classes within this period. The extent of the Yedoma land cover classes was defined from shapefiles of the Yedoma database by Strauss et al. (2017), where all the layers were used except for QG2500k, which shows the lowest probability of Yedoma occurrence.
Since the ESA land cover product uses a different nomenclature for land cover types with different sub-categories, similar classes were amalgamated to fit our tiered land cover system (Table 2). Several minor classes consisting of single pixels spread over the map were generalized and merged with the class surrounding the pixel. We defined Tier II Yedoma classes (Yedoma tundra and Yedoma forest) according to the ESA CCI land cover classes coinciding with Yedoma deposits (Table 3).
The spatial land cover extent was constrained to the Northern Hemisphere permafrost region indicating probability of permafrost occurrence but not the actual area underlain by permafrost (Obu, 2021). This dataset stretches over 17.9×106 km2 of the Northern Hemisphere, and is based on equilibrium-state model for the temperature at the top of the permafrost (TTOP) for the 2000–2016 period (Obu et al., 2019).
Table 3Amalgamation of ESA's CCI land cover classes with the Tier class system above the Yedoma deposits.
The upscaling to estimate the total carbon storage in the northern circumpolar permafrost region was performed in ArcGIS Pro (ESRI, Redlands, CA, USA) by multiplying the mean SOC storage for each Tier I and Tier II class with the spatial extent of the corresponding CCI land cover class. To determine reasonable error estimates for carbon stocks within the permafrost region, we used a spatially weighed 95 % confidence interval (CI) as described by Thompson (1993) assuming that our residuals are normally distributed (Hugelius, 2012).
(2) CI = t ⋅ ∑ a i 2 ⋅ SD i 2 / n i .
The CI accounts for the relative spatial extent, carbon stock variations in pedons, and number of replicates in each upscaling class. Replicates were only considered for pedons reaching the full sampling depth, resulting in fewer replicates available with increasing sampling depth. In Eq. (2): t is the upper α/2 of a normal distribution (t≈1.96), a the % of the area, SD is the standard deviation, n is the number of replicates, and i refers to the specific Tier class.
3.1 SOC estimates
Using our pedon-based dataset, we obtain SOC stock estimates within the northern circumpolar permafrost region of 379.7 and 812.6 Pg for 0–100 and 0–300 cm depth, respectively. Table 4 shows mean SOC storage (kg C m−2) and total SOC stock for all depth increments, including 95 % confidence intervals. The upscaling using these new pedon data shows that almost half of SOC in the northern circumpolar permafrost region is stored in the top meter. The three most abundant classes together (deciduous needleleaf forest, shrub tundra, and graminoid/forb tundra) occupy 67 % of the permafrost region (Table 5) and store most of terrestrial SOC in the northern circumpolar region (74 %). The permafrost wetland class has the largest SOC content to 300 cm with 112.2 kg C m−2, but has only a small areal coverage in the ESA LCC product (1.4 %) which results in a total SOC storage contribution of 3.5 % within the permafrost region. Figure 3 illustrates the spatial distribution of total SOC storage (kg C m−2) to a depth of 0–100 and 0–300 cm for the circumpolar permafrost region. Spatially, the SOC distribution in Fig. 3 follows the same pattern and highlights the largest SOC content predominantly in permafrost peatlands in Western Siberia, Russia, and the Nunavut territory in Canada. Despite that, more than 77 % of the area has a SOC storage to a depth of 300 cm higher than 50 kg m−2.
Table 4Landscape mean and total SOC storage with 95 % CI for the different depth increments for the northern circumpolar permafrost region, excluding water bodies and permanent snow and ice.
∗ The 95 % confidence interval refers to landscape mean SOC storage and total SOC storage.
Table 5Mean and total SOC storage for (a) 0–100 cm and (b) 0–300 cm soil depth separated for the different Tier classes in the northern circumpolar permafrost region, excluding water bodies and permanent snow and ice.
a The number of sampled pedons reaching a full depth of 100 or 300 cm, respectively. b Mean SOC storage and SD calculations include pedons which do not reach the full section depth.
Figure 3Estimated total SOC storage (kg C m−2) to a depth of 0–100 cm (a) and 0–300 cm (b) in northern circumpolar permafrost region. North Pole Lambert azimuthal equal area projection (datum: WGS 84). Base map: made with Natural Earth.
3.2 TN estimates
Our estimates show that the TN stocks down to 100 and 300 cm depth in the northern circumpolar permafrost region are 21.1 and 55.0 Pg, respectively. Table 6 presents the mean and total TN storage for different depth increments with their 95 % confidence interval. As with SOC storage, the most abundant land cover classes (deciduous needleleaf forest, shrub tundra, and graminoid/forb tundra) store most (68 %) of the total TN in the permafrost region. The land cover classes permafrost and non-permafrost wetlands have the largest TN storage with a mean of up to 7 kg N m−2 for the 0–300 cm soil depth (Table 7). Figure 4 illustrates the spatial distribution of total TN storage (kg N m−2) for the circumpolar permafrost region for two depth intervals, 0–100 and 0–300 cm. The spatial distribution of TN has a similar pattern to SOC and highlights the permafrost peatlands in Western Siberia, Russia, and the Nunavut territory in Canada.
Table 6Mean and total TN storage with 95 % CI for the different depth increments for the northern circumpolar permafrost region, excluding water bodies and permanent snow and ice.
∗ The 95 % confidence interval refers to landscape mean TN storage and total TN storage.
Table 7Mean and total TN storage for (a) 0–100 cm and (b) 0–300 cm soil depth separated for the different Tier classes within the northern circumpolar permafrost region, excluding water bodies and permanent snow and ice.
a The number of sampled pedons reaching a full depth of 100 or 300 cm, respectively. b Mean TN storage and SD calculations include pedons which do not reach the full section depth.
Figure 4Estimated total nitrogen storage (kg N m−2) to a depth of 0–100 and 0–300 cm in northern circumpolar permafrost region. North Pole Lambert azimuthal equal area projection (datum: WGS 84). Base map: made with Natural Earth.
3.3 C/N ratio and δ13C
Carbon to nitrogen ratios are often used as an indicator for SOM decomposition because the C/N ratio decreases with a higher degree of humification as more carbon than nitrogen is released during metabolic activity by microorganisms. This is why C/N ratios usually decrease with depth, as deeper layers are typically older and more decomposed (Kuhry and Vitt, 1996). Our data confirm this pattern of fast-decreasing C/N ratio with depth in all land cover classes to about 50 cm of depth followed by weak decline throughout the full pedon depth (Fig. 5a). The C/N values of SOC-rich top soil organic and peat samples are significantly higher than in the mineral samples (p<0.05). The C/N ratios together with stable carbon isotopes (δ13C) can be used to gain insight into the biochemical processes of SOM, botanical origin with depth, and the degradation state (Kracht and Gleixner, 2000). The lowest δ13C values, predominantly in the upper 50 cm, indicate that this SOM is more easily available for microbial utilization with lowest values in peatlands connected to differences in hydrology.
3.4 Soil stratigraphies
Figure 5 illustrates averaged vertical soil stratigraphies for SOC and TN density, C/N ratio with δ13C, dry bulk density, volumetric fractions for water/ice, organic, mineral, air, and texture (sand, silt + clay fraction) separated by land cover class to 300 cm depth. The data show clear differences occurring in the more variable top meter in comparison to the rather stable second and third meter, with the exception in non-permafrost wetlands where the TN and SOC density is more variable below 100 cm depth, which results from only two stratigraphically different available pedons where TN data are available (Table 7). The permafrost wetland class shows the highest and most consistent stratigraphy for SOC and TN density, which is due to the high organic fraction of these soils. In comparison, the barren has the lowest SOC and TN, as these soils are dominated by the coarse mineral fraction, and from ca. 140 cm depth, even our deepest barren sample reached bedrock. While the stratigraphy for the Yedoma classes proves that the Yedoma typical ice-rich silt sediments are noticeable in the high silt + clay and high water/ice fraction, with a strong dependence between the DBD stratigraphy and the mineral fraction stratigraphy.
Figure 5Typical vertical soil stratigraphies for all the land cover classes to 300 cm depth separated for SOC density, TN density, C/N ratio, and delta 13C/12C (a); DBD density, ice/water fraction, organic fraction, and mineral fraction (b); and clay + silt fraction, sand fraction, and air fraction (c).
The goal of the field studies in collecting this dataset has mainly been to improve the knowledge base for studies of climate feedbacks resulting from permafrost thaw. This new open-access database provides georeferenced and quality-assessed soil profile data to serve different scientific communities. While there are multiple databases available containing data on soil carbon storage (Hugelius et al., 2013; Michaelson et al., 2013; Mishra et al., 2021), there is still a lack of soil field data covering a wider range of properties within the hard-to-access northern circumpolar permafrost region.
To test and exemplify the usage of the soil profile database, we used our field-based metadata to classify soil profiles according to a coherent land cover scheme, and combined it with ESA's land cover product to provide a new estimate of soil organic carbon storage in the northern circumpolar permafrost region. Our estimate for SOC is 380±58 Pg to 100 cm soil depth, and 813±136 Pg to 300 cm soil depth for the permafrost region occupying an area of 17.9×106 km2 (excluding area of Tibetan permafrost region, permanent snow, and ice and water bodies). In comparison, Hugelius et al. (2014) estimated SOC stocks in the northern circumpolar permafrost region (17.8×106 km2 excluding exposed bedrock, glaciers and ice sheets, and water bodies) to be 472±27 and 1035±150 to 100 and 300 cm for soils, respectively. A recent publication by Mishra et al. (2021) based on >2700 soil profiles with environmental variables in a geostatistical mapping framework estimated a total SOC stock of 510 Pg (−78 to +79 Pg) and 1000 (−170 to +186 Pg) to 100 and 300 cm, respectively. Although our values are a bit lower than their estimates, they are within each other's ranges. Usage of a different land cover based upscaling approach could be the cause of some of these differences.
Despite the importance of nitrogen for microbial decomposition and plant productivity processes, few large-scale datasets are available on TN storage. Our TN estimate for the northern circumpolar permafrost region is 21±5 Pg to 100 cm soil depth and 55±15 Pg to 300 cm soil depth. This is in line with the only other circumpolar estimate of 66 Pg (±35 Pg) by Harden et al. (2012).
According to Kuhry and Vitt (1996), C/N ratios of peat deposits decrease over time due to cumulative anaerobic degradation, whereas aerobic decomposition and release of CO2 is lowering the C/N ratios in organic and mineral soil horizons (Ping et al., 1998). Our data show that the C/N ratios in organic soil horizons and peat layers were significantly higher than from mineral subsoil horizons. Based on this, we can use the C/N ratio data to assess the relative degree of SOM decomposition on circumpolar scale. However, C/N ratios and stable carbon isotopes are also affected by the original plant type and the climate which can in addition contribute to changes over time.
A key element to this upscaling exercise is the accuracy of the land cover dataset. Despite the relatively high spatial resolution of 300 m, many Arctic landscape features cannot be represented at this scale. However, ESA's land cover map has a good overall accuracy of 73 %, but this means that 27 % of the land cover is possibly mismatched and in need of improvement. Moreover, the accuracy for natural and semi-natural aquatic vegetation, which corresponds to our wetland class, is unfortunately as low as 19 %. According to Hugelius et al. (2020), the areal extent of peatlands for the northern permafrost region (3.7×106 km2) is almost four times the ESA's land cover product estimated areal extent (1.0×106 km2). Therefore, wrongly classified areas would partly explain our lower estimate for SOC and TN on a circumpolar scale since the wetland classes have the largest SOC and TN contents, particularly at greater depths (100–300 cm). This is evident on maps (Figs. 3 and 4) where areas classified as peatlands clearly stand out with their high SOC and TN contents. If we exchange the ESA wetland areal coverage for the values from Hugelius et al. (2020) to 3.7×106 km2 (2.0×106 km2 in permafrost-free peatlands and 1.7×106 km2 permafrost-affected peatlands) and deduct this in proportion from the other classes, our updated SOC and TN stock to 300 cm soil depth increases from 813±136 to 954±162 Pg and from 55±15 to 66±22 Pg, respectively.
Even though the current estimates are based on 651 soil pedons from 16 different study areas, there are uncertainties and data gaps for several regions and ecosystems. With e.g., only one high alpine site and one Yedoma forest site, several areas are highly underrepresented. Also, the study areas are concentrated in European and Russian locations which additionally increases the uncertainties in current estimates. Therefore, combining these data with other datasets especially from North America, Tibet, Yedoma sites, and a different wetland extent would substantially reduce potential error sources and create a more complete picture of SOC and TN storage estimates from land cover based upscaling. To our knowledge, this is the first product which presents a more complete dataset in regard to variables on a circumpolar scale that are commonly used to parameterize earth system models. With this database, we aim to provide georeferenced point data that can easily be implemented and used for geospatial analysis at a circumpolar scale. This upscaling approach was chosen because this database can be easily extended with additional sampling sites and higher resolution land cover maps that will further increase the resolution on a circumpolar scale. These data can also be used for upscaling in a particular area of interest. This will assist in quantifying and modeling ongoing pedological and ecological processes relevant to climate change. Furthermore, this may help identify regions that are more vulnerable to permafrost degradation and greenhouse gas release due to knowledge on texture, water/ice content, or SOC storage.
5 Data availability
Two separated datasets are freely available on the Bolin Centre dataset repository (https://bolin.su.se/data/, last access: 2 September 2022). The dataset (detailed pedon data on soil carbon and nitrogen for the northern permafrost region, https://doi.org/10.17043/palmtag-2022-pedon-1) (Palmtag et al., 2022a) is a geospatial dataset of physical and chemical soil properties from 651 soil pedons and the second dataset (a high spatial resolution soil carbon and nitrogen dataset for the northern permafrost region, https://doi.org/10.17043/palmtag-2022-spatial-1) (Palmtag et al., 2022b) contains GIS grids of the northern circumpolar permafrost region for SOC, TN, and C/N ratios for the different depth increments.
6 Conclusion
This dataset represents a substantial contribution of high-quality soil pedon data and metadata across the northern permafrost region. Our land cover based estimates of total SOC to 100 and 300 cm soil depth are 380±58 and 813±136 Pg, respectively. In addition, we contribute with novel TN estimates for the different land cover classes and depth increments. Our TN estimate to 100 and 300 cm soil depth are 21.1±4.7 and 55±15 Pg which is in line with the only other product available on that scale for TN. Despite a different methodology, they are similar but on the lower edge compared to other recent numbers. We provide data for a wide range of environments and geographical regions across the permafrost region, including georeferencing and metadata. This serves as a base that can be easily combined and extended with data from other sources, as several regions are underrepresented (Alaska, Canada, Tibet). This dataset offers high scientific value as it also contains data on chemical and physical soil properties across the northern circumpolar permafrost region. These additional data can be used to develop or parametrize broad-scale models and to help better understand different aspects of the permafrost–carbon climate feedback.
The supplement related to this article is available online at: https://doi.org/10.5194/essd-14-4095-2022-supplement.
GH, PK, SW, and JP designed the concept of the study. JO wrote the script in Python. JP wrote the initial draft of the article. All authors contributed to the writing and editing of the article.
The contact author has declared that none of the authors has any competing interests.
We thank the ESA CCI Land Cover project for providing the data, which was used for upscaling our product to circumpolar scale.
This research has been supported by the European Space Agency (grant no. 4000123681/18/I-NB), the Horizon 2020 (Nunataryuk (grant no. 773421)), the UK Research and Innovation (CACOON (grant no. NE/R012806/1)), and the Vetenskapsrådet (grant no. 2018-04516).
This paper was edited by Kirsten Elger and reviewed by Loeka Jongejans and Kristen Manies.
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The northern permafrost region covers 22 % of the Northern Hemisphere and holds almost twice as much carbon as the atmosphere. This paper presents data from 651 soil pedons encompassing more than 6500 samples from 16 different study areas across the northern permafrost region. We use this dataset together with ESA's global land cover dataset to estimate soil organic carbon and total nitrogen storage up to 300 cm soil depth, with estimated values of 813 Pg for carbon and 55 Pg for nitrogen.
The northern permafrost region covers 22 % of the Northern Hemisphere and holds almost twice as...
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Chloë Grace Moretz Became A 'Recluse' After Viral Body-Shaming 'Family Guy' Meme
Cole Delbyck
Few young actors have been as consistently booked and busy as Chloë Grace Moretz, who's appeared in more than 50 films since her breakout role in the "Kick Ass" franchise.
But growing up in the public eye came with a major cost for the 25-year-old star, who said that a "horrific" viral meme comparing an edited paparazzi shot to a "Family Guy" character drove her to become a "recluse."
"I've actually never really talked about this, but there was one meme that really affected me, of me walking into a hotel with a pizza box in my hand," Moretz shared in a recent Hunger magazine profile. "And this photo got manipulated into a character from 'Family Guy' with the long legs and the short torso, and it was one of the most widespread memes at the time."
Moretz, who's opened up about being body-shamed throughout her career, said her pain was entirely dismissed by someone who told her to "shut the fuck up" when the meme first surfaced.
Chloë Grace Moretz attends a Louis Vuitton fashion show in 2022. (Photo: Emma McIntyre via Getty Images)
"I just remember sitting there and thinking, my body is being used as a joke and it's something that I can't change about who I am, and it is being posted all over Instagram," she continued. "To this day, when I see that meme, it's something very hard for me to overcome."
The experience left her feeling "super self-conscious" and "kind of sad," especially when it came to going out for public appearances and red carpets.
While Moretz has continued to appear on-screen in recent years in a handful of projects, including "Neighbors 2: Sorority Rising," the 2018 "Suspiria" remake and the LGBTQ drama "The Miseducation of Cameron Post," she "basically became a recluse" in her own life.
"It was great because I got away from the photographers and I was able to be myself, and to have so many experiences that people didn't photograph, but at the same time it made me severely anxious when I was photographed," she told the outlet. "My heart rate would rise and I would hyperventilate."
With therapy and a much-needed career break, Moretz has begun to process her own "self-loathing" and the "jarring shift in my consciousness" about the attention her body has received.
Back in 2016, Moretz dropped out of all her future film roles, including a live-action reimagining of "The Little Mermaid," to "reassess who I am and find myself within my roles again," she said at the time.
But she's back on-screen in a major way with Amazon's upcoming sci-fi series "The Peripheral" from "Westworld" creators Jonathan Nolan and Lisa Joy.
"To say that these past two years have been transformative is an understatement, to say the least," Moretz said about her new perspective. "I'm a very different girl than I was. I feel like a woman now."
This article originally appeared on HuffPost and has been updated.
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redpajama_set_name: RedPajamaCommonCrawl


enet, Ireland's largest open-access network operator, has been named "Best Telecom Service Provider – Republic of Ireland" at the Telecoms Awards 2018, as awarded by TMT News. Now entering its third consecutive year, TMT's Telecoms Awards aims to bring awareness to the most progressive telecom companies in the industry.
This latest recognition is the culmination of a positive series of award successes for enet. Earlier this year, the company was named 2018 Wholesale Telecoms Infrastructure Company of the Year at the Fourth Annual All-Ireland Business Summit, an award that highlights and accredits Irish companies that have distinguished themselves in the conduct of their business. In 2017, enet also won the Technology Business of the Year award at the All-Ireland Business summit.


text:
Q: What object paints JTable grid lines I would like to override whatever method is responsible for rendering JTable grid lines.  I want to create a specific grid line that only prints a short vertical line at the outer edges of each cell.
I created a CellRenderer and a custom border to do this originally because I had thought that maybe the component rendered in a table had a default border and that's how they showed up, I see my custom rendered border but it's inside the cell so this obviously was not where the grid lines are painted.
Can anyone tell me which method is responsible for rending grid lines?

A: Due to kleopatra's comment I was able to arrive at the results I wanted.  I did this by creating a custom TableUI that extended BasicTableUI and I overrode Paint(Graphics g) which is responsible for painting table information.  Once a new TableUI was created I used JTable's setUI method to set the UI to my own custom implementation.

redpajama_set_name: RedPajamaStackExchange


Assuming I have established a viable case for the 3D virtual workplace in post 1 and 2, what about the actual planning, design and virtual architecture required to support it? What are the new characteristics of this environment that deserve consideration when developing a virtual workplace? There is a lot to cover here, but I'll do my best to include the main areas I think deserve the most attention.
First of all, the entire concept of user-generated content adds a unique twist to the virtual workplace. The ability for employees to build and customize their own spaces presents a whole new opportunity not possible (to this extent) in the physical workplace. The visual metaphors workers can evoke with 3D content can be quite illuminating. Erica Driver posted some excellent insight about this in a post back in February that I didn't see until just last night – well worth a read. Every individual and team can customize their spaces to reflect their interests and status. Ultimately, there is no limit to the amount of creativity people will exhibit when given the opportunity and the tools to create anything they can think of. What they choose to do with those tools can convey a lot about who they are, and what is important to them – valuable currency in any kind of team-based collaboration.
Synchronous presence is also an obvious benefit to working virtually, but what about asynchronous presence? In a previous virtual workplace project I worked on, we employed a kind of 'totem' system whereby each employee had their own totem to rez wherever they wanted to suggest their interest or presence. The idea was that, if each project in a company had several employees working on it, they could each rez a totem nearby, so anyone could assess at a glance who was involved with which project . In workplaces that are more self-organizing, this can be an informal yet highly effective way for employees to suggest their interest in joining a particular team or working on a specific project. Taking it a step further, the totem can be programmed to communicate with a back-end database storing additional information pertinent to that employee's status – such as on or offline, a list of projects they're currently working on, their daily schedule, and more.
Virtual interaction also brings a lot of new opportunity for improved methods of communication and collaboration that are native to virtual environments and not easily achieved in physical reality. Obviously a personal favorite of mine is Wikitecture, which I think could also be a very useful tool in virtual workplace development, but there are quite a few new tools being developed, such as MIT's virtual conference rooms that have the potential to make virtual meetings even more effective than real life ones. I think it will be interesting to see what Peter Quirk comes up with in this area as well. His most recent post (found here ) has some interesting thoughts on the topic, especially observing the immediate realities of Second Life interface, and what can be done to improve it for virtual work. The 3D cameras Mitch Kapor recently demonstrated will certainly improve the capacity to more naturally communicate in a virtual world. We have only scratched the surface of what a 3D interface can do to enhance collaboration, conferencing and communication.
In terms of actual deployment, it isn't enough to simply buy an island and let employees build whatever and wherever they please, imho. It might be a useful temporary exercise in helping employees experiment and explore, and perhaps strong communication between employees might result in a coherent and useful workplace infrastructure, but chances are, it will result in a hodge–podge of stuff without any coherent order (see our first experiments with Wikitecture illustrates the outcome). This might be OK if it is always the same group working together on the same projects consistently, but it can quickly become challenging or impossible for new employees to understand and navigate, and does nothing to communicate the company's core values, goals or vision. It becomes an exclusive function of individual expression, with no sense of direction.
On the other hand, a highly structured and polished workplace isn't necessarily the right approach either. Without some degree of flexibility or room for employee expression, the place will remain sterile and lifeless. It is best to find a balance between the two extremes. There are lots of ways to approach this, but one of my favorites is what I think of as 'bone and muscle' approach. With this concept, you establish a coherent structure or backbone that organizes teams, departments or shared group workspace elements of the workplace, then encourage the individuals and teams to customize their spaces with their own content and design. In this way, the organization is able to establish a common visual language and wayfinding strategy for the shared infrastructure, yet employees are able to enjoy the freedom and expression of their own interests and abilities. It is not unlike a city infrastructure – starting with roads, sidewalks, public plazas and land parcels (the backbone), with independent architectural creations (the muscle) completing the urban fabric. I employed that technique on this project, and used a similar strategy for Architecture Islands infrastucture, for the arcspace build and, to some extend on Clear Ink Island. In each case, I learned something different about the various ingredients that need to compliment the architecture in order for community and productivity to thrive so it doesn't whither on the vine, but that will be the topic of another post.
The jury is still out on this debate, but there is certainly a question of whether an organization should simply replicate its physical architecture exactly as it is in real life, and use it as their virtual workplace. My personal feeling is that fresh virtual context brings new opportunities and deserves fresh ways of rethinking the architecture. Having said that, I still think there is distinct value in replicating a building, but only if it is a signature piece that has some value or is easily recognizable and reinforces the organizations identity or history. In this way, the building serves as a kind of logo for the organization. However, I don't think it is appropriate to replicate the entire building exactly as it is built in real life, unless it is to be used as a tool for training and orientation. Not only will it feel strange to the avatar scale, but it will also feel too enclosed and uncomfortable. Perhaps the replicated architecture can serve as a kind of backbone structure upon and around which a more free-form level of customized environment can emerge. However, in the end, it is impractical to expect that a building will function the same way it does in real-life when replicated in Second Life.
In cases where no signature (or singular) building exists, perhaps the virtual architecture can achieve that identity in ways the real-life architecture could not accomplish. In a project I recently worked on, the company CEO suggested that one of the primary goals of the project was to give the employees the sense that they are still all working together under one roof. Early in the company's history, all of their employees worked together in the same space and shared a sense that they were all working together in the same space. As they grew, and opened other offices around the world, they lost the sense that they were all working together. In this case, the goal for the virtual workplace was to serve as a functional and visual metaphor that the employees could still, in a sense, come together and work in the same shared virtual space. In this way, the virtual architecture can serve as a powerful visual metaphor, helping to solve a core challenge the company is facing in a way that physical architecture could never achieve.
In physical reality, the expressiveness of architectural form is necessarily limited by forces such as resale value, and regional context, not to mention laws of gravity and protecting inhabitants from the elements. For the most part, a virtual workplace is free from such limiting factors, allowing for a far more referential expression of a company's organizational structure, core values and vision. Where virtual workplaces lack, they more than compensate for in opportunities and advantages not possible in real life.
For these reasons and more, the time is absolutely right for any company, large or small, to start exploring the potential of a 3D virtual workplace.
I won't even hazard a guess as to the combined total number of employees working for these companies, but I'm sure its astronomical. To be fair, what we might call 'presence' is, for the most part, a combined total of thousands of square miles of vacant ghost-sims left in the wake of last year's hasty marketing boom. But, just for the sake of argument, lets imagine that technology continues to advance exponentially, and that 5 years from now, virtual worlds will make telecommuting feasible for just 1 percent of the employees these companies represent who don't already telecommute. What kind of an impact would that transition have on the physical architecture that traditionally supports the workplace? What if it were 5 or 10 percent? What about 10 years from now? Lead-times on planning, designing and building physical architecture can easily exceed 5 years, so I don't think I'm being unreasonable to think that far ahead. Would we stand to gain anything from a workplace exodus on that scale?
Starting with remote worker isolation, it has long been known that one of the most common challenges for telecommuters, and their in-house peers is the perception of isolation. Often, remote employees can feel distant or left out of the daily pulse of the physical office. Opportunities for chance encounters and informal socialization are lacking, which can have a negative impact on the teleworker's ability to feel connected to the rest of the team. Virtual workplaces can readily enhance the sense of presence, and bring remote employees together. As collaborative technologies continue to emerge in virtual worlds, teams will be able to effectively work together in a shared space, even though they may be located in distant geographic locations. In my opinion, collaboration technologies in virtual worlds are still the weakest link in the movement toward the virtual workplace, but there are good reasons to believe that these challenges will be overcome in the months ahead. Until that time comes, the ability to do real work beyond immersive collaboration, communication and 3D simulation is just out of reach. I'm definitely not suggesting to wait on collaborative technology; that would be a mistake, imho – more on that later.
I don't think we can overestimate the expense of the physical architecture required to support a workplace environment. It is incredibly expensive to build and maintain, and very expensive to change. Virtual architecture costs are minuscule in comparison and far easier to change. It behaves more like a liquid than a static artifact, and has the advantage of being very flexible. It can shift-shape on the fly to reflect the specific needs of that moment. Furthermore, data can be integrated such that the entire workplace environment comes to life with active and dynamic data that is directly relevant to the work being done. Taking this a step further, the architecture of the workplace could even become reflexive or intelligent, insofar as it can recognize and respond to the number of people occupying a space, or even change scale to reflect traffic patterns and popularity of some spaces over others. This kind of flexibility and data integration into the architecture and virtual interface of the workplace itself might seem trivial at first, but I think a fully functioning environment imbued with relevant data and responsiveness could lead to a whole new workplace structure and methodology.
Furthermore, when you look closely at what people actually do when they work together in an office that seemingly necessitates physical presence, it becomes evident that there are several modes of collaboration that could just as easily be accommodated in virtual spaces. When people do sit down and work together in a physical space, what is it that they're doing that cannot possibly be accommodated in a virtual workplace? Viewing PowerPoint decks? Looking at a white-board? Conference calls? Virtual worlds already accommodate these activities quite well, and are getting better at it (so too thinks Forrester if you feel like splurging for the $279 report), so it won't be long before the majority of daily interaction can just as effectively transcend physical space for virtual space. In the near future, I believe we might finally be able to transcend PowerPoint with new modes of virtual presentation and relevant data integration within the virtual space – but we're not quite there yet.
Obviously, nothing can replace physical presence when it comes to high level business interaction, where the nuances of body language are vital, but seriously, what percentage of workers actually engage in this kind of top level strategic management meetings on a daily basis?
Another obvious scenario leading to the rise of the virtual workforce is the cost of commuting. Not only is it becoming more expensive, it is becoming increasingly crowded and less desirable. CEO's for Cities recently posted some thoughts on the Forbes article on the same topic. The time-starved lifestyles many of us lead invite any opportunity we can find to save precious time. Spending 30 minutes in the car driving to and from work is a major loss of valuable time. Spread out over the course of a week, a 30 minute commute (not uncommon by any means) could shave more than 6 weeks worth of workdays over the course of a year.
Think twice before criticizing virtual workers for spending time customizing an avatar if you spend 260 hours a year stuck in traffic, commuting to a redundant workplace.
It is also of vital importance to note that virtual workplaces are incredibly 'green' by nature (see 'Greening the Workforce'). The ecological footprint of a physical building, the energy it takes to create, condition and maintain it, along with employee commuting utilizes a massive amount energy. Of course, virtual world servers take a lot of energy too, but only a tiny fraction of what is required to maintain a physical building. I've even gone so far as to argue in previous posts that real life architectural projects should even be able to secure green accreditation by incorporating virtual spaces instead of physical spaces. What percentage of employees working in a typical metropolitan area actually depend on physical proximity to their colleagues every single day of the week anyway? Imagine the economic and environmental savings if even a fraction of those employees could conduct their work as efficiently in a virtual workplace.
Finally, the design and construction of real-life architecture is not only expensive, but very time consuming. It is not uncommon for the turnaround time on a project to be several years. Second Life, in its infancy, has already demonstrated its viability as a platform for collaboration now. Imagine what the technology will look like several years from now. The virtual workplace certainly won't be right for everyone, or every circumstance, but given the evidence and logic supporting its current and future value, I think it is naive to avoid some level of research and experimentation at this point. The pace of real-world architecture certainly doesn't advance exponentially the way technology does. Personally, I don't find it difficult to imagine newly minted office buildings sitting vacant long after the intended function transcends the building's usefulness. The 2D web changed things quickly, but virtual worlds will be quicker.
Next up: Characteristics and opportunities of virtual environments worth considering when developing a virtual workplace.
Given the rapid growth of virtual worlds, it has quickly become a feasible and popular destination for a vast range of functions, from conducting business, teaching classes, networking, sales, holding conferences to a multitude of other purposes.
In some cases, virtual interaction compliments real life functions. In other cases, virtual counterparts are completely replacing certain kinds of real life interactions. In either case, the phenomenon of physical transcendence into a lower cost virtual medium has already started, and will inevitably and significantly change the way we think about physical architecture in the very near future.
This course will hypothetically consider a large world-class accounting firm that has hired an architecture firm to design a new headquarters. Like any company with employees stationed worldwide, they depend on local commuting, long distance travel and hotelling to accommodate a global work force.
As architectural plans for the headquarters are evolving, a group within the company starts holding their weekly meetings in Second Life as an alternative to long distance travel and commuting. Within a few weeks, they are able to save time and money using this virtual alternative and the concept starts to catch on in other departments throughout the company. As this alternative becomes increasingly pervasive within the company, they realize it could be a significant cost savings to reduce the square footage of the new headquarters in favor of a virtual counterpart.
The architects are informed that the building's square footage can be decreased by 5%.
Who should be responsible for designing the virtual architecture?
Should it interface and share common characteristics with the architecture of the new physical headquarters?
Will such fundamental principles of wayfinding, scale, proportion, and hierarchy be important in the virtual counterpart?
Does an architectural background lend itself to designing this kind of virtual interface, or is the design of this environment a better fit for game designers, 3D modelers and computer programmers?
If construction and annual use of a certain percentage of physical architecture can be transcended into a virtual mode, could it be considered a sustainable or 'green' measure?
This studio asks students to consider and propose a design solution for the virtual workplace described in the previous 'Augmentation of Architecture' course description.
How can the architecture of this virtual space facilitate this new virtual workforce? What kinds of spaces will encourage efficient interaction and communication? How can the architectural concept of the real life building be translated into this virtual interface?
Note: Because Second Life provides an environment where anything is possible, designing virtual spaces encourages (possibly even requires) a return to the basic fundamentals of architecture. When designing in a virtual medium, designs that do not have a strong sense of hierarchy, scale and proportion are unsuccessful and difficult to navigate. Moreover, when the design solution is complete, members of the public can be invited in to tour the design solution and critique the design. By enabling the design to be actually populated by avatars, the success or failure of design gestures becomes immediately apparent.
This course will utilize an in-world 'jury' of selected users who will be asked to inhabit and critique the designs at various intervals throughout the semester from practical, functional and aesthetic perspectives.
When designing in a virtual medium, concepts lacking a strong sense of hierarchy, scale and proportion are unsuccessful and difficult to navigate.
This course asks students to design an art gallery for use in an exclusively virtual environment. The aim of the studio will be to encourage and reinforce a 'back to basics' mentality of design that requires solutions to be both clearly navigable and functional.
The final presentation will consist of a grand opening of the galleries for public viewing. Members of the in-world community will be able to inhabit and critique the final projects.
Tomorrow, Ryan Schultz and I are heading to Milwaukee to demonstrate Second Life to the American Institute of Architecture Students FORUM convention.
For my part, I put together a survey of everything I could think of related to architecture in SL, and Ryan put together a more philosophical perspective of how we think virtual worlds and web 2.0 will be affecting these students, as the next generation of architecture professionals. We will conclude with a live demonstration of the Wikitecture project, and show our progress to-date.
Beyond our demo, we have the unfortunate reality of reporting to them that New Zealand's equivalent of their AIAS convention already kicked their butts earlier this year by purchasing an island, hosting an architecture competition, and streaming their entire conference live into Second Life for everyone to enjoy.
The only comfort we can provide is that Ryan and I (former members of AIAS) took both first and second place in their competition! lol. One way or another, 2008 will be catch-up time for AIAS in Second Life, and we hope to kick-start that process tomorrow!
We will be giving a similar presentation at Metaverse U at Stanford University in February.
Phew… Finally, the Official Kick-Off Meeting for Wikitecture 3.0!
Can mass collaboration and collective intelligence improve the quality of architecture and urban planning?
We are happy to announce that, Studio Wikitecture will continue to try to tease out this question, via it's 3rd Wikitecture experiment kicking off officially on Nov. 7th. To accommodate those in different time zones, there will be two different times: Wednesday, Nov. 7th @ 9:00am and 6:30pm PST/SLT.
The project on which this experiment will center around will be the competition recently announced by the Open Architecture Network. Competition sites range from a medical facility in rural Nepal, a media lab and library in the slums of Nairobi, or a fair trade chocolate factory in Ecuadorian Amazon.
Since the OAN is an "open-source community dedicated to improving living conditions through innovative and sustainable design", we thought it would be a perfect opportunity to submit an entry for this competition that is, in turn, designed and composed in the same collaborative and open-source fashion.
We would be happy for you to join the next experiment and help us design this collaborative competition entry. You don't need any experience in architecture, engineering or construction to participate. We actually believe the more diverse the pool of contributors, the better. You will need, if you don't already, a Second Life account. Registering is easy.
Once you have downloaded the Second Life application, registered an account and log in, press the 'search' key on the bottom of your screen. Look for the group 'Studio Wikitecture' and click 'join.' Enrollment is open to all.
For the login: use your full 'Second Life' name.
If you have an problems, don't hesitate to IM either Keystone Bouchard or Theory Shaw in-world and we'll come by and help you.
We are not only excited about the project, but the new website and in-world interface (not operational, until nov. 7th) that will allow everyone to better communicate and collaborate with each other over the duration of the project's two month time frame. Allow with the following description, this video, provides a nice overview of the technology behind Wikitecture 3.0 as well.
Over the last year, we have been using the virtual world of Second Life as a platform for conducting 'Wikitecture' experiments to work out the procedures and protocols necessary to harness a group's collective intelligence in designing architecture. We have already conducted 2 experiments within Second Life to explore this idea of 'open source architecture'. The videos of their final form can be found here: 1.0 & 2.0. The following gives a brief overview of the evolving functionality behind Wikitecture 1.0, 2.0, & 3.0.
Wikitecture 1.0 was not really a true Wiki in the sense that contributors could not modify or delete the contributions of others. What resulted, although interesting in its own right, was an amalgamation of 'stuff' with not no overall coherency or unity – a result we expected.
In the 2nd experiment, we asked contributing members to enable full-permissions on every object they added. This new protocol enabled designers to add/modify/delete each other's designs. In addition, we set up a Flickr Account that allowed contributors to upload descriptive snapshots of their designs and leave feedback as well. With Wikitecture 2.0, we also introduced an archiving system, where members, through community consensus, were able to roll-back the 'live' design to previously saved iterations. Although this system was still rudimentary, the resultant design was far more unified and coherent than Wikitecture 1.0.
For our 3rd experiment, however, we have continued to try and improve upon this underlying technology. In teaming up with i3D inc., experts in creating virtual applications that cross the 2D/3D divide, we have developed both an in-world interface ('wiki-tree') and external website that continually communicate with each other. From the in-world perspective, contributors are able to archive their particular design into an abstract 'leaf' within a 3-dimensional 'tree canopy'. As this canopy grows, the branching network of 'leaves' communicates to other designers, how related all the different designs are to each other.
image of the 'leaf canopy'. Although not always the case, the general rule will typically apply: one 'archive leaf' = one design iteration = one contributor.
In addition, to fully communicate their vision and rationale behind their designs, this interface will allow contributors to take snapshots of their designs and, combined with descriptive commentary, upload them to the external website.
Since there will be multiple designs iterations within the 'tree canopy' and only a limited amount of land, the 'wiki-tree' interface, by touching the leaves, will allow members to 'rez' out the designs, one by one, onto the viewing parcel. Once rezzed out, viewers are then able to immerse themselves, 3-dimensional, in the design. In addition, to augment the experience of actually occupying the space, the three screens in the viewing kiosk near the 'wiki-tree' will allow users to cycle through the snapshots and comments associated with the active design on the viewing parcel as well. This viewing kiosk will become especially helpful for those who want to communicate their designs informally with a smaller group of individuals.
The 'wiki-tree' allows the community, in turn, to vote and comment on their fellow contributor's designs.
Other than cycling and rezzing out the individual designs from the 'archiving leaves', The website component will allow users all the same functionality as the in-world interface. In other words, through the website, members can vote and add comments, as well as upload images they would like to associate with their saved designs.
What if this collaboratively designed entry actually wins this OAN competition? How will the reward money actually be divvied up amongst the contributors? If you worked on the last Wikitecture experiment, we will be using the same system whereby we ask all the contributors to assess what percentage they feel they have contributed to the design as well as what percentage they feel others have contributed. The general idea being, that when everyone's assessment of each other is averaged out, however subjective it may be, a pretty fair judgment is made to how much (compensation, ownership, IP rights, etc) should be dolled out to each contributor. If, in the event, Studio Wikitecture's entry wins the competition, we will distribute the winnings in this manner.
Although this system of assessment is not perfect, we feel it's a start. This is one component of the experiment we feel will need to be massaged here and there as we go forward and would love your input to help improve it. Throughout the next two months of designing and assessing, if you have an idea on how to improve either this contribution assessment procedure, or any other functionality for that matter, please let us know. We have set up a forum for such discussion: Feedback & F.A.Q.
Although, this collaborative platform is light years beyond what was used for the 2nd experiment, please be aware that it's still somewhere between alpha and the prepubescence beta stage of development—we will most likely encounter our fair share of bugs.
Although running at a base level right now, certain features will not be available until Nov. 7th.
Would you like to participate in the AMD Open Architecture Challenge on a global team of qualified and talented architects, designers and engineers? Studio Wikitecture invites you to just that.
In keeping with the spirit of the Open Architecture Network's goal of 'improving the living standards through collaborative design,' we will be employing the next generation Wikitecture process in order to more fully enable true 3D collaboration by community members from around the world. In much the same way Wikipedia enables multiple contributors to collaborate on content creation, the Wikitecture process gives community members an opportunity to share ideas, edit the contributions of others, and to vote on the success or failure of proposed modifications.
Through a series of ongoing experiments during the past several months, the Wikitecture process has been evolving based on community participation and feedback. With this input, Theory Shaw has developed the 'Wikitecture Tree' concept, and we've hired the clever folks at i3Dnow to build it for us, which will include both inworld and web-based functionality. We hope to roll out this new platform just in time to get started on a collaborative Wikitecture competition entry for the AMD Open Architecture challenge.
The Wikitecture process currently uses the free to use, free to access virtual reality platform of Second Life to enable multiple contributors to share ideas and collaborate on design concepts.
2.) Complete the orientation course to help familiarize yourself with navigation, etc.
3.) Click on the 'Search' button on the bottom of your screen. With the 'All' tab highlighted, search for either 'Keystone Bouchard' or "Theory Shaw' – the organizers of the Wikitecture project. Click on their name, and you'll see an 'Instant Message' button in their profile. Send either of us a message, and we will get back to you shortly with more details on how you can join the community.
4.) By clicking on the 'Map' button and searching for Architecture Island, you will be able to teleport directly into the site location, and migth even run into other members of the in-world community who can help with any questions you may have.
To join our project page on OAN, visit HERE.
I've decided to Open Source several of the scripts behind the Reflexive Architecture installations, with Fumon Kubo's permission under the Creative Commons Attribution-Share Alike 3.0 License.
Since this work is inspired by so many others, it only makes sense to make these open and accessible in order to encourage their ongoing development and evolution. If you use these scripts, I strongly encourage you to share screenshots or machinima of whatever you create for publication here, in order to inspire others to continue developing this. More about reflexive architecture HERE and HERE, machinima here: 1, 2, 3, 4, 5, 6, 7, 8, 9.