cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18739/a25m6275k
title: Ecosystem Carbon Fluxes, Toolik Lake, Alaska, 1995 and 1996

description: Carbon dioxide exchange, air temperature, and photosynthetically active radiation (PAR) were measured on tundra plots at the Toolik Lake Field Station during the summers of 1995 and 1996. Measurements were made on control plots, plots from which snow was removed, and plots from which snow was removed before the installation of heating cables at 10 cm depth. Plots with heating cables were heated two hours per day. Carbon dioxide exchange measurements utilized a Li-Cor 6200 portable gas exchange system, and a Li-Cor quantum sensor was used to measure PAR. Data are available in ASCII and MS Excel formats.
DOI: 10.15468/dl.s92bx7
title: Occurrence Download

description: A dataset containing 1363 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aphis glycines Matsumura, 1917"
 ]
}

 The dataset includes 1363 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027776-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18739/a21v5bf0z
title: Regional Ocean Modeling System (ROMS) output for an idealized East Greenland fjord sensitivity study: physical and biogeochemical fields

description: We use a 3-dimensional, terrain-following, hydrostatic Regional Ocean Modeling System (ROMS) (Haidvogel et al., 2008) to simulate processes within an idealized fjord with features (dimensions, water mass properties, and subglacial discharge rates) similar to those observed for many south east Greenlandic systems. To simulate the biological drawdown of nutrients within the fjord, we add a biogeochemical model with two nutrient types: nitrate and silicate. To test the sensitivity of nutrient export from the fjord under different fjord geometries, forcing conditions, and initial vertical profiles of temperature, salinity, and nutrients, we run the model under 21 different configurations, shared as NetCDF files in this dataset. All time fields are calculated from 12.42-hr-average output to remove the M2 tidal influence on outflow velocities.
 # Characteristic
 1 Base case
 2 Narrower
 3 Wider
 4 Shorter
 5 Longer
 6 Shallower sill
 7 No sill
 8 100 m deeper grounding depth
 9 50 m deeper grounding depth
 10 100 m shallower grounding depth
 11 50 m shallower Atlantic Water/Polar Water interface
 12 No tides
 13 Double discharge
 14 No basal melt
 15 Shelf forcing
 16 Turbid
 17 Subglacial nutrients
 18 Land-terminating
 19 Double phytoplankton max growth rates
 20 Double max zooplankton grazing rate
 21 Lower (½x) phytoplankton light attenuation coefficient
DOI: 10.18739/a2rf5kg4m
title: Winter snow depth as a driver of microbial activity, nutrient cycling, tree growth and treeline advance in the Arctic

description: Overview:
 It has long been thought that temperature exerts a direct control on growth of treeline trees and the position of the treeline. However, our recent work in the Arctic with white spruce suggests that indirect effects of temperature on soil nutrient availability may be of equal or greater importance. We hypothesize that cold soils at the treeline, particularly during winter, limit microbial activity and nutrient availability to the point where trees are barely able to survive and grow. Measurements made during winter have revealed that Arctic forests maintain snowpacks that are much deeper than observed at treeline. Trees are thought to trap snow and lead to a deeper snowpack, insulating the soil from cold air and allowing for greater overwinter microbial activity and greater nutrient mineralization. Indeed, we found a strong positive correlation between white spruce growth and winter snow depth. We propose to isolate the mechanisms underlying this correlation by using snowfences to manipulate winter snow depth and fertilizer to increase soil nutrient availability at three treelines that differ in soil moisture. To provide an experimental test of the importance of temperature as a direct control on treeline tree growth, we propose to incorporate experimental shoot warming into our snowfence experiment in a factorial design. We predict that both experimental snow and nutrient additions will lead to large increases in microbial activity, photosynthesis, tree growth, seed quality, seed production, seedling establishment and recruitment of new trees. We expect to observe the greatest positive responses where soils are wet and cold. Meanwhile, we predict that shoot warming will lead to negligible changes in growth. This research will elucidate the relationship between snow depth and soil nutrient availability, and determine the relative importance of nutrient and temperature limitations at treeline to white spruce – a dominant member of the boreal forest and the northernmost tree species in North America.
 Intellectual Merit:
 The position of the Arctic treeline is an important regulator of surface energy budgets, carbon cycling and subsistence resources in high latitude environments. Our recent research provides correlative evidence of the importance of winter snow depth as a driver of tree growth. Here, we propose to experimentally isolate the importance of snow depth and soil nutrient availability and examine the consequences for microbial processes and tree performance. This is a novel proposal, as we aim to link microbial ecology with large-scale landscape patterns of relevance to regional and global climates. If our hypotheses are confirmed, our findings will contradict the prevailing theory of treeline causation, alter our predictions of where and when treelines may advance and necessitate revision of the many paleoclimate reconstructions based upon correlations between temperature and tree growth near the Arctic treeline.
DOI: 10.18739/a2mp4vp0g
title: Winter snow depth as a driver of microbial activity, nutrient cycling, tree growth and treeline advance in the Arctic

description: Overview:
 It has long been thought that temperature exerts a direct control on growth of treeline trees and the position of the treeline. However, our recent work in the Arctic with white spruce suggests that indirect effects of temperature on soil nutrient availability may be of equal or greater importance. We hypothesize that cold soils at the treeline, particularly during winter, limit microbial activity and nutrient availability to the point where trees are barely able to survive and grow. Measurements made during winter have revealed that Arctic forests maintain snowpacks that are much deeper than observed at treeline. Trees are thought to trap snow and lead to a deeper snowpack, insulating the soil from cold air and allowing for greater overwinter microbial activity and greater nutrient mineralization. Indeed, we found a strong positive correlation between white spruce growth and winter snow depth. We propose to isolate the mechanisms underlying this correlation by using snowfences to manipulate winter snow depth and fertilizer to increase soil nutrient availability at three treelines that differ in soil moisture. To provide an experimental test of the importance of temperature as a direct control on treeline tree growth, we propose to incorporate experimental shoot warming into our snowfence experiment in a factorial design. We predict that both experimental snow and nutrient additions will lead to large increases in microbial activity, photosynthesis, tree growth, seed quality, seed production, seedling establishment and recruitment of new trees. We expect to observe the greatest positive responses where soils are wet and cold. Meanwhile, we predict that shoot warming will lead to negligible changes in growth. This research will elucidate the relationship between snow depth and soil nutrient availability, and determine the relative importance of nutrient and temperature limitations at treeline to white spruce – a dominant member of the boreal forest and the northernmost tree species in North America.
 Intellectual Merit:
 The position of the Arctic treeline is an important regulator of surface energy budgets, carbon cycling and subsistence resources in high latitude environments. Our recent research provides correlative evidence of the importance of winter snow depth as a driver of tree growth. Here, we propose to experimentally isolate the importance of snow depth and soil nutrient availability and examine the consequences for microbial processes and tree performance. This is a novel proposal, as we aim to link microbial ecology with large-scale landscape patterns of relevance to regional and global climates. If our hypotheses are confirmed, our findings will contradict the prevailing theory of treeline causation, alter our predictions of where and when treelines may advance and necessitate revision of the many paleoclimate reconstructions based upon correlations between temperature and tree growth near the Arctic treeline.
DOI: 10.15468/dl.ah428c
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ledermanniella kamerunensis (Engl.) C.Cusset"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027777-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18739/a2gx44v63
title: Vegetation classifications for random points in the Agashashok River watershed in 1952, 1979 and 2015

description: Climate change is expected to increase woody vegetation abundance in the Arctic, yet the magnitude, spatial pattern and pathways of change remain uncertain. We compared historical orthophotos photos (1952 and 1979) with high-resolution satellite imagery (2015) to examine six decades of change in abundance of white spruce (Picea glauca) and tall shrubs (Salix spp., Alnus spp.) near the Agashashok River in northwest Alaska. We established ~3000 random points within our ~5500 ha study area for classification into nine cover types. To examine physiographic controls on tree abundance, we fit multinomial log-linear models with predictors derived from a digital elevation model and with arctic tundra, alpine tundra and “tree” as levels of a categorical response variable. Between 1952 and 2015, points classified as arctic and alpine tundra decreased by 31% and 15%, respectively. Meanwhile, tall shrubs increased by 86%, trees mixed with tall shrubs increased by 385% and forest increased by 84%. Tundra with tall shrubs rarely transitioned to forest. The best multinomial model explained 71% of variation in cover and included elevation, slope and an interaction between slope and “northness”. Treeline was defined as the elevation where the probability of tree presence equaled that of tundra. Mean treeline elevation in 2015 was 202 meters (m), corresponding with a June-August mean air temperature &gt;11° Celsius (C), which is &gt;4°C warmer than the 6-7°C isotherm associated with global treeline elevations. Our results show dramatic increases in the abundance of trees and tall shrubs, question the universality of air temperature as a predictor of treeline elevation and suggest two mutually exclusive pathways of vegetation change, because tundra that gained tall shrubs rarely transitioned to forest. Conversion of tundra to tall shrubs and forest has important and potentially contrasting implications for carbon cycling, surface energy exchange and wildlife habitat in the Arctic.
DOI: 10.18739/a2c53f22p
title: Vegetation classifications for random points in the Agashashok River watershed in 1952, 1979 and 2015

description: Climate change is expected to increase woody vegetation abundance in the Arctic, yet the magnitude, spatial pattern and pathways of change remain uncertain. We compared historical orthophotos photos (1952 and 1979) with high-resolution satellite imagery (2015) to examine six decades of change in abundance of white spruce (Picea glauca) and tall shrubs (Salix spp., Alnus spp.) near the Agashashok River in northwest Alaska. We established ~3000 random points within our ~5500 ha study area for classification into nine cover types. To examine physiographic controls on tree abundance, we fit multinomial log-linear models with predictors derived from a digital elevation model and with arctic tundra, alpine tundra and “tree” as levels of a categorical response variable. Between 1952 and 2015, points classified as arctic and alpine tundra decreased by 31% and 15%, respectively. Meanwhile, tall shrubs increased by 86%, trees mixed with tall shrubs increased by 385% and forest increased by 84%. Tundra with tall shrubs rarely transitioned to forest. The best multinomial model explained 71% of variation in cover and included elevation, slope and an interaction between slope and “northness”. Treeline was defined as the elevation where the probability of tree presence equaled that of tundra. Mean treeline elevation in 2015 was 202 meters (m), corresponding with a June-August mean air temperature &gt;11° Celsius (C), which is &gt;4°C warmer than the 6-7°C isotherm associated with global treeline elevations. Our results show dramatic increases in the abundance of trees and tall shrubs, question the universality of air temperature as a predictor of treeline elevation and suggest two mutually exclusive pathways of vegetation change, because tundra that gained tall shrubs rarely transitioned to forest. Conversion of tundra to tall shrubs and forest has important and potentially contrasting implications for carbon cycling, surface energy exchange and wildlife habitat in the Arctic.
DOI: 10.18739/a27d2q78x
title: Vegetation classifications for random points in the Agashashok River watershed in 1952, 1979 and 2015

description: Climate change is expected to increase woody vegetation abundance in the Arctic, yet the magnitude, spatial pattern and pathways of change remain uncertain. We compared historical orthophotos photos (1952 and 1979) with high-resolution satellite imagery (2015) to examine six decades of change in abundance of white spruce (Picea glauca) and tall shrubs (Salix spp., Alnus spp.) near the Agashashok River in northwest Alaska. We established ~3000 random points within our ~5500 ha study area for classification into nine cover types. To examine physiographic controls on tree abundance, we fit multinomial log-linear models with predictors derived from a digital elevation model and with arctic tundra, alpine tundra and “tree” as levels of a categorical response variable. Between 1952 and 2015, points classified as arctic and alpine tundra decreased by 31% and 15%, respectively. Meanwhile, tall shrubs increased by 86%, trees mixed with tall shrubs increased by 385% and forest increased by 84%. Tundra with tall shrubs rarely transitioned to forest. The best multinomial model explained 71% of variation in cover and included elevation, slope and an interaction between slope and “northness”. Treeline was defined as the elevation where the probability of tree presence equaled that of tundra. Mean treeline elevation in 2015 was 202 meters (m), corresponding with a June-August mean air temperature &gt;11° Celsius (C), which is &gt;4°C warmer than the 6-7°C isotherm associated with global treeline elevations. Our results show dramatic increases in the abundance of trees and tall shrubs, question the universality of air temperature as a predictor of treeline elevation and suggest two mutually exclusive pathways of vegetation change, because tundra that gained tall shrubs rarely transitioned to forest. Conversion of tundra to tall shrubs and forest has important and potentially contrasting implications for carbon cycling, surface energy exchange and wildlife habitat in the Arctic.
DOI: 10.18739/a23n20f45
title: Vegetation classifications for random points in the Agashashok River watershed in 1952, 1979 and 2015

description: Climate change is expected to increase woody vegetation abundance in the Arctic, yet the magnitude, spatial pattern and pathways of change remain uncertain. We compared historical orthophotos photos (1952 and 1979) with high-resolution satellite imagery (2015) to examine six decades of change in abundance of white spruce (Picea glauca) and tall shrubs (Salix spp., Alnus spp.) near the Agashashok River in northwest Alaska. We established ~3000 random points within our ~5500 hectare (ha) study area for classification into nine cover types. To examine physiographic controls on tree abundance, we fit multinomial log-linear models with predictors derived from a digital elevation model and with arctic tundra, alpine tundra and “tree” as levels of a categorical response variable. Between 1952 and 2015, points classified as arctic and alpine tundra decreased by 31% and 15%, respectively. Meanwhile, tall shrubs increased by 86%, trees mixed with tall shrubs increased by 385% and forest increased by 84%. Tundra with tall shrubs rarely transitioned to forest. The best multinomial model explained 71% of variation in cover and included elevation, slope and an interaction between slope and “northness”. Treeline was defined as the elevation where the probability of tree presence equaled that of tundra. Mean treeline elevation in 2015 was 202 meters (m), corresponding with a June-August mean air temperature greater than 11° Celsius (C), which is greater than 4°C warmer than the 6-7°C isotherm associated with global treeline elevations. Our results show dramatic increases in the abundance of trees and tall shrubs, question the universality of air temperature as a predictor of treeline elevation and suggest two mutually exclusive pathways of vegetation change, because tundra that gained tall shrubs rarely transitioned to forest. Conversion of tundra to tall shrubs and forest has important and potentially contrasting implications for carbon cycling, surface energy exchange and wildlife habitat in the Arctic.
DOI: 10.18739/a2zw18t08
title: Winter snow depth as a driver of microbial activity, nutrient cycling, tree growth and treeline advance in the Arctic

description: Overview:
 It has long been thought that temperature exerts a direct control on growth of treeline trees and the position of the treeline. However, our recent work in the Arctic with white spruce suggests that indirect effects of temperature on soil nutrient availability may be of equal or greater importance. We hypothesize that cold soils at the treeline, particularly during winter, limit microbial activity and nutrient availability to the point where trees are barely able to survive and grow. Measurements made during winter have revealed that Arctic forests maintain snowpacks that are much deeper than observed at treeline. Trees are thought to trap snow and lead to a deeper snowpack, insulating the soil from cold air and allowing for greater overwinter microbial activity and greater nutrient mineralization. Indeed, we found a strong positive correlation between white spruce growth and winter snow depth. We propose to isolate the mechanisms underlying this correlation by using snowfences to manipulate winter snow depth and fertilizer to increase soil nutrient availability at three treelines that differ in soil moisture. To provide an experimental test of the importance of temperature as a direct control on treeline tree growth, we propose to incorporate experimental shoot warming into our snowfence experiment in a factorial design. We predict that both experimental snow and nutrient additions will lead to large increases in microbial activity, photosynthesis, tree growth, seed quality, seed production, seedling establishment and recruitment of new trees. We expect to observe the greatest positive responses where soils are wet and cold. Meanwhile, we predict that shoot warming will lead to negligible changes in growth. This research will elucidate the relationship between snow depth and soil nutrient availability, and determine the relative importance of nutrient and temperature limitations at treeline to white spruce – a dominant member of the boreal forest and the northernmost tree species in North America.
 Intellectual Merit:
 The position of the Arctic treeline is an important regulator of surface energy budgets, carbon cycling and subsistence resources in high latitude environments. Our recent research provides correlative evidence of the importance of winter snow depth as a driver of tree growth. Here, we propose to experimentally isolate the importance of snow depth and soil nutrient availability and examine the consequences for microbial processes and tree performance. This is a novel proposal, as we aim to link microbial ecology with large-scale landscape patterns of relevance to regional and global climates. If our hypotheses are confirmed, our findings will contradict the prevailing theory of treeline causation, alter our predictions of where and when treelines may advance and necessitate revision of the many paleoclimate reconstructions based upon correlations between temperature and tree growth near the Arctic treeline.
DOI: 10.18739/a2v698c71
title: Unmanned Aerial Systems (UAS) Multispectral & Normalized difference vegetation index (NDVI) Orthomosaics of Subset area within Circumpolar Active Layer Monitoring (CALM) grid Atqasuk, Alaska, USA, 2019

description: Beginning in the summer of 2018, high resolution multispectral Unmanned Aerial Systems (UAS) datasets were collected across multiple sites in northern Alaska in an effort to characterize landcover, test remote sensing scaling methods and for use in validating satellite data products. Orthomosaic datasets were developed from multispectral images acquired using a Micasense RedEdge-M sensor and using standardized structure-from-Motion (SfM) photogrammetry workflows. UAS data products reflect landscape and vegetation composition and status at time of flight. We produced two data products (1) 6 band multispectral orthomosaic of Circumpolar Active Layer Monitoring Program (CALM) subset area and (2) 1 band normalized Normalized difference vegetation index (NDVI) orthomosaic of CALM subset area. All data have been calibrated using the proprietary Micasense grey-scale reflectance panel and/or the on-board drone sun sensor.
 The 6 band multispectral image consists of:
 Band 1: Blue (475 nm center, 20 nm bandwidth),
 Band 2: Green (560 nm center, 20 nm bandwidth),
 Band 3: Red (668 nm center, 10 nm bandwidth),
 Band 4: Red Edge (717 nm center, 10 nm bandwidth),
 Band 5: Near-IR (840 nm center, 40 nm bandwidth),
 Band 6: NDVI (not scaled)
 The 1 band NDVI product consists of:
 Band 1: Scaled NDVI map (calculated within ArcMap)
DOI: 10.18739/a2qf8jk4c
title: Iliamna Lake (Nanvarpak, Nila Vena) Native and Local Place Names (2016-2019)

description: Alaska Native place name geodatabase records (points and polygons) from Iliamna Lake region compiled by Yoko Kugo as part of NSF-supported dissertation, based on ethnographic field work in Iliamna, Newhalen, Kokhanok, Igiugig, and Levelock from 2016 to 2019. Names are listed in Yugcetun (Yup'ik) language, with accompanying English name and literal meaning. Some Yugcetun are no longer within the collective memory but the literal meaning is still known; for these names only the English name and meaning are given. The database also include local (unofficial) English names in common use in the region. More than 30 community Elders and local knowledge holders contributed to this project, and the project acknowledges the communities of Iliamna, Newhalen, Kokhanok, Igiugig, and Levelock, the Iliamna Lake Place Names Committee.