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53 results for “arctic vegetation”
Vegetation species abundance via point frame from Arctic LTER dry heath tundra, Toolik Field Station, Alaska, 2017
Vegetation (species) abundances were measured from LTER heath tundra herbivore exclosures using the point frame method. This file contains the number of pin hits per species for each subplot.
Arctic vegetation cover fractions derived from Landsat time series (1984-2020) for the greater Mackenzie Delta Region (Western Canadian Arctic)
<p>Data to the publication by Nill et al. (2022) "<em>Arctic shrub expansion revealed by Landsat-derived multitemporal<br> vegetation cover fractions in the Western Canadian Arctic"</em></p> <p>The dataset features Landsat-derived fractional cover estimates of Arctic plant functional types (shrub, evergreen trees, herbaceous, lichen) and other land cover (barren, water) in the greater Mackenzie Delta Region, Canada.<br> We utilized regression-based unmixing based on synthetic training data in order to build multitemporal Kernel Ridge Regression (KRR) models for estimating fractional cover and validated our predictions based on independent very-high-resolution imagery (please be referred to publication for details).<br> <br> <strong>Dataset information</strong><br> The fraction cover predictions ("krr-avg") are provided separately for each epoch (1984-1990, 1991-1996, ..., 2015-2020) and class/cover type. The decadal change images ("dec-cng") between 1984 and 2020 are provided separately for each class/cover type. The naming convention of the files is as follows:</p> <p>XXXX-XXXX_YYY-YYY_int16-10e3_class-Z-Z</p> <ul> <li>XXXX-XXXX = epoch, e.g. 2015-2020</li> <li>YYY-YYY = dataset ("krr-avg" = fraction cover, "dec-cng" = decadal fraction cover change)</li> <li>Z-Z = class ID and associated class name (sh = shrub, cf = coniferous, hb = herbaceous, lc = lichen, wt = water, br = barren)</li> </ul> <p>The fraction cover values are % scaled by 10,000. For instance, a value of 1234 refers to 12.34%. Further image metadata:</p> <ul> <li><strong>Datatype:</strong> Signed 16-bit integer (Int16) </li> <li><strong>Data format: </strong>GeoTiff (.tif)</li> <li><strong>No data value:</strong> -9999</li> <li><strong>Projection:</strong> EPSG:3573 with custom central meridian; WKT string: 'PROJCS["WGS 84 / North Pole LAEA Canada",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Lambert_Azimuthal_Equal_Area"],PARAMETER["latitude_of_center",90],PARAMETER["longitude_of_center",-135],PARAMETER["false_easting",0],PARAMETER["false_northing",0],UNIT["metre",1],AXIS["Easting",EAST],AXIS["Northing",NORTH]]'</li> </ul> <p><strong>Publication</strong><br> Nill, L., Grünberg, I., Ullmann, T., Gessner, M., Boike, J. & Hostert, P. (2022): Arctic shrub expansion revealed by Landsat-derived multitemporal vegetation cover fractions in the Western Canadian Arctic. Remote Sensing of Environment, 2022, 281. https://doi.org/10.1016/j.rse.2022.113228</p> <p><strong>Further information</strong><br> For further information, please see the publication or contact Leon Nill (leon.nill@geo.hu-berlin.de).<br> A web-visualization of this dataset is available <a href="https://ows.geo.hu-berlin.de/webviewer/arctic-shrub/">here</a>.</p>
Data from: Will Current Protected Areas Harbour Refugia for Threatened Arctic Vegetation Types until 2050? A First Assessment
<p>We present predictions of Arctic vegetation for 2050 based on a combination of climate models (namely, EC-Earth3-Veg, IPSL-CM6A-LR, and MRI-ESM2-0), emission scenarios (names, SSP126 and SSP585) and tree dispersal rate scenarios (unrestricted, 20km and 5km) based on the methods of Pearson et al. (2013) and the new raster version of the Circumpolar Arctic Vegetation Map (CAVM) (Raynolds et al. 2019). We additionally present a dataset summarising total areas for each vegetation type in the CAVM and the forecasted models based on the computation of zonal histograms in ArcGIS (zonal_histogram_results.csv), for the total Arctic as well as only within protected areas, defined by the Map of Arctic Protected Areas (CAFF and PAME 2017). We also present a potential map of refugia for what we deem the realistic model (IPSL, SSP585, 20 km tree dispersal) as a raster file. Refugia were identified as regions where the vegetation remained the same between the CAVM and the predictions. Additionally, we present a map of model agreement, showing the degree to which other models agree with the vegetation classification for our refugia.</p> <p>All predictions named according to the tree dispersal rate, climate model, and emissions scenario, preceded by the term "pred". For example: "pred_unres_mri_585" represents the unrestricted tree dispersal, MRI-ESM-0 climate model, and SSP585 scenario-based prediction. The MRI-ESM-0 x SSP585 combination had gaps in data which results in a lack of predictions in some areas; this affects 3 models.</p> <p>Further details and all code associated with these datasets are found <a href="https://github.com/PlekhanovaElena/Arctic_vegetation_prediction">here</a>.</p>
Spectral albedo and summer ground temperature of herbaceous and shrub tundra vegetation at Bylot Island, Canadian High-Arctic
<p>These data are in support of a preprint: </p><p>Comparing spectral albedo and NDVI of herbaceous and shrub tundra vegetation at Bylot Island, Canadian High-Arctic</p><p>Florent Domine, Maria-Belke-Brea, Ghislain Picard, Laurent Arnaud, and Esther Lévesque</p><p>To be submitted in 2023. </p><p>The spectral albedo of several vegetation assemblages on Bylot Island and in Mala River valley on nearby Baffin Island were recorded between 10 and 18 July 2015. The spectral range covered was 346 to 2400 nm. Surfaces were classified according to the main vegetation types. Classes used are graminoids, moss, Salix arctica, soil, and Salix richardsonii. S. richardsonii is the only truly erect species on Bylot Island. Transmission spectra of radiation through the S. richardsonii canopy were also recorded. S. richardsonii spectra were different depending on the location where they were measured and we present spectra for sites in active parts of an alluvial fan (Salix-G2), an inactive part of an alluvial fan (Salix-D1) and in a mesic area on Mala River Valley (Salix-M). We also present typical relative solar irradiance spectra recorded at Bylot Island during the campaign, under clear and overcast conditions. In conjunction with spectral albedo data, these irradiance spectra allow the calculation of the broadband (BB) albedo of the vegetation types and to compare BB albedo values under identical irradiance conditions. 83 spectra were recorded: 39 for S. richardsonii and 44 for low vegetation and soil. 17 transmission spectra under S. richardsonii were recorded. We present here only averages for each vegetation type. We also present averages for all low vegetation types and for all S. richardsonii spectra, to allow the calculation of the radiative impact of erect shrubs at Bylot Island. </p><p>We also present soil temperature data at 15 cm depth for the spots GRASS (mostly Salix Arctica), TUNDRA (Mostly moss), SALIX-D1 (Salix richardsonii) and SALIX-F (Salix richardsonii). SALIX-F is similar to SALIX-G2. The data are during summer 2020. </p><p>The locations of the various spots investigated are: </p><p><strong>Spot name Latitude Longitude Vegetation types found</strong></p><p>TUNDRA 73.150° -80.004° Humid and moist polygons with low vegetation dominated by mosses, graminoids, S. arctica and S. herbacea.</p><p>PLAINE 73.167° -79.915° Low vegetation and bare soil patches caused by cryoturbation (mudboils) with mosses, graminoids and S. arctica.</p><p>GRASS 73.158° -79.907° Low vegetation between patches of S. richardsonii dominated by S. arctica, with litter, mosses, graminoids and occasional bare soil. </p><p>SALIX-D1 73.158° -79.907° Scattered patches of S. richardsonii <35 cm tall. Understory is mosses, graminoids, litter, S. arctica and bare soil.</p><p>SALIX-M 73.006° -80.685° Mesic area with patches of S. richardsonii 35 to 40 cm tall. Understory includes moss, graminoids and litter. Between patches: herb tundra with graminoids and mosses. The area is not within an alluvial fan.</p><p>SALIX-G2 73.168° -79.812° Extended area in an alluvial fan with S. richardsonii >40 cm. Understory includes litter, mosses, graminoids, bare soil, S. arctica and S. reticulata.</p><p>SALIX-F 73.182° -79.745° Similar to SALIX-G2. Ground temperature is monitored there. No spectral data were recorded at that site. </p><p> </p><p> </p>
Data from: Cross-scale regulation of seasonal microclimate by vegetation and snow in the Arctic tundra
<p>The zip file contains data and code from the analyses for von Oppen et al. (2022) <em>Global Change Biology</em> (<a href="https://doi.org/10.1111/gcb.16426">https://doi.org/10.1111/gcb.16426</a>). Access through the provided R project file (e.g. with RStudio) is recommended for seamless running of the code. Please see the paper (link below) for methodological details, results and discussion, and the ReadMe included in the archive for further detail and usage policy.</p>
Russian Arctic Vegetation Archive – a new database of plant community composition and environmental conditions
<p><span>The goal of the Russian Arctic Vegetation Archive is to unite and harmonize data of plot-based plant species and their abundance, vegetation structure and environmental variables from the Russian Arctic (including historical Soviet data). This database can be used to assess the status of the Russian Arctic vegetation and as a baseline to assess biodiversity changes in the future. The archive can be used for scientific studies as well as to inform nature protection and restoration efforts.</span></p>
Data from: Reindeer carcasses modulate vegetation composition and greenness in High-Arctic tundra
Open the record for dataset details and reuse information.
Russian Arctic Vegetation Archive – a new database of plant community composition and environmental conditions
Open the record for dataset details and reuse information.
13C and 15N Content in Arctic Tussock Tundra and Wet Sedge Vegetation
This file contains 13C and 15N content from tussock tundra and wet sedge vegetation collected from experiemental plots during the years 2001-2006.
14C Uptake by Arctic Tussock Tundra Vegetation from 2002-2006
This file contains the 14C content of tussock tundra vegetation from 2002-2006. The 14C labeling occurred the summer of 2002.
14C Uptake by Arctic Wet Sedge Vegetation from 2002-2005
This file contains the 14C content of tussock tundra vegetation from 2002-2005. The 14C labeling occurred the summer of 2002.
Biomass from six vegetation types along a toposequence on a floodplain terrace of the Sagavanirktok River, Alaswka,1988, Arctic LTER.
Biomass was harvested from six vegetation types along a toposequence on a floodplain terrace of the Sagavanirktok River in the northern foothills of the Brooks Range , Alaska (68degrees 46' N, 148 degrees 51' W 50m). The vegetation sites are; upland tussock tundra, "hilltop heath", a "hillslope shrub-lupine", a "footslope Equisetum", a wet sedge tundra, and a "riverside willow".
Carbon, nitrogen and phosphorus content in the seasonally thawed soils are described for four arctic tundra vegetation types located near the Toolik Field Station, Arctic LTER 1993.
Carbon, nitrogen and phosphorus content in thawed soils are described for four arctic tundra vegetation types located near the Toolik Field Station.
Data from: Arctic fungal communities associated with roots of Bistorta vivipara do not respond to the same fine-scale edaphic gradients as the above-ground vegetation
Soil conditions and microclimate are important determinants of the fine-scale distribution of plant species in the Arctic, creating locally heterogeneous vegetation. We hypothesize that root-associated fungal (RAF) communities respond to the same fine-scale environmental gradients as the aboveground vegetation, creating a coherent pattern between aboveground vegetation and RAF. We explored how RAF communities of the ectomycorrhizal (ECM) plant Bistorta vivipara and aboveground vegetation structure of arctic plants were affected by biotic and abiotic variables at 0.3–3.0-m scales. RAF communities were determined using pyrosequencing. Composition and spatial structure of RAF and aboveground vegetation in relation to collected biotic and abiotic variables were analysed by ordination and semi-variance analyses. The vegetation was spatially structured along soil C and N gradients, whereas RAF lacked significant spatial structure. A weak relationship between RAF community composition and the cover of two ECM plants, B. vivipara and S. polaris, was found, and RAF richness increased with host root length and root weight. Results suggest that the fine-scale spatial structure of RAF communities of B. vivipara and the aboveground vegetation are driven by different factors. At fine spatial scales, neighbouring ECM plants may affect RAF community composition, whereas soil nutrients gradients structure the vegetation.
Data from: Arctic fungal communities associated with roots of Bistorta vivipara do not respond to the same fine-scale edaphic gradients as the above-ground vegetation
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Data from: Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data
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Data from: Fifty thousand years of arctic vegetation and megafaunal diet
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Data from: Urine is an important nitrogen source for plants irrespective of vegetation composition in an Arctic tundra: insights from a 15N-enriched urea tracer experiment
1. Mammalian herbivores can strongly influence nitrogen (N) cycling and herbivore urine could be a central component of the N cycle in grazed ecosystems. Despite its potential role for ecosystem productivity and functioning, the fate of N derived from urine has rarely been investigated in grazed ecosystems. 2. This study explored the fate of <sup>15</sup>N-enriched urea in tundra sites that have been either lightly or intensively grazed by reindeer for more than 50 years. We followed the fate of the <sup>15</sup>N applied to the plant canopy, at 2 weeks and 1 year after tracer addition, in the different ecosystem N pools. 3. <sup>15</sup>N-urea was rapidly incorporated in cryptogams and in aboveground parts of vascular plants, while the soil microbial pool and plant roots sequestered only a marginal proportion. Further, the litter layer constituted a large sink for the <sup>15</sup>N-urea, at least in the short term, indicating a high biological activity in the litter layer and high immobilization in the first phases of organic matter decomposition. 4. Mosses and lichens still constituted the largest sink for the <sup>15</sup>N-urea 1 year after tracer addition at both levels of grazing intensity demonstrating their large ability to capture and retain N from urine. Despite large fundamental differences in their traits, deciduous and evergreen shrubs were just as efficient as graminoids in taking up the <sup>15</sup>N-urea. The total recovery of <sup>15</sup>N-urea was lower in the intensively grazed sites, suggesting that reindeer reduce ecosystem N retention. 5. <i>Synthesis</i> The rapid incorporation of the applied <sup>15</sup>N-urea indicates that arctic plants can take advantage of a pulse of incoming N from urine. In addition, δ <sup>15</sup>N values of all taxa in the heavily grazed sites converged towards the δ <sup>15</sup>N values for urine, bringing further evidence that urine is an important N source for plants in grazed tundra ecosystems.
Reduction in biomass of freshwater arctic vegetation by foraging and nesting hyperabundant herbivores shows recovery
Arctic-nesting geese are specialist herbivores of grasses and sedges (collectively, graminoids). Under moderate grazing pressure, these migratory herbivores can create and maintain arctic grazing lawns with high nutritional content and low aboveground biomass. Nutrient and energy subsidies from southern agricultural landscapes during winter have improved survival among populations of Ross's (Anser rossii) and lesser snow geese (Anser caerulescens caerulescens), leading to marked population growth. Resulting goose hyperabundance has raised conservation concern for resilience of arctic ecosystems to withstand cumulative and intense pressures of herbivory and nest construction. We used both design-based (experimental herbivore exclosures) and model-based methods to investigate changes to plant community structure in direct response to foraging and nesting by these species within the Queen Maud Gulf (Ahiak) Migratory Bird Sanctuary, Nunavut, Canada. Annual nest construction and foraging by up to ~1.3 million geese at a large colony at Karrak Lake markedly reduced aboveground biomass of forage (graminoids) and non-forage (foliose and fruticose lichens) vegetation, with spatial variation in reduction associated with intensity of use by geese. Within vast brood-rearing regions, foraging reduced above- and belowground plant biomass of lowland plant communities by 61% and 29%, respectively, between 1994 (when herbivore exclosures were established) and 2017. In addition to landscape diversity associated with abiotic properties created by geomorphic processes, long-term herbivory by geese further increased spatial heterogeneity in vegetation at the landscape scale. Although foraging geese nearly completely depleted aboveground plant biomass in some parts of their brood-rearing areas, belowground biomass was largely conserved, and thus, plant communities had strong potential for aboveground regeneration. We propose that effects of high-density nesting and foraging by Ross's and lesser snow geese in the central Canadian Arctic, while extensive, are ephemeral and prone to reversion following cessation of grazing and nesting pressure, such as that afforded by shifts in herbivore distribution or local population decline.
Supplementary material 2 from: Parisy B, Schmidt NM, Wirta H, Stewart L, Pellissier L, Holben WE, Pannoni S, Somervuo P, Jones MM, Siren J, Vesterinen E, Ovaskainen O, Roslin T (2023) Ecological signals of arctic plant-microbe associations are consistent across eDNA and vegetation surveys. Metabarcoding and Metagenomics 7: e99979. https://doi.org/10.3897/mbmg.7.99979
Key to taxa for Figure 5, figures S11A and S11B
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