Data from field and lab study on germination and plant growth among sub-Arctic mosses

Data from field and lab study on germination and plant growth among sub-Arctic mosses

This record is for the dataset “Predictions for "Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: regional patterns and uncertainties” at <a href= "https://zenodo.org/doi/10.5281/zenodo.4521851">https://zenodo.org/doi/10.5281/zenodo.4521851</a>. <p><p> <b>Description of the predictions</b><p>These data include predictions of annual and growing season carbon dioxide (CO2) fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 across the terrestrial high-latitude tundra and boreal region. We synthesized flux measurements and used geospatial data to predict (i.e., upscale) CO2 fluxes at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly-used statistical models and their ensemble, i.e., the median of all five models. Predictions were made separately for each year and flux. More details can be found in Virkkala et al. "Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: regional patterns and uncertainties" (in review) <p><b>Files in this repository</b> <p>This repository includes 27 rasters for each flux variable (i.e., annual GPP, annual ER, annual NEE, growing season GPP, growing season ER, growing season NEE). These raster files represent ensemble predictions for each flux variable and year (from 1990 to 2015, 26 years in total), and an average prediction across the years. Annual and growing season rasters are found in their own zipped folders.<p>Rasters are in Lambert North Pole Equal-Area Projection and in .tif format and come together with their supporting files which are useful for plotting the maps in e.g. ArcMap. Permanent water bodies and croplands were masked from these predictions. Quality control of the predictors resulted in some pixels lacking values for a given year, resulting in slight inconsistencies in data set extent across the years. Flux predictions need to be multiplied by 0.01 to arrive at the original scale <p>This dataset can be downloaded at <a href= "https://zenodo.org/doi/10.5281/zenodo.4521851">https://zenodo.org/doi/10.5281/zenodo.4521851</a>.

This record is for the dataset “Data for: "Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: regional patterns and uncertainties"" at <a href= "https://doi.org/10.5281/zenodo.4519583 "> https://doi.org/10.5281/zenodo.4519583</a><p><p> This dataset is a compilation of eddy covariance and chamber measurements of annual and growing season carbon dioxide (CO2) fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE). The dataset includes flux measurements conducted during 1990–2015 from 148 terrestrial high-latitude tundra and boreal sites. The fluxes and supporting metadata were synthesized by conducting a literature survey, organizing a community call to retrieve unpublished data, and leveraging the available data in FLUXNET2015. Further, we used geospatial products to derive environmental data to these sites. More details can be found in Virkkala et al. "Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: regional patterns and uncertainties" (in review). <p><b>Files in this repository</b> <p>This repository consists of two datasets: annual_growingseason_CO2flux.csv includes the data and annual_growingseason_CO2flux_metadata.csv provides a description of the columns. <p>This dataset can be downloaded at <a href= "https://doi.org/10.5281/zenodo.4519583 "> https://doi.org/10.5281/zenodo.4519583</a>

Extreme winter warming events in the sub-Arctic have caused considerable vegetation damage due to rapid changes in temperature and loss of snow cover. The frequency of extreme weather is expected to increase due to climate change thereby increasing the potential for recurring vegetation damage in Arctic regions. Here we present data on vegetation recovery from one such natural event and multiple experimental simulations in the sub-Arctic using remote sensing, handheld passive proximal sensors and ground surveys.Normalized difference vegetation index (NDVI) recovered fast (2 years), from the 26% decline following one natural extreme winter warming event. Recovery was associated with declines in dead Empetrum nigrum (dominant dwarf shrub) from ground surveys. However, E. nigrum healthy leaf NDVI was also reduced (16%) following this winter warming event in experimental plots (both control and treatments), suggesting that non-obvious plant damage (i.e., physiological stress) had occurred in addition to the dead E. nigrum shoots that was considered responsible for the regional 26% NDVI decline. Plot and leaf level NDVI provided useful additional information that could not be obtained from vegetation surveys and regional remote sensing (MODIS) alone. The major damage of an extreme winter warming event appears to be relatively transitory. However, potential knock-on effects on higher trophic levels (e.g., rodents, reindeer, and bear) could be unpredictable and large. Repeated warming events year after year, which can be expected under winter climate warming, could result in damage that may take much longer to recover.

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