• Energy Research

This dataset provides estimates of live, oven-dried aboveground biomass of all plants (tree, shrub, graminoid, forb, bryophyte) and all woody plants (tree, shrub) at 30-meter resolution across the Arctic tundra biome. Estimates of woody plant dominance are also provided as: (woody plant biomass / plant biomass) * 100. Plant biomass and woody plant biomass were estimated for each pixel (grams per square meter [g / m2]) using field harvest data for calibration/validation along with modeled seasonal surface reflectance data derived using Landsat satellite imagery and the Continuous Change Detection and Classification algorithm, and other supplementary predictors related to topography, region (e.g. bioclimate zone, ecosystem type), land cover, and derivative spectral products. Modeling was performed in a two-stage process using random forest models. First, biomass presence/absence was predicted using probability forests. Then, biomass quantity was predicted using regression forests. The model outputs were combined to produce final biomass estimates. Pixel uncertainty was assessed using Monte Carlo iterations. Field and remote sensing data were permuted during each iteration and the median (50th percentile, p500) predictions for each pixel were considered best estimates. In addition, this dataset provides the lower (2.5th percentile, p025) and upper (97.5th percentile, p975) bounds of a 95% uncertainty interval. Estimates of woody plant dominance are not modeled directly, but rather derived from plant biomass and woody plant biomass best estimates. The Pan Arctic domain includes both the Polar Arctic, defined using bioclimate zone data from the Circumpolar Arctic Vegetation Mapping Project (CAVM; Walker et al., 2005), and the Oro Arctic (treeless alpine tundra at high latitudes outside the Polar Arctic), defined using tundra ecoregions from the RESOLVE ecoregions dataset (Dinerstein et al., 2017) and treeline data from CAVM (CAVM Team, 2003). The mapped products focus on Arctic tundra vegetation biomass, but the coarse delineation of this biome meant some forested areas were included within the study domain. Therefore, this dataset also provides a tree mask product that can be used to mask out areas with canopy height ≥ 5 meters. This mask helps reduce, but does not eliminate entirely, areas of dense tree cover within the domain. Users should be cautious of predictions in forested areas as the models used to predict biomass were not well constrained in these areas. This dataset includes 132 files: 128 cloud-optimized GeoTIFFs, 2 tables in comma-separated values (CSV) format, 1 vector polygon in Shapefile format, and one figure in JPEG format. Raster data is provided in the WGS 84 / North Pole LAEA Bering Sea projection (EPSG:3571) at 30 meter (m) resolution. Raster data are tiled with letters representing rows and numbers representing columns, but note that some tiles do not contain unmasked pixels. We included all tiles nonetheless to maintain consistency. Tiling information can be found in the ‘metadata’ directory as a figure (JPEG) or shapefile.

The dynamics of rapid changes in carbon (C) partitioning within forest ecosystems are not well understood, which limits improvement of mechanistic models of C cycling. Our objective was to inform model processes by describing relationships between C partitioning and accessible environmental or physiological measurements, with a special emphasis on short-term C flux through a forest ecosystem. We exposed eight 7-year-old loblolly pine (Pinus taeda L.) trees to air enriched with (13)CO(2) and then implemented adjacent light shade (LS) and heavy shade (HS) treatments in order to manipulate C uptake and flux. The impacts of shading on photosynthesis, plant water potential, sap flow, basal area growth, root growth and soil CO(2) efflux rate (CER) were assessed for each tree over a 3-week period. The progression of the (13)C label was concurrently tracked from the atmosphere through foliage, phloem, roots and surface soil CO(2) efflux. The HS treatment significantly reduced C uptake, sap flow, stem growth and fine root standing crop, and resulted in greater residual soil water content to 1 m depth. Soil CER was strongly correlated with sap flow on the previous day, but not the current day, with no apparent treatment effect on the relationship. Although there were apparent reductions in new C flux belowground, the HS treatment did not noticeably reduce the magnitude of belowground autotrophic and heterotrophic respiration based on surface soil CER, which was overwhelmingly driven by soil temperature and moisture. The (13)C label was immediately detected in foliage on label day (half-life = 0.5 day), progressed through phloem by Day 2 (half-life = 4.7 days), roots by Days 2-4, and subsequently was evident as respiratory release from soil which peaked between Days 3 and 6. The δ(13)C of soil CO(2) efflux was strongly correlated with phloem δ(13)C on the previous day, or 2 days earlier. While the (13)C label was readily tracked through the ecosystem, the fate of root C through respiratory, mycorrhizal or exudative release pathways was not assessed. These data detail the timing and relative magnitude of C flux through various components of a young pine stand in relation to environmental conditions.

ABSTRACTThe below‐ground growing season often extends beyond the above‐ground growing season in tundra ecosystems and as the climate warms, shifts in growing seasons are expected. However, we do not yet know to what extent, when and where asynchrony in above‐ and below‐ground phenology occurs and whether variation is driven by local vegetation communities or spatial variation in microclimate. Here, we combined above‐ and below‐ground plant phenology metrics to compare the relative timings and magnitudes of leaf and fine‐root growth and senescence across microclimates and plant communities at five sites across the Arctic and alpine tundra biome. We observed asynchronous growth between above‐ and below‐ground plant tissue, with the below‐ground season extending up to 74% (~56 days) beyond the onset of above‐ground leaf senescence. Plant community type, rather than microclimate, was a key factor controlling the timing, productivity, and growth rates of fine roots, with graminoid roots exhibiting a distinct ‘pulse’ of growth later into the growing season than shrub roots. Our findings indicate the potential of vegetation change to influence below‐ground carbon storage as the climate warms and roots remain active in unfrozen soils for longer. Taken together, our findings of increased root growth in soils that remain thawed later into the growing season, in combination with ongoing tundra vegetation change including increased shrub and graminoid abundance, indicate increased below‐ground productivity and altered carbon cycling in the tundra biome.

SummaryAtmospheric carbon dioxide concentration ([CO2]) is increasing, which increases leaf‐scale photosynthesis and intrinsic water‐use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO2] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO2]‐driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO2] (iCO2) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre‐industrial times. Established theory, supported by experiments, indicates that iCO2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO2 responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2, albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.

Summary We analysed the responses of 11 ecosystem models to elevated atmospheric [CO2] (eCO2) at two temperate forest ecosystems (Duke and Oak Ridge National Laboratory (ORNL) Free‐Air CO2 Enrichment (FACE) experiments) to test alternative representations of carbon (C)–nitrogen (N) cycle processes. We decomposed the model responses into component processes affecting the response to eCO2 and confronted these with observations from the FACE experiments. Most of the models reproduced the observed initial enhancement of net primary production (NPP) at both sites, but none was able to simulate both the sustained 10‐yr enhancement at Duke and the declining response at ORNL: models generally showed signs of progressive N limitation as a result of lower than observed plant N uptake. Nonetheless, many models showed qualitative agreement with observed component processes. The results suggest that improved representation of above‐ground–below‐ground interactions and better constraints on plant stoichiometry are important for a predictive understanding of eCO2 effects. Improved accuracy of soil organic matter inventories is pivotal to reduce uncertainty in the observed C–N budgets. The two FACE experiments are insufficient to fully constrain terrestrial responses to eCO2, given the complexity of factors leading to the observed diverging trends, and the consequential inability of the models to explain these trends. Nevertheless, the ecosystem models were able to capture important features of the experiments, lending some support to their projections.

Nitrogen (N) is the primary growth‐limiting nutrient in many terrestrial ecosystems, and therefore plant production per unit N taken up (i.e., N use efficiency, NUE) is a fundamentally important component of ecosystem function. Nitrogen use efficiency comprises two components: N productivity (AN, plant production per peak biomass N content) and the mean residence time of N in plant biomass (MRTN). We utilized a five‐year fertilization experiment to examine the manner in which increases in N and phosphorus (P) availability affected plant NUE at multiple biological scales (i.e., from leaf to community level). We fertilized a natural gradient of nutrient‐limited peatland ecosystems in the Upper Peninsula of Michigan, USA, with 6 g N·m−2·yr−1, 2 g P·m−2·yr−1, or a combination of N and P. Our objectives were to determine how changes in carbon and N allocation within a plant to leaf and woody tissue and changes in species composition within a community, both above‐ and belowground, would affect (1) NUE; (2) the adaptive trade‐off between the components of NUE; (3) the efficiency with which plants acquired N from the soil (N uptake efficiency); and (4) plant community production per unit soil N availability (N response efficiency, NRE). As expected, N and P addition generally increased aboveground production and N uptake. In particular, P availability strongly affected the way in which plants took up and used N. Nitrogen use efficiency response to nutrient addition was not straightforward. Nitrogen use efficiency differed between leaf and woody tissue, among species, and across the ombrotrophic–minerotrophic gradient because plants and communities were adapted to maximize eitherANor MRTN, but not both concurrently. Increased N availability strongly decreased plant and community N uptake efficiency, while increased P availability increased N uptake efficiency, particularly in a nitrogen‐fixing shrub. Nitrogen uptake efficiency was more important in controlling overall plant community response to soil N availability than was NUE, and above‐ and belowground community N uptake efficiencies responded to nutrient addition in a similar manner. Our results demonstrate that plants respond to nutrient availability at multiple biological scales, and we suggest that N uptake efficiency may be a more representative measurement of plant responses to nutrient availability gradients than plant NUE.