Suchergebnisse

This is the final version. Available on open access from Nature Research via the DOI in this record ; Data availability: All data used in this manuscript are fully open access and available. The soil data were obtained from a published snapshot derived from the World Soil Information database (https://doi.org/10.17027/isric-wdcsoils.20160003), the long-term climate data are available in the WorldClim version 2.0 database (http://worldclim.org), while the MODIS primary productivity, evapotranspiration, and landcover data are available in the MOD17A3 (https://doi.org/10.5067/MODIS/MOD17A3.006), MOD16A2 (https://doi.org/10.5067/MODIS/MOD16A2.006) and MCD12Q1 (https://doi.org/10.5067/MODIS/MCD12Q1.006) databases respectively. The UKESM data from the sixth coupled model intercomparison project (CMIP6) is available in the public data archive (https://data.ceda.ac.uk/badc/cmip6/data/CMIP6/CMIP/MOHC/UKESM1-0-LL). ; Physical and chemical stabilisation mechanisms are now known to play a critical role in controlling carbon (C) storage in mineral soils, leading to suggestions that climate warming-induced C losses may be lower than previously predicted. By analysing > 9,000 soil profiles, here we show that, overall, C storage declines strongly with mean annual temperature. However, the reduction in C storage with temperature was more than three times greater in coarse-textured soils, with limited capacities for stabilising organic matter, than in fine-textured soils with greater stabilisation capacities. This pattern was observed independently in cool and warm regions, and after accounting for potentially confounding factors (plant productivity, precipitation, aridity, cation exchange capacity, and pH). The results could not, however, be represented by an established Earth system model (ESM). We conclude that warming will promote substantial soil C losses, but ESMs may not be predicting these losses accurately or which stocks are most vulnerable. ; Natural Environment Research Council (NERC) ; Swedish Research Council ; European Union Horizon 2020

This is the final version. Available on open access via the DOI in this record ; Data availability: The datasets analysed during this study are available online: CMIP5 model output [https://esgf-node.llnl.gov/search/cmip5/], CMIP6 model output [https://esgf-node.llnl.gov/search/cmip6/], The WFDEI Meteorological Forcing Data [https://rda.ucar.edu/datasets/ds314.2/], CARDAMOM Heterotrophic Respiration [https://datashare.is.ed.ac.uk/handle/10283/875], MODIS Net Primary Production [https://lpdaac.usgs.gov/products/mod17a3v055/], Raich et al. 2002 Soil Respiration [https://cdiac.ess-dive.lbl.gov/epubs/ndp/ndp081/ndp081.html], Hashimoto et al. 2015 Heterotrophic Respiration [http://cse.ffpri.affrc.go.jp/shojih/data/index.html], and the datasets for observational Soil Carbon [https://github.com/rebeccamayvarney/soiltau_ec]. ; Code availability: The Python code used to complete the analysis and produce the figures in this study is available in the following online repository [https://github.com/rebeccamayvarney/soiltau_ec]. ; Carbon cycle feedbacks represent large uncertainties on climate change projections, and the response of soil carbon to climate change contributes the greatest uncertainty to this. Future changes in soil carbon depend on changes in litter and root inputs from plants, and especially on reductions in the turnover time of soil carbon (τs) with warming. The latter represents the change in soil carbon due to the response of soil turnover time (∆Cs,τ), and can be diagnosed from projections made with Earth System Models (ESMs). It is found to span a large range even at the Paris Agreement Target of 2◦C global warming. We use the spatial variability of τs inferred from observations to obtain a constraint on ∆Cs,τ . This spatial emergent constraint allows us to greatly reduce the uncertainty in ∆Cs,τ at 2◦C global warming. We do likewise for other levels of global warming to derive a best estimate for the effective sensitivity of τs to global warming, and derive a q10 equivalent value for heterotrophic respiration. ; European Research Council (ERC) ; Natural Environment Research Council (NERC) ; European Union Horizon 2020 ; Met Office Hadley Centre Climate Programme

This is the final version. Available on open access from the National Academy of Sciences via the DOI in this record ; Data Availability. The results and peat core data are summarized in Datasets S1–S6. Maps of predicted peatland extent, peat depth, and peat C and N storage (10-km pixels) are archived and freely available for download at https://bolin.su.se/data/hugelius-2020 ; Northern peatlands have accumulated large stocks of organic carbon (C) and nitrogen (N), but their spatial distribution and vulnerability to climate warming remain uncertain. Here, we used machine-learning techniques with extensive peat core data (n > 7,000) to create observation-based maps of northern peatland C and N stocks, and to assess their response to warming and permafrost thaw. We estimate that northern peatlands cover 3.7 ± 0.5 million km2 and store 415 ± 150 Pg C and 10 ± 7 Pg N. Nearly half of the peatland area and peat C stocks are permafrost affected. Using modeled global warming stabilization scenarios (from 1.5 to 6 °C warming), we project that the current sink of atmospheric C (0.10 ± 0.02 Pg C⋅y-1) in northern peatlands will shift to a C source as 0.8 to 1.9 million km2 of permafrost-affected peatlands thaw. The projected thaw would cause peatland greenhouse gas emissions equal to ∼1% of anthropogenic radiative forcing in this century. The main forcing is from methane emissions (0.7 to 3 Pg cumulative CH4-C) with smaller carbon dioxide forcing (1 to 2 Pg CO2-C) and minor nitrous oxide losses. We project that initial CO2-C losses reverse after ∼200 y, as warming strengthens peatland C-sinks. We project substantial, but highly uncertain, additional losses of peat into fluvial systems of 10 to 30 Pg C and 0.4 to 0.9 Pg N. The combined gaseous and fluvial peatland C loss estimated here adds 30 to 50% onto previous estimates of permafrost-thaw C losses, with southern permafrost regions being the most vulnerable. ; Swedish Research Council ; European Union ; European Union Horizon 2020 ; Gordon and Betty and Gordon Moore Foundation ; Natural Environment Research Council (NERC) ; National Science Foundation ; National Natural Science Foundation of China