An observation-based constraint on permafrost loss as a function of global warming

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordPermafrost, which covers 15 million km 2 of the land surface, is one of the components of the Earth system that is most sensitive to warming. Loss of permafrost would radically change high-latitude hydrology and biogeochemical cycling, and could therefore provide very significant feedbacks on climate change. The latest climate models all predict warming of high-latitude soils and thus thawing of permafrost under future climate change, but with widely varying magnitudes of permafrost thaw. Here we show that in each of the models, their present-day spatial distribution of permafrost and air temperature can be used to infer the sensitivity of permafrost to future global warming. Using the same approach for the observed permafrost distribution and air temperature, we estimate a sensitivity of permafrost area loss to global mean warming at stabilization of million km 2 °C â '1 (1σ confidence), which is around 20% higher than previous studies. Our method facilitates an assessment for COP21 climate change targets: if the climate is stabilized at 2 °C above pre-industrial levels, we estimate that the permafrost area would eventually be reduced by over 40%. Stabilizing at 1.5 °C rather than 2 °C would save approximately 2 million km 2 of permafrost.European Union Seventh Framework ProgrammeNatural Environment Research Council (NERC)Swedish Research CouncilResearch Council of NorwayUK DECC/Defra Met Office HadleyEuropean Unio

Temperature effects on carbon storage are controlled by soil stabilisation capacities

This is the final version. Available on open access from Nature Research via the DOI in this recordData 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 CouncilEuropean Union Horizon 202

Simulating increased permafrost peatland plant productivity in response to belowground fertilisation using the JULES land surface model

This is the final version. Available from MDPI via the DOI in this record. Data Availability Statement: Abisko meteorological data and snow depth data are available on request from the Abisko Scientific Research Station (https://polar.se/en/research-in-abisko) (last access: 17 April 2022), and the soil temperature data are archived in the GTN-P database (https: //gtnp.arcticportal.org/) (last access: 17 April 2022). Soil carbon profiles are available from the following Zenodo repository: https://zenodo.org/record/5818180#.YmmBftrMKUk (last access: 17 April 2022).Several experimental studies have shown that climate-warming-induced permafrost thaw releases previously unavailable nitrogen which can lower nitrogen limitation, increase plant productivity, and counteract some of the carbon released from thawing permafrost. The net effect of this belowground fertilisation effect remains debated and is yet to be included in Earth System models. Here, we included the impact of thaw-related nitrogen fertilisation on vegetation in the Joint UK Land Environment Simulator (JULES) land surface model for the first time. We evaluated its ability to replicate a three-year belowground fertilisation experiment in which JULES was generally able to simulate belowground fertilisation in accordance with the observations. We also ran simulations under future climate to investigate how belowground nitrogen fertilisation affects the carbon cycle. These simulations indicate an increase in plant-available inorganic nitrogen at the thaw front by the end of the century with only the productivity of deep-rooting plants increasing in response. This suggests that deep-rooting species will have a competitive advantage under future climate warming. Our results also illustrate the capacity to simulate belowground nitrogen fertilisation at the thaw front in a global land surface model, leading towards a more complete representation of coupled carbon and nitrogen dynamics in the northern high latitudes.European Union’s Horizon 2020e Joint UK BEIS/Defra Met Office Hadley Centre Climate ProgrammeNatural Environment Research Council (NERC

Simulated responses of soil carbon to climate change in CMIP6 Earth system models: the role of false priming

This is the final version. Available from Copernicus Publications / European Geosciences Union via the DOI in this record. The CMIP data analysed during this study are available online: CMIP6 (https://esgf-node.llnl.gov/search/cmip6/, last access: 8 April 2022) and CMIP5 (https://esgf-node.llnl.gov/search/cmip5/, last access: 12 April 2022).Code is available on GitHub (https://github.com/rebeccamayvarney/CMIP6_dCs, last access: 28 July 2023).Reliable estimates of soil carbon change are required to determine the carbon budgets consistent with the Paris Agreement climate targets. This study evaluates projections of soil carbon during the 21st century in Coupled Model Intercomparison Project Phase 6 (CMIP6) Earth system models (ESMs) under a range of atmospheric composition scenarios. In general, we find a reduced spread of changes in global soil carbon (ΔCs) in CMIP6 compared to the previous CMIP5 model generation. However, similar reductions were not seen in the derived contributions to ΔCs due to both increases in plant net primary productivity (NPP, named ΔCs,NPP) and reductions in the effective soil carbon turnover time (τs, named ΔCs,τ). Instead, we find a strong relationship across the CMIP6 models between these NPP and τs components of ΔCs, with more positive values of ΔCs,NPP being correlated with more negative values of ΔCs,τ. We show that the concept of “false priming” is likely to be contributing to this emergent relationship, which leads to a decrease in the effective soil carbon turnover time as a direct result of NPP increase and occurs when the rate of increase in NPP is relatively fast compared to the slower timescales of a multi-pool soil carbon model. This finding suggests that the structure of soil carbon models within ESMs in CMIP6 has likely contributed towards the reduction in the overall model spread in future soil carbon projections since CMIP5.European Union’s Horizon 2020European Union’s Horizon 202

A spatial emergent constraint on the sensitivity of soil carbon turnover to global warming (article)

This is the final version. Available on open access from Nature Research via the DOI in this recordData 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 in 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. An approximation to the latter term for the top one metre of soil (ΔCs,τ) can be diagnosed from projections made with the CMIP6 and CMIP5 Earth System Models (ESMs), and is found to span a large range even at 2 °C of global warming (-196 ± 117 PgC). Here, we present a constraint on ΔCs,τ, which makes use of current heterotrophic respiration and the spatial variability of τs inferred from observations. This spatial emergent constraint allows us to halve the uncertainty in ΔCs,τ at 2 °C to -232 ± 52 PgC

Carbon budget for 1.5 and 2oC targets lowered by natural wetland and permafrost feedbacks

Methane emissions from natural wetlands and carbon release from permafrost thaw have a positive feedback on climate, yet are not represented in most state-of-the-art climate models. Furthermore, a fraction of the thawed permafrost carbon is released as methane, enhancing the combined feedback strength. We present simulations with an intermediate complexity climate model which follow prescribed global warming pathways to stabilisation at 1.5°C or 2.0°C above pre-industrial levels by the year 2100, and that incorporates a state-of-the-art global land surface model with updated descriptions of wetland and permafrost carbon release. We demonstrate that the climate feedbacks from those two processes are substantial. Specifically, permissible anthropogenic fossil fuel CO2 emission budgets are reduced by 17-23% (47-56 GtC) for stabilisation at 1.5°C, and 9-13% (52-57 GtC) for 2.0°C stabilisation. In our simulations these feedback processes respond faster at temperatures below 1.5°C, and the differences between the 1.5°C and 2°C targets are disproportionately small. This key finding is due to our interest in transient emission pathways to the year 2100 and does not consider the longer term implications of these feedback processes. We conclude that natural feedback processes from wetlands and permafrost must be considered in assessments of transient emission pathways to limit global warming

Simulating carbon accumulation and loss in the central Congo peatlands

Peatlands of the central Congo Basin have accumulated carbon over millennia. They currently store some 29 billion tonnes of carbon in peat. However, our understanding of the controls on peat carbon accumulation and loss and the vulnerability of this stored carbon to climate change is in its infancy. Here we present a new model of tropical peatland development, DigiBog_Congo, that we use to simulate peat carbon accumulation and loss in a rain-fed interfluvial peatland that began forming ~20,000 calendar years Before Present (cal. yr BP, where ‘present’ is 1950 CE). Overall, the simulated age-depth curve is in good agreement with palaeoenvironmental reconstructions derived from a peat core at the same location as our model simulation. We find two key controls on long-term peat accumulation: water at the peat surface (surface wetness) and the very slow anoxic decay of recalcitrant material. Our main simulation shows that between the Late Glacial and early Holocene there were several multidecadal periods where net peat and carbon gain alternated with net loss. Later, a climatic dry phase beginning ~5200 cal. yr BP caused the peatland to become a long-term carbon source from ~3975 to 900 cal. yr BP. Peat as old as ~7000 cal. yr BP was decomposed before the peatland's surface became wetter again, suggesting that changes in rainfall alone were sufficient to cause a catastrophic loss of peat carbon lasting thousands of years. During this time, 6.4 m of the column of peat was lost, resulting in 57% of the simulated carbon stock being released. Our study provides an approach to understanding the future impact of climate change and potential land-use change on this vulnerable store of carbon

Towards a microbial process-based understanding of the resilience of peatland ecosystem service provisioning – a research agenda

Peatlands are wetland ecosystems with great significance as natural habitats and as major global carbon stores. They have been subject to widespread exploitation and degradation with resulting losses in characteristic biota and ecosystem functions such as climate regulation. More recently, large-scale programmes have been established to restore peatland ecosystems and the various services they provide to society. Despite significant progress in peatland science and restoration practice, we lack a process-based understanding of how soil microbiota influence peatland functioning and mediate the resilience and recovery of ecosystem services, to perturbations associated with land use and climate change. We argue that there is a need to: in the short-term, characterise peatland microbial communities across a range of spatial and temporal scales and develop an improved understanding of the links between peatland habitat, ecological functions and microbial processes; in the medium term, define what a successfully restored ’target’ peatland microbiome looks like for key carbon cycle related ecosystem services and develop microbial-based monitoring tools for assessing restoration needs; and in the longer term, to use this knowledge to influence restoration practices and assess progress on the trajectory towards ‘intact’ peatland status. Rapid advances in genetic characterisation of the structure and functions of microbial communities offer the potential for transformative progress in these areas, but the scale and speed of methodological and conceptual advances in studying ecosystem functions is a challenge for peatland scientists. Advances in this area require multidisciplinary collaborations between peatland scientists, data scientists and microbiologists and ultimately, collaboration with the modelling community. Developing a process-based understanding of the resilience and recovery of peatlands to perturbations, such as climate extremes, fires, and drainage, will be key to meeting climate targets and delivering ecosystem services cost effectively

New insights in the relation between climate and slope failures at high-elevation sites

Climate change is now unequivocal; however, the type and extent of terrestrial impacts are still widely debated. Among these, the effects on slope stability are receiving a growing attention in recent years, both as terrestrial indicators of climate change and implications for hazard assessment. High-elevation areas are particularly suitable for these studies, because of the presence of the cryosphere, which is particularly sensitive to climate. In this paper, we analyze 358 slope failures which occurred in the Italian Alps in the period 2000–2016, at an elevation above 1500 m a.s.l. We use a statistical-based method to detect climate anomalies associated with the occurrence of slope failures, with the aim to catch an eventual climate signal in the preparation and/or triggering of the considered case studies. We first analyze the probability values assumed by 25 climate variables on the occasion of a slope-failure occurrence. We then perform a dimensionality reduction procedure and come out with a set of four most significant and representative climate variables, in particular heavy precipitation and short-term high temperature. Our study highlights that slope failures occur in association with one or more climate anomalies in almost 92% of our case studies. One or more temperature anomalies are detected in association with most case studies, in combination or not with precipitation (47% and 38%, respectively). Summer events prevail, and an increasing role of positive temperature anomalies from spring to winter, and with elevation and failure size, emerges. While not providing a final evidence of the role of climate warming on slope instability increase at high elevation in recent years, the results of our study strengthen this hypothesis, calling for more extensive and in-depth studies on the subject