Arctic Soil Governs Whether Climate Change Drives Global Losses or Gains in Soil Carbon

Key uncertainties in terrestrial carbon cycle projections revolve around the timing, direction, and magnitude of the carbon cycle feedback to climate change. This is especially true in carbon-rich Arctic ecosystems, where permafrost soils contain roughly one third of the world's soil carbon stocks, which are likely vulnerable to loss. Using an ensemble of soil biogeochemical models that reflect recent changes in the conceptual understanding of factors responsible for soil carbon persistence, we quantify potential soil carbon responses under two representative climate change scenarios. Our results illustrate that models disagree on the sign and magnitude of global soil changes through 2100, with disagreements primarily driven by divergent responses of Arctic systems. These results largely reflect different assumptions about the nature of soil carbon persistence and vulnerabilities, underscoring the challenges associated with setting allowable greenhouse gas emission targets that will limit global warming to 1.5°C

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

Disentangling the Effects of Vapor Pressure Deficit and Soil Water Availability on Canopy Conductance in a Seasonal Tropical Forest During the 2015 El Niño Drought

Water deficit in the atmosphere and soil are two key interactive factors that constrain transpiration and vegetation productivity. It is not clear which of these two factors is more important for the water and carbon flux response to drought stress in ecosystems. In this study, field data and numerical modeling were used to isolate their impact on evapotranspiration (ET) and gross primary productivity (GPP) at a tropical forest site in Barro Colorado Island (BCI), Panama, focusing on their response to the drought induced by the El Niño event of 2015–2016. Numerical simulations were performed using a plant hydrodynamic scheme (HYDRO) and a heuristic approach that ignores stomatal sensitivity to leaf water potential in the Energy Exascale Earth System Model (E3SM) Land Model (ELM). The sensitivity of canopy conductance (Gs) to vapor pressure deficit (VPD) obtained from eddy-covariance fluxes and measured sap flux shows that, at both ecosystem and plant scale, soil water stress is more important in limiting Gs than VPD at BCI during the El Niño event. The model simulations confirmed the importance of water stress limitation on Gs, but overestimated the VPD impact on Gs compared to that estimated from the observations. We also found that the predicted soil moisture is less sensitive to the diversity of plant hydraulic traits than ET and GPP. During the dry season at BCI, seasonal ET, especially soil evaporation at VPD \u3e 0.42 kPa, simulated using HYDRO and ELM, were too strong and will require alternative parameterizations

Controls on terrestrial carbon feedbacks by productivity versus turnover in the CMIP5 Earth System Models

PublishedJournal Article© Author(s) 2015. To better understand sources of uncertainty in projections of terrestrial carbon cycle feedbacks, we present an approach to separate the controls on modeled carbon changes. We separate carbon changes into four categories using a linearized, equilibrium approach: those arising from changed inputs (productivity-driven changes), and outputs (turnover-driven changes), of both the live and dead carbon pools. Using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations for five models, we find that changes to the live pools are primarily explained by productivity-driven changes, with only one model showing large compensating changes to live carbon turnover times. For dead carbon pools, the situation is more complex as all models predict a large reduction in turnover times in response to increases in productivity. This response arises from the common representation of a broad spectrum of decomposition turnover times via a multi-pool approach, in which flux-weighted turnover times are faster than mass-weighted turnover times. This leads to a shift in the distribution of carbon among dead pools in response to changes in inputs, and therefore a transient but long-lived reduction in turnover times. Since this behavior, a reduction in inferred turnover times resulting from an increase in inputs, is superficially similar to priming processes, but occurring without the mechanisms responsible for priming, we call the phenomenon "false priming", and show that it masks much of the intrinsic changes to dead carbon turnover times as a result of changing climate. These patterns hold across the fully coupled, biogeochemically coupled, and radiatively coupled 1 % yr-1 increasing CO2 experiments. We disaggregate inter-model uncertainty in the globally integrated equilibrium carbon responses to initial turnover times, initial productivity, fractional changes in turnover, and fractional changes in productivity. For both the live and dead carbon pools, inter-model spread in carbon changes arising from initial conditions is dominated by model disagreement on turnover times, whereas inter-model spread in carbon changes from fractional changes to these terms is dominated by model disagreement on changes to productivity in response to both warming and CO2 fertilization. However, the lack of changing turnover time control on carbon responses, for both live and dead carbon pools, in response to the imposed forcings may arise from a common lack of process representation behind changing turnover times (e.g., allocation and mortality for live carbon; permafrost, microbial dynamics, and mineral stabilization for dead carbon), rather than a true estimate of the importance of these processes.This research was supported by the Director, Office of Science, Office of Biological and Environmental Research of the U.S. Department of Energy under Contract no. DE-AC02-05CH11231 as part of their Regional and Global Climate Modeling Program. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups listed in Table 1 for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. CDJ was supported by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101)

Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES)

Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's future climate. In the last decade, the vegetation component within ESMs has witnessed great progress from simple "big-leaf" approaches to demographically structured approaches, which have a better representation of plant size, canopy structure, and disturbances. These demographically structured vegetation models typically have a large number of input parameters, and sensitivity analysis is needed to quantify the impact of each parameter on the model outputs for a better understanding of model behavior. In this study, we conducted a comprehensive sensitivity analysis to diagnose the Community Land Model coupled to the Functionally Assembled Terrestrial Simulator, or CLM4.5(FATES). Specifically, we quantified the first- and second-order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks for a tropical site with an extent of 1×1°. While the photosynthetic capacity parameter (Vc;max25) is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which determine survival and growth strategies within the model. The parameter sensitivity changes with different sizes of trees and climate conditions. The results of this study highlight the importance of understanding the dynamics of the next generation of demographically enabled vegetation models within ESMs to improve model parameterization and structure for better model fidelity

The influence of soil communities on the temperature sensitivity of soil respiration

Soil respiration represents a major carbon flux between terrestrial ecosystems and the atmosphere, and is expected to accelerate under climate warming. Despite its importance in climate change forecasts, however, our understanding of the effects of temperature on soil respiration (RS) is incomplete. Using a metabolic ecology approach we link soil biota metabolism, community composition and heterotrophic activity, to predict RS rates across five biomes. We find that accounting for the ecological mechanisms underpinning decomposition processes predicts climatological RS variations observed in an independent dataset (n = 312). The importance of community composition is evident because without it RS is substantially underestimated. With increasing temperature, we predict a latitudinal increase in RS temperature sensitivity, with Q10 values ranging between 2.33 ±0.01 in tropical forests to 2.72 ±0.03 in tundra. This global trend has been widely observed, but has not previously been linked to soil communities

Decadal soil carbon accumulation across Tibetan permafrost regions

Acknowledgements We thank the members of Peking University Sampling Teams (2001–2004) and IBCAS Sampling Teams (2013–2014) for assistance in field data collection. We also thank the Forestry Bureau of Qinghai Province and the Forestry Bureau of Tibet Autonomous Region for their permission and assistance during the sampling process. This study was financially supported by the National Natural Science Foundation of China (31670482 and 31322011), National Basic Research Program of China on Global Change (2014CB954001 and 2015CB954201), Chinese Academy of Sciences-Peking University Pioneer Cooperation Team, and the Thousand Young Talents Program.Peer reviewedPostprintPostprin

The Effects of Carbon Dioxide Removal on the Carbon Cycle

Increasing atmospheric CO2 is having detrimental effects on the Earth system. Societies have recognized that anthropogenic CO2 release must be rapidly reduced to avoid potentially catastrophic impacts. Achieving this via emissions reductions alone will be very difficult. Carbon dioxide removal (CDR) has been suggested to complement and compensate for insufficient emissions reductions, through increasing natural carbon sinks, engineering new carbon sinks, or combining natural uptake with engineered storage. Here, we review the carbon cycle responses to different CDR approaches and highlight the often-overlooked interaction and feedbacks between carbon reservoirs that ultimately determines CDR efficacy. We also identify future research that will be needed if CDR is to play a role in climate change mitigation, these include coordinated studies to better understand (i) the underlying mechanisms of each method, (ii) how they could be explicitly simulated, (iii) how reversible changes in the climate and carbon cycle are, and (iv) how to evaluate and monitor CDR

Reconciling global-model estimates and country reporting of anthropogenic forest CO2 sinks

This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this recordData availability: The data that support the findings of this study are available from the corresponding author upon request.Achieving the long-term temperature goal of the Paris Agreement requires forest-based mitigation. Collective progress towards this goal will be assessed by the Paris Agreement’s Global stocktake. At present, there is a discrepancy of about 4 GtCO2yr−1in global anthropogenic net land-use emissions between global models (reflected in IPCC assessment reports) and aggregated national GHG inventories (under the UNFCCC). We show that a substantial part of this discrepancy (about 3.2 GtCO2yr−1) can be explained by conceptual differences in anthropogenic forest sink estimation, related to the representation of environmental change impacts and the areas considered as managed. For a more credible tracking of collective progress under the Global stocktake, these conceptual differences between models and inventories need to be reconciled. We implement a new method of disaggregation of global land model results that allows greater comparability with GHG inventories. This provides a deeper understanding of model–inventory differences, allowing more transparent analysis of forest-based mitigation and facilitating a more accurate Global stocktake.J.H. was supported by EU FP7 through project LUC4C (GA603542) and the UK NERC project GGRiLS-GAP. G.G. was supported by Administrative Arrangement Number 340203/2016/742550/SER/CLIMA.A3. A.K.J. was supported by the NSF (AGS 12-43071) and DOE (DE-SC0016323). J.E.M.S.N. was supported by the German Research Foundation’s Emmy Noether Programme (grant number PO1751/1-1). G.G., J.H., G.P.P. and L.P. received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 776810 (VERIFY). C.D.K. was supported by the US DOE under Contract DE-AC02-05CH11231 as part of their RGMA (BGC-Feedbacks SFA) and TES Programs (NGEE-Tropics). A.K.J. was supported under the US NSF (NSF-AGS-12-43071)

Weaker land–climate feedbacks from nutrient uptake during photosynthesis-inactive periods

Terrestrial carbon–climate feedbacks depend on two large and opposing fluxes—soil organic matter decomposition and photosynthesis—that are tightly regulated by nutrients . Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 represented nutrient dynamics poorly , rendering predictions of twenty-first century carbon–climate feedbacks highly uncertain. Here, we use a new land model to quantify the effects of observed plant nutrient uptake mechanisms missing in most other ESMs. In particular, we estimate the global role of root nutrient competition with microbes and abiotic processes during periods without photosynthesis. Nitrogen and phosphorus uptake during these periods account for 45 and 43%, respectively, of annual uptake, with large latitudinal variation. Globally, night-time nutrient uptake dominates this signal. Simulations show that ignoring this plant uptake, as is done when applying an instantaneous relative demand approach, leads to large positive biases in annual nitrogen leaching (96%) and N O emissions (44%). This N O emission bias has a GWP equivalent of ~2.4 PgCO yr , which is substantial compared to the current terrestrial CO sink. Such large biases will lead to predictions of overly open terrestrial nutrient cycles and lower carbon sequestration capacity. Both factors imply over-prediction of positive terrestrial feedbacks with climate in current ESMs. 1,2 1,3 −1 2 2 2