Climate-dependent responses of root and shoot biomass to drought duration and intensity in grasslands-a meta-analysis

Understanding the effects of altered precipitation regimes on root biomass in grasslands is crucial for predicting grassland responses to climate change. Nonetheless, studies investigating the effects of drought on belowground vegetation have produced mixed results. In particular, root biomass under reduced precipitation may increase, decrease or show a delayed response compared to shoot biomass, highlighting a knowledge gap in the relationship between belowground net primary production and drought. To address this gap, we conducted a meta-analysis of nearly 100 field observations of grassland root and shoot biomass changes under experimental rainfall reduction to disentangle the main drivers behind grassland responses to drought. Using a response-ratio approach we tested the hypothesis that water scarcity would induce a decrease in total biomass, but an increase in belowground biomass allocation with increased drought length and intensity, and that climate (as defined by the aridity index of the study location) would be an additional predictor. As expected, meteorological drought decreased root and shoot biomass, but aboveground and belowground biomass exhibited contrasting responses to drought duration and intensity, and their interaction with climate. In particular, drought duration had negative effects on root biomass only in wet climates while more intense drought had negative effects on root biomass only in dry climates. Shoot biomass responded negatively to drought duration regardless of climate. These results show that long-term climate is an important modulator of belowground vegetation responses to drought, which might be a consequence of different drought tolerance and adaptation strategies. This variability in vegetation responses to drought suggests that physiological plasticity and community composition shifts may mediate how climate affects carbon allocation in grasslands, and thus ultimately carbon storage in soil.

Vegetation, topography and soil depth drive microbial community structure in two Swedish grasslands

Soil microbial diversity and community composition are shaped by various factors linked to land management, topographic position, and vegetation. To study the effects of these drivers, we characterized fungal and bacterial communities from bulk soil at four soil depths ranging from the surface to below the rooting zone of two Swedish grasslands with differing land-use history, each including both an upper and a lower catenary position. We hypothesized that differences in plant species richness and plant functional group composition between the four study sites would drive the variation in soil microbial community composition and correlate with microbial diversity, and that microbial biomass and diversity would decrease with soil depth following a decline in resource availability. While vegetation was identified as the main driver of microbial community composition, the explained variation was significantly higher for bacteria than for fungi, and the communities differed more between grasslands than between catenary positions. Microbial biomass derived from DNA abundance decreased with depth but diversity remained relatively stable, indicating diverse microbial communities even below the rooting zone. Finally, plant-microbial diversity correlations were significant only for specific plant and fungal functional groups, emphasizing the importance of functional interactions over general species richness.

Microbial carbon use efficiency promotes global soil carbon storage

Soils store more carbon than other terrestrial ecosystems1,2. How soil organic carbon (SOC) forms and persists remains uncertain1,3, which makes it challenging to understand how it will respond to climatic change3,4. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss5-7. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways4,6,8-11, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes12,13. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved7,14,15. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.

Tradeoffs and synergies in wetland multifunctionality: A scaling issue

Wetland area in agricultural landscapes has been heavily reduced to gain land for crop production, but in recent years there is increased societal recognition of the negative consequences from wetland loss on nutrient retention, biodiversity and a range of other benefits to humans. The current trend is therefore to re-establish wetlands, often with an aim to achieve the simultaneous delivery of multiple ecosystem services, i.e., multifunctionality. Here we review the literature on key objectives used to motivate wetland re-establishment in temperate agricultural landscapes (provision of flow regulation, nutrient retention, climate mitigation, biodiversity conservation and cultural ecosystem services), and their relationships to environmental properties, in order to identify potential for tradeoffs and synergies concerning the development of multifunctional wetlands. Through this process, we find that there is a need for a change in scale from a focus on single wetlands to wetlandscapes (multiple neighboring wetlands including their catchments and surrounding landscape features) if multiple societal and environmental goals are to be achieved. Finally, we discuss the key factors to be considered when planning for re-establishment of wetlands that can support achievement of a wide range of objectives at the landscape scale.

Extensive global wetland loss over the past three centuries

Wetlands have long been drained for human use, thereby strongly affecting greenhouse gas fluxes, flood control, nutrient cycling and biodiversity^1,2. Nevertheless, the global extent of natural wetland loss remains remarkably uncertain³. Here, we reconstruct the spatial distribution and timing of wetland loss through conversion to seven human land uses between 1700 and 2020, by combining national and subnational records of drainage and conversion with land-use maps and simulated wetland extents. We estimate that 3.4 million km² (confidence interval 2.9-3.8) of inland wetlands have been lost since 1700, primarily for conversion to croplands. This net loss of 21% (confidence interval 16-23%) of global wetland area is lower than that suggested previously by extrapolations of data disproportionately from high-loss regions. Wetland loss has been concentrated in Europe, the United States and China, and rapidly expanded during the mid-twentieth century. Our reconstruction elucidates the timing and land-use drivers of global wetland losses, providing an improved historical baseline to guide assessment of wetland loss impact on Earth system processes, conservation planning to protect remaining wetlands and prioritization of sites for wetland restoration⁴.

Anthropogenic emission is the main contributor to the rise of atmospheric methane during 1993–2017

Atmospheric methane (CH₄) concentrations have shown a puzzling resumption in growth since 2007 following a period of stabilization from 2000 to 2006. Multiple hypotheses have been proposed to explain the temporal variations in CH₄ growth, and attribute the rise of atmospheric CH₄ either to increases in emissions from fossil fuel activities, agriculture and natural wetlands, or to a decrease in the atmospheric chemical sink. Here, we use a comprehensive ensemble of CH₄ source estimates and isotopic δ¹³C-CH₄ source signature data to show that the resumption of CH₄ growth is most likely due to increased anthropogenic emissions. Our emission scenarios that have the fewest biases with respect to isotopic composition suggest that the agriculture, landfill and waste sectors were responsible for 53 ± 13% of the renewed growth over the period 2007–2017 compared to 2000–2006; industrial fossil fuel sources explained an additional 34 ± 24%, and wetland sources contributed the least at 13 ± 9%. The hypothesis that a large increase in emissions from natural wetlands drove the decrease in atmospheric δ¹³C-CH₄ values cannot be reconciled with current process-based wetland CH₄ models. This finding suggests the need for increased wetland measurements to better understand the contemporary and future role of wetlands in the rise of atmospheric methane and climate feedback. Our findings highlight the predominant role of anthropogenic activities in driving the growth of atmospheric CH₄ concentrations.

Permafrost Thaw Increases Methylmercury Formation in Subarctic Fennoscandia

Methylmercury (MeHg) forms in anoxic environments and can bioaccumulate and biomagnify in aquatic food webs to concentrations of concern for human and wildlife health. Mercury (Hg) pollution in the Arctic environment may worsen as these areas warm and Hg, currently locked in permafrost soils, is remobilized. One of the main concerns is the development of Hg methylation hotspots in the terrestrial environment due to thermokarst formation. The extent to which net methylation of Hg is enhanced upon thaw is, however, largely unknown. Here, we have studied the formation of Hg methylation hotspots using existing thaw gradients at five Fennoscandian permafrost peatland sites. Total Hg (HgT) and MeHg concentrations were analyzed in 178 soil samples from 14 peat cores. We observed 10 times higher concentrations of MeHg and 13 times higher %MeHg in the collapse fen (representing thawed conditions) as compared to the peat plateau (representing frozen conditions). This suggests significantly greater net methylation of Hg when thermokarst wetlands are formed. In addition, we report HgT to soil organic carbon ratios representative of Fennoscandian permafrost peatlands (median and interquartile range of 0.09 ± 0.07 μg HgT g^-1 C) that are of value for future estimates of circumpolar HgT stocks.

Microbiome structure and functional potential in permafrost soils of the Western Canadian Arctic

Substantial amounts of topsoil organic matter (OM) in Arctic Cryosols have been translocated by the process of cryoturbation into deeper soil horizons (cryoOM), reducing its decomposition. Recent Arctic warming deepens the Cryosols´ active layer, making more topsoil and cryoOM carbon accessible for microbial transformation. To quantify bacteria, archaea and selected microbial groups (methanogens - mcrA gene and diazotrophs - nifH gene) and to investigate bacterial and archaeal diversity, we collected 83 soil samples from four different soil horizons of three distinct tundra types located in Qikiqtaruk (Hershel Island, Western Canada). In general, the abundance of bacteria and diazotrophs decreased from topsoil to permafrost, but not for cryoOM. No such difference was observed for archaea and methanogens. CryoOM was enriched with oligotrophic (slow-growing microorganism) taxa capable of recalcitrant OM degradation. We found distinct microbial patterns in each tundra type: topsoil from wet-polygonal tundra had the lowest abundance of bacteria and diazotrophs, but the highest abundance of methanogens. Wet-polygonal tundra, therefore, represented a hotspot for methanogenesis. Oligotrophic and copiotrophic (fast-growing microorganism) genera of methanogens and diazotrophs were distinctly distributed in topsoil and cryoOM, resulting in different rates of nitrogen flux into these horizons affecting OM vulnerability and potential CO2 and CH4 release.

Spatial heterogeneity and environmental predictors of permafrost region soil organic carbon stocks

Large stocks of soil organic carbon (SOC) have accumulated in the Northern Hemisphere permafrost region, but their current amounts and future fate remain uncertain. By analyzing dataset combining >2700 soil profiles with environmental variables in a geospatial framework, we generated spatially explicit estimates of permafrost-region SOC stocks, quantified spatial heterogeneity, and identified key environmental predictors. We estimated that Pg C are stored in the top 3 m of permafrost region soils. The greatest uncertainties occurred in circumpolar toe-slope positions and in flat areas of the Tibetan region. We found that soil wetness index and elevation are the dominant topographic controllers and surface air temperature (circumpolar region) and precipitation (Tibetan region) are significant climatic controllers of SOC stocks. Our results provide first high-resolution geospatial assessment of permafrost region SOC stocks and their relationships with environmental factors, which are crucial for modeling the response of permafrost affected soils to changing climate.

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

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 (τ_s) with warming. An approximation to the latter term for the top one metre of soil (ΔC_s,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 ΔC_s,τ, which makes use of current heterotrophic respiration and the spatial variability of τ_s inferred from observations. This spatial emergent constraint allows us to halve the uncertainty in ΔC_s,τ at 2 °C to -232 ± 52 PgC.

Deep Learning Optimizes Data-Driven Representation of Soil Organic Carbon in Earth System Model Over the Conterminous United States

Soil organic carbon (SOC) is a key component of the global carbon cycle, yet it is not well-represented in Earth system models to accurately predict global carbon dynamics in response to climate change. This novel study integrated deep learning, data assimilation, 25,444 vertical soil profiles, and the Community Land Model version 5 (CLM5) to optimize the model representation of SOC over the conterminous United States. We firstly constrained parameters in CLM5 using observations of vertical profiles of SOC in both a batch mode (using all individual soil layers in one batch) and at individual sites (site-by-site). The estimated parameter values from the site-by-site data assimilation were then either randomly sampled (random-sampling) to generate continentally homogeneous (constant) parameter values or maximally preserved for their spatially heterogeneous distributions (varying parameter values to match the spatial patterns from the site-by-site data assimilation) so as to optimize spatial representation of SOC in CLM5 through a deep learning technique (neural networking) over the conterminous United States. Comparing modeled spatial distributions of SOC by CLM5 to observations yielded increasing predictive accuracy from default CLM5 settings (R ² = 0.32) to randomly sampled (0.36), one-batch estimated (0.43), and deep learning optimized (0.62) parameter values. While CLM5 with parameter values derived from random-sampling and one-batch methods substantially corrected the overestimated SOC storage by that with default model parameters, there were still considerable geographical biases. CLM5 with the spatially heterogeneous parameter values optimized from the neural networking method had the least estimation error and less geographical biases across the conterminous United States. Our study indicated that deep learning in combination with data assimilation can significantly improve the representation of SOC by complex land biogeochemical models.

Controls of soil organic matter on soil thermal dynamics in the northern high latitudes

Permafrost warming and potential soil carbon (SOC) release after thawing may amplify climate change, yet model estimates of present-day and future permafrost extent vary widely, partly due to uncertainties in simulated soil temperature. Here, we derive thermal diffusivity, a key parameter in the soil thermal regime, from depth-specific measurements of monthly soil temperature at about 200 sites in the high latitude regions. We find that, among the tested soil properties including SOC, soil texture, bulk density, and soil moisture, SOC is the dominant factor controlling the variability of diffusivity among sites. Analysis of the CMIP5 model outputs reveals that the parameterization of thermal diffusivity drives the differences in simulated present-day permafrost extent among these models. The strong SOC-thermics coupling is crucial for projecting future permafrost dynamics, since the response of soil temperature and permafrost area to a rising air temperature would be impacted by potential changes in SOC.

Soils in the northern permafrost region contain large quantities of organic carbon, formed over long time scales under cold climates. Here the authors test a number of soil properties and show that soil organic carbon is the dominant factor controlling thermal diffusivity among 200 sites in high latitude regions.

Approaching the potential of model-data comparisons of global land carbon storage

Carbon storage dynamics in vegetation and soil are determined by the balance of carbon influx and turnover. Estimates of these opposing fluxes differ markedly among different empirical datasets and models leading to uncertainty and divergent trends. To trace the origin of such discrepancies through time and across major biomes and climatic regions, we used a model-data fusion framework. The framework emulates carbon cycling and its component processes in a global dynamic ecosystem model, LPJ-GUESS, and preserves the model-simulated pools and fluxes in space and time. Thus, it allows us to replace simulated carbon influx and turnover with estimates derived from empirical data, bringing together the strength of the model in representing processes, with the richness of observational data informing the estimations. The resulting vegetation and soil carbon storage and global land carbon fluxes were compared to independent empirical datasets. Results show model-data agreement comparable to, or even better than, the agreement between independent empirical datasets. This suggests that only marginal improvement in land carbon cycle simulations can be gained from comparisons of models with current-generation datasets on vegetation and soil carbon. Consequently, we recommend that model skill should be assessed relative to reference data uncertainty in future model evaluation studies.

Tundra landscape heterogeneity, not interannual variability, controls the decadal regional carbon balance in the Western Russian Arctic

Across the Arctic, the net ecosystem carbon (C) balance of tundra ecosystems is highly uncertain due to substantial temporal variability of C fluxes and to landscape heterogeneity. We modeled both carbon dioxide (CO₂ ) and methane (CH₄ ) fluxes for the dominant land cover types in a ~100-km² sub-Arctic tundra region in northeast European Russia for the period of 2006-2015 using process-based biogeochemical models. Modeled net annual CO₂ fluxes ranged from -300 g C m^-2  year^-1 [net uptake] in a willow fen to 3 g C m^-2  year^-1 [net source] in dry lichen tundra. Modeled annual CH₄ emissions ranged from -0.2 to 22.3 g C m^-2  year^-1 at a peat plateau site and a willow fen site, respectively. Interannual variability over the decade was relatively small (20%-25%) in comparison with variability among the land cover types (150%). Using high-resolution land cover classification, the region was a net sink of atmospheric CO₂ across most land cover types but a net source of CH₄ to the atmosphere due to high emissions from permafrost-free fens. Using a lower resolution for land cover classification resulted in a 20%-65% underestimation of regional CH₄ flux relative to high-resolution classification and smaller (10%) overestimation of regional CO₂ uptake due to the underestimation of wetland area by 60%. The relative fraction of uplands versus wetlands was key to determining the net regional C balance at this and other Arctic tundra sites because wetlands were hot spots for C cycling in Arctic tundra ecosystems.

Networking our science to characterize the state, vulnerabilities, and management opportunities of soil organic matter

Soil organic matter (SOM) supports the Earth's ability to sustain terrestrial ecosystems, provide food and fiber, and retains the largest pool of actively cycling carbon. Over 75% of the soil organic carbon (SOC) in the top meter of soil is directly affected by human land use. Large land areas have lost SOC as a result of land use practices, yet there are compensatory opportunities to enhance productivity and SOC storage in degraded lands through improved management practices. Large areas with and without intentional management are also being subjected to rapid changes in climate, making many SOC stocks vulnerable to losses by decomposition or disturbance. In order to quantify potential SOC losses or sequestration at field, regional, and global scales, measurements for detecting changes in SOC are needed. Such measurements and soil-management best practices should be based on well established and emerging scientific understanding of processes of C stabilization and destabilization over various timescales, soil types, and spatial scales. As newly engaged members of the International Soil Carbon Network, we have identified gaps in data, modeling, and communication that underscore the need for an open, shared network to frame and guide the study of SOM and SOC and their management for sustained production and climate regulation.

Circumpolar distribution and carbon storage of thermokarst landscapes

Thermokarst is the process whereby the thawing of ice-rich permafrost ground causes land subsidence, resulting in development of distinctive landforms. Accelerated thermokarst due to climate change will damage infrastructure, but also impact hydrology, ecology and biogeochemistry. Here, we present a circumpolar assessment of the distribution of thermokarst landscapes, defined as landscapes comprised of current thermokarst landforms and areas susceptible to future thermokarst development. At 3.6 × 106 km2, thermokarst landscapes are estimated to cover ∼20% of the northern permafrost region, with approximately equal contributions from three landscape types where characteristic wetland, lake and hillslope thermokarst landforms occur. We estimate that approximately half of the below-ground organic carbon within the study region is stored in thermokarst landscapes. Our results highlight the importance of explicitly considering thermokarst when assessing impacts of climate change, including future landscape greenhouse gas emissions, and provide a means for assessing such impacts at the circumpolar scale.

Plant-derived compounds stimulate the decomposition of organic matter in arctic permafrost soils

Arctic ecosystems are warming rapidly, which is expected to promote soil organic matter (SOM) decomposition. In addition to the direct warming effect, decomposition can also be indirectly stimulated via increased plant productivity and plant-soil C allocation, and this so called “priming effect” might significantly alter the ecosystem C balance. In this study, we provide first mechanistic insights into the susceptibility of SOM decomposition in arctic permafrost soils to priming. By comparing 119 soils from four locations across the Siberian Arctic that cover all horizons of active layer and upper permafrost, we found that an increased availability of plant-derived organic C particularly stimulated decomposition in subsoil horizons where most of the arctic soil carbon is located. Considering the 1,035 Pg of arctic soil carbon, such an additional stimulation of decomposition beyond the direct temperature effect can accelerate net ecosystem C losses, and amplify the positive feedback to global warming.

A simplified, data-constrained approach to estimate the permafrost carbon-climate feedback

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation-Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2-33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9-112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of -14 to -19 Pg C °C(-1) on a 100 year time scale. For CH4 emissions, our approach assumes a fixed saturated area and that increases in CH4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10-18%. The simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.