Globally, root production accounts for 33–67% of terrestrial net primary productivity and influences decomposition via root production and turnover, carbon (C) allocation to mycorrhizal fungi and ...root exudation. As recognized above ground, the timing of phenological events affects terrestrial C balance, yet there is no parallel understanding for below‐ground phenology. In this paper we examine the phenology of root production and its relationship to temperature, soil moisture, and above‐ground phenology. Synthesizing 87 observations of whole‐plant phenology from 40 studies, we found that, on average, root growth occurs 25 ± 8 d after shoot growth but that the offset between the peak in root and shoot growth varies > 200 d across biomes (boreal, temperate, Mediterranean, and subtropical). Root and shoot growth are positively correlated with median monthly temperature and mean monthly precipitation in boreal, temperate, and subtropical biomes. However, a temperature hysteresis in these biomes leads to the hypothesis that internal controls over C allocation to roots are an equally, if not more, important driver of phenology. The specific mechanisms are as yet unclear but they are likely mediated by some combination of photoassimilate supply, hormonal signaling, and growth form.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Abstract
Soil is the largest terrestrial reservoir of organic carbon and is central for climate change mitigation and carbon-climate feedbacks. Chemical and physical associations of soil carbon with ...minerals play a critical role in carbon storage, but the amount and global capacity for storage in this form remain unquantified. Here, we produce spatially-resolved global estimates of mineral-associated organic carbon stocks and carbon-storage capacity by analyzing 1144 globally-distributed soil profiles. We show that current stocks total 899 Pg C to a depth of 1 m in non-permafrost mineral soils. Although this constitutes 66% and 70% of soil carbon in surface and deeper layers, respectively, it is only 42% and 21% of the mineralogical capacity. Regions under agricultural management and deeper soil layers show the largest undersaturation of mineral-associated carbon. Critically, the degree of undersaturation indicates sequestration efficiency over years to decades. We show that, across 103 carbon-accrual measurements spanning management interventions globally, soils furthest from their mineralogical capacity are more effective at accruing carbon; sequestration rates average 3-times higher in soils at one tenth of their capacity compared to soils at one half of their capacity. Our findings provide insights into the world’s soils, their capacity to store carbon, and priority regions and actions for soil carbon management.
While there is an emerging view that roots and their associated microbes actively alter resource availability and soil organic matter (SOM) decomposition, the ecosystem consequences of such ...rhizosphere effects have rarely been quantified. Using a meta‐analysis, we show that multiple indices of microbially mediated C and nitrogen (N) cycling, including SOM decomposition, are significantly enhanced in the rhizospheres of diverse vegetation types. Then, using a numerical model that combines rhizosphere effect sizes with fine root morphology and depth distributions, we show that root‐accelerated mineralization and priming can account for up to one‐third of the total C and N mineralized in temperate forest soils. Finally, using a stoichiometrically constrained microbial decomposition model, we show that these effects can be induced by relatively modest fluxes of root‐derived C, on the order of 4% and 6% of gross and net primary production, respectively. Collectively, our results indicate that rhizosphere processes are a widespread, quantitatively important driver of SOM decomposition and nutrient release at the ecosystem scale, with potential consequences for global C stocks and vegetation feedbacks to climate.
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Climatic, atmospheric, and land-use changes all have the potential to alter soil microbial activity, mediated by changes in plant inputs. Many microbial models of soil organic carbon (SOC) ...decomposition have been proposed recently to advance prediction of climate and carbon (C) feedbacks. Most of these models, however, exhibit unrealistic oscillatory behavior and SOC insensitivity to long-term changes in C inputs. Here we diagnose the source of these problems in four archetypal models and propose a density-dependent formulation of microbial turnover, motivated by community-level interactions, that limits population sizes and reduces oscillations. We compare model predictions to 24 long-term C-input field manipulations and identify key benchmarks. The proposed formulation reproduces soil C responses to long-term C-input changes and implies greater SOC storage associated with CO
-fertilization-driven increases in C inputs over the coming century compared to recent microbial models. This study provides a simple modification to improve microbial models for inclusion in Earth System Models.
First‐order organic matter decomposition models are used within most Earth System Models (ESMs) to project future global carbon cycling; these models have been criticized for not accurately ...representing mechanisms of soil organic carbon (SOC) stabilization and SOC response to climate change. New soil biogeochemical models have been developed, but their evaluation is limited to observations from laboratory incubations or few field experiments. Given the global scope of ESMs, a comprehensive evaluation of such models is essential using in situ observations of a wide range of SOC stocks over large spatial scales before their introduction to ESMs. In this study, we collected a set of in situ observations of SOC, litterfall and soil properties from 206 sites covering different forest and soil types in Europe and China. These data were used to calibrate the model MIMICS (The MIcrobial‐MIneral Carbon Stabilization model), which we compared to the widely used first‐order model CENTURY. We show that, compared to CENTURY, MIMICS more accurately estimates forest SOC concentrations and the sensitivities of SOC to variation in soil temperature, clay content and litter input. The ratios of microbial biomass to total SOC predicted by MIMICS agree well with independent observations from globally distributed forest sites. By testing different hypotheses regarding (using alternative process representations) the physicochemical constraints on SOC deprotection and microbial turnover in MIMICS, the errors of simulated SOC concentrations across sites were further decreased. We show that MIMICS can resolve the dominant mechanisms of SOC decomposition and stabilization and that it can be a reliable tool for predictions of terrestrial SOC dynamics under future climate change. It also allows us to evaluate at large scale the rapidly evolving understanding of SOC formation and stabilization based on laboratory and limited filed observation.
Microbial explicit decomposition models have been developed to replace the conventional first‐order model used in most Earth System Models, but their evaluation was limited to observations from laboratory incubations or few field experiments. A comprehensive evaluation of these models is essential using large‐scale in situ observations. We found that, compared to first‐order decomposition model, microbial explicit model more accurately estimates SOC concentrations, microbe/SOC ratio, SOC composition and the sensitivities of SOC stock to changed climate, litter input and soil properties. We support to replace the first‐order decomposition model used in existing Earth System Models with microbial explicit model.
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Soil carbon (C) models are used to predict C sequestration responses to climate and land use change. Yet, the soil models embedded in Earth system models typically do not represent processes that ...reflect our current understanding of soil C cycling, such as microbial decomposition, mineral association, and aggregation. Rather, they rely on conceptual pools with turnover times that are fit to bulk C stocks and/or fluxes. As measurements of soil fractions become increasingly available, it is necessary for soil C models to represent these measurable quantities so that model processes can be evaluated more accurately. Here we present Version 2 (V2) of the Millennial model, a soil model developed to simulate C pools that can be measured by extraction or fractionation, including particulate organic C, mineral-associated organic C, aggregate C, microbial biomass, and low molecular weight C. Model processes have been updated to reflect the current understanding of mineral-association, temperature sensitivity and reaction kinetics, and different model structures were tested within an open-source framework. We evaluated the ability of Millennial V2 to simulate total soil organic C (SOC), as well as the mineral-associated and particulate fractions, using three independent data sets of soil fractionation measurements spanning a range of climate and geochemistry in Australia (N = 495), Europe (N = 175), and across the globe (N = 659). When using all the data together (N = 1329), the Millennial V2 model predicted SOC (RMSE = 3.3 kg C m−2, AIC = 675, Rin2 = 0.31, Rout2 = 0.26) better than the widely-used first-order decomposition model Century (RMSE = 3.4 kg C m−2, AIC = 696, Rin2 = 0.21, Rout2 = 0.18) across sites, despite the fact that Millennial V2 has an increase in process complexity and number of parameters compared to Century. Millennial V2 also reproduced the observed fraction of C in MAOM and larger particle size fractions for most latitudes and biomes, and allows for a more detailed understanding of the pools and processes that affect model performance. It is important to note that this study evaluates the spatial variation in C stock only, and that the temporal dynamics of Millennial V2 remain to be tested. The Millennial V2 model updates the conceptual Century model pools and processes and represents our current understanding of the roles that microbial activity, mineral association and aggregation play in soil C sequestration.
•The Millennial Version 2 model was developed to predict measurable soil C pools.•The model was evaluated at 1329 globally-distributed sites.•Millennial V2 predicted SOC stocks and fractions better than the Century model.•The model also predicted new sites better than a machine learning model.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
There is growing interest in enhancing soil carbon sequestration (SCS) as a climate mitigation strategy, including neutralizing atmospheric emissions from fossil‐fuel combustion through the ...development of soil carbon offset markets. Several studies have focused on refining estimates of the magnitude of potential SCS or on developing methods for soil carbon quantification in markets. We call on scientists and policy makers to resist assimilating soils into carbon offset markets due to not only fundamental flaws in the logic of these markets to reach climate neutrality but also environmental justice concerns. Here, we first highlight how carbon offset markets rely on an inappropriate substitution of inert fossil carbon with dynamic stocks of soil carbon. We then note the failure of these markets to account for intersecting anthropogenic perturbations to the carbon cycle, including the soil carbon debt and ongoing agricultural emissions. Next, we invite scientists to consider soil functions beyond productivity and profitability. Finally, we describe and support historical opposition to offset markets by environmental justice advocates. We encourage scientists to consider how their research and communications can promote diverse soil functions and just climate‐change mitigation.
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8.
The Millennial model Abramoff, Rose; Xu, Xiaofeng; Hartman, Melannie ...
Biogeochemistry,
01/2018, Volume:
137, Issue:
1/2
Journal Article
Peer reviewed
Open access
Soil organic carbon (SOC) can be defined by measurable chemical and physical pools, such as mineral-associated carbon, carbon physically entrapped in aggregates, dissolved carbon, and fragments of ...plant detritus. Yet, most soil models use conceptual rather than measurable SOC pools. What would the traditional pool-based soil model look like if it were built today, reflecting the latest understanding of biological, chemical, and physical transformations in soils? We propose a conceptual model—the Millennial model—that defines pools as measurable entities. First, we discuss relevant pool definitions conceptually and in terms of the measurements that can be used to quantify pool size, formation, and destabilization. Then, we develop a numerical model following the Millennial model conceptual framework to evaluate against the Century model, a widely-used standard for estimating SOC stocks across space and through time. The Millennial model predicts qualitatively similar changes in total SOC in response to single factor perturbations when compared to Century, but different responses to multiple factor perturbations. We review important conceptual and behavioral differences between the Millennial and Century modeling approaches, and the field and lab measurements needed to constrain parameter values. We propose the Millennial model as a simple but comprehensive framework to model SOC pools and guide measurements for further model development.
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BFBNIB, DOBA, EMUNI, FZAB, GEOZS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NMLJ, NUK, OBVAL, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Vegetation is a key component in the global carbon cycle as it stores ~450 GtC as biomass, and removes about a third of anthropogenic CO2 emissions. However, in some regions, the rate of plant carbon ...uptake is beginning to slow, largely because of water stress. Here, we develop a new observation‐based methodology to diagnose vegetation water stress and link it to environmental drivers. We used the ratio of remotely sensed land surface to near surface atmospheric temperatures (LST/Tair) to represent vegetation water stress, and built regression tree models (random forests) to assess the relationship between LST/Tair and the main environmental drivers of surface energy fluxes in the tropical Americas. We further determined ecosystem traits associated with water stress and surface energy partitioning, pinpointed critical thresholds for water stress, and quantified changes in ecosystem carbon uptake associated with crossing these critical thresholds. We found that the top drivers of LST/Tair, explaining over a quarter of its local variability in the study region, are (1) radiation, in 58% of the study region; (2) water supply from precipitation, in 30% of the study region; and (3) atmospheric water demand from vapor pressure deficits (VPD), in 22% of the study region. Regions in which LST/Tair variation is driven by radiation are located in regions of high aboveground biomass or at high elevations, while regions in which LST/Tair is driven by water supply from precipitation or atmospheric demand tend to have low species richness. Carbon uptake by photosynthesis can be reduced by up to 80% in water‐limited regions when critical thresholds for precipitation and air dryness are exceeded simultaneously, that is, as compound events. Our results demonstrate that vegetation structure and diversity can be important for regulating surface energy and carbon fluxes over tropical regions.
We developed a new methodology to improve our understanding of vegetation water stress, based on remotely sensed land surface and near surface atmospheric temperatures and applied it in the tropical Americas. We showed where radiation, atmospheric dryness, and precipitation control variations of water stress, pinpointed critical thresholds for water stress, and quantified reductions in ecosystem carbon uptake associated with crossing these critical thresholds. We found that carbon uptake by gross primary production can be reduced by up to 80% from water stress, and demonstrate that vegetation structure and diversity can be important for regulating surface energy and carbon fluxes.
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