Enhanced silicate weathering accelerates forest carbon sequestration by stimulating the soil mineral carbon pump.

Enhanced silicate rock weathering (ERW) is an emerging strategy for carbon dioxide removal (CDR) from the atmosphere to mitigate anthropogenic climate change. ERW aims at promoting soil inorganic carbon sequestration by accelerating geochemical weathering processes. Theoretically, ERW may also impact soil organic carbon (SOC), the largest carbon pool in terrestrial ecosystems, but experimental evidence for this is largely lacking. Here, we conducted a 2-year field experiment in tropical rubber plantations in the southeast of China to evaluate the effects of wollastonite powder additions (0, 0.25, and 0.5 kg m-2) on both soil organic and inorganic carbon at 0-10 cm depth. We found that ERW significantly increased the concentration of SOC and HCO3 -, but the increases in SOC were four and eight times higher than that of HCO3 - with low- and high-level wollastonite applications. ERW had positive effects on the accrual of organic carbon in mineral-associated organic matter (MAOM) and macroaggregate fractions, but not on particulate organic matter. Path analysis suggested that ERW increased MAOM mainly by increasing the release of Ca, Si, and Fe, and to a lesser extent by stimulating root growth and microbial-derived carbon inputs. Our study indicates that ERW with wollastonite can promote SOC sequestration in stable MOAM in surface soils through both the soil mineral carbon pump and microbial carbon pump. These effects may have been larger than the inorganic CDR during our experiment. We argue it is essential to account for the responses of SOC in the assessments of CDR by ERW.

Carbon-phosphorus cycle models overestimate CO2 enrichment response in a mature Eucalyptus forest.

The importance of phosphorus (P) in regulating ecosystem responses to climate change has fostered P-cycle implementation in land surface models, but their CO2 effects predictions have not been evaluated against measurements. Here, we perform a data-driven model evaluation where simulations of eight widely used P-enabled models were confronted with observations from a long-term free-air CO2 enrichment experiment in a mature, P-limited Eucalyptus forest. We show that most models predicted the correct sign and magnitude of the CO2 effect on ecosystem carbon (C) sequestration, but they generally overestimated the effects on plant C uptake and growth. We identify leaf-to-canopy scaling of photosynthesis, plant tissue stoichiometry, plant belowground C allocation, and the subsequent consequences for plant-microbial interaction as key areas in which models of ecosystem C-P interaction can be improved. Together, this data-model intercomparison reveals data-driven insights into the performance and functionality of P-enabled models and adds to the existing evidence that the global CO2-driven carbon sink is overestimated by models.

Global critical soil moisture thresholds of plant water stress.

During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.

Enhanced rock weathering increased soil phosphorus availability and altered root phosphorus-acquisition strategies.

Enhanced rock weathering (ERW) has been proposed as a measure to enhance the carbon (C)-sequestration potential and fertility of soils. The effects of this practice on the soil phosphorus (P) pools and the general mechanisms affecting microbial P cycling, as well as plant P uptake are not well understood. Here, the impact of ERW on soil P availability and microbial P cycling functional groups and root P-acquisition traits were explored through a 2-year wollastonite field addition experiment in a tropical rubber plantation. The results show that ERW significantly increased soil microbial carbon-use efficiency and total P concentrations and indirectly increased soil P availability by enhancing organic P mobilization and mineralization of rhizosheath carboxylates and phosphatase, respectively. Also, ERW stimulated the activities of P-solubilizing (gcd, ppa and ppx) and mineralizing enzymes (phoADN and phnAPHLFXIM), thus contributing to the inorganic P solubilization and organic P mineralization. Accompanying the increase in soil P availability, the P-acquisition strategy of the rubber fine roots changed from do-it-yourself acquisition by roots to dependence on mycorrhizal collaboration and the release of root exudates. In addition, the direct effects of ERW on root P-acquisition traits (such as root diameter, specific root length, and mycorrhizal colonization rate) may also be related to changes in the pattern of belowground carbon investments in plants. Our study provides a new insight that ERW increases carbon-sequestration potential and P availability in tropical forests and profoundly affects belowground plant resource-use strategies.

Size, distribution, and vulnerability of the global soil inorganic carbon.

Global estimates of the size, distribution, and vulnerability of soil inorganic carbon (SIC) remain largely unquantified. By compiling 223,593 field-based measurements and developing machine-learning models, we report that global soils store 2305 ± 636 (±1 SD) billion tonnes of carbon as SIC over the top 2-meter depth. Under future scenarios, soil acidification associated with nitrogen additions to terrestrial ecosystems will reduce global SIC (0.3 meters) up to 23 billion tonnes of carbon over the next 30 years, with India and China being the most affected. Our synthesis of present-day land-water carbon inventories and inland-water carbonate chemistry reveals that at least 1.13 ± 0.33 billion tonnes of inorganic carbon is lost to inland-waters through soils annually, resulting in large but overlooked impacts on atmospheric and hydrospheric carbon dynamics.

A global dataset on phosphorus in agricultural soils.

Numerous drivers such as farming practices, erosion, land-use change, and soil biogeochemical background, determine the global spatial distribution of phosphorus (P) in agricultural soils. Here, we revised an approach published earlier (called here GPASOIL-v0), in which several global datasets describing these drivers were combined with a process model for soil P dynamics to reconstruct the past and current distribution of P in cropland and grassland soils. The objective of the present update, called GPASOIL-v1, is to incorporate recent advances in process understanding about soil inorganic P dynamics, in datasets to describe the different drivers, and in regional soil P measurements for benchmarking. We trace the impact of the update on the reconstructed soil P. After the update we estimate a global averaged inorganic labile P of 187 kgP ha-1 for cropland and 91 kgP ha-1 for grassland in 2018 for the top 0-0.3 m soil layer, but these values are sensitive to the mineralization rates chosen for the organic P pools. Uncertainty in the driver estimates lead to coefficients of variation of 0.22 and 0.54 for cropland and grassland, respectively. This work makes the methods for simulating the agricultural soil P maps more transparent and reproducible than previous estimates, and increases the confidence in the new estimates, while the evaluation against regional dataset still suggests rooms for further improvement.