A transition from arbuscular to ectomycorrhizal forests halts soil carbon sequestration during subtropical forest rewilding.

Ecological succession and restoration rapidly promote multiple dimensions of ecosystem functions and mitigate global climate change. However, the factors governing the limited capacity to sequester soil organic carbon (SOC) in old forests are poorly understood. Ecological theory predicts that plants and microorganisms jointly evolve into a more mutualistic relationship to accelerate detritus decomposition and nutrient regeneration in old than young forests, likely explaining the changes in C sinks across forest succession or rewilding. To test this hypothesis, we conducted a field experiment of root-mycorrhizal exclusion in successional subtropical forests to investigate plant-decomposer interactions and their effects on SOC sequestration. Our results showed that SOC accrual rate at the 0-10 cm soil layer was 1.26 mg g-1 yr-1 in early-successional arbuscular mycorrhizal (AM) forests, which was higher than that in the late-successional ectomycorrhizal (EcM) forests with non-significant change. A transition from early-successional AM to late-successional EcM forests increase fungal diversity, especially EcM fungi. In the late-successional forests, the presence of ectomycorrhizal hyphae promotes SOC decomposition and nutrient cycle by increasing soil nitrogen and phosphorus degrading enzyme activity as well as saprotrophic microbial richness. Across early- to late-successional forests, mycorrhizal priming effects on SOC decomposition explain a slow-down in the capacity of older forests to sequester soil C. Our findings suggest that a transition from AM to EcM forests supporting greater C decomposition can halt the capacity of forests to provide nature-based global climate change solutions.

Mycorrhizal associations relate to stable convergence in plant-microbial competition for nitrogen absorption under high nitrogen conditions.

Nitrogen (N) immobilization (Nim, including microbial N assimilation) and plant N uptake (PNU) are the two most important pathways of N retention in soils. The ratio of Nim to PNU (hereafter Nim:PNU ratio) generally reflects the degree of N limitation for plant growth in terrestrial ecosystems. However, the key factors driving the pattern of Nim:PNU ratio across global ecosystems remain unclear. Here, using a global data set of 1018 observations from 184 studies, we examined the relative importance of mycorrhizal associations, climate, plant, and soil properties on the Nim:PNU ratio across terrestrial ecosystems. Our results show that mycorrhizal fungi type (arbuscular mycorrhizal (AM) or ectomycorrhizal (EM) fungi) in combination with soil inorganic N mainly explain the global variation in the Nim:PNU ratio in terrestrial ecosystems. In AM fungi-associated ecosystems, the relationship between Nim and PNU displays a weaker negative correlation (r = -.06, p < .001), whereas there is a stronger positive correlation (r = .25, p < .001) in EM fungi-associated ecosystems. Our meta-analysis thus suggests that the AM-associated plants display a weak interaction with soil microorganisms for N absorption, while EM-associated plants cooperate with soil microorganisms. Furthermore, we find that the Nim:PNU ratio for both AM- and EM-associated ecosystems gradually converge around a stable value (13.8 ± 0.5 for AM- and 12.1 ± 1.2 for EM-associated ecosystems) under high soil inorganic N conditions. Our findings highlight the dependence of plant-microbial interaction for N absorption on both plant mycorrhizal association and soil inorganic N, with the stable convergence of the Nim:PNU ratio under high soil N conditions.

Global turnover of soil mineral-associated and particulate organic carbon.

Soil organic carbon (SOC) persistence is predominantly governed by mineral protection, consequently, soil mineral-associated (MAOC) and particulate organic carbon (POC) turnovers have different impacts on the vulnerability of SOC to climate change. Here, we generate the global MAOC and POC maps using 8341 observations and then infer the turnover times of MAOC and POC by a data-model integration approach. Global MAOC and POC storages are 975 964 987 Pg C (mean with 5% and 95% quantiles) and 330 323 337 Pg C, while global mean MAOC and POC turnover times are 129 45 383 yr and 23 5 82 yr in the top meter, respectively. Climate warming-induced acceleration of MAOC and POC decomposition is greater in subsoil than that in topsoil. Overall, the global atlas of MAOC and POC turnover, together with the global distributions of MAOC and POC stocks, provide a benchmark for Earth system models to diagnose SOC-climate change feedback.

Mycorrhizal mediation of soil carbon in permafrost regions depends on soil nutrient stoichiometry and physical protection.

Mycorrhizal associations are considered as one of the key drivers for soil carbon (C) accumulation and stability. However, how mycorrhizal associations influence soil organic C (SOC) and its fractions (i.e., particulate organic C [POC] and mineral-associated organic C [MAOC]) remain unclear. In this study, we examined effects of plant mycorrhizal associations with arbuscular mycorrhiza (AM), ectomycorrhiza (ECM), and their mixture (Mixed) on SOC and its fractions as well as soil stoichiometric ratios across 800-km transect in permafrost regions. Our results showed that soil with only ECM-associated trees had significantly higher SOC and POC compared to only AM-associated tree species, while soil in Mixed plots with both AM- and ECM- associated trees tend to be somewhat in the middle. Using structural equation models, we found that mycorrhizal association significantly influenced SOC and its fraction (i.e., POC, MAOC) indirectly through soil stoichiometric ratios (C:N, C:P, and N:P). These results suggest that selecting ECM tree species, characterized by a "slow cycling" nutrient uptake strategy, can effectively enhance accumulation of SOC and its fractions in permafrost forest ecosystems. Our findings provide novel insights for quantitatively assessing the influence of mycorrhiza-associated tree species on the management of soil C pool and biogeochemical cycling.

Plant biomass responses to elevated CO2 are mediated by phosphorus uptake.

Elevated atmospheric CO2 concentrations [CO2] potentially alter carbon (C) and phosphorus (P) cycles in terrestrial ecosystems. Although numerous field experiments and a few meta-analyses have been conducted, it is still largely unclear how the P cycle affects plant biomass responses under elevated [CO2] globally. Here, we conducted a global synthesis by analyzing 111 studies on the responses of above- and belowground P cycling to elevated [CO2], to examine how changes in the P cycle affect the plant biomass response to elevated [CO2]. Our results show that elevated [CO2] significantly increased plant aboveground biomass (+13 %), stem biomass (+4 %), leaf biomass (+11 %), belowground biomass (+12 %), and the root: shoot ratio (+7 %). Effects of elevated [CO2] on aboveground biomass, belowground biomass, and root: shoot ratio were best explained by plant P uptake. In addition, elevated [CO2]-induced changes in the aboveground P pool, leaf P pool, and leaf P concentration were modulated by ecological drivers, such as ΔCO2, experimental duration, and aridity index. Our findings highlight the importance of plant P uptake for both above- and belowground plant biomass responses under elevated [CO2], which should be considered in future biosphere models to improve predictions of terrestrial carbon-climate feedbacks.

Apparent thermal acclimation of soil heterotrophic respiration mainly mediated by substrate availability.

Multiple lines of existing evidence suggest that increasing CO2 emission from soils in response to rising temperature could accelerate global warming. However, in experimental studies, the initial positive response of soil heterotrophic respiration (RH ) to warming often weakens over time (referred to apparent thermal acclimation). If the decreased RH is driven by thermal adaptation of soil microbial community, the potential for soil carbon (C) losses would be reduced substantially. In the meanwhile, the response could equally be caused by substrate depletion, and would then reflect the gradual loss of soil C. To address uncertainties regarding the causes of apparent thermal acclimation, we carried out sterilization and inoculation experiments using the soil samples from an alpine meadow with 6 years of warming and nitrogen (N) addition. We demonstrate that substrate depletion, rather than microbial adaptation, determined the response of RH to long-term warming. Furthermore, N addition appeared to alleviate the apparent acclimation of RH to warming. Our study provides strong empirical support for substrate availability being the cause of the apparent acclimation of soil microbial respiration to temperature. Thus, these mechanistic insights could facilitate efforts of biogeochemical modeling to accurately project soil C stocks in the future climate.

Global systematic review with meta-analysis shows that warming effects on terrestrial plant biomass allocation are influenced by precipitation and mycorrhizal association.

Biomass allocation in plants is fundamental for understanding and predicting terrestrial carbon storage. Yet, our knowledge regarding warming effects on root: shoot ratio (R/S) remains limited. Here, we present a meta-analysis encompassing more than 300 studies and including angiosperms and gymnosperms as well as different biomes (cropland, desert, forest, grassland, tundra, and wetland). The meta-analysis shows that average warming of 2.50 °C (median = 2 °C) significantly increases biomass allocation to roots with a mean increase of 8.1% in R/S. Two factors associate significantly with this response to warming: mean annual precipitation and the type of mycorrhizal fungi associated with plants. Warming-induced allocation to roots is greater in drier habitats when compared to shoots (+15.1% in R/S), while lower in wetter habitats (+4.9% in R/S). This R/S pattern is more frequent in plants associated with arbuscular mycorrhizal fungi, compared to ectomycorrhizal fungi. These results show that precipitation variability and mycorrhizal association can affect terrestrial carbon dynamics by influencing biomass allocation strategies in a warmer world, suggesting that climate change could influence belowground C sequestration.

Temperature and Rainfall Patterns Constrain the Multidimensional Rewilding of Global Forests.

The long-term contribution of global forest restoration to support multiple dimensions of biodiversity and ecosystem function remains largely illusive across contrasting climates and forest types. This hampers the capacity to predict the future of forest rewilding under changing global climates. Here, 120 studies are synthesized across five continents, and it is found that forest restoration promotes multiple dimensions of biodiversity and ecosystem function such as soil fertility, plant biomass, microbial habitat, and carbon sequestration across contrasting climates and forest types. Based on global relationship between stand age and soil organic carbon stock, planting 350 million hectares of forest under the UN Bonn Challenge can sequester >30 Gt soil C in the surface 20 cm over the next century. However, these findings also indicate that predicted increases in temperature and reductions in precipitation can constrain the positive effects of forest rewilding on biodiversity and ecosystem function. Further, important tradeoffs are found in very old forests, with considerable disconnection between biodiversity and ecosystem function. Together, these findings provide evidence of the importance of the multidimensional rewilding of forests, suggesting that on-going climatic changes may dampen the expectations of the positive effects of forest restoration on biodiversity and ecosystem function.

Differential effects of nitrogen vs. phosphorus limitation on terrestrial carbon storage in two subtropical forests: A Bayesian approach.

Nitrogen (N) and phosphorus (P) have been demonstrated to limit terrestrial carbon (C) storage in terrestrial ecosystems. However, the reliable indicator to infer N and P limitation are still lacking, especially in subtropical forests. Here we used a terrestrial ecosystem (TECO) model framework in combination with a Bayesian approach to evaluate effects of nutrient limitation from added N/P processes and data sets on C storage capacities in two subtropical forests (Tiantong and Qianyanzhou [QYZ]). Three of the six simulation experiments were developed with assimilating data (TECO C model with C data [C-C], TECO C-N coupling model with C and N data [CN-CN], and TECO C-N-P model with C, N, and P data [CNP-CNP]), and the other three ones were simulated without assimilating data (C-only, CN-only, and CNP-only). We found that P dominantly constrained C storage capacities in Tiantong (42%) whereas N limitation decreased C storage projections in QYZ (44%). Our analysis indicated that the stoichiometry of wood biomass and soil microbe (e.g., N:P ratio) were more sensitive indicators of N or P limitation than that of other pools. Furthermore, effects of P-induced limitation were mainly on root biomass by additional P data and on both metabolic litter and soil organic carbon (SOC) by added P processes. N-induced effects were mainly from added N data that limited plant non-photosynthetic tissues (e.g., woody biomass and litter). The different effects of N and P modules on C storage projections reflected the diverse nutrient acquisition strategies associated with stand ages and plant species under nutrient stressed environment. These findings suggest that the interaction between plants and microorganisms regulate effects of nutrient availability on ecosystem C storage, and stoichiometric flexibility of N and P in plant and soil C pools could improve the representation of N and P limitation in terrestrial ecosystem models.

Long-term measurements in a mixed-grass prairie reveal a change in soil organic carbon recalcitrance and its environmental sensitivity under warming.

Soil respiration, the major pathway for ecosystem carbon (C) loss, has the potential to enter a positive feedback loop with the atmospheric CO2 due to climate warming. For reliable projections of climate-carbon feedbacks, accurate quantification of soil respiration and identification of mechanisms that control its variability are essential. Process-based models simulate soil respiration as functions of belowground C input, organic matter quality, and sensitivity to environmental conditions. However, evaluation and calibration of process-based models against the long-term in situ measurements are rare. Here, we evaluate the performance of the Terrestrial ECOsystem (TECO) model in simulating total and heterotrophic soil respiration measured during a 16-year warming experiment in a mixed-grass prairie; calibrate model parameters against these and other measurements collected during the experiment; and explore whether the mechanisms of C dynamics have changed over the years. Calibrating model parameters against observations of individual years substantially improved model performance in comparison to pre-calibration simulations, explaining 79-86% of variability in observed soil respiration. Interannual variation of the calibrated model parameters indicated increasing recalcitrance of soil C and changing environmental sensitivity of microbes. Overall, we found that (1) soil organic C became more recalcitrant in intact soil compared to root-free soil; (2) warming offset the effects of increasing C recalcitrance in intact soil and changed microbial sensitivity to moisture conditions. These findings indicate that soil respiration may decrease in the future due to C quality, but this decrease may be offset by warming-induced changes in C cycling mechanisms and their responses to moisture conditions.

Global variation of soil microbial carbon-use efficiency in relation to growth temperature and substrate supply.

Soil microbial carbon-use efficiency (CUE), which is defined as the ratio of growth over C uptake, is commonly assumed as a constant or estimated by a temperature-dependent function in current microbial-explicit soil carbon (C) models. The temperature-dependent function (i.e., CUE = CUE0 + m × (T - 20)) simulates the dynamic CUE based on the specific CUE at a given reference temperature (i.e., CUE0) and a temperature response coefficient (i.e., m). Here, based on 780 observations from 98 sites, we showed a divergent spatial distribution of the soil microbial CUE (0.5 ± 0.25; mean ± SD) at the global scale. Then, the key parameters CUE0 and m in the above equation were estimated as 0.475 and -0.016, respectively, based on the observations with the Markov chain Monte Carlo technique. We also found a strong dependence of microbial CUE on the type of C substrate. The multiple regression analysis showed that glucose influences the variation of measured CUE associated with the environmental factors. Overall, this study confirms the global divergence of soil microbial CUE and calls for the incorporation of C substrate beside temperature in estimating the microbial CUE in different biomes.

Matrix approach to land carbon cycle modeling: A case study with the Community Land Model.

The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically-resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standard CLM4.5 across different spatial-temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts of CO2 fertilization on litter and SOC dynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin-up, permit thorough parametric sensitivity tests, enable pool-based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective.