Sulman, Benjamin N., Elena Shevliakova, E R Brzostek, S N Kivlin, and Sergey Malyshev, et al., April 2019: Diverse mycorrhizal associations enhance terrestrial C storage in a global model. Global Biogeochemical Cycles, 33(4), DOI:10.1029/2018GB005973. Abstract
Accurate projections of the terrestrial carbon (C) sink are critical to understanding the future global C cycle and setting CO2 emission reduction goals. Current earth system models (ESMs) and dynamic global vegetation models (DGVMs) with coupled carbon‐nitrogen cycles project that future terrestrial C sequestration will be limited by nitrogen (N) availability, but the magnitude of N limitation remains a critical uncertainty. Plants use multiple symbiotic nutrient acquisition strategies to mitigate N limitation, but current DGVMs omit these mechanisms. Fully coupling N‐acquiring plant‐microbe symbioses to soil organic matter (SOM) cycling within a DGVM for the first time, we show that increases in N acquisition via SOM decomposition and atmospheric N2 fixation could support long‐term enhancement of terrestrial C sequestration at global scales under elevated CO2. The model reproduced elevated CO2 responses from two experiments (Duke and Oak Ridge) representing contrasting N acquisition strategies. N release from enhanced SOM decomposition supported vegetation growth at Duke, while inorganic N depletion limited growth at Oak Ridge. Global simulations reproduced spatial patterns of N‐acquiring symbioses from a novel niche‐based map of mycorrhizal fungi. Under a 100 ppm increase in CO2 concentrations, shifts in N acquisition pathways facilitated 200 Pg C of terrestrial C sequestration over 100 years compared to 50 Pg C for a scenario with static N acquisition pathways. Our results suggest that N acquisition strategies are important determinants of terrestrial C sequestration potential under elevated CO2, and that nitrogen‐enabled DGVMs that omit symbiotic N acquisition may underestimate future terrestrial C uptake.
The continual growth in the availability, detail, and wealth of environmental data provides an invaluable asset to improve the characterization of land heterogeneity in Earth System models – a persistent challenge in macroscale models. However, due to the nature of these data (volume and complexity) and the computational constraints of macroscale models, until now these data have been underutilized for global applications. As a proof of concept, this study explores over a 1/4 degree (~ 25 km) grid cell in southeastern California how to effectively and efficiently harness these data in Earth System models. First, a novel hierarchical multivariate clustering approach (HMC) is used to summarize the high dimensional environmental data space into hydrologically interconnected representative clusters (i.e., tiles). These tiles and their associated properties are then used to parameterize the sub-grid heterogeneity of the Geophysical Fluid Dynamics Laboratory (GFDL) LM4-HB land model. To assess how this data-driven approach to assemble the model tiles impacts the simulated water, energy, and carbon cycles, model experiments are run using a series of different tile configurations assembled by HMC. The results over the 1/4 degree macroscale grid cell and the underlying 30-meter fine-scale grid in southeastern California show that: 1) the observed similarity over the landscape makes it possible to robustly account for the role of multi-scale heterogeneity in the macroscale states and fluxes with around 300 sub-grid land model tiles; 2) assembling the sub-grid tiles from observed data, at times, leads to noticeable differences in the macroscale water, energy, and carbon cycles; for example, explicit subsurface interactions between the tiles leads to a dampening of macroscale extremes; 3) connecting the fine-scale grid to the model tiles via HMC enables circumventing the classic scale discrepancies between the macroscale and field-scale estimates; this has potentially significant implications for the evaluation and application of Earth System models.
Sulman, Benjamin N., et al., November 2018: Multiple models and experiments underscore large uncertainty in soil carbon dynamics. Biogeochemistry, 141(2), DOI:10.1007/s10533-018-0509-z. Abstract
Soils contain more carbon than plants or the atmosphere, and sensitivities of soil organic carbon (SOC) stocks to changing climate and plant productivity are a major uncertainty in global carbon cycle projections. Despite a consensus that microbial degradation and mineral stabilization processes control SOC cycling, no systematic synthesis of long-term warming and litter addition experiments has been used to test process-based microbe-mineral SOC models. We explored SOC responses to warming and increased carbon inputs using a synthesis of 147 field manipulation experiments and five SOC models with different representations of microbial and mineral processes. Model projections diverged but encompassed a similar range of variability as the experimental results. Experimental measurements were insufficient to eliminate or validate individual model outcomes. While all models projected that CO2 efflux would increase and SOC stocks would decline under warming, nearly one-third of experiments observed decreases in CO2 flux and nearly half of experiments observed increases in SOC stocks under warming. Long-term measurements of C inputs to soil and their changes under warming are needed to reconcile modeled and observed patterns. Measurements separating the responses of mineral-protected and unprotected SOC fractions in manipulation experiments are needed to address key uncertainties in microbial degradation and mineral stabilization mechanisms. Integrating models with experimental design will allow targeting of these uncertainties and help to reconcile divergence among models to produce more confident projections of SOC responses to global changes.
Wieder, W R., M D Hartman, and Benjamin N Sulman, et al., April 2018: Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models. Global Change Biology, 24(4), DOI:10.1111/gcb.13979. Abstract
Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first‐order, microbial implicit approach (CASA‐CNP), and two recently developed microbially explicit models that can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0–100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single‐forcing experiments with changed inputs, temperature, and moisture suggest that uncertainty associated with freeze‐thaw processes as well as soil textural effects on soil carbon stabilization were larger than direct temperature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. By providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about factors regulating the turnover of soil organic matter.
Sulman, Benjamin N., E R Brzostek, C Medici, and Elena Shevliakova, et al., August 2017: Feedbacks between plant N demand and rhizosphere priming depend on type of mycorrhizal association. Ecology Letters, 20(8), DOI:10.1111/ele.12802. Abstract
Ecosystem carbon (C) balance is hypothesised to be sensitive to the mycorrhizal strategies that plants use to acquire nutrients. To test this idea, we coupled an optimality-based plant nitrogen (N) acquisition model with a microbe-focused soil organic matter (SOM) model. The model accurately predicted rhizosphere processes and C–N dynamics across a gradient of stands varying in their relative abundance of arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) trees. When mycorrhizal dominance was switched – ECM trees dominating plots previously occupied by AM trees, and vice versa – legacy effects were apparent, with consequences for both C and N stocks in soil. Under elevated productivity, ECM trees enhanced decomposition more than AM trees via microbial priming of unprotected SOM. Collectively, our results show that ecosystem responses to global change may hinge on the balance between rhizosphere priming and SOM protection, and highlight the importance of dynamically linking plants and microbes in terrestrial biosphere models.
Sulman, Benjamin N., et al., September 2016: High atmospheric demand for water can limit forest carbon uptake and transpiration as severely as dry soil. Geophysical Research Letters, 43(18), DOI:10.1002/2016GL069416. Abstract
When stressed by low soil water content (SWC) or high vapor pressure deficit (VPD), plants close stomata, reducing transpiration and photosynthesis. However, it has historically been difficult to disentangle the magnitudes of VPD compared to SWC limitations on ecosystem-scale fluxes. We used a thirteen-year record of eddy covariance measurements from a forest in south-central Indiana, USA to quantify how transpiration and photosynthesis respond to fluctuations in VPD vs. SWC. High VPD and low SWC both explained reductions in photosynthesis relative to its long-term mean, as well as reductions in transpiration relative to potential transpiration estimated with the Penman-Monteith equation. Flux responses to typical fluctuations in SWC and VPD had similar magnitudes. Integrated over the year, VPD fluctuations accounted for significant reductions of GPP in both non-drought and drought years. Our results suggest that increasing VPD under climatic warming could reduce forest CO2 uptake regardless of changes in SWC.
Sulman, Benjamin N., R P Phillips, A Christopher Oishi, Elena Shevliakova, and Stephen W Pacala, December 2014: Microbe-driven turnover offsets mineral-mediated storage of soil carbon under elevated CO2. Nature Climate Change, 4(12), DOI:10.1038/nclimate2436. Abstract
The sensitivity of soil organic carbon (SOC) to changing environmental conditions represents a critical uncertainty in coupled carbon cycle–climate models1. Much of this uncertainty arises from our limited understanding of the extent to which root–microbe interactions induce SOC losses (through accelerated decomposition or ‘priming’2) or indirectly promote SOC gains (via ‘protection’ through interactions with mineral particles3, 4). We developed a new SOC model to examine priming and protection responses to rising atmospheric CO2. The model captured disparate SOC responses at two temperate free-air CO2 enrichment (FACE) experiments. We show that stabilization of ‘new’ carbon in protected SOC pools may equal or exceed microbial priming of ‘old’ SOC in ecosystems with readily decomposable litter and high clay content (for example, Oak Ridge5). In contrast, carbon losses induced through priming dominate the net SOC response in ecosystems with more resistant litters and lower clay content (for example, Duke6). The SOC model was fully integrated into a global terrestrial carbon cycle model to run global simulations of elevated CO2 effects. Although protected carbon provides an important constraint on priming effects, priming nonetheless reduced SOC storage in the majority of terrestrial areas, partially counterbalancing SOC gains from enhanced ecosystem productivity.
