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1. Scientific Communities Striving for a Common Cause: Innovations in Carbon Cycle Science

   https://doi.org/10.1175/BAMS-D-19-0306.1  

   Whelan, Mary E. ; Anderegg, Leander D. ; Badgley, Grayson ; Campbell, J. Elliott ; Commane, Roisin ; Frankenberg, Christian ; Hilton, Timothy W. ; Kuai, Le ; Parazoo, Nicholas ; Shiga, Yoichi ; et al ( September 2020 , Bulletin of the American Meteorological Society)

   Abstract Where does the carbon released by burning fossil fuels go? Currently, ocean and land systems remove about half of the CO 2 emitted by human activities; the remainder stays in the atmosphere. These removal processes are sensitive to feedbacks in the energy, carbon, and water cycles that will change in the future. Observing how much carbon is taken up on land through photosynthesis is complicated because carbon is simultaneously respired by plants, animals, and microbes. Global observations from satellites and air samples suggest that natural ecosystems take up about as much CO 2 as they emit. To match the data, our land models generate imaginary Earths where carbon uptake and respiration are roughly balanced, but the absolute quantities of carbon being exchanged vary widely. Getting the magnitude of the flux is essential to make sure our models are capturing the right pattern for the right reasons. Combining two cutting-edge tools, carbonyl sulfide (OCS) and solar-induced fluorescence (SIF), will help develop an independent answer of how much carbon is being taken up by global ecosystems. Photosynthesis requires CO 2 , light, and water. OCS provides a spatially and temporally integrated picture of the “front door” of photosynthesis, proportional to CO 2 uptake and water loss through plant stomata. SIF provides a high-resolution snapshot of the “side door,” scaling with the light captured by leaves. These two independent pieces of information help us understand plant water and carbon exchange. A coordinated effort to generate SIF and OCS data through satellite, airborne, and ground observations will improve our process-based models to predict how these cycles will change in the future. 

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2. The ECCO‐Darwin Data‐Assimilative Global Ocean Biogeochemistry Model: Estimates of Seasonal to Multidecadal Surface Ocean p CO 2 and Air‐Sea CO 2 Flux

   https://doi.org/10.1029/2019MS001888  

   Carroll, D. ; Menemenlis, D. ; Adkins, J. F. ; Bowman, K. W. ; Brix, H. ; Dutkiewicz, S. ; Fenty, I. ; Gierach, M. M. ; Hill, C. ; Jahn, O. ; et al ( October 2020 , Journal of Advances in Modeling Earth Systems)

   Quantifying variability in the ocean carbon sink remains problematic due to sparse observations and spatiotemporal variability in surface oceanpCO₂. To address this challenge, we have updated and improved ECCO‐Darwin, a global ocean biogeochemistry model that assimilates both physical and biogeochemical observations. The model consists of an adjoint‐based ocean circulation estimate from the Estimating the Circulation and Climate of the Ocean (ECCO) consortium and an ecosystem model developed by the Massachusetts Institute of Technology Darwin Project. In addition to the data‐constrained ECCO physics, a Green's function approach is used to optimize the biogeochemistry by adjusting initial conditions and six biogeochemical parameters. Over seasonal to multidecadal timescales (1995–2017), ECCO‐Darwin exhibits broad‐scale consistency with observed surface oceanpCO₂and air‐sea CO₂flux reconstructions in most biomes, particularly in the subtropical and equatorial regions. The largest differences between CO₂uptake occur in subpolar seasonally stratified biomes, where ECCO‐Darwin results in stronger winter uptake. Compared to the Global Carbon Project OBMs, ECCO‐Darwin has a time‐mean global ocean CO₂sink (2.47 ± 0.50 Pg C year⁻¹) and interannual variability that are more consistent with interpolation‐based products. Compared to interpolation‐based methods, ECCO‐Darwin is less sensitive to sparse and irregularly sampled observations. Thus, ECCO‐Darwin provides a basis for identifying and predicting the consequences of natural and anthropogenic perturbations to the ocean carbon cycle, as well as the climate‐related sensitivity of marine ecosystems. Our study further highlights the importance of physically consistent, property‐conserving reconstructions, as are provided by ECCO, for ocean biogeochemistry studies.

    

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3. Bedrock Weathering Controls on Terrestrial Carbon‐Nitrogen‐Climate Interactions

   https://doi.org/10.1029/2020GB006933  

   Dass, Pawlok ; Houlton, Benjamin Z. ; Wang, Yingping ; Wårlind, David ; Morford, Scott ( October 2021 , Global Biogeochemical Cycles)

   Anthropogenic nitrogen deposition is widely considered to increase CO₂sequestration by land plants on a global scale. Here, we demonstrate that bedrock nitrogen weathering contributes significantly more to nitrogen‐carbon interactions than anthropogenic nitrogen deposition. This working hypothesis is based on the introduction of empirical results into a global biogeochemical simulation model over the time period of the mid‐1800s to the end of the 21st century. Our findings suggest that rock nitrogen inputs have contributed roughly 2–11 times more to plant CO₂capture than nitrogen deposition inputs since pre‐industrial times. Climate change projections based on RCP 8.5 show that rock nitrogen inputs and biological nitrogen fixation contribute 2–5 times more to terrestrial carbon uptake than anthropogenic nitrogen deposition though year 2101. Future responses of rock N inputs on plant CO₂capture rates are more signficant at higher latitudes and in mountainous environments, where geological and climate factors promote higher rock weathering rates. The enhancement of plant CO₂uptake via rock nitrogen weathering partially resolves nitrogen‐carbon discrepancies in Earth system models and offers an alternative explanation for lack of progressive nitrogen limitation in the terrestrial biosphere. We conclude that natural N inputs impart major control over terrestrial CO₂sequestration in Earth’s ecosystems.

    

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4. Inferred drought‐induced plant allocation shifts and their impact on drought legacy at a tropical forest site

   https://doi.org/10.1111/gcb.17287  

   Worden, Matthew_A ; Famiglietti, Caroline_A ; Levine, Paul_A ; Ma, Shuang ; Bloom, A_Anthony ; Bonal, Damien ; Stahl, Clément ; Konings, Alexandra_G ( May 2024 , Global Change Biology)

   While droughts predominantly induce immediate reductions in plant carbon uptake, they can also exert long‐lasting effects on carbon fluxes through associated changes in leaf area, soil carbon, etc. Among other mechanisms, shifts in carbon allocation due to water stress can contribute to the legacy effects of drought on carbon fluxes. However, the magnitude and impact of these allocation shifts on carbon fluxes and pools remain poorly understood. Using data from a wet tropical flux tower site in French Guiana, we demonstrate that drought‐induced carbon allocation shifts can be reliably inferred by assimilating Net Biosphere Exchange (NBE) and other observations within the CARbon DAta MOdel fraMework. This model‐data fusion system allows inference of optimized carbon and water cycle parameters and states from multiple observational data streams. We then examined how these inferred shifts affected the duration and magnitude of drought's impact on NBE during and after the extreme event. Compared to a static allocation scheme analogous to those typically implemented in land surface models, dynamic allocation reduced average carbon uptake during drought recovery by a factor of 2.8. Additionally, the dynamic model extended the average recovery time by 5 months. The inferred allocation shifts influenced the post‐drought period by altering foliage and fine root pools, which in turn modulated gross primary productivity and heterotrophic respiration for up to a decade. These changes can create a bust‐boom cycle where carbon uptake is enhanced some years after a drought, compared to what would have occurred under drought‐free conditions. Overall, allocation shifts accounted for 65% [45%–75%] of drought legacy effects in modeled NBE. In summary, drought‐induced carbon allocation shifts can play a substantial role in the enduring influence of drought on cumulative land‐atmosphere CO₂exchanges and should be accounted for in ecosystem models.

    

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5. Assessing Model Predictions of Carbon Dynamics in Global Drylands

   https://doi.org/10.3389/fenvs.2022.790200  

   Fawcett, Dominic ; Cunliffe, Andrew M. ; Sitch, Stephen ; O’Sullivan, Michael ; Anderson, Karen ; Brazier, Richard E. ; Hill, Timothy C. ; Anthoni, Peter ; Arneth, Almut ; Arora, Vivek K. ; et al ( April 2022 , Frontiers in Environmental Science)

   Drylands cover ca. 40% of the land surface and are hypothesised to play a major role in the global carbon cycle, controlling both long-term trends and interannual variation. These insights originate from land surface models (LSMs) that have not been extensively calibrated and evaluated for water-limited ecosystems. We need to learn more about dryland carbon dynamics, particularly as the transitory response and rapid turnover rates of semi-arid systems may limit their function as a carbon sink over multi-decadal scales. We quantified aboveground biomass carbon (AGC; inferred from SMOS L-band vegetation optical depth) and gross primary productivity (GPP; from PML-v2 inferred from MODIS observations) and tested their spatial and temporal correspondence with estimates from the TRENDY ensemble of LSMs. We found strong correspondence in GPP between LSMs and PML-v2 both in spatial patterns (Pearson’s r = 0.9 for TRENDY-mean) and in inter-annual variability, but not in trends. Conversely, for AGC we found lesser correspondence in space (Pearson’s r = 0.75 for TRENDY-mean, strong biases for individual models) and in the magnitude of inter-annual variability compared to satellite retrievals. These disagreements likely arise from limited representation of ecosystem responses to plant water availability, fire, and photodegradation that drive dryland carbon dynamics. We assessed inter-model agreement and drivers of long-term change in carbon stocks over centennial timescales. This analysis suggested that the simulated trend of increasing carbon stocks in drylands is in soils and primarily driven by increased productivity due to CO 2 enrichment. However, there is limited empirical evidence of this 50-year sink in dryland soils. Our findings highlight important uncertainties in simulations of dryland ecosystems by current LSMs, suggesting a need for continued model refinements and for greater caution when interpreting LSM estimates with regards to current and future carbon dynamics in drylands and by extension the global carbon cycle. 

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