Carbon Cycle Model Research Articles

Influences of the bark economics spectrum and positive termite feedback on bark and xylem decomposition.

The plant economics spectrum integrates trade-offs and covariation in resource economic traits of different plant organs and their consequences for pivotal ecosystem processes, such as decomposition. However, in this concept stems are often considered as one unit ignoring the important functional differences between wood (xylem) and bark. These differences may not only affect the performance of woody plants during their lifetime, but may also have important "afterlife effects." Specifically, bark quality may strongly affect deadwood decomposition of different woody species. We hypothesized that (1) bark quality strongly influences bark decomposability to microbial decomposers, and possibly amplifies the interspecific variation in decomposition by invertebrate consumption, especially termites; and (2) bark decomposition has secondary effects on xylem mass loss by providing access to decomposers including invertebrates such as termites. We tested these hypotheses across 34 subtropical woody species representing five common plant functional types, by conducting an insitu deadwood decomposition experiment over 12-month in two sites in subtropical evergreen broad-leaved forest in China. We employed visual examination and surface density measurement to quantify termite consumption to both bark and the underlying xylem, respectively. Using principal component analysis, we synthesized seven bark traits to provide the first empirical evidence for a bark economics spectrum (BES), with high BES values (i.e., bark thickness, nitrogen, phosphorus, and cellulose contents) indicating a resource acquisitive strategy and low BES values (i.e., carbon, lignin, and dry matter contents) indicating a resource conservative strategy. The BES affected interspecific variation in bark mass loss and this relationship was strongly amplified by termites. The BES also explained nearly half of the interspecific variation in termite consumption to xylem, making it an important contributor to deadwood decomposition overall. Moreover, the above across-species relationships manifested also within plant functional types, highlighting the value of using continuous variation in bark traits rather than categorical plant functional types in carbon cycle modeling. Our findings demonstrate the potent role of the BES in influencing deadwood decomposition including positive invertebrate feedback thereon in warm-climate forests, with implications for the role of bark quality in carbon cycling in other woody biomes.

Arid Coastal Carbonates and the Phanerozoic Record of Carbonate Chemistry

AbstractOcean chemistry and carbonate sedimentation link Earth's climate, carbon cycle, and marine pH. The carbonate system in seawater is complex and there are large uncertainties in key parameters in deep time. Here, we link sedimentary textures formed in arid coastal environments and preserved in the rock record to past seawater carbonate chemistry. Prior to the mid‐Mesozoic, tepee structures and pisoids – features associated with peritidal environments – co‐vary with available shelf area during cycles of supercontinent formation and rifting. In contrast, tepees and pisoids are consistently scarce after the mid‐Mesozoic, which coincides with a radiation in pelagic calcifiers as well as the breakup of Pangea. Numerical models suggest that the global and temporal abundances of tepee structures and pisoids are correlated with secular shifts in seawater chemistry, and that trends likely reflect the underlying influence of tectonics and biotic innovation on marine alkalinity and the saturation states of carbonate minerals. As independent sedimentary proxies, tepees and pisoids serve as benchmarks for global carbon cycle models and provide a new proxy record of seawater chemistry that can help discern links among tectonics, biotic innovation, and seawater chemistry.

Controls on Physical and Chemical Denudation in a Mixed Carbonate‐Siliciclastic Orogen

AbstractMixed siliciclastic‐carbonate active orogens are common on Earth's surface, yet most studies have focused on erosion and weathering in silicate‐rich landscapes. Relative to purely siliciclastic landscapes, the response of erosion and weathering to uplift may differ in mixed‐lithology regions. However, our knowledge of weathering and erosion in mixed carbonate‐silicate lithologies is limited and, thus, so is our understanding of the mechanistic coupling between uplift, weathering, and the carbon cycle. Here, we partition denudation fluxes into erosion and weathering fluxes of carbonates and silicates in the Northern Apennines—a mixed carbonate‐siliciclastic active orogen—using dissolved solutes, the carbonate sand fraction, and existing 10Be denudation rates. Erosion generally dominates total denudation fluxes relative to weathering by an order of magnitude. Carbonate and silicate contributions to erosion vary between lithologic units, but weathering fluxes are systematically dominated by carbonates. Silicate weathering may be kinetically limited, whereas carbonate weathering may be limited by acid supply. Carbonate re‐precipitation estimated by comparing ion ratios (Sr, Ca, Na) from rivers and bedrock suggests that up to 90% of dissolved Ca2+ is lost from carbonate‐rich catchments. Corresponding [Ca2+] estimates for the weathering zone are high, likely driven by high soil CO2 partial pressures (pCO2); however, re‐equilibration with atmospheric pCO2 in rivers converts solutes back into grains that become part of the physical denudation flux. Weathering limits in this landscape therefore differ between the subsurface weathering zone and riverine exports, and our findings suggest that carbon cycle models may overestimate the sensitivity to erosion of solute exports (Ca2+ and HCO3−) derived from carbonate weathering.

Spatial patterns of global-scale forest root-shoot ratio and their controlling factors

The forest root-shoot ratio (R/S), i.e., the ratio of belowground to aboveground biomass at the stand level, is widely used in global and regional forest carbon stock estimation and in modeling of the forest carbon cycle. Despite recent advances in understanding forest R/S variations at the individual-tree level, spatial patterns of stand-level forest R/S ratio across the globe and their driving factors remain relatively unknown. Here, we compiled and analyzed an extensive dataset from 873 forest sites worldwide, analyzed and quantified the effects of major environmental and forest growth-related variables on the stand-level R/S ratio. Based on this analysis, we further mapped the spatial pattern of the global forest R/S ratio. Our results show that, globally, variations on the stand-level forest R/S ratio are largely affected by canopy height, latitude, climatic water deficit, forest type and regeneration method, which collectively explain 37% of the variations in R/S ratio. In addition, our results suggest significant intercontinental and national variations in forest R/S ratio. At the continental scale, forest R/S ratio is highest in Oceania and lowest in South America. At the national scale, Australia has the highest forest R/S ratio while Russia has the lowest values. The forest R/S ratio is generally lower in moist tropical regions, but increases when moving to the extra-tropics when seasonality in precipitation increases. The R/S ratio in temperate and boreal regions shows prominent spatial features regulated by forest species composition and regeneration method. We conclude that future changes in environmental, biotic and anthropogenic factors, such as increased climatic water deficit and forest management, might influence the forest R/S ratio, with implications for the global and regional land carbon cycle.

Deep Ocean Storage of Heat and CO2 in the Fram Strait, Arctic Ocean During the Last Glacial Period

AbstractThe Fram Strait is the only deep gateway between the Arctic Ocean and the Nordic Seas and thus is a key area to study past changes in ocean circulation and the marine carbon cycle. Here, we study deep ocean temperature, δ18O, carbonate chemistry (i.e., carbonate ion concentration [CO32−]), and nutrient content in the Fram Strait during the late glacial (35,000–19,000 years BP) and the Holocene based on benthic foraminiferal geochemistry and carbon cycle modeling. Our results indicate a thickening of Atlantic water penetrating into the northern Nordic Seas, forming a subsurface Atlantic intermediate water layer reaching to at least ∼2,600 m water depth during most of the late glacial period. The recirculating Atlantic layer was characterized by relatively high [CO32−] and low δ13C during the late glacial, and provides evidence for a Nordic Seas source to the glacial North Atlantic intermediate water flowing at 2,000–3,000 m water depth, most likely via the Denmark Strait. In addition, we discuss evidence for enhanced terrestrial carbon input to the Nordic Seas at ∼23.5 ka. Comparing our δ13C and qualitative [CO32−] records with results of carbon cycle box modeling suggests that the total terrestrial CO2 release during this carbon input event was low, slow, or directly to the atmosphere.

Incorporating the stable carbon isotope <sup>13</sup>C in the ocean biogeochemical component of the Max Planck Institute Earth System Model

Abstract. The stable carbon isotopic composition (δ13C) is an important variable to study the ocean carbon cycle across different timescales. We include a new representation of the stable carbon isotope 13C into the HAMburg Ocean Carbon Cycle model (HAMOCC), the ocean biogeochemical component of the Max Planck Institute Earth System Model (MPI-ESM). 13C is explicitly resolved for all oceanic carbon pools considered. We account for fractionation during air–sea gas exchange and for biological fractionation ϵp associated with photosynthetic carbon fixation during phytoplankton growth. We examine two ϵp parameterisations of different complexity: ϵpPopp varies with surface dissolved CO2 concentration (Popp et al., 1989), while ϵpLaws additionally depends on local phytoplankton growth rates (Laws et al., 1995). When compared to observations of δ13C of dissolved inorganic carbon (DIC), both parameterisations yield similar performance. However, with regard to δ13C in particulate organic carbon (POC) ϵpPopp shows a considerably improved performance compared to ϵpLaws. This is because ϵpLaws produces too strong a preference for 12C, resulting in δ13CPOC that is too low in our model. The model also well reproduces the global oceanic anthropogenic CO2 sink and the oceanic 13C Suess effect, i.e. the intrusion and distribution of the isotopically light anthropogenic CO2 in the ocean. The satisfactory model performance of the present-day oceanic δ13C distribution using ϵpPopp and of the anthropogenic CO2 uptake allows us to further investigate the potential sources of uncertainty of the Eide et al. (2017a) approach for estimating the oceanic 13C Suess effect. Eide et al. (2017a) derived the first global oceanic 13C Suess effect estimate based on observations. They have noted a potential underestimation, but their approach does not provide any insight about the cause. By applying the Eide et al. (2017a) approach to the model data we are able to investigate in detail potential sources of underestimation of the 13C Suess effect. Based on our model we find underestimations of the 13C Suess effect at 200 m by 0.24 ‰ in the Indian Ocean, 0.21 ‰ in the North Pacific, 0.26 ‰ in the South Pacific, 0.1 ‰ in the North Atlantic and 0.14 ‰ in the South Atlantic. We attribute the major sources of underestimation to two assumptions in the Eide et al. (2017a) approach: the spatially uniform preformed component of δ13CDIC in year 1940 and the neglect of processes that are not directly linked to the oceanic uptake and transport of chlorofluorocarbon-12 (CFC-12) such as the decrease in δ13CPOC over the industrial period. The new 13C module in the ocean biogeochemical component of MPI-ESM shows satisfying performance. It is a useful tool to study the ocean carbon sink under the anthropogenic influences, and it will be applied to investigating variations of ocean carbon cycle in the past.

Is photosynthetic enhancement sustained through three years of elevated CO2 exposure in 175-year-old Quercus robur?

Current carbon cycle models attribute rising atmospheric CO2 as the major driver of the increased terrestrial carbon sink, but with substantial uncertainties. The photosynthetic response of trees to elevated atmospheric CO2 is a necessary step, but not the only one, for sustaining the terrestrial carbon uptake, but can vary diurnally, seasonally and with duration of CO2 exposure. Hence, we sought to quantify the photosynthetic response of the canopy-dominant species, Quercus robur, in a mature deciduous forest to elevated CO2 (eCO2) (+150 μmol mol−1 CO2) over the first 3 years of a long-term free air CO2 enrichment facility at the Birmingham Institute of Forest Research in central England (BIFoR FACE). Over 3000 measurements of leaf gas exchange and related biochemical parameters were conducted in the upper canopy to assess the diurnal and seasonal responses of photosynthesis during the 2nd and 3rd year of eCO2 exposure. Measurements of photosynthetic capacity via biochemical parameters, derived from CO2 response curves, (Vcmax and Jmax) together with leaf nitrogen concentrations from the pre-treatment year to the 3rd year of eCO2 exposure, were examined. We hypothesized an initial enhancement in light-saturated net photosynthetic rates (Asat) with CO2 enrichment of ≈37% based on theory but also expected photosynthetic capacity would fall over the duration of the study. Over the 3-year period, Asat of upper-canopy leaves was 33 ± 8% higher (mean and standard error) in trees grown in eCO2 compared with ambient CO2 (aCO2), and photosynthetic enhancement decreased with decreasing light. There were no significant effects of CO2 treatment on Vcmax or Jmax, nor leaf nitrogen. Our results suggest that mature Q. robur may exhibit a sustained, positive response to eCO2 without photosynthetic downregulation, suggesting that, with adequate nutrients, there will be sustained enhancement in C assimilated by these mature trees. Further research will be required to understand the location and role of the additionally assimilated carbon.

Improving intra‐ and inter‐annual GPP predictions by using individual tree inventories and leaf growth dynamics

Abstract Carbon sequestration is a key ecosystem service provided by forests. Inventory data based on individual trees are considered to be the most accurate method for estimating forest productivity. However, the estimations of forest photosynthesis from inventory data remain understudied, particularly when considering the growth and development of individual trees under the background of global change. Here, we used the leaf growth process with phenology and non‐structural carbohydrates (NSC) storage to revise an individual‐tree‐based carbon model, FORCCHN. This model couples leaf development and biomass to quantify gross primary productivity (GPP) in the forests, where growth is decoupled from photosynthesis in daily step. The model was initialized with inventory‐based forest data rather than the more widely used satellite‐based data. We tested the model against measured above‐ground woody biomass, growth of leaf biomass, daily gross ecosystem exchange (GEE) and yearly GEE at five representative forest sites in the Northern Hemisphere. We also compared the results from the original model and the revised model at five forest sites. Including leaf growth dynamics and inventory‐based initialization improved the predicted performance (r2) of GPP by an average of 33%. Synthesis and applications. Our results suggest that the appropriate vegetation data sources (i.e. inventory or satellite selection) and the effective predictions of the growth process should be considered when developing future carbon cycle models and forest carbon estimation options. Applying and improving such carbon models to evaluate carbon sequestration is an important part of forest carbon sink management.

Estimating Remaining Carbon Budgets Using Temperature Responses Informed by CMIP6

A remaining carbon budget (RCB) estimates how much CO2 we can emit and still reach a specific temperature target. The RCB concept is attractive since it easily communicates to the public and policymakers, but RCBs are also subject to uncertainties. The expected warming levels for a given carbon budget has a wide uncertainty range, which increases with less ambitious targets, i.e., with higher CO2 emissions and temperatures. Leading causes of RCB uncertainty are the future non-CO2 emissions, Earth system feedbacks, and the spread in the climate sensitivity among climate models. The latter is investigated in this paper, using a simple carbon cycle model and emulators of the temperature responses of the Earth System Models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble. Driving 41 CMIP6 emulators with 127 different emission scenarios for the 21st century, we find almost perfect linear relationship between maximum global surface air temperature and cumulative carbon emissions, allowing unambiguous estimates of RCB for each CMIP6 model. The range of these estimates over the model ensemble is a measure of the uncertainty in the RCB arising from the range in climate sensitivity over this ensemble, and it is suggested that observational constraints imposed on the transient climate response in the model ensemble can reduce uncertainty in RCB estimates.

The Sensitivity of the Marine Carbonate System to Regional Ocean Alkalinity Enhancement

Ocean Alkalinity Enhancement (OAE) simultaneously mitigates atmospheric concentrations of CO2 and ocean acidification; however, no previous studies have investigated the response of the non-linear marine carbonate system sensitivity to alkalinity enhancement on regional scales. We hypothesise that regional implementations of OAE can sequester more atmospheric CO2 than a global implementation. To address this, we investigate physical regimes and alkalinity sensitivity as drivers of the carbon-uptake potential response to global and different regional simulations of OAE. In this idealised ocean-only set-up, total alkalinity is enhanced at a rate of 0.25 Pmol a-1 in 75-year simulations using the Max Planck Institute Ocean Model coupled to the HAMburg Ocean Carbon Cycle model with pre-industrial atmospheric forcing. Alkalinity is enhanced globally and in eight regions: the Subpolar and Subtropical Atlantic and Pacific gyres, the Indian Ocean and the Southern Ocean. This study reveals that regional alkalinity enhancement has the capacity to exceed carbon uptake by global OAE. We find that 82–175 Pg more carbon is sequestered into the ocean when alkalinity is enhanced regionally and 156 PgC when enhanced globally, compared with the background-state. The Southern Ocean application is most efficient, sequestering 12% more carbon than the Global experiment despite OAE being applied across a surface area 40 times smaller. For the first time, we find that different carbon-uptake potentials are driven by the surface pattern of total alkalinity redistributed by physical regimes across areas of different carbon-uptake efficiencies. We also show that, while the marine carbonate system becomes less sensitive to alkalinity enhancement in all experiments globally, regional responses to enhanced alkalinity vary depending upon the background concentrations of dissolved inorganic carbon and total alkalinity. Furthermore, the Subpolar North Atlantic displays a previously unexpected alkalinity sensitivity increase in response to high total alkalinity concentrations.

An updated framework for climate change impact assessment of bioenergy and an application in poplar biomass

Mainstream life cycle assessment (LCA) studies on the climate change impact of bioenergy fail to account for some direct impacts, such as biomass-derived CO2 emissions and potential impacts on future carbon dynamics. For a more persuasive assessment of the climate change impacts of bioenergy, a simplified and comprehensive framework was developed for LCA by integrating the atmospheric carbon cycle model, plant growth model, and biomass decomposition model. The system includes four components: fossil fuel-derived greenhouse gas (GHG) emissions, biogenic CO2 emissions, biomass regrowth for compensation, and the difference in carbon sequestration from the reference scenario. For an illustration purpose, the framework was applied in the study of the climate change impacts of hybrid poplar use for bio-ethanol, bio-diesel, heating, and bio-power. The LCA study indicated that the fossil fuel-derived GHG emissions (15.77–42.55 kg CO2 eq/GJ) from biomass utilization were lower than those from the combustion of fossil fuels. Because the fossil fuel-derived GHG emissions, biogenic CO2 emissions, and biomass regrowth for compensation were positive, the sums of the three components (120.21–243.97 kg CO2 eq/GJ) were higher than the emissions from the combustion of fossil fuels. However, biomass utilization may improve biomass regrowth or avoid biomass decomposition. The differences in carbon sequestration are usually negative and can offset the positive climate change impacts. The final total climate change impacts for the different types of bioenergy were from –26.85 kg CO2 eq/GJ to 1.08 kg CO2 eq/GJ. The newly developed framework is more persuasive and comprehensive than the conventional LCA because it includes all the direct impacts of biomass utilization based on the biomass characteristics. The application of this framework can ensure the sustainable utilization of biomass and avoid ecosystem degradation.

Modeling the typhoon disturbance effect on ecosystem carbon storage dynamics in a subtropical forest of China's coastal region

As an important ecological factor shaping terrestrial ecosystem states and destabilizing coastal forest ecosystems, typhoon events have become the focus of attention in recent years. However, there are limited studies on the change of carbon storage dynamics of subtropical forest ecosystems under typhoon disturbance. Here, we developed a theoretical ecosystem carbon cycle model combined with forest inventory data and measurements to evaluate pluriannual typhoon response of East Monsoon subtropical forest ecosystem carbon storage dynamics in Tiantong mountain (29°48′N, 121°47′E). We focused on the relationships between typhoon regime and ecosystem carbon storage dynamics, and forest resistance and resilience to typhoon disturbances. We showed that the disturbed plant biomass contributed to the reduced forest ecosystem carbon storage capacity. The modeling analyses underscored the critical role of biomass turnover time in forest ecosystem carbon storage capacity. The soil organic matter was highly stable under severe typhoons while the resistance of biomass and litter carbon amounts to increasingly severe typhoons decreased. The theoretical estimates provided by this study are instructive for the policy making of subtropical forest conservation and management under global environmental changes.

Temporally variable parameters simulate asymmetrical interannual variation of aboveground and belowground carbon pools in an alpine meadow

Exploring interannual variation (IAV) of terrestrial carbon cycle is crucial for understanding the climate-carbon cycle feedback. However, model simulations of IAV in carbon pools are highly sensitive to parameterization. Although researches indicate that parameters vary as environment changes, most terrestrial carbon cycle models apply time-invariant parameters, leading to uncertainty in reproducing IAV. We compared the IAV simulation accuracy of carbon pools between constant and temporally variable parameters, generated by a piecewise model-data fusion framework based on long-term multi-observations in an alpine meadow over the Tibetan Plateau. Piecewise assimilation showed that key parameters involved in photosynthesis and allocation processes exhibited significant temporal variation under warming and nitrogen deposition. Specifically, day length threshold for leaf senescence was postponed, while allocation to autotrophic respiration, allocation to root, leaf nitrogen content, and nitrogen use efficiency increased. Compared with constant parameters, temporally variable parameters captured the observed asymmetrical response of aboveground and belowground carbon pools to climate fluctuations, improved modeled magnitude of IAV in carbon pools by 34% on average, and advanced carbon sink estimation accuracy by 43.15%. Therefore, fitting parameter dynamics to climatic conditions can provide a benchmark for future simulation in the Tibetan Plateau. Our research suggests that IAV in different carbon pools is crucial in determining carbon sinks. Temporal variations of parameters present how ecosystems adapt to a changing environment and should be incorporated to terrestrial carbon cycle models to reduce uncertainty in model prediction.

A dynamic monetary valuation perspective for carbon sequestration: Effect on biomass utilization strategy of Caragana plantation as an illustration

Carbon sequestration plays an essential role in climate regulation, and its monetary value is critical for decision-making. To encourage carbon sequestration and avoid expensing the ecosystem services for future generations, a dynamic monetary valuation perspective was developed by integrating a carbon dynamics model of ecosystems and an atmospheric carbon cycle model. A case study of biomass utilization in Northern Shaanxi was conducted to illustrative the performance of this approach by comparing with the conventional approach. The carbon dynamics in the available lands were simulated by the CENTURY model under the RCP4.5 climate change scenario. The results suggested that the carbon storage was doubled without biomass utilization in the projected 25 years. When biomass was harvested, carbon storage decreased slightly. The monetary value without biomass harvesting in the dynamic approach was higher than that in the conventional approach. After analogizing the monetary values of carbon sequestration and biomass utilization, there was a lower likelihood of biomass harvesting in the dynamic approach than in the conventional approach.

A tighter constraint on Earth-system sensitivity from long-term temperature and carbon-cycle observations

The long-term temperature response to a given change in CO2 forcing, or Earth-system sensitivity (ESS), is a key parameter quantifying our understanding about the relationship between changes in Earth’s radiative forcing and the resulting long-term Earth-system response. Current ESS estimates are subject to sizable uncertainties. Long-term carbon cycle models can provide a useful avenue to constrain ESS, but previous efforts either use rather informal statistical approaches or focus on discrete paleoevents. Here, we improve on previous ESS estimates by using a Bayesian approach to fuse deep-time CO2 and temperature data over the last 420 Myrs with a long-term carbon cycle model. Our median ESS estimate of 3.4 °C (2.6-4.7 °C; 5-95% range) shows a narrower range than previous assessments. We show that weaker chemical weathering relative to the a priori model configuration via reduced weatherable land area yields better agreement with temperature records during the Cretaceous. Research into improving the understanding about these weathering mechanisms hence provides potentially powerful avenues to further constrain this fundamental Earth-system property.

Accounting for canopy structure improves hyperspectral radiative transfer and sun-induced chlorophyll fluorescence representations in a new generation Earth System model

Three-dimensional (3D) vegetation canopy structure plays an important role in the way radiation interacts with the land surface. Accurately representing this process in Earth System models (ESMs) is crucial for the modeling of the global carbon, energy, and water cycles and hence future climate projections. Despite the importance of accounting for 3D canopy structure, the inability to represent such complexity at regional and global scales has impeded a successful implementation into ESMs. An alternative approach is to use an implicit clumping index to account for the horizontal heterogeneity in vegetation canopy representations in ESMs at global scale. This paper evaluates how modeled hyperspectral shortwave radiation partitioning of the terrestrial biosphere, as well as Sun-Induced Chlorophyll Fluorescence (SIF) are impacted when a clumping index parameterization is incorporated in the radiative transfer scheme of a new generation ESM, the Climate Model Alliance (CliMA). An accurate hyperspectral radiative transfer representation within ESMs is critical for accurately using of satellite data to confront, constrain, and improve land model processes. The newly implemented scheme is compared to Monte Carlo calculations for idealized scenes from the Radiation transfer Model Intercomparison for the Project for Intercomparison of Land-Surface Parameterizations (RAMI4PILPS), for open forest canopies both with and without snow on the ground. Results indicate that it is critical to account for canopy structural heterogeneity when calculating hyperspectral radiation transfer. The RMSE in shortwave radiation is reduced for reflectance (25%), absorptance (66%), and transmittance (75%) compared to the scenario without considering clumping. Calculated SIF is validated against satellite remote sensing data with the recently launched NASA Orbiting Carbon Observatory (OCO) 3, showing that including vertical and horizontal canopy structure when deriving SIF can improve model predictions in up to 51% in comparison to the scenario without clumping. By adding a clumping index into the CliMA-Land model, the relationship between canopy structure and SIF, Gross Primary Productivity (GPP), hyperspectral radiative transfer, and viewing geometry at the canopy scale can be explored in detail.

Shoring up the foundations of production to respiration ratios in lakes

AbstractThe ratio of primary production to ecosystem respiration rates (P:R ratio) is an ostensibly simple calculation that is used to characterize lake function, including trophic status, the incorporation of terrestrial organic carbon into lacustrian food webs, and the direction of carbon dioxide (CO2) flux between a lake and the atmosphere. However, many predictive links between P:R ratios and lake ecosystem function stem from a historically plankton‐centric perspective and the common use of the diel oxygen curve approach. We review the evolution of the use of P:R ratios and examine common assumptions underlying their application to (1) eutrophication, (2) carbon flux through lake food webs, and (3) the role of lakes in the global carbon budget. Foundational P:R studies have been complicated principally by the following: most P:R ratios were calculated from mid‐lake measurements and failed to incorporate nonplanktonic dynamics; there has been confusion regarding the food web implications when P:R ≠ 1; and CO2 fluxes between lakes and the atmosphere are influenced by nonmetabolic processes. We argue for a re‐assessment, or shoring up, of several fundamental assumptions that continue to guide metabolism research in lakes by accounting for mixing, benthic‐littoral processes, groundwater fluxes, and abiotic controls on gas dynamics to better understand lake food webs and accurately integrate lake ecosystems into landscape‐scale carbon cycling models.

Effect of precipitation frequency on litter decomposition of three annual species (Setaria viridis, Artemisia sacrorum, and Chenopodium acuminatum) in a semi-arid sandy grassland of northeastern China

Annual total precipitation typically fails to predict litter decomposition rates, especially in semi-arid regions, where precipitation frequency (PF) significantly affects decomposition. We hypothesized that low PF would decrease decomposition rates. We performed a litterbag decomposition experiment with litter of three annual species at three depths (aboveground litter, litter at 0–10 and 10–20 cm below the surface). We used the same total amount (280 mm), but three precipitation frequencies (PF1, 10 mm every 5 days; PF2, 20 mm every 10 days; PF3, 40 mm every 20 days) during the growing season. We measured the remaining mass, carbon (C) content, nitrogen (N) content, C:N ratio, and C and N losses of each species at the three positions. Litter decomposition and the C and N dynamics were influenced by species, depth, and PF. Low PF significantly decreased litter decomposition (mass loss rates of 49.7, 49.1, and 41.2% for PF1, PF2, and PF3, respectively). This effect interacted with placement-depth but not with species. This interaction also existed for C and N dynamics except for the N loss rate. The influence of PF on C loss mainly resulted from its effect on mass loss, whereas N loss was not affected by PF. Our results highlight the importance of PF for litter decomposition in a semi-arid region. The relationship between PF and litter decomposition provides a theoretical basis for regional carbon-cycle models and carbon budget predictions. Our results also suggest that non-graminaceous species showed higher potential than grasses for improving soil carbon in semi-arid sandy grasslands due to faster decomposition rates, especially below ground.

Beyond biomass to carbon fluxes: application and evaluation of a comprehensive forest carbon monitoring system

Accurate quantification of forest carbon stocks and fluxes over regions is needed to monitor forest resources as they respond to changes in climate, disturbance and management, and also to evaluate contributions of forest sector to the regional and global carbon balances. In previous work we introduced a national forest carbon monitoring system (NFCMS) that combines forest inventory data, satellite remote sensing of stand biomass and forest disturbances, and an ecosystem carbon cycle model to assess contemporary forest carbon dynamics at a 30 m resolution. In this study, we evaluate the NFCMS estimates of biomass and carbon fluxes with available data products for the Pacific Northwest (PNW) region, and then analyze the regional carbon balance over the period 1986–2010. The biomass estimates have good agreements with evaluation datasets (eMapR, NBCD2000, and Hagen2005) at regional and forest type levels, and at spatial scales of 1 km2 and larger. Regionwide, PNW forests acted as a stable net sink for atmospheric CO2 (18.5 Tg C yr–1) within forestlands. However, harvesting activities removed significant amounts of carbon, equating to over 75% of annual net carbon sink, though only 25% of this (∼3.5 Tg C yr–1) is emitted to the atmosphere within 50 years. Wildfires contributed modestly to carbon emissions in most years, however, the severe fires of 2002 and 2006 released 16.6 and 7.1 Tg C, respectively. The study demonstrates the potential of the NFCMS framework to serve as a candidate measuring, reporting and verification system, informed by field and remotely sensed inventories, and tracking the carbon balance of the forest sector across the United States.

Optimal model complexity for terrestrial carbon cycle prediction

Abstract. The terrestrial carbon cycle plays a critical role in modulating the interactions of climate with the Earth system, but different models often make vastly different predictions of its behavior. Efforts to reduce model uncertainty have commonly focused on model structure, namely by introducing additional processes and increasing structural complexity. However, the extent to which increased structural complexity can directly improve predictive skill is unclear. While adding processes may improve realism, the resulting models are often encumbered by a greater number of poorly determined or over-generalized parameters. To guide efficient model development, here we map the theoretical relationship between model complexity and predictive skill. To do so, we developed 16 structurally distinct carbon cycle models spanning an axis of complexity and incorporated them into a model–data fusion system. We calibrated each model at six globally distributed eddy covariance sites with long observation time series and under 42 data scenarios that resulted in different degrees of parameter uncertainty. For each combination of site, data scenario, and model, we then predicted net ecosystem exchange (NEE) and leaf area index (LAI) for validation against independent local site data. Though the maximum model complexity we evaluated is lower than most traditional terrestrial biosphere models, the complexity range we explored provides universal insight into the inter-relationship between structural uncertainty, parametric uncertainty, and model forecast skill. Specifically, increased complexity only improves forecast skill if parameters are adequately informed (e.g., when NEE observations are used for calibration). Otherwise, increased complexity can degrade skill and an intermediate-complexity model is optimal. This finding remains consistent regardless of whether NEE or LAI is predicted. Our COMPLexity EXperiment (COMPLEX) highlights the importance of robust observation-based parameterization for land surface modeling and suggests that data characterizing net carbon fluxes will be key to improving decadal predictions of high-dimensional terrestrial biosphere models.