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Browsing by Author "Lombardozzi, Danica L."

Now showing 1 - 5 of 5
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    Beyond Static Benchmarking: Using Experimental Manipulations to Evaluate Land Model Assumptions
    Wieder, William R.; Lawrence, David M.; Fisher, Rosie A.; Bonan, Gordon B.; Cheng, Susan J.; Goodale, Christine L.; Grandy, A. Stuart; Koven, Charles D.; Lombardozzi, Danica L.; Oleson, Keith W.; Thomas, R. Quinn (American Geophysical Union, 2019-10-28)
    Land models are often used to simulate terrestrial responses to future environmental changes, but these models are not commonly evaluated with data from experimental manipulations. Results from experimental manipulations can identify and evaluate model assumptions that are consistent with appropriate ecosystem responses to future environmental change. We conducted simulations using three coupled carbon-nitrogen versions of the Community Land Model (CLM, versions 4, 4.5, and—the newly developed—5), and compared the simulated response to nitrogen (N) and atmospheric carbon dioxide (CO2) enrichment with meta-analyses of observations from similar experimental manipulations. In control simulations, successive versions of CLM showed a poleward increase in gross primary productivity and an overall bias reduction, compared to FLUXNET-MTE observations. Simulations with N and CO2 enrichment demonstrate that CLM transitioned from a model that exhibited strong nitrogen limitation of the terrestrial carbon cycle (CLM4) to a model that showed greater responsiveness to elevated concentrations of CO2 in the atmosphere (CLM5). Overall, CLM5 simulations showed better agreement with observed ecosystem responses to experimental N and CO2 enrichment than previous versions of the model. These simulations also exposed shortcomings in structural assumptions and parameterizations. Specifically, no version of CLM captures changes in plant physiology, allocation, and nutrient uptake that are likely important aspects of terrestrial ecosystems' responses to environmental change. These highlight priority areas that should be addressed in future model developments. Moving forward, incorporating results from experimental manipulations into model benchmarking tools that are used to evaluate model performance will help increase confidence in terrestrial carbon cycle projections.
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    The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty
    Lawrence, David M.; Fisher, Rosie A.; Koven, Charles D.; Oleson, Keith W.; Swenson, Sean C.; Bonan, Gordon B.; Collier, Nathan; Ghimire, Bardan; van Kampenhout, Leo; Kennedy, Daniel; Kluzek, Erik; Lawrence, Peter J.; Li, Fang; Li, Hongyi; Lombardozzi, Danica L.; Riley, William J.; Sacks, William J.; Shi, Mingjie; Vertenstein, Mariana; Wieder, William R.; Xu, Chonggang; Ali, Ashehad A.; Badger, Andrew M.; Bisht, Gautam; van den Broeke, Michiel; Brunke, Michael A.; Burns, Sean P.; Buzan, Jonathan; Clark, Martyn; Craig, Anthony; Dahlin, Kyla; Drewniak, Beth; Fisher, Joshua B.; Flanner, Mark; Fox, Andrew M.; Gentine, Pierre; Hoffman, Forrest; Keppel-Aleks, Gretchen; Knox, Ryan; Kumar, Sanjiv; Lenaerts, Jan; Leung, L. Ruby; Lipscomb, William H.; Lu, Yaqiong; Pandey, Ashutosh; Pelletier, Jon D.; Perket, Justin; Randerson, James T.; Ricciuto, Daniel M.; Sanderson, Benjamin M.; Slater, Andrew; Subin, Zachary M.; Tang, Jinyun; Thomas, R. Quinn; Martin, Maria Val; Zeng, Xubin (American Geophysical Union, 2019-10-19)
    The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.
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    Decadal fates and impacts of nitrogen additions on temperate forest carbon storage: a data-model comparison
    Cheng, Susan J.; Hess, Peter G.; Wieder, William R.; Thomas, R. Quinn; Nadelhoffer, Knute J.; Vira, Julius; Lombardozzi, Danica L.; Gundersen, Per; Fernandez, Ivan J.; Schleppi, Patrick; Gruselle, Marie-Cecile; Moldan, Filip; Goodale, Christine L. (Copernicus, 2019-07-16)
    To accurately capture the impacts of nitrogen (N) on the land carbon (C) sink in Earth system models, model responses to both N limitation and ecosystem N additions (e.g., from atmospheric N deposition and fertilizer) need to be evaluated. The response of the land C sink to N additions depends on the fate of these additions: that is, how much of the added N is lost from the ecosystem through N loss pathways or recovered and used to increase C storage in plants and soils. Here, we evaluate the C-N dynamics of the latest version of a global land model, the Community Land Model version 5 (CLM5), and how they vary when ecosystems have large N inputs and losses (i.e., an open N cycle) or small N inputs and losses (i.e., a closed N cycle). This comparison allows us to identify potential improvements to CLM5 that would apply to simulated N cycles along the open-to-closed spectrum. We also compare the short-(< 3 years) and longerterm (5-17 years) N fates in CLM5 against observations from 13 long-term 15N tracer addition experiments at eight temperate forest sites. Simulations using both open and closed N cycles overestimated plant N recovery following N additions. In particular, the model configuration with a closed N cycle simulated that plants acquired more than twice the amount of added N recovered in 15N tracer studies on short timescales (CLM5: 46 ± 12 %; observations: 18 ± 12 %; mean across sites ±1 standard deviation) and almost twice as much on longer timescales (CLM5: 23±6 %; observations: 13±5 %). Soil N recoveries in simulations with closed N cycles were closer to observations in the short term (CLM5: 40 ± 10 %; observations: 54±22 %) but smaller than observations in the long term (CLM5: 59±15 %; observations: 69±18 %). Simulations with open N cycles estimated similar patterns in plant and soil N recovery, except that soil N recovery was also smaller than observations in the short term. In both open and closed sets of simulations, soil N recoveries in CLM5 occurred from the cycling of N through plants rather than through direct immobilization in the soil, as is often indicated by tracer studies. Although CLM5 greatly overestimated plant N recovery, the simulated increase in C stocks to recovered N was not much larger than estimated by observations, largely because the model's assumed C:N ratio for wood was nearly half that suggested by measurements at the field sites. Overall, results suggest that simulating accu rate ecosystem responses to changes in N additions requires increasing soil competition for N relative to plants and examining model assumptions of C V N stoichiometry, which should also improve model estimates of other terrestrial C-N processes and interactions.
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    Increasing the spatial and temporal impact of ecological research: A roadmap for integrating a novel terrestrial process into an Earth system model
    Kyker-Snowman, Emily; Lombardozzi, Danica L.; Bonan, Gordon B.; Cheng, Susan J.; Dukes, Jeffrey S.; Frey, Serita D.; Jacobs, Elin M.; McNellis, Risa; Rady, Joshua M.; Smith, Nicholas G.; Thomas, R. Quinn; Wieder, William W.; Grandy, A. Stuart (Wiley, 2021-09-20)
    Terrestrial ecosystems regulate Earth's climate through water, energy, and biogeochemical transformations. Despite a key role in regulating the Earth system, terrestrial ecology has historically been underrepresented in the Earth system models (ESMs) that are used to understand and project global environmental change. Ecology and Earth system modeling must be integrated for scientists to fully comprehend the role of ecological systems in driving and responding to global change. Ecological insights can improve ESM realism and reduce process uncertainty, while ESMs offer ecologists an opportunity to broadly test ecological theory and increase the impact of their work by scaling concepts through time and space. Despite this mutualism, meaningfully integrating the two remains a persistent challenge, in part because of logistical obstacles in translating processes into mathematical formulas and identifying ways to integrate new theories and code into large, complex model structures. To help overcome this interdisciplinary challenge, we present a framework consisting of a series of interconnected stages for integrating a new ecological process or insight into an ESM. First, we highlight the multiple ways that ecological observations and modeling iteratively strengthen one another, dispelling the illusion that the ecologist's role ends with initial provision of data. Second, we show that many valuable insights, products, and theoretical developments are produced through sustained interdisciplinary collaborations between empiricists and modelers, regardless of eventual inclusion of a process in an ESM. Finally, we provide concrete actions and resources to facilitate learning and collaboration at every stage of data-model integration. This framework will create synergies that will transform our understanding of ecology within the Earth system, ultimately improving our understanding of global environmental change and broadening the impact of ecological research.
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    Modest capacity of no-till farming to offset emissions over 21st century
    Graham, Michael W.; Thomas, R. Quinn; Lombardozzi, Danica L.; O'Rourke, Megan E. (IOP, 2021-05-01)
    'No-till' (NT) agriculture, which eliminates nearly all physical disturbance of the soil surface on croplands, has been widely promoted as a means of soil organic carbon (SOC) sequestration with the potential to mitigate climate change. Here we provide the first global estimates of the SOC sequestration potential of NT adoption using a global land surface model (LSM). We use an LSM to simulate losses of SOC due to intensive tillage (IT) over the historical time period (1850-2014), followed by future simulations (2015-2100) assessing the SOC sequestration potential of adopting NT globally. Historical losses due to simulated IT practices ranged from 6.8 to 16.8 Gt C, or roughly 5%-13% of the 133 Gt C of global cumulative SOC losses attributable to agriculture reported elsewhere. Cumulative SOC sequestration in NT simulations over the entire 21st century was equivalent to approximately one year of current fossil fuel emissions and ranged between 6.6 and 14.4 Gt C (0.08-0.17 Gt C yr-1). Modeled increases in SOC sequestration under NT were concentrated in cool, humid temperate regions, with minimal SOC gains in the tropics. These results indicate that the global potential for SOC sequestration from NT adoption may be more limited than reported in some studies and promoted by policymakers. Our incorporation of tillage practices into an LSM is a major step toward integration of soil tillage as a management practice into LSMs and associated Earth system models. Future work should focus on improving process-understanding of tillage practices and their integration into LSMs, as well as resolving modeled versus observed estimates of SOC sequestration from NT adoption, particularly in the tropics.