The Science
The land surface is a crucial part of the Earth system, and land surface models (LSMs) are key to some of the most important problems facing society today.  But large uncertainty in LSM predictions, and a poor ability to attribute the sources of that uncertainty, mean that new strategies are needed.  We identify three “grand challenges” facing LSM developers and propose strategies to help overcome these problems.

The Impact
This article, part of an invited collection of Grand Challenges papers published in AGU journals, seeks to focus LSM developers on the largest problems facing land surface science. We seek to galvanize the community to focus on problems related to process complexity, the many dimensions of sub-gridscale heterogeneity, and the representation of coupled physical-ecological dynamics, as key barriers in LSM science.

Summary
LSMs are critical pieces of Earth system models, needed for projection of the extent of global change, as well as impacts on critical terrestrial systems such as agriculture, freshwater resources, ecosystems, and built infrastructure. However, LSM predictions show a stubborn uncertainty that has been difficult to attribute to specific process representations and parameter values.  At the same time, the scope of LSMs has grown complex—for valid reasons—because of the many interacting processes that make up terrestrial systems. We argue that, as a first “Grand Challenge”, the LSM community must focus more clearly on the process complexity of LSMs, in order to better allow scaling from simplified models to highly interacting representation of a full LSM.  A second “Grand Challenge” relates to the differing views of heterogeneity in LSMs, which focus on various subsets and combinations of, e.g., disturbance, hillslopes, microclimate, vegetation communities, recent weather, snow depth, land management, and others.  But a general approach to identifying what are the dominant dimensions of heterogeneity at a given location, and how to most efficiently resolve that heterogeneity has not yet emerged.  A third “Grand Challenge” is on how to understand the dynamics of model parameters that are governed by complex interactions between physical and ecological dynamics; in particular we review three leading approaches: empirical, optimality-based, and competition-resolving, and identify questions about when to use each of these, how different aspects may and may not be combined, and what the implications are for each of these.

Contacts (BER PM): Renu Joseph and Dan Stover, Renu.Joseph@science.doe.gov (301-903-9237), and Daniel.Stover@science.doe.gov (301-903-0289) 

PI Contact: Charlie Koven, Staff Scientist, Lawrence Berkeley National Lab, cdkoven@lbl.gov, 510.486.6724

Funding
DOE Early Career Research Program, Rubisco SFA, NGEE-Tropics

Publications
Fisher, R. A., and Koven, C. D. (2020), Perspectives on the Future of Land Surface Models and the Challenges of Representing Complex Terrestrial Systems, Journal of Advances in Modeling Earth Systems, doi:10.1029/2018MS001453

The Science
The annual fluxes of carbon in the tropics play a critical role in regulating Earth’s climate and are highly sensitive to global change, however our process representation of the factors regulating tropical carbon uptake and loss in Earth System Models (ESMs) is poor. Tropical photosynthesis is an especially critical process to represent accurately in ESMs, yet we have very limited information on the spatial and temporal patterns of key parameters that regulate leaf level photosynthesis, such as the maximum carboxylation capacity (known as Vc,max). In addition, the tropics have the highest plant diversity of any terrestrial ecosystem on Earth making it very challenging for ESMs to capture the important variation in photosynthetic capacity across tropical species as well as with leaf age. This study investigated the capacity to provide much richer information on the spatial and seasonal variation in tropical Vc,max across a broad range of tree species using a spectroscopic approach, compared with traditional gas exchange methods.

The Impact
The seasonal and spatial variation in photosynthetic capacity of terrestrial vegetation strongly regulates seasonal to annual fluxes of carbon between the land and the atmosphere, yet ESMs currently lack a detailed representation of this variation given data limitations related to the logistical and technical challenges of collecting this data using traditional approaches. On the other hand, our spectroscopic approach presented here can be used to rapidly estimate plant photosynthetic capacity across a range of tropical species, leaf phenological stage, and locations paving the way for a broad-scale remote sensing approach capable of measuring photosynthetic properties over large areas and through time.

Summary
Traditionally, Vc,max is inferred from direct measurements of leaf photosynthetic carbon assimilation rate at saturating light and at different levels of atmospheric CO2 concentration to describe the “CO2 response curve” of a leaf, which is then used to derive the maximum carboxylation capacity, or Vc,max. This direct approach is considered the “gold standard” but is also very time consuming and can be logistically challenging in remote areas, such as the tropics. Instead, we explored the use of spectroscopy to estimate the Vc,max of tropical leaves using only leaf-level reflectance measurements. To do this we collected leaf age and Vc,max data and linked these with measurements of leaf reflectance from a range of species sampled from tropical forests in Panama and Brazil.  Our results showed that leaf spectroscopy can rapidly predict Vc,max across our species with high accuracy and low error. We also show that combining spectroscopic models enables the construction of the Vc,max-age relationship solely from leaf reflectance, suggesting that the spectroscopy technique can capture the seasonal variability in Vc,max in the tropics, potentially providing a powerful new way to inform ESMs.

Contacts (BER PM): Daniel Stover, SC-23.1, Daniel.Stover@science.doe.gov (301-903-0289) 

PI Contact: Shawn P. Serbin, Brookhaven National Laboratory,  sserbin@bnl.gov 

Funding
This work was supported by the Next-Generation Ecosystem Experiments (NGEE Tropics) project that is supported by the Office of Biological and Environmental Research in the Department of Energy, Office of Science.

Publications
Wu J, Rogers A, Albert LP, Ely K, Prohaska N, Wolfe BT, Oliveira Jr RC, Saleska SR, Serbin SP. 2019. Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests. New Phytologist 224(2): 663-674.

Related Links
Article URL:  https://nph.onlinelibrary.wiley.com/doi/full/10.1111/nph.16029
“Of Leaves and Light” BNL newsroom article: https://www.bnl.gov/newsroom/news.php?a=213279

The Science
Studies and raw data on root systems in Puerto Rican tropical forests, including data from Spanish-language publications not previously published in English, were synthesized and analyzed in comparison with other tropical studies, and gaps were exposed for future studies.

The Impact
Studies including root data in Puerto Rico are representative for the tropics. However, fine-root functional trait data for tropical ecosystems have not been fully explored. Our synthesis will be used to enrich root database representation for the tropics, and ultimately better inform Earth System Models.

Summary
Fine roots play an important role in plant nutrition, as well as in carbon, water and nutrient cycling. Fine roots account for a third of terrestrial net primary production (NPP), and inclusion of their structure and function in global carbon models should improve predictions of ecosystem responses to climate change. Unfortunately, studies focusing on underground plant components are much less frequent than those on aboveground structure. This disparity is more marked in the tropics, where one third of the planet’s terrestrial NPP is produced. Available tropical forest fine root data in Puerto Rico is overrepresented considering its land cover. This Caribbean island’s biodiversity, frequency of natural disturbances, ease of access to forests, and long-term plots have created an ideal place for the study of tropical ecological processes. This literature review emphasizes 50 years of root research and patterns revealed around Puerto Rico. The data in this review were compiled from scientific publications, conference reports, symposiums, and include new raw data shared by some researches. Emergent patterns for fine roots include the shallower distribution of fine roots compared to other tropical forests, the greater root:shoot ratio compared to other tropical metanalysis, the little variation in root phosphorus concentrations among forest types, and the slow recovery of root biomass after hurricane disturbance. Because more than half of the data on roots come from the wet tropical Luquillo Experimental Forest, other habitat types are under-represented. Gaps in knowledge about fine roots in Puerto Rico’s ecosystems are noted as examples to promote and guide future studies.

Contacts (BER PM): Daniel Stover, SC-23.1, Daniel.Stover@science.doe.gov (301-903-0289) 

PI Contact: Richard Norby, Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, rjn@ornl.gov, 865-576-5261

Funding
This research was supported as part of the Next Generation Ecosystem Experiments‐Tropics, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. Oak Ridge National Laboratory (ORNL) is managed by University of Tennessee (UT)-Battelle, LLC, for the U.S. Department of Energy under contractDE-AC05-00OR22725.

Publications
Yaffar D and Norby RJ. 2020. A historical and comparative review of 50 years of root data collection in Puerto Rico. Biotropica, DOI: 10.1111/btp.12771

The Science
Floods account for a significant and increasing number of reported natural hazards globally. As extreme precipitation is projected to increase in a warmer climate, there is an urgent need to improve understanding and modeling of floods to improve flood prediction and inform infrastructure planning. Analyses of flood characteristics have focused on using streamflow data, but flood inundation area has more direct societal and ecological implications.

A team led by scientists at the U.S. Department of Energy’s Pacific Northwest National Laboratory calibrated and evaluated a newly developed floodplain inundation model in the Energy Exascale Earth System Model (E3SM). Global simulations of flood inundation area for 1953-2004 revealed significant changes in flood generation mechanisms in some basins around the world. In the Amazon basin, for example, increasing concentration of extreme rainfall events within the wet season has increased its contribution to floods in the recent decades by synchronizing the occurrence of extreme rainfall more often with saturated soil in the wet season.

The Impact
Despite the complex and highly dynamic nature of flood processes, this study demonstrated the ability of a physically-based inundation model in E3SM for realistic simulation of floodplain inundation. Global simulations of flood inundation provided insights on the mechanisms for floods and their trends in major basins around the world.

Summary
In this study, scientists applied a newly developed, physically-based inundation model coupled with a river routing model (Model for Scale Adaptive River Transport, MOSART) within the Energy Exascale Earth System Model (E3SM) framework to investigate flood inundation dynamics. After calibration using observed streamflow and satellite-derived flood extent, the model was used to simulate global flood inundation from 1953 to 2004. The mean date and seasonality of annual maximum flood, defined based on flood extent, exhibit significant regional differences across 16 major basins.

Generally, soil moisture and monthly maximum daily rainfall are the dominant drivers of floods in tropical basins while monthly maximum daily snowmelt is the dominant driver in high latitude basins. From 1953-1982 to 1975-2004, significant changes in flood generation mechanisms are found in some basins such as Amazon, Lena, Yenisey, and Kolyma. Analysis of the rainfall seasonality and water balance at grid scale reveals during the later period, the occurrence of extreme rainfall has concentrated more in the wet season in the Amazon, which increases the co-occurrence of extreme rainfall and wet soil to produce flooding.  Fewer extreme rainfall events and increasing soil moisture reduced the contribution of monthly maximum rainfall and increased the role of monthly maximum snowmelt in floods in the Lena and Yenisey basins, respectively. Lastly, increased soil moisture and frequency of large monthly maximum snowmelt reduced the contribution of the latter to floods in the Kolyma basin. This study demonstrates the usefulness of the floodplain inundation model in E3SM for understanding floods and predicting their future changes.

Contacts (BER PMs): Sally McFarlane, Earth System Modeling Program Area, Sally.McFarlane@science.doe.gov
Dan Stover, Terrestrial Ecosystem Science Program, Dan.Stover@science.doe.gov

PI Contact: L. Ruby Leung, Pacific Northwest National Laboratory, Ruby.Leung@pnnl.gov

Funding
The U.S. Department of Energy Office of Science, Biological and Environmental Research supported this research as part of the Earth System Modeling Program Area through the Energy Exascale Earth System Model (E3SM) project. LRL was also supported by the Terrestrial Ecosystem Science Program through the Next Generation Ecosystem Experiment (NGEE) Tropics project.

Publication
Mao, Y., T. Zhou, L.R. Leung, T.K. Tesfa, H.-Y. Li, K. Wang, Z. Tan, and A. Getirana. 2019. “Flood Inundation Generation Mechanisms and Their Changes from 1953 to 2004 in Global Major River Basins.” J. Geophys. Res., doi:10.1029/2019JD031381.

Related Links
https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019JD031381

The Science
The effects of rising atmospheric CO2 on tropical forests have been the focus of a large body of research, and the question of whether intact tropical forests will act as a large CO2 sink remains contested. Evidence supporting a sink, using pan-tropical inventory analyses, has suggested that the Earth’s intact tropical forests sequester roughly half of the global net terrestrial sink. However, more recent studies show these biomass sinks to be overestimated, or no increased forest productivity with rising CO2. An additional research need is to directly compare predictions between two terrestrial modeling approaches that are at the forefront of earth system modeling, which differ in vegetation structure competitive processes (i.e. ‘big-leaf’ models and Vegetation Demographic Models (VDMs)).

The Impact
With a doubling of CO2, three of the four models used here predicted an appreciable biomass sink (0.77 to 1.24 Mg ha-1 yr-1). ELMv1-ECA, the only model that includes phosphorus constraints, predicted the lowest biomass sink relative to initial biomass stocks (+21%), lower than the other biogeochemical (BGC) model, CLM5 (+48%). Model projections differed primarily through variations in nutrient constraints, then carbon allocation, initial biomass, and density- dependent mortality. The VDM’s performance (ELM-FATES and ED2) was similar or better than the BGC models run in carbon-only mode, suggesting that nutrient competition in VDMs will improve predictions. We demonstrate that VDMs are comparable to non-demographic (i.e.,‘big-leaf’) models, but also include finer-scale demography and competition that can be evaluated against field observations.

These VDMs were designed to operate at the ESM scale, but have never been fully tested for this application. This study takes a step at showing the potential advantages of coupling FATES to an ESM’s land surface model by comparing ED2 with ELM-FATES, which displayed a more realistically constrained absolute biomass sink, net primary productivity (NPP) flux, mortality rates, and leaf area index (LAI) compared to ED2. We conclude that VDMs are applicable and fruitful at ESM scale (e.g., similarities or improved performance compared to unconstrained C-only big-leaf models), but more testing needs to be done over regional to global scales.

Summary
For this study we simulated an old-growth tropical forest using six versions of four terrestrial models differing in scale of vegetation structure, and representation of BGC cycling, all driven with CO2 forcing from the preindustrial period to 2100. The models were benchmarked against tree inventory and eddy covariance data from a Brazilian site for present-day predictions. A quasi-factorial design was used to test structured vegetation dynamics and plant competition for nutrients as two critical processes to tropical forest dynamics and CO2 fertilization responses (i.e., direct “CO2 effect” or β-response). In addition to results listed above, our results revealed that all models used here predicted positive vegetation growth that outpaced mortality for an intact Brazilian forest, leading to continual increases in present-day biomass accumulation. Interestingly, the field data indicated that a quarter of canopy trees didn’t grow over the 15-year period, and biomass change was near-neutral. The results found here and model testing will benefit both DOE’s E3SM Project and the NGEE-Tropics Project.

Contacts (BER PM): Dan Stover and Sally McFarlane, Daniel.Stover@science.doe.gov (301-903-0289) and Sally.McFarlane@science.doe.gov (301-903-0943)

PI Contact): Jeffrey Q. Chambers William J. Riley, Lawrence Berkeley National Lab, jchambers@lbl.gov, wjriley@lbl.gov

Funding
DE-AC02-05CH11231 as part of their Next Generation Ecosystem Experiment-Tropics (NGEE-Tropics) and the Energy Exascale Earth System (E3SM) Program, as well as Laboratory Directed Research and Development (LDRD) funding from Berkeley Lab, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research.

Publication
Holm, J. A., Knox, R. G., Zhu, Q., Fisher, R. A., Koven, C. D., Nogueira Lima, A. J., Riley, W. J., Longo, M., Negron-Juarez, R. I., Araujo, A. C. de., Kueppers, L. M., Moorcroft, P. R., Higuchi, N., Chambers, J. Q. ( 2020). The Central Amazon biomass sink under current and future atmospheric CO2: Predictions from big-leaf and demographic vegetation models. Journal of Geophysical Research: Biogeosciences, 125, e2019JG005500. https://doi.org/10.1029/2019JG005500.

The Science
This paper showed an increasingly stronger impact on terrestrial gross primary production (GPP) by extreme droughts than by mild and moderate droughts over the twenty-first century. Specifically, the percentage contribution by extreme droughts to the total GPP reduction associated with all droughts was projected to increase from ~28% during 1850–1999 to ~50% during 2075–2099. 

The Impact
Even though higher CO2 concentrations in future decades can increase GPP, low soil water availability and disturbances associated with droughts could reduce the benefits of such CO2 fertilization. This study conducted the first global analysis to quantify potential impacts of drought on future GPP, which could guide future modeling and field experiments.

Summary
Terrestrial gross primary production (GPP) is the basis of vegetation growth and food production globally and plays a critical role in regulating atmospheric CO2 through its impact on ecosystem carbon balance. Here we analysed outputs of 13 Earth system models to show an increasingly stronger impact on GPP by extreme droughts than by mild and moderate droughts over the twenty-first century. The droughts were defined on the basis of root-weighted plant accessible water. Due to a dramatic increase in the frequency of extreme droughts, the magnitude of globally averaged reductions in GPP associated with extreme droughts was projected to be nearly tripled by the last quarter of this century (2075–2099) relative to that of the historical period (1850–1999) under both high and intermediate greenhouse gas (GHG) emission scenarios. By contrast, the magnitude of GPP reductions associated with mild and moderate droughts was not projected to increase substantially. These drought impacts were widely distributed with particularly high risks for the Amazon, Southern Africa, Mediterranean Basin, Australia and Southwestern United States. Our analysis indicates a high risk of extreme droughts to the global carbon cycle with atmospheric warming; however, this risk can be potentially mitigated by positive anomalies of GPP associated with favorable environmental conditions.

Contacts (BER PM): Daniel Stover, SC-23.1, Daniel.Stover@science.doe.gov (301-903-0289)

PI Contact: Chonggang Xu, Los Alamos National Laboratory, Los Alamos, NM, Email: cxu@lanl.gov; Phone: 505-665-9773

Funding
This work was funded by the Next Generation Ecosystem Experiment–Tropics project and the Survival/Mortality project sponsored by the DOE Office of Science, Office of Biological and Environmental Research, the Laboratory Directed Research and Development program of the Los Alamos National Laboratory and the University of California’s Laboratory Fees Research Program (grant no. LFR-18-542511).

Publications
Xu, C., McDowell, N.G., Fisher, R.A. , L. Wei, S. Sevanto, E. Weng, R. Middleton. Increasing impacts of extreme droughts on vegetation productivity under climate change. Nature Climate Chang. 9, 948–953 (2019) doi:10.1038/s41558-019-0630-6

Related Links
https://www.nature.com/articles/s41558-019-0630-6