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FATES Vegetation-Fire Model Predicts Tropical Ecosystem Biogeography

Simulated feedback between fire behavior and vegetation traits drive emergent patterns.

Image courtesy of Jacquelyn K. Shuman, NASA Ames Research Center. Fire is an essential component of many ecosystems, shaping the distribution of trees and grasses. Managed fire, shown implemented in South Africa’s Kruger National Park, can be used to understand fuel moisture thresholds and fire behavior and effects.

Image courtesy of Jacquelyn K. Shuman, NASA Ames Research Center Fire is an essential component of many ecosystems, shaping the distribution of trees and grasses.  Managed fire, shown implemented in South Africa’s Kruger National Park, can be used to understand fuel moisture thresholds and fire behavior and effects.

The Science

Frequent fire can prevent trees from growing in drier regions of the tropics. In wet tropical forests, fire is infrequent and low intensity. Researchers adapted a model of fire behavior for use with a model of vegetation dynamics to capture this interaction between fire and trees in predictions of tropical ecosystems across climate gradients. The predictions captured the gradient from high to low biomass along with a transition from wet tropical forest to drier savanna and grassland across South America. This new modeling capability is essential to predicting how Amazon forest could change under future drier conditions.

The Impact

The dynamic interaction between fire and vegetation is not well represented in most global model predictions of the future climate and biosphere. Yet it is expected to be important to both. This work demonstrates an important new modeling capability that expands the potential applications for the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a vanguard vegetation model supported by the DOE. The model captures the feedback and interactions between fire, changing fuels, surviving tree canopies and local conditions, and can be used to project where tropical trees and grasses are likely to survive under future climate and fuel conditions.

Summary

To accurately project changes in fire and its impacts requires fire-vegetation models that integrate plant properties that affect fire behaviors and the response of vegetation distribution and structure to fire. We adapted the fire behavior and effects module, Spread and Intensity of Fire (SPITFIRE), for use with the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a size-structured vegetation demographic model, and tested model predictions of tropical forest and grassland biogeography. In the simulations, three types of vegetation competed for resources: a fire-vulnerable tree, a fire-tolerant tree, and a fire-promoting grass. We found the model sensitive to a parameter governing fuel moisture, with drier fuels expanding grass, fire-tolerant trees, and fire-burned area. Fire mortality was elevated for small and fire-vulnerable trees, as in observations. The model captured productivity and spatial biomass patterns in fire-disturbed forests, but was biased in less disturbed areas. Although burned fraction was predicted as greater than observed in grass-dominated areas, biogeography of fire-tolerant and fire-vulnerable trees corresponded to observations across the tropics. The results reflect a positive grass–fire feedback and suggest that infrequent-fire forests may be vulnerable to higher fire intensities. With SPITFIRE, FATES is useful for assessing the vulnerability and resilience of tropical forests to fire.

Contact

Jacquelyn Shuman
NASA Ames Research Center
jacquelyn.k.shuman@nasa.gov, 303-319-1509 

Funding

This esearch was supported as part of the Next Generation Ecosystem Experiments-Tropics (NGEE-Tropics), funded by the U.S. Department of Energy, Office of Science.

Publications

J.K. Shuman, et al. “Dynamic ecosystem assembly and escaping the “fire-trap” in the tropics: Insights from FATES_15.0.0.” Geoscientific Model Development 17, 4643–4671 (2024) [DOI: 10.5194/gmd-17-4643-2024]

Remotely sensed cyclone canopy damage metrics complement litterfall metrics

Tropical forest responses vary with cyclone intensity, frequency, soil phosphorus, and elevation

Image courtesy of Richard J. Norby: Tree and forest canopy damage near the El Verde Field Station in Puerto Rico shown from the ground about one year following Hurricane Maria.

The Science

Hurricanes damage forests across tropical regions. With some difficulty, damage to tree canopies is measured on the ground, but satellites can also detect this damage. Researchers evaluated how well tree canopy damage assessed from space matched with leaf and branch damage assessed on the ground. They found that these two types of measurements were related, and that wind speed, site history with hurricanes, elevation and soil fertility influence the amount of damage. Regrowth of leaves and branches occurred in just a few months. Ultimately, ground-and space-based measurements provide complementary views of hurricane effects. 

The Impact

Analysis of damage from the same storms using both ground and satellite data reveals strengths and limitations of satellite data for understanding damage. In particular, soil fertility can potentially influence the amount of canopy damage. It would be ideal to evaluate this across a much wider set of storms than have been observed from the ground, but this study indicates that care must be taken in interpreting results because the influence of soil fertility on ground and satellite measurements may differ.

Summary

Researchers obtained satellite images associated with hurricanes that had been studied using ground-based observations of litterfall. The study used two alternate vegetation indices derived from satellite images to assess hurricane damage and recovery affecting tropical forests in Hawaii, Puerto Rico, Mexico, Australia, and Taiwan between 2004 and 2017. Changes in leaf area index (LAI) and enhanced vegetation index (EVI) were found to moderately correlate (r = −0.52 and −0.60) with changes in ground-based litterfall measurements. The largest drops in LAI (−77%) and EVI (−77%) occurred in Mexico (Jalisco) and Puerto Rico, respectively. LAI recovered to pre-hurricane levels in about four months, and EVI in two months, while litterfall took ten months. LAI and EVI reductions were larger in forests with more phosphorus rich soil, but with low confidence. The historical frequency and intensity of hurricanes also influenced the amount of damage.

Contact

Dellena Bloom
University of Florida and Lawrence Berkeley National Laboratory
develyn.bloom@ufl.edu

Dr. Barbara Bomfim 
Lawrence Berkeley National Laboratory
bbomfim@lbl.gov or babomfimf@gmail.com

Funding

This research was supported as part of the Next Generation Ecosystem Experiments-Tropics (NGEE-Tropics), funded by the U.S. Department of Energy, Office of Science and by the U.S. Department of Energy, Office of Science, and Office of Workforce Development for Teachers and Scientists (WDTS) under the Science Undergraduate Laboratory Internship (SULI) program.

Publications

Bloom, D.E., et al. “Combining field and remote sensing data to estimate forest canopy damage and recovery following tropical cyclones across tropical regions” Environmental Research: Ecology 2 035004 (2023). [DOI: 10.1088/2752-664X/acfaa3]

 

Hysteresis area at the canopy level during and after a drought event in the Central Amazon

The changes in the hysteresis area during the 2015 ENSO drought compared to the post-drought period highlight the risk of hydraulic failure of tropical species under extreme heat stress.

Image credit B. Gimenez: I give full permission for this and other uses by BER. This image has not previously been published in any other format.  A view of the Amazon forest canopy using a telescopic boom lift (Genie Z80/60), maintained by the NGEE-tropics project and the National Institute of Amazonian Research (INPA).

The Science

During the 2015 ENSO-driven drought in the Central Amazon, canopy-level transpiration exhibited significant deviations due to exceptionally high Vapor Pressure Deficit (VPD) conditions and increased temporal differences between the peaks of stomatal conductance (gs) and VPD. This resulted in an increased hysteresis effect, as evidenced by the expanded hysteresis area (Harea) across multiple ecophysiological variables compared to the post-drought period. These canopy-level observations were developed using two distinct methods due to the difficulty of accessing canopy layers in the Amazon forest. First, species selection was determined by the proximity of the tree crown to the K-34 flux tower. The K-34 tower provided access to the crowns of a few species for leaf-level measurements. Additionally, we conducted leaf gas exchange experiments using, for the first time in the Amazon forest, a 26.0 m telescopic boom lift (Genie® Z-80/60) to access the canopy of multiple species.

The Impact

There are several challenges to performing in situ observations at the canopy level in tropical ecosystems such as the Amazon forest. This difficulty in conducting leaf-level measurements in the tropics is being overcome by the use of towers, climbing techniques, canopy walkways, canopy-access cranes (e.g., Panama and Daintree Forest in Australia), and, for the first time in a the Amazon forest, a telescopic boom lift (“cherry picker”) used as reported by this study (Manaus, ZF-2). This significant effort in the Amazon forest has provided new insights into leaf gas exchange processes and the access of multiple species at different canopy levels. From this perspective, understanding the patterns of stomatal conductance and leaf water potential across a range of species, along with canopy temperature and vapor pressure deficit measurements as demonstrated by this study, is crucial for improving the climate models in 21st century such as FATES, especially during extreme drought events.

Summary

Understanding forest water limitation during droughts within a warming climate is essential for accurate predictions of forest-climate interactions. In hyperdiverse ecosystems like the Amazon forest, the mechanisms shaping hysteresis patterns in transpiration relative to environmental factors are not well understood. From this perspective, we investigated these dynamics by conducting in situ leaf-level measurements throughout and after the 2015 El Niño-Southern Oscillation (ENSO) drought. Our findings indicate a substantial increase in the hysteresis area (Harea) among transpiration (E), vapor pressure deficit (VPD), and stomatal conductance (gs) at canopy level during the ENSO peak, attributed to both temporal lag and differences in magnitude between gs and VPD peaks. Specifically, the canopy species Pouteria anomala exhibited an increased Harea, due to earlier maximum gs rates leading to a greater temporal lag with VPD compared to the post-drought period. Additionally, leaf water potential (ΨL) and canopy temperature (Tcanopy) showed larger Harea during the ENSO peak compared to post-drought conditions across all studied species, suggesting that stomatal closure, particularly during the afternoon, acts to minimize water loss and may explain the counterclockwise hysteresis observed between ΨL and Tcanopy. The pronounced Harea during the drought points to a potential imbalance between water supply and demand, underlining the role of stomatal behavior of isohydric species in response to drought. 

Contact

Bruno O. Gimenez
University of California – Berkeley (UCB)
b_gimenez@berkeley.edu

Funding

This work  is based upon work supported as part of the Next Generation Ecosystem Experiments-Tropics (NGEE-Tropics), as part of DOE’s Terrestrial Ecosystem Science Program – Contract No. DE-AC02–05CH11231. Additional funding for this research was provided by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), INCT – Madeiras da Amazônia, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) – Processo: 403839/2021-1 Chamada CNPq/MCTI/FNDCT Nº 18/2021 – Faixa A – Grupos Emergentes Universal 2021, and Fundação de Amparo à Pesquisa do Estado do Amazonas (FAPEAM).

Publications

Gimenez, B. O., Souza, D. C., Higuchi, N., Negrón-Juárez, R. I., de Jesus Sampaio-Filho, I., Araújo, A. C., … & Chambers, J. Q. (2024). “Hysteresis area at the canopy level during and after a drought event in the Central Amazon” Agricultural and Forest Meteorology, 353, 110052. https://doi.org/10.1016/j.agrformet.2024.110052

Calibration of the SMAP soil moisture retrieval algorithm to reduce bias over the Amazon rainforest

Berkeley Lab Scientists using ground-based observations of soil moisture (SM) data from the Next Generation Ecosystem Experiment-Tropics (NGEE-Tropics) have shown that the NASA Soil Moisture Active Passive (SMAP) satellite has serious limitations in tropical rainforests. Ground-based observations of SM data were used to calibrate NASA SMAP but this calibration is site-dependent.

NASA SMAP soil moisture shows little seasonal variation (a), despite significant seasonal variation in rainfall (b). Based-period 2015-2019. Rainfall data is from Global Precipitation Measurements (GPM). (c) Sensitivity test of the τ–ω model used by SMAP algorithm to determine soil moisture at the NGEE-Tropics core site in Manaus.  Source Cho et al. 2024

 

The Science

Soil moisture (SM) is crucial for the Earth’s ecosystem, impacting climate and vegetation health. Obtaining in situ observations of SM is labor-intensive and complex, particularly in remote and densely vegetated regions like the Amazon rainforest. NASA’s Soil Moisture Active and Passive (SMAP) mission, utilizing an L-band radiometer, aims to monitor global SM. Yet, the performance of NASA SMAP SM over tropical forests has not been investigated due to scarce in-situ measurements. This study assessed and analyzed the SMAP SM retrievals in the Amazon, employing the single-channel algorithm (SCA) and adjusting vegetation optical depth (τ) and single scattering albedo (ω), two key vegetation parameters. The SMAP SM deviated substantially from the in-situ SM. However, calibrating τ and ω values, characterized by a lower τ, resulted in better agreement with the in-situ measurements.

The Impact

Our study emphasizes the pressing need for innovative methodologies to accurately retrieve SM in high vegetation water content regions like the Amazon rainforest using SMAP data. 

Contact

Robinson Negron-Juarez
Lawrence Berkeley National Laboratory
robinson.inj@lbl.gov

Funding

This study is sponsored by NASA SMAP Science Team Funding under agreement 80HQTR21T0064. Manaus soil moisture data is funded by the Next Generation Ecosystem Experiments-Tropics, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research.

Publications

Cho K, Negron-Juarez R, Colliander A, Cosio E, Salinas N, Araujo A, Chambers J, Wan J, Calibration of the SMAP soil moisture retrieval algorithm to reduce bias over the Amazon rainforest, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024), doi: http://doi.org/10.1109/JSTARS.2024.3388914 

 

Nutrient Dynamics in a Coupled Terrestrial Biosphere and Land Model (ELM-FATES-CNP)

Berkeley Lab scientists have expanded the capacity of a demographic vegetation model (FATES) to cycle nitrogen and phosphorus. This model is a component of Earth System Modeling, a tool that is used to make predictions and understand the current state of our planet’s water, carbon, and energy cycles.

*Note that in this diagram, N represents any nutrient, including nitrogen and phosphorus.

Image courtesy of Knox et al. (2024). Illustration by Diana Swantek, Lawrence Berkeley National Laboratory. Visualization of the dynamic interaction between differential carbon (C)and nutrient (N) storage and fine-root growth. A plant (left) with a proportionally more fine root will tend to have decreased carbon allocation and increased nutrient allocation, than a plant (right) with a proportionally less fine root. The algorithm presented here seeks to balance these allocations by modifying fine-root growth.

The Science

This research created numerical algorithms that represent how plants uptake mineralized nutrients from the soil, allocate nutrients to tissues and organs, and ultimately release it to litter for decomposition.  Model output was compared with observations at Barro Colorado Island (BCI) in Panama.  Of note, the relative supply of nutrients for each species of nitrogen and phosphorus, versus carbon in plant storage is directed to dynamically control the relative proportion of fine-roots, which enables interesting new plant competition and coexistence dynamics. 

The Impact

This new model capacity is critical to representing realistic pan-tropical and global vegetation response in a changing climate, and the net land carbon sink in Earth System Models.  

Contact

Ryan Knox
Lawrence Berkeley National Laboratory
rgknox@lbl.gov

Funding

Funding for this research was provided by the Department of Energy, Office of Science, Biological and Environmental Research (BER) Program, through the Next Generation Ecosystem Experiment – Tropics project.

Publications

Knox, R. G., Koven, C. D., Riley, W. J., Walker, A. P., Wright, S. J., Holm, J. A., et al. (2024). Nutrient dynamics in a coupled terrestrial biosphere and land model (ELM-FATES-CNP). Journal of Advances in Modeling Earth Systems, 16, e2023MS003689. https://doi.org/10.1029/2023MS003689. 

 

Functionally Assembled Terrestrial Ecosystem Simulator (FATES) for Hurricane Disturbance and Recovery

Factors determining hurricane disturbance and forest recovery in ELM-FATES

[Shi et al., 2024] The linear regression coefficient of biomass recovery (R recovery ) for experiments with varied hurricane mortality rates. (a) and (b) show the R recovery based on a relatively equal and realistic pre-hurricane biomass partition between plant types.

The Science

Hurricanes are affecting the tropical forests. This study uses the Functionally Assembled Terrestrial Ecosystem Simulator of the Energy Exascale Earth System Model Land Model (ELM-FATES). The model simulations in the Luquillo Experimental Forest (LEF) of Puerto Rico and the random forest feature importance imply that hurricane mortality and background mortality are the two major factors regulating post-hurricane forest recovery. Increased hurricane mortality leads to the transformation of the LEF into an ecosystem dominated by light-demanding plant functional types. ELM-FATES provides a reasonable representation of the seasonality of carbon and water fluxes at the LEF, when compared to various data products.

The Impact

This research improves understanding of the Functionally Assembled Terrestrial Ecosystem Simulator of the Energy Exascale Earth System Model (E3SM) Land Model (ELM-FATES) behavior associated with hurricane disturbance and post-hurricane forest recovery. This accomplishment involved conducting model simulations that incorporated hurricane disturbances of varying intensity at the Luquillo Experimental Forest of Northeast Puerto Rico. Additionally, random forest feature importance estimates were used in the process. This research provides guidance for ELM-FATES parameterization and dynamic vegetation model development in representing hurricane induced forest damage with various intensities. 

Summary

To enhance the understanding of forest recovery after hurricanes, we implemented hurricane induced forest damage into the Functionally Assembled Terrestrial Ecosystem Simulator, coupled with the Energy Exascale Earth System Model Land Model (ELM-FATES). We performed ensemble ELM-FATES simulations with varied forest damage intensities in the Luquillo Experimental Forest, Puerto Rico, and used the output to identify factors controlling the post-hurricane forest recovery, which was further evaluated with random forest feature importance (RFFI) that quantifies the sensitivity of the key model parameters to the post-hurricane forest recovery. The results imply that hurricane mortality and background mortality are the major factors regulating post-hurricane forest recovery. Changes to the intensity of simulated hurricanes could alter forest composition and structure during recovery, which modifies forest ecological processes and potentially shift the wet forests in Puerto Rico to states with increased vulnerability to tropical cyclones. This research enhances our understanding of the ELM-FATES model behavior associated with hurricane disturbance and broadens the application of RFFI in quantifying the parameter sensitivity of a dynamic global vegetation model (DGVM). This research addresses the essential role of representing hurricane induced forest damage in DGVMs, an advanced tool for the future studies of tropical forest dynamics. 

Contact

Mingjie Shi
Pacific Northwest National Laboratory
mingjie.shi@pnnl.gov 

Funding

This research was conducted at Pacific Northwest National Laboratory, operated for the U.S. Department of Energy by Battelle Memorial Institute under contract DE-AC05-76RL01830. This study was supported by the Department of Energy’s (DOE) Office of Biological and Environmental Research as part of the Terrestrial Ecosystem Science program through the Next-Generation Ecosystem Experiments (NGEE)-Tropics project.

Publications

Shi, M., Keller, M., Bomfim, B., Li, L.,et al. “Functionally assembled terrestrial ecosystem simulator (FATES) for hurricane disturbance and recovery.” Journal of Advances in Modeling Earth Systems, 16, e2023MS003679 (2024). [https://doi.org/10.1029/2023MS003679].

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