This page has only limited features, please log in for full access.
Forest disturbance and regrowth are key processes in forest dynamics, but detailed information on these processes is difficult to obtain in remote forests such as the Amazon. We used chronosequences of Landsat satellite imagery (Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus) to determine the sensitivity of surface reflectance from all spectral bands to windthrow, clear-cut, and clear-cut and burned (cut + burn) and their successional pathways of forest regrowth in the Central Amazon. We also assessed whether the forest demography model Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM-FATES, accurately represents the changes for windthrow and clear-cut. The results show that all spectral bands from the Landsat satellites were sensitive to the disturbances but after 3 to 6 years only the near-infrared (NIR) band had significant changes associated with the successional pathways of forest regrowth for all the disturbances considered. In general, the NIR values decreased immediately after disturbance, increased to maximum values with the establishment of pioneers and early successional tree species, and then decreased slowly and almost linearly to pre-disturbance conditions with the dynamics of forest succession. Statistical methods predict that NIR values will return to pre-disturbance values in about 39, 36, and 56 years for windthrow, clear-cut, and cut + burn disturbances, respectively. The NIR band captured the observed, and different, successional pathways of forest regrowth after windthrow, clear-cut, and cut + burn. Consistent with inferences from the NIR observations, ELM-FATES predicted higher peaks of biomass and stem density after clear-cuts than after windthrows. ELM-FATES also predicted recovery of forest structure and canopy coverage back to pre-disturbance conditions in 38 years after windthrows and 41 years after clear-cut. The similarity of ELM-FATES predictions of regrowth patterns after windthrow and clear-cut to those of the NIR results suggests the NIR band can be used to benchmark forest regrowth in ecosystem models. Our results show the potential of Landsat imagery data for mapping forest regrowth from different types of disturbances, benchmarking, and the improvement of forest regrowth models.
Robinson I. Negrón-Juárez; Jennifer A. Holm; Boris Faybishenko; Daniel Magnabosco-Marra; Rosie A. Fisher; Jacquelyn K. Shuman; Alessandro C. De Araujo; William J. Riley; Jeffrey Q. Chambers. Landsat near-infrared (NIR) band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon. Biogeosciences 2020, 17, 6185 -6205.
AMA StyleRobinson I. Negrón-Juárez, Jennifer A. Holm, Boris Faybishenko, Daniel Magnabosco-Marra, Rosie A. Fisher, Jacquelyn K. Shuman, Alessandro C. De Araujo, William J. Riley, Jeffrey Q. Chambers. Landsat near-infrared (NIR) band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon. Biogeosciences. 2020; 17 (23):6185-6205.
Chicago/Turabian StyleRobinson I. Negrón-Juárez; Jennifer A. Holm; Boris Faybishenko; Daniel Magnabosco-Marra; Rosie A. Fisher; Jacquelyn K. Shuman; Alessandro C. De Araujo; William J. Riley; Jeffrey Q. Chambers. 2020. "Landsat near-infrared (NIR) band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon." Biogeosciences 17, no. 23: 6185-6205.
Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early- and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.
Charles D. Koven; Ryan G. Knox; Rosie A. Fisher; Jeffrey Q. Chambers; Bradley O. Christoffersen; Stuart J. Davies; Matteo Detto; Michael C. Dietze; Boris Faybishenko; Jennifer Holm; Maoyi Huang; Marlies Kovenock; Lara M. Kueppers; Gregory Lemieux; Elias Massoud; Nathan G. McDowell; Helene C. Muller-Landau; Jessica F. Needham; Richard J. Norby; Thomas Powell; Alistair Rogers; Shawn P. Serbin; Jacquelyn K. Shuman; Abigail L. S. Swann; Charuleka Varadharajan; Anthony P. Walker; S. Joseph Wright; Chonggang Xu. Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama. Biogeosciences 2020, 17, 3017 -3044.
AMA StyleCharles D. Koven, Ryan G. Knox, Rosie A. Fisher, Jeffrey Q. Chambers, Bradley O. Christoffersen, Stuart J. Davies, Matteo Detto, Michael C. Dietze, Boris Faybishenko, Jennifer Holm, Maoyi Huang, Marlies Kovenock, Lara M. Kueppers, Gregory Lemieux, Elias Massoud, Nathan G. McDowell, Helene C. Muller-Landau, Jessica F. Needham, Richard J. Norby, Thomas Powell, Alistair Rogers, Shawn P. Serbin, Jacquelyn K. Shuman, Abigail L. S. Swann, Charuleka Varadharajan, Anthony P. Walker, S. Joseph Wright, Chonggang Xu. Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama. Biogeosciences. 2020; 17 (11):3017-3044.
Chicago/Turabian StyleCharles D. Koven; Ryan G. Knox; Rosie A. Fisher; Jeffrey Q. Chambers; Bradley O. Christoffersen; Stuart J. Davies; Matteo Detto; Michael C. Dietze; Boris Faybishenko; Jennifer Holm; Maoyi Huang; Marlies Kovenock; Lara M. Kueppers; Gregory Lemieux; Elias Massoud; Nathan G. McDowell; Helene C. Muller-Landau; Jessica F. Needham; Richard J. Norby; Thomas Powell; Alistair Rogers; Shawn P. Serbin; Jacquelyn K. Shuman; Abigail L. S. Swann; Charuleka Varadharajan; Anthony P. Walker; S. Joseph Wright; Chonggang Xu. 2020. "Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama." Biogeosciences 17, no. 11: 3017-3044.
Climatic extreme events are expected to occur more frequently and potentially be stronger in the future, increasing the likelihood of unprecedented climate extremes (UCEs), or record-breaking events such as prolonged droughts, to occur. To prepare for UCEs and their impacts, we need to develop a better understanding of terrestrial ecosystem responses to events such as extreme drought. We know that intense, extreme droughts can substantially affect ecosystem stability and carbon cycling through increased plant mortality and delaying ecosystem recovery. Our ability to predict such effects is limited due to the lack of experiments focusing on climatic excursions beyond the range of historical experience.
We explore the response of forest ecosystems to UCEs using two dynamic vegetation demographic models (VDMs), ED2 and LPJ-GUESS, in which the abundances of different plant functional types, as well as tree size- and age-class structure, are emergent properties of resource competition. We investigate the hypothesis that ecosystem responses to UCEs (e.g., unprecedented droughts) cannot be extrapolated from ecosystem responses to milder extremes, as a result of non-linear ecosystem responses (e.g. due to plant plasticity, functional diversity, and trait combinations). We evaluate each model’s mechanisms and state variables prior, during, and after a continuum of drought intensities ultimately reaching very extreme drought scenarios (i.e., 0% to 100% reduction in precipitation for drought durations of 1-year, 2-year, and 4-year scenarios) at two dry forested sites: Palo Verde, Costa Rica (i.e. tropical) and EucFACE, Australia (i.e. temperate). Both models produce nonlinear responses to these UCEs. Due to differences in model structure and process representation, the model’s sensitivity of biomass loss diverged based on either duration or intensity of droughts, as well as different model responses at each site. Biomass losses in ED2 are sensitive to drought duration, while in LPJ-GUESS they are mainly driven by drought intensity. Elevated atmospheric CO2 concentrations alone did not buffer the ecosystems from carbon losses during UCEs in the majority of our simulations. Our findings highlight discrepancies in process formulations and uncertainties in models, notably related to availability in plant carbohydrate storage and the diversity of plant hydraulic schemes. This shows that different hypotheses of plant responses to UCEs exist in two similar models, reflecting knowledge gaps, which should be tested with gap-informed field experiments. This iterative modeling-experiment framework would help improve predictions of terrestrial ecosystem responses and climate feedbacks.
Jennifer A. Holm; David M. Medvigy; Benjamin Smith; Jeffrey S. Dukes; Claus Beier; Mikhail Mishurov; Xiangtao Xu; Jeremy W. Lichstein; Craig D. Allen; Klaus S. Larsen; Yiqi Luo; Cari Ficken; William T. Pockman; William R.L. Anderegg; Anja Rammig. Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies. 2020, 1 .
AMA StyleJennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R.L. Anderegg, Anja Rammig. Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies. . 2020; ():1.
Chicago/Turabian StyleJennifer A. Holm; David M. Medvigy; Benjamin Smith; Jeffrey S. Dukes; Claus Beier; Mikhail Mishurov; Xiangtao Xu; Jeremy W. Lichstein; Craig D. Allen; Klaus S. Larsen; Yiqi Luo; Cari Ficken; William T. Pockman; William R.L. Anderegg; Anja Rammig. 2020. "Exploring the impacts of unprecedented climate extremes on forest ecosystems: hypotheses to guide modeling and experimental studies." , no. : 1.
There is large uncertainty whether Amazon forests will remain a carbon sink as atmospheric CO2 increases. Hence, we simulated an old‐growth tropical forest using six versions of four terrestrial models differing in scale of vegetation structure, and representation of biogeochemical (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. All models predicted positive vegetation growth that outpaced mortality, leading to continual increases in present‐day biomass accumulation. Notably, the two Vegetation Demographic Models (VDMs) (ED2 and ELM‐FATES) always predicted positive stem diameter growth in all size classes. The field data, however, indicated that a quarter of canopy trees didn't grow over the 15‐year period, and while high interannual variation existed, biomass change was near‐neutral. With a doubling of CO2, three of the four models predicted an appreciable biomass sink (0.77 to 1.24 Mg ha‐1 yr‐1). ELMv1‐ECA, the only model used here that includes phosphorus constraints, predicted the lowest biomass sink relative to initial biomass stocks (+21%), lower than the other BGC model, CLM5 (+48%). Models projections differed primarily through variations in nutrient constraints, then carbon allocation, initial biomass, and density‐ dependent mortality. The VDM's performance 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.
Jennifer A. Holm; Ryan G. Knox; Qing Zhu; Rosie A. Fisher; Charles D. Koven; Adriano J. Nogueira Lima; William J. Riley; Marcos Longo; Robinson I. Negrón‐Juárez; Alessandro C. de Araujo; Lara M. Kueppers; Paul R. Moorcroft; Niro Higuchi; Jeffrey Q. Chambers. The Central Amazon Biomass Sink Under Current and Future Atmospheric CO 2 : Predictions From Big‐Leaf and Demographic Vegetation Models. Journal of Geophysical Research: Biogeosciences 2020, 125, 1 .
AMA StyleJennifer A. Holm, Ryan G. Knox, Qing Zhu, Rosie A. Fisher, Charles D. Koven, Adriano J. Nogueira Lima, William J. Riley, Marcos Longo, Robinson I. Negrón‐Juárez, Alessandro C. de Araujo, Lara M. Kueppers, Paul R. Moorcroft, Niro Higuchi, Jeffrey Q. Chambers. The Central Amazon Biomass Sink Under Current and Future Atmospheric CO 2 : Predictions From Big‐Leaf and Demographic Vegetation Models. Journal of Geophysical Research: Biogeosciences. 2020; 125 (3):1.
Chicago/Turabian StyleJennifer A. Holm; Ryan G. Knox; Qing Zhu; Rosie A. Fisher; Charles D. Koven; Adriano J. Nogueira Lima; William J. Riley; Marcos Longo; Robinson I. Negrón‐Juárez; Alessandro C. de Araujo; Lara M. Kueppers; Paul R. Moorcroft; Niro Higuchi; Jeffrey Q. Chambers. 2020. "The Central Amazon Biomass Sink Under Current and Future Atmospheric CO 2 : Predictions From Big‐Leaf and Demographic Vegetation Models." Journal of Geophysical Research: Biogeosciences 125, no. 3: 1.
Forest disturbance and regrowth are key processes in forest dynamics but detailed information of these processes is difficult to obtain in remote forests as the Amazon. We used chronosequences of Landsat satellite imagery to determine the sensitivity of surface reflectance from all spectral bands to windthrow, clearcutting, and burning and their successional pathways of forest regrowth in the Central Amazon. We also assess whether the forest demography model Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM-FATES, accurately represents the changes for windthrow and clearcut. The results show that all spectral bands from Landsat satellite were sensitive to the disturbances but after 3 to 6 years only the Near Infrared (NIR) band had significant changes associated with the successional pathways of forest regrowth for all the disturbances considered. In general, the NIR decreased immediately after disturbance, increased to maximum values with the establishment of pioneers and early-successional tree species, and then decreased slowly and almost linearly to pre-disturbance conditions with the dynamics of forest succession. Statistical methods predict that NIR will return to pre-disturbance values in about 39 years (consistent with observational data of biomass regrowth following windthrows), and 36 and 56 years for clearcut and burning. The NIR captured the observed successional pathways of forest regrowth after clearcut and burning that diverge through time. ELM-FATES predicted higher peaks of initial forest responses (e.g., biomass, stem density) after clearcuts than after windthrows, similar to the changes in NIR. However, ELM-FATES predicted a faster recovery of forest structure and canopy-coverage back to pre-disturbance conditions for windthrows compared to clearcuts. The similarity of ELM-FATES predictions of regrowth patterns after windthrow and clearcut to those of the NIR results suggest that the dynamics of forest regrowth for these disturbances are represented with appropriate fidelity within ELM-FATES and useful as a benchmarking tool.
Robinson I. Negrón-Juárez; Jennifer A. Holm; Boris Faybishenko; Daniel Magnabosco-Marra; Rosie A. Fisher; Jacquelyn K. Shuman; Alessandro C. De Araujo; William J. Riley; Jeffrey Q. Chambers. Landsat NIR band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon. 2019, 2019, 1 -34.
AMA StyleRobinson I. Negrón-Juárez, Jennifer A. Holm, Boris Faybishenko, Daniel Magnabosco-Marra, Rosie A. Fisher, Jacquelyn K. Shuman, Alessandro C. De Araujo, William J. Riley, Jeffrey Q. Chambers. Landsat NIR band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon. . 2019; 2019 ():1-34.
Chicago/Turabian StyleRobinson I. Negrón-Juárez; Jennifer A. Holm; Boris Faybishenko; Daniel Magnabosco-Marra; Rosie A. Fisher; Jacquelyn K. Shuman; Alessandro C. De Araujo; William J. Riley; Jeffrey Q. Chambers. 2019. "Landsat NIR band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon." 2019, no. : 1-34.
Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include: (a) the number of competing PFTs present in any simulation, and (b) parameters that govern disturbance and height-based light competition. While single-PFT simulations are roughy consistent with observations of productivity at BCI, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e. the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early and late successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not, and to better understand the relationships between these two types of model parameters, to quantify sources of uncertainty in VDMs.
Charles D. Koven; Ryan G. Knox; Rosie A. Fisher; Jeffrey Chambers; Bradley O. Christoffersen; Stuart J. Davies; Matteo Detto; Michael C. Dietze; Boris Faybishenko; Jennifer Holm; Maoyi Huang; Marlies Kovenock; Lara M. Kueppers; Gregory Lemieux; Elias Massoud; Nathan G. McDowell; Helene C. Muller-Landau; Jessica F. Needham; Richard J. Norby; Thomas Powell; Alistair Rogers; Shawn P. Serbin; Jacquelyn K. Shuman; Abigail L. S. Swann; Charuleka Varadharajan; Anthony P. Walker; S. Joseph Wright; Chonggang Xu. Benchmarking and Parameter Sensitivity of Physiological and Vegetation Dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama. 2019, 2019, 1 -46.
AMA StyleCharles D. Koven, Ryan G. Knox, Rosie A. Fisher, Jeffrey Chambers, Bradley O. Christoffersen, Stuart J. Davies, Matteo Detto, Michael C. Dietze, Boris Faybishenko, Jennifer Holm, Maoyi Huang, Marlies Kovenock, Lara M. Kueppers, Gregory Lemieux, Elias Massoud, Nathan G. McDowell, Helene C. Muller-Landau, Jessica F. Needham, Richard J. Norby, Thomas Powell, Alistair Rogers, Shawn P. Serbin, Jacquelyn K. Shuman, Abigail L. S. Swann, Charuleka Varadharajan, Anthony P. Walker, S. Joseph Wright, Chonggang Xu. Benchmarking and Parameter Sensitivity of Physiological and Vegetation Dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama. . 2019; 2019 ():1-46.
Chicago/Turabian StyleCharles D. Koven; Ryan G. Knox; Rosie A. Fisher; Jeffrey Chambers; Bradley O. Christoffersen; Stuart J. Davies; Matteo Detto; Michael C. Dietze; Boris Faybishenko; Jennifer Holm; Maoyi Huang; Marlies Kovenock; Lara M. Kueppers; Gregory Lemieux; Elias Massoud; Nathan G. McDowell; Helene C. Muller-Landau; Jessica F. Needham; Richard J. Norby; Thomas Powell; Alistair Rogers; Shawn P. Serbin; Jacquelyn K. Shuman; Abigail L. S. Swann; Charuleka Varadharajan; Anthony P. Walker; S. Joseph Wright; Chonggang Xu. 2019. "Benchmarking and Parameter Sensitivity of Physiological and Vegetation Dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama." 2019, no. : 1-46.
Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's future climate. In the last decade, the vegetation component within ESMs has witnessed great progress from simple “big-leaf” approaches to demographically structured approaches, which have a better representation of plant size, canopy structure, and disturbances. These demographically structured vegetation models typically have a large number of input parameters, and sensitivity analysis is needed to quantify the impact of each parameter on the model outputs for a better understanding of model behavior. In this study, we conducted a comprehensive sensitivity analysis to diagnose the Community Land Model coupled to the Functionally Assembled Terrestrial Simulator, or CLM4.5(FATES). Specifically, we quantified the first- and second-order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks for a tropical site with an extent of 1×1∘. While the photosynthetic capacity parameter (Vc,max25) is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which determine survival and growth strategies within the model. The parameter sensitivity changes with different sizes of trees and climate conditions. The results of this study highlight the importance of understanding the dynamics of the next generation of demographically enabled vegetation models within ESMs to improve model parameterization and structure for better model fidelity.
Elias C. Massoud; Chonggang Xu; Rosie A. Fisher; Ryan G. Knox; Anthony P. Walker; Shawn P. Serbin; Bradley O. Christoffersen; Jennifer A. Holm; Lara M. Kueppers; Daniel M. Ricciuto; Liang Wei; Daniel J. Johnson; Jeffrey Q. Chambers; Charlie D. Koven; Nate G. McDowell; Jasper A. Vrugt. Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES). Geoscientific Model Development 2019, 12, 4133 -4164.
AMA StyleElias C. Massoud, Chonggang Xu, Rosie A. Fisher, Ryan G. Knox, Anthony P. Walker, Shawn P. Serbin, Bradley O. Christoffersen, Jennifer A. Holm, Lara M. Kueppers, Daniel M. Ricciuto, Liang Wei, Daniel J. Johnson, Jeffrey Q. Chambers, Charlie D. Koven, Nate G. McDowell, Jasper A. Vrugt. Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES). Geoscientific Model Development. 2019; 12 (9):4133-4164.
Chicago/Turabian StyleElias C. Massoud; Chonggang Xu; Rosie A. Fisher; Ryan G. Knox; Anthony P. Walker; Shawn P. Serbin; Bradley O. Christoffersen; Jennifer A. Holm; Lara M. Kueppers; Daniel M. Ricciuto; Liang Wei; Daniel J. Johnson; Jeffrey Q. Chambers; Charlie D. Koven; Nate G. McDowell; Jasper A. Vrugt. 2019. "Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES)." Geoscientific Model Development 12, no. 9: 4133-4164.
Katrin Fleischer; Anja Rammig; Martin G. De Kauwe; Anthony P. Walker; Tomas F. Domingues; Lucia Fuchslueger; Sabrina Garcia; Daniel S. Goll; Adriana Grandis; Mingkai Jiang; Vanessa Haverd; Florian Hofhansl; Jennifer A. Holm; Bart Kruijt; Felix Leung; Belinda E. Medlyn; Lina M. Mercado; Richard J. Norby; Bernard Pak; Celso Von Randow; Carlos A. Quesada; Karst J. Schaap; Oscar J. Valverde-Barrantes; Ying-Ping Wang; Xiaojuan Yang; Sönke Zaehle; Qing Zhu; David M. Lapola. Amazon forest response to CO2 fertilization dependent on plant phosphorus acquisition. Nature Geoscience 2019, 12, 736 -741.
AMA StyleKatrin Fleischer, Anja Rammig, Martin G. De Kauwe, Anthony P. Walker, Tomas F. Domingues, Lucia Fuchslueger, Sabrina Garcia, Daniel S. Goll, Adriana Grandis, Mingkai Jiang, Vanessa Haverd, Florian Hofhansl, Jennifer A. Holm, Bart Kruijt, Felix Leung, Belinda E. Medlyn, Lina M. Mercado, Richard J. Norby, Bernard Pak, Celso Von Randow, Carlos A. Quesada, Karst J. Schaap, Oscar J. Valverde-Barrantes, Ying-Ping Wang, Xiaojuan Yang, Sönke Zaehle, Qing Zhu, David M. Lapola. Amazon forest response to CO2 fertilization dependent on plant phosphorus acquisition. Nature Geoscience. 2019; 12 (9):736-741.
Chicago/Turabian StyleKatrin Fleischer; Anja Rammig; Martin G. De Kauwe; Anthony P. Walker; Tomas F. Domingues; Lucia Fuchslueger; Sabrina Garcia; Daniel S. Goll; Adriana Grandis; Mingkai Jiang; Vanessa Haverd; Florian Hofhansl; Jennifer A. Holm; Bart Kruijt; Felix Leung; Belinda E. Medlyn; Lina M. Mercado; Richard J. Norby; Bernard Pak; Celso Von Randow; Carlos A. Quesada; Karst J. Schaap; Oscar J. Valverde-Barrantes; Ying-Ping Wang; Xiaojuan Yang; Sönke Zaehle; Qing Zhu; David M. Lapola. 2019. "Amazon forest response to CO2 fertilization dependent on plant phosphorus acquisition." Nature Geoscience 12, no. 9: 736-741.
Vegetation plays a key role in regulating global carbon cycles and is a key component of the Earth System Models (ESMs) aimed to project Earth's future climates. In the last decade, the vegetation component within ESMs has witnessed great progresses from simple 'big-leaf' approaches to demographically-structured approaches, which has a better representation of plant size, canopy structure, and disturbances. The demographically-structured vegetation models are typically controlled by a large number of parameters, and sensitivity analysis is generally needed to quantify the impact of each parameter on the model outputs for a better understanding of model behaviors. In this study, we use the Fourier Amplitude Sensitivity Test (FAST) to diagnose the Community Land Model coupled to the Ecosystem Demography Model, or CLM4.5(ED). We investigate the first and second order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks. While the photosynthetic capacity parameter Vc,max25 is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which are shown here to determine vegetation demography and carbon stocks through their impacts on survival and growth strategies. The results of this study highlights the importance of understanding the dynamics of the next generation of demographically-enabled vegetation models within ESMs toward improved model parameterization and model structure for better model fidelity.
Elias C. Massoud; Chonggang Xu; Rosie Fisher; Ryan Knox; Anthony Walker; Shawn Serbin; Bradley Christoffersen; Jennifer Holm; Lara Kueppers; Daniel M. Ricciuto; Liang Wei; Daniel Johnson; Jeff Chambers; Charlie Koven; Nate McDowell; Jasper Vrugt. Identification of key parameters controlling demographicallystructured vegetation dynamics in a Land Surface Model [CLM4.5(ED)]. 2019, 2019, 1 -44.
AMA StyleElias C. Massoud, Chonggang Xu, Rosie Fisher, Ryan Knox, Anthony Walker, Shawn Serbin, Bradley Christoffersen, Jennifer Holm, Lara Kueppers, Daniel M. Ricciuto, Liang Wei, Daniel Johnson, Jeff Chambers, Charlie Koven, Nate McDowell, Jasper Vrugt. Identification of key parameters controlling demographicallystructured vegetation dynamics in a Land Surface Model [CLM4.5(ED)]. . 2019; 2019 ():1-44.
Chicago/Turabian StyleElias C. Massoud; Chonggang Xu; Rosie Fisher; Ryan Knox; Anthony Walker; Shawn Serbin; Bradley Christoffersen; Jennifer Holm; Lara Kueppers; Daniel M. Ricciuto; Liang Wei; Daniel Johnson; Jeff Chambers; Charlie Koven; Nate McDowell; Jasper Vrugt. 2019. "Identification of key parameters controlling demographicallystructured vegetation dynamics in a Land Surface Model [CLM4.5(ED)]." 2019, no. : 1-44.
Tree mortality is a key driver of forest community composition and carbon dynamics. Strong winds associated with severe convective storms are dominant natural drivers of tree mortality in the Amazon. Why forests vary with respect to their vulnerability to wind events and how the predicted increase in storm events might affect forest ecosystems within the Amazon are not well understood. We found that windthrows are common in the Amazon region extending from northwest (Peru, Colombia, Venezuela, and west Brazil) to central Brazil, with the highest occurrence of windthrows in the northwest Amazon. More frequent winds, produced by more frequent severe convective systems, in combination with well-known processes that limit the anchoring of trees in the soil, help to explain the higher vulnerability of the northwest Amazon forests to winds. Projected increases in the frequency and intensity of convective storms in the Amazon have the potential to increase wind-related tree mortality. A forest demographic model calibrated for the northwestern and the central Amazon showed that northwestern forests are more resilient to increase in wind-related tree mortality than forests in the central Amazon. Our study emphasizes the importance of including wind-related tree mortality in model simulations for reliable predictions of the future of tropical forests and their effects on the Earth' system.
Robinson I Negron-Juarez; Jennifer A Holm; Daniel Magnabosco Marra; Sami W Rifai; William J Riley; Jeffrey Q Chambers; Charles D Koven; Ryan G Knox; Megan E McGroddy; Alan V Di Vittorio; Jose Urquiza-Muñoz; Rodil Tello-Espinoza; Waldemar Alegria Muñoz; Gabriel H P M Ribeiro; Niro Higuchi. Vulnerability of Amazon forests to storm-driven tree mortality. Environmental Research Letters 2018, 13, 054021 .
AMA StyleRobinson I Negron-Juarez, Jennifer A Holm, Daniel Magnabosco Marra, Sami W Rifai, William J Riley, Jeffrey Q Chambers, Charles D Koven, Ryan G Knox, Megan E McGroddy, Alan V Di Vittorio, Jose Urquiza-Muñoz, Rodil Tello-Espinoza, Waldemar Alegria Muñoz, Gabriel H P M Ribeiro, Niro Higuchi. Vulnerability of Amazon forests to storm-driven tree mortality. Environmental Research Letters. 2018; 13 (5):054021.
Chicago/Turabian StyleRobinson I Negron-Juarez; Jennifer A Holm; Daniel Magnabosco Marra; Sami W Rifai; William J Riley; Jeffrey Q Chambers; Charles D Koven; Ryan G Knox; Megan E McGroddy; Alan V Di Vittorio; Jose Urquiza-Muñoz; Rodil Tello-Espinoza; Waldemar Alegria Muñoz; Gabriel H P M Ribeiro; Niro Higuchi. 2018. "Vulnerability of Amazon forests to storm-driven tree mortality." Environmental Research Letters 13, no. 5: 054021.
Jennifer A Holm; Skip J Van Bloem; Guy R Larocque; Herman H Shugart. Shifts in biomass and productivity for a subtropical dry forest in response to simulated elevated hurricane disturbances. Environmental Research Letters 2017, 12, 025007 .
AMA StyleJennifer A Holm, Skip J Van Bloem, Guy R Larocque, Herman H Shugart. Shifts in biomass and productivity for a subtropical dry forest in response to simulated elevated hurricane disturbances. Environmental Research Letters. 2017; 12 (2):025007.
Chicago/Turabian StyleJennifer A Holm; Skip J Van Bloem; Guy R Larocque; Herman H Shugart. 2017. "Shifts in biomass and productivity for a subtropical dry forest in response to simulated elevated hurricane disturbances." Environmental Research Letters 12, no. 2: 025007.
Jennifer A. Holm; Lara M. Kueppers; Jeffrey Chambers. Novel tropical forests: response to global change. New Phytologist 2017, 213, 988 -992.
AMA StyleJennifer A. Holm, Lara M. Kueppers, Jeffrey Chambers. Novel tropical forests: response to global change. New Phytologist. 2017; 213 (3):988-992.
Chicago/Turabian StyleJennifer A. Holm; Lara M. Kueppers; Jeffrey Chambers. 2017. "Novel tropical forests: response to global change." New Phytologist 213, no. 3: 988-992.
Tropical forests absorb large amounts of atmospheric CO2 through photosynthesis but elevated temperatures suppress this absorption and promote monoterpene emissions. Using 13CO2 labeling, here we show that monoterpene emissions from tropical leaves derive from recent photosynthesis and demonstrate distinct temperature optima for five groups (Groups 1–5), potentially corresponding to different enzymatic temperature‐dependent reaction mechanisms within β‐ocimene synthases. As diurnal and seasonal leaf temperatures increased during the Amazonian 2015 El Niño event, leaf and landscape monoterpene emissions showed strong linear enrichments of β‐ocimenes (+4.4% °C−1) at the expense of other monoterpene isomers. The observed inverse temperature response of α‐pinene (−0.8% °C−1), typically assumed to be the dominant monoterpene with moderate reactivity, was not accurately simulated by current global emission models. Given that β‐ocimenes are highly reactive with respect to both atmospheric and biological oxidants, the results suggest that highly reactive β‐ocimenes may play important roles in the thermotolerance of photosynthesis by functioning as effective antioxidants within plants and as efficient atmospheric precursors of secondary organic aerosols. Thus, monoterpene composition may represent a new sensitive ‘thermometer’ of leaf oxidative stress and atmospheric reactivity, and therefore a new tool in future studies of warming impacts on tropical biosphere‐atmosphere carbon‐cycle feedbacks.
Kolby Jardine; Angela B. Jardine; Jennifer A. Holm; Danica L. Lombardozzi; Robinson I. Negron-Juarez; Scot T. Martin; Harry Beller; Bruno Gimenez; Niro Higuchi; Jeffrey Chambers. Monoterpene ‘thermometer’ of tropical forest-atmosphere response to climate warming. Plant, Cell & Environment 2016, 40, 441 -452.
AMA StyleKolby Jardine, Angela B. Jardine, Jennifer A. Holm, Danica L. Lombardozzi, Robinson I. Negron-Juarez, Scot T. Martin, Harry Beller, Bruno Gimenez, Niro Higuchi, Jeffrey Chambers. Monoterpene ‘thermometer’ of tropical forest-atmosphere response to climate warming. Plant, Cell & Environment. 2016; 40 (3):441-452.
Chicago/Turabian StyleKolby Jardine; Angela B. Jardine; Jennifer A. Holm; Danica L. Lombardozzi; Robinson I. Negron-Juarez; Scot T. Martin; Harry Beller; Bruno Gimenez; Niro Higuchi; Jeffrey Chambers. 2016. "Monoterpene ‘thermometer’ of tropical forest-atmosphere response to climate warming." Plant, Cell & Environment 40, no. 3: 441-452.
We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties using the parameter space defined by the GLOPNET global leaf trait database. Furthermore, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked to each other, but we also find support for direct linkages to environmental conditions. We advocate intensified study of the costs and benefits of plant life history strategies in different environments and the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.
R. A. Fisher; S. Muszala; M. Verteinstein; P. Lawrence; C. Xu; N. G. McDowell; R. G. Knox; C. Koven; J. Holm; B. M. Rogers; A. Spessa; G. Bonan. Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes, CLM4.5(ED). Geoscientific Model Development 2015, 8, 3593 -3619.
AMA StyleR. A. Fisher, S. Muszala, M. Verteinstein, P. Lawrence, C. Xu, N. G. McDowell, R. G. Knox, C. Koven, J. Holm, B. M. Rogers, A. Spessa, G. Bonan. Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes, CLM4.5(ED). Geoscientific Model Development. 2015; 8 (11):3593-3619.
Chicago/Turabian StyleR. A. Fisher; S. Muszala; M. Verteinstein; P. Lawrence; C. Xu; N. G. McDowell; R. G. Knox; C. Koven; J. Holm; B. M. Rogers; A. Spessa; G. Bonan. 2015. "Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes, CLM4.5(ED)." Geoscientific Model Development 8, no. 11: 3593-3619.
Prolonged drought stress combined with high leaf temperatures can induce programmed leaf senescence involving lipid peroxidation, and the loss of net carbon assimilation during early stages of tree mortality. Periodic droughts are known to induce widespread tree mortality in the Amazon rainforest, but little is known about the role of lipid peroxidation during drought-induced leaf senescence. In this study, we present observations of green leaf volatile (GLV) emissions during membrane peroxidation processes associated with the combined effects of high leaf temperatures and drought-induced leaf senescence from individual detached leaves and a rainforest ecosystem in the central Amazon. Temperature-dependent leaf emissions of volatile terpenoids were observed during the morning, and together with transpiration and net photosynthesis, showed a post-midday depression. This post-midday depression was associated with a stimulation of C5 and C6 GLV emissions, which continued to increase throughout the late afternoon in a temperature-independent fashion. During the 2010 drought in the Amazon Basin, which resulted in widespread tree mortality, green leaf volatile emissions (C6 GLVs) were observed to build up within the forest canopy atmosphere, likely associated with high leaf temperatures and enhanced drought-induced leaf senescence processes. The results suggest that observations of GLVs in the tropical boundary layer could be used as a chemical sensor of reduced ecosystem productivity associated with drought stress.
Kolby J. Jardine; Jeffrey Q. Chambers; Jennifer A. Holm; Angela B. Jardine; Clarissa G. Fontes; Raquel F. Zorzanelli; Kimberly T. Meyers; Vinicius Fernadez De Souza; Sabrina Garcia; Bruno O. Gimenez; Luani Rosa De Oliveira Piva; Niro Higuchi; Paulo Artaxo; Scot Martin; Antônio O. Manzi. Green Leaf Volatile Emissions during High Temperature and Drought Stress in a Central Amazon Rainforest. Plants 2015, 4, 678 -690.
AMA StyleKolby J. Jardine, Jeffrey Q. Chambers, Jennifer A. Holm, Angela B. Jardine, Clarissa G. Fontes, Raquel F. Zorzanelli, Kimberly T. Meyers, Vinicius Fernadez De Souza, Sabrina Garcia, Bruno O. Gimenez, Luani Rosa De Oliveira Piva, Niro Higuchi, Paulo Artaxo, Scot Martin, Antônio O. Manzi. Green Leaf Volatile Emissions during High Temperature and Drought Stress in a Central Amazon Rainforest. Plants. 2015; 4 (3):678-690.
Chicago/Turabian StyleKolby J. Jardine; Jeffrey Q. Chambers; Jennifer A. Holm; Angela B. Jardine; Clarissa G. Fontes; Raquel F. Zorzanelli; Kimberly T. Meyers; Vinicius Fernadez De Souza; Sabrina Garcia; Bruno O. Gimenez; Luani Rosa De Oliveira Piva; Niro Higuchi; Paulo Artaxo; Scot Martin; Antônio O. Manzi. 2015. "Green Leaf Volatile Emissions during High Temperature and Drought Stress in a Central Amazon Rainforest." Plants 4, no. 3: 678-690.
We describe an implementation of the Ecosystem Demography (ED) concept in the Community Land Model. The structure of CLM(ED) and the physiological and structural modifications applied to the CLM are presented. A major motivation of this development is to allow the prediction of biome boundaries directly from plant physiological traits via their competitive interactions. Here we investigate the performance of the model for an example biome boundary in Eastern North America. We explore the sensitivity of the predicted biome boundaries and ecosystem properties to the variation of leaf properties determined by the parameter space defined by the GLOPNET global leaf trait database. Further, we investigate the impact of four sequential alterations to the structural assumptions in the model governing the relative carbon economy of deciduous and evergreen plants. The default assumption is that the costs and benefits of deciduous vs. evergreen leaf strategies, in terms of carbon assimilation and expenditure, can reproduce the geographical structure of biome boundaries and ecosystem functioning. We find some support for this assumption, but only under particular combinations of model traits and structural assumptions. Many questions remain regarding the preferred methods for deployment of plant trait information in land surface models. In some cases, plant traits might best be closely linked with each other, but we also find support for direct linkages to environmental conditions. We advocate for intensified study of the costs and benefits of plant life history strategies in different environments, and for the increased use of parametric and structural ensembles in the development and analysis of complex vegetation models.
R. A. Fisher; S. Muszala; M. Verteinstein; P. Lawrence; C. Xu; N. G. McDowell; R. G. Knox; C. Koven; J. Holm; B. M. Rogers; G. Bonan. Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes. Geoscientific Model Development Discussions 2015, 8, 3593 -3619.
AMA StyleR. A. Fisher, S. Muszala, M. Verteinstein, P. Lawrence, C. Xu, N. G. McDowell, R. G. Knox, C. Koven, J. Holm, B. M. Rogers, G. Bonan. Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes. Geoscientific Model Development Discussions. 2015; 8 (11):3593-3619.
Chicago/Turabian StyleR. A. Fisher; S. Muszala; M. Verteinstein; P. Lawrence; C. Xu; N. G. McDowell; R. G. Knox; C. Koven; J. Holm; B. M. Rogers; G. Bonan. 2015. "Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes." Geoscientific Model Development Discussions 8, no. 11: 3593-3619.
Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.
B. Bond-Lamberty; J. P. Fisk; J. A. Holm; Vanessa Bailey; G. Bohrer; C. M. Gough. Moderate forest disturbance as a stringent test for gap and big-leaf models. Biogeosciences 2015, 12, 513 -526.
AMA StyleB. Bond-Lamberty, J. P. Fisk, J. A. Holm, Vanessa Bailey, G. Bohrer, C. M. Gough. Moderate forest disturbance as a stringent test for gap and big-leaf models. Biogeosciences. 2015; 12 (2):513-526.
Chicago/Turabian StyleB. Bond-Lamberty; J. P. Fisk; J. A. Holm; Vanessa Bailey; G. Bohrer; C. M. Gough. 2015. "Moderate forest disturbance as a stringent test for gap and big-leaf models." Biogeosciences 12, no. 2: 513-526.
Uncertainties surrounding vegetation response to increased disturbance rates associated with climate change remains a major global change issue for Amazonian forests. Additionally, turnover rates computed as the average of mortality and recruitment rates in the western Amazon basin are doubled when compared to the central Amazon, and notable gradients currently exist in specific wood density and aboveground biomass (AGB) between these two regions. This study investigates the extent to which the variation in disturbance regimes contributes to these regional gradients. To address this issue, we evaluated disturbance–recovery processes in a central Amazonian forest under two scenarios of increased disturbance rates using first ZELIG-TROP, a dynamic vegetation gap model which we calibrated using long-term inventory data, and second using the Community Land Model (CLM), a global land surface model that is part of the Community Earth System Model (CESM). Upon doubling the mortality rate in the central Amazon to mirror the natural disturbance regime in the western Amazon of ∼2% mortality, the two regions continued to differ in multiple forest processes. With the inclusion of elevated natural disturbances, at steady state, AGB significantly decreased by 41.9% with no significant difference between modeled AGB and empirical AGB from the western Amazon data sets (104 vs. 107 Mg C ha−1, respectively). However, different processes were responsible for the reductions in AGB between the models and empirical data set. The empirical data set suggests that a decrease in wood density is a driver leading to the reduction in AGB. While decreased stand basal area was the driver of AGB loss in ZELIG-TROP, a forest attribute that does not significantly vary across the Amazon Basin. Further comparisons found that stem density, specific wood density, and basal area growth rates differed between the two Amazonian regions. Last, to help quantify the impacts of increased disturbances on the climate and earth system, we evaluated the fidelity of tree mortality and disturbance in CLM. Similar to ZELIG-TROP, CLM predicted a net carbon loss of 49.9%, with an insignificant effect on aboveground net primary productivity (ANPP). Decreased leaf area index (LAI) was the driver of AGB loss in CLM, another forest attribute that does not significantly vary across the Amazon Basin, and the temporal variability in carbon stock and fluxes was not replicated in CLM. Our results suggest that (1) the variability between regions cannot be entirely explained by the variability in disturbance regime, but rather potentially sensitive to intrinsic environmental factors; or (2) the models are not accurately simulating all tropical forest characteristics in response to increased disturbances.
J. A. Holm; Jeffrey Chambers; William D Collins; Niro Higuchi. Forest response to increased disturbance in the central Amazon and comparison to western Amazonian forests. Biogeosciences 2014, 11, 5773 -5794.
AMA StyleJ. A. Holm, Jeffrey Chambers, William D Collins, Niro Higuchi. Forest response to increased disturbance in the central Amazon and comparison to western Amazonian forests. Biogeosciences. 2014; 11 (20):5773-5794.
Chicago/Turabian StyleJ. A. Holm; Jeffrey Chambers; William D Collins; Niro Higuchi. 2014. "Forest response to increased disturbance in the central Amazon and comparison to western Amazonian forests." Biogeosciences 11, no. 20: 5773-5794.
The volatile gas isoprene is emitted in teragrams per annum quantities from the terrestrial biosphere and exerts a large effect on atmospheric chemistry. Isoprene is made primarily from recently fixed photosynthate; however, alternate carbon sources play an important role, particularly when photosynthate is limiting. We examined the relative contribution of these alternate carbon sources under changes in light and temperature, the two environmental conditions that have the strongest influence over isoprene emission. Using a novel real-time analytical approach that allowed us to examine dynamic changes in carbon sources, we observed that relative contributions do not change as a function of light intensity. We found that the classical uncoupling of isoprene emission from net photosynthesis at elevated leaf temperatures is associated with an increased contribution of alternate carbon. We also observed a rapid compensatory response where alternate carbon sources compensated for transient decreases in recently fixed carbon during thermal ramping, thereby maintaining overall increases in isoprene production rates at high temperatures. Photorespiration is known to contribute to the decline in net photosynthesis at high leaf temperatures. A reduction in the temperature at which the contribution of alternate carbon sources increased was observed under photorespiratory conditions, while photosynthetic conditions increased this temperature. Feeding [2-13C]glycine (a photorespiratory intermediate) stimulated emissions of [13C1–5]isoprene and 13CO2, supporting the possibility that photorespiration can provide an alternate source of carbon for isoprene synthesis. Our observations have important implications for establishing improved mechanistic predictions of isoprene emissions and primary carbon metabolism, particularly under the predicted increases in future global temperatures.
Kolby Jardine; Jeffrey Chambers; Eliane G. Alves; Andrea Teixeira; Sabrina Garcia; Jennifer A. Holm; Niro Higuchi; Antonio Manzi; Leif Abrell; Jose D. Fuentes; Lars Nielsen; Margaret Torn; Claudia Vickers. Dynamic Balancing of Isoprene Carbon Sources Reflects Photosynthetic and Photorespiratory Responses to Temperature Stress. Plant Physiology 2014, 166, 2051 -2064.
AMA StyleKolby Jardine, Jeffrey Chambers, Eliane G. Alves, Andrea Teixeira, Sabrina Garcia, Jennifer A. Holm, Niro Higuchi, Antonio Manzi, Leif Abrell, Jose D. Fuentes, Lars Nielsen, Margaret Torn, Claudia Vickers. Dynamic Balancing of Isoprene Carbon Sources Reflects Photosynthetic and Photorespiratory Responses to Temperature Stress. Plant Physiology. 2014; 166 (4):2051-2064.
Chicago/Turabian StyleKolby Jardine; Jeffrey Chambers; Eliane G. Alves; Andrea Teixeira; Sabrina Garcia; Jennifer A. Holm; Niro Higuchi; Antonio Manzi; Leif Abrell; Jose D. Fuentes; Lars Nielsen; Margaret Torn; Claudia Vickers. 2014. "Dynamic Balancing of Isoprene Carbon Sources Reflects Photosynthetic and Photorespiratory Responses to Temperature Stress." Plant Physiology 166, no. 4: 2051-2064.
Tropical trees are known to be large emitters of biogenic volatile organic compounds (BVOC), accounting for up to 75% of the global isoprene budget. Once in the atmosphere, these compounds influence multiple processes associated with air quality and climate. However, uncertainty in biogenic emissions is two-fold, (1) the environmental controls over isoprene emissions from tropical forests remain highly uncertain; and (2) our ability to accurately represent these environmental controls within models is lacking. This study evaluated the biophysical parameters that drive the global Model of Emissions of Gases and Aerosols from Nature (MEGAN) embedded in a biogeochemistry land surface model, the Community Land Model (CLM), with a focus on isoprene emissions from an Amazonian forest. Upon evaluating the sensitivity of 19 parameters in CLM that currently influence isoprene emissions by using a Monte Carlo analysis, up to 61% of the uncertainty in mean isoprene emissions was caused by the uncertainty in the parameters related to leaf temperature. The eight parameters associated with photosynthetic active radiation (PAR) contributed in total to only 15% of the uncertainty in mean isoprene emissions. Leaf temperature was strongly correlated with isoprene emission activity (R2 = 0.89). However, when compared to field measurements in the Central Amazon, CLM failed to capture the upper 10–14 °C of leaf temperatures throughout the year (i.e., failed to represent ~32 to 46 °C), and the spread observed in field measurements was not representative in CLM. This is an important parameter to accurately simulate due to the non-linear response of emissions to temperature. MEGAN-CLM 4.0 overestimated isoprene emissions by 60% for a Central Amazon forest (5.7 mg m−2 h−1 vs. 3.6 mg m−2 h−1), but due to reductions in leaf area index (LAI) by 28% in MEGAN-CLM 4.5 isoprene emissions were within 7% of observed data (3.8 mg m−2 h−1). When a slight adjustment to leaf temperature was made to match observations, isoprene emissions increased 24%, up to 4.8 mg m−2 h−1. Air temperatures are very likely to increase in tropical regions as a result of human induced climate change. Reducing the uncertainty of leaf temperature in BVOC algorithms, as well as improving the accuracy of replicating leaf temperature output in land surface models is warranted in order to improve estimations of tropical BVOC emissions.
J. A. Holm; K. Jardine; Alex B Guenther; Jeffrey Q Chambers; Edgard S Tribuzy. Evaluation of MEGAN-CLM parameter sensitivity to predictions of isoprene emissions from an Amazonian rainforest. Atmospheric Chemistry and Physics 2014, 1 .
AMA StyleJ. A. Holm, K. Jardine, Alex B Guenther, Jeffrey Q Chambers, Edgard S Tribuzy. Evaluation of MEGAN-CLM parameter sensitivity to predictions of isoprene emissions from an Amazonian rainforest. Atmospheric Chemistry and Physics. 2014; ():1.
Chicago/Turabian StyleJ. A. Holm; K. Jardine; Alex B Guenther; Jeffrey Q Chambers; Edgard S Tribuzy. 2014. "Evaluation of MEGAN-CLM parameter sensitivity to predictions of isoprene emissions from an Amazonian rainforest." Atmospheric Chemistry and Physics , no. : 1.