News Archive - NGEE

Age-dependent leaf physiology and consequences for crown-scale carbon

Photosynthetic Capacity of Branches Increases During the Dry Season in a Central Amazon Forest

First direct evidence from individual trees that new leaf growth and development cause overall forest green-up

The Science

Amazon forest ecosystems are observed by satellites to green-up and by towers to increase in photosynthetic uptake during the dry season, but the mechanisms for this at the tree and leaf scale have been much debated. Here we tested how leaf age-dependent physiology and leaf demography combine to affect photosynthetic capacity of a central Amazon forest during the dry season in a field-based study independent of remote sensing or eddy covariance methods. We found the first direct field evidence that branch-scale photosynthetic capacity increases during the dry season, with a magnitude consistent with increases in ecosystem-scale photosynthetic capacity derived from flux towers.

The Impact

This new study is the first to directly show the mechanistic basis for the much-debated Amazon forest dry season green up phenomenon. It highlights the role of endogenous phenological rhythms – not just seasonal variation in climate drivers – as a key mechanism regulating the seasonality of photosynthesis. This is important because in most earth system models, the seasonality of tropical evergreen ecosystems is driven by climatic seasonality, not biological phenology, and many of these models do not yet correctly simulate this pattern. This study thus strongly supports the incorporation of leaf phenology into earth system models as a means to represent our best understanding of the key processes regulating photosynthesis.

Summary

We conducted demographic surveys of leaf age composition, and measured age-dependence of leaf physiology in broadleaf canopy trees of abundant species at a central eastern Amazon site. Using a novel leaf-to-branch scaling approach, we used this data to independently test the much-debated hypothesis—arising from satellite and tower-based observations—that leaf phenology could explain the forest-scale pattern of dry season photosynthesis. We found that photosynthetic capacity, as indicated by parameters of biochemical limitations on photosynthesis (V_cmax, J_max, and TPU), was higher in recently matured leaves than either young or old leaves, and stomatal conductance was higher for recently matured leaves than old leaves. Most tree branches had several different leaf age categories simultaneously present, and the number of recently mature leaves on branches of our focal trees increased as the dry season progressed (before October 15 versus after October 15), as old leaves were exchanged for young leaves that then matured. Together, these findings suggest that aggregated whole-branch V_cmax increases during the dry season, with a magnitude consistent with increases in ecosystem-scale photosynthetic capacity observed from flux towers.

Contacts (BER PM)

Daniel Stover
SC-23.1
Daniel.Stover@science.doe.gov (301-903-0289)

(PI Contact)

Lead author contact information
Loren Albert
Brown University
loren_albert@brown.edu

Institutional contact

Scott Saleska
University of Arizona
saleska@email.arizona.edu

Funding

This project received U.S. DOE support through GoAmazon, award DE-SC0008383. It was also supported by the US National Science Foundation (NSF) (award OISE-0730305 to S. Saleska), the Philecology Foundation through University of Arizona Biosphere 2 and a Marshall Foundation of Arizona dissertation fellowship to L.P.Albert. J. Wu was supported in part by the Next-Generation Ecosystem Experiment (NGEE-Tropics) project of DOE’s Office of Biological and Environmental Research.

Publications

Albert, L.P., J. Wu, N Prohaska, P.B. de Camargo, T.E. Huxman, E.S. Tribuzy, V.Y. Ivanov, R.S. Oliveira, S. Garcia, M.N. Smith, RC Oliviera, Jr., N. Restrepo-Coupe, R. da Silva, S.C. Stark, G.A. Martins, D.V. Penha, S.R. Saleska. (2018) Age-dependent leaf physiology and consequences for crown-scale carbon uptake during the dry season in an Amazon evergreen forest. New Phytologist. DOI: 10.1111/nph.15056

Climate sensitive size-dependent survival in tropical trees

Climate Sensitive Size-dependent Survival in Tropical Trees

Survival of trees in the tropics can be grouped into four types and the abundance of each type is related to climatic factors.

The Science

Discovered size-dependent survival of tropical tree species is classifiable into four major categories of plants, is not related to common plant traits and whose abundance is related to climatic factors.

The Impact

Our work indicates the size-dependent models of forest dynamics can represent tropical forests survival dynamics with four groups of species. This can have a major impact on how we model forests at the global scale and improve our predictions of carbon in tropical forests which is an outstanding area of uncertainty thus far.

Summary

We found species were classifiable into four “survival modes” that explain life-history variation that shapes carbon-cycling and the relative abundances within forests. Frequently collected functional traits, such as wood density, leaf mass per area, and seed mass, were not generally predictive of species’ survival modes. Mean annual temperature and cumulative water deficit predicted the proportion of biomass of survival modes, indicating important links between evolutionary strategies, climate, and carbon cycling. The application of survival modes in demographic simulations predicted biomass change across forest sites. Our results reveal globally identifiable size-dependent survival strategies that differ across diverse systems in a consistent way. The abundance of survival modes and interaction with climate ultimately determine forest structure, carbon storage in biomass, and future forest trajectories.

Contacts (BER PM)

Daniel Stover
SC-23.1
Daniel.Stover@science.doe.gov (301-903-0289)

Dorothy Koch
SC-23.1
Dorothy.Koch@science.doe.gov (301-903-0105)

(PI Contact)

Nate McDowell
Pacific Northwest National Laboratory
nate.mcdowell@pnnl.gov

Funding

The development of this project benefited from ForestGEO workshops in 2015, 2016 and 2017 (NSF DEB-1046113 to S.J. Davies). Contributions by C. Xu, J. Chambers, S. Davies and N. McDowell were supported by the Next-Generation Ecosystem Experiments (NGEE-Tropics) project, funded by the U.S. Department of Energy, Office of Biological and Environmental Research. D. Johnson was supported by Los Alamos National Laboratory (Director’s Post-doctoral Fellowship).

Publications

DJ Johnson et al. (47 coauthors), “Climate sensitive size-dependent survival in tropical trees.” Nature Ecology and Evolution (2018). (in press)]

New DOE Earth System Model Released

The U.S. Department of Energy’s Energy Exascale Earth System Model (E3SM) project, supported by the Office of Science in the Biological and Environmental Research Office, released its new high-resolution earth modeling system to the broader scientific community on April 23, 2018. E3SM will have weather-scale resolution and use advanced computers to simulate aspects of Earth’s variability and anticipate decadal changes that will critically impact the U.S. energy sector in coming years. NGEE-Tropics’ next-generation dynamic vegetation model, FATES (the Functionally-Assembled Terrestrial Ecosystem Simulator), was fully integrated into E3SM and its land model in 2017, and continues to be an important part of E3SM’s model development and science campaigns.

Warm ENSO phase drives coordination between leaf and fruit phenology

Resource acquisition and reproductive strategies of tropical forest in response to the El Niño–Southern Oscillation

The Science
It has been suggested that tree phenology may be regulated by climatic oscillations. Here, we present a 30 year tropical forest dataset that suggests leaf and fruit production is coordinated with ENSO cycles, with greater leaf fall observed prior to El Niño followed by greater seed production.

Coordination between leafing and fruiting at multiple temporal scales. a Wavelet coherence between leaf fall and seed fall shows strong coordination at both seasonal and ENSO cycles (red regions). b Phase-angle histogram for leaf fall and seed fall for the seasonal cycle and c for periods of 2–7 years, corresponding to the ENSO cycle. Phase angles were calculated for areas inside the cone of influence and for coherence >0.5 in a. Negative angles (blue area) indicate that leaf fall leads seed fall

The Impact
The response of tropical forest to ENSO events and in general to drought and other environmental stress are still under exploration. Here, we show a relatively strong response of tropical phenology (fruiting and leafing) to a warming phase of ENSO. This discovery can help to understand the mechanisms of response or adaptation of plants to climate variability and pave the road to their implementation into Earth Ecosystem Models.

Summary
For the first time an interaction between phenophases of tropical plants (leafing and fruiting) is shown to be driven by large scale periodic climate variations. This interaction mirrors the dynamics between dry and wet season, suggesting adaptive strategies to optimize reproduction and resource acquisition in response to environmental stress.

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

(PI Contact)
Matteo Detto
Associate Researcher, Dept. of Ecology and Evolutionary Biology Princeton University and Smithsonian Tropical Research Institute
mdetto@princeton.edu

Funding
The Environmental Sciences Program of the Smithsonian Institution funded the data collection. Matteo Detto was partially supported by NGEE-Tropics. Raul Rios, Brian Harvey, and Steven Paton collected the BCI climate data.

Publications
Detto, M., Wright, S. J., Calderón, O. & Muller-Landau, H. C. Resource acquisition and reproductive strategies of tropical forest in response to the El Niño-Southern Oscillation. Nature Communications, 9, 1–8 (2018).

Rapid assessment of Hurricane Maria’s impact to Puerto Rico forests

On the early morning of September 20, 2017, Hurricane Maria made landfall in southeast Puerto Rico as a strong Category 4 storm with maximum sustained winds of ~250 kph. The powerful storm traveled the island in a northwesterly direction causing widespread destruction. This study focused on a rapid assessment of Hurricane Maria’s impact to Puerto Rico’s forests. Calibrated and corrected Landsat 8 image composites for the entire island were generated using Google Earth Engine for a comparable pre-Maria and post-Maria time period that accounted for phenology. Spectral mixture analysis (SMA) using image-derived endmembers was carried out on both composites to calculate the change in the non-photosynthetic vegetation (ΔNPV) spectral response, a metric that quantifies the increased fraction of exposed wood and surface litter associated with tree mortality and crown damage from the storm. Hurricane simulations were also conducted using the Weather Research and Forecasting (WRF) regional climate model to estimate wind speeds associated with forest disturbance. Dramatic changes in forest structure across the entire island were evident from pre- and post-Maria composited Landsat 8 images. A ΔNPV map for only the forested pixels illustrated significant spatial variability in disturbance, with emergent patterns associated with factors such as slope, aspect and elevation. An initial order-of-magnitude impact estimate based on previous work indicated that Hurricane Maria may have caused mortality and severe damage to 23-31 million trees. Additional field work and image analyses are required to further detail the impact of Hurricane Maria to Puerto Rico forests.

Other resources

Plant water potential improves prediction of empirical stomatal models

The Science

We find that current leaf-level empirical models over-predict stomatal conductance during drought conditions and a recently proposed model improves predictions during drought conditions.

The Impact

Including the impairment of soil-to-leaf water transport will improve predictions of stomatal conductance during drought conditions. Many biomes contain a diversity of plant stomatal strategies during water stress.

Summary

Ecosystem models rely on empirical relationships to predict stomatal responses to changing environmental conditions, but these are not well tested during drought conditions. We compiled datasets of stomatal conductance and leaf water potential for 34 woody plant species that span global forest biomes. We tested how well three major stomatal models and a recently proposed model predicted measured stomatal conductance. We found that current models consistently over predicted stomatal conductance during dry conditions whereas the recently proposed model, which includes loss of hydraulic transport capacity, improved predictions compared to current models, particularly during droughts. Our results also show that many biomes contain a diversity of plant stomatal strategies during water stress. Such improvements in stomatal simulation will help to predict the response of ecosystems to future climate extremes.

Contacts (BER PM)

Daniel Stover
SC-23.1
Daniel.Stover@science.doe.gov (301-903-0289)

Dorothy Koch
SC-23.1
Dorothy.Koch@science.doe.gov (301-903-0105)

(PI Contact)

William R. L. Anderegg
Univsersity of Utah
anderegg@utah.edu

Funding

Funding for this research was provided by NSF DEB EF-1340270 and the Climate Mitigation Initiative at the Princeton Environmental Institute, Princeton University. SL acknowledges financial support from the China Scholarship Council (CSC). VRD acknowledges funding from Ramón y Cajal fellowship (RYC-2012-10970). Brett T. Wolfe was supported by the Next Generation Ecosystem Experiments-Tropics, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. DJC acknowledges funding from the National Science Centre, Poland (NN309 713340). WRLA was supported in part by NSF DEB 1714972.

Publications

Anderegg WRL, Wolf A, Arango-Velez A, Choat B, Chmura DJ, Jansen S, Kolb T, Li S, Meinzer F, Pita P, Resco de Dios V, Sperry JS, Wolfe BT, Pacala S (2017), Plant water potential improves prediction of empirical stomatal models, PLOS ONE. DOI:10.1371/journal.pone.0185481