The Science
Much research has examined the sensitivity of tropical terrestrial ecosystems to various environmental drivers. The predictability of tropical vegetation greenness based on sea surface temperatures (SSTs), however, has not been well explored. This study employed fine spatial resolution remotely-sensed Enhanced Vegetation Index (EVI) and SST indices from tropical ocean basins to investigate the predictability of tropical vegetation greenness in response to SSTs and established empirical models with optimal parameters for hindcast predictions. Three evaluation metrics were used to assess the model performance, i.e., correlations between historical observed and predicted values, percentage of correctly predicted signs of EVI anomalies, and percentage of correct signs for extreme EVI anomalies. Our findings reveal that the pan-tropical EVI was tightly connected to the SSTs over tropical ocean basins. The strongest impacts of SSTs on EVI were identified mainly over the arid or semi-arid tropical regions.

The Impact
Our work provides a basis for the prediction of changes in greenness of tropical terrestrial ecosystems at seasonal to intra-seasonal scales. Moreover, the statistics-based observational relationships have the potential to facilitate the benchmarking of Earth System Models regarding their ability to capture the responses of tropical vegetation growth to long-term signals of oceanic forcings.

Summary
Three tropical regions, namely northeastern Brazil, eastern tropical Africa, and northern Australia, that are located in arid or semi-arid climate zones and covered mainly by sparse vegetation including open shrub, were found to be associated with evident influences of SSTs on vegetation growth and consequently high ecological predictability on seasonal to intra-seasonal time scales. Over the tropical rainforests, however, the weakest oceanic influences and thus lowest predictability were identified. The developed statistical models partially predicted the EVI dynamics based on selected SST indices over the pan tropics with limitations owing to the impacts from factors other than climate and model simplicity. As a future direction, more sophisticated statistical models will be tested. We will also evaluate the reliability of the statistics-based model for extracting key oceanic impacts on tropical terrestrial ecosystem production using dynamic experiments with an Earth system model, for example those from the High Resolution Model Intercomparison Project driven by observed SSTs. We will include vegetation data that is more physiologically related to plant photosynthesis, including the observation-based gross primary productivity and solar-induced fluorescence. Furthermore, dimension reduction techniques will be applied to quantify the leading modes of SSTs and precipitation and their relationships with vegetation greenness, thus to reduce dimensionality.

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

PI Contact: Jiafu Mao: Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, maoj@ornl.gov (865-576-7815)

Funding
Yan, J. Mao, X. Shi, F.M. Hoffman, N. Mcdowell, M. Xu, L. Gu and D.M. Ricciuto are supported by DOE Office of Science, Biological and Environmental Research, including support from the following programs: Terrestrial Ecosystem Science Program (NGEE-Tropics project); Regional and Global Climate Modeling Program (ORNL RUBISCO SFA).

Publications
Yan, B., J. Mao*, X. Shi, F. M. Hoffman, M. Notaro, T. Zhou, N. Mcdowell, R.E. Dickinson, M. Xu, L. Gu, and D.M. Ricciuto, Predictability of tropical vegetation greenness using sea surface temperatures. Environ. Res. Commun. 1 (2019) 031003. doi: 10.1088/2515-7620/ab178a.

The Science
Climate – specifically annual precipitation – modulates the speed with which water is transported through tropical trees.

The Impact
This study demonstrates that local climate plays an important role in the sap flux response of humid tropical forests to evaporative demand. Moreover, we highlight that trees growing in wetter regions in the tropics may be subjected to a reduced sap flux velocity with the high evaporative demand predicted by most climate models.

Summary
Transpiration in humid tropical forests modulates the global water cycle and is a key driver of climate regulation. Yet, our understanding of how tropical trees regulate sap flux in response to climate variability remain elusive. With a progressively warming climate, atmospheric evaporative demand (i.e., vapor pressure deficit, VPD) will be increasingly important for plant functioning, becoming the major control of plant water use in the 21st century. Using measurements in 34 tree species at seven sites across a precipitation gradient in the neotropics, we determined how the maximum sap flux velocity (vmax) and the VPD threshold at which vmax is reached (VPDmax) vary with precipitation regime (mean annual precipitation, MAP; seasonal drought intensity, PDRY) and two functional traits related to foliar and wood economics spectra (leaf mass per area, LMA; wood specific gravity, WSG). We show that, even though vmax is highly variable within sites, it follows a negative trend in response to increasing MAP and PDRY across sites. LMA and WSG exerted little effect on vmax and VPDmax, suggesting that these widely-used functional traits provide limited explanatory power of dynamic plant responses to environmental variation within hyper-diverse forests. This study demonstrates that long-term precipitation plays an important role in the sap flux response of humid tropical forests to VPD. Our findings suggest that under higher evaporative demand, trees growing in wetter environments in humid tropical regions may be subjected to reduced water exchange with the atmosphere relative to trees growing in drier climates.

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

PI Contact: Grossiord Charlotte(1) & Brad Christoffersen(2), (1) Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf 8903, Switzerland; (2) Department of Biology and School of Earth, Environmental, and Marine Sciences, University of Texas Rio Grande Valley, Edinburg, TX, USA; charlotte.grossiord@wsl.ch; bradley.christoffersen@utrgv.edu

Funding
This project was supported in part by the Next Generation Ecosystem Experiments Tropics, funded by the US Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Sciences Program, under Award Number DE-SC-0011806. CG was supported by the Swiss National Science Foundation SNF (5231.00639.001.01). BC was supported in part by the Laboratory Directed Research and Development Program Project 8872 of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U. S. Department of Energy. This work has benefited from an “Investissements d’Avenir” grant managed by Agence Nationale de la Recherche (CEBA, ref. ANR-10-LABX-25-01). Data recorded in French Guiana (FRG) were collected at the Guyaflux sites which belong to the SOERE F-ORE-T and is supported annually by Ecofor, Allenvi and the French national research infrastructure, ANAEE-F.

Publications
Grossiord, B. Christoffersen et al., “Precipitation mediates sap flux sensitivity to evaporative demand in the neotropics.” Oecologia (2019), doi: 10.1007/s00442-019-04513-x

Related Links
https://link.springer.com/article/10.1007/s00442-019-04513-x

The Science
Very few trees die. That results in very sparse information and great uncertainty about mortality. This work develops a technique to use spatial information to increase accuracy in the estimation of mortality.

The Impact
The general method described here, with modifications, could be applied to reduce uncertainty in the estimation of proportions related to any temporally or spatially structured phenomenon with two possible outcomes.

Summary
Many ecological applications, like the study of mortality rates, require the estimation of proportions and confidence intervals for them. The traditional way of doing this applies the binomial distribution, which describes the outcome of a series of Bernoulli trials. This distribution assumes that observations are independent and the probability of success is the same for all the individual observations. Both assumptions are obviously false in many cases. I show how to apply bootstrap and the Poisson binomial distribution (a generalization of the binomial distribution) to the estimation of proportions. Any information at the individual level would result in better (narrower) confidence intervals around the estimation of proportions. As a case study, I applied this method to the calculation of mortality rates in a forest plot of tropical trees in Lambir Hills National Park, Malaysia. I calculated central estimates and 95% confidence intervals for species‐level mortality rates for 1,007 tree species. I used a very simple model of spatial dependence in survival to estimate individual‐level risk of mortality. The results obtained by accounting for heterogeneity in individual‐level risk of mortality were comparable to those obtained with the binomial distribution in terms of central estimates, but the precision increased in virtually all cases, with an average reduction in the width of the confidence interval of ~20%. Spatial information allows the estimation of individual‐level probabilities of survival, and this increases the precision in the estimates of mortality rates. The general method described here, with modifications, could be applied to reduce uncertainty in the estimation of proportions related to any spatially structured phenomenon with two possible outcomes. More sophisticated approaches can yield better estimates of individual‐level mortality and thus narrower confidence intervals.

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

PI Contact: Gabriel Arellano, University of Michigan, gabriel.arellano.torres@gmail.com

Funding
This study was developed as part of the Next Generation Ecosystem Experiments‐Tropics, funded by the U.S. Department of Energy (Office of Science, Office of Biological and Environmental Research). The Lambir 52‐ha plot was established as a collaboration between the Forest Department of Sarawak, Malaysia, Harvard University (NSF awards DEB‐9107247 and DEB‐9629601) and Osaka City University (grants 06041094, 08NP0901 and 09NP0901). The research has been supported by the Asia program of the Arnold Arboretum (Harvard University), the Center for Tropical Forest Science (Smithsonian Tropical Research Institute), the NSF award DEB‐1545761 to Stuart J. Davies, and the Sarawak Forest Department.

Publications
Arellano, G. (2019), Calculation of narrower confidence intervals for tree mortality rates when we know nothing but the location of the death/survival events, Ecology and Evolution, 9, 9644-9653. [DOI: https://doi.org/10.1002/ece3.5495]

Related Links
https://onlinelibrary.wiley.com/doi/abs/10.1002/ece3.5495

The Science
The role of phosphorus availability has not been considered in any of the CMIP5 models. This study shows that phosphorus availability could greatly reduce the projected CO2-induced carbon sink in Amazon rainforests. This study suggests that the Amazon rainforest response to increasing atmospheric CO2 depends upon the ability of trees to up-regulate phosphorus acquisition in response to increased carbon availability.

The Impact
Currently CMIP5 models predict that the Amazon rainforest will continue to act as carbon sinks in the future due to the CO2 fertilization effect. However the role of phosphorus availability (which is impoverished across the Amazon Basin yet controls forest functioning) has not been considered within CMIP5 simulations. This study suggests that the CMIP5 predicted carbon sink would likely be much less due to phosphorus limitation, suggesting Amazon rainforests may be less resilient to climate change than previously assumed.

Summary
An ensemble of 14 terrestrial ecosystem models was used to simulate the planned free-air CO2 enrichment experiment AmazonFACE. Model simulations showed that phosphorus availability reduced the projected CO2-induced carbon sink by about 50% compared to estimates from models assuming no phosphorus limitation. Large variations in ecosystem responses to elevated CO2 among Phosphorus-enabled models (ranging from 5 to 140 g Carbon m-2 yr-2 in biomass carbon response) are mainly due to contrasting representations of plant phosphorus use and acquisition strategies among models. This study highlights the importance of phosphorus acquisition and use, including alternative strategies, in Amazon rainforest responses to increasing atmospheric CO2 concentration.

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

PI Contact: Jeffrey Q. Chambers, Lawrence Berkeley National Lab, jchambers@lbl.gov

Funding
DE-AC02-05CH11231 as part of their Next Generation Ecosystem Experiment-Tropics (NGEE-Tropics) and Exascale Energy Earth System Model (E3SM) programs.

Publication
Fleischer K, A. Rammig, M.G. De Kauwe, A. P. Walker, T.F. Domingues, L. Fuchslueger, S. Garcia, D. Goll, A. Grandis, M. Jiang, V.E. Haverd, F. Hofhansl, J. Holm, B. Kruijt, F. Leung, B. Medlyn, L.M. Mercado, R.J. Norby, B.C. Pak, B. Quesada, C. von Randow, K. Schaap, O. Valverde-Barrantes, Y. Wang, X. Yang, S. Zaehle, Q. Zhu, D. Lapola. Amazon forest responses to CO2 fertilization dependent on plant phosphorus acquisition, Nature Geoscience, https://doi.org/10.1038/s41561-019-0404-9, 2019.

The Science
In the Amazon basin, an estimated 25–50% of precipitation is recycled back to the atmosphere through forest transpiration, with important implications for the interactions between the biosphere and atmosphere. In this study, we present in situ field observations of environmental (direct solar radiation, air temperature (Tair) and vapor pressure deficit (VPD)) and physiological (sap velocity (Vs), stomatal conductance (gs), and leaf water potential (ΨL)) variables and their correlations with leaf temperature (Tleaf) during the 2015–2016 El Niño-Southern Oscillation (ENSO). In order to observe the interactions between physiological variables and fast changing environmental conditions, we collected high temporal frequency data (15–60 min) in two primary rainforest sites located in the Eastern (Santarém) and in the Central (Manaus) Amazon. Since the 2015–2016 ENSO event was the warmest period in the Amazon forest over the past 13 years, we expected peak Tleaf to increase and subsequently hysteretic behavior of water use vs. Tleaf to become more pronounced. In this study, we explored the mechanisms that regulate tree transpiration and the diurnal hysteresis patterns between physiological and environmental variables to contrast different tree species responses to the extreme 2015 dry season (ENSO) and a normal 2017 dry season (“control scenario”).

The Impact
Despite expectations of a significant delay due to the large vertical distance between the observations of sap velocity (Vs) and leaf temperature (Tleaf), the two variables tightly track each other, during the day and night. On some days during the 2015 dry season, the differences between Tleaf and Tair were close to 8°C for some species (average difference between Tleaf and Tair for all species: 1.65 ± 1.07°C). For the first time in the Amazon forest, the quantitative differences and the hysteresis pattern between Tleaf and Tair were demonstrated and compared during the 2015 (ENSO) and 2017 (“control scenario”) dry seasons. The relationship between Tleaf and Tair was significantly different between these two periods and, in general, Tleaf was higher than Tair during the middle morning to early afternoon. The use of the variable Tleaf together with Tair is extremely important to ecophysiological observations due to the differences in terms of magnitude and temporal patterns. Also, Tleaf is an important variable to estimate the true water vapor pressure gradient between the substomatal cavity and the boundary layer of the air near the leaf surface (ΔVPD).

Sap velocity displayed species-specific diurnal hysteresis patterns that were strongly linked to gs and ΔVPD and reflected by changes in Tleaf. In the morning, gs was linearly related to Tleaf and sap velocity displayed a sigmoidal relationship with Tleaf. In the afternoon, stomatal conductance declined as Tleaf approached a daily peak, allowing ΨL to begin recovery, while sap velocity declined with an exponential relationship with Tleaf. Hysteresis indices (Tleaf : Tair and Tleaf : ΨL) were much more pronounced during the ENSO event than during a typical dry season and varied between species, which reflects species-specific capacitance and tree hydraulic traits. The clockwise hysteresis in Vs-Tleaf and Vs-ΔVPD was evident with morning periods showing higher temperature sensitivities than afternoon and night periods and in this study is referred to as the “gs effect”. In Manaus, the scatter plot of Vs-direct solar radiation revealed a counterclockwise hysteresis pattern, on the same day as the Vs-ΔVPD clockwise hysteresis. For the same direct solar radiation values, higher Vs values in the afternoon were observed relative to the morning period, and in this study this pattern is referred to as the “VPD effect.”

Summary
Current climate change scenarios indicate warmer temperatures and the potential for more extreme droughts in the tropics, such that a mechanistic understanding of the water cycle from individual trees to landscapes is needed to adequately predict future changes in forest structure and function. In this study, we contrasted physiological responses of tropical trees during a normal dry season with the extreme dry season due to the 2015–2016 El Niño-Southern Oscillation (ENSO) event. We quantified high resolution temporal dynamics of sap velocity (Vs), stomatal conductance (gs) and leaf water potential (ΨL) of multiple canopy trees, and their correlations with leaf temperature (Tleaf) and environmental conditions [direct solar radiation, air temperature (Tair) and vapor pressure deficit (VPD)]. The experiment leveraged canopy access towers to measure adjacent trees at the ZF2 and Tapajós tropical forest research (near the cities of Manaus and Santarém). The temporal difference between the peak of gs (late morning) and the peak of VPD (early afternoon) is one of the major regulators of sap velocity hysteresis patterns. Sap velocity displayed species-specific diurnal hysteresis patterns reflected by changes in Tleaf. In the morning, Tleaf and sap velocity displayed a sigmoidal relationship. In the afternoon, stomatal conductance declined as Tleaf approached a daily peak, allowing ΨL to begin recovery, while sap velocity declined with an exponential relationship with Tleaf. In Manaus, hysteresis indices of the variables Tleaf-Tair and ΨL-Tleaf were calculated for different species and a significant difference (p < 0.01, α = 0.05) was observed when the 2015 dry season (ENSO period) was compared with the 2017 dry season (“control scenario”). In some days during the 2015 ENSO event, Tleaf approached 40°C for all studied species and the differences between Tleaf and Tair reached as high at 8°C (average difference: 1.65 ± 1.07°C). Generally, Tleaf was higher than Tair during the middle morning to early afternoon, and lower than Tair during the early morning, late afternoon and night. Our results support the hypothesis that partial stomatal closure allows for a recovery in ΨL during the afternoon period giving an observed counterclockwise hysteresis pattern between ΨL and Tleaf.

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

PI Contact: Bruno O. Gimenez, Smithsonian Tropical Research Institute (STRI), bruno.oliva.gimenez@gmail.com
Kolby J. Jardine, Lawrence Berkeley National Laboratory (LBNL), Climate and Ecosystem Sciences Division, kjjardine@lbl.gov

Funding
This material is based upon work supported as part of the Next Generation Ecosystem Experiments-Tropics (NGEE-Tropics) funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research through contract No. DE-AC02-05CH11231 to LBNL, as part of DOE’s Terrestrial Ecosystem Science Program. Additional funding for this research was provided by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).

Publications
Gimenez B., Jardine K., Higuchi N., Negrón-Juárez R., Sampaio-Filho I., Cobello L., Fontes C., Dawson T., Varadharajan C., Christianson D., Spanner G., Araújo A., Warren J., Newman B., Holm J., Koven C., McDowell N., Chambers J., (2019) Species-Specific Shifts in Diurnal Sap Velocity Dynamics and Hysteretic Behavior of Ecophysiological Variables During the 2015-2016 El Niño Event in the Amazon Forest Front. Plant Sci. 10:830. https://doi.org/10.3389/fpls.2019.00830

Related Links
https://www.frontiersin.org/articles/10.3389/fpls.2019.00830/full

The Science
During El Niño events, atmospheric teleconnections with sea surface temperature (SST) anomalies in the equatorial Pacific cause higher temperatures and reduced rainfall in the Amazon, leading to increased CO2 emissions. While some of the temperature increase results directly from the SST-atmosphere teleconnection, drier soil resulting from reduced rainfall can also contribute to higher temperatures and resulting CO2 flux anomalies. Researchers from the University of California, Irvine and the Oak Ridge National Laboratory modified the Energy Exascale Earth System Model (E3SM) to decouple the direct effects of SST anomalies from the resulting soil moisture anomalies, in order to determine the relative importance of each of these drivers.

The Impact
Soil moisture variability was found to amplify and extend the effects of SST forcing on eastern Amazon temperature and carbon fluxes in E3SM. During the wet season, the direct, circulation-driven effect of El NIño-Southern Oscillation (ENSO) SST anomalies dominated temperature and carbon cycle variability throughout the Amazon. During the following dry season, after ENSO SST anomalies had dissipated, soil moisture variability became the dominant driver in the east, explaining 67–82% of the temperature difference between El Niño and La Niña years, and 85–91% percent of the difference in carbon fluxes. These results highlight the need to consider the interdependence between temperature and hydrology when attributing the relative contribution of these factors to interannual variability of the terrestrial carbon cycle. Specifically, when offline models are forced with observations or reanalysis, the contribution of temperature may be overestimated when its own variability is modulated by hydrology via land-atmosphere coupling.

Summary
We demonstrated that in E3SM, soil moisture anomalies resulting from SST variability extended and strengthened the temperature and CO2 flux anomalies associated with ENSO. This indicates the need to consider the interdependent relationship between temperature and the hydrologic cycle  when attributing mechanisms to ENSO-driven variability in the tropical terrestrial carbon cycle.

Contacts (BER PMs): Dr. Renu Joseph (Primary), SC-23, Renu.Joseph@science.doe.gov (301-903-9237); Dr. Dorothy Koch, SC-23, Dorothy.Koch@science.doe.gov (301-903-0105); Dr. Daniel Stover, SC-23, Daniel.Stover@science.doe.gov (301-903-0289)

Author Contact: Paul A. Levine, University of California, Irvine (paul.levine@uci.edu, 949-824-9030) and Dr. James T. Randerson, University of California, Irvine (jranders@uci.edu, 949-824-9030)

PI Contact: Dr. Forrest M. Hoffman, Climate Change Science Institute (CCSI), Oak Ridge National Laboratory, forrest@climatemodeling.org (865-576-7680)

Funding
This research was funded, in part, by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation Scientific Focus Area (RUBISCO SFA), which is sponsored by the Regional and Global Model Assessment (RGMA) Program in the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research (BER) in the US Department of Energy (DOE) Office of Science. This research used resources from Project m2467 of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility (DE-AC02-05CH11231), and from Project cli106bgc of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility (DE-AC05-00OR22725). P.A.L. received funding support from NASA Headquarters under the NASA Earth and Space Science Fellowship Program (NNX16AO38H). J.T.R. and Y.C. received additional funding support from the DOE Office of Science Earth System Modeling Program (DE-SC0006791) and NASA’s SMAP and CMS programs. M.S.P. received funding support from the DOE Early Career Program (DE-SC0012152). M.X. and F.M.H. received additional funding support from the Energy Exascale Earth System Model (E3SM) Project and the Next Generation Ecosystem Experiments–Tropics (NGEE-Tropics) Project, sponsored by BER in the DOE Office of Science.

Publications
Levine, P. A., J. T. Randerson, Y. Chen, M. S. Pritchard, M. Xu, and F. M. Hoffman (2019), Soil moisture variability intensifies and prolongs eastern Amazon temperature and carbon cycle response to El Niño-Southern Oscillation, J. Clim., 32(4):1273–1292, doi:10.1175/JCLI-D-18-0150.1.

Related Links
Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation (RUBISCO) Scientific Focus Area. https://www.bgc-feedbacks.org/
Energy Exascale Earth System Model (E3SM). https://e3sm.org/
Next Generation Ecosystem Experiments–Tropics (NGEE-Tropics). https://ngee-tropics.lbl.gov/