Intact rainforest and Land-use Change in Amazônia: Scott R. Saleska Harvard University: S.C. Wofsy, L. Hutyra, A.H. Rice, B.C. Daube, D.M. Matross, E.H.

Slides:



Advertisements
Similar presentations
Progress in understanding carbon dynamics in primary forests CD08 team.
Advertisements

Variation in ages and growth rates of trees in Amazonian tropical forests: consequences for carbon and forest management Simone Vieira, Plínio Camargo,
The Carbon Farming Initiative and Agricultural Emissions This presentation was prepared by the University of Melbourne for the Regional Landcare Facilitator.
Lauren Sanchez, Middlebury College
Seasonality & Interannual variability in photosynthetic metabolism of Amazon rainforests: insights from remote sensing Kamel Didan, Scott Saleska, Natalia.
The age of C respired from ecosystems Susan Trumbore, Jim Randerson, Claudia Czimczik, Nicole Nowinski (UC Irvine) Jeff Chambers (Tulane) Eric Davidson.
The C budget of Japan: Ecosystem Model (TsuBiMo) Y. YAMAGATA and G. ALEXANDROV Climate Change Research Project, National Institute for Environmental Studies,
Diagnostic canopy Prognostic canopy. Offline results: Combined influence of sun/shade and prognostic canopy scheme, compared to CLM3.0. CLM3-CN running.
Daniel Metcalfe Oxford University Centre for the Environment Comprehensive monitoring of carbon allocation and cycling across.
A MONASH UNIVERSITY PERSPECTIVE Musa Kilinc and Danielle Martin School of Geography and Environmental Science.
Seventh Carbon Dioxide Conference – Boulder, September 25-30, 2005 The Amazon and the modern carbon cycle Jean Ometto (1), Antonio Nobre (2), Humberto.
Magnitude and Spatial Distribution of Uncertainty in Ecosystem Production and Biomass of Amazonia Caused by Vegetation Characteristics Christopher Potter.
UC IRVINE: SCOTT MILLER, ED READ, CHRIS DOUGHTY, MIKE GOULDEN USP: HELBER FREITAS, HUMBERTO DA ROCHA Boat-Based Eddy Covariance Measurements of CO 2 Exchange.
Scott Saleska Paul Moorcroft David Fitzjarrald (SUNY-Albany) Geoff Parker (SERC) Plinio Camargo (CENA-USP) Steven Wofsy Natural disturbance regimes and.
Carbon flux at the scale up field of GLBRC. The Eddy Covariance cluster towers Terenzio Zenone 1 Jiquan Chen 1 Burkhard Wilske 1 and Mike Deal 1 Kevin.
Jun-Aug/annual mean T precip.sum (degC) (mm) / / / / / / / /810 Jun-Aug/annual mean.
Carbon Cycle Basics Ranga Myneni Boston University 1/12 Egon Schiele ( ) Autumn Sun 1.
The Carbon Cycle 3 I.Introduction: Changes to Global C Cycle (Ch. 15) II.C-cycle overview: pools & fluxes (Ch. 6) III. Controls on GPP (Ch. 5) IV.Controls.
QUESTIONS 1.How do elements in the lithosphere get transferred to the atmosphere? 2.Imagine an early Earth with a weak Sun and frozen ocean (“snowball.
Effects of Forest Management on Carbon Flux and Storage Jiquan Chen, Randy Jensen, Qinglin Li, Rachel Henderson & Jianye Xu University of Toledo & Missouri.
Robert W. Christopherson Charlie Thomsen Chapter 19 Ecosystem Essentials.
Global Emissions from the Agriculture and Forest Sectors: Status and Trends Indu K Murthy Indian Institute of Science.
Nara Luísa Reis de Andrade, Luciana Sanches, Peter Zeilhofer, Segundo Durval Rezende Pereira, José de Souza Nogueira Environmental Physics Research Group.
Paul R. Moorcroft David Medvigy, Stephen Wofsy, J. William Munger, M. Dietze Harvard University Developing a predictive science of the biosphere.
Prepare for leaf senescence Peak litterfall Flush of leaves Max aerosol load μmol m -2 s -1 Climatic variability, carbon exchange and vegetation vulnerability.
Variance and Vulnerability in Amazonian Forests: Effects of climatic variability and extreme events on the structure and survival of tropical forests Steven.
Summary of Research on Climate Change Feedbacks in the Arctic Erica Betts April 01, 2008.
Nelius Foley, Matteo Sottocornola, Paul Leahy, Valerie Rondeau, Ger Kiely Hydrology, Micrometeorology and Climate Change University College Cork, IrelandEnvironmental.
Wood and soil surface CO 2 flux from the Tapajós National Forest Evilene C. Lopes 1, Michael Keller 1,2, Patrick M. Crill 1,3, Ruth K. Varner 4, William.
Measurement of aerosol and VOC turbulent fluxes and in-canopy particle characterization at a pristine forest in Amazonia Luciana Rizzo.
The impacts of land mosaics and human activity on ecosystem productivity Jeanette Eckert.
Translation to the New TCO Panel Beverly Law Prof. Global Change Forest Science Science Chair, AmeriFlux Network Oregon State University.
LBA ECO Synthesis Activities Summary of Current Activities Michael Keller NASA LBA-ECO Project Scientist.
Eva van Gorsel1, Ray Leuning1, Helen A
Introduction: Globally, atmospheric concentrations of CO 2 are rising, and are expected to increase forest productivity and carbon storage. However, forest.
CO 2 - Net Ecosystem Exchange and the Global Carbon Exchange Question Soil respiration chamber at College Woods near Durham New Hampshire. (Complex Systems.
State-of-the-Art of the Simulation of Net Primary Production of Tropical Forest Ecosystems Marcos Heil Costa, Edson Luis Nunes, Monica C. A. Senna, Hewlley.
Primary Production in Terrestrial Systems Fundamentals of Ecosystem Ecology Class Cary Institute January 2013 Gary Lovett.
THINKING beyond the canopy Removing technical barriers to include tropical peatlands in the REDD+ mechanism Daniel Murdiyarso, Kristell Hergoualc’h and.
size-class (cm) trees/ha km 83: y = * x (0.124) ( ) R ² =
Investigating the Carbon Cycle in Terrestrial Ecosystems (ICCTE) Scott Ollinger * -PI, Jana Albrecktova †, Bobby Braswell *, Rita Freuder *, Mary Martin.
Biomass Dynamics of Amazonian Forest Fragments William F. Laurance & Henrique Nascimento Smithsonian Tropical Research Institute, Panama Biological Dynamics.
The age of C respired from tropical forest Susan Trumbore, Jim Randerson (UC Irvine) Jeff Chambers (Tulane) Simone Vieira, Plínio Camargo, Everaldo Telles,
Carbon and water cycling along the western Sierra gradient Anne Kelly SSCZO annual meeting August 21, 2012.
Compositional Shifts in Undisturbed Neotropical Forests: Effects of Climate Change? William F. Laurance 1,2 & Richard Condit 1 William F. Laurance 1,2.
WP coordinator meeting June 17/ WP3 progress report.
300 Years of NEP Caused By Land Use, CO 2 Fertilization and Climate Change According to LM3 Shevliakova, Malyshev, Hurtt and Pacala.
Controls on tropical forest CO 2 and energy exchange Michael L Goulden, Scott D Miller, Humberto da Rocha, Chris Doughty, Helber Freitas, Adelaine Michela.
Landscape-level (Eddy Covariance) Measurement of CO 2 and Other Fluxes Measuring Components of Solar Radiation Close-up of Eddy Covariance Flux Sensors.
Biometric Measures of Carbon Cycling Before and After Selective Logging in Tapajós National Forest - Para - Brasil 1,2 Figueira, A.M.S.; 3 Sousa,C.A.;
Fig 1 –The top figure shows canopy PAR during the dry season of 2001 between AM. The bottom two figures show leaf level light and temperature in.
Seasonal Emissions of N 2 O, NO, CO and CO 2 in Brazilian Savannas Subjected to Prescribed Fires Alexandre Pinto, Mercedes Bustamante, Laura Viana, Universidade.
High drought-tolerance of an Eastern Amazon forest: results from a large scale rainfall exclusion Gina Cardinot 1,2, Daniel Nepstad 2,3, Missy Holbrook.
Changes in carbon cycling by Brazilian rain forest: effects of soil moisture reduction on soil, leaves and canopy Patrick Meir, AC Lola da Costa, S Almeida.
Mechanistic model for light-controlled phenology - its implication on the seasonality of water and carbon fluxes in the Amazon rainforests Yeonjoo Kim.
Estimating scalar fluxes in tropical forests using higher-order closure models Mario Siqueira 1, Humberto R Rocha 2, Michael L Goulden 3, Scott D Miller.
Measuring the Effect of Selective Logging on Forest-Atmosphere Exchange Scott Miller, Mike Goulden, Humberto da Rocha, Helber Freitas, Mary Menton, Adelaine.
Methane production. Current atmospheric concentrations: CH 4 : ~1.7ppm CO 2 : ~380ppm On molar basis, CH 4 is 22 X’s more powerful than CO 2 as a greenhouse.
Measuring the Effect of Selective Logging on Forest-Atmosphere Exchange Scott Miller, Mike Goulden, Humberto da Rocha, Helber Freitas, Mary Menton, Adelaine.
Scott Saleska (U. of Arizona) Lucy Hutyra, Elizabeth Hammond-Pyle, Dan Curran, Bill Munger, Greg Santoni, Steve Wofsy (Harvard University) Kadson Oliveira.
Daily net carbon exchange as a mediator of heterotrophic soil respiration across two forest chronosequences Jared L. DeForest, Asko Noormets, and Jiquan.
Carbon Dynamics in Coarse Woody Debris Pools at the Tapajos National Forest in Brazil Hudson Silva Patrick Crill Michael Keller.
Carbon Fixation and Storage in Mangrove Forests University of Virginia
CLM-CN update: Sensitivity to CO2, temperature, and precipitation in C-only vs. C-N mode Peter Thornton, Jean-Francois Lamarque, Mariana Vertenstein, Nan.
Tropical rainforest: carbon sink or carbon source?
Field Data & Instrumentation
OGWC – Forest C Bev Law Prof. Global Change Biology & Terrestrial Systems Science Oregon State University Oct 6, 2016.
Ecosystem Demography model version 2 (ED2)
CLM-CN update: Sensitivity to CO2, temperature, and precipitation in C-only vs. C-N mode Peter Thornton, Jean-Francois Lamarque, Mariana Vertenstein, Nan.
Global Forest Carbon Budget (tons of C/y)
Presentation transcript:

Intact rainforest and Land-use Change in Amazônia: Scott R. Saleska Harvard University: S.C. Wofsy, L. Hutyra, A.H. Rice, B.C. Daube, D.M. Matross, E.H. Pyle, J.W. Munger University of Sao Paulo: P.B. de Camargo, H. de Rocha; INPE: V.W. Kirchhoff; U.C. Irvine: M.L. Goulden, S.D. Miller Seeing both the forest and the trees

Land-use change I (obvious): Biomass burning, conversion to agriculture

Land-use change II (subtle): Treefall destroys research site Outhouse Outhouse remnants Fallen tree

How can both kinds of changes be important?

“Changed” forest: High intensity  relatively smaller area (e.g. burning, total clearing) (1.9 million ha/year in 1990s) (Source: Brazilian Space Agency, INPE) “Intact” forest: small effect  huge area (~600 million ha)

How can both kinds of changes be important? “Changed” forest: High intensity  relatively smaller area (e.g. burning, total clearing) (1.9 million ha/year in 1990s) (Source: Brazilian Space Agency, INPE) “Intact” forest: small effect  huge area (~600 million ha)  ~0.3% per year change in what that intact forest is doing is comparable to all the land use change

Land-use change II (subtle): Treefall destroys research site Outhouse Outhouse remnants Fallen tree

Santarém Rio Amazonas Rio Tapajós Km 67 site Km 83 site (logged Sept ’01) Intact rainforest research sites in a protected reserve: the Tapajós National Forest, near Santarém, Brazil

Profile system inlets (8 levels) 58 m: Level 1 Eddy flux 47 m: Level 2 Eddy flux Part 1: Eddy flux (“the forest”) 64m tall tower: Tapajos forest, Km 67

Flux CO 2 = w ’ CO 2 ’ w’ = vertical wind CO 2 = (CO 2 + CO 2 ’) Eddy covariance m s o C Seconds CO 2 rich Cool CO 2 depleted Warm  mol CO 2 mol -1 a) w b) T c) CO 2

(A)Eddy flux of CO 2 for eddy1 (58m) and eddy2 (47m); (B)friction velocity (u*) (turbulence); (C)mean CO 2 concentration 0- 60m ("canopy storage"); (D)net ecosystem exchange (NEE = Eddy flux+ ) Initial Results: Hourly time series from the Primary Forest eddy flux tower at km 67 On windy nights (10-11 April, u*>0.2 m/s (B)) CO 2 efflux (A) is strongly positive, CO 2 storage (C) is low, and NEE (D)  flux (A). On calm nights (12-14 April), flux (A) and u* (B) are virtually zero, and CO 2 storage is high, causing NEE to be significantly higher than eddy flux. calm nights windy nights 10 April 12 April14 April Date in 2001

uptake loss to atmosphere start of dry season logging at km 83 Sum hourly fluxes to get ecosystem carbon balance over time: Summary: (1) towers agree with each other; (2) Forest ecosystem is showing net carbon loss (first in Amazonia) Biometry Cumulative NEE (loss to atmosphere), kg C ha Cumulative Net Ecosystem Exchange (NEE) and precip Average annual C-balance over two years:

Some Questions 1.Why is the forest not in carbon balance? 2.How does this flux (~ 1 Mg C/ha/yr) compare to those from land-use change?

Part 2 (“the trees”): Biometric Study of Tapajós Forest, km 67 dendrometers, 1000 trees dbh tapes, 2800 trees quantify woody debris, coarse fine, and litter

net uptake | net C emission growth/loss rate (Mg C ha -1 yr -1 ) Live Biomass ( tC/ha) mortality growth recruit Recruitment, growth, mortality, and dead wood stock directly measured live wood net gain: 1.4  0.6 MgC ha -1 yr -1 Carbon fluxes from live and dead biomass,

net uptake | net C emission growth/loss rate (Mg C ha -1 yr -1 ) Live Biomass ( tC/ha) Dead Wood (30 – 45 tC/ha) mortality growth recruit mortality decomp- osition Best estimate decomposition k (0.12  0.02 yr -1 ) based on field studies near Manaus (Chambers et al. 2001) Recruitment, growth, mortality, and dead wood stock directly measured live wood net gain: 1.4  0.6 MgC ha -1 yr -1 dead wood net loss: +3.3  1.1 Carbon fluxes from live and dead biomass,

net uptake | net C emission growth/loss rate (Mg C ha -1 yr -1 ) Live Biomass ( tC/ha) Dead Wood (30 – 45 tC/ha) whole- forest net loss: +1.9  1.0 mortality growth recruit mortality decomp- osition Best estimate decomposition k (0.12  0.02 yr -1 ) based on field studies near Manaus (Chambers et al. 2001) Recruitment, growth, mortality, and dead wood stock directly measured live wood net gain: 1.4  0.6 MgC ha -1 yr -1 dead wood net loss: +3.3  1.1 Carbon fluxes from live and dead biomass,

net uptake | net C emission growth/loss rate (Mg C ha -1 yr -1 ) Live Biomass ( tC/ha) Dead Wood (30 – 45 tC/ha) whole- forest net loss: +1.9  1.0 mortality growth recruit mortality decomp- osition Best estimate decomposition k (0.12  0.02 yr -1 ) based on field studies near Manaus (Chambers et al. 2001) Recruitment, growth, mortality, and dead wood stock directly measured Eddy Flux +1.3  0.9 Net Flux is sensitive to the decomposition rate of the dead wood, k. (Note: This forest would be losing carbon even if decomposition was as low as in a temperate forest in the southern U.S.) Biometry agrees with eddy flux live wood net gain: 1.4  0.6 MgC ha -1 yr -1 dead wood net loss: +3.3  1.1 Carbon fluxes from live and dead biomass,

Question 1: Why is this forest not in carbon balance? Three observations to consider: (1) The balance for live wood and dead wood is in opposite directions net uptake | net C emission Carbon fluxes from live and dead biomass, growth/loss rate (Mg C ha -1 yr -1 ) Live Biomass ( tC/ha) Dead Wood (30 – 45 tC/ha) whole- forest net loss: +1.9  1.0 mortality growth recruit mortality decomp- osition Best estimate decomposition k (0.12  0.02 yr -1 ) based on field studies near Manaus (Chambers et al. 2001) Recruitment, growth, mortality, and dead wood stock directly measured Eddy Flux, +1.3  0.9 live wood net gain: 1.4  0.6 MgC ha -1 yr -1 dead wood net loss: +3.3  1.1

Question 1: Why is this forest not in carbon balance? Three observations to consider: (1) The balance for live wood and dead wood is in opposite directions (2) Stock of above- ground dead wood is exceptionally large: in comparison to other sites; relative to what is needed for steady-state (  decade of mortality inputs to accumulate the excess dead wood stock) net uptake | net C emission Carbon fluxes from live and dead biomass, growth/loss rate (Mg C ha -1 yr -1 ) Live Biomass ( tC/ha) Dead Wood (30 – 45 tC/ha) whole- forest net loss: +1.9  1.0 mortality growth recruit mortality decomp- osition Best estimate decomposition k (0.12  0.02 yr -1 ) based on field studies near Manaus (Chambers et al. 2001) Recruitment, growth, mortality, and dead wood stock directly measured Eddy Flux, +1.3  0.9 live wood net gain: 1.4  0.6 MgC ha -1 yr -1 dead wood net loss: +3.3  1.1

Recruitment Growth Net = 1.5 Mg C ha -1 yr -1 Mortality Outgrowth Flux from Biomass & Changes in tree number density, by size class Observation 3: Demographic shift: (a) The increase in flux to biomass is in the smaller size classes (b) Corresponding increase in density of tree stems in the smaller size classes Question 1 (cont’d): Why is this forest not in carbon balance?  95% Conf. on each bin uptake loss to atmosphere

Recruitment Growth Net = 1.5 Mg C ha -1 yr -1 Mortality Outgrowth Recruitment Net Mortality Outgrowth size class, cm DBH density change, stems ha -1 Flux from Biomass & Changes in tree number density, by size class Question 1 (cont’d): Why is this forest not in carbon balance?  95% Conf. on each bin uptake loss to atmosphere Observation 3: Demographic shift: (a) The increase in flux to biomass is in the smaller size classes (b) Corresponding increase in density of tree stems in the smaller size classes

Hypothesis: Tapajós forest site is recovering from recent episode(s) of disturbance which: (1) Caused sharply elevated mortality preceeding onset of this study. (2) Caused a large increase in dead wood pool (to the point where losses exceed inputs) (3) Opened canopy gaps causing significant new growth and recruitment into smaller size classes of live wood (making overall growth uptake exceptionally high) Question 1: Why is this forest not in carbon balance?

Hypothesis: Tapajós forest site is recovering from recent episode(s) of disturbance which: (1) Caused sharply elevated mortality preceeding onset of this study. (2) Caused a large increase in dead wood pool (to the point where losses exceed inputs) (3) Opened canopy gaps causing significant new growth and recruitment into smaller size classes of live wood (making overall growth uptake exceptionally high) Question 1: Why is this forest not in carbon balance? Perhaps contributed to by recent El Niňo droughts? Condit et al. (1995), Williamson et al. (2000) link El Nino to elevated tree mortality

Summary: Net Carbon loss, because respiration losses from excess dead wood dominate gains from tree growth transient disturbance-recovery dynamic – possibly typical of old-growth forest, but not seen in eddy flux studies so far

Source: Moorcroft, Hurtt & Pacala (2001) Modeled flux following disturbance in gap of a “balanced-biosphere” rainforest near Manaus Gap Age (time since disturbance in years) Mg (C) ha -1 yr Tapajos Km 67 site (loss) npp = net primary productivity (uptake) rh = heterotrophic respiration (loss) nep = net ecosystem productivity (change in carbon balance)

Summary: Net Carbon loss, because respiration losses from excess dead wood dominate gains from tree growth transient disturbance-recovery dynamic – possibly typical of old-growth forest, but not seen in eddy flux studies so far Implications for Land-use change: Intact forest is dynamic: small changes in dynamics caused by human-induced changes in global climate can have effects comparable to more obvious land-use change:

Summary: Net Carbon loss, because respiration losses from excess dead wood dominate gains from tree growth transient disturbance-recovery dynamic – possibly typical of old-growth forest, but not seen in eddy flux studies so far Implications for Land-use change: Intact forest is dynamic: small changes in dynamics caused by human-induced changes in global climate can have effects comparable to more obvious land-use change: –rising CO 2 could stimulate forest, causing more carbon uptake

Summary: Net Carbon loss, because respiration losses from excess dead wood dominate gains from tree growth transient disturbance-recovery dynamic – possibly typical of old-growth forest, but not seen in eddy flux studies so far Implications for Land-use change: Intact forest is dynamic: small changes in dynamics caused by human-induced changes in global climate can have effects comparable to more obvious land-use change: –rising CO 2 could stimulate forest, causing more carbon uptake –Global warming could increase El Niño droughts, and forest disturbance, causing more carbon loss

Source: Moorcroft, Hurtt & Pacala (2001) Modeled flux following disturbance in gap of a “balanced-biosphere” rainforest near Manaus Gap Age (time since disturbance in years) Mg (C) ha -1 yr Tapajos Km 67 site (loss) npp = net primary productivity (uptake) rh = heterotrophic respiration (loss) nep = net ecosystem productivity (change in carbon balance)

Source: Moorcroft, Hurtt & Pacala (2001) Modeled flux following disturbance in gap of a “balanced-biosphere” rainforest near Manaus Gap Age (time since disturbance in years) Mg (C) ha -1 yr Tapajos Km 67 site (loss) Amount of change in nep, that, spread across the intact Amazon, would be ~twice that from deforestation: ±1 Mg ha -1 yr -1 x 600 million ha = ±0.6 Pg yr -1 ` npp = net primary productivity (uptake) rh = heterotrophic respiration (loss) nep = net ecosystem productivity (change in carbon balance)

Source: Moorcroft, Hurtt & Pacala (2001) Modeled flux following disturbance in gap of a “balanced-biosphere” rainforest near Manaus Gap Age (time since disturbance in years) Mg (C) ha -1 yr Tapajos Km 67 site (loss) Amount of change in nep, that, spread across the intact Amazon, would be ~twice that from deforestation: ±1 Mg ha -1 yr -1 x 600 million ha = ±0.6 Pg yr -1 versus 0.3 Pg yr -1 lost from Amazonian deforestation (~1.4 Pg yr -1 global deforest.) ` npp = net primary productivity (uptake) rh = heterotrophic respiration (loss) nep = net ecosystem productivity (change in carbon balance)

Summary: Net Carbon loss, because respiration losses from excess dead wood dominate gains from tree growth transient disturbance-recovery dynamic – possibly typical of old-growth forest, but not seen in eddy flux studies so far Implications for Land-use change: Intact forest is dynamic: small changes in dynamics caused by human-induced changes in global climate can have effects comparable to more obvious land-use change: –rising CO 2 could stimulate forest, causing more carbon uptake –Global warming could increase El Niño droughts, and forest disturbance, causing more carbon loss Integrated analysis of different kinds of change needed for full understanding of consequences of land-use change

Biometry plots upwind of flux tower, with locations & sizes of all trees >35cm, subset>10cm DBH Transects (from 35 cm DBH) (inset) Coarse Woody Debris Plots Legend for CWD Plots plot size of wood # area > 30cm cm cm m 2 25 m 2 1 m 2 tower (20 ha, 2800 trees, stratified) N

Questions Land-use Change: change relative to what? (i.e. what did the land do before its use was changed?) What is “change”? -forest conversion, often by fire, to agricultural or grazing lands -Logging -Global climate change

Q: Is there “lost flux”? We expect total nighttime NEE (which depends only on the physiology of forest respiration), to be essentially independent of atmospheric turbulence. Definition: Net Ecosystem Exchange: NEE = Eddy Flux + Flux out the top“Storage flux ” “Turbulence” (e.g. U* = friction velocity) Idealized Relations: NEE components, however, are expected to depend on turbulence, but in opposite directions NEE Eddy Flux “shut-off” of eddy transport at low turbulence… Storage Flux … leads to compensating build-up of CO 2 in canopy

Q: Is there “lost flux”? We expect total nighttime NEE (which depends only on the physiology of forest respiration), to be essentially independent of atmospheric turbulence. Observed Relations: Fall-off in NEE for U*<0.2 Answer: Yes, it looks like it. As U*  0, eddy flux decreases and storage flux increases as expected, but their sum (NEE) declines for U* < 0.2 m/sec:

Q: Is there “lost flux”? We expect total nighttime NEE (which depends only on the physiology of forest respiration), to be essentially independent of atmospheric turbulence. Observed Relations: Fall-off in NEE for U*<0.2 Answer: Yes, it looks like it. As U*  0, eddy flux decreases and storage flux increases as expected, but their sum (NEE) declines for U* < 0.2 m/sec: We take this as evidence of lost flux. Solution: filter out data below some U* threshold, then fill by interpolation “lost flux”

uptake loss to atmosphere uncorrected eddy flux km67 km83 Cumulative Net Ecosystem Exchange (NEE) and precip Average annual C-balance start of dry season logging at km 83 Summary: (1) with U* correction, towers agree with each other; (Part 1)