Component fluxes of the Carbon balance of Europe and their - PowerPoint PPT Presentation

Component fluxes of the Carbon balance of Europe and their uncertainties Philippe Ciais Laboratoire des Sciences du Climat et de l’Environnement Gif sur Yvette, France

Fossil fuel emissions drive the increase of CO 2

Land and ocean absorb ≈ 55 % of emissions on average Canadell et al. PNAS, press Land sink is the most uncertain term

Uncertainties are Everybody’s tired. Large But Let’s make a deal … Don’t be affraid of The biosphere !

The knowledge challenge Atmospheric and Ecosystem Observations to constraint the C budget of large regions Atmospheric Concentration Networks Ecosystem Flux Networks

Starting point European ecosystems carbon budget 600 Top down 500 Atmospheric estimate 400 300 200 Tg C/year 100 0 Bottom up -100 Ecosystem -200 estimate -300 -400 Janssens et al., -500 2003 Science -600 Forest, Grass- Crop- Peat use woodland land land Reminder : Emissions = 1200 TgC y-1

The Net carbon balance (NBP) Estimates of NPP, HR for major European ecosystems • CO 2 Estimates of NBP (carbon balance) • Underlying processes • Disturbance Plant Soil and litter Trends • (fire, harvest) respiration respiration Photosynthesis Variability • Short- Medium- Long-term term term carbon carbon carbon storage uptake storage NBP NPP NEP Is the small difference of two larger gross fluxes : NBP = (NPP) - (Soil and litter respiration + disturbance)

Goals of this study Estimates of NPP, HR of major • European ecosystems Associated estimates of NBP • Underlying processes • Variability • Trends •

Two different planets • Global Biogeochemical models • Emission factors -> This presentation -> This Meeting – NOT Simple – Simple – INdirect link to data – Directly based on data – DONT account WELL for management – Account for management – HARD to compare with each others – Can be compared with each others – Dynamic evolution of ecosystem flux in response to weather, climate and – ‘static’ Do not account for atmospheric changes ecosystem flux variability and trends in a changing world – Account for (some) of – ‘rigid’ Do not account very well ecosystem heterogenity for ecosystem heterogenity – CAN account for ALL ecosystems – DONT account for ALL (if you’re not afraid of simplifications) ecosystems

Biogeochemical models This is a forest

Emission factors Flux = EF * Area This is a forest

The knowledge challenge Example of interannual variability, the 2003 heatwave impact on Europe‘s carbon balance: A 0.5 PgC loss event Ciais et al. Nature 2005

Models without data are like fantasy…. Need to combine both … But data without a model often look like chaos

Forests

Forest • Data and Method – National forest inventory diameter increment (sample based inventories) – NPP is modelled using expansion factors and leaf + root turnover rates – NBP is modelled as biomass increment + soil carbon balance

Evolution of stocks vs. NPP since 1950 Compare : Odum Paradigm (one forest)

Litterfall does not tail with NPP for conifers, and moderately increases with NPP for broadleaved Carbon saving sylvivulture

Contribution of climate and CO 2 CO 2 + Climate effects Estimated with biogeochemical models < 50%

Forests: conclusions • NPP = 280 gCm -2 y -1 • NBP = 50 gCm -2 y -1 • NPP possibly underestimated – Biogeochemical models ≈ 370 - 550 gCm -2 y -1 – Ecological data ≈ 400-600 gCm -2 y -1 • Stocks increased by 75% since 1950 • Carbon stocks have remained proportional to NPP in nearly all European countries

Factors driving the forest C balance • Changes in forest area alone do not explain the stock increase • Management-related factors – Juvenile age distribution – Harvesting less than the increment (policy favoring high forest stands) – Better nitrogen recycling in soils • Biogeochemical factors - N deposition (Magnani et al. 2007) - CO 2 and climate effects <50%

Croplands

Croplands No pan-European soil C inventory • NPP is inferred from FAO national yield • statistics NBP is the modelled soil C balance driven by: • Recent past changes in farmers practice, – cultivar species, – CO 2 and climate – [assumes no C inputs to soils ; 100% oxidation of – harvest]

ORCHIDEE-STICS European model of cropland carbon cycling Water and energy fluxes (hrly) Carbon fluxes (hrly) Output fields Soil water content (daily) GPP, NPP, yield Carbon pools (daily) Input land data (fixed) ORCHIDEE • Land atmosphere Exchange Soil texture Global • Allocation and growth Soil depth • Mortality Vegetation Land cover • Soil organic matter decomposition Model Input climate data (hourly) Leaf Area Index Date of harvest Root density profile Amount of irrigation Temperature Canopy height Harvest index Precipitation Nitrogen stress on photosynthesis SW down radiation Air humidity • Crop phenology STICS Wind • Root dynamics LW down radiation Crop Model • Nitrogen cycle • Above-ground carbon dynamics Wheat / Corn Input practice data (annual)

Model integration over 1901-2000 Simul Atmospheric Climate Farming practice [CO 2 ] Sowing date ation Crop Variety (short / long season length) Nitrogen fertilizer amount Fertilizer type (organic / mineral) Irrigation (yes / no) Organic fertilisers 2 t ha -1 yr -1 300 ppm 1900 CNT until equilibrium S1 from 300 to 370 ppm 1900 Organic fertilisers 2 t ha -1 yr -1 from 300 to 370 ppm 1901-2000 Organic fertilisers 2 t ha -1 yr -1 S2 from 300 to 370 ppm 1901-2000 1900-1950 Organic fertilisers 2 t ha -1 yr -1 (32 kgN ha -1 yr -1 ) S3 1951-2000 Mineral fertilisers from 32 to 150 kgN ha -1 yr -1 1951-2000 Increase of harvest index (linear) from 0.25 to 0.45 1951-2000 Irrigation from 0 to 200 mm yr -1 (maize only) 1900-1980 Short cycle varieties for wheat & maize 1981-2000 Long cycle varieties for wheat & maize 1900-2000 Increase of soil carbon pools' turnover by 10%

Model evaluation against historical yield data

Modelled cropland soil C balance If no increase in harvest index ‘Best’ case If ploughing X2 If no mineral fertilizers Derivative of C(t) = NBP Large sensitivity to, and legacy of past practice

Changes in cropland NPP and soil C 1901 2000 - 1901 CO 2 CO 2 + Climate CO 2 + Climate + Gervois et al. Practice submitted

Cropland NPP, NBP distribution during the 1990s

Croplands: Conclusions • NPP = 660 gC m -2 y -1 • NBP = 8.4 gC m -2 y -1 • Soil C is a small sink, – Agrees with crop model analysis Smith et al. 2005 – Disagrees with former CESAR model results – Regional inventories show moderate to large sources • Uncertainties on cropland NBP due to – Ploughing impacts on soil C turnover rates – Crop rotation – Historical changes in varieties – Straw and residues fate

Factors driving the croplands C balance • NBP mostly determined by past practice change • Rebuilding stocks as a rebound from intensive ploughing 30 years ago • Rising CO 2 has a <10% effect in increasing yields, but a 30% effect in increasing in water use efficiency • Spring dryness trends have negatively impacted yields in Iberian Peninsula, but this effect is compensated by practice changes

Importance of european grasslands  Area and number of animals  20% of Geographic Europe’s area (140 Mha)  140 millions of sheep / 140 millions of cows  Fluxes  CO 2 - annual yield production ~ 1 - 6 t C ha -1 y -1 - animal respiration ~ 1 t C y -1  N 2 O - soil emission 0.1-1 t Ceq ha -1 y -1  CH 4 - animal emission 0.3-1.5 t Ceq y -1  Very few continental scale estimates and large uncertainties  carbon balance = 101 ± 133 TgC y -1 (Janssens, 2001) → empirical model = 259 ± 75 Gg N 2 O y -1 (Freibauer, 2003)  soil N 2 O emissions → Grasslands emission factor = 6.8 Mt CH 4 y -1  animals CH 4 emissions → emission factor

Grasslands • No pan-European NPP data (virtually impossible to measure) • No soil C inventory to measure NBP • GPP and NPP modelled at continental scale ; but estimating NBP was not tackled • NBP/GPP ratio estimated at 9 eddy-covariance sites and used in upscaling NBP = (NBP site /GPP site )*GPP model

PaSim grassland model CH 4 Nitrogen Inputs Carbon Inputs CO 2 emissions Nitrogen outputs emissions N deposition N2O N2O CO2 CH4 NH3 N2 NO3- N fertiliser N fixation autotrophic heterotrophic photosynthesis yield respiration respiration decomposition substrate yield allocation cutting volatilization root lamina stem ear Carbon and Nitrogen BIOMASS nitri/ grazing denitrification N uptake mortality leaching animals Carbon and Nitrogen litter (structural / metabolic) urine decomposition dung active slow passive soil carbon and nitrogen

NBP Import Export NPP N 2 O CH 4 GPP Soil HR Run at equilibrium, thus HR equalling NPP Tested against 9 eddy coveriance site level GPP and NEE Management (grazing / cut) intensity distribution is calculated High N inputs / zero N inputs end-members