How to moderate the impact of agriculture on climate

B.Seguin, D.Arrouays, J.F Soussana INRA (France),

A.Bondeau, S.Zaehle PIK Potsdam (Germany)

N.de Noblet, P.Smith, N.Viovy, N.Vuichard LSCE (France)

Introductory remarks (1)

The inverse of the usual view: how the climate impacts agriculture ?

Introductory remarks (2) ‘ moderate’ implies: . an a priori of negative impact (to be discussed) . impact well understood (not totally

the case !!) the impact of agriculture on climate may combine :

. indirect effects on GHG net emissions (CO2,CH4,N20.. and H2O ) . direct effects on SEB components , water cycle and local/global climate to be considered concurrently( regional climate change potential as defined by Pielke et al 2002) at different spatial scales…

I. At field scale (~100m) basically action by management practices as : . conservation tillage,fertilization/ irrigation scheduling,

residues, animal feed,.. for GHG emissions . mainly irrigation for biophysical SEB, but also timing of

crop cycles (winter/summer) scale corresponding to practical outputs of farmer tactical

decisions within the strategic options first level of interactions (tillage CO2/N20, irrigation for

SEB/ N20, pasture management for CH4/N20..)

Manure / Slurry

OM fluxes

Dissolved organic C

Herbivore

Vegetation

Soil

Atmosphere

CH4

CO2

CO2

CH4

CO2

N2O

At field scale : first level of interactions

But also surface biophysical variables:albedo, roughness, surface temp.. etc !!!

At field scale (~100m)

also the basic scale for physical assessment by measure and modelling

N2O: automated static chambers and TDL

SF6 pill

SF6CH4

CH4 , SF6

CH4: in-situ SF6 tracer method

CO2: eddy-correlation system

Carbon Loss since Ploughing

0

0.05

0.1

0.15

0.2

0.25

0.3

J un-02 J ul-02 Aug-02 Sep-02 Oct-02

Cu

mu

lati

ve C

arb

on

Loss

(kg

C m-2

)

Carbon loss: 0.25 t C ha-1 within 5 monthsOr 1.9% of total carbon in the top 15 cm

of soil CEH

-1500

-1000

-500

0

500

1000

1500

24/04 24/05 23/06 23/07 22/08 21/09

Cum

ulat

ed G

WP

(equ

ival

ent C

/CO

2 h

a-1

) the effect of management mode

CH4 Int

CH4 Ext

CO2 Ext

CO2 Int

N2O IntN2O Ext

Cumulative fluxes in C equivalentfor each gas (Laqueuille, 2002)

Intensive Extensive Extensive

the effect of management mode

( 2002)

-600

-500

-400

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-100

0

100

200

300

400

a m j j a s o o

Cum

ula

ted

GW

P (e

qu

ival

ent C

/CO

2 h

a-1

)

Extensive

Intensive

Greenhouse gas balance (Laqueuille, 2002)

II .At farm scale (~1 to 10 km) the basic scale for strategic options (choice of agricultural

productions and resulting crop/livestock systems) mainly driven by economical constraints includes alternative solutions as energy cropping (biomass

for heat and power, biofuels) and biogas second level of interactions (annual crops/livestock,

conventional/organic farming..) including the fuel energy use (fertilizers, machinery..)

accessible with farm-scale models

CH4 N2O CO2

tC e

q. h

a-1 yr

-1

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Stockage et traitement déjections animalesExhalé/Respiré par les animauxGrasslandCulturesCombustion energie fossileStockage aliment

(Salètes et al., GHG Conference, Leipzig, 2004)

Bilan de GES d’une ferme d’élevage bovin mixte (100 ha SAU)

Mitigation options at livestock farm level Nitrogen Carbon Water

Management

Technology

Structural Change

FertilizationSoil cultivationStocking rate

Manure storageSoil cultivation

Grazing

IrrigationDrainage

Groundwater level

Fertilizer type Manure processing

Housing system

Manure digestionSoil cultivation

Farm typeAnimal number

Other crops

Farm typeAnimal number

Other crops

FloodingWater buffers

(after Oenema, WUR, NL)

Farm scale budgets and mitigation

Account for all emissions from the barn to the pastures

(J Olesen, DIAS, DK)

III. At large scales (~ 10 to 1000 km) mainly land-use (crops, pastures,forests,urban areas..

with/without irrigation) and landscape components (trees, hedges)

only accessible with atmospheric models:

. local features (detailed land-use, irrigation, landscape components like trees, hedges) in mesoscale models

. regional features (main land-use classes) in global models

Average organic C stocks in French soils vs. land useLand use and average soil organic C stocks (0-30 cm) in France

0

10

20

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60

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80

90

100

Vin

e/O

rch

ard

Ara

ble

lan

d

Ran

gela

nd

Con

ifero

us

Dec

idu

ous

.

Com

ple

x

Gra

ssla

nd

Gra

ssla

nd

Mix

ed fo

rest

Mo

un

tain

Mo

un

tain

gra

ssla

nd

gra

ssla

nd

Wet

land

Stocks (t C ha-1)

(Arrouays et al. 2002)

(0-30 cm)

Effect of land-use changes on carbone storage for France (computed)

Arrouays, J. Balesdent, 08/06/01

-2

-1

0

1

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-1

0

1

2

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8S

tock

age

annu

el d

eca

rbon

el(M

t a

n-1)

Abandon de la jachère triennale ou quadriennale

Mise en prairies

Afforestation

Artificialisation et bâtiment

Retournements de prairies

Jachère Européenne

1850 20001900 19501850 20001900 19501850 20001900 19501850 20001900 1950

Land use change effects on soil carbon stocks

-40

-30

-20

-10

0

10

20

30

40

0 20 40 60 80 100 120Years after start of policy measure

Carb

on s

tock

s(tC

/ha)

arable -> forest

arable -> grassland forest -> arable grassland -> arable

Land use change: carbon storage is slower than carbon relase(After INRA, 2002)

GWP (Eq tC-CO2 ha-1 yr-1 ) over Europe for grassland vegetation with cutting management

GWP (Eq tC-CO2 ha-1 yr-1 ) over Europe for grassland vegetation with a grazed management

The effect of land-use on surface radiative balance

Snow 0.7 300 20 420 20 280Desert 0.40 600 50 618 218 382Bare soil 0.25 750 45 580 180 570Dry pasture 0.25 750 40 544 144 607Irr. pasture 0.20 800 32 490 90 710forest 0.10 900 28 460 60 840

a (1-a) Rg Ts Rs Rs - Ra Rn  

Rn = (1-a) Rg – (Rs - Ra)

Computed values of Rn (W/m2) near midday for different land uses 

with Rg = 1000, Ra = 400 and Ta = 27 °

The effect of land-use on local climateLand-use classes % surface (1987) LAI(15/4/87) ZOm(15/4/87) Ts(15/4/87) Ta(15/4/87)

Dry meadow 23 0.5 0.5 25.2 21

Irr. meadow 12 2 2 22.7 19.3

Rice 9 0.5 1 24.2 21.9

Wheat 9.5 2 4 21.5 21.5

Swamp 7 2 2 22.9 21

Vegetable 3.5 3 3 22.3 20.9

Forests 10 4 10 20.1 20.3

from Courault et al (1998)

20.

19

18

17.

16

450

300

200

50

LE latent heat flux Ta air temp

Land use change => feedback on the climateForested Deforested: cropland or pasture

(Foley et al. 2003)

irrigation may induce a global warming of 0.03 to 0.1 W/m2 and a local cooling of 0.8 °K on large irrigated areas (Boucher et al 2004)

The effect of landscape components on surface parameters

computed influence of relative spacing of tree hedges on albedo (for a surface base value of 0.2) from Guyot and Seguin 1976

Schematic influence of relative spacing of tree hedges on surface aerodynamic roughness z0 and displacement height dfrom Seguin (1973)

Two examples of implementation of agriculture within GCM in european projects : why?

to determine the changes of energy and matter (esp. water and carbon) fluxes at the soil-vegetation-atmosphere interface, and the changes in carbon stocks and runoff that occur when agriculture takes place instead of natural vegetation

=> feedback on the climate

LPJ

Implementation of agriculture within LPJ – how?

Sowing date estimation:for 4 temperate CFTs = f(T), for 4 tropical CFTs = f(P)Adaptation of heat sum and vernalization requirement

Oct Jul

LAI, ~ 6

Total biomass, ~ 20 tDM/haGrain harvested, ~ 6 tDM/ha

Daily coupled growth and development simulation:Phenology, LAI change, carbon allocation to leaves, roots, storage organs, ... Estimation of the harvesting period

No water stress for irrigated crops, computation of the water requirement and of the effective irrigation

For grasses, several cuts (f(LAI)), or regular grazing

Winter wheat

Harvested biomass removed, residues sent to the litter pool or removed (fodder, biofuel, ...)

Possibility of multiple cropping (e.g. rice)Grass during the intercrop season otherwise

each CFT on a distinct stand with access to a

separate soil water pool

Two examples of implementation of agriculture within GCM in european projects : how?

LPJ

LPJ-crops - global results 20th century trends

LPJ-crops - global results 20th century trends

Initial Conditions State of atmosphere and ocean

At a given time

Boundary conditionsSolar radiation

GHG concentrationsVEGETATION COVER

ModelVariables describing

the state of climate

Reference simulation (potential vegetation = mainly forests)Perturbated simulation (vegetation = agriculture)

Numerical experiment with the IPSL model

Land-use by agriculture

Results for Europe..Differences: (agriculture – potential vegetation)

Brovkin et al., GEB, 1999

But….

Crops are not adequately represented by vegetation models inside climate models …

Blé d’hiver

ORCHIDEE

50 100 150 200 250 300 3500

1

2

3

4

5

6

50 100 150 200 250 300 3500

1

2

3

4

5

6LAI :

Corn

LAI

daysdays

Winter wheat

measures

C3 ~ 35% C4 ~ 2.5 %

Agriculture ~ 37.5% of the Europe surface

Resolution = 1°*1° ( combining the CORINE land-ues map with FAO data to partition C3 & C4)

distribution of surfaces occupied by agriculture in Europe

Figure 8

NOCROP

CROP

Figure 8

The influence of crop/ no crop on water balance at the european scale

The influence of C3 crop (wheat/soybean)

Evapotranspiration(mm/jour)

Flux de chaleur sensible(W/m2)

ORCHIDEE

ORCHIDEE-STICS / C3 =wheat

ORCHIDEE-STICS / C3 = soybean

4

-5

Photosynthesis and carbon fluxes at the european scale

LAI NEP (gC/m2/day)

ORCHIDEE

ORCHIDEE-STICS / C3 = wheat

ORCHIDEE-STICS / C3 = soybean

NPP (gC/m2/day)

technical bases for mitigation of GHG emissions by agriculture exist at the field scale

their advantages may be limited (or possibly inversed) by technical aspects at the field scale when considering trade-offs with other GHG or longer term scales.

consistent inventories at the plot scale are lacking in current IPCC methodology

strategical orientations at the farm level (organic/conventional, extensive/intensive management for grassland, etc..) may lead to farm use efficiency as the best tool

Conclusions (1/2)

Conclusions (2/2) At the larger scales, land-use also induce significant trade-

offs, so that biophysical variables need to be considered to fully evaluate the effect of GHG mitigation procedures

Only more comprehensive studies allowing to assess the overall aspects at the various scales (from local to global) will give the significant inputs

If GHG emissions may be considered as aggregative along spatial scales, actions on micro or local climates may significantly locally affect the global climate