Environmental efficiencies & sustainable animal productions

Ph LECOMTE

D. Berre, T Hiep, E Tillard, J Vayssieres, M Vigne

GLOBAL AGENDA OF ACTION IN SUPPORT OF SUSTAINABLE LIVESTOCK DEVELOPMENT

CONSULTATION ON FOCUS AREA NUMBER 1:

CLOSING THE EFFICIENCY GAP IN NATURAL RESOURCE USE

2-4 April, FAO HQ-Rome, Italy

• More food production, less producing impact • Efficiency vs Efficacy a major shift

• “efficacy”: maximising goals without really specifying the means.

• “efficiency” : being effective in making efficient use of resources - natural, human, informational, material, financial, etc.: ecoefficiency, sustainable efficiency …

• Performance diversities • Large Diversity of systems // landscapes • Comparative "value(s)« of ecoefficiency very diverse • Inside LFS / landscapes a large diversity of efficiency exist

• How to exploit diversity and progress

Stakes, Postulates, Challenges

PC 1

PC

2

1 RE 1 VN 2 RE 2 VN 3 VN 4 VN

Groups

G1 G2

G4

G3

0.4 0.0 -0.5

0.50

0.00

-0.50

PC 1

PC 2

PROT Cc

MAT four

STARCH Cc

CELL Cc

CELL for.

HEM Cc

HEM for.

UFL Cc

UFL four

Kg DM Cc

Kg DM for

Diet efficiencies

Hiep et al., 2006

Groupes G1 G2 G3 G4 Diet classes

RE (n=44), % 39 61 0 0

VN (n=70), % 13 17 24 46

Diets

Forage Prot.+, Mj+

Hémic+,

Cell+ Mj- Hémic+

Supplement Prot.+ Starch+ Cell+ Starch+

DM intake total, kg DM/d 18.3 19.5 12.2 15.7

Suppl., kg DM/d 11.1 11.2 5.4 6.6

Forages C4 type, % 66 81 100 98

Animal prod. Efficiencies

Milk 4% fat, kg/d 19.7 19.6 8.3 15.3

Milk/DM intake 1.06 1.00 0.68 0.95

Milk/DM Suppl. 1.8 1.8 1.6 2.3

Environmental Efficiencies

CH4, litre/d 502 552 439 490

CH4/kg DM intake, litre/d 28 29 36 32

CH4/ Milk, litre/d 27 30 61 37

N total excreted, g/d 320 286 130 196

N excrété/N intake, dl 0.72 0.69 0.71 0.66

N excr./Milk, g/kg 16.2 14.6 15.8 12.9

0.0

0.4

0.8

1.2

1.6 Milk4%

Milk/DM int.

Milk/DM suppl.

CH4 total

CH4/kg DM int. CH4/lit. Milk

N total excr.

N excr./N int.

N excr/lit. Milk

G1

G2

G3

G4

Diet efficiencies

• Around mean efficiencies variation coeff. extend 14 - 35 %

• Large progress margins inside groups

Coeff. NR Energies MJ/unité

Coeff. GHG eqCO2

INDIRECT Energies & Emissions (Extraction, Manufacturing, Transport,)

DIRECT Energies & Emissions (Fuel, Electricity, Gaz,…)

FARM

INPUTS Fertilizers, concentrates fuel, water, …: plastics, …

Machinery

Housing

PRODUCTS Litre, kg,

Gross Energy

• Life cycle analysis(LCA) • 31 dairy farms in tropical landscapes

Farm scale efficiencies

3.5 3.0 2.5 2.0 1.5 1.0

40

35

30

25

20

eq tCO2/1000L

Fuel Eq /

100 l M

ilk

CAFR

GREG

HtStJO

OUEST

PALM

17.6 - 40.7

26.2 EQF

1.4 - 3.4

2.7 t eq CO²

Farm scale efficiencies

µ Landscapes

• A large variability around means • Not a landscape attribute

2.5 2.0 1.5 1.0 0.5

+

-

kg Milk / kg Suppl purchased

+

-

eq t

CO

2/1

000L m

ilk

Rev

€ /

Kg

milk

-

+

Fuel

eq

. / 1

00

l m

ilk

Ecological intensification

• A way toward multiefficiency progress • Not only a matter of feeding • Importance of daily management practices : Health,

reproduction, mortality, culling…

BIOGAS production : Hyp. : 1 700 m3 de lisier/an

50 000 kWh electricity . + 85 000 kW heat (to valorise?) Energy efficiency= 0,65 PHOTOVOLTAIC production : Hyp. : 200 m² de capteurs / roofs => 38 000 kWh electricity Energy efficiency= 0,59

Combination: EE = 0,84 vs 0.39

Additional functions on the farm

Environmental and economic efficiency

Toward new markets ?

65 300

11 000

5 600

2 700

46 000

Gain

9,2

-

-

1,1

8,1

Gain

336 14

576 24

672 28

Pot.

Payments Improvements

8 952 373 TOTAL

312 13

? ?

2 880 120

4 176 174

65 300

11 000

5 600

2 700

46 000

Gain

( € )

9,2

-

-

1,1

8,1

Gain

(EQF/100L)

336 14

576 24

672 28

(en € ) (en € )

t eqCO2

8 952 373 TOTAL

312 13

? ?

2 880 120

4 176 174

GHG avoided

CC manufacturing &

transport

Animal CH4

Fert. manufact. &

transport

Pasture CO2

sequestration

Manure GHG avoided

emission

GHG for electricity

avoided

GHG for electricity

avoided

Conc. Use efficiency

Substitute Min./Org. Fertiliser

Biogas production

Photovolt. production

Data Envelopment Analysis (DEA) : non-parametric frontier model

INPUTS (land, labor, forage, feeds …)

OUTPUTS (milk, meat, GHG,

nitrogen…)

Inefficient firm

Production frontier

Efficient firm

Projection on the frontier

Projection direction

• Efficiency of firms assessed by mathematical formulation of a production technology characterized by inputs and outputs

• Allows integration of undesirable outputs (GHG, Nitrogen excess, …)

• Directional distance function characterize path of inefficiency reduction

Adressing diversity of efficiencies

Classical « efficacy » logic

Directions in inefficiency reduction

Good outputs

Bad outputs

Inputs level fixed

• Efficiency can be considered / different projection direction on the frontier

Good outputs

Bad outputs

Farmer’s view : optimize milk production, Society’s view : reduce pollution

Good outputs

Bad outputs level fixed

Inputs

Dairy coop. view : increase inputs to reach the optimal amount of good production

Dataset for Data Envelopment Analysis

Input (x) / Output (y) Units Mean Standard deviation

Min Max

Milk production (MP) : Tons of milk 285.8 140.5 83.7 669.4

Nitrogen surplus (NS) : Kg of nitrogen 6090.8 3673.5 1371.5 21780.4

Greenhouse gases (GHG) : Tons of gas (eq. CO2) 488.4 244.1 148.6 1149.6

Livestock unit (LU) : Livestock unit 61.4 26.3 27 131.2

Feed charges (FC) : Tons of dry matter 231.9 114.1 69.19 525.1

Total labor (L) : Total labor (h)

7414.8

3398.2

2190

18158

land endowment (LE) : Surface (Ha) 22,2 16,0 3 72

gy

1by

2by

1x

2x

3x

4x

• 4 inputs, 1 good output and 2 undesirable outputs are considered :

Eco-efficiency assessment

• Progress margin can be assessed according to difft point of view

Milk production Emissions, Surpluses Inputs

GHG NS Feed

charges Herd Labor

Collective 25,65% 31,19% 31,98% 34,63%

Society -22,79% -24,12%

Farmers 13,04%

• A potential milk production raise of 25.65% is possible if farmers accept to increase their inputs by more than 30%.

• If inefficiency reduction only focus on pollution reduction, GHG and nitrogen surpluses can be reduced by 22.79% and 24.12 % respectively

• Farmers can increase their milk production by 13.04 %, given their current inputs and pollution levels

Compared GHG levels

• Efficiency improvement allow a significant reduction of GHG, below the mean value in France

• With resources reallocation, GHG level is even more reduced, and may become lower than minimal emission rate identified by the FAO

0

0.5

1

1.5

2

2.5

3

3.5

4

Observed level Optimal level optimal levelwith

reallocation

FAO (region min)

PLANETE (mini)

PLANETE (maxi)

PLANETE(mean)

Collective

Farmers

Society

Kg

eq. C

O2/L

Exploring beyond the frontiers the domain of possible efficiencies

Promising approach to measure potential inefficiency reduction in different context by generating large datasets and identifying the optimal amount of production (and pollution) for given levels of inputs

whole-farm dynamic model

Global analytic scheme

P1

-

+

P2

-

+

Pn

-

+

Simulations Input_1 Input_2 Input_3 Output_1 Output_2

Output_3

1 143 1289 35 12908 100 987

2 145 1376 39 13765 122 876

3 156 1298 63 14002 153 765

4 163 1498 29 13788 176 786

4 122 1538 54 12982 263 796

n … … … … … …

Improve efficiency determinant

.

.

.

Conclusions

• Efficiency shift, a real challenge for the future

• Complexity in adressing multiple goals efficiency

• Still a lot to do to observe compare reconsider experiment

• Scaling the efficiencies

• Marginal cost of efficiencies improvements

• Sum of small efficiency increase vs a unique integrated effcicient model

• Multi, (eco) efficiency value chaining

Tank