Ms. Isabelle Cousin, INRA, France. Global Symposium on Soil Erosion (GSER19), 15 - 17 May 2019 at FAO HQ.

1. Evaluating the “Soil stabilisation and control of erosion”
ecosystem service provided by agricultural ecosystems
over the French territory
J. Daroussin, I. Cousin, A. Tibi, Y. Le Bissonnais,
A. Girardin, A. Meillet, P. Choler, O.Therond
INRA, France
1

2. 2
Rationale
French context
 4 million hectares of grassland removed between 1971 and 2000
 Increased risk of soil erosion
 Develop agricultural ecosystems exhibiting a high level of control of erosion
Objective of this work
 To propose a robust methodology to quantify the ecosystem service (ES)
linked to erosion control, at fine scale, for large areas
Framework
 French National Assessment of Ecosystem Services (EFESE)
 EFESE-EA project leaded by INRA for agricultural ecosystems

3. Ecosystem Socio-economic system
Other
ecosystems
Socio-economic
environment
Farmer
C
C
C
CC ES
ESC
C
Agricultural ecosystem
F
F
Benefit
(farmer)
Society
The EFESE-EA conceptual model for ES evaluation
Benefit
(society)
Biophysical determinants F Biophysical
exogenous factors
Anthropic
exogenous factors
F
Soil stabilisation and erosion control
. Preserve the soil capital and
the potential of production
. Limit irrigation
. Limit flooding and associated
mudslides
. Preserve soil water quality

4. The conceptual model applied to erosion ES
Biophysical determinants F Biophysical
exogenous factors
Anthropic
exogenous factors
F Anthropic
exogenous factors
Spatio temporal
configuration of
vegetation
Soil mineral and organic
composition
Ecosystem Socio-economic system
Other
ecosystems
Socio-economic
environment
Farmer
C
C
C
CC ES
ESC
C
Agricultural ecosystem
F
F
Benefit
(farmer)
SocietyBenefit
(society)

5. The conceptual model applied to erosion ES
Biophysical determinants F Biophysical
exogenous factors
Anthropic
exogenous factors
F Anthropic
exogenous factors
Spatio temporal
configuration of
vegetation
Soil mineral and organic
composition
Topography Rainfall
characteristics
Ecosystem Socio-economic system
Other
ecosystems
Socio-economic
environment
Farmer
C
C
C
CC ES
ESC
C
Agricultural ecosystem
F
F
Benefit
(farmer)
SocietyBenefit
(society)

6. The conceptual model applied to erosion ES
Biophysical determinants F Biophysical
exogenous factors
Anthropic
exogenous factors
F Anthropic
exogenous factors
Spatio temporal
configuration of
vegetation
Soil mineral and organic
composition
Topography Rainfall
characteristics
Ecosystem Socio-economic system
Other
ecosystems
Socio-economic
environment
Farmer
C
C
C
CC ES
ESC
C
Agricultural ecosystem
F
Benefit
(farmer)
SocietyBenefit
(society)
F
Irrigation

7. Spatio temporal
configuration of
vegetation
Soil mineral and organic
composition
Topography Rainfall
characteristics
Soil protection factor
by vegetation (bare
soil to forests and
permanent grasslands)
Soil
Crusting
Soil
Erodibility
 French Land Parcel
Identification System
 Corine Land Cover
 MODIS data
1:1M European Soil Geographical Database:
 Soil type
 Surface texture
 Parent material
Erosivity = f(slope,
runoff contributing
area)
French IGN Digital
Elevation Model at
25 m resolution
Rainfall agressiveness
= f(rainfall depth,
rainfall intensity)
Soil stabilisation and control of erosion
Météo-France data (30 years):
 SAFRAN 8 km resolution
 Aurhély model at
1 km resolution

8. Soil stabilisation and control of erosion
Soil protection factor
by vegetation (bare
soil to forests and
permanent grasslands)
Soil
Crusting
Soil
Erodibility
1:1M European Soil Geographical database:
 Soil type
 Surface texture
 Parent material
 French Land Parcel
Identification System
 Corine Land Cover
 MODIS data
 Current erosion rate
 Erosion rate for bare soil
everywhere
 Erosion rate for permanent
cover everywhere
Maximum ES level =
(Erosion rate for bare soil)
– (Erosion rate for perm. cover)
Current ES level =
(Erosion rate for bare soil)
– (Current erosion rate)
Erosivity = f(slope,
runoff contributing
area)
Rainfall agressiveness
= f(rainfall depth,
rainfall intensity)
Météo-France data (30 years):
 SAFRAN 8 km resolution
 Aurhély model at
1 km resolution
French IGN Digital
Elevation Model at
25 m resolution
Erosion rateOne output per season ; annual average

9. Levels of Ecosystem Service
Current ES level Maximum ES level
(Erosion rate for bare soil) - (Current erosion rate) (Erosion rate for bare soil) - (Erosion rate for permanent cover)
Masque toutes Surface AGricoles (SAG)
serviceANU100
0 t/ha/year of stabilised soil
> 0 to 1
> 1 to 3
> 3 to 5
> 5 t/ha/year of stabilised soil

10. Levels of Ecosystem Service
Relative ES level
(Current ES level) / (Maximum ES level)
0 to 0.7
0.7 to 0.8
0.8 to 0.95
0.95 to 1
because serviceMax is = 0
EFESE
Écosystèmes Agricoles
(modèle Mesales)
06/03/2019 10:31:20
0 100 200 300
km
Masque toutes Surface AGricoles (SA
serviceRelatifANU100
0: because service is = 0
0 to 0.7
0.7 to 0.8
0.8 to 0.95
0.95 to 1
because serviceMax is = 0
Current ES level Max. ES level

11. Soil stabilization and erosion control at the
French scale
Vegetation effect
 Predominant role of vegetation cover and seasonal phenology
 Agricultural practices linked to a permanent soil cover: cover crops during fallow
period, management of surface residues, sowing under permanent cover
(especially for cropping areas with intense autumn and winter rainfalls)
Main improvement of the MESALES model for EFESE-EA
 Seasonal variation of the vegetation cover
Possible additional improvements
 Use of soil databases with data at finer resolution
 Develop new pedotransfer functions for erodibility
 Implement the retroaction of vegetal cover on the soil organic matter
 Methodology available to be run at the European or Global scales
 Evaluation of land cover and land-use change scenarios to test
political tools promoting high level services

12. Thank you for you attention !
Acknowledgements - This work was completed in the framework of the “EFESE -
Ecosystèmes Agricoles” study by INRA at the request of the French Ministry of Ecology. It
was also supported by INRA’s own research program on Ecosystem Services. The EFESE-EA
study involved about seventy scientific experts with complementary disciplinary expertise
(ecology, agronomy, hydrology, animal science, economy, etc.) and data management
specialists.
For more information, see the EFESE-EA report (in French), chapter 8.5 :
http://institut.inra.fr/Missions/Eclairer-les-decisions/Etudes/Toutes-les-
actualites/EFESE-services-ecosystemiques-rendus-par-les-ecosystemes-agricoles

14. 14

15. The EFESE-EA conceptual model for ES evaluation
Ecosystem Socio-economic system
Other
ecosystems
Socio-economic
environment
Farmer
C
C
C
CC ES
ESC
C
Agricultural ecosystem
F
F
Benefit
(farmer)
SocietyBenefit
(society)
Biophysical determinants F Biophysical
exogenous factors
Anthropic
exogenous factors
F

16. 16
Levels of Ecosystem Service
Relative ES level
(Current ES level) / (Maximum ES level)
0 to 0.7
0.7 to 0.8
0.8 to 0.95
0.95 to 1
because serviceMax is = 0
EFESE
Écosystèmes Agricoles
(modèle Mesales)
06/03/2019 10:31:20
0 100 200 300
km
Masque toutes Surface AGricoles (SAG)
serviceRelatifANU100
0: because service is = 0
0 to 0.7
0.7 to 0.8
0.8 to 0.95
0.95 to 1
because serviceMax is = 0