# A modeling framework for designing and assessing multi-functional agricultural landscapes with scenario analysis

Pierre Chopin, Jean-Marc Blazy, Loic Guinde, Jacques Wéry, Thierry Doré

► To cite this version:

Pierre Chopin, Jean-Marc Blazy, Loic Guinde, Jacques Wéry, Thierry Doré. A modeling framework for designing and assessing multi-functional agricultural landscapes with scenario analysis. 5. International Symposium for Farming Systems Design (AGRO2015), Sep 2015, Montpellier, France. 553 p., 2015, Proceedings of the 5th International Symposium for farming systems design "Multi-functional farming systems in a changing world". hal-02740901

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INRA
SCIENCE & IMPACT

# A modeling framework for designing and assessing multi-functional agricultural landscapes with scenario analysis

AgroParisTech
INSTITUT DES SCIENCES ET INDUSTRIES DU VIVANT ET DE L'ENVIRONNEMENT
PARIS INSTITUTE OF TECHNOLOGY FOR LIFE, FOOD AND ENVIRONMENTAL SCIENCES

Pierre CHOPIN*¹, Jean-Marc BLAZY¹, Loïc Guindé¹, Jacques Wery², Thierry DORÉ³,⁴

¹ INRA, UR1321, ASTRO Agrosystèmes tropicaux, F97170 Petit-Bourg, Guadeloupe

² Montpellier Sup Agro UMR System 2 place Viala, 24060 Montpellier, France

³ AgroParisTech, UMR 211 Agronomie, F-78850 Thiverval-Grignon, France

⁴ INRA, UMR 211 Agronomie, F-78850 Thiverval-Grignon, France

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Montpellier
Agro

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REGION
GUADELOUPE

l'Europe
's'Engage
en Guadeloupe

## Introduction

In order to ascertain whether a combination of levers of change of local agriculture can drive agriculture towards sustainability, we designed a modeling framework, to explore successive steps of scenario development and assessment with indicators. To this end we introduce an approach based on several types of scenarios.

**Objective:**

Obtaining multi-functional landscapes with several levers tested in a logical order to improve the overall response of agriculture to sustainability issues

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## Modeling framework

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## Material & method

For adopting such framework, a regional optimization model coupled to regional indicators are needed for the sustainability assessment.

We used the MOSAICA model (Chopin et al., 2015) to design and assess agricultural landscapes in Guadeloupe (french island in the Caribbean). MOSAICA is a bioeconomic model that simulate farmer's decision process in term of cropping system allocation to plots through an optimization of the sum of farmers' individual utilities.

The model can be used to assess the potential of landscape to fullfill sustainability objectives by optimizing other functions (e.g. maximizing food crops production).

The model is used for all the steps of the framework described here. Relevant levers that could improve the response to sustainability issues while preventing from negative impacts are combined in a "Go sustainable scenario"

## Results

The exploratory scenario designed to respond to the energy self sufficiency issue tested the implementation of a biomass plant production. It increased the production of energy without adverse effects on other issues. This lever was combined to other relevant levers (new horticulture cropping systems, an increase of workforce at regional scale) in a "Go sustainable scenario"

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The Go sustainable scenario increased the overall sustainability of agricultural landscapes with the development of energy crops all over Guadeloupe and organic horticulture next to rivers

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<figure><img src="image_10.png" /><figcaption>Current landscape in 2010</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>Go sustainable scenario</figcaption></figure>

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Positive impacts in the south of Guadeloupe on the water quality in the abstraction sources

## Discussion

The modeling framework guides the use of the regional model that could be used in other regions to help identify the most appropriate levers to increase the response of agriculture to sustainable development.

This holistic approach provides analysis of changes that occur at the regional, the farm and the field scale, and can highlight the evolution of externalities of cropping system mosaics in a quantitative and spatially explicit way.

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INRA
SCIENCE & IMPACT

•email: pierre.chopin@antilles.inra.fr
INRA Antilles-Guyane, UR1321, AgroSystèmes Tropicaux
F-97170, Petit-Bourg (Guadeloupe), France
http://www.antilles.inra.fr/astro

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FSD5
Proceedings

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SEPTEMBER
7-10, 2015
Le Corum
MONTPELLIER
France

5th International Symposium
for Farming Systems Design

"Multi-functional farming systems
in a changing world"
# A MODELING FRAMEWORK FOR DESIGNING AND ASSESSING MULTI-FUNCTIONAL AGRICULTURAL LANDSCAPES WITH SCENARIO ANALYSIS

Pierre Chopin *±<fnref n="1" />, Jean-Marc Blazy<fnref n="1" />, Loïc Guindé<fnref n="1" />, Jacques Wery<fnref n="2" /> & Thierry Doré<fnref n="3" />,<fnref n="4" />

* Speaker

Corresponding author: (pierre.chopin@antilles.inra.fr)

## 1 Introduction

In order to insure the provision of food and services by agriculture while limiting its negative impacts, innovative agricultural systems have to be designed. The design of such systems has shown some limits in addressing regional and global issues. For instance, at the field scale, some cropping systems may fail to reach the objectives defined at the regional scale due to the low scaling integration and the spatial heterogeneity in the region. Model-based prototyping of agricultural landscapes can allow the impact assessment at regional level of drivers that act at field, farm and regional levels. In order to ascertain whether a combination of levers can drive agriculture towards sustainability, we designed a modeling framework, to explore successive steps of scenario development and assessment with indicators. To this end we introduce an approach based on several types of scenarios.

## 2 Materials and Methods

The method is built to i) understand the potential levels of sustainability that can be reached by the cropping system mosaics and ii) gain knowledge on the potential levers of change of the cropping system mosaics (Fig. 1). The framework guides the assessment of the consequences of several types of scenario, with a regional bioeconomic model, on the organization of cropping systems. Indicators are used to assess the cropping systems externalities at regional scale. An iterative approach is presented to guide the use of the model with different phases (Fig. 1): scenarios are built in a pre-modeling phase; they are implemented in a modeling phase for visualizing their consequences on the cropping system mosaics; the post-modeling phase assesses the contribution of the cropping system mosaics to sustainable development.

<figure><img src="image_2.png" /><figcaption>Fig.1. The modelling framework for building sustainable agricultural landscapes</figcaption></figure>

<footnote n="1">¹ INRA, UR1321 ASTRO Agrosystèmes Tropicaux, F-97170 Petit-Bourg (Guadeloupe), France</footnote>

<footnote n="2">² Montpellier Sup Agro UMR System 2 place Viala, 24060 Montpellier, France</footnote>

<footnote n="3">³ AgroParisTech, UMR 211 Agronomie, F-78850 Thiverval-Grignon, France</footnote>

<footnote n="4">⁴ INRA, UMR 211 Agronomie, F-78850 Thiverval-Grignon, France</footnote>
Proceedings of the 5th International
Symposium for Farming Systems Design

FSD5

Montpellier, September 7 - 10, 2015

Editors: Gritti Emmanuel S. – Wery Jacques

Cover design: Olivier Piau – Lisbeth Michel

Final edition: Gritti Emmanuel S.

Special thanks to the scientific committee's members for their commitment in the reviewing and editing processes
We built our framework around the MOSAICA regional bioeconomic model (Chopin et al., submitted). MOSAICA optimizes the overall farmer's utilities by allocating cropping systems to their spatially located plots. The allocation process of cropping systems to plots, recorded in a geographical database, is driven by several types of constraints or objectives implemented at different spatial scales among which biophysical, economic, structure constraints at field, farm, sub-regional or regional scales. The optimization of farmer's utilities or other variables of the system produce new agricultural landscapes that are assessed with a set of sustainability indicators.

In our framework, the MOSAICA model is used with four different types of scenario for prototyping agricultural landscapes for one specific goal (such as energy self-sufficiency). First, short-term optimized scenario provides a target value by optimizing one given sustainability indicator (e.g. the production of biomass for electricity). Secondly, an exploratory scenario combines several types of levers (economic, agronomic...) to reach the target value defined before (the overall farmer's revenue is maximized). Thirdly, normative scenario is introduced to assess whether or not the target can be reached with the levers from the exploratory scenario. Fourthly, a long-term optimized scenario is parameterized to assess the relevance of levers to improve the long-term potential of the system (by optimizing the production of biomass with the levers selected). The levers that improve the state of the system for each objective, (increase food production, employment...) are selected and combined in a last exploratory scenario called "Go sustainable" scenario to improve the overall response of agricultural landscapes to sustainable development.

## 3 Results - Discussion

<table><caption>Table 1. Results for the energy self-sufficiency objective with the different type of scenario</caption><thead><tr><th rowspan="2">Sustainability objective</th><th rowspan="2">Indicator</th><th rowspan="2">Initial</th><th colspan="4">Type of scenarios</th></tr><tr><th>Short-term optimized</th><th>Exploratory</th><th>Normative</th><th>Long-term optimized</th></tr></thead><tbody><tr><td>Energy self-sufficiency</td><td>Potential production of electricity (MW)</td><td>30</td><td>52</td><td>56</td><td>56</td><td>93</td></tr></tbody></table>

We here present some results from the use of the framework in Guadeloupe, a French archipelago in the Caribbean for the energy self-sufficiency objective (Chopin et al., to be submitted). The levers tested are the decrease of subsidies for sugar, the setting up of a biomass industry for electricity production and the addition of a crop energy activity for farmers. The response to the sustainability objective increases with levers (Table 1) that help achieve the objective of producing 56MW.yr⁻¹ and also improve the potential of response of the landscape in long-term scenario to 93MW.yr⁻¹.

<figure><img src="image_3.png" /><figcaption>Fig. 2. Evolution of responses to sustainable issues compared to the initial situation</figcaption></figure>

The "Go sustainable scenario" which combines all the relevant levers selected for each of the five objectives improves the system by increasing its contribution to each objective selected (Fig. 2). For instance, the response of the food self-sufficiency objective increased by 150% and the overall agricultural value doubled compared to the initial landscape due to the development of crop-gardening, in the south of Guadeloupe, and energy crops within the entire region.

## 4 Conclusions

The modeling framework guides the use of the regional model could be used in other regions to help identify the most appropriate levers to increase the response of agriculture to sustainable development. This holistic approach provides analysis of changes that occur at the regional, the farm and the field scale, and can highlight the evolution of externalities of cropping system mosaics in a quantitative and spatially explicit way.

## References

* Chopin, P., Blazy, J.-M., Guindé, Loïc., Doré, T. MOSAICA: a multi-scale bioeconomic model for the design and ex ante assessment of cropping system mosaics. Submitted to Agricultural Systems.

* Chopin, P., Blazy, J.-M., Guindé, Loïc., Wery, J., Doré, T. Designing multi-functional landscapes in agricultural regions: Application to the Guadeloupe Island. To be submitted to Global Environmental Change.
## SCIENTIFIC COMMITTEE

Francois AFFHOLDER, CIRAD, France

Senthold ASSENG, University of Florida, USA

Jean Marc BARBIER, INRA Montpellier, France

Marc BENOIT, INRA Mirecourt, France

Jacques Eric BERGEZ, INRA Toulouse, France

Peter CARBERRY, ICRISAT, India

Ken CASSMAN, University of Nebraska, USA

Olaf CHRISTEN, Agronomy and Organic Farming University of Halle, Germany

Lionel DABBADIE, UMR ISEM, CIRAD

Santiago DOGLIOTTI, Universidad de la Republica, Uruguay

Patrick DUGAN, CGIAR Research Program on Aquatic Agricultural Systems, WorldFish, Malaysia

Michel DURU, INRA Toulouse, France

Frank EWERT, Bonn University, Germany

Bruno GERARD, Global Conservation Agriculture Program CIMMYT, Mexico

Ken GILLER, Wageningen UR, The Netherlands

Bernard HUBERT, Agropolis International, France

Marie Helene JEUFFROY, INRA Grignon, France

Philippe LECOMTE, CIRAD, France

Lingling LI, Gansu Agricultural University, China

Wei li LIANG, Hebei Agricultural University, China

Eric MALEZIEUX, CIRAD, France

Charles Henri MOULIN, Montpellier SupAgro, France

Bruno RAPIDEL, CIRAD, Costa Rica

Daniel RODRIGUEZ, University of Queensland, Australia

Pablo TITTONELL, Wageningen UR, The Netherlands

Martin VAN ITTERSUM, Wageningen UR, The Netherlands

Jacques WERY, Montpellier SupAgro / ESA, France Chair of the FSD5 Scientific and
Organizing Committees

## LOCAL ORGANIZING COMMITTEE

Coordination:

Brigitte Cabantous, Agropolis International

Hatem Belhouchette, UMR System, IAM.M

Emmanuel S. Gritti, UMR System, Montpellier SupAgro

Laure Hossard, UMR Innovation, INRA

Amandine Lurette, UMR Selmet, INRA

Isabelle Massaï, Chaire AgroSys

Raphaël Metral, UMR System, Montpellier SupAgro

Olivier Mikolasek, UMR ISEM, CIRAD

Carole Picard, UMR System, INRA

Sandrine Renoir, UMR System, CIRAD

Charles Staver, Bioversity International

Nathalie Villemejeanne, Agropolis International
# FOREWORD

Eight years after the launching of the FSD (Farming Systems Design) initiative in Catania (2007), the European Society for Agronomy (http://www.european-agronomy.org) has been mandated to organize its fifth symposium with the specific objective to strengthen the interdisciplinary and methodological focus of FSD. The overall objective is to promote research and capacity building on methodologies for the analysis and design of Agricultural Systems on a worldwide level. The research focus of this FSD community is the farm system level, the interactions and feedbacks at lower and higher levels of integration and the tools and methods required for understanding and implementing multi-functional farming systems expressing good trade-offs between agricultural production and ecosystems services. In a time when challenges for farming systems are increasingly defined by other systems operating at higher scales (food security, climate change, natural resource conservation, poverty alleviation...) it is important to keep an active scientific community sustaining innovation and capacity building on farming systems and their interfaces with those embedding systems and global issues.

These proceedings are aimed to serve as a compendium of the on going research in the FSD domain when considered worldwide and across the various sectors of agriculture (including fish-based systems). They include all the presentations (orals and posters) selected by the Scientific Committee of the 5th Farming Systems Design conference held in Montpellier (France) from September 7 to 9, 2015 (http://fsd5.european-agronomy.org/). A part of these communication have also been selected to compose special issues of major journals in the domain (Agricultural Systems and European Journal of Agronomy) and others will give raise to individual submissions in other journals.

The major achievements and challenges of the FSD approach are browsed through the 6 short sessions of the symposium "Farming Systems Design in Action: Methods, Achievements and Challenges" and are further developed and illustrated in the thematic sessions covering:

* *The grounds of the FSD approach* in quantitative analysis of crops (session T1. Assessing performances and services of cropping systems) and farms (T2. Assessing performances and services of farming systems).

* *The research frontiers on methodologies* for systems experiments at field level (W3. Cropping systems design: what can we do with field experiments and expert knowledge?), support of transition pathways at farm level (W4. Farms in transition), integrated analysis (T7. Scaling up from farm to landscape and multiscale scenario analysis of agricultural systems) and design (T8. Co-design and co-innovation with farmers and stakeholders) of agricultural systems.

* *A specific focus on crop models* (T3. Crop modelling and yield gap analysis for agricultural systems analysis and design) and *farm models* (T4. What's new with bio-economic models for the analysis and design of agricultural systems?) and the way they can be developed and used to sustain system's analysis and design.

* *Three typical challenges* on which the multi-scale and multi-domain FSD approach is likely to bring significant breakthrough: T5. Designing Climate Smart Agricultural Systems; T6. Designing sustainable agricultural systems with legumes; W6. Pathways for sustainable intensification of African agriculture?

* *Applications of the FSD approach to specific types of farming systems:* W1. Animal-based systems and crop-livestock interactions at farm and territory level; W7. Aquaculture systems, W2. Annual crops based systems; W5. Silvo-arable and silvo-pastoral systems.

**Prof. Jacques Wery**

(FSD5 Chair and ESA Executive Secretary)
# Table of content

## Plenary symposium "Farming Systems Design in Action: Methods, Achievements and Challenges"

**Systems Analysis for management and design in Agriculture: can we do it with only two concepts ?**

Jacques Wery

**Designing ecological intensive farming systems in China: Challenges and strategies**

Fu Chen, Wei-Li Liang, Qing-Quan Chu, Hai-Lin Zhang & Tian-Zhi Ren

**From cropping systems design towards sustainable agrifood systems design: new challenges for agronomists**

Jean-Marc Meynard, Marie-Hélène Jeuffroy, Amélie Lefèvre, Marie-Benoît Magrini & Camille Michon

**Quantifying beef production gaps of two farming systems in the Charolais basin, France**

Aart van der Linden, Gerrie W.J. van de Ven, Simon J. Oosting, Martin K. van Ittersum & Imke J.M. de Boer

**Path dependence and transition: a theoretical perspective on farm**

Alfons Balmann, Franziska Appel, Frans Hermans, Karin Kataria, Arlette Ostermeyer, Zhanli Sun & Vladislav Valentinov

**Innovation by smallholder farmers for more diverse and intensive farming systems**

Bill Bellotti, Gavin Ramsay, Ashok Kumar, Avijit Choudhury & Nivedita Narain

**Analysing farming system design activities in the light of Design Studies concepts**

Marie-Hélène Jeuffroy, Marianne Cerf, Lorène Prost & Jean-Marc Meynard

**Bridging the gaps between ecological principles and actions for designing biodiversity-based agriculture**

Duru M, Benoît M, Bergez JE, Jeuffroy MH, Justes E, Martin G, Martin-Clouaire R, Meynard JM, Ozier-Lafontaine H, Prost L, Rapidel B,

Toffolini Q, Sarthou JP & Therond O

**Exploration of windows of opportunity for improved nutrition, productivity and resource management at the landscape level**

Jeroen C.J. Groot, Fabrice Declerck, Roseline Remans, Natalia Estrada Carmona, Stephanie Alvarez, Nester Mashingaidze, Celine Termote,

Ray-Yu Yang, Jessica Raneri & Gina Kennedy

**Impact of farming systems on agricultural landscapes and biodiversity: from plot to farm and landscape.**

Gilles Martel, Stéphanie Aviron, Hugues Boussard, Alexandre Joannon & Bénédicte Roche

**Policies and institutions fostering sustainable agricultural systems**

Erik Mathijs, Alfons Balmann & Isabelle Bonjean

## T1. Assessing performances and services of cropping systems (field level experiments, surveys and databases)

Chair: David Parson, University of Tasmania

Co-chair: Eric Malézieux, CIRAD

**Improving resource use efficiency and soil conservation in smallholder vegetable systems though improved soil tillage and residue management**

Florence Alliaume, Walter A.H. Rossing, Pablo Tittonell & Santiago Dogliotti

**Impact of a legume living mulch on winter weat yield and its nitrogen nutrition**

Jérôme Labreuche, Jean-Pierre Cohan, Edouard Baranger, Romain Légère & Stéphane Jézéquel

**Integrated double-mulching practices optimizes soil temperature and improves soil water utilization in arid environments**

Qiang Chai, Jihua Yu, Wen Yin, Cai Zhao, Falong Hu & Yantai Gan

**A preliminary study on adaptability of maize-maize double cropping in Hebei area of the North China Plain**

Wei-li Liang, Gui-yan Wang, Fu Chen, Dan Wu, Hai-lin Zhang & Hong-zhan Lv

**Trade-off between productivity and nitrous oxide emissions in subtropical broad-acre systems - a modelling approach**

Henrike Mielenz, Peter J. Thorburn, Clemens Scheer, Massimiliano De Antoni Migliorati, Mike Bell & Peter R. Grace

**Impact of two simple fertilization strategies on farmers' product carbon footprints and gross margins of wheat and maize production in the North China Plain**

Nan Ha, Til Feike, Haifeng Xiao & Enno Bahrs

**Environmental performance of nitrogen fertiliser limits on root crops potatoes and sugar beets**

Karoline D'Haene, Joost Salomez, Stefaan De Neve, Jeroen De Waele & Georges Hofman

**Farming systems to support flexible climate response strategies for cambodian smallholder farmers**

N.P. Dalgliesh, P.L. Poulton, P. Charlesworth & L. Le Non

**Reducing pesticide use while reaching economic and environmental sustainability in Arable Farming**

Martin Lechenet, Vincent Bretagnolle, Christian Bockstaller, François Boissinot, Marie-Sophie Petit, Sandrine Petit & Nicolas M. Munier-Jolain

**Using FADN to derive cropping scheme distribution in Italy**

Giuliano Vitali, Sergio Albertazzi, Davide Rizzo, Concetta Cardillo & Guido Baldoni

**Characterization and quantification of robustness for designing more sustainable and robust wheat production**

Nicolas Urruty, Christian Huyghe, Delphine Tailliez-Lefebvre & Philippe Gate

**Cut fallow to replace black fallow in an organic production system**

Göran Bergkvist, Kjell Mangerud, Ewa Magnuski & Lars Olav Brandsæter

**Assessing environmental impacts of cropping systems: comparison of an indicator- based and a life-cycle analysis-based method**

Christian Bockstaller, Marine Marion-Wuillemin, Nouraya Akkal-Corfini, Nicolas Munier-Jolain & Michael S. Corson

**Water productivity, Irrigation management and Systematization for Rice Farming Systems in Uruguay**

Gonzalo Carracelas, Claudia Marchesi & Andrés Lavecchia

**Phosphorus offtake by silage maize and cut grassland in temperate regions**

Karoline D'Haene & Georges Hofman

**The effect of bio-phosphate fertilizer to increasesoil phosphate, growth and yield of maize and P fertilizer efficiency on marginal soil**

Betty Natalie Fitriatin, Anny Yuniarti & Tien Turmuktini

**Effect of green manure on chemical, physical of soil and yield of millet**

Choon-woo Lee, Min-tae Kim, Jin-hee Ryu, Jong-seo Choi, Min-tae Kim, Suk-jin Kim, Kang-sup Kim & Ki-do Park
**Application of Organic Fertilizers for pesticide degradation from Agricultural Soil under Controlled Conditions**
Mohammad Mehdizadeh

**Designing innovative strategies of nitrogen fertilization by coupling diagnosis of the uses of existing tools and participatory workshops.**
Clémence Ravier, Marie-Hélène Jeuffroy, Philippe Gate, Jean-Pierre Cohan & Jean-Marc Meynard

**Impacts of crop rotation, soil tillage and irrigation on yield and agroecological parameters: an assessment of different energy cropping systems in Northeast Germany**
Timm Sauer, Moritz Reckling, Gunhild Rosner & Johannes Hufnagel

**Decline of rice grain yield under delayed transplanting in wheat-rice double cropping system in South Korea**
Shingu Kang, Bonil Ku, Wangyu Sang, Hyunseok Lee, Hongkyu Park, Youngdoo Kim, Jiiyoung Shon, Woonho Yang & Jeomho Lee

**Improvement of vineyard sustainability according to biogeochemical cycle of nitrogen in field**
Marie Thiollet-Scholtus, Najat Nassr, Aude Langenfeld, Mohamed Benbrahim, Lionel Ley, Julie, Grignion & Christian Bockstaller

**Silobag Storage: A Novel Technology for Modern Farming Systems**
Hernán A. Urcola & Ricardo E. Bartosik

**The effects of different tillage methods on soil temperature, water content, bulk density, and yield of winter wheat in southern Henan of China**
De-qi Zhang & Xiang-dong Li

## T2. Assessing performances and services of farming systems (farm level surveys and databases)

Chair: Jean-Marc Barbier, INRA

Co-chair: Wei-li Liang, Hebei Agricultural University

**Adaptations of farming systems to cities: periurban farms beyond the short food- supply chains**
Marraccini Elisa, Houdart Marie, Debolini Marta, Filippini Rosalia, Lardon Sylvie & Bonari Enrico

**Food security, income and agriculture in the new ruralities of Central America**
Diego Valbuena, Santiago López-Ridaura, Mark van Wijk, Pablo Siles, Edwin García & Orlando Téllez

**Ecological intensification in Rio de la Plata grasslands**
Pablo Modernel, Walter Rossing, Santiago Dogliotti, Marc Corbeels, Valentin Picasso & Pablo Tittonell

**Optimizing milk and beef production systems on farm level**
Martina Alig, Pierre Mischler & Hélène Chambaut

**Farming system models for supporting farm resilience: research needs, gaps and promising approaches**
Quang Bao Le

**Factors influencing the flexibility of farming systems – Case study of the Flemish beef farming sector**
Laura Schotte, Jonas Hanssens, Xavier Gellynck, Fleur Marchand & Erwin Wauters

**Methods for designing farms that include a coal seam gas extraction enterprise.**
Neil I. Huth, Perry L. Poulton, Brett Cocks & Ethel Samalca

**Interview-based structuring of operational decision-making by farmers**
Charlotte Daydé, Stéphane Couture & Roger Martin-Clouaire

**Strategies to manage crop planning complexity in very diversified direct selling farming systems: the example of organic market gardeners**
Kevin Morel & François Léger

**Labour Productivity Analysis in Mixed Family Farm Systems to support a Co- Innovation Process**
Paula Colnago, Gina Favretto & Santiago Dogliotti

**Evaluation of sustainability of peasant farming systems in VallesCalchaquies (NW of Argentina)**
Maria Daniela Chavez & Gonzalo Carlos Bravo

**Development of a trajectory to support sustainable choices at farm level**
Ine Coteur, Fleur Marchand, Lies Debruyne, Floris Dalemans & Ludwig Lauwers

**Evaluating the sustainability of urban agriculture projects**
Agnès Fargue-Lelièvre & Anne-Cécile Daniel

**Improve Nitrogen use efficiency in mixed crop-livestock system in North China Plain**
Guiyan Wang Pengfei Shi

## T3. Crop modeling and yield gap analysis for agricultural systems analysis and design

Chair: Sentold Asseng, University of Florida

Co-chair: Frank Ewert, Bonn University

**Are our modelling tools ready to cope with agricultural systems evolution?**
Jacques-Eric Bergez, Marcelo Donatelli, Frank Ewert, Dean Holzworth, Gerrit Hoogenboom, Hélène Raynal & Claudio Stockle

**Putting the coherence between crop processes and model inputs at the core of model development: a case study for water stress in intercropped systems**
Nicolas Bertrand, Sébastien Roux, Maé Guinet & Jacques Wery

**How could yield gap assessment contribute to cropping system design?**
Nicolas Guilpart, Patricio Grassini, Victor O. Sadras & Kenneth G. Cassman

**Explaining rice yield gaps at farm level in Central Luzon, Philippines: An application of stochastic frontier analysis and crop modelling**
João Vasco Silva, Pytrik Reidsma Alice Laborte & Martin K. van Ittersum

**Modelling the population dynamics of root lesion nematodes**
Jeremy Whish, Darren Kriticos & John Thompson

**Combining yield gap and efficiency analysis to analyze farmers' fields network: a case study on nitrogen in durum wheat in Tunisia**
Y. BenZekri, K. Barkaoui, I. Mekki, H. Marrou, H. Belhouchette & J. Wery

**Explaining yield variability between farmers as a first step to reduce yield gaps**
Mariana Scarlato, Santiago Dogliotti, Cecilia Berrueta, Carlos Barros, Facundo Reherman, Alejandra Borges, Margarita Garcia & Gustavo Giménez

**On methodology of deciding nitrogen intensity: a case with dynamic typology in the small scale wheat-maize system in the North China Plain**
Wei-li Liang, Gui-yan Wang, Fu Chen & Ai-ping Xia

**Trade-offs between greenhouse gas abatement and profitability of alternative management practices on Australian grain farms**
Elizabeth Meier, Peter Thorburn, Marit Kragt, Nikki Dumbrell, Jody Biggs & Stuart McAlpine

**Yield gap analysis and crop insurance**
Alba Castañeda-Vera, Alberto Garrido & M. Inés Minguez
Modeling attainable yield and yield losses due to pests and diseases to compare performances of coffee farming systems

Rolando Cerda, Jacques Avelino, Esther Lechevallier, Louise Krolczyk, Charlie Mathiot, Eugénie Clément, Christian Gary, Philippe Tixier & Clémentine Alli

# T4. What's new with bioeconomic models for the analysis and design of agricultural systems?

Chair: Francois Affholder, CIRAD

Co-chair: Hatem Belhouchette, IAM.M

DAHBSIM, a Dynamic Agricultural Household Bio-Economic Model

Guillermo Flichman, Hatem Belhouchette, Maria Blanco, Roza Chenoune, Sophie Drogué, Adam Komarek, James Hawkins, Wajid Nasim & Siwa Msangi

Is « bio-economic » farm modelling of any help for farming system design?

François Affholder, Damien Jourdain, Marc Corbeels, Véronique Alary, Krishna Naudin, Philippe Bonnal, Eric Scopel, Françoise Gerard, Philippe Quirion & Hatem Belhouchette

Trade-offs in soil fertility management on arable farms

Jules Bos, Hein ten Berge, Jan Verhagen & Martin van Ittersum

A spatially-explicit multi-scale bioeconomic model to design and assess agricultural landscapes

Pierre Chopin, Jean-Marc Blazy, Loïc Guindé & Thierry Doré

Linking modelling with optimization techniques to maximise farming system productivity - Preliminary assessment in an experimental field study

Subash Nataraja Pillai, Jagpal Singh & Babooji Gangwar

Characterization of farming systems in drylands of South Asia for assessing resource constraints and technologies

Thiagarajah Ramilan, Shalander Kumar, Nageswara Rao & Anthony Whitebread

Identifying sustainable farms under diverse agro-ecological conditions and livelihood strategies in southern Africa: An interdisciplinary simulation-based approach

David Berre, Munyaradzi Mutenje, Marc Corbeels, Leonard Rusinamhodzi, Christian Thierfelder & Santiago Lopez-Ridaura

Dynamic Crop Production Responses to Realizations of Weather and Production with Application in Jordan

David Boussios, Paul V. Preckel, Yigezu Yigezu & Prakash N. Dixit

Strategic and tactical Urban Farm design, a conception and sizing problem

Nicolas Brulard, Van-Dat Cung & Nicolas Catusse

A household model to assess consumption-production-resources nexus in West Africa: The rice based farming systems in Sierra Leone

Roza Chenoune, Thomas Allen, Guillermo Flichman, Yigezu Yigezu, Alain Capillon & Hatem Belhouchette

# T5. Design Climate Smart Agricultural Systems: methods, scales, results and challenges

Chair: Olaf Christen, Agronomy and Organic Farming University of Halle

Co-chair: Jacques-Eric Bergez, INRA

Farm4 Prophet - Managing whole farm business risk in Australia

Harm van Rees, Tim Hutchings, Zvi Hochman, Tim McClelland & Robbie Scott

Specification of nitrogen use in regional climate impact assessment studies

Heidi Webbe, Gang Zhao, Wolfgang Britz, Wim de Vries, Joost Wolf, Thomas Gaiser, Holger Hoffmann & Frank Ewert

Re-designing smallholder farming futures for reduced vulnerability to climate change in semi-arid southern Africa

Sabine Homann-Kee Tui, Katrien Descheemaeker, Patricia Masikati, Arthur Chibwana Gama, Olivier Crespo, Lieven Claessens & Roberto Valdivia

Resilience of adaptation strategies for small-holder farmers in Cambodian lowland rice ecosystems in response to future climate uncertainty.

Perry L. Poulton, Neal P. Dalgliesh, Seng Vang, Touch Veasna & Philip Charlesworth

Assessing impacts of changes in farm management and farm structural change on sustainable development in a rural area in the Netherlands

Pytrik Reidsma, Martha M. Bakker, Argyris Kanellopoulos, Shah J. Alam, Wim Paas, Johannes Kros & Wim de Vries

Potential impacts of climate change on legume-based cropping systems

Ralf Bloch & Johann Bachinger

Climate change adaptation in Australian wheat farm systems upscaled from farm to national scale

Afshin Ghahramani, Philip N. Kokic, Andrew D. Moore & Bangyou Zheng

Climate change impact on Western Australian mixed farm systems

Afshin Ghahramani, Andrew D. Moore, Steven J. Crimp, David Bowran

Will breeding efforts be counteracted by uncertain water supply due to prospective climate change?

Nikolai Svoboda, Maximilian Strer & Johannes Hufnagel

The contributions of recent climate change trends to maize phenology and yield in Northeast China

Zhijuan Liu & Xiaoguang Yang

Running NUANCES-FARMSIM to predict greenhouse gas emissions in mixed smallholder crop-livestock systems under different scenarios in Western Kenya

Daniel Ortiz Gonzalo, Mariana Rufino, Todd Rosenstock, Philippe Vaast, Myles Oelofse, Andreas de Neergaard & Alain Albrecht

# T6. Designing sustainables agricultural systems with legumes

Chair: Marie-Hélène Jeuffroy, INRA

Co-chair: Snapp Sieglinde, Michigan State University

Greener food production in Africa: intensification through multipurpose legumes

Sieglinde Snapp, Regis Chikowo, Mateete Bekunda, Chiwimbo Gwenambira & Placid Mpeketula

A comparison of past and current cropping systems with designed innovative cropping systems including legume crops, in three french regions.

Marion Soulie, Laurence Guichard, Marie-Hélène Jeuffroy, Catherine Mignolet, Elise Pelzer & Céline Schott
Design and ex ante assessment of cropping systems with legumes in four European countries

Céline Bourlet, Elise Pelzer, Georg Carlsson, Erik Steen Jensen, Etienne-Pascal Journet, Eric Justes, Christophe Lecomte, Rafael J. Lopez-Bellido, Marek Seidenglanz, Anne-Sophie Voisin & Marie-Hélène Jeuffroy

Designing legume-supported cropping systems

Moritz Reckling, Göran Bergkvist, Frederick Stoddard, Christine A Watson, Aurelio Pristeri, Ion Toncea, Robin Walker, Peter Zander, Jens-Martin Hecker & Johann Bachinger

Design of innovative legume-based systems: the case of soybean-based cropping systems in Oise, northern France

Elisa Marraccini, Alicia Ayerdi-Gotor, Romain Armand, Olivier Scheurer & Christine Leclercq

Comparison of yields, protein contents and environmental impacts of grain legumes for designing legume-based cropping systems in Europe

Charles Cernay, Elise Pelzer, Jean-Marc Meynard, Tamara Ben-Ari & David Makowski

Pushing for intensified protein per capita production on smallholder farms in Malawi through 1000+ farmers experimenting with diverse grain legumes

Regis Chikowo, Sieglinde Snapp, Erin Anders, Wezi Mhango & Mateete Bekunda

Below and aboveground pigeonpea productivity in a novel doubled-up legume cropping system across three agro-ecologies in central Malawi

Chiwimbo Gwenambira, Sieglende Snapp & Regis Chikowo

Combination of undersown catch crops and row-hoeing for optimizing nitrogen supply and weed control in organic spring barley

Thi Thuy Hong Phan & Kristian Thorup-Kristensen

A territorial design and assessment of legume-based cropping systems to gain ecosystem services

Marie-Hélène Jeuffroy, Célia Cholez, Guénaelle Corre-Hellou, Marie-Benoît Magrini, Martine Mauline, Elise Pelzer & Marion Soulié

Legume-grass mixtures grown on arable land under the conditions of water deficits

Jaroslav Lang & Daniela Knotova

# T7. Scaling up from farm to landscape and multiscale scenario analysis of agricultural systems

Chair: Martin Van Ittersum, Wageningen UR

Co-chairs: Bernard Hubert, Agropolis International & Marc Benoit, INRA

Integrating field, farm and territory scales in the design of agricultural systems

Jean-Marc Blazy, Pierre Chopin, Thierry Doré, & Jacques Wery

Participatory scenarios' development and assessement for sustainable farming systems in Camargue, south of France.

V. Couderc, L. Hossard, J.M. Barbier, J.C. Mouret, S.L. Ridaura, & S. Delmotte

The farm and landscape gap - partial versus emerging global efficiencies in agricultural systems

Santiago Lopez-Ridaura & Pablo A. Tittonell

Coll-ICLS: a participatory tool to support crop-livestock integration among farms

G. Martin, M. Moraine, J. Ryschawy, M.A. Magne, J.P. Sarthou, M. Duru & O. Therond

Does the recoupling of crop and livestock production at the district level lead to environmental benefits? A case-study approach in Europe.

John Regan, Silvia Marton, Olivia Barrantes, Eimear Ruane, Marjoleine Hanegraaf, Jérémy Berland, Ramon Reine, Sylvain Pellerin, & Thomas Nesme

A system analysis of crop rotations with sugar beet and/or silage maize for biogas production - ecological and economical approaches

Anna Jacobs, Sebastian Auburger, Enno Bahrs, Wiebke Brauer-Siebrecht, Olaf Christen, Philipp Götze, Heinz-Josef Koch, Oliver Mußhoff, Niels Pelka, Jan Rücknagel & Bernward Märländer

Design of cropping systems at territorial scale: methodological lessons from case studies

Rémy Ballot, Emilia Chantre, Laurence Guichard, Florence Jacquet, Laurette Paravano, Lorène Prost, Clémence Ravier, Raymond Reau & Marie-Hélène Jeuffroy

Indicators for the evaluation of nitrogen efficiency and nitrogen balance in agriculture for 27 Member States of the European Union

Olivier Godinot, Philippe Leterme, Françoise Vertès, & Matthieu Carof

Scaling up agricultural catchment management strategies from field and farm scale to landscape scale

Chris Stoate, Jeremy Biggs, Adrianna Hawczak, John Szczur & Sarah-Jane Osborne

Integrating agricultural and water policies for more sustainable crop production in arid Northwestern China

Til Feike & Martin Henseler

Farm type-specific adoption behaviour in sustainable soil nutrient management: the case of smallholder farms in Ioba province, Burkina Faso.

Boundia Alexandre Thiombiano, & Quang Bao Le

A modeling framework for designing and assessing multi-functional agricultural landscapes with scenario analysis

Pierre Chopin, Jean-Marc Blazy, Loïc Guindé, Jacques Wery & Thierry Doré,

Crop-livestock farming systems in Australia: what levels of integration result in different benefits?

Andrew D. Moore, Lindsay W. Bell, Dean T. Thomas & Andrew P. Smith

Co-Designing Organic Residue Recycling Chains in Off-Balance Regions

Tom Wassenaar & Jérôme Queste

The farming system component of European agricultural landscapes

Erling Andersen

Farming system dynamics and their drivers in Mediterranean landscapes: a case study on the Vaucluse departement based on agricultural census data (PACA region, France)

Marta Debolini & Martine Guerif

Meta-analysis of yield gap explaining factors and opportunities for alternative data collection approaches

Eskender Beza, João Vasco Silva, Lammert Kooistra & Pytrik Reidsma

Sustainable extensification—breathing new life into Africa's sleeping giant

Mary Ollenburger, Katrien Descheemaeker, Todd Crane & Ken Giller

Faming systems analysis and land policy: The case of the Office du Niger area in Mali

Laurence Roudart & Benoît Dave

Land pressure and agrarian mutation, spatial modelling of farming systems evolution from plot to regional scale in West Burkina Faso

Camille Jahel, Christian Baron, Eric Vall, Agnes Bégué, Kalifa Coulibaly, Medina Karambiri, Mathieu Castets, Stéphane Dupuy & Danny Lo Seen

Characterization of crop rotations variability by combining modelling and local farm interviews

Florent Levavasseur, Clémence Bouty, Aude Barbottin, Valentin Verret & Philippe Martin
Use of aerial photogrammetry to minimize erosion threats from broad scale resource developments on farmlands.

Perry L. Poulton, Neil I. Huth, Peter Caccetta, Brett Cocks, Jeremy Wallace & Xiaoliang Wu

Use of crop sequences for data-mining of remotely sensed time series across multiplescales: opportunities for scaling up research on
**agricultural dynamics**

Davide Rizzo, El Ghali Lazrak, Jean-François Mari, Laurence Hubert-Moy & Marc Benoît

Are crop sequence evolutions influenced by farm territory dynamics?

Clémence Bouty, Florent Levavasseur, Philippe Martin & Aude Barbottin

An Integrated Look at The Diversity, Sustainability and Dynamics of Argentina's Farming Systems

Mirna Mosciaro, Gonzalo Carlos Bravo, María Daniela Chavez, Hernán Alejandro Urcola, Víctor Brescia, María Eugenia Van Den Bosch & Carlos Ghida Daza

Linking landscape patterns and farm trajectories: a prerequisite to design eco-efficient landscapes in agricultural frontiers of Brazilian
**Eastern Amazon**

Sophie Plassin, René Poccard-Chapuis & Jean-François Tourrand

Deciphering Corporate Governance and Environmental Commitment within South- East Asia Transnationals in strengthening Farming Systems interactions

Jean-Marc Roda, Norfaryanti Kamaruddin & Rafael Palhiarim Tobias

Observatories of territorial practices: a tool to contribute to sustainable development of territories and performance of production systems

Javier Alejandro Vitale, Cecilia Inés Aranguren Marcelo Saavedra, Sandra Elizabeth Ledesma, Erika Zain El Din, Eduardo Daniel Cittadini, Roberto Arnaldo Cittadini & Marc Benoît

T8. Co-design and co-innovation with farmers and stakeholders: methods, results and challenges

Chair: Michel Duru, INRA

Co-chairs: Santiago Dogliotti, Universidad de la Republic & Marie-Hélène Jeuffroy, INRA

Co-design ecologically intensive fish farming systems using agroecology and ecosystem services

Joël Aubin, Hélène Rey-Valette, Syndhia Mathé, Aurélie Wilfart, Marc Legendre, Jacques Slembrouck, Edurdo Chia, Gérard Masson, Myriam Callier, Jean-Paul Blancheton, Aurélien Tocqueville, Domenico Caruso & Pascal Fontaine

Re-disigned farming system as a key for biodiversity conservation in Uruguay

Oscar Blumetto, Santiago Scarlato, Guadalupe Tiscornia, Andrés Castagna, Felipe García, Gerónimo Cardozo & Andrea Ruggia

Co-design of improved climbing bean technologies for smallholder farmers in Uganda

Esther Ronner, Katrien Descheemaeker, Conny Almekinders, Peter Ebanyat & Ken Giller

Iterative design and ex ante assessment of cropping systems including energy crops in the Dijon plain (France)

Anabelle Laurent, Claire Lesur-Dumoulin, Raymond Reau, Laurence Guichard, Marion Soulié, & Chantal Loyce

Designing agroforestry systems for food production and provision of other ecosystems services: cases in the sub-humid tropics of
**Nicaragua**

Diego Valbuena, Pablo Siles, Aracely Castro, Steven Fonte, Martín Mena, Orlando Téllez, Laurent Rousseau, Reynaldo Mendoza, Falguni Guharay & Rein van der Hoek

Managing pasture-herd interactions in livestock family farm systems based on natural grasslands in Uruguay

Andrea Ruggia, Santiago Scarlato, Gerónimo Cardozo, Verónica Aguerre, Santiago Dogliotti, Walter Rossing & Pablo Tittonell

Designing appropriate agroforestry systems: a systematic understanding of adoption decisions

Lieve Borremans, Bert Borubens & Erwin Wauters

Participatory design of irrigated landscapes to limit the risk of water crisis

Clément Murgue, Olivier Therond & Delphine Leenhardt

Participatory prototyping for complex rice based adaptative systems design in east Java, Indonesia

Uma Khumairoh, Egbert A. Lantinga, Jeroen C.J.Groot, Pablo A. Tittonell & Didik Suprayogo

Innovative design of smart farming systems: Some insights from the enhancement of native mycorrhizae in Martinique

Marie Chave & Valérie Angeon

Integrated Farming System for Sustainable Rural Livelihood of small and marginal farmers of North Eastern Transitional Zone (Zone-)
and North Eastern Dry Zone (Zone-) of Hyderabad Karnataka Region

U. K. Shanwad, R. L. Jadhav, Santiago Lopez-Ridaura, M. L. Jat, Ivan Ortiz-Monasterio & A. G. Sreenivas

Structuring data gathering on organic farms: the transdisciplinary development and use of a farm scan within a broader methodological
framework

Jo Bijttebier, Ludwig Lauwers & Fleur Marchand

Co-innovation as an effective approach to promote changes in farm management in livestock systems in Uruguay

Santiago Scarlato, María Marta Albicette, Isabel Bortagaray, Andrea Ruggia, Mariana Scarlato & Verónica Aguerre

How to co-build a viable farming model? Guadeloupe and Martinique Cases

Bérengère Merlot, Arnaud Larade, Valérie Angeon & Eduardo Chia

Agronomic knowledge for cropping system design: characterization and dynamics of mobilization

Quentin Toffolini, Marie-Hélène Jeuffroy & Lorène Prost

The need for agronomic indicators to monitor and assess action and to enhance learning loops during cropping system redesign process

Quentin Toffolini, Marie-Hélène Jeuffroy & Lorène Prost

De novo design workshop: a method for co-designing innovative cropping systems

Raymond Reau Caballero, Michael Geloen, Anabelle Laurent, Chantal Loyce & Anne Schaub

Forages for Reduced Nitrate Leaching - a cross sector approach

Paul Edwards, Ina J.B. Pinxterhuis & Denise Bewsell

A research trajectory driven by scaling out: from a detailed farm model (SEDIVER) to a participatory board game (Forage Rummy)

Guillaume Martin

Photovoltaic Water Pumping System -Sustainable Water Irrigation for Best Farming System

P. S. Shehrawat

Gender and wealth influence how smallholder farmers make on-farm changes: a case study from Uganda

Skye Gabb, Peter Dorward & Graham Clarkson

Scaling up agro-ecological innovation adoption among farming systems. Application to improved fallows in Martinique

Laurent Parrot, Laurent Hennig, Eric Roux, Lucile Vantard, Alexandra Jestin, François Ratye & Paula Fernandès

A participatory approach to design and assess integrated crop-livestock systems at territory level

Marc Moraine, Michel Duru, Clément Murgue, Julie Ryschawy & Olivier Therond
Designing a livestock rearing system with stakeholders in Thailand highlands: Companion modelling for integrating knowledge and strengthening the adaptive capacity of herders and foresters

Dumrongrojwatthana Pongchai, Le Page Christophe & Trébuil Guy

Improving the livelihood of rural communities and natural resource management in the mountains of the Maghreb countries of Algeria, Morocco and Tunisia

Mohamed Moussaoui, Mohammed Elmourid Salah Chouaki, Rachid Mrabet, Rachidi Youssef Lalaoui & Mohamed Elloumi

To mulch or to muck? Modelling the benefits and trade offs in the use of crop residues in Kenya

D Rodriguez, P deVoil, M Herrero, M. Odendos, B Power, M Rufino & MT van Wijk

Valorization of sustainable management practices in the farm based small economy

Katharina E. Diehl, Bettina König & Shadi K. Hamadeh

Innovation, knowledge management and researchers' postures: exploring their linkages for improving the performance of innovation platforms

Aurélie Toillier, Bernard Triomphe, Der Dabire, Syndhia Mathé, Francois Ruf, Koutou Mahamoudou & Ludovic Temple

An innovative approach to simulating household adaptation and investment

David Parsons, Arthur Masson, Caroline Mohammed & Rohan Nelson

Small farm viability in Central America – can tools for smallholder decision-making play a key role?

Charles Saver, Sandrine Freguin, Falguni Guharay, Martin Mena, Pablo Siles, Marie Turmel & Rein van der Hoek

Opening the black box: innovation process and logics of functioning of peasant farming systems

Gonzalo Bravo

Participative design of conservation agriculture cropping systems in organic agriculture

Marion Casagrande, Vincent Lefèvre, Mathieu Capitaine & Joséphine Peigné

The institutional innovation in INTA for approaching the territories' complexity of the Argentinean farmland

Eduardo Daniel Cittadini, Sandra Elizabeth Ledesma & Erika Zain El Din

Adaptation of the Open Innovation Approach for Knowledge and Technology Transfer in an Intensive Agricultural Landscape

Stéphane Gariépy, Julie Ruiz, Samuel Comtois & Virginie Zingraff

Uruguay family farming improvement project

Virginia Porcile, Raúl Gómez Miller, Alfredo Albín & Trevor Jackson

## W1. Animal-based systems and crop-livestock interactions at farm and territory level

Chair: Charles-Henri Moulin, Montpellier SupAgro

Co-chair: Amandine Lurette, INRA

Using the viability theory to assess the trade-offs between production, adaptability and robustness of grassland agroecosystem

Rodolphe Sabatier, Lawrence G. Oates & Randall D. Jackson

Between social cohesion and rural management: the “Real Employment” calculation as a useful tool of analysis

Anna Roca Torrent & Cristina Tous de Sousa

Labour profiles and Electronic Identification (EID) technology: assessing different management approaches on extensive sheep farming systems

Claire Morgan-Davies, Nicola Lambe, Ann McLaren, Harriet Wishart, Tony Waterhouse & Davy McCracken

Bio-economic assessments of the CAP reform and feed self-sufficiency scenarios on dairy farms in Piedmont, Italy

Stefano Gaudino, Pytrik Reidsma, Argyris Kanellopoulos, Dario Sacco & Martin van Ittersum

Improving the performances of a pastoral system: simulation results against field data

Magali Jouven, Marielle Roulenc, Fabien Carriere, Sébastien Douls, Frédéric Vezinet, Didier Foulquier & Marc Benoît

Division of labour in dairy farming – a way to increase income and reduce environ- mental impact?

Silvia M.R.R. Marton, Albert Zimmermann & Gérard Gaillard

Improving Nutrient Use Efficiency By Reconnecting Crops And Livestock

Christine A Watson, Geoff Squire, Graham Begg, Cairistiona F E Topp & Anthony C Edwards

Co-innovation of family farm systems: developing sustainable livestock production systems based on natural grasslands

Verónica Aguerre, Andrea Ruggia, Santiago Scarlato & Maria Marta Albicette

Production gaps in livestock grazing systems in Sierras del Este, Uruguay: magnitude, causes and strategies to reduce them.

Ignacio Paparambora & Raúl Gómez

Herbage allowance a management tool for re-design livestock grazing systems: four cases of studies

Geronimo Cardozo, Martin Jaurena & Martin Do Carmo

Participatory Design of Livestock Systems: Explore, Experiment, Innovate (case study in Burkina Faso)

Jéthro Delma B., Eric Vall, Hassan B Nacro & Valérie Bougouma-Yameogo

Integrating empirical and scientific knowledge to evaluate the transition to a once-a- day milking in dairy ewe farms

Amandine Lurette, Catherine De Boissieu, Emmanuel Morin, Philippe Hassoun, Francis Barillet & Charles-Henri Moulin

PATUCHEV and REDCap: two additional research and development schemes for high performance and sustainable goat farming

H. Caillat & J. Jost

Redesigning a dairy system based on agroecological principles using a collaborative method

Sandra Novak, Rémy Delagarde, Jean-Louis Fiorelli, Jean-Claude Emile, Anne Farruggia, Laurence Guichard & Fabien Liagre

Crop-livestock integration of cereal-based mixed farming systems in the Terai and Mid-hills in Nepal

Victoria Alomia, Jeroen Groot, Carlo Bettinelli, Andrew Mc. Donald & Pablo Tittonell

Crop-Livestock Integration improves the Energy Use Efficiency of smallholder mixed farming systems - the case of western Burkina Faso

O.Ida Bénagabou, Melanie Blanchard, Jonathan Vayssières, Mathieu Vigne, Eric Vall, Philippe Lecomte, Valérie Bougouma & H.Bismark Nacro

French sheep meat sector and drivers of its evolution since 1970

Gabriel Teno, Charles-Henri Moulin & Marie-Odile Nozieres

Mongolian water quality problem and health of free-grazing sheep

Yu Yoshihara ±, Chika Tada, Moe Takada, Nyam-Osor Purevdorj, Khorolmaa Chimedtseren & Yutaka Nakai
## W2. Annual crops based systems

Chair: Laure Hossard, INRA

Co-chair: Eric Scopel, CIRAD

**Cropping system intensification to increase food security and profitability among smallholder farmers in Zimbabwe**

Siyabusa Mkuhlani, Isaiah Nyagumbo, Walter Mupangwa, Neil MacLeod, Cam Mac Donald, Peter de Voil & Daniel Rodriguez

**Experimental assessment of winter malting barley genotypes in low-input system**

Damien Beillouin, Jean-François Herbommez, Claire Perrot, Arnaud Gauffreteau & Marie-Hélène Jeuffroy

**Potential yield and yield gap at farm level are different from the field level: A case study on a large Dutch potato farm**

Pytrik Reidsma, Jarno Rietema, Yulin Yan, Joop Kroes & João Vasco Silva

**Combining systems analysis tools for the integrated assessment of scenarios in rice production systems at different scales.**

Jean-Marc Barbier, Stefano Bocchi, Sylvestre Delmotte, Andrea Porro, Francesca Orlando, Mirco Boschetti, Pietro Alessandro Brivio, Giacinto Manfron, Simone Bregaglio, Giovanni Capelli, Roberto Confalonieri, Françoise Ruget, Vincent Courderc, Laure Hossard, Jean-Claude Mouret & Santiago Lopez-Ridaura

**Trajectories of farming systems and land use changes in Southern Ethiopia**

Yodit Kebede, Frédéric Baudron, Felix Bianchi, Kristin Abraham, Kassahun Lemi Woyessa, Pablo Tittonell & Lammert Kooistra

**Sweet sorghum: methodological exploration of a multifunctionality to innovate in Haitian agriculture**

Annaïg Levesque, Ludovic Temple, Serge Braconnier & Bénédique Paul

## W3. Cropping systems design: what can we do with field experiments and expert knowledge?

Chair: Jean-Marc Meynard, INRA

Co-chair: Raphaël Metral, Montpellier SupAgro

**System experiments: methodological progress**

Jean-Marc Meynard

**SYPPRE :**A project to promote innovations in arable crop production mobilizing farmers and stakeholders and including co-design, ex-ante evaluation and experimentation of multi-service farming systems matching with regional challenges.

Clotilde Toqué, Stéphane Cadoux, Pascaline Pierson, Rémy Duval, Anne-Laure Toupet, Francis Flenet, Benoît Carroué, Frédérique Angevin & Philippe Gate

**Describing cropping system tested in an experimental network: contribution to analysis of results and sustainability performances and to inspiration of farmers, trainers and R&D**

Marie-Sophie Petit, Violaine Deytieux, Anne Schaub, Camille Fonteny, Clotilde Toque, Sébastien Minette, Stéphane Cadoux, Anne-Laure Toupet, Michaël Geloen, Christophe Vivier, Eric Bizot & Raymond Reau

**Design and multicriteria assessment of low-input cropping systems prototypes based on agroecological principles in southwestern France**

Eric Justes, Daniel Plaza-Bonilla, Grégory Vériceil, Yolaine Hily, Didier Raffaillac, André Gavaland & Jean-Marie Nolot

**An example of agro-ecological transition on the Saint-Laurent de la Prée research farm: method and first results**

Daphné Durant

**Design and development of Integrated farming system module for various agro ecosystems of Hyderabad- Karnataka region**

Bheemśainrao Desai, Satyanarayan Rao, S. Biradar, Prahlad Ubhale & Sangeeta NP

**Decisional-model for analyzing and scaling out innovative cropping systems**

Raymond Reau, Vincent Cellier, Violaine Deytieux, Marie-Sophie Petit, Anne Schaub, Patrice Cotinet & Jean-Luc Giteau

**Integrated effects of conservation agriculture in a crop-livestock system on western loess plateau, china**

Lingling Li, Renzhi Zhang, Bill Bellotti & Adam Komarek

**A procedure to analyze multiple Ecosystem Services in apple orchards**

Constance Demestihas, Daniel Plénet, Michel Génard, Dominique Grasselly, Iñaki García de Cortázar-Atauri, Marie Launay, Nicolas Beaudoin, Sylvaine Simon, Marie Charreyron, Marie-Hélène Robin & Françoise Lescourret

**Intercropping grains, oilseeds and row crops with forage species to enhance cropping system sustainability**

Aaron A. S. Mills, Isabelle Breune, Christine Noronha, Judith Nyiraneza, Gaëtan Parent & A. Vernon Rodd

**Origins of the performance gaps in innovative cropping systems under experimental assessment**

Caroline Colienne-David, Gilles Grandseau, Véronique Tanneau, Marie-Hélène Jeuffroy & Thierry Doré

**Design, experimentation and assessment of four protected vegetable cropping systems adapted to different food systems**

Amélie Lefèvre, Chloé Salembier, Benjamin Perrin, Claire Lesur-Dumoulin & Jean-Marc Meynard

**Farming systems design to facilitate transition toward low input agriculture**

Marie Thiollet-Scholtus & Xavier Coquil

**System approach farming reduces the carbon footprint of crop production**

Yantai Gan, Chang LianG, Qiang Chai, Reynald Lemke, Con Campbell & Robert Zentner

**Open-up the (co)design process of farming systems: a reflexive analysis.**

Aurélie Cardona, Amélie Lefèvre & Chloé Salembier

**Design of innovative orchards: proposal of an adapted conceptual framework**

Sylvaine Simon, Magalie Lesueur-Jannoyer, Daniel Plénet, Pierre-Éric Lauri & Fabrice Le Bellec

## W4. Farms in transition to organic agriculture or agroecology

Chair: Jacques Wery, Montpellier SupAgro

**Farmer's proximity to organic farming in two French cash crop regions: focus on technical practices, commercial strategies and professional networks**

Caroline Petit, Pauline Leblanc, Julia Sicard, Catherine Mignolet & Fabienne Barataud

**Conversion towards organic farming leads to a complexification of the farming system management: application to vineyard systems**

Anne Merot

**A transdisciplinary approach to structure knowledge gathering on organic farming systems: evaluation of organic farm strategies in the case of Flanders**

Fleur Marchand, Jo Bijttebier, Jef Van Meensel, Matthias Strubbe & Ludwig Lauwers

**Co-design of organic farming systems on the Canadian Prairies**

Martin Entz, Joanne Thiessen Martens, Gary Martens, Michelle Carkner, Derek Lynch, Mark Kopecky & Kristen Podolsky
Decision making processes and factors driving apple protection strategies at farm level

Solène Pissonnier, Claire Lavigne, Jean-François Toubon & Pierre-Yves Le Gal

Production 2020: designing and assessing sustainable farming systems in Switzerland

Martin Braunschweig, Andreas Roesch, Maria Bystricky, Thomas Nemecek & Gérard Gaillard

Projections to Latent Structures (PLS) to evaluate farming system effects on agro-ecosystem services: Changes after transition from conventional to organic farming system

Libère Nkurunziza, Hákan Marstorp, Iman Raj Chongtham, Kristin Thored, Ingrid Öborn, Göran Bergkvist & Jan Bengtsson

Characterizing agroecological farming systems by combining the resilience and ESR framework

Laura Schotte, Erwin Wauters, & Fleur Marchand

Modelling Adaptive Decision-Making of Farmer: an Integrated Economic and Management Model, with an Application to Smallholders in India

Marion Robert, Alban Thomas & Jacques-Eric Bergez

The viability of small islands agro-systems: the case of the French West Indies

Angeon V., H. Ozier-Lafontaine, S. Bates, E. Chia, A. Desilles, J.-L. Diman, P. Andres-Domenech, M.-H. Durand, A. Fanchone, A. Larade, G. Loranger-Merciris, B. Merlot & P. Saint-Pierre

Agronomic, environmental and social assessment of soil management strategies limiting herbicide application in Mediterranean vineyards, at the catchment scale

Patrick Andrieux, Anne Biarnès, Jean-Marc Barbier, Claude Compagnone, Xavier Delpuech, Christian Gary, Aurélie Metay & Marc Voltz

Pesticides pressure assessment using TFI (treatment frequency index) at the field, farm and watershed scale

Magalie Lesueur Jannoyer, Philippe Cattan, Marie Raimbault, Céline Gentil, Vincent Bonnal & Marianne Le Bail

Food production typology of farms: an assessment of periurban farming systems.

R. Filippini, E. Marraccini, E. Bonari & S. Lardon,

## W5. Silvo-pastoral systems

Chair: Bruno Rapidel, CIRAD

Co-chair: Marie Gosme, INRA

Multi-scale studies of the relationships between cropping structure and pest and disease regulation services.

Cynthia Gidoin, Régis Babin, Leïla Bagny Beilhé, Corentin Barbu, Marie Gosme, Marie-Hélène Jeuffroy, Marie-Ange Ngo Bieng, Muriel Valentin-Morison & Gerben Martijn ten Hoopen

Ecosystem services provided by coffee agroecosystems across a range of topo-climatic conditions and management strategies

Rolando Cerda, Clémentine Allinne, Louise Krolczyk, Charlie Mathiot, Eugénie Clément, Celia A. Harvey, Jean-Noel Aubertot, Philippe Tixier, Christian Gary & Jacques Avelino

Evaluation and design of multispecies cropping systems with perennials: are current methods applicable?

Bruno Rapidel, Delphine Mézière, Raphaël Metral, Christian Dupraz, Anne Mérot, Clémentine Allinne & Christian Gary

Design of Agroforestry systems with coffee is facilitated by the description of relationships between Ecosystem Services provided

Martin Notaro, Aurélie Metay, Sandrine Fréguin-Gresh, Jean-François Le Coq, Pablo Siles & Bruno Rapidel

What is the multifunctionality of the mango orchards in Senegal?

Hubert de Bon, Paterne Diatta, Lamine Diame, Cheikh Amet Bassirou Sané, Jean-Yves Rey, Karamoko Diarra & Isabelle Grechi

Mapping spatial distribution of Cocoa Swollen Shoot Disease for effective rehabilitation strategies in infected areas

Zokou Franck Oro Lucien Diby, Noel Dougbado, Marie-Paul N'Guessan, Christophe Kouame, Hypolite Diby & Christian Cilas

Systemic analysis of a temperate forest garden: a contribution to complex agrosystems study

Charlotte Pasquier, Alain Canet & Jacques Wery

"Cropping the roots" of agroforestry systems: applying moderate water stress and water competition at plantation to increase tree root biomass

Oswaldo Forey, Jacques Wery & Aurélie Metay

New agro-ecologic paradigm for little farming exploitations to obtain alimentary sovereignty

Serge Valet & Mikael Motelica-Heino

## W6. Pathways for sustainable intensification of African agriculture?

Chair: Ken Giller, WUR

Co-chairs: Philippe Lecomte, CIRAD & Liang Weili, Hebei Agricultural University

Integrating the women's labor investment into the performance assessment of ox-drawn cotton production in Côte d'Ivoire

Michel Fok, Siaka Koné & Faridath Aboudou

The risk of declines in soil fertility and crop productivity due to decreased livestock presence in agropastoral zones of West Africa

Jonathan Vayssières, Mélanie Blanchard, Mathieu Vigne, Dominique Masse, Alain Albrecht, Eric Vall, René Poccard-Chapuis, Christian Corniaux & Philippe Lecomte

Soil nutrient balance, economic performance and scenarios for closing nutrient gaps in heterogeneous smallholder farm systems in southwestern Burkina Faso

Boundia Alexandre Thiombiano, & Bao Le Quang

Pathways for the sustainable intensification of agriculture

D. Rodriguez, A. Bekele, P. deVoil, M. Herrero, B. Power, M. Rufino & M.T. van Wijk

Tailoring cropping systems to variable climate, diverse farms and landscapes

Leonard Rusinamhodzi, David Berre, Santiago-Lopez Ridaura & Marc Corbeels

Socio-ecological conditions for food security in African drylands: A quantitative and spatially-explicit typology to facilitate learning

Diana Sietz, Jenny Ordoñez, Marcel Kok, Peter Janssen, Henk Hilderink & Han Van Dijk

Improving the productive performance of family farms in Senegalese rural area

Assane Beye & Astou Diao Camara

Emerging farms in Northern Cameroon: an economic and social change towards high agricultural productivity?

Hervé Guibert, Ibrahim Ngamié, Henri Clavier, Michel Havard & Pinardel Kenne

A GxExM approach to manage climate risks in rainfed maize cropping systems

Joseph Eyre, Hae Koo Kim, Peter deVoil, Amsal Tarekegne, Zaman-Allah Mainassara & Daniel Rodriguez

Combined and targeted application of crop residues and cattle manure increases maize productivity in a crop-livestock farming system on granitic sandy soils of Zimbabwe

Isaiah Nyagumbo, Siyabusa Mkuhlani, Leonard Rusinamhodzi, Sandra Madamombe & Walter Mupangwa
Innovative participatory farming system design: combining on-farm crop/livestock trials with ex-ante trade-off analysis

Gatien N. Falconnier, Katrien Descheemaeker, Thomas A. Van Mourik & Ken E. Giller

Ecosystem services for West African farming families: the role of woody shrub mulch

Georges F. Félix, Jean-Marie Douzet, Marcel Ouédraogo, Philippe Belliard, Rabah Lahmar, Cathy Clermont-Dauphin, Johannes Scholberg, Pablo Tittonell, & Laurent Cournac

Climate Change Impacts and Food Production in Sub Saharan Africa

Adedugbe Adebola

Assessing soil water trajectories and WUE: A multi-year modeling approach to design resilient cereal-legume rotations in the dry areas

Hélène Marrou, Michel Edmond Ghanem, Hatem Belhouchette, Carina Moeller & Thomas R. Sinclair

Improving resource allocation in nitrogen constrained systems: acknowledging within and cross-farm variability effect on yield and NUE

Nascimento Nhantumbo, John Dimes, Miranda Mortlock, Isaiah Nyagumbo & Daniel Rodriguez

Application of farm typology to explore soil fertility variability and farm-specific nutrient management recommendations in smallholder farming systems in sub-Saharan Africa

Shamie Zingore, Regis Chikowo & Mirasole Pampolino

Bio-physical and Socio-economic Factors Influencing Farmers' Decisions on Whether to Intercrop or Sole Crop Maize in Ethiopia

Abeya Temesgen, Shu Fukai, Moti Jaleta & Daniel Rodriguez

Institutionalizing Systems Approaches for Improving Agricultural Livelihoods in an Arid Ecoregion of South Asia

Shalander Kumar, Anthony Whitbread & Thiagrajah Ramilan

What level of detail in input data and crop models is required for food production studies in West Africa?

Katharina Waha, Neil Huth, Peter Carberry & Enli Wang

Participatory modelling of the trajectories of agro-sylvo-pastoral systems at landscape and community levels in West Africa – the case of Senegalese groundnut basin

Myriam Grillot, Jonathan Vayssières, Jérémy Bourgoin, Alassane Bah, Frédérique Jankowski, Richard Lalou & Dominique Masse

A more integrated approach for a diversity of intensification approaches and pathways to cope with the necessity of sustainable intensification of African agri-food systems: The IntensAfrica initiative: Position paper.

Etienne Hainzelin, Philippe Petithuguenin & Florent Maraux

Ex-ante analysis of opportunities for the sustainable intensification of maize production in Mozambique

Caspar Roxburgh & Daniel Rodriguez

Possible ex-ante assessment of rice-vegetable systems performances when facing data scarcity: use of the PERSYST model in West Africa

Théo Furlan, Rémy Ballot, Laurence Guichard & Joël Huat,

Participatory Management of Farming Systems in the Western Highlands of Cameroon for Poverty alleviation

Henri Grisseur Djoukeng

Fighting food insecurity and alleviating poverty in the face of climate change through rice-growing in Tonga (west-Cameroon)

Christelle Tchieudjo & Moïse Moupou

W7. Aquaculture systems

Chair: Patrick Dugan, WorldFish Center

Co-chair: Lionel Dabbadie, CIRAD

Effectiveness of a participatory approach for collection of economic data in aquaculture systems at farm level in Brazil

Manoel Xavier Filho Pedroza, Andrea Elena Pizarro Munoz & Roberto Manolio Valladão Flores

The role of fish farming in the farming system in the Betafo areas of Madagascar: approach by agronomic analysis and socio-economic inquiries.

Marc Oswald, Sophie Moreau & Aurélie Metay

Aquaculture systems & farming systems: inside, outside or side-by-side?

Lionel Dabbadie & Olivier Mikolasek

MarketAccessandfishfarms'densityinasub---Saharanruralcountryside:acase study of the village of Gbotoye in the forested areas of Guinea.

Charline Rangé, Augustin Pallière, Alpha Ly, Moïse Théa & Marc Oswald

Ré-SyPiEx

Research and development network on Extensive Fish farming in Western and Central Africa

Ibrahim Imorou Toko, Celestin Telecony Ble, Olivier Mikolasek, Minette Tomedi Eyango, Antoine Chikou, Thomas Efole Ewoukem, Dominique Ombredane, Adja Ferdinand Vanga & Jacob Afouda Yabi

Lessons learnt from a review of extensive fish farming inside family plantations economie through West Africa and of their contribution to the local value chain.

Marc Oswald, Olivier Mikolasek, Pierre Meké, Celestin Telecony Ble, Thomas Efole Ewoukem, Adja Ferdinand Vanga, Ibrahim Imorou Toko, Minette Tomedi Eyango

A food systems approach to aquaculture: re-orienting farming systems for improving nutritional outcomes

Andrew Thorne-Lyman, Sven Genschick, Michael J. Phillips, Shakuntala H. Thilsted & Patrick Dugan
Plenary symposium

“Farming Systems Design in Action:
Methods, Achievements and Challenges”
# Systems Analysis for management and design in Agriculture: can we do it with only two concepts ?

Jacques Wery *±1

## 1 Challenge

In many countries of the world, systems analysis is seen as a major driver of innovation and sustainability improvement in agriculture by research institutions, by development agencies but also by private companies and advisory services. On one side the transition towards productive and resource efficient systems (agroecology, sustainable intensification...) requires more knowledge and management of ecological processes. This implies to focuss on interactions and emerging properties, two key components of a system's analysis, rather than on relationships between input and output of a black box. On the other side the performances and sustainability of the farming systems are increasingly defined by other systems (food system, climate change, resources conservation, poverty alleviation, sustainable development...). This implies to work on the three other components of a system's analysis that are limits, environment and flows (e.g. Lamanda et al., 2012) rather than "escaping" from the farming system to work on its embedding or co-existing systems. Managing or designing such complex agricultural systems (AgSys) require science-based operational frameworks combining all these system's components and at the proper scale (field, farm, landscape...).

We argue that this can be achieved with only two concepts that support the development of methodologies across the various scales of AgSys. Discussions during the 5th Farming Systems Design symposium will provide the opportunity to analyse if these concepts are operational in any type of agriculture and research posture and which other concepts are required to complete the framework.

## 2 Concepts and scale integration

As shown by LeGal et al., (2011) AgSys can be analysed as nested hierarchical systems with three sub-systems from quite different domain: (i) a biophysical domain composed of ecological processes at stake in plants, soils, animals (the “process-based operating” sub-system); (ii) a technical domain where techniques are combined in a coherent set to achieve farmers objectives under a limited set of machineries, land, input and labour (the “technique-based managed” sub-system); (iii) a decision system made of objectives and decision rules (the “human-based decision” sub-system). Each of these domains can be the system under study in a research activity but the design of innovative systems requires to adress the whole, as environmental sustainability emerge from the first domain while economic and social sustainability emerge from the two others. In the seek for a trade-off between parsimony and completeness in system's analysis (Lamanda et al., 2012), we propose that every AgSys can be defined by the combination of two concepts, the other aspects and especially the human component of farms being captured in the interactions with other systems.

### 2.1. The Agrosystem and its basic processes

An Agrosystem (As) can be defined as a biophysical « controlled » system meaning that, in contrary to natural systems, its structure and a large part of its input and output are managed by a « pilot » (generally a farmer) in order to derive plant (or animal) production(s) as well as ecosystems services (Lamanda et al., 2012). From this definition and agro-ecosystem can be understood as a combination of As (which are controlled by one or several farmers) and ecosystems which are generally not under the control of a pilot. An As is analyzed and managed as a combination of desired plants (productive plants and service plants) and undesired plants (weeds), of desired (e.g. worms) and undesired (e.g. pests) animals and of a set of soil horizons. It can be considered at any scale from a m², a field, a landscape or the cultivated area in a region. Our experience of conceptual modelling of As, mainly at field level, with the protocol of Lamanda et al. (2012) showed that, in order to avoid over-complexification, the structure of the system should be built with a unique type of component, that we called the "Basic Agrosystem Process" (BAP), which is an extension to soil-plant-animal systems of the basic plant process defined by Wery (2005). A BAP is defined by three attributes:

- It can be quantified or specified at a daily time-step and at the level where resource capture or sharing has a meaning (e.g. m² for the example of the daily net primary production of each species in an agroforestry system). This n level is called the level of "Analysis" of the system.

- It is a major driver of the performance, service or emerging property under study and allows to define the problem that the conceptual model is aimed to address. This n+1 level is called the level of "Relevance" and it is expressed at a more aggregative level (in space and time) than level n (in the above example it would be biomass produced per ha and per year for each of the two species in association).

<footnote n="1">¹ UMR System Supagro, 2 place Viala, 34060 Montpellier, France</footnote>

<footnote>* Speaker</footnote>

<footnote>± Corresponding author: Jacques.wery@supagro.fr</footnote>
- The BAP can be supported by knowledge on functions of plant organs, soil aggregates or animal at a lower level (n-1) which is called the “Functional” level.

**2.2. The Activity**

The technical system by which a farmer “control” at least part of the BAPs of an As can be described with the concept of “Activity” (Act), which is widely used in bio-economic models of AgSys (Flichman et al., 2011). An Act is a coherent set of techniques using farm resources (land, labour, money), inputs (fertilizers, pesticides, energy....), and natural resources (land, water, biodiversity...):

- to provision a service to the AgSys. The output of an Act can be money from direct selling (eg. wheat grain), resource to another activity (eg. forage from cropping system provided to the animal sub-system), money from non productive services (e.g. on farm tourism, Environmental Services such as C sequestration),

-to provision a service (or dis-service) to another system: food for the household, quality water to refill a water table, habitat to biodiversity, landscape for recreation...

An Act (e.g. wheat crop) may provide several services (e.g. grain, straw, C sequestration) or di-services (e.g. N leaching) and a given service (e.g. C sequestration) can be provisioned by several act (e.g crops, grasslands, trees) (Flichman et al., 2011).

As for the As, the Act concept can be used to analyse a problem at field level (e.g. a wheat field), at farm level (e.g. all wheat fields managed on the same way by a farmer), at landscape level (e.g. the area on which a cooperative collect wheat) or at global scale (the wheat production area of a food system).

**3 Revisiting Agricultural Systems definition**

We hypothesize (Fig. 1) that these concepts of As and Act and their interrelationships should allow for the "conceptualization of a problem" in agriculture into an *Agricultural System* (AgSys), defined as a complex controlled system combining biophysical processes and technico-economic activities at one of the above scales or across these scales. In addition to providing a definition to the widely used but poorly defined concept of AgSys, this approach allows to manage the multi-scale and multi-domain dimensions of challenges for agricultural systems analysis, assessment or design at the interfaces with other socio-ecosystems (food security, climate change...). Each of these concepts are supported by an intense and diversified activity of modelling (mainly dynamic process-based modelling for As and bio-economic modelling for Act) and their interrelationships at multiple-scales support integrated modelling of AgSys (van Ittersum *et al*., 2008).

<figure><img src="image_3.png" /><figcaption>Fig. 1. Agricultural systems defined as a multi-scale and multi-domain combination of Agrosystems and Activities.</figcaption></figure>

This framework also allows for studies focussed on specific levels and domains such as the *Farm System* (i.e. a combination of activities with farm territory and household as boundaries), the *Farming System* (as a population of individual farm systems in a territory (Giller, 2013), or the *Cropping System* (as a combination of activities controlling the dynamic of an Agrosystem on a set of fields).

**References**

Flichman, G., Louhichi, K. & Boisson, J.M. (2011). Modelling the relationship between agriculture and the environment using bio-economic models: some conceptual issues. Chap. 1 in G. Flichman (ed.), Bio-Economic Models applied to Agricultural Systems, Springer, DOI 10.1007/978-94-007-1902-6_2

Fresco, L.O. & Westphal, E. (1988). A hierarchical classification of farm systems. Experimental Agriculture 24: 399-419.

Giller, K. (2013). Can we define the term ‘farming systems’? A question of scale. Outlook on Agriculture 42: 149-153. DOI: 10.5367/oa.2013.0139

Lamanda N., Roux S., Delmotte S., Merot A., Rapidel B., Adam M., Wery J. (2012) A protocol for the conceptualisation of an agro-ecosystem to guide data acquisition and analysis and expert knowledge integration. European Journal of Agronomy 38:104-116.

Le Gal, P.Y., Merot, A., Moulin, C.H., Navarrete, M., Wery, J., 2010. A modelling framework to support farmers in designing agricultural production systems. Environmental Modelling & Software 25: 258-268.

Van Ittersum, M.K., Ewert, F., Heckelei, T., Wery, J., Alkan Olsson, J., Andersen, E., Bezlepkina, I., Brouwer, F., Donatelli, M., Flichman, G., Olsson, L., Rizzoli, A.E., Van der Wal, T., Wien, J.E., Wolf, J., 2008. Integrated assessment of agricultural systems - A component-based framework for the European Union (SEAMLESS). Agricultural Systems 96: 150-165.

Wery, J., 2005. Differential effects of soil water deficit on the basic plant functions and their significance to analyse crop responses to water deficit in indeterminate plants. Australian Journal of Agricultural Research 56 (11), 1201-1209.
# Designing ecological intensive farming systems in China: Challenges and strategies

Fu Chen *±<fnref n="1" />*, Wei-Li Liang <fnref n="2" />, Qing-Quan Chu <fnref n="1" />, Hai-Lin Zhang <fnref n="1" /> & Tian-Zhi Ren <fnref n="3" />

## 1 Introduction

Production of food grains has increased from less than 300 to 600 million tons in China over the past 50 years. However, this great achievement has been accomplished at high resource, environmental, and economic costs. Water shortages, environment deterioration, and increasing production cost become more and more prominent in China, and these represent the major challenges to sustainable agriculture development (SAD)(Ju et al., 2009; Guo et al., 2010; Carberry et al., 2013). Therefore, it is crucial for SAD to design novel farming systems that are input-resource efficient and environmental safe. The objective of this study was to assess agricultural input efficiency in China and identify the challenges and strategies for designing ecologically sensitive intensive farming systems in China.

## 2 Materials and Methods

Agricultural input efficiency data related to production of gains in China was adapted from statistical bulletins of agricultural production published in the Chinese Agricultural Statistics Yearbook from 1979 to 2013. We selected the wheat-maize (*Triticumaestivum* L. - *Zea mays* L.) double cropping system (CS) in the North China Plain (NCP) as a case study due to the NCP being a region of typical intensive farming with scarce resources. The case study data were collected from farmers who participated in a survey (120 questionnaires) and on-farm experiments in Wuqiao, Hebei Province in 2013. The technological efficiency (Y/YN: Y is the yield of the farms and YN is the simulated yield by DNDC model with the same nitrogen input conditions) was also analyzed based on the questionnaires.

## 3 Results - Discussion

Food grain production in China increased from $3.32×10^8$ to $6.02×10^8$ t from 1979 to 2013, which was nearly a doubling (Fig. 1). The yield per hectare also nearly doubled from 1979 to 2013, from 2785 to 5377 kg/ha. In addition, agricultural inputs also increased rapidly. For example, the fertilizer consumption increased 4.4 times, pesticides increased 1.3 times (compared to 1991 due to a lack of data before 1991), and effective irrigation area increased by 41%. In the last 30 years, the requirements of fertilizers, pesticides, effective irrigation area, total power of agriculture machinery, rural electricity consumption, and agriculture supporting expenditure expenses have been increased dramatically by 18-34%. In addition, the efficiency of agriculture input-resources has tended to decrease and the economic cost per unit of area has almost increased by 2 times during this period.

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Relative change in agriculture inputs and food grain production ($10^8$ t). The input items in 1979 were regarded as 100, apart from the pesticide consumption, for which 1991 was regarded as 100 because of a lack of data before 1991.</figcaption></figure>

The conventional intensive farming system has resulted in not only an increase in the cost of input-resources, but also resulted in severe pressures on the eco-environment in China. Further agricultural development in most of northern China is challenged by serious water shortages, with the area affected being greater than 30 billion m<fnref n="3" />. Groundwater has been universally over-exploited in the NCP and Sanjiang Plain of Northeast China. In addition, agricultural non-point source pollution has been aggravated due to the high input of chemical fertilizers. Currently, nearly $1.3×10^7$

<footnote n="1">¹College of Agronomy and Biotechnology, China Agricultural University; Key Laboratory of Farming System, Ministry of Agriculture of China</footnote>

<footnote n="2">²College of Agronomy, Agricultural University of Hebei</footnote>

<footnote n="3">³Agro-environmental Protection Institute, Ministry of Agriculture of China</footnote>

<footnote>* Speaker</footnote>

<footnote>± Corresponding author: chenfu@cau.edu.cn</footnote>
ha of cultivated land have been affected by pollution from pesticides, and 3.3×10⁶ ha of cultivated land have been exposed to a moderate degree of pollution or worse. Therefore, there is an urgent requirement to develop an ecologically safe intensive farming system for use in China. This case study in the NCP indicated that the usage efficiency of fertilizers and irrigation water for most farmers was still at a low level. Among the 120 questionnaires, more than half showed high nitrogen inputs with low outputs and approximate one third with low inputs with low outputs, which means that less than 20% of the farmers achieve a reasonable result (Fig. 2). In addition, the irrigation efficiency varied greatly (Fig. 3). These indicate that yield increases from only adding more inputs have not been realized. The technological efficiency of the wheat-maize cropping system was only around 0.7 in Wuqiao, and the technological efficiency higher than 1 only accounted for 2.1% of the survey. The land per family is only about 0.4 ha, and the net income from the wheat-maize cropping system is ~$1960/ha in the NCP, and this is not adequate for the farmers to meet their needs. Thus, it is critical to design novel farming systems with high input-resource efficiency, which are environmentally safe and give high incomes to for farmers. It is essential to improve crop yields by integrated soil and crop management practices, rather than only by increasing inputs of chemical fertilizers, pesticides, and plastic films, especially not by increasing the input rate of a single nutrient. In addition, to promote greater efficiency, farm sizes should be increased.

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Yield distributions with different nitrogen application rate based on farmer questionnaires. I, II, III, and IV denotes ideal inputs with high yields, high inputs with high yields, low inputs with low yields and high input with low yields, respectively.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Yield variations under different irrigation levels based on farmer questionnaires.</figcaption></figure>

## 4 Conclusions

Challenges (e.g., high inputs, shortage of resources and laborers, and agro-environmental pollution) lie ahead for China's agriculture. Therefore, a conversion of the traditional farming system to a novel ecologically sensitive intensive one could be a solution to these issues. This research suggests that it is necessary to establish a resource-environment subsidizing system based on environmental capacity, ecological safety, and level of farm inputs; this will help to regulate farmer behavior and enhance their environmental awareness. Above all, coordinated efforts by policy makers, researchers, extension agents, farmers, and other relevant stakeholders are important keys to the successful design of a new farming system.

*Acknowledgements*. This study was funded by Special Fund for Agro-scientific Research in the Public Interest in China (201103001).

## References

Carberry, P.S. Liang, W.L. Twomlow, S., Holzworth, D.P., Dimes, J.P., McClelland, T., Huth, N., Chen, F., Hochman, Z., &Keating, B. (2013). Scope for improved eco-efficiency varies among diverse cropping systems. *Proceedings of the National Academy of Sciences*, **110**, 8381-8386.

Guo, J.H., Liu, X.J., Zhang, Y., Shen, J.L., Han, W.X., Zhang, W.F., Christie, P., Goulding, K.W.T., Vitousek, P.M., &Zhang, F.S. (2010). Significant Acidification in Major Chinese Croplands. *Science*, **5968**, 1008-1010.

Ju, X.T., Xing, G.X., Chen, X.P., Zhang, S.L., Zhang, L.J., Liu, X.J., Cui, Z.L., Yin, B., Christie, P., Zhu, Z.L., Zhang, F.S. (2009). Reducing environmental risk by improving N management in intensive Chinese agricultural systems. *Proceedings of the National Academy of Sciences*, **106**, 3041-3046.
# From cropping systems design towards sustainable agrifood systems design: new challenges for agronomists

Jean-Marc Meynard<sup>*±1</sup>, Marie-Hélène Jeuffroy<sup>2</sup>, Amélie Lefèvre<sup>3</sup>, Marie-Benoît Magrini<sup>4</sup> & Camille Michon<sup>5</sup>

## 1 Introduction

Instead of working to increase the sustainability of agriculture and food separately what benefit would be gained by reconnecting the innovation dynamics in both domains, improving the entire agrifood system?

The agrifood system (« the way in which people organize themselves, in space and in time, to obtain and consume their food » Malassis, 1994) includes production, trade, processing, distribution and consumption activities that are in very close interaction with each others. Because both the stakeholders and the researchers are specialists in one or other of these segments, innovation in agriculture is today carried out separately from innovation in processing or nutrition (Spiertz, 2012). Our objective is to specify the consequences, for the design of innovations, of an integrated approach, taking the whole of the agrifood system into account.

## 2 A design of coupled innovations, involving production, processing and consumption

A first approach consists of transferring the solution of a problem to another level of the agrifood system. Usually, to optimize the processing procedure, agrifood industry imposes standards of marketable quality on farmers (Allaire, 2010), or draw up contracts with precise specifications (Hensen & Humphrey, 2012), thus configuring the raw material. Innovation in agriculture relates to the technical practices or cropping systems which make it possible to attain the quality desired by the processors. Innovation can then take the form of rules for adapting the techniques to the environment, or for excluding certain cropping systems (for low protein malting barley, see for ex. Le Bail & Meynard, 2003). Innovation can also take the form of specifications with imposed techniques (for ex., following a precise schedule for the production of vegetables for the canning industry). It is less frequent for a production problem to be solved by innovating in the processing procedure. For ex., today the need for high-protein wheat grains to make bread, leads to field applications of large amounts of nitrogen fertilizer, which increases losses of non-used nitrogen. Producing bread with low-protein wheat grains or even without any wheat protein at all (Benatallah et al., 2012) could be possible to the condition of changing the technological process or the formulation. The technological innovation could help to decrease the environmental impacts of wheat production, but changes are required from several actors, including bakers, millers, cooperatives, farmers and consumers.

Indeed, a more ambitious coupling consists of designing simultaneous innovations coordinating the domains of production, processing and consumption, while taking into account synergies or antagonisms between innovations. A good example of this is the development of short distribution channels for vegetables in the industrialized countries; it is based on innovations that are both organizational and agronomic, as the production methods are very different from those used in long distribution channels (Lefèvre et al., 2015). Another example is the objective of reducing the consumption of animal protein, to the benefit of plant proteins, which would be necessary for global food safety (Baroni et al., 2006). Increasing the legume family, which produces protein-rich grains, would be interesting: as they fix atmospheric nitrogen, they do not require nitrate fertilizer, thus saving fossil energy resources and emitting few greenhouse gases (CO2 and N2O). However, in Europe, there is still very little legume production for human consumption. Developing it will require the coordination of different innovations to make the crop, agro-industrial use and legume consumption attractive to the stakeholders, and particularly to consumers precooked preparations making them easy to use in cooking; technological processes enabling the grains to be extracted from new ingredients; innovative crop successions and intercrops including grain legumes; breeding of productive varieties suitable for food uses and for production and processing techniques... (Voisin et al., 2014). Connecting simultaneous innovation procedures in these various domains, to ensure they are compatible and maximize their synergies, requires the design procedures to be revised, and the functioning of the R&D departments of the companies concerned to be reorganized. Theoretical frameworks of innovative design (Le Masson et al., 2006) offer pathways for such an ambition: innovative design, that refers to a process of exploration aimed at satisfying very new expectations, seems to be particularly relevant for coupled innovations, whose identity is not fully specified in the early stages of design, and become progressively more precise as the designed objects take shape.

<footnote n="1"><sup>1</sup>INRA, UMR1048 SAD-APT INRA-AgroParisTech, 78850 Thiverval-Grignon, France</footnote>

<footnote n="2"><sup>2</sup>INRA, UMR211 Agronomie INRA-AgroParisTech, 78850 Thiverval-Grignon, France</footnote>

<footnote n="3"><sup>3</sup>INRA, INRA SAD UE411 Domaine expérimental Alénya Roussillon, 66200 Alénya, France</footnote>

<footnote n="4"><sup>4</sup>INRA, INRA, UMR1248 AGIR, INRA-INP-ENSAT, 31326 Castanet-Tolosan, France</footnote>

<footnote n="5"><sup>5</sup>AgroParisTech, UMR1145 Ingénierie Procédés Aliments, AgroParisTech-INRA, 91300 Massy, France</footnote>

<footnote>*± Speaker & Corresponding author: meynard@grignon.inra.fr</footnote>
## 3 Collective design in innovation niches

The previous examples and the literature (e.g. Bos, 2008) show that innovation for the sustainability of agrifood systems may rely on broad-based stakeholders collectives. The innovation process unfolds in a sociotechnical regime, defined by a collective of stakeholders and their networks, practices and knowledge, the technologies they use, their collective representations, the standards and rules they adopt. The regime configures the innovation process: innovations that do not call into question the networks of stakeholders, the social representations and the standards, and which are in synergy with innovations previously diffused, have more chance of seeing the light of day and being diffused (path dependency). Consequently, the dominant socio technical regime is locked-in by this path dependency, and it should not be expected that radical innovations will emerge. As underlined by the sociotechnical transitions theory, radical changes are prepared outside the dominant sociotechnical regime, in "innovation niches", composed of minority actors who convey challenges for the future (Kemp et al., 1998). In these niches emerge new networks of stakeholders, new practices, new technologies or modes of organizing exchanges. If the socio-political context develops in their favor, or if, in the name of the general interest, they have the support of public authorities, they will be able to be diffused in the dominant regime (Geels, 2002).

Thus the transition of agrifood systems requires not only an effort of organizational and technical innovation in the niches, but also institutional and regulatory innovations (the latter supported by public authorities) to favor the hybridization of the niches with the dominant regime. Let's take the example of crop diversification. The increase in international trade has supported the specialization of agricultures, as each nation, each region, develops the productions where it has a competitive advantage: soybean in the Argentinean Pampa, wheat and oilseed rape in the Paris basin, the oil palm in South-East Asia, the banana in Central America.... The result is wide expanses of monocultures and short rotations, which are prejudicial to biodiversity and are often only possible with the massive use of pesticides. In France, although crop diversification is seen as desirable by many stakeholders and the public authorities, there is a technological lock-in around the dominant species, which blocks or at least greatly handicaps the development of minor species, even though new outlets could exist for their products. Meynard et al. (2014) showed, in coherence with the transition theory, that the situation could be unlocked if there were a simultaneous and coordinated mobilization of the levers of: i) genetic innovation, i.e. the selection of diversification species; ii) agronomic innovation, i.e. successions that include these crops and iii) technological innovation, such as processing procedures opening up new outlets for minor species. But this would also involve levers which relate directly to public authorities, intended to facilitate the consolidation of new sectors, via arrangements to coordinate actors or standards that help the market to institutionalize those diversification products (Meynard et al., 2014). Designing in the niches, and with the actors in the niches, does not mean that agronomic and technological innovations will necessarily be only for a limited audience, but their appropriation by a wider audience will depend on social, institutional or regulatory innovations, which will need to be placed in the schedule of interdisciplinary research involving the agronomic sciences.

## 4 Conclusions

For agronomists, designing in agrifood systems involves a renewal in the organization of design: coordinating the design of a wide variety of innovations (agronomic, technological, organizational, institutional), integrating new knowledge linked with new social pressures (ie. nutrition, health and pleasure) and public policies, and redefining the round table of stakeholders engaged in design to lock-out the dominant regime.

## References

* Allaire, G. (2010). Applying economic sociology to understand the meaning of "Quality" in food markets. *Agricultural Economics*, 41(s1), 167-180.

* Baroni, L., Cenci, L., Tettamanti, M. & Berati, M. (2006). Evaluating the environmental impact of various dietary patterns combined with different food production systems. *European Journal of Clinical Nutrition*, 61 (2): 279-286.

* Benatallah L., Zidoune M.N. & Michon C. (2012). Optimization of HPMC and Water Addition for a Gluten-Free Formula with Rice and Field Bean Based on Rheological Properties of Doughs. *International Review of Chemical Engineering (I.RE.CH.E.)*, 4(5), 474-481.

* Bos A.P. (2008) Instrumentalization Theory and reflexive Design in Animal Husbandry. *Social Epistemology* Vol. 22, No. 1, pp. 29–50

* Geels F.W. (2002). Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study. *Res.Policy*31 : 1257-1274.

* Kemp, R., Schot, J., & Hoogma, R. (1998). Regime shifts to sustainability through processes of niche formation: the approach of strategic niche management. *Technology Analysis & Strategic Management*, 10(2) : 175-198.

* Henson, S. & Humphrey J., (2012). Private Standards in global agri-food chains. in Marx A., Maertens M., Swinnen J. and Wouters J. (eds) *Private Standards and Global Governance: Economic, Legal and Political Perspectives*, Cheltenham, Edward Elgar, pp. 98-113.

* Le Bail M. & Meynard J.M. (2003). Yield and protein concentration of spring malting barley: the effects of cropping systems in the Paris Basin (France). *Agronomie*. 23 : 13-27.

* Lefèvre A., Salembier C., Perrin B., Lesur-Dumoulin C. & Meynard J.M. (2015) Design, experimentation and assessment of four protected vegetable cropping systems adapted to different food systems. 5th international symposium for farming system design, Montpellier

* Le Masson, P., Weil, B. & Hatchuel, A. (2006). Les processus d'innovation: Conception innovante et croissance des entreprises, Hermes science publ.

* Malassis L., (1994). Nourrir les Hommes, Dominos-Flammarion, Paris : 110 p.

* Meynard J.M., Messéan A., Charlier A., Charrier F., Fares M., Le Bail M., Magrini M.B., Savini I. & Rechauchère O.(2014). *La diversification des cultures. Lever les obstacles agronomiques et économiques*. Editions QUAE, Versailles :104 p.

* Voisin, A. S., Guéguen, J., Huyghe, C., Jeuffroy, M. H., Magrini, M. B., Meynard, J. M., Mougel Ch., Pellerin S. & Pelzer, E. (2014). Legumes for feed, food, biomaterials and bioenergy in Europe: a review. *Agronomy for Sustainable Development*, 34: 361-380.

* Spiertz, JHJ.(2012). Avenues to meet food security. The role of agronomy on solving complexity in food production and resource use. EJA 43, 1-8.
# Quantifying beef production gaps of two farming systems in the Charolais basin, France

Aart van der Linden *±1,2, Gerrie W.J. van de Ven<fnref n="1" />, Simon J. Oosting <fnref n="2" />, Martin K. van Ittersum<fnref n="1" /> & Imke
J.M. de Boer <fnref n="2" />

## 1 Introduction

Sustainable intensification of livestock production systems is a way to realise the increasing global demand for meat. Current empirical studies reveal meat production levels obtained by best practices, but do not clarify the theoretically achievable (i.e. potential) and feed limited production. Potential production is defined by animal genotype and climate only (Fig. 1). Feed limited production is determined by genotype, climate, availability of drinking water, and the quality and quantity of feed. Actual production is the production that farmers achieve in practice. This production level is, next to genotype, climate, water, and feed, determined by diseases and stress in livestock (Van de Ven et al., 2003).

<figure><img src="image_7.png" /><figcaption>Fig. 1. Potential, limited, and actual production of crops (left) and livestock (right).</figcaption></figure>

In crop production, the production ecological concepts of potential, limited, and actual production (Fig. 1) (Van Ittersum & Rabbinge, 1997) are generally used to give insight in the scope to increase production from their actual levels (Van Ittersum et al., 2013). These concepts are also applicable to livestock production (Van de Ven et al., 2003; Van der Linden et al.), but so far the effects of genotype, climate, feed quality, and feed quantity have not been quantified systematically using production ecological concepts in livestock production. This research, therefore, aims to quantify potential, feed quality limited, and actual beef production in two French beef production systems at herd level. Feed quantity limitation is not included.

## 2 Materials and Methods

A mechanistic, dynamic model was developed to simulate beef cattle growth based on genotype, climate, housing, feed quantity, and feed quality. This model is analogous to crop growth models that are based on the production ecological concepts. The beef cattle model combines feed digestion, thermoregulation, and feed utilisation sub-models in a novel way to simulate processes at animal level. Results from animal level are scaled up to herd level. Energy, heat, and protein flows are described in the model, which is programmed in R 3.0.2. Input data for the model are parameters for a specific genotype or breed, daily climate data, and information on housing, feed quality and feed quantity intake. The model was applied to two beef production systems with different feeding strategies of Charolais cattle in the Charolais Basin, France. System A corresponds to farm type 11111 and system B to farm type 31041 as described by Réseaux d'Elevage Charolais (2012). System A produced heavier animals and has a longer grazing period than system B. The fraction concentrates in the diet is larger in system B than in system A.

Potential production was expressed as a feed efficiency (FE, g beef kg⁻<fnref n="1" /> DM feed). Potential production in both systems was simulated with an *ad libitum* fed diet containing 65.8 % barley and 34.2% hay. This diet prevented feed quality and quantity limitation. Under potential production, FE was maximized at herd level, and all female calves were kept for replacement. Culling was set at 50% per year after birth of the first calf. Feed quality limited production was simulated with a diet containing concentrates and hay when cattle were housed during winter, and grass during other periods of the year. Concentrate intake (barley) was 4.8% of the DM intake in system A and 18.3% of the DM intake in system B,

<footnote n="1">¹ Plant Production Systems, Plant Sciences Group, Wageningen University</footnote>

<footnote n="2">² Animal Production Systems, Animal Sciences Group, Wageningen University</footnote>

<footnote>* Speaker</footnote>

<footnote>± Corresponding author: aart.vanderlinden@wur.nl</footnote>
which corresponded to the diet under actual production. Feed quality limited production was simulated with the same culling rates and slaughter weights as under potential production. Actual production was calculated from data provided by Réseaux d'Elevage Charolais (2012). Yield gaps were calculated as the difference between potential and actual production, and the difference between feed quality limited production and actual production. Relative yield gaps were calculated as the yield gap divided by potential or feed quality limited production.

**3 Results and discussion**

FE at herd level was highest under potential production and feed quality limited production, when male calves were slaughtered at 1000 kg. Potential production in systems A and B (Fig. 2) was slightly different (64.0 vs 64.4 g beef kg⁻¹ DM feed). FE in system A was lower due to a longer grazing period and hence a higher energy requirement for grazing. Feed quality limited production, with the same culling rates and slaughter weights as under potential production, was lower in system A than in system B (51.7 vs 54.1 g beef kg⁻¹ DM feed), which is explained by a lower fraction of concentrates in the diet. Actual production was lower in system A than in system B (24.9 vs 31.2 g beef kg⁻¹ DM feed).

<figure><img src="image_8.png" /><figcaption>**Fig. 2.** Simulated feed efficiency in beef production systems A and B under potential, feed quality limited, and actual production.</figcaption></figure>

The relative yield gap between actual and potential production was 61% in system A and 52% in system B, and the relative yield gap between actual and feed quality limited production was 52% in system A and 42% in system B. The latter yield gaps can be explained by feed quality limitation, as well as stress and diseases. In crop production, yields tend to plateau at 75-85% of potential or water limited production (i.e. minimum yield gaps equal 15-25%), and further yield gap mitigation is not economically or practically feasible (Van Ittersum *et al.*, 2013). In our study, simulated yield gaps are much larger than such minimum yield gaps. Grazing and suckler cow premiums might not urge farmers to mitigate current yield gaps, but also social factors (e.g. labour availability) may play a role. More model validation is required to further improve accuracy of the simulation results. Multiplying beef production (kg beef t⁻¹ DM feed) and feed crop production (t DM ha⁻¹ year⁻¹) results in the beef production per unit of land (kg beef ha⁻¹ year⁻¹). Quantifying potential and limited production of crops and livestock according to production ecology allows us to assess land use per kg of animal product.

**4 Conclusions**

The production ecological concepts were successfully applied to livestock production. We benchmarked actual beef production relative to potential and feed quality limited production of two French beef production systems at herd level. Results indicate that potential production is more than two times the actual production in both systems. Hence, there is considerable scope to increase beef production in the Charolais basin, from a bio-physical perspective.

**References**

Réseaux d'Elevage Charolais (2012). Bassin Charolais. Conjoncture économique des systèmes bovins Charolais, Campagne 2012. Document, Chambre d'Agriculture, Institut de l'Elevage, 50pp.

Van de Ven, G.W.J., de Ridder, N., van Keulen, H. & van Ittersum M.K. (2003). Concepts in production ecology for analysis and design of animal and plant-animal production systems. *Agricultural Systems*, **76**, 507-525.

Van der Linden, A., Oosting, S.J., van de Ven, G.W.J, de Boer, I.J.M. & van Ittersum, M.K. A framework for quantitative analysis of livestock systems using the theoretical concepts of production ecology. Submitted to *Agricultural Systems*.

Van Ittersum, M.K. & Rabbinge, R. (1997). Concepts in production ecology for analysis and quantification of agricultural input-output combinations. *Field Crops Research*, **52**, 197-208.

Van Ittersum, M.K., Cassman, K.G., Grassini, P., Wolf, J., Tittonell, P. & Hochman, Z. (2013). Yield gap analysis with local to global relevance-A review. *Field Crops Research*, **143**, 4-17.
PATH DEPENDENCE AND TRANSITION: A THEORETICAL PERSPECTIVE ON
FARM STRUCTURES

Alfons Balmann<sup>*±1</sup>, Franziska Appel<sup>1</sup>, Frans Hermans<sup>1</sup>, Karin Kataria<sup>1</sup>, Arlette Ostermeyer<sup>1</sup>, Zhanli Sun<sup>1</sup>
& Vladislav Valentinov<sup>1</sup>

Farming systems are closely connected with the regional farm structures. Even within and between regions with similar agricultural conditions (climatic, soil, infrastructural, economic, social), farm structures and farming systems can be very heterogeneous. One general explanation for this heterogeneity is the path dependence of structural change (Balmann, 1995). Current agricultural structures are shaped by historical events and previous pathways. Agricultural structures tend to be locked in certain regimes and evolve at a rather slow speed. This inertia is caused by long investment cycles, slow changes in human and financial capital, persistent institutions, specific mental models of the actors and state conserving agricultural policies. As a result, agricultural structures appear often resilient to external changes.

Path dependence is however not absolutely perpetual. Under certain conditions, farm structures and related farming systems may be subject to abrupt changes. Such changes can be considered as structural transitions or regime shifts. On the one hand, these changes can be triggered by pull factors such as path breaking and path creating activities of certain actors or by new opportunities resulting from new technologies or markets. On the other hand, these changes may also be caused by push factors such as changing environmental conditions (natural, economic, institutional) which erode the preconditions of the current farming structures and systems. An erosion of preconditions may also result from an unsustainability of the existing system. Often, pull and push factors complement each other for a transition. Before however, fundamental structural changes occur from such causes, some additional facilitators or catalysts of changes are necessary. One reason is that a “valley of tears” might have to be overcome or is assumed by the actors as to huge. Another reason is that structural changes generate winners and losers.

Path dependent systems typically have multiple optima. The transition from one optimum to another one implies then the necessity to cross a local minimum, i.e. a “valley of tears”. Accordingly, transitions require investments. These only pay off, if the additional value of the new optimum is higher than the investment costs. Even if the additional value is sufficiently high, there is still the question whether the payoffs are to the benefit of those who are investing. Another question is whether it is possible to coordinate a transition among the actors. Reasons for such coordination problems can result from communication deficits, moral hazard, and bounded rationality. With regard to structural changes, all these types of obstacles are to be expected (Balmann et al., 2006). One problem are sunk costs of existing assets which would be devaluated. Another reason is that a modernization on one stage of a supply chain may also require investments on other stages, and last but not least, smart solutions for successful transitions need to be identified.

Although, structural changes which occur slowly or as transitions have to be seen as important drivers of economic development, structural changes are often perceived negatively. This can partly be explained by the Schumpeterian argument of “creative destruction” saying that “the process of industrial mutation (...) incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one” (Schumpeter, 1942). Over the past two centuries, structural changes affected particularly the agricultural sector which nowadays contributes in western economies only marginal shares to GDP and employment while two hundred years ago, agriculture was the main sector in Europe and even more the US (USDA, 2001). This development was driven by enormous productivity increases within agriculture and by fast economic growth outside agriculture. A side effect was a substitution of labor through capital. As a result, on the one hand incomes of many farmers and their families increased while many other farms exited, i.e. there were winners and losers.

The process of structural change is neither smooth, nor are farms homogeneous. The distribution of farm sizes is skewed and follows to some degree the Pareto rule, saying that a minor share of large farms farm a major share of total land and produce a major share of total production. These differing preconditions imply that farmers have quite different opportunities to develop as well as differing perceptions about the likely impacts of changes. Because of the skewness, usually a large fraction of farms is on the downside with rather poor development perspectives. As experimental results show that loss aversion affects individual behavior more that potential gains (Kahneman and

<footnote n="1">¹Leibniz Institute of Agricultural Development in Transition Economies (IAMO)</footnote>

<footnote>* Speaker</footnote>

<footnote>‡ Corresponding author: balmann@iamo.de</footnote>
Tversky, 1984), the uncertainty on the implications of substantial innovations and eventually resulting subsequent path breaking structural adjustments causes often more skepticism about losses that enthusiasm about the gains.

Both factors, the skewness of individual development perspectives and the loss aversion provide additional explanations why many farms are concerned about structural changes. These concerns have further implications. If the original cause of structural change is that the current system is under pressure to change (either because superior states exist or because its preconditions are eroded), the concerns of the potential losers may cause pressure to stabilize the existing system. If these attempts are successful, the external pressure to adapt may accumulate and cause a kind of subsidy trap (cf. footnote 2) in which the burdens to adapt towards superior solutions increase, as neither the sustainability problems are resolved nor the competitiveness of the current systems improves. This phenomenon resembles the Luhmannian problem of selfreproducing systems. Accordingly, "*systems develop own degrees of freedom, which they can exhaust as long as it is possible, that is, as long as the environment can tolerate it ... The overall effect [of operational closure] however is ... not adaptation, but amplification of deviations*" (Luhmann, N., 1997, p.133). Luhmann argued that social systems fulfill their function at the cost of developing autopoietic properties which lower their sensitivity to the complexity of their environment (Valentinov, 2014).

The above conceptual reflections will be analyzed for the future of the dairy sector after the abolition of the quota system. On the one hand, it will be illustrated that path braking activities of a few dairy farmers may trigger a fundamental change at the system level. On the other hand, it will be discussed which intrasectoral frictions may arise.

**References**

- Balmann, A. (1995). Pfadabhängigkeiten in Agrarstrukturentwicklungen. Begriff, Ursachen und Konsequenzen. Berlin.

- Balmann, A., Dautzenberg, K., Happe, K. & Kellermann, K. (2006). On the dynamics of structural change in agriculture: Internal frictions, policy threats and vertical integration, *Outlook on Agriculture* **35**, 115-121.

- Economic Research Service, U.S. Department of Agriculture (USDA) (2001). A History of American Agriculture 1776-1990. Accessed via http://inventors.about.com/library/inventors/blfarm4.htm on March 29, 2015.

- Kahneman, D. & Tversky, A. (1984). Choices, Values, and Frames. *American Psychologist* **39** (4), 341–350.

- Luhmann, N. (1997). Die Gesellschaft der Gesellschaft. Frankfurt am Main.

- Schumpeter, J. (1942). Capitalism, Socialism and Democracy.

- Valentinov, V. (2014). K. William Kapp's theory of social costs: A Luhmannian interpretation. *Ecological Economics* **97**, 28-33.
# Innovation by smallholder farmers for more diverse and intensive farming systems

Bill Bellotti*±<fnref n="1" />, Gavin Ramsay<fnref n="2" /> Ashok Kumar<fnref n="3" /> Avijit Choudhury<fnref n="3" /> & Nivedita Narain<fnref n="3" />

## 1 Introduction

The east Indian states of Jharkhand, Bihar and West Bengal are characterised by endemic poverty, high incidence and severity of malnutrition, and entrenched discrimination against women. Rice dominates local cropping systems and transplanted rice monoculture is the traditional farming practice. Rice also dominates traditional diets and contributes to widespread malnutrition. In similar communities in neighbouring Bangladesh up to 77% of household calorie intake is derived from rice, contributing to 'hidden hunger'. The dominance of transplanted rice also contributes to the disempowerment of women with the menial tasks of transplanting and hand weeding traditionally reserved for women. Against this background, an agricultural research for development project is working with local indigenous communities to diversify and intensify cropping systems, increase household income, improve food security and empower women farmers. The project is having positive impacts on crop productivity, household income, food security, and human capacity for independent innovation. This paper focusses on the process of engaging women farmers in the research process that leads to development of their capacity for solving problems and realising opportunities, including their role in developing more diverse and intensive farming systems.

## 2 Materials and Methods

The research is located in three tribal villages, Bhubhui and Talaboru in Jharkhand and Churinsara in West Bengal, all three on the East India Plateau. Average annual rainfall is around 1,200 mm, highly concentrated in the monsoon (June-October), and highly variable both within and between seasons. The landscape is undulating and soils variable ranging from mainly coarse textured soils in the uplands and medium-uplands, with finer textured soils in the lowlands. Transplanted rice is the dominant cropping system and while this system is well adapted in the wetter lowlands, it is a very risky proposition in the medium-uplands which dominate in terms of area. Rice is risky in the medium-uplands due to the unreliable timing and duration of ponding that is essential for transplanting (Cornish, et al., 2015). The research is focussed on developing alternatives to transplanted rice in the medium-uplands. Options include vegetables, maize, and aerobic Direct Seeded Rice (aDSR) during the monsoon (kharif), and vegetables, pulses, oilseeds, and wheat post monsoon (rabi). The research is conducted on farm and experimental treatments are managed by farmers. Individual research farmers are selected from within local Self Help Groups previously established by PRADAN for development purposes. Participation in research through these SHGs facilitates individual and collective learning.

## 3 Results – Discussion

<figure><img src="image_9.png" /><figcaption>**Fig. 1.** Smallholder farmers play critical roles in the innovation of new farming systems.</figcaption></figure>

<footnote n="1">¹ University of Western Sydney, Richmond, Australia</footnote>

<footnote n="2">² Charles Sturt University, Wagga Wagga, Australia</footnote>

<footnote n="3">³ Professional Assistance for Development Action (PRADAN), New Delhi, India</footnote>

<footnote>*Speaker</footnote>

<footnote>‡Corresponding author: w.bellotti@uws.edu.au</footnote>
Innovation is described here as the process by which new knowledge, discovery, invention, etc. is developed into commercial (or in this case including subsistence) practice. Figure 1 is employed as a framework for describing the active role of farmers in research and innovation using the example of aerobic Direct Seeded Rice as a case study.

1. *Identification of problems and opportunities worthy of research*

Potential research topics are identified in partnership with local farming communities. The research team hold discussions with Self Help Groups (SHGs) established by Professional Assistance for Development Action (PRADAN) to discuss current needs and future opportunities. Out of these discussions the initial problem of failed transplanted rice emerged and led to research comparing transplanted rice with aDSR under farmer-managed conditions. After several years of on-farm research new research questions have emerged, e.g. the importance of early sowing of the *rabi* crop necessitating early sowing and short duration cultivars of the preceding rice crop, and the improvement in soil physical conditions following cessation of puddling associated with ponding and transplanting.

2. *Research, discovery, creation of new knowledge*

The research involves side-by-side comparisons of the two rice systems (transplanted rice vs aDSR), including the possible sowing of a *rabi* crop following rice harvest, in farmer fields under farmer management. Farmers were involved in developing a locally acceptable version of aDSR including the absence of puddling, hand sowing of seed and fertiliser in lines, opportunistic ponding, and mechanical weeding between rows. Data is collected on basic soil and crop performance, as well as management inputs and practices. Farmers are involved in data collection and results are discussed collectively in the SHGs. Farmers make direct observations and pose new questions.

3. *Farmer evaluation of the intervention*

The small fields, close community and high population density result in many farmers observing the research fields. Farmers are free to observe progress at any time and free to draw their own conclusions. In recent years, when the monsoon has arrived late, transplanted rice has often failed and the aDSR treatment has performed comparatively well. Another attraction of aDSR is the reduced labour requirement, freeing women for more profitable use of their time. Farmers are also reporting improved soil physical conditions after aDSR leading to better *rabi* crop establishment. The area under aDSR is expanding each year indicating farmer acceptance.

4. *Farmer implementation of the intervention*

An integral component of this locally developed aDSR system is the use of manually operated implements for line sowing and between-row weed control. Demand for these simple implements currently outstrips supply. Farmers have initiated variations on the aDSR system, e.g. intercropping rice with a pulse crop (Black Gram, *Vigna mungo*), and relay sowing chickpea (*Cicer arietinum*) prior to rice harvest. These farmer initiated comparisons are evidence of a culture of experimentation emerging from the SHGs. Concerns with aDSR raised by farmers include choice of cultivar, fertiliser rates, weed management, and crop damage from pests associated with early maturity.

5. *Farmer dissemination and diffusion, scaling out*

The local SHG facilitates the process of data collection and results are quickly communicated within and beyond the SHG. Villagers inspect the research fields on a fortnightly basis often coinciding with data collection, stimulating much debate and discussion. Research farmers have also hosted field visits of over 200 farmers from neighbouring villages. Farmer-to-farmer communication has much greater credibility and influence than outside experts on farmer practice.

**4 Conclusions**

The key to diversifying and intensifying local cropping systems is the transition from transplanted rice to aDSR. This is partly because aDSR can be sown and harvested earlier than transplanted rice, making a *rabi* crop, with or without irrigation, possible. Also, the labour requirement of aDSR is much less than for transplanted rice, thus freeing up labour, particularly that of women, for more profitable and nutritious enterprises such as vegetables. The transition from traditional transplanted rice to aDSR represents a major change for farmers and researchers, both in thinking about, and the practice of, the rice-based cropping system. Aerobic Direct Seeded Rice represents not just a change in rice establishment method, but a transformation of the cropping system. The consequences of changing to aDSR include bio-physical, socio-economic and psycho-social effects. This complex chain of events requires a deep understanding of constraints and opportunities from participating farmers and is justification for the process of deep engagement of farmers in the research activity. Farmers play an active and essential role in all stages of the innovation cycle and there is evidence that farmers are developing independent capacity for innovation. Without this active farmer participation the aDSR intervention would be scaled out much slower, or possibly not at all in these regions.

*Acknowledgements.* Project members, particularly our research farmers never fail to inspire. The people of Australia support this research through the Australian Centre for International Agricultural Research project LWR/2010/082, Improving livelihoods with innovative cropping systems on the East India Plateau.

**References**

Cornish, PS et al., (2015) Improving crop production for food security and improved livelihoods on the East India Plateau. I. Rainfall-related risks with rice and opportunities for improved cropping systems. *Agricultural Systems*, in press.
# Analysing farming system design activities in the light of Design Studies concepts

Marie-Hélène Jeuffroy*±1, Marianne Cerf<fnref n="2" />, Lorène Prost<fnref n="2" /> & Jean-Marc Meynard³

## 1 Introduction

Major environmental challenges and increasing societal demand for food and non food products lead to the necessity of a deep redesign of farming practices (Meynard et al., 2012). This redesign generates a great deal of research in agronomy, about innovative solutions. Design Studies (Cross, 2007), which focus on the nature of design processes and their organization (e.g. Detienne 2006, Le Masson et al., 2013), provide useful concepts to address the methodological challenges that farming system design is now facing. Design is an active and deliberate process aiming at generating simultaneously concepts and knowledge, which might result in new products or new technologies, used by actors. As innovation is not only the aggregation of existing knowledge, design is a bridge process between research (as an activity of knowledge production) and innovation. In this paper, from our experience of several case studies, we analyse design in agriculture in the light of two concepts proposed by the Design Studies, *innovative design* and *users' activities*.

## 2 Redesign in agronomy calls for innovative design

As agriculture is currently facing many and sometimes contradictory challenges, agriculture calls for a considerable effort of *innovative design*, defined in Design Studies as a process of exploration aimed at satisfying completely new expectations. Opposed to rule-based design, which aims to gradually improve existing products or technologies without changing the objectives, innovative design is required when the identity of the objects to be designed is not a priori known (Le Masson et al., 2006).

In order to meet the huge challenges of agriculture, agronomists developed various methods for innovative design of cropping and farming systems. First, model-based design helps to explore large combinations of techniques, to determine those that are the most suited to a set of specifications. Model-based design allows to predict long-term effects of the designed solutions, and to estimate impacts that are difficult /impossible to be measured (Bergez et al., 2010). As models restrict the exploration to the scientific existing knowledge, other methods, were proposed, that make space for different sources of knowledge (expert and scientific, local and generic). They are grouped under the name "prototyping" that was initially used by Vereijken (1997) in agriculture. For instance, the prototyping design workshops of Reau et al. (2012) gather a large diversity of stakeholders, researchers and agricultural actors, bearing knowledge and points of view on objectives for agriculture. They are based on an animation enhancing the exploration of breakthrough innovations, designed to reach new objectives and to overcome the problems or impacts encountered in the present farming systems. A third method is the system experiment (Colnenne-David & Doré, 2014). It consists in implementing, assessing and improving prototypes of cropping or farming systems, integrating experts" knowledge in the system management and reframing it progressively (Meynard, 2015). The fourth method is the step-by-step design, aiming at progressively improving existing systems in order to adapt them to new objectives. It begins by a diagnosis on the present system, then changes are proposed and implemented, a new assessment is realised, in a continuous loop of progress (Meynard et al., 2012). Finally, at the territorial scale, companion modelling, combining modelling and role-playing games (Etienne 2014), are powerful approaches to accompany the collective learning process and the design of innovative solutions involving a large diversity of actors. All these methods allow to build innovative farming systems or collective organizations of farming systems, the limits, purposes, and characteristics of which being unknown at the start of the design process.

## 3 Design is strongly linked with the users' activities

In agriculture, many actors and stakeholders, by their activities, contribute to the design of cropping or farming systems: design is highly distributed. Sometimes, some practices are designed and imposed on farmers by contracts or specifications from food processing firms. Other times, the target of collective firms being to optimize the logistics, these organizations impose to grow particular varieties in some locations, thus contributing to the design of the cropping systems. In other cases, farmers use monitoring tools, designed by pesticide or fertilizers sellers. Most often, cropping systems design is enhanced by the participation of the farmer in exchange groups involving other farmers and advisors (Compagnone, 2014). The methods presented above were developed to involve the knowledge, aims and means of action from all the actors concerned by the successful implementation of new farming systems. Indeed, in agriculture,

<footnote n="1">¹ INRA, UMR211 Agronomie INRA-AgroParisTech, 78850 Thiverval-Grignon, France ² INRA, UR1326 SenS, UPEM Cité Descartes, 77454 Marne-la-Vallée Cedex 2, France ³ INRA, UMR1048 SAD-APT INRA-AgroParisTech, 78850 Thiverval-Grignon, France</footnote>

<footnote>* Speaker</footnote>

<footnote n="2">² Corresponding author: Jeuffroy@grignon.inra.fr</footnote>
this implies that all the actors who by their activities influence the potential value and feasibility of a given farming system, contribute themselves to the design.

This distributed design process should adapt in a flexible way to the huge diversity of pedo-climatic conditions and socio-economic environments in which the innovative system will be implemented. Farms differ in terms of soil types, climatic conditions, available resources (human labour, machinery, economic resources), ecological vulnerabilities, surrounding agro-industries. Farmers also differ from each others in their vision for the future. Thus, it is not possible and not desirable to design innovations that might fit everywhere. Rather than designing a small number of „ideal” innovations, agronomists have to prepare and make available a diversity of solutions, in which farmers could choose, such as libraries of innovations (Meynard et al., 2012; Guichardet al., 2015). Agronomists face to this variety by designing either local systems, strictly adapted to local conditions, or generic solutions fitted to a large range of environments, thus leading to strategic choice to be done. They should be more involved in developing tools and methods helping farmers to innovate (and to assess their own innovations) and to adapt to their situation the innovations that have been judged interesting by others. Design Studies show that the implementation of a designed object is a creative process during the course of which both this object and the users" activities are reframed (Rabardel & Béguin, 2005). Design methods proposed by agronomists should allow taking on board use situations in a way that enables users to experiment the changes that might occur through the use of the designed artefact.

## 4 Conclusions

Design in agronomy should enrich its exploration and implementation methods, inspired from Design Studies. In this aim, it could be relevant to imagine original combinations of already existing methods presented in this paper, as each one has limits regarding the strong challenges for agriculture. For example, combining modeling, allowing assessing interactions, with local knowledge should be a great challenge for agronomists, leading to a renewal of models, and to the production of new types of knowledge for action, such as indicators for monitoring the long-term action or for allowing learning for farmers (Toffolini et al., 2015).

Moreover these challenges also call for a renewal of the designer skills and design organizations. For example, a successful design workshop does not require a scientist putting on the table all the scientific knowledge, part of it being impossible to use in the local situations, but a combination of skills: scientists, experts with local knowledge, experts in innovations enhancing the exploration process, and a facilitator organizing the discussions and governing the design process (Reau et al., 2012). To enhance this process, this huge call for design should require a change in the activities of people involved in design, and a change in the organization of their institutions. The experience of the industry shows that design should partially pilot knowledge production, while it is often considered, in scientific bodies, that design is a simple assembly of knowledge. Finally, as the design process is based on an exploration of new concepts and knowledge, it is not possible to plan the design process, and to identify the scientific domains required and the skills to invite. The paradox is that innovative design is an increasing priority in research bodies, but this activity is not consistent with the actual organization of research, based on short-term well defined projects.

## References

* Bergez, J. E., Colbach, N., Crespo, O., Garcia, F., Jeuffroy, M. H., Justes, E., Loyce, C., Munier-Jolain, N., & Sadok, W. (2010). Designing crop management systems by simulation. *European Journal of Agronomy*, **32**(1), 3–9.

* Compagnone, C. (2014). Burgundy Winemakers and respect of the environment. Occupational networks and dynamics of change. *Revue Francaise De Sociologie*, **55**(2), 319–358.

* Cross, N. (2007). Forty years of design research. *Design Studies*, **28**(1), 1–4.

* Détienne, F. (2006). Collaborative design: Managing task interdependencies and multiple perspectives. *Interacting with Computers*, **18**(1), 1–20. Dorst, K. (2008). Design research: a revolution-waiting-to-happen. *Design Studies*, **29**(1), 4–11.

* Étienne, M. (Ed.). (2014). Companion Modelling, A Participatory Approach to Support Sustainable Development. Dordrecht: Springer Netherlands.

* Le Masson, P., Dorst, K., & Subrahmanian, E. (2013). Design theory: history, state of the art and advancements. *Research in Engineering Design*, **24**(2), 97–103.

* Meynard, J.M., Dedieu, B., & Bos, A. P. (2012). Re-design and co-design of farming systems. An overview of methods and practices. In *Farming Systems Research Into the 21st Century: The New Dynamic*. Springer.

* Le Masson, P., Weil, B., & Hatchuel, A. (2006). Les processus d'innovation: Conception innovante et croissance des entreprises, Hermes science publ.

* Colnenne & Doré 2014. Designing innovative productive cropping systems with quantified and ambitious environmental goals. *Renewable Agriculture and Food Systems*, http://dx.doi.org/10.1017/S1742170514000313

* Meynard J.M. (2015). System experiments: methodological progress. 5th International symposium for Farming System Design, Montpellier, France.

* Guichard, L., Ballot, R., Halska, J., Lambert, E., Meynard, J.M., Minette, S., Petit, M.S., Reau, R., & Soulignac, V. (2015). Agropeps, un outil web collaboratif de gestion des connaissances pour Produire, Echanger, Pratiquer, S'informer sur les systèmes de culture durables. *Innovations Agronomiques*, **43**, 83-94

* Rabardel, P. & Béguin, P. (2005). Instrument mediated activity: from subject development to anthropocentric design. *Theoretical Issues in Ergonomics Science*, **6**(5), 429–461.

* Reau, R., Monnot, L.-A., Schaub, A., Munier-Jolain, N., Pambou, I., Bockstaller, C., Cariolle, M., Chabert, A., & Dumans, P. (2012). Les ateliers de conception de systèmes de culture pour construire, évaluer et identifier des prototypes prometteurs. *Innovations Agronomiques*, **20**, 5–33.

* Toffolini, Q., Jeuffroy, M.H., & Prost, L. (2015). The need for agronomic indicators to monitor and assess action and to enhance learning loops during cropping systems redesign process. 5th International symposium for Farming System Design, Montpellier, France

* Vereijken, P. (1997). A methodical way of prototyping integrated and ecological arable farming systems (I/EAFS) in interaction with pilot farms. *Developments in Crop Science*, **25**, 293–308
Bridging the gaps between ecological principles and actions for designing
biodiversity-based agriculture

Duru M *±¹*, Benoît M ⁷, Bergez JE ¹, Jeuffroy MH ², Justes E ¹, Martin G ¹, Martin-Clouaire R ³,
Meynard JM ⁴, Ozier-Lafontaine H ⁵, Prost L ⁸, Rapidel B ⁶, Toffolini Q ²,⁸, Sarthou JP ¹, Therond O ¹

1 INRA UMR 1248 F-31326 Castanet Tolasan

2 INRA UMR 211 F-78850 Thiverval-Grignon

3 INRA UR 875 F-31326 CastanetTolasan

4 INRA UMR 1048 AgroParistech 16 rue C Bernard F-785231 Paris Cedex 05

5 INRA UR 1321 F-97170 Petit-Bourg Guadeloupe

6 CIRAD UMR System 2 place Viala F-34060 Montpellier

7 INRA UR 055 Aster F-88500 Mirecourt

8 INRA UMR 1326, F-77454 Marne-la-Vallée

* Speaker

± Corresponding author: mduru@toulouse.inra.fr

**1 Introduction**

In developed countries, a production-oriented agriculture was intensively promoted after World War II. It is based on the use of “off-the-shelf” technologies (synthetic inputs, fossil energy, genetics...) that limit, as much as possible, the effect of reducing production factors and level the heterogeneity of the environment. This model led to a standardisation of production methods and to a specialisation of territories according to their suitability for specific land uses. In the 1980s, the negative effects of this production system on biodiversity, ecosystems, global changes, and human health started to emerge. Moreover the increasing scarcity of fossil resources, healthy soils and water started to be a society concern. Objectification of the negative impacts of agriculture and redefinition of the objectives of agriculture in agricultural policies have led to two forms of ecological modernisation of agriculture (Horlings and Marsden, 2011). One, in continuity with the production-oriented agriculture aims at increasing the resource-use efficiency. It does not fundamentally renew the features of scientific knowledge production mode. The second, departing from the production-oriented model, aims at developing biodiversity to produce ecosystem services (ES) that support production and regulate flows. Provision of these ES requires managing biodiversity at field, farm and landscape levels (Kremen et al., 2012). We focus on issues related to the implementation of biologically diversified farming systems and landscapes.

**2 Foundations and issues of a biodiversity-based agriculture**

Increasing biodiversity in space and time is expected to provide ES to agriculture (eg. soil fertility conservation, biological control of pests) and to society at local (eg. water regulation) or global scales (eg. climate regulation). ES to agriculture are of particular importance because they offer opportunities to farmers to strongly reduce use of synthetic inputs. Several authors (e.g. Altieri, 1999) agree about three prime-order agroecological principles for designing agricultural practices that favor these ES: (i) increasing plant diversity and soil cover through adapted crop sequences (cover-crops, varieties or species mixtures)to decrease nutrient and radiation losses and increasing above and underground biomass production and rhizosphere deposition to, in turn, increase biological, physical and chemical soil fertility, and biological regulations; (ii) minimizing mechanical and chemical disturbances of soil functioning and, whenever possible, seeding or planting directly into untilled soil to increase soil organic matter to support development of soil micro-, meso- and macrofauna for promoting soil fertility, biological regulation, and hence improve soil structure; (iii) organizing the landscape matrix (spatial crop distribution, grass trip, hedgerow, other semi-natural habitats...) to increase biological regulations favoring natural pest control and pollination.

However, implementing agricultural systems based on these principles remains difficult because locally-relevant knowledge on relationships between management practice, biodiversity, and ES is still incomplete, especially when ES depend on associated biodiversity (eg. micro-, meso- and macro fauna: Bommarco et al., 2013). Therefore, promoting biodiversified farming systems and landscapes requires site-specific transformational changes. Management practices for enhancing ES need to be adaptive and flexible. Farmers practicing biodiversified agriculture usually proceed by trial-and-error process, sharing their experience with their peers to facilitate and accelerate learning and in turn limit risk. This is akin to what is called “adaptive management” in science, i.e. iteration of design and implementation of actions, monitoring of their effects, learning about agroecosystem functioning (William 2011). This leads researchers to produce methods and tools that are: (i) flexible enough to take local specificities into account and to integrate both emergent scientific and local knowledge, (ii) integrative, to reproduce with adequate accuracy the emerging properties of complex assemblages of species and practices, (iii) learning-oriented to promote the development of local knowledge, and (iv)a means to cope with uncertainty within an adaptive management scheme.
## 3 Building learning-oriented support tools to link principles and actions

To reach these above objectives, and from our diverse experiences, we argue that the development of learning-oriented tools should be collegiate (i.e. involving scientists, extensionists, farmers and other stakeholders), to stimulate knowledge exchanges. Because the main objective is to design a consistent foundation of the complex agroecosystem to implement and manage, user-friendliness and accuracy of predicted effects of management practices are also important characteristics. To support the key steps of the adaptive management they have to be useful both to design farming systems and to assess the ecosystem benefits that they bring.

Researchers, farmers and agricultural advisors are not well-equipped to deal with design of complex adaptive systems and assessment of their dynamics. Few mechanistic models dealing with agroecosystems address relations between management, biodiversity and ES. Most existing models focus on representations of the plant-soil-atmosphere system with mechanistic modeling of abiotic resources interactions and effects on plant production (energy, water, N, C). Given the expected features of learning tools, we identify three main types of emergent support tools likely to be helpful to lead the transition toward biodiversity-based agriculture: (i) knowledge bases, (ii) model-based, (iii) farm- landscape indicators usable by farmers and allowing them to think about past effects and predicting effects of future actions:

i. Knowledge bases contain structured scientific facts and empirical information compiled from cumulative experiences that enable biodiversity management to be inferred in specific situations. They have been developed recently, for example, to help selecting cover-crop species by providing information about suitable production situations (main cropping system, climate, soil) and expected ecosystem services. Some are built from plant-trait- based functional profiles (Ozier-Lafontaine et al. 2011), while others rely on expert knowledge about plant features (e.g. Naudin et al. 2011). A challenge would be to allow consolidate these knowledge bases with practitioner's feedbacks.

ii. Model-based games allow designing potentially adapted farming systems and even landscape organizations through stimulation of knowledge exchange and learning about the effects of planned and associated biodiversity on ecosystem services. They can be used to perform iterative design and *ex-ante* assessment of spatiotemporal distributions of crops, livestock and semi-natural habitats potentially promoting input services. These participatory- design approaches are based on manipulating “boundary objects” such as board games, cards, geographic or cognitive maps and computer models to create a shared language among the actors involved (e.g. farmers, advisors, students, scientists, other stakeholders). Materials and computer items are used either simultaneously or successively to collectively design and assess alternative farming systems (Martin *et al.* 2011) or landscapes.

iii. Finally field-farm-landscape indicators are necessary to reveal aspects of agroecosystems that provide ecosystem services to be estimated. Such aspects first include the soil state, for which several indicators already exist and are used. However, indicators of the balance between noxious, beneficial and neutral soil organisms, hence of the real or potential natural pest control of soil, have to be made available, in a simplified form, to farmers. Surprisingly little is known about the status of farmland biodiversity and how it changes under different farming practices. A new toolbox, called the “BioBio indicator set” (Herzog et al 2013), has recently been developed for a variety of farm types and scales in Europe. It is the fruit of a close collaboration between scientists, environmentalists and farmers, which imparts saliency to the toolbox.

## 4 Prospects for a research agenda

The development of learning tools to support biodiversity-based agriculture is still in its infancy. To develop tools in the line with an adaptive management frame, we propose to combine several scientific disciplines: (i) advances in ecological science for characterizing, first, planned and associated-biodiversity responses to locally controllable or exogenous drivers, and, second, effects of biodiversity on ecosystem services, (ii) advances in management and design sciences for designing methods facilitating the collaboration between stakeholders involved in biodiversity-based agriculture and farmers, and the evaluation of these collaborations, and (iii) agricultural and social sciences for building learning-support tools taking into account their use.

## References

* Altieri, M. (1999). The ecological role of biodiversity in agroecosystems. *Agriculture Ecosystem and Environment, 74*, 19-31.

* Bommarco, R., D. Kleijn, Potts S.G. (2013). "Ecological intensification: harnessing ecosystem services for food security." *Trends in Ecology and Evolution* **28**, 230-238.

* Herzog, F., *et al*. (2013). Measuring farmland biodiversity. *Solutions, 4*, 52-58.

* Horlings, LG. & Marsden, TK. (2011). Towards the real green revolution? Exploring the conceptual dimensions of a new ecological modernization of agriculture that could “feed the world”. *Global Environmental change, 21*, 441-452.

* Kremen, C., Iles, A. & Bacon, C. (2012). Diversified farmings: an agroecological, systems-based. *Ecology and Society, 17*(4), 44.

* Martin, G., Felten, B. &Duru, M. (2011). Forage rummy : A game to support the participatory design of adapted livestock systems. *Environmental Modelling and Software, 26*, 1442-1453.

* Naudin, K., Scopel, E., Husson, O., Auzoux, S., Penot, E. &Giller. KE.(2011). Prototyping rotation and association with cover crop and no till (5th World Congress of Conservation Agriculture)

* Ozier-Lafontaine, H., Publicol, M., Blazy, J.M.&Melfort, C. (2011). SIMSERV: Expert system of assistance to the selection of plants of service for various agro-ecological and socio-economic contexts. LicenceCeCILL (http://www.cecill.info/index.en.html).

* Williams, BK. (2011). Adaptive management of natural resources-framework and issues. *Journal of Environmental Management, 92*, 1336-1353.
# Exploration of windows of opportunity for improved nutrition, productivity and resource management at the landscape level

Jeroen C.J. Groot *±1, Fabrice Declerck 2, Roseline Remans 3, Natalia Estrada Carmona 2, Stephanie Alvarez 1, Nester Mashingaidze 1,4, Celine Termote 2, Ray-Yu Yang 5, Jessica Raneri 2 & Gina Kennedy 2

## 1 Introduction

The Nutrition-Sensitive Landscapes (NSL) approach focuses on building diversity into the landscape and food systems to provide multiple sources of nutrients as well as other ecosystem services that are critical for environmental and population resilience. The NSL method offers proactive management towards more sustainable diets for vulnerable populations. We aim to explore tradeoffs and synergies between nutrition security, agricultural production, market interactions and natural resource management. It entails multi-disciplinary analyses of how women's and men's choices in land and farm management and in food acquisition and consumption patterns affect the food system, nutrition adequacy and ecosystem services. Systems analysis is one of the pillars in the NSL approach. It applies experiential learning cycles in case study sites in Zambia, Kenya and Vietnam.

## 2 Materials and Methods

Central to the methodology is a gendered participatory approach in all phases of the learning cycle. Results obtained with and for women and men in the study communities include descriptions of use of terrestrial and aquatic resources and of place and time-determined food consumption and farming practices. Case studies are undertaken in Vihiga County (Kenya), Son La province (Vietnam) and the Barotse Floodplain (Zambia) to assess the interactions and interconnectivity in agricultural production, natural resource management (NRM) and nutrition diversity. In each country, two small landscapes were selected for a participatory inventory of diet diversity and sufficiency in relation to farm productivity, exchanges with markets, ecological functions, and the availability of food resources in the landscape. The case study landscapes are contrasting in natural resource availability, farming practices and/or dominant market orientation (subsistence or commercial). The current diet and nutrition, resource endowment, productivity and NRM are characterized and evaluated through surveys and stakeholder sessions.

<figure><img src="image_10.png" /><figcaption>**Fig. 1.** Exploration of solution spaces delineated by the solid line (i.e. tradeoff), using different techniques.</figcaption></figure>

<footnote n="1">¹ Farming Systems Ecology Group, Wageningen University, Netherlands</footnote>

<footnote n="2">² Bioversity International, Rome, Italy</footnote>

<footnote n="3">³ The earth Institute, Columbia University, New York, USA.</footnote>

<footnote n="4">⁴ IITA, Bujumbura, Burundi</footnote>

<footnote n="5">⁵ World Vegetable Centre, Tainan, Taiwan</footnote>

<footnote>* Speaker</footnote>

<footnote>‡ Corresponding author: jeroen.groot@wur.nl</footnote>
## 3 Results – Discussion

In addition to the participatory assessment of the multifunctional food systems, in these sites we describe and explain current systems, and we systematically explore windows of opportunity for sustainable redesign and innovation in landscape and farm systems for improved nutrition. Instead of identifying an arbitrary set of possible scenarios (Fig. 1a) or applying single or constrained or weighted optimization (Figs. 1b-e), we explore the whole spaces of solutions (Fig. 1f) (Groot *et al.*, 2009). Solution spaces show a larger and broader set of alternative agro-ecosystem configurations that differ in performance of selected indicators, and thereby allow exploring and visualizing the windows of opportunities, and trade-offs and synergies.

The potential of new options for land-use and diet composition will be explored using the spatially explicit multi-objective optimization models (Fig. 2), linking farm level bio-economic models (Groot *et al.* 2012) with landscape models (Groot *et al.*, 2007). Indicators relevant to evaluate the dietary diversity (Kennedy *et al.* 2010), food patterns and nutrient adequacy at the individual and household level are added to the bio-economic models. Moreover, the diversity of foods available on-farm and in the surrounding landscape is quantified through the nutritional functional diversity indicator (Remans *et al.*, 2011). These nutrition-related indicators can be analyzed in relation to socio-economic indicators like profitability, household budgets and labor use, and environmental indicators such as habitat connectivity, land-use diversity, nutrient losses and soil organic matter accumulation.

<figure><img src="image_11.png" /><figcaption>**Fig. 2.** Exploration with models following the Describe, Explain, Explore and Design phases of the DEED cycle.</figcaption></figure>

## 4 Conclusions

The combination on-farm trials, surveys, modeling analyses and participatory evaluations drive the learning cycle from which innovations can emerge. This integrated approach and visualization of windows of opportunities through solution spaces will effectively inform discussions with stakeholders in the planning process of possible interventions to increase diet diversity, agricultural productivity and NRM in project action sites.

*Acknowledgements.* This research is funded by the CGIAR Research Programs of Humidtopics, Agriculture for Nutrition and Health (A4NH), and Aquatic Agricultural Systems (AAS).

## References

* Groot, J.C.J., Oomen, G.J.M., & Rossing, W.A.H. (2012). Multi-objective optimization and design of farming systems. *Agricultural Systems, 110*, 63–77.

* Groot, J.C.J., Rossing, W.A.H., Jellema, A., Stobbelaar, D.J., Renting, H., & Van Ittersum, M.K. (2007). Exploring multi-scale trade-offs between nature conservation, agricultural profits and landscape quality – A methodology to support discussions on land-use perspectives. *Agriculture, Ecosystems & Environment, 120*, 58–69.

* Groot, J.C.J., Rossing, W.A.H., Tichit, M., Turpin, N., Jellema, A., Baudry, J., Verburg, P.H., Doyen, L. & van de Ven, G. W. J. (2009). On the contribution of modelling to multifunctional agriculture: learning from comparisons. *Journal of Environmental Management, 90*, S147–60.

* Kennedy, G, Ballard T. & Dop, M.C. (2013). Guidelines for measuring household and individual dietary diversity. Nutrition and Consumer Protection Division, Food and Agriculture Organization of the United Nations, Rome, Italy, 53 pp.

* Remans, R., Flynn, D.F.B., DeClerck, F., Diru, W., Fanzo, J., Gaynor, K., Lambrecht, I., Mudiope, J., Mutuo, P.K., Nkhoma, P., Siriri, D., Sullivan, C., & Palm, C.A. (2011). Assessing nutritional diversity of cropping systems in African villages. *PloS One, 6*, e21235.
# Impact of farming systems on agricultural landscapes and biodiversity: from plot to farm and landscape.

Gilles Martel *±<fnref n="1" />, Stéphanie Aviron <fnref n="1" />, Hugues Boussard <fnref n="1" />, Alexandre Joannon <fnref n="1" />, Bénédicte Roche <fnref n="1" />

## 1 Introduction

Green-way policies in agricultural landscapes focus on ecological continuities between semi-natural elements (hedgerows, permanent grasslands, woods). These policies assume that annual crops and temporary grasslands have a negative or neutral impact on biodiversity. However, some works have shown that the presence of annual crops with dense cover and spatial continuities between different crops could also have a positive impact on biodiversity, either on woody species (see e.g. Ouin et al. 2000) or on crop species (see e.g. Burel et al. 2013). These landscape patterns are directly linked to farmers' decisions about the choice of crops they cultivate and their allocation on the farm fields. These decisions are related to fields characteristics and crop management requirements. In livestock farms, these decisions are also linked to animal management, particularly the way they are fed and the way fodder is produced (on-farm or bought) (Garcia et al., 2005). The aim of this study was to evaluate the impact of contrasted livestock farming systems management on landscape patterns related to cultivated covers and potential biodiversity, here carabid beetles in bocage landscapes in Brittany, France. We achieved this goal through a multi-level modelling framework in order to combine field, farm and landscape level analysis.

## 2 Materials and Methods

We developed a methodology combining farmers' decision making analysis, ecological observations and modelling. Modelling has been done at the field, farm and landscape levels. We applied our methodology to a case study in Brittany, France. We compared two livestock systems, swine and dairy, in one bocage landscape (circle of 1 km diameter) which fields were farmed by 8 farms. A farm decision-based model was first built from farmers' interviews to simulate cropping patterns at the field and farm levels. Land-use patterns were then simulated at the landscape level by aggregating predicted cropping patterns of the 8 farms. Ecological statistical models were built from empirical data on carabid beetles, to predict carabid abundances at the field level in (i) annual crops and (ii) semi-natural (woody) elements in simulated landscapes. Each farm were either simulated as a dairy or a swine farm, leading to a total of 256 landscape scenarios, each repeated 250 times, one scenario corresponding to 10 years of rotation. We used APIland library dedicated to landscape modelling (Boussard et al., 2010).

## 3 Results and Discussion

From an ecological point of view we predicted that carabid species of annual crops were more abundant in swine production landscapes due to increased spatial continuities (edge length) between maize and winter cereals, whereas abundances of species of woody elements were enhanced in mixed landscapes (dairy and swine) because of higher land-use diversity (Fig. 1).

<figure><img src="image_12.png" /><figcaption>**Fig. 1.** Predicted abundances of (a) carabid species of annual crops and (b) species of woody according to the number of farms in dairy vs. swine production systems.</figcaption></figure>

<footnote n="1">¹ INRA UR0980 SAD-Paysage, 35042 RENNES Cedex, France</footnote>

<footnote>* Speaker</footnote>

<footnote>± Corresponding author: gilles.martel@rennes.inra.fr</footnote>
On table 1 we can observe that there is a relation between farms' farming system and crop areas within the simulated landscape. This is particularly true for wheat and grassland, while maize area is relatively less variable. As a result we can see a significant relation between farms' farming systems and spatial continuities between maize and winter cereals. A second result is that the intra-scenario variability is rather high (S.D. between 4.4 and 8.7 ha except for grassland in the swine scenario; from 288 to 466 meters of spatial continuities), which points out some flexibility to manage landscape to promote crop acreage and spatial continuities that would enhance carabid abundances.

<table><caption>**Table 1.** Mean and S.D. of land-uses areas and spatial continuities (edge length) between winter cereals and maize for 3 contrasted scenarios out of the 256 simulated (2500 landscapes per scenario: 10 years and 250 repetitions).</caption><thead><tr><th rowspan="2">Scenarios</th><th colspan="2">Wheat (ha)</th><th colspan="2">Maize (ha)</th><th colspan="2">Grassland (ha)</th><th colspan="2">Spatial continuities (m)</th></tr><tr><th>Mean</th><th>S.D.</th><th>Mean</th><th>S.D.</th><th>Mean</th><th>S.D.</th><th>Mean</th><th>S.D.</th></tr></thead><tbody><tr><td>Swine only</td><td>27.6</td><td>8.7</td><td>16.8</td><td>7.2</td><td>0.4</td><td>0</td><td>2246</td><td>466</td></tr><tr><td>Mixed</td><td>14.9</td><td>5.9</td><td>15.1</td><td>6.7</td><td>27.9</td><td>5.1</td><td>1095</td><td>433</td></tr><tr><td>Dairy only</td><td>5.8</td><td>4.4</td><td>21.6</td><td>6.8</td><td>37.4</td><td>6.2</td><td>339</td><td>288</td></tr></tbody></table>

Relative contribution of each farm to carabid beetles abundances was then calculated (Table 2). It corresponds to the increase in the mean number of carabid beetles predicted when converting a farm from dairy to swine farming system. Farm size is the main factor explaining this contribution (see farms 1,2 and 4). But, it is not a general rule, since farm 2 and 9 contributions are respectively higher than the ones of farm 4 and 8. Potential grassland area in the landscape, related to the position of milking facilities (within, close or far from the landscape), and the edge length between fields are two other factors to consider. Indeed, they favor the increase of spatial continuities between maize and winter cereals when shifting from dairy to swine farming systems.

<table><caption>**Table 2.** Farm relative contribution (case of annual crops carabid beetles)</caption><thead><tr><th rowspan="2"></th><th colspan="4">Areas and edges length calculated for each farm</th><th rowspan="2">Relative contribution</th></tr><tr><th>Arable land (ha)</th><th>Edges (m)</th><th>Min grassland area (ha)</th><th>Max grassland area (ha)</th></tr></thead><tbody><tr><td>F2</td><td>16.6</td><td>2 544</td><td>1.9</td><td>16.6</td><td>230.1</td></tr><tr><td>F4</td><td>20.5</td><td>2 829</td><td>0.0</td><td>20.5</td><td>122.9</td></tr><tr><td>F1</td><td>14.3</td><td>1 484</td><td>0.0</td><td>14.2</td><td>72.7</td></tr><tr><td>F9</td><td>4.7</td><td>1115</td><td>0.0</td><td>4.7</td><td>42.2</td></tr><tr><td>F6</td><td>2.5</td><td>345</td><td>0.0</td><td>2.5</td><td>16.4</td></tr><tr><td>F3</td><td>1.2</td><td>222</td><td>0.0</td><td>1.2</td><td>16.2</td></tr><tr><td>F7</td><td>3.2</td><td>1177</td><td>0.0</td><td>3.2</td><td>14.1</td></tr><tr><td>F8</td><td>7.3</td><td>713</td><td>0.0</td><td>0.0</td><td>0.1</td></tr></tbody></table>

## 4 Conclusion

Our multi-level and agro-ecological modeling framework allowed to evaluate the impact of different farming systems (dairy and swine) on landscapes patterns and abundances of carabid beetles. We showed that over-representation of swine farming system leads to increased edge length between maize and winter cereals and so favoring crop carabid beetles. On the contrary, a diversity of farming systems seems to be required in order to favor woody carabid beetles. Moreover we showed that for a given set of farming systems in a landscape there was a variability of crop patterns and edge length between cultivated covers. This indicates that there are some rooms to maneuver crop allocation to fields in agricultural landscapes. But these rooms for maneuver have to be thought at a collective level since they result from several farmers decisions, some farms having a higher contribution to the landscape pattern and resulting biodiversity.

*Acknowledgements.* This work has been funded by the French Ministry of Ecology (DIVA-Agriconnect project), INRA Payote research group and Zone Atelier Armorique (supported by CNRS and INRA)

## References

Boussard, H.; Martel, G.; Vasseur, C. 2010. Spatial links specifications in the APILand simulation approach: an application to the coupling of a farm model and a carabid population model, Montpellier 2010, LandMod2010

Burel, F., Aviron, S., Baudry, J., Le Feon, V., & Vasseur, C. (2013). The structure and dynamics of agricultural landscapes as drivers of biodiversity. Pp. 285-308 in: Fu, B. & Jones, B., "Landscape ecology for sustainable environment and culture", Elsevier.

Garcia F. et al. (2005) Tournesol : un modèle pour simuler les asselements en exploitation bovine laitière, Rencontres Recherche Ruminants. pp. 195-198.

Ouin, A., Paillat, G., Butet, A. & Burel, F. (2000) Spatial dynamics of wood mouse (Apodemus sylvaticus) in an agricultural landscape under intensive use in the mont saint michel bay (france). *Agriculture, Ecosystems & Environment*, **78**, 159-165.
# Policies and institutions fostering sustainable agricultural systems

Erik Mathijs *±1, Alfons Balmann 2 & Isabelle Bonjean 3*

## 1 Introduction

The aim of this paper is to investigate how policies and institutions do or do not foster sustainable agricultural systems. First, the paper reviews how policy—in interaction with institutions, including supply chain practices—affects farm structures and their sustainability. Second, an overview is given of how policy has influenced farm structures over time and across various geographies. Third, the paper derives which policy mix would be required to generate sustainable agricultural systems and evaluates to which extent current policies worldwide are or are not evolving towards such a policy mix.

## 2 Theoretical perspectives on the interaction between policies, institutions and sustainable agricultural systems

Economic theory posits that farm structures result from farmers' choices concerning specialisation, technology and scale, which in turn are affected by the relative prices of farm inputs and outputs. Under perfect institutional and political settings, farms reach their optimal scale and factors of production are paid their opportunity costs (Kislev & Peterson, 1983), while at the same time environmental externalities are internalised into input and output prices, thus resulting in sustainable agricultural systems. In addition, farmers' decisions are influenced by a variety of constraints related to availability of production technologies, the biophysical environment, input and output markets, credit and insurance markets and knowledge (Stoorvogel et al., 2004), the farmers' resources and abilities. Finally, institutions—including policies—can affect this economic rationale in multiple ways.

Scott (1994: 68) defines institutions as “…symbolic and behavioural systems containing representational, constitutive, and normative rules together with regulatory mechanisms that define a common meaning system and give rise to distinctive actors and action routines.” Policies and regulations may provide financial incentives or disincentives and may set limitations, thus influencing farmers’ relative prices and thus choices. Policies may influence trade, property right regimes, farmer decisions about to what and how much grow, the relative cost of land through regulations, taxes and subsidies, or standards. Furthermore, non-agricultural policies may affect agricultural systems, such as labour law, fiscal regimes and environmental standards (Bowman & Zilberman, 2013). Such policy is partly desirable, as without it environmental externalities would not be internalised by markets, but may partly also distort farmers’ choices. In turn, public policy cannot be seen without consideration of supply chain practices, that reflect output demand and input supply conditions, and of credit and risk considerations, that greatly influence farmers’ choice set for instance through standards.

But institutions also refer to meaning systems—as proposed by Scott (1994)—an important part of which are mental models and social structure. While there is a rich literature on the adoption of environmentally friendly practices in agriculture pointing to influence of farmers’ personal characteristics, attitude, social norms, etc., this literature does not show a universal pattern, such that efforts to promote sustainable agricultural systems need to be tailor made for local conditions (Knowler & Bradshaw, 2007; Wauters & Mathijs, 2014). Furthermore, transforming agricultural systems towards sustainability entails changing mental models, which proofs to be particularly difficult. As a result, farm development trajectories are often locked-in, that is, strongly dependent on historical events as demonstrated by for instance Happe *et al.* (2008).

## 3 A global overview of policies and institutions influencing sustainable agricultural systems

How have policies and institutions influenced the sustainability of agricultural systems over time and across geographies? For this, three clusters of countries are considered, depending on their level of development. Typically, countries tend to increase the protection of their agriculture as they develop economically (Thompson, 1998).

First, low-income countries typically do not support agricultural development through policy, as they lack the financial means to do so. Often, agricultural exports are even taxed to raise revenues. Food security is the major concern, while concern for the environment is absent. As a result, natural capital tends to be overexploited, leading to land degradation, particularly in population dense areas, where the incentive to intensify production is very high. The demand for organic produce is rising leading to increasing market incentives for sustainability as mediated by some multinational retailers and food processors.

<footnote n="1">¹ Bioeconomics Division, Department of Earth and Environmental Sciences, University of Leuven</footnote>

<footnote n="2">² Leibniz Institute of Agricultural Development in Transition Economies (IAMO)</footnote>

<footnote n="3">³ Bioeconomics Division, Department of Earth and Environmental Sciences, University of Leuven</footnote>

<footnote>* Speaker</footnote>

<footnote>‡ Corresponding author: erik.mathijs@kuleuven.be</footnote>
Second, in emerging economies—such as Brazil, Russia, India and China—economic growth is the dominant paradigm using export-led strategies. Concern for the environment is still limited and mainly market driven if at all present. Agricultural systems tend to modernize as labour costs increase due to increasing non-agricultural incomes resulting in a substitution of labour by capital and increasing farm size increases. Partly, the situation is similar to that in Europe and the USA after the Second World War. Partly, global trends such as increasingly integrated supply chains accelerate modernisation

Third, high-income countries are typically characterised by policies setting various limitations to agriculture on the one hand, but also by providing a relatively large amount of financial support. In addition, demand for products produced in a sustainable way increases, leading to both public and private incentives for agricultural systems to become greener. An important barrier is path dependences resulting from existing institutional settings, sunk costs, know-how and mental models. Particularly in areas with high population density, the intensity of agricultural systems may be too high leading to high land prices making it very costly to extensify.

## 4 Designing policies for sustainability

What policy mix leads to sustainable agricultural systems? As indicated before, no universal answer is possible, as local conditions may vary too much across sectors and regions. We formulate three sets of principles we deem important for policies to truly lead to sustainable agricultural systems:

1. *Set the right targets and framework.* Any good policy starts from formulating and communicating a clear, normative objective. Setting the right targets and translating them into standards is therefore the first key step towards creating sustainable agricultural systems. Targets will not only guide policy, but also private investment in clean technologies, thus leading to a competitive advantage when markets start asking for sustainable products (Porter & van der Linde, 1995).

2. *Develop knowledge, institutions and infrastructure.* Changing practice requires developing new knowledge, while changing structures requires investing in new infrastructure. Failure to do so, will result in lock-in, that is, efforts towards making systems more sustainable will be focused on making current systems more resource efficient, rather than designing new systems (Freibauer et al., 2011). As institutions lay the foundation for knowledge and structures, institutional change should accompany policy for sustainability. Institutional change involves changing the mind-set of anyone involved in the agricultural knowledge and innovation system.

3. *Provide the right financial incentives and regulations.* Markets are generally not capable of correcting the environmental externalities generated by firms, due to high transaction costs, the non-point nature of pollution, etc. Regulation is thus necessary. However, setting financial incentives such as environmental taxes at the right level requires correct information, but also coherence in policies—for instance farmers should not face contradictory public policies related to their practices and choices (Mathijs et al., 2015).

## References

* Bowman, M.S. & Zilberman, D. (2013). Economic factors affecting diversified farming systems. *Ecology and Society*, **18**, 33.

* Freibauer, A., Mathijs, E., Brunori, G., Damianova, Z., Faroult, E., Girona i Gomis, J., O'Brien, L. & Treyer, S. (2011). Sustainable food consumption and production in a resource-constrained world. 3rd SCAR Foresight Exercise. Publications Office of the European Union, Luxembourg.

* Happe, K., Balmann, A., Kellermann, K. & Sahrbacher, C. (2008). Does structure matter? The impact of switching the agricultural policy regime on farm structures. *Journal of Economic Behavior & Organization*, **67**, 431-444.

* Kislev, Y. & Peterson, W. (1983). Prices, technology, and farm size. *Journal of Political Economy*, **90**, 578-595.

* Knowler, D. & Bradshaw, B. (2007). Farmer's adoption of conservation agriculture: A review and synthesis of recent research. *Food Policy*, **32**, 25-48.

* Mathijs, E., Brunori, G., Carus, M., Griffon, M. & Last, L. (2015). Sustainable agriculture, forestry and fisheries in the bioeconomy – A challenge for Europe. 4th SCAR Foresight Exercise. Publications Office of the European Union, Luxembourg.

* Porter, M. & van der Linde, C. (1995). Toward a new conception of the environment-competitiveness relationship. *Journal of Economic Perspectives*, **9**, 97-118.

* Scott, R.W. (1994). Institutions and organizations. Toward a theoretical synthesis. In: Scott, R.W., Meyer, J.W. and Associates. Institutional environments and organizations. Structural complexity and individualism. Sage Publications, London, 55-80.

* Stoorvogel, J.J., Antle, J.M., Crissman, C.C. & Bowen, W. (2004). The tradeoff analysis model: integrated bio-physical and economic modeling of agricultural production systems. *Agricultural Systems*, **80**, 43-66.

* Thompson, R.L. (1998). Public policy for sustainable agriculture and rural equity. *Food Policy*, **23**, 1-7.

* Wauters, E. & Mathijs, E. (2014). The adoption of farm level soil conservation practices in developed countries: a meta-analytic review. *International Journal of Agricultural Resources, Governance and Ecology*, **10**, 78-102.
# T1. Assessing performances and services of cropping systems (field level experiments, surveys and databases)

Chair: David Parson, University of Tasmania

Co-chair: Eric Malézieux, CIRAD
# Improving resource use efficiency and soil conservation in smallholder vegetable systems though improved soil tillage and residue management

Florencia Alliaume *±1,2*, Walter A.H. Rossing 2, Pablo Tittonell 2 & Santiago Dogliotti 3

## 1 Introduction

Smallholder vegetable farmers tend to specialize and intensify their production systems to secure income. In south Uruguay, frequent tillage and little or no inputs of organic matter have resulted in soil degradation that has decreased soil productivity and threatens systems sustainability (Alliaume et al., 2013). The development of production systems that are able to stop soil deterioration and even improve soil quality is key to the sustainability of vegetable production systems in this region. In a context where water availability limits irrigation, and spatial and temporal variability of rainfall is increasing, it is imperative to introduce practices that reduce runoff and erosion, and increase the capture of rainfall water in the soil. Reduced tillage in combination with mulching maybe a viable alternative to reduce runoff, soil degradation and erosion, and improve water conservation (Alliaume et al., 2014). Our aim was to develop a tool that illustrates the effect of adopting different soil management practices in terms of water balance and erosion at a farm scale.

## 2 Materials and Methods

A three year on-station experiment was carried out to analyse the effect of reduced tillage, cover crops and organic matter addition on water runoff, soil erosion, soil moisture supply capacity on tomato, maize and onion crops. Treatments were: reduced tillage +oat as a cover crop left as mulch + chicken manure (RT), and three conventional tillage treatments: one that incorporates chicken manure (CChm), one with a cover crop incorporated to the soil and a third one as control, with no organic material addition. The rotation involved tomato -oat/fallow - tomato - oat/fallow - tomato- oat/fallow- sweet corn - oat/fallow - onion. The results showed that RT contributed to in situ moisture conservation and reduction of runoff and soil loss on degraded mollisols used for horticulture. Based on the results of this experiment we developed a summary model with a generic approach that needs local parameterization to estimate water infiltration and water balance under vegetable cropping as a function of rainfall, residue and crop cover, and soil water content. We also measured all the variables needed by Revised Universal Soil Loss Equation (RUSLE) model and incorporate a routine to estimate soil erosion.

## 3 Discussion

The soil moisture during the four commercial crops was both measured and estimated to be larger under RT than under CChm at all soil depths. The model developed requires few inputs and was sensitive to differences in soil cover, reproducing moments in which the soil was wetter and drier, although in several moments, there was an overestimation of the soil moisture (Fig. 1). The water infiltration however was accurately estimated (data not shown).

<figure><img src="image_13.png" /><figcaption>Fig. 1. Simulated and measured soil moisture from 0 to 100cm depth, during two tomato, maize and onion crops.</figcaption></figure>

<footnote n="1">¹ Departamento de Suelos y Aguas, Facultad de Agronomía, Universidad de la República</footnote>

<footnote n="2">² Farming Systems Ecology, Plant Science, Wageningen University</footnote>

<footnote n="3">³ Departamento de Producción Vegetal, Facultad de Agronomía, Universidad de la República</footnote>

<footnote>* Speaker</footnote>

<footnote>± Corresponding author: florenal@fagro.edu.uy</footnote>
The larger soil water capture under RT was explained by a larger infiltration into the soil, except during the first tomato crop because it was a very dry season and the interception by the mulch resulted in less water infiltrated; and by reduced soil evaporation (Table 1.). The change in water dynamics have at least two direct positive consequences: reduced runoff led to reduced erosion risk, and larger water availability for transpiration may result in larger yields. Larger soil water capture under RT, might result in larger deep drainage, especially during a winter-spring crop such as onion (Table 1).

<table><caption>**Table 1.** Water balance components estimated for two soils management during four commercial crops.</caption><thead><tr><th rowspan="2">Soil management</th><th colspan="2">Tomato 2010/2011</th><th colspan="2">Tomato 2011/2012</th><th colspan="2">Sweet Corn</th><th colspan="2">Onion</th></tr><tr><th>RT</th><th>CChm</th><th>RT</th><th>CChm</th><th>RT</th><th>CChm</th><th>RT</th><th>CChm</th></tr></thead><tbody><tr><td>Rainfall (mm)</td><td colspan="2">113,7</td><td colspan="2">467,9</td><td colspan="2">346,6</td><td colspan="2">575,9</td></tr><tr><td>Runoff (mm) (% of rainfall)</td><td>4,9 (4)</td><td>13,3 (12)</td><td>42,7 (9)</td><td>107,2 (23)</td><td>75,0 (22)</td><td>113,5 (33)</td><td>115,9 (20)</td><td>191,5 (33)</td></tr><tr><td>Interception (mm)</td><td>40,9</td><td>16,5</td><td>52,3</td><td>16,5</td><td>21,6</td><td>6,3</td><td>44,4</td><td>24,3</td></tr><tr><td>Deep drainage (mm)</td><td>0,0</td><td>0,0</td><td>33,6</td><td>25,5</td><td>100,7</td><td>62,5</td><td>136,5</td><td>19,1</td></tr><tr><td>Infiltration (mm)</td><td>71,1</td><td>84,3</td><td>368,1</td><td>345,1</td><td>252,4</td><td>227,8</td><td>425,5</td><td>363,4</td></tr><tr><td>Actual evap. (mm)</td><td>50,4</td><td>72,5</td><td>105,2</td><td>155,3</td><td>35,3</td><td>55,3</td><td>45,4</td><td>68,7</td></tr><tr><td>Actual transp. (mm)</td><td>152,1</td><td>108,4</td><td>244,8</td><td>192,2</td><td>134,9</td><td>130,1</td><td>202,7</td><td>203,3</td></tr><tr><td>ETP (mm)</td><td>572,5</td><td>569,7</td><td>559,6</td><td>559,1</td><td>318,7</td><td>318,5</td><td>401,7</td><td>404,6</td></tr><tr><td>P. transp. (mm)</td><td>355,3</td><td>354,5</td><td>277,7</td><td>277,6</td><td>140,6</td><td>140,5</td><td>211,2</td><td>212,0</td></tr><tr><td>Pot. - Actual. transp. (m³)</td><td>2032</td><td>2461</td><td>329</td><td>854</td><td>57</td><td>104</td><td>85</td><td>87</td></tr></tbody></table>

The water use efficiency reported for processing tomato crop in Uruguay (Scarlato, 2009; Alvarez, 2010) ranges between 100 and 180 kg ha⁻¹ of fresh fruit per mm of irrigated water. From that data and looking at the differences in actual transpiration between soil treatments (Table 1), we can estimate an yield increment under RT between 4000 and 9000 kg ha⁻¹ compared with CChm assuming that the transpiration efficiency is the same as the irrigated water, which is a conservative assumption. In the same way, in order to fulfil the transpiration demand (P. transp) during both tomato crops we would have to irrigate between 400 and 500 m³ more under CChm than under RT (Table 1), water that in many farms is not available, or the farmer could have saved it or increased the irrigated area.

A major consequence of introducing RT is the reduction in erosion risk. As we can see in Table 2., an estimate for a LuvicPhaeozem (k=0.23), common in the south of Uruguay, resulted in soil losses below or equal to the tolerance level 7t ha⁻¹ year⁻¹ for slopes till 3% and 80 m long managed under RT, while CChm was over the tolerance level in all combinations of length and slope.

<table><caption>**Table 2.** Average annual soil loss during a three years vegetable crops rotation under two soil managements. Estimations using RUSLE for various combinations of length and degree of slope are presented.</caption><thead><tr><th rowspan="2">length (m)</th><th rowspan="2">slope (%)</th><th rowspan="2">RUSLE LS factor</th><th colspan="2">Soil loss (t ha<sup>-1</sup> year<sup>-1</sup>)</th></tr><tr><th>RT</th><th>CChm</th></tr></thead><tbody><tr><td>30</td><td>4,5</td><td>0,579</td><td>8</td><td>25</td></tr><tr><td>80</td><td>3,0</td><td>0,528</td><td>7</td><td>23</td></tr><tr><td>30</td><td>3,0</td><td>0,389</td><td>6</td><td>17</td></tr><tr><td>80</td><td>2,5</td><td>0,430</td><td>6</td><td>19</td></tr><tr><td>30</td><td>2,5</td><td>0,327</td><td>5</td><td>14</td></tr><tr><td>80</td><td>1,5</td><td>0,249</td><td>4</td><td>11</td></tr><tr><td>30</td><td>1,5</td><td>0,204</td><td>3</td><td>9</td></tr></tbody></table>

## 4 Conclusions

The model developed was sensitive to differences in soil moisture due to soil management. Even if it has to be improved, it already illustrates the effect of adopting different soil managements in terms of water balance and erosion at rotation scale. Results show significant decrease of soil erosion and water requirements for irrigation under RT, thus enabling an increase in irrigated area of vegetable crops and crop yields.

*Acknowledgements.* Without the help of Gabriella Jorge, José Pedro Dieste, colleagues at the Faculty of Agronomy, and personal at the South Center Station this research would have not be possible, so our sincere acknowledge to all of them, also toAlejandra Borges for her support on statistic analysis. This research was funded by the Sectorial Comission of Scientific Research (CSIC) and the National Agency of Research and Innovation (ANII).

## References

* Alliaume, F, Rossing W.A.H.; García, M.; Giller, K.; Doglioti, S. (2013). Changes in soil quality and plant available water capacity following systems re-design on commercial vegetable farms. European Journal of Agronomy, v.: 46, p.: 10 - 19, 2013

* Alliaume, F; Rossing, W.A.H.; Tittonell, P.; Jorge, G. & Dogliotti, S. (2014). Reduced tillage and cover crops improve water capture and reduce erosion of fine textured soils in raised bed tomato systems. Agriculture, Ecosystems and Environment, 183, 127-137.

* Alvarez, D. (2010). Efecto de la disponibilidad de agua en el crecimiento, desarrollo, rendimiento y calidad de tomate para industria. Tesis, Facutlad de Agronomía, UDELAR. 85p. Montevideo, Uruguay.

* Scarlato, M. (2009). Efecto de la disponibilidad de agua en el crecimiento, desarrollo, rendimiento y calidad de tomate para industria, cv. Loica. Tesis, Facutlad de Agronomía, UDELAR. 91p. Montevideo, Uruguay.
# IMPACT OF A LEGUME LIVING MULCH ON WINTER WHEAT YIELD AND ITS NITROGEN NUTRITION

Jérôme Labreuche *±<fnref n="1" />*, Jean-Pierre Cohan <fnref n="2" />, Edouard Baranger <fnref n="3" />, Romain Légère <fnref n="2" /> & Stéphane Jézéquel <fnref n="4" />

## 1 Introduction

A living mulch has a life cycle which can be far longer than the one of an annual cover crop. It can have a stronger impact on soil characteristics, on the environment and on commercial crops included in the rotation. A cover crop already established in the preceding crop can also have a stronger development than an annual cover crop, especially in dry summer conditions or in short intercropping periods. A living mulch can facilitate the main crop growth through for example soil structure improvement (Carof et al., 2007) or soil nitrogen availability (Bergkvist, 2003). It can also show strong competition on the main crop for light, nutrients and water. Depending on the main crop growth dynamics, the living mulch growth dynamics and the cropping system management, the balance between facilitation and competition can be completely different (Den Hollander et al., 2007).

## 2 Materials and Methods

This article presents a field trials synthesis on winter wheat established on legumes living mulch (Table 1). Wheat was harvested in 2013 and 2014 in northern France. The living mulches were mainly established in the previous crop (oilseed rape, fodder maize...). Wheat has been sown directly in the living mulch with a disc drill. The cover crops were either terminated in the wheat crop cycle or stayed alive during the entire wheat crop cycle. In the first case, living mulch were killed usually in winter with herbicides. Sometimes, wheat crop was too much competitive on cover crops, especially for light on white clover (Trifoliumrepens L.). When cover crops were not terminated in wheat crop, they were suppressed by wheat herbicides in order not to be too much competitive on wheat.

In all cases, nitrogen supply was the same between all treatments. The impact of cover crops on nitrogen absorption by wheat has been investigated in all these experiments.

<table><caption>Table 1. Description of the field experiments.</caption><thead><tr><td>Trial location<br>zip code, village (country)</td><td>Crop<br>(previous crop)</td><td>Crop harvest<br>year</td><td>Living mulch species</td><td>Sowing period / Destruction<br>period of living mulch</td></tr></thead><tbody><tr><td>91720 Boigneville (France)</td><td>Winter wheat<br>(oilseed rape)</td><td>2013</td><td>White clover (Trifoliumrepens) White clover<br>(Trifoliumrepens)</td><td>August 2011 / October 2012<br>August 2011 / March 2013</td></tr><tr><td>91720 Boigneville (France)</td><td>Winter wheat<br>(fallow)</td><td>2014</td><td>Lucerne (Medicago sativa) White clover<br>(Trifoliumrepens)<br>Common sainfoin (Onobrychisviciifolia) Black<br>medic (Medicagolupulina) Firdsfoot trefoil<br>(Lotus corniculatus)</td><td>July 2013 / March 2014<br>July 2013 / March 2014<br>July 2013 / March 2014<br>July 2013 / March 2014 July<br>2013 / No destruction</td></tr><tr><td>91720 Boigneville (France)</td><td>Winter wheat (grain<br>corn)</td><td>2014</td><td>White clover (Trifoliumrepens)</td><td>July 2013 / No destruction</td></tr><tr><td>36100 Brives (France)</td><td>Winter<br>wheat (oilseed rape)</td><td>2013</td><td>Lucerne (Medicago sativa)</td><td>July 2013 / No destruction</td></tr><tr><td>44370 La Chapelle Saint<br>Sauveur (France)</td><td>Winter wheat<br>(fodder corn)</td><td>2014</td><td>Mixture of 3 clovers : berseem, subterranean,<br>crimson (TrifoliumAlexandrinum, subterraneum<br>and incarnatum)</td><td>May 2014 / Winter 2013/2014</td></tr></tbody></table>

## 3 Results – Discussion

The impact of legume living mulch on wheat yield was variable, from -17% to +15% as compared to wheat managed as a sole crop (figure 1). In the case of living mulches that have been terminated in the wheat crop cycle, the impact on wheat yield has been on average positive. In one case, black medic showed a negative impact on wheat development at the end of winter. This cover crop did not stop growing in winter 2013/2014 that has been mild. It has not been enough suppressed by herbicides or cold weather. For other legume species terminated in the wheat crop, we had neutral to positive impact of living mulch on wheat yield. Nitrogen supply to the crop seems to explain this trend. In the experiment carried out in la Chapelle St Sauveur, the mixture of three clovers allowed an increase of 10% of wheat yield, without modifying the optimum amount of nitrogen necessary to obtain the best yield. It is

<footnote n="1">¹ ARVALIS – Institut du végétal Station expérimentale 91720 Boigneville FRANCE</footnote>

<footnote n="2">² ARVALIS – Institut du végétal La Jaillière 44370 La Chapelle Saint Sauveur FRANCE</footnote>

<footnote n="3">³ ARVALIS – Institut du végétal Domaine du Chaumoy 18570 Le Subdray FRANCE</footnote>

<footnote n="4">⁴ ARVALIS – Institut du végétal Avenue Charles Richaud 04700 Oraison FRANCE</footnote>

<footnote>* Speaker</footnote>

<footnote>± Corresponding author: j.labreuche@arvalisinstitutduvegetal.fr</footnote>
supposed that cover crops improved soil structure and helped to reduce waterlogging. In these wet conditions, in a drained loamy soil during a rainy winter, cover crops helped wheat establishment.

We had three trials in which the legumes living mulch stayed alive during the entire wheat crop cycle. Results varied depending on the situation. In the case of Boigneville2 in 2014 (figure 1), wheat was established late in autumn 2013 after a grain corn. Wheat establishment was poor (126 plants.m⁻¹). In this case, wheat has not been able to suppress white clover development because it was not enough competitive for light. Cover crop decreased wheat biomass and nitrogen status from the stem elongation and yield by 17%.

In the case of the Brives experiment, different nitrogen amount were spread on wheat drilled directly on a lucerne living mulch as compared to a control situation (soil tillage, no living mulch). The optimum yield was the same in any case but we could get it with a smaller amount of nitrogen in the living mulch. Nitrogen supply from the soil+lucerne system to wheat was improved from 30 to 60 kg N.ha⁻¹ as compared to the control.

In the last field trial with a birds foot trefoil living mulch, we got an increase of wheat yield. The cover crop biomass was of approximately 2.7t.ha⁻¹ of dry matter at wheat harvest. Birds foot trefoil dormant variety showed a small development in winter and in spring. Wheat crop was very competitive on this cover crop, except in July when wheat has become senescent. Due to rainy conditions, the cover crop produced much biomass in late July, before harvest.

<figure><img src="image_14.png" /><figcaption>**Fig. 1.** Impact of legume living mulches on wheat yield in five field trials. The cover crops were either terminated in the wheat crop cycle (biomass = 0 at wheat harvest) or stayed alive during the entire wheat crop cycle (biomass > 0).</figcaption></figure>

Cover crops were: white clover (WC), lucerne (MED), birds foot trefoil (BFT), common sainfoin (SAIN), black medic (BM), mixture of berseem, subterranean and crimson clovers (3 clovers).

## 4 Conclusions

Sowing wheat crop in a living mulch is an innovative practice that seems to improve cropping systems in some cases.

Sowing cover crops in the previous crop can allow a strong biomass production in spite of short intercropping periods.

When cover crops are terminated before sowing wheat or during winter, positive impacts on wheat such as nitrogen release or soil structure improvement could be expected in some cases without too many constraints on wheat management. As the legume living mulch stays alive during the entire wheat crop cycle, wheat management has to be adapted: crop establishment, weed control, cover crop suppression... Three factors are very important to manage facilitation / competition process: the crop competitive ability, the living mulch competitive ability and the cover crop suppression (chemically or mechanically). Some field trials are currently carried out by ARVALIS-Institut du vegetal in order to optimize this new practice and to assess their impact on crops yield, nitrogen release and the environment.

## References

* Bergkvist, G. (2003). Effect of White Clover and Nitrogen Availability on the Grain Yield of Winter Wheat in a Three-Season Intercropping System. *Acta Agriculturae Scandinavica, Section B - Soil & Plant Science* 53, 97-109.

* Carof, M., S. De Tourdonnet, Y. Coquet, V. Hallaire, et J. Roger-Estrade. (2007). Hydraulic conductivity and porosity under conventional and no-tillage and the effect of three species of cover crop in northern France. *Soil Use and Management* 23, 230-237.

* Den Hollander, N. G., L. Bastiaans, et M. J. Kropff. (2007). Clover as a cover crop for weed suppression in an intercropping design. *European Journal of Agronomy* 26, 104-112.