Farm and landscape tools at Farming Systems Ecology

Farm and landscape tools at Farming Systems Ecology Workshop on Modelling Biodiversity and Ecosystem Services, Rome, 7 & 8 May 2015 Walter Rossing & Jeroen Groot

Biocontrol, pollination, and more • • • Biocontrol Agricultural returns Soil fertility Biodiversity Nutritive values Landscape amenity Water quality Recreational value etc What is the scope for improvement in one objective before trading off with others?

Reality (agroecosystems) Adapted from Goewie (1993) and Tittonell (2013) Problems Questions Structure Analysis Function Synthesis Purpose Function Knowledge Purpose Structure Conclusions Research Decisions New facts, new realities Design

Learning cycles and the role of research Design Which? Plan: Which improvements? Explore Diversify What if? Action: Implementing a ‘bright idea’ In. DEED Analysis: What are implications? Describe: What? Observation: Find out consequences Explain: Why?

Co-innovation and Modeling Platform for Agro-eco System Simulation Landscapes COMPASS Landscape. IMAGES - Landscape. DISPLAY - Actor. IMAGES Farms Economic results Spatial coherence Technology Nutritional adoption diversity Landscape quality Nutrient losses Landscape metrics Policy efficiency Species dispersal Farm typologies Farm. IMAGES - Farm. DESIGN - Farm. STEPS - Farm. DANCES - Farm. SCALES Fields, landscape elements Nutrient balance Farming style Feed balance Human nutrition GHG emissions Labor balance Economic results Nutrient losses Bio-energy production Household budget Field. IMAGES - NDICEA - ROTAT - Rot. SOM - Rot. EROSION - Rot. YIELD Nutrient balance Organic matter Soil erosion Water balance Insect dispersal Crop yield Nutrient uptake Nutrient losses Plant diversity Seed predation

Outline § Framework for exploration of multiple objectives at multiple scales § Farm and Landscape models at Farming Systems Ecology ● Farm DESIGN ● Landscape IMAGES

Framework for exploration of multiple objectives at multiple scales Nature value Gross margin

Framework for exploration of multiple objectives at multiple scales Nature value Rank 1 Gross margin

Framework for exploration of multiple objectives at multiple scales Nature value 2 2 Gross margin

Framework for exploration of multiple objectives at multiple scales by allocating land-use activities evaluate for multiple indicators evolutionary algorithm generate rank using non-weighting Pareto-based methods Farm DESIGN Landscape IMAGES Nature value 1 2 3 3 4 4 1 2 3 2 2 1 5 Gross margin

Framework for exploration of multiple objectives at multiple scales by allocating land-use activities evaluate for multiple indicators evolutionary algorithm generate Pareto or trade-off frontier Nature value rank using non-weighting Pareto-based methods Farm DESIGN Landscape IMAGES Gross margin Pareto ranking applicable with any number of objectives

Outline § Framework for exploration of multiple objectives at multiple scales § Farm and Landscape models at Farming Systems Ecology ● Farm DESIGN ● Landscape IMAGES

Model concept Farm DESIGN Model outputs: e. g. § Static / quasi dynamic; Spatially implicit Feed balance (E, P) Nutrient flows, balances (C, NPK) Use of crops/feeds Feed Areas of crops Manure production &breakdown Organic matter balance Numbers of animals Crop Farm family Water balance Animal Labor balance Economic results Soil Bio-energy production Manure Greenhouse gas emissions Human nutrition indicators Amount of manures/fertilizers Environment Economics Buildings Machines

Farm DESIGN: Describe / explain Inputs (Describe): MODEL Outputs (Explain): Maize mgt i; area Operating profit Groundnut mgt k; area Labour balance Milk cow; number Calves; number Fertilizer type t; amount Rotation area Organic matter balance Nitrogen soil losses

Farm DESIGN: Explore EXPLORATION Decision variables: Minimum = 0 Maximum = 10 Objectives and constraints: Inputs (Describe): MODEL Outputs (Explain): Maize mgt i; area Operating profit Groundnut mgt k; area Labour balance Milk cow; number Calves; number Fertilizer type t; amount Rotation area Organic matter balance Nitrogen soil losses ✔ Objective Direction= minimize, or maximize ✔ Constraint Minimum = 1000 Maximum = 2000

Farm DESIGN interface Groot et al (2012) Agric Syst. DESCRIBE – current farm configuration EXPLAIN – indicators of farm performance DESIGN – adjusted farm configurations EXPLORE – tradeoffs and synergies

Red = original farm Blue = farms performing better for all objectives Green = other farms that meet constraints Groot, Oomen & Rossing, 2012. Agricultural Systems.

Nutrient cycle example

Model concept Landscape IMAGES § Static / quasi dynamic; Spatially explicit Model outputs: e. g. Ecological connectivity Land-use / landscape diversity Pest suppression potential Plant-derived resources (insects) Landscape quality (culture-history) Functional nutritional diversity Field and field margin polygons which hold land use activities Delimitation of farms And: Aggregated farm indicators

Landscape IMAGES interface Groot et al (2007) Agric Ecosyst Environ. Groot et al (2010) Eur J Agron. DESCRIBE – current land-use configuration EXPLAIN – indicators of landscape performance DESIGN – adjusted landscape configurations EXPLORE – tradeoffs and synergies

Farming and hedgerow management NFW Friesian Landscape Management NGO Groot et al (2007) Agriculture, Ecosystems and Environment 120, 58 -69.

Farming and hedgerow management NFW Groot et al (2007) Agriculture, Ecosystems and Environment 120, 58 -69.

Spatial cohesion a. g. L/T ratio b. Pareto frontier for 7 indicators of ecology, landscape quality and cost (Groot et al. , 2010; EJA) LEGEND extremes intermediates best compromises h. l. d. i. m. p. e. j. n. q. s. f. k. o. r. t. u. Sight line homogeneity Hedgerows added (km) Hedgerows removed (km) Hedgerows added (km) Sight line homogeneity Porosity c. Hedgerow length (km) Spatial cohesion L/T ratio Porosity

Strengthening hedgerow structure NFW As planned by the landscape management NGO Groot et al (2010) European Journal of Agronomy 32, 112 -119.

Flexible technical framework (general core)

Multi-scale and multifunctional assessment § Field – farm – household – landscape Field indicators: Farm indicators: Landscape indicators: Crop yield Economic results Ecological coherence Nutrient uptake Flows, balances of C, N, P, K Nutritional functional diversity Crop composition Water balance Land-use diversity Water dynamics Manure production &breakdown Landscape amenity Soil nutrient dynamics Organic matter balance Household indicators: Organic matter dynamics Labor balance Dietary diversity Erosion rate Feed balance (E, P) Nutrition adequacy Bio-energy production Household budget Greenhouse gas emissions

Types of models § Evaluation modules (spatially implicit or explicit): ● Static (e. g. balances: economics, nutritional quality, labour; erosion) ● Dynamic simulation (e. g. soil organic matter) ● Landscape metrics ● Network analysis ● Etc. § Framework kernel: ● Pareto-based Differential Evolution (evolutionary algorithm) ● [Agent based models]

Current projects § § § § § CRP Humidtropics (Ph. D + 2 postdocs; Kenya, Zambia), with IITA, ICRAF, Bioversity, AVRDC § § CCAFS (through Birthe Paul; South Vietnam, Tanzania), with CIAT § § § CIRAD/Africa RICE (Ph. D; Benin) - Smallholder livelihoods in rice-based systems CRP Agric. for Nutrition & Health (Zambia), with Bioversity, Columbia Univ. , IFPRI CATIE/CIRAD/Sup. Agro Ag. Train (Ph. D; Costa Rica)– Ecosystem services in coffee CIRAD (2 Ph. D; Amazonia)– Integrated crop-livestock-tree systems CRP WLE (Vietnam, Cambodia) Consultancy – Landscapes and biological control, FFS NWO (China) postdoc – Living landscapes biological control and pollination NWO (postdoc; the Netherlands)- Biodiversity Works national program EU-FP 7 (postdoc; Europe)- Quantification of Ecosystem Services in Agro-ecosystems CRPs MAIZE (Attic; 4 Ph. D + postdoc; Ethiopia, Nepal, Mexico) and WHEAT (Nutrition), with CIMMYT Africa RISING (2 Ph. D; Tanzania, Malawi, Eastern Zambia, Northern Ghana), with IITA, CIAT, IFPRI, MSU IRD/Univ. O/NGOs WASSA (Burkina Faso) Ph. D project – Woody amendments for soil FAO (Madagascar, Zimbabwe) Ph. D + postdoc – Building resilience for climate change

Thank you for your attention Walter. rossing@wur. nl Jeroen. groot@wur. nl

Quasi-dynamic application: adaptive capacity Adaptation space by adding new resources or technologies Adaptation space by re-arranging current resources and technologies Cortez-Arriola et al. , in prep.

Scenarios, optimization, tradeoff analysis Groot et al (2009) Journal of Environmental Management 90, S 147 -S 160.

Nutrition indicators § Dietary diversity scores, based on 9 -16 food groups ● HDDS, WDDS, MDD-W (Kennedy et al. , 2010, 2014) § Food pattern ● Balancing demand supply of food groups § Nutrient adequacy ● Balancing requirement and supply of energy, nutrients § Nutritional Functional Diversity ● Fraction of foods diversity available in an area or farm, relative to the ‘potential’ diversity in that landscape

Relating goals of society to indicators UPublic UFarmer Groot et al (2007) Agriculture, Ecosystems and Environment 120, 58 -69.

Parra-López et al (2009) Land Use Policy 26, 1020 -1030.

Evolution of solution spaces ΔU = change in utility ΔUsociety=0 ΔUpublic p 2 p 1 p 0 p 1 ΔUprivate Parra-López et al (2009) Land Use Policy 26, 1020 -1030.