Building a model based on APSIM that simulates smallholder crop-livestock systems. David Parsons

TIAR – research • development • extension • education • training

Building a model based on APSIM that simulates

smallholder crop-livestock systems

David ParsonsChuck NicholsonBob BlakeQuirine KetteringsLuis RamirezDanny FoxLuis TedeschiJerry Cherney


Yucatan MexicoMilpa – shifting cultivation


Hair sheep in Yucatan


The role for modelling mixed systems in developing countries

• There is a general lack of knowledge of what actually goes on in these complex smallholder mixed systems.

• “Modelling realistically offers the only way of identifying and quantifying the subtle but highly significant interactions that occur between the various components of smallholders’ systems” (Thornton & Herrero, 2001).

• Modelling is a method for integrating information in a rational way.


Challenges for crop-livestock models

• Often sufficient in one discipline (soils, crops, livestock, economics) but not the others

• May not be dynamic between components• Modelling can be very time consuming• Construction of a model for a specific

application is costly, therefore a generic modelling framework is preferable.


Objectives

• Develop a crop-livestock model to assess the biophysical and economic consequences of management decisions/farming practices evident in Yucatan mixed systems.

• Dynamically link all components of the model• Be descriptive of the system, predictive in relation to

outcomes (given specific farmer decisions), but not prescriptive (suggesting what farmers should be doing).


Within village Home garden & Sheep pens

Field Crops

Forest

Cultivated forage

Tree harvest

Grain purchase

Movement of fodder

Cut & carry

Cut & carry residuesCut & carry

Graze

Graze

Supplement purchase

Graze residues

By-product purchaseMovement of sheep

Tree purchaseForage purchase

Grain

Outside village

Movement of nutrients through sheep and fodder

Cultivated forageCut & carryGraze

Buy and sell sheep


Components of the integrated model

• APSIM (Agricultural production simulator)– Simulate crop production (soils, crops, weather)

• Vensim– Icon-based modeling software– ‘System dynamics’ software

• SRNS (Small Ruminant Nutrition System)– Based on CNCPS-S (Cornell Net Carbohydrate and

Protein System for Sheep)


Crop

Grass

Corral

APSIM Vensim™

Flock dynamics

Livestock feeding

Nutrient allocations

Management

Labor

Economics

Venlink interface variables

Climate

Soil organic matter, nutrient ,and water dynamics

Surface organic matter

Plant growth

The Integrated model

IntakeWeight gainManure quantity Manure quality

SRNS data


Venlink interface variablesCrop Grass Corral

APSIM to

Vensim

Grain harvestedGrain proteinStover harvestedStover protein

Grass leaf and stem availableGrass leaf and stem protein

Manure in pileManure N in pileRefusals in pileRefusal N in pile

Vensim to

APSIM

Manure to milpaManure C:NRefusals to milpaRefusals C:NMilpa cultivation cycleUrea to milpaFraction of stover harvested

Manure to grassManure C:NRefusals to grassRefusals C:NUrea to grass

Manure to corralManure C:NRefusals to corralRefusals C:NEmpty manure pile signal


Crop

Effects of applied manure

Grass

Effects of applied manure

Corral

Breakdown of stored manure

APSIM Vensim™

Manure allocation calculations

Manure C:N calculations

Define manure use

Quantity and C:N of stored manure

Example - manure

Manure quantity Manure quality

SRNS data

Manure quantity Manure quality

Manure allocation, C:N and use info


Example Vensim screen


Some model limitations

• Not all modules in APSIM are P responsive. • SRNS also does not track P (yet).• Wider range of tropical crop modules needed in

APSIM, particularly forage crops.• Simulation time


Possible model improvements

• More choices of soils and crops.• Lack of knowledge of the underlying processes of manure

decomposition: – Manure decomposition in soil is ok– Manure on surface and in piles not as well understood– Technologies that improve manure management

• Secondary feed quality data is needed to generate SRNS runs, i.e. data that is not generated by the APSIM model section.

• A dynamic SRNS would offer numerous benefits.


Why not code it all in APSIM?

APSIM has great flexibility to write ‘manager’ codeVisual nature of Vensim is a great helpPartial model testingAccessing text/excel data using VensimSensitivity analysis, optimization


Types of scenario analyses

• What are the biophysical and household outcomes from differing:– Types of farms (livestock vs. crop vs. livestock & crop)– Manure management and use practices– Livestock feeding practices– etc.


Example Implications of model outputs1. Logical for smallholders to make use of the natural resources

available. Focus on using common land

2. Cut and carry systems can be more labor efficient than common land grazing systems (where continuous supervision is needed).

3. Investment in increased integration through the use of crop by-products may not be a favorable option while common land is available.

4. Investment in infrastructure to grow improved forages may lead to decreased returns to labor and net income.


Review of this modeling approach• Crop-livestock systems, particularly those in developing

countries, are variable and complex, making it difficult for a particular modeling package to be applicable to every situation.

• Our model builds on a foundation of well a established soil-crop-climate model (APSIM) and sheep model (SRNS)

• Links with Vensim allow flexibility to develop model structure to simulate individual systems and address particular research questions

Building a model based on APSIM that simulates smallholder crop-livestock systems. David Parsons

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