“Dryland Systems”

Key tradeoffs questions and tools for CRP1.1

Anthony M. Whitbread

Crop Production Systems in the Tropics

University of Göttingen, Germany

W. Payne (ICARDA), T. Gerik (TA&M), D. White (CSIRO), P. Lecomte (UMR-SELMET), H. Belhouchette (CIHEAM-IAMM), G. Hammer (QCCA)

“Dryland Systems”

Dryland Systems targets the poor and highly vulnerable populations of dry areas in developing countries and the agricultural production systems on which they depend for food and livelihoods

Integrated Agricultural Production Systems for Improved Food Security and Livelihoods in Dry Areas

• 65 % of the worlds agricultural lands fall into the category of drylands

• The majority of the poorest people live in semi-arid areas.

• Mixed farming systems

• High climate variability and, in-general, high vulnerability to changes in climate.

• Already extensive degradation

• Systems analysis needs

Dryland Systems- key features

Targets 2 Strategic Research Themes..production systems where:

Reduced vulnerability and increased resilience to shocks (SRT2)

Sustainable intensification to reduce food security and generate income (SRT3)

Conceptual Framework and Steps in Impact Pathway

SRT1: Approaches and models for strengthening innovation systems, building stakeholder innovation capacity, and linking knowledge to policy action

SRT2: Reducing vulnerability and managing risk

SRT3: Sustainable intensification for more productive, profitable and diversified dryland agriculture with well-established linkages to markets

SRT4: Measuring impacts and cross-regional synthesis

Markets

Tradeoffs and scale

Microbe-plant

Community, watershed, region…

Farm, household, livelihood…

Field, flock, forest

Markets

Key tradeoffs and tools: plant to field scale

Microbe-plant

Examples • High and low harvest index (fodder, building material Vs grain)• Short duration risk avoidance Vs longer duration higher yielding• Effect of stay green traits in sorghum across environment

Tools• Detailed crop models that capture interactions between environment

and genotype….and phenotype

e.g. Hammer et al. (2010) uses “….sufficient physiological rigour for complex phenotypic traits to become emergent properties of the model dynamics.”[Hammer et al. 2010. J. Exp. Botany 61(8), 2185-2202.]

Simulating consequences on grain yield- sorghumYield consequences reflect trends in field data (e.g. Dalby)

Source: Hammer pers. comm

Key tradeoffs and tools: Field to farm scale

Examples:• Fallow weed control and consequences for soil water at sowing (&

labour tradeoffs)• Quantifying the riskiness of various intervention strategies (e.g.

fertiliser response x season)• Comparing decisions around crop type/variety and time of planting

Tools• Crop-soil models that capture interactions between environment and

genotype (e.g. APSIM, DSSAT)• Summary models that capture model output statically (e.g. IAT)• Farm level models that capture interactions (e.g. APSFARM, NUANCES)

Effect of variations in PAW and seeding opportunity on percentage of modelled yields – South Australian wheat belt Upper tercile

(white)Middle tercile (grey)Lower tercile (black)

Planting opportunity: Early Late

Fertilizer response in extra bags grain for one bag applied AN (15 kg N/ha)

Sowing window from 1 Nova 1 Decb

Plant population (/m2) 2.0d 3.5c 2.0 3.5

Weed control good poore good poor good poor good poor

Soil Depth Soil fertility

Shallow (50 cm) low 10 1 3 0 8 1 2 0 mod 9 3 9 1 7 3 6 1 high 7 4 8 2 5 3 5 1

Medium (100 cm) low 17 5 14 1 15 4 11 0 mod 11 6 16 5 11 7 15 5 high 9 6 14 6 8 7 13 6

Deep (>150 cm) low 16 6 17 2 15 0 15 2 mod 11 7 17 7 10 8 15 8 high 8 6 14 8 8 6 13 9

very low risk (one year in 10) medium risk (one year in 5)high risk situations

Key tradeoffs and tools: Farm to watershed or regional scales…

Examples:• Impacts of soil conservation measures (buffers, etc.) in watershed to

national level erosion assessments (e.g. USDA)• Impacts of widely adopted agronomic interventions on watershed

processes (e.g. Lake Tana in NW Ethiopia).

Tools• SWAT-APEX-EPIC (http://swat.tamu.edu/ http://apex.tamu.edu/)• Bio-economic modelling frameworks (farm to regional) e.g. or

Integrated Agricultural Assessment Tools (IAAT) (CIRAD & CIHEAM)

• Hydrologic analysis showed sufficient water for dry season irrigation• Crop yields responded strongly to N, dry season irrigation, improved

varieties• Major environmental consequences due to increased yields - reductions

in soil erosion and sedimentation

ConclusionsThis CRP has aims at agro-ecosystems where: (i) systems are highly vulnerable ….increase resilience to shocks(ii) systems where some sustainable intensification options are available

Mixed (crop-livestock) farming systems are dominant and therefore key tradeoffs at field/farm level include enterprise selection/ labour/ residues/ investment/ climate risk management…

Tools available (defined largely by the interested partners):• pasture-tree-crop-soil modelling (CSIRO, APSRU group, Australia)• whole farm/watershed management (Texas A&M, USA)• Animal (CIRAD) and whole farm to regional economic modelling (CIHEAM-

Montpellier)• Underpinned by efforts to develop research methods support (Reading

University)A community of practice of model expertise

underpinning many of the CRP1.1 activities.

Systems analysis is not just about the tools, its also how they are applied (e.g. Whitbread et al 2010, Ag. Systems show 4 distinct modes of use in SSA)

Dryland Systems focuses on two agro-ecosystems (SRT2 and SRT3)