GYGA-OFRA collaboration

Climate-Soil-Cropping system extrapolation domains

Lieven ClaessensOFRA inception workshop, Nairobi, 26/11/13

Global Yield Gap Atlas (GYGA) www.yieldgap.org

University of Nebraska (UNL) Wageningen University & Alterra

Kenneth Cassman Patricio Grassini Martin van Ittersum Lenny van Bussel Joost Wolf

Justin van Wart Haishun Yang Hendrik Boogaard Hugo de Groot Daniel van Kraalingen

Regional coordinators and partners

Lieven Claessens (ICRISAT) Kazuki Saito (Africa Rice)

Funding sources:

Gates Foundation (SSA, S Asia)

UNL Water for Food Institute (N & S Amer)

USAID (N Africa, Middle East)

EUROPE:

- ca. 30 countries:

Global Yield Gap Atlas: www.yieldgap.org

Year

1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050

Po

pu

lati

on

(x

10

9)

0

1

2

3

4

5

6

7

Rural

Urban

70%

30%

Can agriculture reliably and sustainably provision an urban population of 6+ billion?

4Source: http://esa.un.org/unup/index.asp

Why yield gap analysis?

Currently not possible to provide reliable answers to critical questions of policy makers and R&D organizations:

Food production potential for a region or country (on existing farm land, if farmers adopted best management practices)?

Will it be possible for country/region X to be self-sufficient in food production by 2030 or 2050? Under different climate and socio-economic scenarios?

When and where can we predict crop yields to stagnate because they reach biophysical yield ceilings?

What are the causes of yield gaps and how to overcome them? How can we target options for sustainable intensification?

What are the regions to target experimentation and what are extrapolation domains?

Previous yield gap studies

Regional studies:crop growth models, experiments, best management practiceslocal relevance, but not possible to compare them mutually, due to

inconsistent concepts and methods Global studies:

statistical procedures or generic crop growth modelsconsistent, but generally too coarse, lacking local detail and hence

agronomic relevance

van Ittersum et al., Field Crops Research 143, 2013

Motivation and focus on Sub-Saharan Africa

GYGA aspirations: Food and water security for a population exceeding 9 billion by

2050 while conserving natural resources = high(er) and stable yields on currently used arable land suitable for sustainable intensification

Especially relevant for smallholder systems in SSA: 80% of food produced in SSA from smallholder agriculture (IFAD, 2011)

Food production not keeping pace with population growth More to food security than production alone (distribution,

demand, waste, governance, population)… Major options in SSA for improving productivity and

environmental outputs simultaneously

Sustainable intensification in SSA smallholder context

Smallholder production systems extremely diverse: Agro-ecology (climate, soil, landform) Socio-economic conditions (e.g. access to land, labour, inputs,

markets) No ‘silver bullet’ intervention for sustainable intensification! Rather ‘best fit’ approach from basket of options (Giller et al., 2011)

Examples from the basket of options Integrated Soil Fertility Management (Tittonell & Giller, 2013; Giller et

al., 2011; Khan et al., 2010; Vanlauwe et al., 2010; Altieri et al., 2012)

Crop-livestock integration, dual-purpose crops (Valbuena et al., 2012; Homann et al.; Claessens et al., 2009)

Fertilizer micro-dosing Seed technologies (hybrids, seed priming,…) New crops and crop rotations/combinations/intercropping

(e.g. banana-coffee (van Asten) sorghum-legumes (Atakos et al., 2013)

Small scale irrigation/mechanization Soil water management (e.g. tied ridges, terracing)

Conservation agriculture (e.g. mulching, zero-tillage, rotation with legume,…)

Agroforestry

Importance of soils for SI in SSA Degraded and poorly responsive soils cover large parts of

SSA and represent the majority of poor farmers’ fields Where natural resources are degraded, yield gaps become

poverty traps (Tittonell & Giller, 2013)

African form of sustainable intensification needs to be targeted to ag. system’s responsiveness to limited amounts of ‘intervention’ (inputs, technologies from basket, policies)

Proposed index for soil suitability/responsiveness

‘Inherent’ soil properties contributing to yield potential: WHC (texture, bulk density, infiltration, soil temperature) Rooting depth not limiting Slope (runoff/erosion) not limiting

Properties that are, in principle, amenable to modification through management and inputs:

Soil fertility/health (SOM of topsoil as proxy?) Measure of physical and chemical degradation + (ir)reversibility

• pH, salinity, toxicity,…

Classify each (quantified) property and combine in (weighted) matrix for Soil Suitability Index

Possible sources of soil data ISRIC-AfSIS suitability/constraints maps

Soil rooting conditions Soil nutrient availability and retention capacity Soil salinity, toxicity, workability

AfSIS 1km soil property maps of Africa: Texture SOC pH CEC Bulk Density

AfSIS Land Degradation Surveillance Framework 60 sentinel sites, 19,200 soil samples,….

ISRIC/AfSIS: 3D regression kriging with

~12,000 legacy profiles (including ISRIC-WISE)

1km resolution

• SOC

• pH

• Texture

• CEC

• Bulk Density

• WRB groups

Yield gap analysis: ‘bottom-up’ protocol

Climate zones

Crop-specific harvested areas

Weather station buffer zones

Soil types and cropping systems

Crop model simulations

Actual yields

Yield gaps

Ewert et al., 2011

Aggregation and upscaling

van Wart et al, 2013

5%

GYGA upscaling method

20% 15%

30%

25% 5%

CZ1CZ2

CZ3

CZ4

ST1

ST2

ST3Select soil type in harvested area as near to the selected weather stations as possible

In case two soil types have similar dominant level, these two will be selected

ST4

Linking Soil Suitability with Yield Gap Assessment

GYGA yield gap assessment will give indication about yield gaps and stability of potential/water limited yield over time

Overlaying soil suitability index with yield gaps will identify zones where (lack of) soil quality can explain a large part of the yield gap:

High soil suitability with large (stable) yield gap= high potential for sustainable intensification (productivity side)

Conclusions

Targeting sustainable intensification options is and important component of global future security studies

Focus on soil suitability especially relevant for smallholder systems in SSA

New sources of high resolution soil data can help in constructing a soil suitability index tuned towards the basket of intervention/adaptation options

Combined with GYGA approaches to yield gap assessment, ‘best bet’ areas/systems for sustainable intensification can be identified: extrapolation domains for OFRA

THANKS!