gyga-ofra collaboration climate-soil-cropping system extrapolation domains lieven claessens ofra...
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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!