Utilizing a framework of indicators to assess sustainable intensification Sieglinde Snapp 1,2, Philip Grabowski 1, Regis Chikowo 1,3, Erin Anders 1 and Mateete Bekunda 2 Contact: 1 Plant Soil and Microbial Sciences Department, Michigan State University, East Lansing, Michigan - USA 2 International Institute of Tropical Agriculture (IITA), Arusha – Tanzania 3 Department of Crop Science, University of Zimbabwe, Harare – Zimbabwe

What is sustainable intensification? SocialEconomic Human conditionEnvironment Productivity

Objective: evaluate relative sustainability of a technology or intervention SI Framework Field/Animal Herd Scale Farm/Household Scale Landscape/Administrative DOMAINSELECT INDICATORS ProductivityYield Residue production Yield variability EconomicProfitability (gross margins) Labor availability Land availability EnvironmentalMonths soil cover Nutrient balances Human ConditionNutrition Food Security SocialGender equity Social conflict SCALE

Productivity domain Field/plotFarmHousehold Landscape or Administrative Unit Measurement method Yield (partitioned by species and tissue type) and residues (total = NPP) kg biomass (yield, fodder, residue, weeds) / ha / season 1,2,3 kg tree product (fruit, wood, fodder) / area under crown (or trees per ha) 1,2 kg (yield, fodder, residue) / ha / season 1,2,3 Farmer perceptions and ratings of technology yield performance 5 Net Primary Productivity (above ground) 4 1 Agricultural survey (recall) 2 Yield measurements 3 Crop models (point models) 4 Remote sensing 5 Farmer participatory trials Animal productivity considering land area Animal production by product (milk yield, weight gain, meat, manure, reproduction rate) 1,2 Animal production by product (milk yield, weight gain, meat, manure) / ha grazing and fodder land used 1,2 Animal product/farm/year 1,2 Net commercial off-take relative to the total grazing and fodder production area 1 1 Agricultural survey (recall) 2 Production measurements

Environment domain Field/plotFarmHousehold Landscape or Administrative Unit Measurement method Nutrient Partial Balance kg N,P, and K inputs (fertilizer, manure, etc.) less kg N, P, and K in total biomass removed (harvest, grazing) per hectare per year 1,2 N/A kg N,P, and K inputs (fertilizer, manure, etc.) – kg N, P, and K in total biomass removed (harvest, grazing) per hectare per year 1,2 1 Agricultural survey for inputs and outputs 2 Lookup tables to estimate nutrients in harvest and organic inputs GHG EmissionsCO 2 equivalents per hectare (also broken down by CO 2, CH 4, and N 2 O) 1 N/ACO 2 equivalents per hectare (also broken down by CO 2, CH 4, and N 2 O) 1 1 Lookup tables for each activity or input

Applying the indicators to evaluate legume systems in Malawi Systems compared: Mz0 – Continuous sole maize – no fertilizer MzNPK – Continuous sole maize with 69 kg N/ha fertilizer PpMz – Maize-Pigeonpea intercrop with 35 kg N/ha fertilizer GnPp-Mz – Groundnut-Pigeonpea intercrop rotated with maize (35 kg N/ha fertilizer in maize phase) Data sources: 1)Mother trials – yield and biomass (2-3 seasons) 2)APSIM modeling results – yield variability, long-term soil changes 3)Survey data (baseline for prices + hh composition; baby trials survey for pairwise ranking of technologies

Results Legume systems improve soil Competitive for maize and profits Improved nutrition High female ranking

Results Legume systems improve soil Competitive for maize and profits Improved nutrition High female ranking

Results Legume systems improve soil Competitive for maize and profits Improved nutrition High female ranking

Discussion Data gaps related to social conflict over residue grazing and labor Complex gender effects from intensifying legume production

Conclusion The SI indicator framework facilitated holistic analysis of legume systems and the identification of important data gaps A transdisciplinary approach (interdisciplinary research collaboratively engaging with farmers) is needed to develop and assess management practices for sustainable intensification

DFID funded SAIRLA project Objective – Analyze and develop tools for analyzing the effects of agricultural interventions on women and youth Focus on supporting decision-makers’ use of gender analysis for SI projects and contextualizing gender indicators through farmer participation IITA lead agency, Gundula Fischer as PI P. Grabowski and L. Zulu at MSU Supporting LUANAR (Malawi) and Univ. of Ghana August 2016 to December 2019