Burra, Dharani Dhar

Douxchamps, Sabine

Epper, Carole A.

Long, Chau Thi Minh

Paul, Birthe K.

Tschopp, Damien

Tungani, Victor

CGSpace

 Agricultural intensification pathways and agro-environmental trade-offs in the Greater Mekong  Paul, B.K.1, Tungani, V.1, Epper, C.2,3, Tschopp, D.2,3, Burra, D.2, Chau, L.4, Douxchamps, S.2 1International Center for Tropical Agriculture (CIAT), Nairobi, Kenya 2International Center for Tropical Agriculture (CIAT), Hanoi, Vietnam 3ETH Zurich, Switzerland 4Western Highlands Agriculture & Forestry Science Institute (WASI), Buon Ma Thuot, Vietnam 1. Introduction  The Greater Mekong area is undergoing socio-economic change with growing population, incomes and increasing demand for animal-source foods. Traditional diverse and subsistence-oriented agriculture is being replaced by market-oriented production focused on a few (cash) crops. In the Central Highlands of Vietnam for instance, local government advocates for development of the beef value chains to meet the high domestic demand and create economic opportunities for smallholder farmers (Stür, et al., 2013). However, rapid intensification can have environmental trade-offs including loss of (agro)biodiversity, deforestation, nutrient pollution, and greenhouse gas (GHG) emissions.  2. Materials and methods  Survey data from approximately 1300 households in Laos (XiengKhuang province), Cambodia (Ratanakiri province), and Vietnam (Central Highlands) was used for this study (Figure 1a). The survey was administered using the Rural Household Multi-Indicator Survey tool (RhoMIS) (Hammond et al. 2016). A market orientation and production diversity score was calculated for each household. Households were then categorized into four distinct farm types: low diversity and low market orientation (LDLM), low diversity high market orientation (LDHM), high diversity low market orientation (HDLM), and high diversity high market orientation (HDHM). 24 farms across classes and sites were selected – eight farms in each country, two representing each farm type (Figure 1b). Additional data collection from these 24 farms included a more detailed household survey, soil samples, and nutrient flow maps. The farming systems were simulated and compared with the whole-farm bio-economic optimization model FarmDESIGN (Groot et al. 2012).       Figure 1: Location of farming systems for bio-economic modeling in Laos, Cambodia and Vietnam (a); and modeling farming systems and all approximately 1300 RHoMIS households scored along market orientation and production diversity (b).  3. Results – Discussion  The sites represent various farming systems and stages of intensification. Farmers in the Central Highlands of Vietnam have intensified production on relatively small farms (0.5 - 3 ha), focusing on major cash crops such as cassava, cashew, coffee, and pepper under high input use, especially mineral fertilizers. Cattle are mostly improved breeds under cut-and-carry feeding, often with improved varieties of Napier grass (Pennisetum purpureum). Farmers in XiengKhuang, Laos, are practicing diverse subsistence-oriented agriculture, while slowly moving towards more market-oriented production. Larger local cattle herds, as well as a variety of crops including rice, tea, pasture, and vegetables are found. Farming systems in Ratanakiri, Cambodia, rely on relatively recent forest clearing and could therefore exploit larger farm sizes (3.5 – 10.5 ha) for rubber, cashew, and cassava for markets in Vietnam and China, with hardly any livestock except chicken.        b. a.     Figure 2: GHG emissions per farm (kg CO2-eq) across farm types and study sites in Cambodia, Laos and Vietnam (a); nitrogen (N) inputs and outputs (kg N/ha) across farm types and sites, with numbers on top or below bars indicating N balance (b).    050001000015000200002500030000CLDLM1CLDLM2CLDHM1CLDHM2CHDLM1CHDLM2CHDHM1CHDHM2LLDLM1LLDLM2LLDHM1LLDHM2LHDLM1LHDLM2LHDHM1LHDHM2VLDLM1VLDHM1VLDHM2VLDHM3VLDHM4VHDHM1VHDHM2VHDHM3kg CO2-eq/farmChicken Duck TurkeyPigs Young Adults Pigs Adult CowFattening Cow Calf Improved calfImproved steer Fishpond Green manure appliedImported manure Stable manure PastureYard SA UreaNPK1 NPK2 Rice1Rice 2 Burning Symbiotic N fixationAtmospheric N deposition-150-100-50050100150200250CLDLM1CLDLM2CLDHM1CLDHM2CHDLM1CHDLM2CHDHM1CHDHM2LLDLM1LLDLM2LLDHM1LLDHM2LHDLM1LHDLM2LHDHM1LHDHM2VLDLM1VLDHM1VLDHM2VLDHM3VLDHM4VHDHM1VHDHM2VHDHM3N flow at farm level kg/ha Import crop products Import manure FixationDeposition Non-symb. fixation Export crop productsExport animal products Export animal manure Export of household excreta-1718-48-22-15-25---49-7-85-1- -553283876819152-33603a. b.  Although farming systems in the Central Highlands of Vietnam have considerable GHG emissions from mineral fertilizer use, GHG emissions from Ratanakiri (Cambodia) and XiengKhuang (Laos) were higher due to the common practice of cassava and maize residue burning. All farming systems have GHG emissions from rice cultivation (Figure 2a). N balances are mostly negative in the Cambodian and Laos sites, reflecting low input use. In the Lao site, fallowing is still used as traditional soil fertility management technique, balancing nutrient mining during cropping seasons. The large farm areas of recently cleared forest in the Cambodian site does not yet make it urgent to invest in soil fertility, although soybean cultivation contributes to N inputs into the systems through biological N fixation. Farming systems in the Vietnamese site are the only ones applying substantial amounts of N mineral fertilizer, leading to positive balances (Figure 2b).  4. Conclusions Sustainable livestock intensification could potentially play an important role to mitigate agro-environmental trade-offs and thereby contribute to sustainable intensification. Small herds of well-managed and productive cattle can convert residues into animal-source food and manure for fertilization, while reducing the polluting practice of residue burning. A previous study found that has shown that forage-based livestock fattening can increase operating profits by 35%, while maintaining soil organic matter and decreasing GHG intensities (Birnholz et al. 2017). Multi-objective optimization will elucidate potential agro-environmental impacts of various agricultural intensification pathways, including close crop-livestock integration.  Acknowledgements This study was carried out under the project ‘Hands and Minds connected to boost eco-efficiency of smallholder livestock-crop systems’, led by the International Center for Tropical Agriculture with funding from the German Federal Ministry for Economic Cooperation and Development (BMZ). The work was undertaken as part of the CGIAR Research Programs on Livestock and Humidtropics, which are supported by the CGIAR Fund Donors and bilateral funding agreements. ETH Zurich, Group of Plant Nutrition, supported MSc field work. We thank the farmers for their time and collaboration.  References Birnholz, C., Bolliger, A., Tan Khanh, T., Groot, J., Paul, B.K., 2017. Bio-economic evaluation and optimization of livestock intensification options in the Central Highlands of Vietnam. Working Paper No. 433. International Center for Tropical Agriculture (CIAT), Nairobi, Kenya 31. Groot, J., Oomen, G., & Rossing, W. (2012). Multi-objective optimization and design of farming systems. Agricultural Systems, 110, 63-77. Hammond, J., Fraval, S., van Etten, J., Suchini, J. G., Mercado, L., Pagella, T., Frelat, R., Lannerstad, M., Douxchamps, S., Teufel, N., Valbuena, D. and van Wijk, M. T., 2017. The Rural Household Multi-Indicator Survey (RHoMIS) for rapid characterisation of households to inform Climate Smart Agriculture interventions: description and applications in East Africa and Central America. Agricultural Systems 151, 225-233.  Stür, W., Khanh, T., & Duncan, A. (2013). Transformation of smallholder beef cattle production in Vietnam. International Journal of Agricultural Sustainability, 11(4), 363–381.  

Agricultural intensification pathways and agroenvironmental trade offs in the Greater Mekong

Agricultural intensification pathways and agro-environmental trade-offs in the Greater Mekong20th of August 2019, Montevideo, UruguayFarming Systems Design Conference‘Strategies to reduce environmental impacts of agricultural systems’Birthe K. Paul, Victor Tungani, Carole Epper, Damien Tschopp, Dharani Burra, Chau Thi Minh Long, Sabine DouxchampsB.Paul@cgiar.orgIntroduction• Greater Mekong Subregion: Cambodia, China, Laos, Myanmar, Thailand, Vietnam• Rapid and profound agricultural transformation from subsistence agriculture to commercial production• Drivers include infrastructure development, improved market access and government policy• Growing population and increasing incomesleading to higher demand for animal source foods• Environmental implications of these developments include rising GHG emissions, nutrient cycling/pollution, deforestation• Sustainable intensification pathways are neededIntroduction: study sitesThree contrasting study sites to capture different levels of agricultural transition:- XiangKhouang region, Laos: mixed crop-livestock, 1200 masl, 16 persons/m2, subsistence oriented- Ratanakiri province, Cambodia: low input monoculture, 200-400 masl, 17 persons/m2- Central Highlands, Vietnam: intensive agricultural production, 400-800 masl, 110 persons/m2, market orientedIntroduction: Household dietary diversityRitzema, R.S., Douxchamps, S., Fraval, S., Bolliger, A., Hok, L., Phengsavanh, P., Long, C.T.M., Hammond, J., van Wijk, M. 2019. Household level drivers of dietary diversity in transitioning agricultural systems: Evidence from the Greater Subregion. Agricultural Systems, 176, 102657.  Drivers of dietary diversity and agricultural transition pathways are site-specificIntroduction: Nutrient balances in LaosEpper, C., Paul, B.K., Burra, D., Phengsavanh, P., Ritzema, R., Syfongxay, C., Groot, J.C.J., Six, J., Frossard, E., Oberson, A., Douxchamps, S. Nutrient flows and intensification options for smallholder farmers of the Lao uplands. Revisions submitted to Agricultural Systems. -50050100150N-BalanceP-BalanceN-NRILand productivityIncomeM-50050100150N-BalanceP-BalanceN-NRILand productivityIncomeDRecyclingRotatingFattening-50050100150N-BalanceP-BalanceN-NRILand productivityIncomeDMRecyclingRotatingFattening-50050100150N-BalanceP-BalanceN-NRILand productivityIncomeZPrinciples for sustainable intensification of these systems: no residue burning, stay diverse, integrate livestock, use small amounts of P fertilizer Introduction: Cattle fattening impacts in Vietnam Returns BaselineForage-based cattle fattening sc.Grain-based cattle fatting sc.Gross margin crops 5093.24 4238.99 5481.54Risk crop margin 0 0 0Gross margin animals 38.41 2837.18 1569.37CostsFertilizers/Manure costs598.07 577.94 165.53Crop protection costs 62.59 92.19 49.14Hired casual labor costs376.74 508.37 316.91Hired regular labor costs0 379.11 0TotalsOperating profit (+return farm. labor)4094.25 5518.56 6519.33Change from baseline 35% 59%Own labor costs 702.82 702.84 504.08Return to own labor 3.92 5.28 5.82Home consumption 551.78 211.64 211.64BaselineForage-based cattle fattening sc.Grain-based cattle fatting sc.InputsRoot biomass and stubble557 604 536Surface residue retention0 0 0Own manure 759 2377 0Imported manure 0 0 0OutputsManure degradation 688 2156 0SOM degradation 536 536 536Erosion losses 0 0 0BalanceBalance 93 290 1Change from baseline 212% -99%Profitability (USD/farm/year) SOM balance (kg/ha)Birnholz, C., Bolliger, A., Tan Khanh, T., Groot, J., Paul, B. (2017). Bio-economic evaluation and optimization of livestock intensification options in the Central Highlands of Vietnam. Working Paper No. 433. International Center for Tropical Agriculture (CIAT), Nairobi, Kenya. 31 p. http://hdl.handle.net/10568/79446 Study objectivesSystematic exploration of agro-environmental trade-offs of various intensification pathways across the Greater Mekong• Describe farming systems and quantify agro-environmental performance and trade-offs in sites of various stages of agricultural transition• Assess how market orientation and production diversity influence agro-environmental trade-offs • Explore alternative future intensification pathwaysMM: Household survey 1,300 households sampled using the RHoMIS survey tool from Dec 2015 – Mar 2016- Market orientation and production diversity score was calculated- Households were then categorized into four farm types• Low diversity low market orientation (LDLM)• Low diversity high market orientation (LDHM)• High diversity low market orientation (HDLM)• High diversity high market orientation (HDHM)Same RHoMIS dataset used as in Ritzema et al. 2019MM: Whole farm modeling• Random selection of 24 households for farming system modeling: eight households per country, two per type (in Vietnam only three types represented as low market situation uncommon) • Additional data collection included a more detailed household survey, soil samples, and nutrient flow maps• Farming systems modeled and compared with whole-farm bio-economic model FarmDESIGNDESCRIBE EXPLAIN EVALUATE EXPLOREMM: Approaches to farming system selectionGeographic scope Number of farming systems ReferenceFarming system population modeling Mali: Koutiala 30 Falconnier et al. 2015India: Uttarakhand 42 Ditzler et al. 2018Tanzania: Lushoto district 164 Shikuku et al. 2017India: Bihar 269 Lopez-Ridaura et al. 2018Burkina Faso, Ghana, Senegal 600 Douxchamps et al. 2016Rwanda: different districts 884 Paul et al. 2018Kenya, Tanzania, Uganda, Ethiopia, Senegal, Burkina Faso 1019 Henderson et al. 2016 East and West Africa: 7 countries 1800 Ritzema et al. 2017Sub-Saharan Africa 13000 Frelat et al. 2018Farming system type modelingConstructed farming systems from survey averages, government census, expert knowledge, policy documents India, Ethiopia 4 Mayberry et al. 2018India, Ethiopia 5 Mayberry et al. 2017Mexico: Yucatan 1 Parsons et al. 2011Zimbabwe: Nkayi 6 Descheemaeker et al. 2018Real farming systems selected from surveys, multivariate- statistics,purposive selectionTanzania: Babati 4 Paul et al. in reviewBurkina Faso: Yatenga 2 Rigolot et al. 2017China: Gansu 3 Komarek et al. 2012Kenya: Vihiga 9 Waithaka et al. 2006Mexico: Michoacan 6 Cortez-Arriola et al. 2014Ghana: three regions 9 Michaelscheck et al. 2018Vietnam: Son La 2 Ditzler et al. 2019 Brazil: Cerrados 6 Alary et al. 2016Results: Farming systems diversity01234567891011[ha]Crop areasRice CassavaMaize BananaSweetCorn MangoSugarcane CoffeeCashew SoybeanRubber Tea plantationWild Tea PastureVA06 HomegardenCucumber+beans+coriander+spring onion+garlic VegetablesCassava+Soybean+Pumpkin+Chilli Maize+Cucumber+SoybeanCambodia Laos VietnamResults: Farming systems diversity02468101214TLUChicken Duck Turkey Cow Improved cow CalfImproved calf Improved steer Fattening Cow Cow F Young Pig Pig YoungCambodia Laos VietnamResults environmental impacts: N balance-150-100-50050100150200250CLDLM1CLDLM2CLDHM1CLDHM2CHDLM1CHDLM2CHDHM1CHDHM2LLDLM1LLDLM2LLDHM1LLDHM2LHDLM1LHDLM2LHDHM1LHDHM2VLDLM1VLDHM1VLDHM2VLDHM3VLDHM4VHDHM1VHDHM2VHDHM3N flow at farm level [kg N ha-1y-1] Import crop products Import manure FixationDeposition Non-symb. fixation Export crop productsExport animal products Export animal manure Export of household excreta-34-5-41-29-15-27-31-25-62-3-961-68-83189857519262-3484LaosCambodia Vietnam2-15Results environmental impacts: GHG emissions0246810[t CO2eq. ha-1y-1 ]Per hectareNon-ruminants Ruminants Manure emissionsGreen manure Mineral fertilizers Rice managementBurning of organic material N fixation and N deposition051015202530[t CO2eq. Y-1]Per farmNon-ruminants RuminantsManure Green manureMineral fertilizers Rice managementBurning of organic material N fixation and N depositionAgro-environmental trade-offs051015202530350 5000 10000 15000 20000 25000Annual GHG emissions [t CO2 eq. Farm-1y-1]Gross margin (animals and crops) [USD y-1]CambodiaLDLMCambodia LDHMCambodia HDLMCambodia HDHMLaos LDLMLaosLDHMLaosHDLMLaosHDHMVietnamLDLMVietnamLDHMVietnamHDHM-150-100-500501001502002500 5000 10000 15000 20000 25000Annual farm N balance [kg N ha-1y-1]Gross margin (animals and crops) [USD y-1]Conclusions• Intensification not always leading to higher environmental impacts – e.g. residue burning a large GHG source in Cambodia and Laos • Nutrient management: In Vietnam risk of nutrient pollution, other countries need more inputs through fertilizer, manure recycling and residue use (mulching or feeding) instead of burning, integration of legumes• Between-country trends seem to be more important in determining environmental impacts than market orientation or diversity – though statistical analysis is pending• Potential role of livestock in sustainable intensification and mitigating agro-environmental trade-offs – converting residues into animal source food and manure for fertilization, reducing residue burning• Optimization can explore potential agro-environmental impacts of various agricultural intensification pathwaysThank you!Funding from• BMZ through project ‘Hands and Minds Connected to Boost Eco-efficiency in Smallholder Livestock-Crop Systems: Participatory approaches in Laos, Cambodia and Vietnam’• CGIAR Research Programs on Livestock and Humidtropics• ETH Zurich Plant Nutrition GroupThanks to Lyda Hok, RUA in Cambodia and Seuth Phengsavan, NAFRI in Laos for adviceAll pictures by Birthe Paul, Neil Palmer and Georgina Smith, CIAT

Agricultural intensification pathways and agro-environmental trade offs in the Greater Mekong

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Agricultural intensification pathways and agroenvironmental trade offs in the Greater Mekong

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