This document summarizes research on using agrobiodiversity to manage pests and diseases. The research involved working with over 1500 smallholder farmers across multiple crops and locations. It found that higher crop diversity on farms reduced vulnerability to pests and diseases by disrupting pest and pathogen transmission. Analyzing over 2000 farmer interviews and field trials, the research also identified traditional crop varieties with different resistance profiles that could help smallholders reduce crop losses from biotic stresses with low-input options. Overall, the research concluded that agrobiodiversity benefits smallholder food security and livelihoods by decreasing crop failure risks from pests and diseases.

1. Use of Agrobiodiversity for Pest and Disease Management Carlo Fadda, Bioversity International ODDG Seminars, 19 May 2011

2. Outline Overview of the Project Research Methodology Main Results Final Remarks

3. The project idea Farmers need to face several biotic and abiotic stresses. Traditional crop varieties as one of the few resources available to poor farmers : Make use of the intra-specific diversity among the traditional varieties maintained by farmers to reduce pest and disease pressures Strategy Build on existing knowledge (farmer and researcher) Exploit the natural resistance that results from the co-evolution of pest and host species Provide farmers with low-input options through reduced use of pesticides

4. We can not predict that a new pest or pathogen will develop But we can use local genetic diversity and have a diverse set of crop varieties for farmers to reduce their risk of crop loss from pests and diseases A diverse set of varieties with: Non-uniform resistance Less probability that migrations of new pathogens or mutations of existing pathogens will damage the crop

5. Crops (foodsecurity of smallfarmers; differentbreedingsystems) Coverage of different resistance gene system (where resistance is controlled by both major and minor genes) Transmission systems: seed-borne, soil-borne, and air-borne Plant organ affected: leaf, stem, seeds and roots

6. Outcome: Benefits to local communities Reduced crop vulnerability Reduced crop loss Increased incomes Increased capacity and leadership abilities Benefit sharing protocols with communities

7. Methodology Participatory Diagnostic: Focus Group Discussion; Household Survey; Technical Evaluation (laboratory and field analysis).

8. Focus Group Discussion More than 1500 farmers attended the FGD globally

9. Based on the information from FGD; Sixty farmers randomly selected interviewed in each community for each crop; More than 2000 farmers were interviewed worldwide Information on diversity is combined with field observations (option 1). Household Survey

10. Amount and distribution of bean varieties Results – Farmers’ Knowledge Kabwohe Rubaya Nakaseke HH richness 2.21 2.20 2.556 HH Simpson 0.32 0.375 0.432 Community richness 23 26 16 Community Simpson 0.85 0.914 0.799 Divergence 0.62 0.59 0.46

11. Farmers’ Knowledge (Cont.) Dalixiang Baiyangnuo Magu Variation of resistance to rice blast in different traditional rice varieties 1-S 2-MS 3-MR 4-R

12. Results - Option 1 10 sample points were taken randomly in a field and these points’ for panicle blast different levels of resistance. Its range of variation was from 7% to 25%. Average disease incidence of 10 sample points for Dalixiang

13. Results - Option 1 (Cont.)

14. Biotic diversity regulates pests and diseases Crop genetic diversity in farmer’s fields – reducing vulnerability Reducing the probability of crop loss from pest and diseases now and in the future Weighted Damage Index = Crop loss (household) Variety richness at household level Variety Evenness at household level Household Damage Index Higher variety richness/evenness – less variance in damage: a risk minimizing argument for crop variety diversity in the production system Peng et al., 2011

15. Results – Option 2 Of 63 varieties, 3 didn’t flower .HR, R and MR accounted for 5%, 1.67% and 15%, respectively. The remaining 78.33% ranged from MS to HS (56.67%). HR 3 Qiena, Zhangmeleng-1, Chujing-27 R 1 Modelong-1 MR 9 Chengnuo-88 ， Nuoyou-9 ， Baiyangnuo ， Qiejiaba ， Qiege ， Chujing-24 ， Bendipinzhong ， Dulong-1 ， Xiangnuo

16. Option 2 (Cont.) Within varieties, the resistance of different individual to rice blast was various. For example, Shanyou-63 was susceptible to panicle blast, but its 30 individuals had different performance on resistance to blast, which was from HR to HS. So did other varieties.

17. Results – Option 4 Disease grade of leaf blast Disease grade of panicle blast Resistance R MR MS S MS S HS No. 25 13 14 6 11 13 27 Precentage 43.10 22.41 24.14 10.34 21.57 25.49 52.94 No. of varieties 58 51 Seedling nursery Field identification nursery

18. Isolates of Rice Blast Fungus 212 isolates were collected in farmer fields and in trials. Results – option 3 Province isolates Yunnan Yuanyang 62 shiling 45 Banna 21 Sichuan shehong 41 Guizhou Meitan 31 Yunnan+ Guizhou predominant races 12 Total 212

19. Option 3 - (Cont.) 0.85 Shili Shili Yuanyang Yuanyang Meitan Yuanyang Meitan Shehong Shehong Banna Banna 37 differenthaplotypesand 27genetic lineagesat 0 . 85 similar linkagedistancelevel ,in 212 isolatesofblastfungus .

20. Results - option 5 Cultivars Isolates Frequency of virulent on cultivars 143-7a 08-SL-1-21 9-3 Y2009-31-1-6 S-2009-10-1-5 G2009-7-1-1 G2009-6-1-3 Hongyang-3 R R R R R S S 28.57 Yijing-1 R S S R R R R 28.57 magu S R R S R R R 28.57 Tuobeigu R R R S S R R 28.57 Changnuo-2 R R S R S R - 33.33 Hejing-7 R S S S R R R 42.86 Zaogu S R R S S R R 42.86 Xiangnuo R R R S R S S 42.86 Yinuo931 R S R S R S R 42.86 Chujing27 S R S S R R R 42.86 tuojiangnuo R S S R S R R 42.86 Chujing24 S R R S R S R 42.86 dulong-2 R S S S R R S 57.14 Chengnuo88 R S R S S S R 57.14 Yuelianggu S S R R S S R 57.14 Zimigu S R S S R S R 57.14 Nuoyou-9 S R S S S R R 57.14 zhangmeleng-2 R R S R S S S 57.14 zhangmeleng-3 R S S S R S R 57.14 Aijiaogu S R - S R S S 66.67 kaomolao S S S - R R S 66.67 Baiyangnuo R R S S S S S 71.43 Dianza31 S R R S S S S 71.43 Amoqie S S S S R R S 71.43 Hongjiaogu S S S S R R S 71.43

22. Option 5 (Cont.) 3.51% 59.65% 14.04% 21.05% 1.75% 54.39% 1.75% 12.20% 19.30% 12.20%

23. Three cultivars were R and two cultivars were MR when varieties are inoculated with isolates from Guizhou All the others were susceptible. These five cultivars are traditional cultivars from Yunnan. The twelve cultivars that are more resistant when inoculated with Yunnan isolates are different from the 5 varieties resistant to the Guizhouinoculum. This showed that genetic and pathotypic structure of rice blast fungus population from Yunnan and Guizhou might be different. Option 5 (Cont.)

24. Conclusions 2009 wet; 2010 dry Ochoa et al., 2010, unpublished data Anthracnose Ascochyta ALS Rust 2009 2010 2009 2010 2009 2010 2009 2010 Average 2.98 2.45 4.84 3.54 1.57 3.28 3.88 3.62

25. Conclusions DS of rust Populations plot mixture 48.1 5.0 44.0 29 5.0 48.5 65.1 15.0 6.7 29.1 16.2 62.5 45 21.7 27.5 58.1 22.5 5.0 64 27.5 44.0 28 52.0 8.3 67 52.0 27.5 33 52.0 44.0 21 68.3 33.3 22 71.2 18.8 47 71.2 44.0 65 71.2 46.8 50.1 80.0 6.7 Average 45.0 26.1

26. Theoretical framework Damage abatement framework (Litchenberg&Zilberman, 1986). Banana diversity is treated as a direct input to yield and as an abatement input to yield losses caused by biophysical constraints Econometric estimation approach Non- linear methods, a logistic model specification. Conclusions

27. Banana variety diversity has no direct effect on yield Banana variety diversity reduces the yield losses caused by bio-physical constraints Gender of the farmer, nature of the decision maker, pests and diseases and distance to the tarmac roads influence banana variety diversity on farms Evenness of banana varieties within a plot produces more abatement effects Results (Cont.)

28. THANK YOU FOR YOUR ATTENTION

29. Let’s support diversity

30. Production information: Yield, yield losses, acreage, information on the banana varieties, labor, etc Household characteristics: Age, education, decision making, etc Market characteristics: Distances to markets, roads, buying and selling characteristics Farm characteristics; Slope, soil fertility, soil moisture Results (Cont.)