A Metapopulation Approach to Farmer Seed Systems

1. A Metapopulation Approach to Farmer Seed Systems M. Eric Van Dusen Ciriacy-Wantrup Post-Doctoral Fellow UC Berkeley

2. Metapopulation …a set of local populations which interact via individuals moving among populations… -Hanski and Gilpin (1991) Farmer Seed System …a set of farmers whose crop varieties are related through the exchange of seeds…

3. Seed Systems – In Situ Conservation • Move from targeting individual farmers to larger spatial scales of communities and regions • Environmental heterogeneity limits the extent of genetic erosion • landraces survive in niches • In Situ conservation is dynamic, encompassing evolutionary processes

4. Zoatecpan, Puebla – infra-subsistence production, small landholdings, contiguous maize plots

5. Seed Systems – Biosafety • Escape of transgenes in Mexico • How did it get there? • Possible Impacts and Containment • Selection Pressures, Selection Practices • Mixing with Local materials • Biosafety for future releases • How far does material travel? • Document farmer practices

6. Government maize supplies – hundreds of tons per week… Private Traders – 40 tons of maize direct from the US border at Laredo

7. Seed Systems – dissemination of improved materials • Green Revolution gains limited by low varietal turnover rates • Farmer-to-Farmer exchange fundamental to dissemination in many areas • Move towards participatory approaches, especially to reach marginal environments • Robust approaches to disaster seed relief

8. Participatory Breeding – new emphasis on techniques to integrate with local practices, focus on local selection behavior, target marginal conditions and marginal farmers

9. Evolution of Meta-population theory MacArthur and Wilson (1967) Mainland - Island Bio-geographic Model Levins (1969) Meta-Population Ecological Model

10. Metapopulation characteristics • Patchiness of the environment • Heterogeneity of landscape creates ecological niches, where certain species dominate • Local extinction possible • As long as there is some degree of migration, local extinction in any given patch is possible • Extinction Debt – present but declining • Genetic Rescue – add enough variability to make patch viable • Colonization of empty patches • Distance and distribution of patches matters • Successful establishment can depend on other factors

11. Crop meta-populations • Individual farmers manage local populations, and are linked through seed exchange and gene flow • Seeds are adapted to local agro-ecological conditions (patchiness) • Farmers experience loss of seed (local extinction), but this is mitigated through seed exchange (migration) • Varieties may compete for the same land area for in situ conservation (habitat fragmentation)

12. Biology matters • Self pollinated - Wheat, Rice • Exchange seed without loss of quality • Seed remains relatively pure • Geneflow less common • Open Pollinated – Maize • adapt to local conditions • high diversity within one seed lot • Geneflow through pollen

13. Case Study : Mexican milpa system • Survey Sample • 280 HH • 24 villages • 2 ecological zones • Social – Economic module • Seed System module

14. Extinction parameters(i.e. my dissertation) • Household-Farm model of activity choice • Link diversity outcomes to economic forces • Nest household, agro-ecological and market models • Major versus Minor Crops • Varieties: blue and yellow maize • Species: intercropped beans and squash • Land area, agro-ecological conditions drive maize diversity • Household characteristics, market integration, labor intensity impact secondary crop diversity

15. Migration parameters to derive from household data • Geneflow • Pollen • Seed sample size – drift, inbreeding, mutations • Turnover Rate • Age of Seed Lots • Loss, Change, Replacement • Exchange • Within community • Within ecological region

16. Field 1 Field 2 Field 3 Geneflow - Pollen Drift • Contamination decreases with distance • Field size determines level of exposure to pollen drift

17. Geneflow – pollen drift

18. Effective Population SizeSelection Behavior

19. Effective Population SizeMinimum number of ears selected

20. Turnover Rate Age of Maize Seed Lots by type

21. Source of seed by type Crosstabulation: Source versus Age

22. Turnover Rate Age and Origin of Bean Seed

23. How old is a seed lot, really? Q1- How long have you had the seed you are currently planting? Q2 – When is the last time you renewed your seed? Crosstab: Age vs Renewal

24. Econometrics • Link seed age to socio-economic factors • Tobit: age of seed lots (censored at >25) • Nest household, farm, market conditions • Other specifications on • Logit: who holds seed forever, who replaces frequently • Duration Model – Semiparametric specs

25. Summary Statistics

26. Tobit Regresion Age of Seed Lots

27. Tobit RegresssionTotal Varieties Planted

28. Directions for Future Research • Build simulation model with empirical parameters • Compare across crops and regions • Build different scenarios for diffusion, conservation, genetic escape • Incorporate genetic data

29. Cases • Contamination - Spread of Gene into local population • Solve for Rate under a) selection b) no selection • Drift – Accumulation of Mutations - • Solve for Effective Population size / Renewal Rate • Spread of Improved Materials • Solve for rate of adoption/ diffusion

30. Three scales of analysisand parameters for model 1) Farmer and Field Contamination Rate Field Size [0.1-2 ha] Inflow Rate [0.001 – 0.005] Shape of Field [Square, Rectangle…] Rate of Deleterious mutations [0.001 – 0.01?] 2) Group of Farmers in Village Field Size [0.1-2 ha] New Seed renewal Rate [1-2 Farmers/Village/Yr] Seed Age Classes [0-5 yrs, 5-25 yrs, >25 yrs] Spatial Configuration [lattice, hub-spoke, non-scaling] 3) Group of Villages Rate of Exchange between villages [1-5%] Spatial Configuration [lattice, hub-spoke, non-scaling]

31. How many populations can you see in this picture?