Transcript www.bioecon-network.org

A Metapopulation Approach to
Farmer Seed Systems
M. Eric Van Dusen
Ciriacy-Wantrup Post-Doctoral Fellow
UC Berkeley
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…
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
Zoatecpan, Puebla – infra-subsistence production,
small landholdings, contiguous maize plots
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
Private Traders – 40 tons of maize
direct from the US border at Laredo
Government maize supplies –
hundreds of tons per week…
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
Participatory Breeding – new emphasis on techniques to integrate
with local practices, focus on local selection behavior, target
marginal conditions and marginal farmers
Evolution of Meta-population theory
MacArthur and Wilson (1967)
Levins (1969)
Mainland - Island
Meta-Population
Bio-geographic Model
Ecological Model
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
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)
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
Case Study : Mexican milpa system
• Survey Sample
– 280 HH
– 24 villages
– 2 ecological zones
• Social – Economic module
• Seed System module
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
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
Geneflow - Pollen Drift
Field 1
Field 2
Field 3
• Contamination decreases with distance
• Field size determines level of exposure to pollen drift
Geneflow – pollen drift
40%
Percent of HH with maize
area
12%
Percent contaminated
Contaminated Area
10%
35%
30%
25%
8%
20%
6%
15%
4%
10%
2%
5%
0%
0%
2500
5000
10000
Maize area in m^3
20000
30000
Percent of Population
14%
Effective Population Size
Selection Behavior
Select in field
Percent of Farmers
% 1
Select in storage
%
99
Select at harvest
Select during the year
%
%
27
18
Select at planting
%
55
Selected by man
Selected by woman
%
%
47
20
Selected by both
%
33
Effective Population Size
Minimum number of ears selected
400
0.4
Percent of land area
0.35
Number of Ears
300
0.3
250
0.25
200
0.2
150
0.15
100
0.1
50
0.05
0
0
2500
5000
10000
Maize area in m^3
20000
30000
Percent total population
Number of Ears
350
Turnover Rate
Age of Maize Seed Lots by type
Years
0-5
5-10
10-15
15-20
20-25
>25
Totals
White
42
32
17
12
2
115
220
19%
15%
8%
5%
1%
52%
Yellow
11
2
4
2
1
27
47
23%
4%
9%
4%
2%
57%
Blue
Total
4
21%
57 20%
1
5%
35 12%
1
5%
22
8%
1
5%
15
5%
0
0%
3
1%
12
63% 154 54%
19
286
Source of seed by type
White
Yellow
Blue
Father
45%
56%
68%
Village
52%
40%
32%
Other
3%
4%
0%
Crosstabulation: Source versus Age
Age 0 to5
Age 5 to 25
Age > 25
Totals
Father
Neighbor
Other
Totals
40
24
71
99
37
36
42
115
2
3
1
6
43
63
114
220
Turnover Rate
Age and Origin of Bean Seed
Years
0-5
5to20
>=20
Source of Seed
Father
Same Village
Other Village
N
Ph
Ph
Polyanthus Vulgaris
(bush)
25%
40%
14%
19%
61%
40%
40%
47%
13%
104
33%
45%
21%
42
Ph
Ph
Other
Vulgaris Coccineus
(vine)
10%
33%
36%
10%
33%
18%
81%
33%
45%
43%
48%
10%
21
33%
50%
17%
6
27%
36%
36%
11
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
Age 0 to5
Age 5 to 25
Age > 25
Totals
Last time seed renewed
0 to 5
5 to 25
> 25
Totals
33
1
9
43
27
23
13
63
59
4
51
114
119
28
73
220
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
Summary Statistics
Tobit Regresion
Age of Seed Lots
Tobit Regresssion
Total Varieties Planted
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
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
Three scales of analysis
and 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]
How many populations can you see in this picture?