Hypothesis based typologies for capturing diversity by Descheemaeker et al
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Transcript of Hypothesis based typologies for capturing diversity by Descheemaeker et al
Hypothesis based typologies for capturing diversity
Stephanie Alvarez, Wim Paas, Katrien Descheemaeker, Jeroen Groot
Wageningen University, Farming Systems Ecology & Plant Production Systems groups
Humidtropics
Aim of typologies:
- Capture variability of farming systems
- Understand heterogeneity in regions
Introduction
Hengsdijk et al., 2014; N2Africa report – 2 action sites in Kenya
Franke et al., 2014
Aim of typologies:
- Capture variability of farming systems
- Understand heterogeneity in regions
For
1. Targeting and tailoring
2. Scaling out; dissemination
3. Selection of representative farms
4. Scaling up; extrapolate to larger scale
Introduction
Major steps:
1. What is the objective?
2. Hypothesis on farming systems
diversity
3. Data collection
4. Selection of key variables
5. Clustering the farms
6. Hypothesis and typology verification
Overall:
Combine expert knowledge from
participatory work with statistical
analysis
Guidelines
Major steps:
1. What is the objective?
Specific: Improve forage production in
mixed systems of Rwanda
Broad: Improve food security in the
humid tropics
Guidelines
Major steps:
2. Hypothesis on farming systems
diversity
Participatory process for ex-ante
description of farm types ; identification
of discriminating criteria
Guidelines
Major steps:
3. Data collection
4. Selection of key variables
Variable categories:
- Structural vs. functional characteristics
- Resource availability vs. management
- Biophysical vs. socio-economic
- Farm vs. external
key variables: 5 - 46, av. 15
sampled farms: 18 – 2746, av. 138
#farms > 5 * #variables
Guidelines
Major steps:
5. Clustering the farms
Guidelines
Major steps:
5. Clustering the farming systems
a. Multivariate statistics
(PCA, MCA, MFA)
Discriminating variables
Guidelines
Guidelines
Major steps:
5. Clustering the farming systems
a. Multivariate statistics
(PCA, MCA, MFA)
Discriminating variables
b. Cluster analysis
Major steps:
6. Hypothesis and typology verification
Guidelines
Major steps:
6. Hypothesis and typology verification
Example from Ghana – participatory and statistical approach
Guidelines
Poster, Katja Kuivanen et al.
Major steps:
1. What is the objective?
2. Hypothesis on farming systems
diversity
3. Data collection
4. Selection of key variables
5. Clustering the farms
6. Hypothesis and typology verification
Guidelines
coffee >35%
grazing land>20%
khat>30%
enset>35%
Classification trees and trends
Homegarden types in Ethiopia
Khat Enset-cereal
Enset Enset-coffee
Enset-livestock
Khat Enset-cereal
Enset Enset-coffee
Enset-livestock
Are
a sh
are
of
khat
(%
)
Are
a sh
are
of
coff
ee (
%)
Khat Enset-cereal
Enset Enset-coffee
Enset-livestock
Are
a sh
are
of
ense
t (%
)
Are
a sh
are
of
graz
ing
lan
d (
%)
Khat Enset-cereal
Enset Enset-coffee
Enset-livestock
Farms
4 types
Enset-coffee
3 types
Enset-livestock
2 types
Enset-cereal-vegetable
Enset
Khat
khat
>30%
coffee
>35% Grazing
land>20%
Enset
>35%
1991 2013 20132 2 12 2 12 2 12 2 12 2 12 2 12 2 12 2 12 2 12 2 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 3 12 3 12 3 12 3 12 3 12 3 12 3 12 3 12 3 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 1 12 1 12 12 12 12 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 44444 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 3 44 3 44 3 44 3 44 3 44 34 34 34 3 54 3 54 3 54 3 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 1 54 1 54 1 54 1 54 1 54 1 54 1 54 1 55553 2 53 2 53 5 53 5 53 5 53 5 53 5 53 5 53 3 53 3 53 3 53 3 53 3 53 4 53 4 53 4 53 4 53 4 53 4 53 4 53 4 53 4 53 43 43 43 4 23 4 23 4 23 4 23 4 23 4 23 4 23 4 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 22225 2 25 2 25 2 25 2 25 2 25 2 25 5 25 5 25 5 25 5 25 5 25 5 25 5 25 5 25 5 25 5 25 5 25 3 25 3 25 35 35 45 4 35 4 35 4 35 4 35 4 35 4 35 4 35 4 35 1 35 1 35 1 35 1 35 1 35 1 35 1 35 1 35 1 35 1 35 1 33331 1 31 1 31 1 31 1 31 1 31 1 31 1 31 1 3
Enset
Enset-
livestock
Enset-
coffee
Enset-
cereal-
vegetable
Khat
1991 2013 20132 2 12 2 12 2 12 2 12 2 12 2 12 2 12 2 12 2 12 2 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 5 12 3 12 3 12 3 12 3 12 3 12 3 12 3 12 3 12 3 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 4 12 1 12 1 12 12 12 12 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 42 1 44444 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 2 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 5 44 3 44 3 44 3 44 3 44 3 44 34 34 34 3 54 3 54 3 54 3 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 4 54 1 54 1 54 1 54 1 54 1 54 1 54 1 54 1 55553 2 53 2 53 5 53 5 53 5 53 5 53 5 53 5 53 3 53 3 53 3 53 3 53 3 53 4 53 4 53 4 53 4 53 4 53 4 53 4 53 4 53 4 53 43 43 43 4 23 4 23 4 23 4 23 4 23 4 23 4 23 4 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 23 1 22225 2 25 2 25 2 25 2 25 2 25 2 25 5 25 5 25 5 25 5 25 5 25 5 25 5 25 5 25 5 25 5 25 5 25 3 25 3 25 35 35 45 4 35 4 35 4 35 4 35 4 35 4 35 4 35 4 35 1 35 1 35 1 35 1 35 1 35 1 35 1 35 1 35 1 35 1 35 1 33331 1 31 1 31 1 31 1 31 1 31 1 31 1 31 1 3
Khat
Enset-
livestock
Enset-
cereal-
vegetable
Enset
Enset-
coffee
Classification trees and trends
31%
30%
19%
17%
3%
24%
24%
21%
18%
13%
Spatial organization of farm types
Type Main characteristics
1 HRE, large cattle herd, ample off-farm activities
2 MRE, large farms, market orientation
3 MRE, small ruminants, on-farm labour intensive
4 MRE, small ruminants, ample hired labour
5 LRE, maize dominated, few off-farm activities
6 SRC, livestock sales, ample off-farm activities
Katja Kuivanen
Small & medium farms
Small ruminants
Market oriented
farms
High resource
endowed farms
Statistical background and examples
Appendix C of the report
R code to explore the data and run the analysis
Tips for interpretation of statistical results
Conclusions
Typology guidelines: 6 steps, no recipe book
Interpretation of results ; degree of subjectivity
Combine statistical methods with participatory work
Thank you
https://humidtropics.cgiar.org/constructing-typologies-to-capture-farming-systems-diversity
http://humidtropics.cgiar.org/openaccess/?did=231