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Farm typologies and resilience: household diversity seen as alternative system states. Pablo Tittonell
 

Farm typologies and resilience: household diversity seen as alternative system states. Pablo Tittonell

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A presentation from the WCCA 2011 event held in Brisbane, Australia.

A presentation from the WCCA 2011 event held in Brisbane, Australia.

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    Farm typologies and resilience: household diversity seen as alternative system states. Pablo Tittonell Farm typologies and resilience: household diversity seen as alternative system states. Pablo Tittonell Presentation Transcript

    • Farm typologies and resilience:Household diversity seen asalternative system statesPablo Tittonell1,21Centre de coopération Internationale en Recherche Agronomique pour le DéveloppementMontpellier, France2Tropical Resource Ecology Program, University of Zimbabwe, Harare Farming Systems Design September 27, 2011 Brisbane, Australia
    • Introduction Farm typologies (i) Aim at categorising diversity in livelihood strategies and/or levels of household resource endowment; (ii) Used in a diversity of applications (research, policy, monitoring and evaluation, econometrics, etc.); (iii) Should respond to the objectives of the study/ intervention; (iv) Often used as the basis for scaling-up/ scaling out-approaches; (v) Different methods are used to categorise household diversity: statistical clustering, participatory rankings, expert knowledge, etc. Structural Based on resources and asset levels Functional Livelihood strategies and household dynamics
    • Structural typologies Smallholder households in NE Zimbabwe Farm type Farm size # Livestock # Scotch Maize yield (ha) carts (t ha-1) Poor 20 < 0.7 0 None 0.2 – 1.0 Clustering (e.g. multi-dimensional scaling) Medium 0.7 – 1.2 2–4 1 1.0 – 1.2 40 Rich > 1.2 4 - 22 2 2.0 – 3.5 50% similarity Within-group similarity (%) 60 80 100 Farm samples
    • Functional typologies • Resource endowment (allocation pattern) • Production orientation (subsistence, markets) • Livelihood strategy (e.g., access to non-/ off-farm income) • Household structure (position on farm development cycle) • Household dynamics (where do they come from/ go?) Dependence on off-farm income Hypothesis: - + + + Different household types may be Type 2 as alternate states of the Rich seen farms same system (in this case, the smallholder rural livelihood system) + Type 1 + Resource endowment Resource endowment farms Market orientation This may allow: Fo od s elf Type 3 su Medium • Understanding the nature and resilience of poverty trapsy ffic ien c farms • Analysing possible shifts (or not) between household types in response to Type 4 farms - e.g. poverty alleviation measures, market or climatic scenarios, etc. - Type 5 Poor farms - -
    • Underlying assumptions about household diversity Farm productivity Smallholder farming systems A) No alternate regimes arms B) Two alternate regimes B B fState of capital stock (fast variable) tock State of capital stock (fast variable) - L ives Syst em state I - Hysteresis Threshold A A + ‘Destocking’ + I ‘Stocking’te I Syst em s ta Underlying (controlling) variable Underlying (controlling) variable Assumptions: Assumptions: Policies and development Moving form A to B may not be so interventions may impact on the farms easy; these are two alternative right driving variables to move -lives tock system regimes; interventions need gradually from A to B Non to provoke a ‘jump’ (hysteresis) A threshold may be there… Discontinuity, irreversibility… Resources
    • Livelihoods aspirations and strategies of the poor Dorward (2009) • People aspire to maintain their current welfare and to advance it • Expanding their existing activities and/or moving into new activities ‘Hanging In’: assets are held and activities engaged in to maintain livelihood levels (adverse socio-economic circumstances) ‘Stepping Up’ current activities engaged in, with investments in assets to expand these activities, to increase production and income to improve livelihoods ‘Stepping Out’ activities engaged in to accumulate assets which in time can provide a ‘launch pad’ for moving into different activities – e.g. accumulation of livestock as savings to finance children’s education
    • Western Kenya 1000 inhabitants per Km2
    • Heterogeneity and landscape dynamics Farm developmental cycle (Forbes, 1949)Resources Maturity h De wt o cli gr ne nd an ta d Maintaining & en dis m reproducing so sh resources; bli lut ta ion production Es Expanding • Formerlyfamily & household that has been subdivided as the children married a single may exceed Sub-dividing consumption land resources Time (life cycle) Tittonell et al., Ag Sys 2007
    • A functional typology for East African highland systems Type 1 Type 3 MKT LVSTK FOOD MKT CSH CNS HOME OFF-FA RM OE Wealthier households Mid-class to poor households CSH WOOD LVSTK Type 2 Resource HOME CSH allocation CNS WOOD strategies MKT LVSTK Type 4 MKT LVSTK CNS CNS FOOD HOME FOOD HOME OFF-FARM WOOD WOOD Type 5 Cash MKT FOOD Labour CNS HOM E OFF-FARM Nutrients WOOD CSHTittonell et al., AGEE 2005a,b
    • Functional farm types and system states Performance (well-being) T2 T1 ‘Stepping out’ P’’ ‘Stepping up’ T3 P’ T4 ‘Hanging in’ T5 R’’ R’ Resources (natural, social, human)
    • 100 40 Total hous IncomeIndicators of ‘resources’ and ‘performance’ Total household income (kSh yr ) -1 120 300 Household type 1 Income per capita (kSh yr ) 50 20 -1 Household type 2 250 100 Household type 3 Household type 4 200 80 Household type 5 0 0 300 120 0 1 2 3 4 5 0.0 0.4 Total household income (kSh yr ) 150 60 System state II -1 Income per capita (kSh yr ) -1 6 250 1.0 100 2 t ha-1 40 Food production per capita (t dm) 100 Stepping out Food production (t dm farm-1) 1 us$ day-1 50 5 20 200 0.8 80 0 1 t ha-1 0 0 4 1 2 3 4 5 0.0 0.4 0.8 1.2 150 0.6 60 6 -1 2 t ha 120 1.0 Food production per capita (t dm) 3 Household type 1 Food production (t dm farm-1) 100 40 come per capita (kSh yr ) 5 -1 0.8 Household type 2 100-1 0.4 1 t ha Household type 3 4 2 50 0.6 20 Household type 4 3 80 0.2 Household type 5 1 0.4 0 0 2 System state 1 0 I 602 3 4 5 0.0 0 0.0 0.2 1 0 1 2 Cropping land (ha) 3 4 5 0.0 0.4 Self-sufficiency 6 -1 1.0 Cropping landt (ha) 40 2 ha (t dm) 0 0.0 Land rm-1) 0 1 2 3 4 5 0.0 0.4 0.8 1.2 5 Cropping land (ha) Land:labour ratio 1 us$ day-1 0.8 20
    • Testing across a wider range of systems (Market orientation) % % area allocated to cash crops(Market orientation) area allocated to cash crops Meru S. Meru S. Vi ab le Mbale f ar Mbale m siz e s Desirable effect of intensification Agroecological potentialPopulation (People per Km2) Mi Mbeere 0-2 nim Mbeere 3 - 10 um far 11 - 20 Vihiga m Mbale siz Tororo 21 - 50 Vihiga es 51 - 100 Siaya Tororo 101 - 200 Siaya Meru S. 201 - 500 501 - 1000 Vihiga >1000 % area under fallow % area under fallow (Traditional management) Siaya (Traditional management) Tororo Mbeere Mark opport et unities ion lat y pu t Po ensi Tittonell et al., AgSys 2010 d TSBF, 2007
    • Concluding remarks • There is ample potential to bring ‘down to earth’ the attractive concepts around resilience thinking for use in the context of farming systems research • A promising entry point: Farm typologies seen as alternative states of a given rural livelihood system •This challenges a few assumptions: the existence of thresholds, continuity, reversibility, and the use of classical socio-economic indicators to cluster similar groups out of large household surveys • Poverty traps become evident: improving livelihoods (i.e. facilitating a shift upwards) does not necessarily imply more ‘resources’ (e.g. agricultural inputs, livestock or more efficient technologies) • Will this always work? Where not, why? More research is needed…Pablo.tittonell@cirad.fr Thanks for your attention