Session 3.1 small farm diversification strategies


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Session 3.1 small farm diversification strategies

  1. 1. March 12, 2014 Small farm diversification strategies by coffee farmers around Mount Kenya in Kenya Sammy Carsan Aldo Stroebel, Frank Place and Ramni Jamnadass Word Congress on Agroforestry, 11th February, 2014. DELHI, INDIA
  2. 2. March 12, 2014 1) Background: Evolution of Kenya’s coffee smallholder sector 2) Study Context: Why coffee agro-forests? 3) Statement of objectives & hypotheses 4) Methods: sampling approach a) Coffee farms typologies 6) Results & Discussions Conclusions Presentation outline
  3. 3. March 12, 2014 • Kenya’s coffee in the past estimated to offer livelihood support to over 5 million people directly and indirectly • Developments summed during and after the ICA market regime • Living standards, incomes, food security in coffee growing negatively • Uncertainties in international market and loss of coffee productivity have affected overall coffee profitability • Are smallholders ready for incentives to shift from traditional cash crop systems? Is AF tree cultivation a good incentive? • How will resource availability and market drivers influence investments on cash crops Evolution of Kenya’s smallholder coffee
  4. 4. March 12, 2014 Compared to robustas the arabica price differential (premium) is about US$ C 60 (s.d 34.63, n = 129) per pound in the last ten years. Mean price for Columbian Milds, New York Composite and Robusta coffee from 2000 to 2010 Source: ICO Statistics, 2010
  5. 5. March 12, 2014 Kenya’s coffee exports fell by over 50% between 2000 and September, 2010; world market share declined from 3.1% in 1986 to 0.6% by 2006 (ICO, 2010). Columbian mild coffee exports by: Columbia, Kenya and Tanzania Source: ICO statistics, 2010
  6. 6. March 12, 2014 • ‘Shaded’ coffee as opposed to open ‘sun’ coffee’-a more sustainable production approach (Mas and Diestch, 2004). Coffee AF systems act as reservoirs of indigenous tree species (Perfecto et al., 2005). Trees yield complimentary products e.g. fruits, timber and firewood which diversify, diet and stabilize farmer incomes • Peeters (2003) :coffee shaded with any density of Cordia alliodora has better benefit-cost ratio than un-shaded estates although yields were lower. Simplifying these systems was disadvantageous even if coffee production increases. • Structurally complex habitats support more diverse fauna (Garcia et al., 2009). • Coffee AF seen as an approaches to build alliances between ecologically sustainable agriculture and conservation efforts in protected areas. Trees contribute ecological services similar to those provided by forest e.g. soil protection, nutrient cycling, water retention and carbon capture (Chazdon et al., 2009). • Farmers benefit culturally by maintaining biological diversity that ensure productivity (Lengkeek et al. 2005). • Genetic diversity helps farmers to manage their inputs in more efficient ways- e.g. a mix of fast growing and slow growing timber grown for different markets; fruit species with different fruiting phenology to contribute to HH food security (Dawson et al., 2009) Coffee agro-forests and sustainability?
  7. 7. March 12, 2014 • To assess how changes in coffee production influences small farm intensification/diversification strategies Hypothesis: • Smallholders with stagnated or decreasing coffee production (yields, density of bushes) support higher enterprise intensification rates with maize, banana, livestock and trees. Study objectives
  8. 8. March 12, 2014 • Cross-sectional survey in three coffee districts of Mt Kenya (Meru , Embu & Kirinyaga) • The zones are comparable on coffee and other crops production practices and largely representative of smallholder coffee systems in Kenya • The regions have strong farmer organization by cooperatives and societies Research Methods
  9. 9. March 12, 2014 • 10 Farmer Cooperative Societies (FCS) covering UM1,2 & 3 in Meru, Embu & Kirinyaga Counties selected • Membership used to draw a random set of farms categorized as either “increasing”, “decreasing” or “stable” • Cherry deliveries for last 5 years (2004-2008) considered • 5 farmers were picked per category selecting 15 farms per FCS, later 2 farms were selected giving 6 farms per FCS. • 60 farms were selected per category comprising 180 farms for the entire survey done from June- August 2009 Sampling strategy
  10. 10. March 12, 2014 • SES data collected: family & land size, labour and non labour costs, distance to markets, coffee size (bushes & cherry), tree inventory, maize & banana value, livestock units (TLU) & daily milk value, fertilizer and manure use, crop diversity, tree basal area, avocado trees • Simple descriptive statistics such as means(s.d) were used to profile household and farm characteristics • Intensification (value/Ha) verified by: coffee bushes, cherry value, no of trees, maize, banana outputs per hectare ad inputs such as fertilizer, manure labour and non labour costs per hectare • Regression analysis: pairwise correlations and GLMs used to assess effects of coffee production ‘trends’ on farm intensification • Response variates were transformed by natural log or square root (after Shapiro Normality tests) • Farm types: increasing, decreasing and stable were used as explanatory variates. Farm size effects were also tested • Fisher’s least significance difference (LSD) was used to compare differences between farm categories at P < 0.05 and P < 0.1 level) • Farm crop diversity was calculated using Simpson Index of Diversification (SID) Farm and HH assessments
  11. 11. March 12, 2014 Farm tree inventories methods • All trees ≥5 cm DBH measured • Tree basal area (tree cross-sectional area measured at breast height) calculated • Local/common names of trees recorded from local farmer consultations • All trees were identified to species level according to Beentje (1994) or Maundu and Tengnäs (2005).
  12. 12. March 12, 2014 Results- Farm crop diversity • Farm crop richness (SID) was 7.1 (s.d=1.71) • Farm with lowest diversity had 2 crop types and one with highest had 12 • The ten most prevalent crops (maize, beans, banana, avocado, macadamia, mango, beans, papaw, irish potatoes and khat) on farms represent 88% of all crop types present on all farms. • Stable farms had higher counts of livestock, banana and avocado; increasing farms had fewer bananas but higher livestock presence while the decreasing ones had smaller enterprise count overall. • Other results showed that crop diversity was strongly and positively associated with farm size but negatively related to fertilizer and TLU ha-1; and maize and banana value ha-1 even though analyzed data was inconclusive with the later.
  13. 13. March 12, 2014 Coffee and trees on farms…? • 75% (156) farms cultivate 250-750 bushes ha-1 • 61%(110) produce 1000-2000 kg cherry ha-1 yr-1 • 41% (75) farms, tree density : 100-200 trees ha-1 • 30% (54) farms: TBA class of 1.1-1.9 m2 ha-1 • 22% (40) farms: TBA class of 2.0-2.9 m2 ha-1 • 35% (66) farms : TBA class of 3-5 m2 ha-1 • Average tree volume : 36.31 (31.1-41.5 ) m3 ha-1
  14. 14. March 12, 2014 Findings: functional coffee farm typology 2101 kg yr-1 (s.d = 1380) 1032 kg yr-1 (s.d = 907) 688 kg yr-1 (s.d = 709). • Farm categories were statistically different (ANOVA test, P < 0.001) • Increasing farms had more bushes than stable (17% , P < 0.05) and decreasing ones (5.5% P < 0.05). Decreasing farms had higher bushes than stable (12.3%, P>0.05)
  15. 15. March 12, 2014 Farms descriptive variables Coffee farm categories and means (s.d) for all variables ‘Stable’ ‘Decreasing’ ‘Increasing’ Rank Maize value ha-1 17843(17955) 19098(19138) 14769(13594) Dec>Stab>Inc Banana value ha-1 48463(78453) 57806(105745) 28416(35768) Dec>Stab>Inc Coffee age years 35.23(12.96) 37.7(12.43) 33.7(11.97) Dec>Stab>Inc Avocado trees ha-1 5.956(8.41) 7.580(15.77) 4.064(4.123) Dec>Stab>Inc AFT Vol. ha-1 30.4(20.4) 34.4(38.1) 32.4(21.6) Dec>Incr>Stab Family size 4.9(2.5) 4.8(2.2) 5.3(2.2) Inc>Stab>Dec Land size (ha) 1.3(1.3) 1.1(0.84) 1.4(0.97) Inc>Stab>Dec Cherry/bush (Kg) 4.4(3.2) 3.84(3.7) 4.63(2.53) Inc>Stab>Dec Cherry value ha-1 61180(58526) 47220(49604) 69587(54482) Inc>Stab>Dec Milk value day-1 118(119.4) 94(112.4) 152.3(143.8) Inc>Stab>Dec Coffee bushes ha-1 499.7(379.1) 569.6(694.5) 601.6(497.4) Inc>Dec>Stab TLU Ha-1 5.38(5.5) 4.26(4.9) 3.87(2.9) Stab>Dec>Inc AFT ha-1 229(223) 202(152) 182(99) Stab>Dec>Inc Macadamia trees ha-1 18.04(27.6) 16.89(19.81) 13.52(18.02) Stab>Dec>Inc Mango trees ha-1 10.54(24.53) 7.57(8.678) 5.65 (9.68) Stab>Dec>Inc Farms and households characteristics
  16. 16. March 12, 2014 Farms input sizes • Fertilizer use ha-1 increases significantly (P < 0.05), with the coffee bushes, maize value, manure, TLU; but is negatively related to farms crops diversity and distance to market. • Manure application ha-1 was positively associated with coffee bushes, TLU and banana value. Manure application was negatively related to farm crop diversity. • Labour expenditure were positively correlated to fertilizer, manure, coffee bushes and negatively related to market distance and crop diversity. • Fertilizer and manure application were negatively correlated to farm sizes (P < 0.05).
  17. 17. March 12, 2014 General linear regressions coefficient for various ‘intensification’ variables against farm categories and farm size LSDs: Increasing vs Stable (*); Increasing Vs Decreasing (+); Decreasing Vs Stable (#). Significant difference level: P<0.01(*** +++ ###); P< 0.05(** ++ ##); P<0.1 (*+ #)
  18. 18. March 12, 2014 Small coffee farms intensification • Comparisons: cherry value, milk value, avocado trees, fertilizer, labour, non- labour costs were used to gauge levels of farm intensification. • Cherry value by the increasing farms was significantly bigger (P < 0.05) than the decreasing ones but not for the stable ones. While value for the decreasing farms was significantly lower (P < 0.1) compared to the stable farms. • Daily milk value by the increasing farms was significantly bigger (P < 0.05) than the decreasing (38.3%) and stable (22.5%) ones. The stable farms milk value was not significantly higher (P>0.1) compared to the decreasing (20%) ones. Other results confirmed that milk outputs could be increased in bigger farms. • Surprisingly, results showed that maize value increases significantly with farms TBA, no. of coffee bushes and banana value, but negatively related to farm and household size. • The no. of avocado tree ha-1 were significantly higher (P < 0.05) in the decreasing (46%) and stable (32%) compared to the increasing ones. Findings further showed that avocado intensification is significantly reduced in bigger farm sizes. • Finally, findings revealed that cherry value and coffee bushes ha-1 was significantly (P < 0.001) smaller in bigger farm sizes.
  19. 19. March 12, 2014 • Annual labour costs were significantly higher (P < 0.1) for increasing farms compared to the stable (30.2%) and the decreasing ones (24.4%). Labour costs for the decreasing farms were not significantly higher (P>0.01) than the stable ones (7.7%). • Other non-labour costs such as pesticides and seeds for the increasing farms were significantly bigger (P < 0.05) compared to the stable (14.2%) and decreasing ones (12.9%). Non labour costs were not significantly (P > 0.1) higher in the decreasing (1.4 %) farms compared to the stable ones. • Fertilizer use was significantly higher (P < 0.05) for the increasing farms compared to the stable (33.9%) and the decreasing ones (27.9%). Fertilizer use on decreasing farms was not significantly higher compared to the stable (8.4%) ones. Small coffee farms intensification
  20. 20. March 12, 2014 Discussion points • Findings showing that coffee is significantly reduced in bigger farm sizes suggests that input affordability, negatively related to farm size, could limit future plans on coffee expansion. • Farms decreasing or stable in coffee production are characterized by more trees, banana, and maize while those with increasing coffee have bigger dairy milk enterprises • Smaller land sizes accelerates farm intensification with trees, coffee, banana, maize and livestock enterprises while crop diversification is significantly enhanced by bigger land sizes. • Fertilizer use increases significantly with the no. of coffee stems, maize value and amount of manure applied; however distance to markets have a negative correlation with fertilizer use • Manure use is positively associated with labour costs, coffee bushes, TLU and banana value but significantly reduced with higher farm crop diversity • Labour costs can significantly affect fertilizer & manure use implying higher costs could seriously influence farm nutrient status
  21. 21. March 12, 2014 • Farmer intensification/diversification interests with lower input but higher return crops such as avocado shown to be significantly bigger in decreasing and stable farms compared to the increasing ones. • Farmers that can’t afford high costs of maintaining coffee production opt for crops that provide food security (maize, banana). They also have higher levels of livestock units and trees to serve as self- insurance for the household. • Measures such as the no. of avocado trees and milk output (dairy activities) per farm were useful indicators to discern farm productivity differences rather than total tree and livestock counts per farm • It was clear that inputs such as fertilizer are tremendously reduced with declining coffee production raising concerns that small coffee farms could decline to low productivity systems. • These trends would probably change with a high profitability shift in coffee. It is therefore critical that policy makers are aware of these trends in order to support enterprises that are attractive to farmers. Concluding remarks
  22. 22. March 12, 2014 Thank you for your attention!