Article Figures & Data
Figures
- Figure 1.
Map of study sites and survey locations in Machakos, Makueni and Kitui counties in eastern Kenya.
- Figure 2.
Upset plots of who was involved in A) digging the planned comparison planting basins, B) preparing land using farmers usual cultivation practice; C) planting the planned comparison tree seedlings, and D) watering the planned comparison tree seedlings. Upset plots employ a matrix-based layout to show intersections of sets and their frequencies (e.g., data from a multiple response question) (Conway et al. 2017). The bottom left bar chart shows the total number of respondents that selected each answer (set), the dot plot displays the various answer combinations (intersections), and the upper bar chart shows the number of respondents who answered using each combination (intersection size).
- Figure 3.
Gender of those involved in A) digging the planned comparison planting basins, and B) preparing land using farmer’s usual cultivation practice, in each study site.
Tables
- Table 1.
Tree species distributed by the project (Magaju et al. 2020), their uses and environmental and socio-economic benefits (Orwa et al. 2009).
Tree Species Uses and Benefits Total Seedlings Planted Mangifera indica (mango) Fruit, apiculture, timber, firewood, charcoal, shade/shelter, tannin/dyes, medicine, soil improvement: mulch 15,226 Melia volkensii (melia) Timber, apiculture, livestock fodder, pesticide 7,330 Azadirachta indica (neem) Erosion control, medicine, pesticide, timber, fruits, charcoal, shade/shelter, tannin/dyes 5,618 Senna siamea (Siamese senna) Livestock fodder, erosion control, firewood, charcoal, timber, soil improvement: mulch, medicine, shade/shelter, tannin/dyes 3,905 Moringa oleifera (moringa) Vegetable/oil, erosion control, livestock fodder, apiculture, fibre, tannin/dyes, medicine, soil improvement: mulch 1,702 Carica papaya (pawpaw) Fruit, medicine 1,068 Calliandra calothyrsus (Calliandra) Livestock fodder, erosion control, apiculture, firewood, fibre, shade/shelter, soil improvement: nitrogen fixing and mulch 348 - Table 2.
Climatic information for study sites. Statistics presents: mean (SD) annual precipitation (Funk et al. 2015) and annual temperature (Sparks 2018).
Machakos County Makueni County Kitui County Mwala Yatta Kibwezi East Mbooni East Waita Lower Yatta Annual average precipitation (mm) 866.6 (198.4) 710.9 (189.0) 609.9 (166.9) 689.7 (187.0) 768.3 (220.2) 617.9 (163.6) Annual average temperature (C°) 21.2 23.0 25.2 23.1 25.4 23.1 - Table 3.
Gender of study participants involved in the surveys, interviews and focus group discussions in each site.
Machakos Makueni Kitui Mwala (n = 145) Yatta (n = 357) Kibwezi East (n = 322) Mbooni East (n = 189) Mwingi East (n = 582) Kitui Rural (n = 378) Total (n = 1973) Planting basin survey Men 14 7 25 13 20 24 103 Women 26 34 65 62 73 148 408 Tree planting survey Men 33 53 34 44 203 62 429 Women 45 238 158 47 260 116 864 Individual interviews Men 2 4 4 3 3 3 19 Female 8 7 7 8 6 7 43 Focus group participants Men 5 6 7 5 9 9 41 Female 12 8 22 7 8 9 66 - Table 4.
Socio-economic characteristics of farmers participating in the planned comparisons. Statistics presented: count (%) and mean (SD).
Tree Planting Planned Comparison Machakos County Makueni County Kitui County Mwala (n = 78) Yatta (n = 291) Kibwezi East (n = 192) Mbooni East (n = 91) Mwingi East (n = 463) Kitui Rural (n = 178) Total (n = 1293) Gender (women) 45 (58%) 238 (82%) 158 (82%) 47 (52%) 260 (56%) 116 (65%) 864 (67%) Married 66 (85%) 234 (80%) 172 (90%) 67 (74%) 411 (89%) 160 (90%) 1110 (86%) Age 48.9 (12.8) 49.5 (14.2) 43.6 (11.9) 46.2 (12.6) 44.9 (12.7) 44.9 (13.5) 46.0 (13.2) Household size 4.7 (2.7) 5.3 (2.3) 5.4 (1.7) 6.6 (4.0) 6.2 (2.6) 6.1 (2.5) 5.8 (2.6) Farm size (ha) 2.4 (1.4) 2.4 (11.8) 3.1 (3.7) 7.4 (11.3) 4.0 (2.3) 1.8 (1.2) 3.3 (6.8) Primary source of income (farming) 73 (94%) 201 (69%) 158 (82%) 71 (78%) 371 (80%) 163 (92%) 1037 (80%) Secondary source of income (off-farm income) 11 (14%) 74 (25%) 99 (52%) 41 (45%) 116 (25%) 89 (50%) 430 (33%) Estimated distance to main road (km) 2.1 (2.2) 2.3 (2.4) 1.6 (1.7) 1.7 (1.4) 7.0 (5.0) 1.8 (1.4) 3.8 (4.2) Received food aid in past five years 1 (1%) 5 (2%) 7 (4%) 7 (8%) 277 (60%) 64 (37%) 362 (30%) House with a permanent roof 72 (92%) 247 (85%) 160 (83%) 86 (95%) 237 (51%) 109 (61%) 911 (70%) Planting Basin Planned Comparison Machakos County Makueni County Kitui County Mwala (n = 40) Yatta (n = 41) Kibwezi East (n = 90) Mbooni East (n = 75) Mwingi East (n = 93) Kitui Rural (n = 172) Total (n = 511) Gender (women) 26 (65%) 34 (83%) 65 (72%) 62 (83%) 73 (78%) 148 (86%) 408 (80%) Married 34 (85%) 34 (83%) 83 (92%) 65 (87%) 81 (87%) 152 (88%) 449 (88%) Age 51.6 (11.0) 55.3 (14.5) 47.1 (13.4) 45.5 (10.9) 42.9 (7.6) 45.6 (12.1) 46.6 (12.0) Household size 4.0 (2.1) 6.3 (2.6) 5.5 (1.7) 6.7 (4.4) 6.6 (2.3) 6.2 (2.4) 6.0 (2.8) Farm size (ha) 2.2 (2.4) 1.6 (1.1) 3.8 (5.4) 4.5 (5.3) 4.3 (2.3) 1.7 (1.1) 3.0 (3.6) Primary source of income from farming 36 (90%) 22 (54%) 78 (87%) 46 (61%) 73 (78%) 166 (97%) 421 (82%) Secondary source of income (off-farm income) 7 (18%) 7 (17%) 43 (48%) 35 (47%) 28 (30%) 87 (51%) 207 (41%) Estimated distance to main road (km) 2.7 (3.7) 2.3 (2.3) 1.7 (1.3) 1.3 (0.9) 7.1 (4.9) 1.4 (1.1) 2.7 (3.3) Received food aid in past five years 1 (3%) 0 (0%) 22 (24%) 28 (37%) 34 (37%) 60 (35%) 145 (28%) House with a permanent roof 39 (98%) 32 (78%) 74 (82%) 71 (95%) 58 (62%) 113 (66%) 387 (76%) - Table 5.
Those involved in the household’s decision to participate in the planned comparisons. Statistics presented: count (%) and Fisher’s exact test (two-sided). Unmarried includes single, divorced and widowed.
Who decided to be involved in the planned comparison? p-value Myself Jointly Spouse Other Planting basins Married women (n = 345) 209 (61%) 125 (36%) 2 (1%) 9 (3%) < 0.001 Married men (n = 94) 54 (57%) 30 (32%) 8 (9%) 2 (2%) Unmarried women (n = 44) 43 (98%) 0 (0%) 0 (0%) 1 (2%) — Unmarried men (n = 3) 3 (100%) 0 (0%) 0 (0%) 0 (0%) Tree planting Married women (n = 758) 521 (69%) 200 (26%) 23 (3%) 14 (2%) < 0.001 Married men (n = 382) 322 (84%) 48 (13%) 6 (2%) 6 (2%) Unmarried women (n = 106) 104 (98%) — — 2 (2%) 0.587 Unmarried men (n = 47) 45 (96%) — — 2 (4%) Married women Planting basins (n = 345) 209 (61%) 125 (36%) 2 (1%) 9 (3%) < 0.001 Tree planting (n = 758) 521 (69%) 200 (26%) 23 (3%) 14 (2%) Married men Planting basins (n = 94) 54 (57%) 30 (32%) 8 (9%) 2 (2%) < 0.001 Tree planting (n = 382) 322 (84%) 48 (13%) 6 (2%) 6 (2%) - Table 6.
Responses from focus group participants to male and female vignettes on the uptake of new technologies.
Women’s vignettes—attending a training on a new farming practice Men (n = 50) Women (n = 66) Consultation Faith talked to her husband and explained what she had learnt and how it would benefit the farm. He then agreed on trying the new practice and allowed her to make the decisions about it. 76% (38) 80% (53) Veronica also talked to her husband, but he was not convinced because he did not attend the training. She insisted and after a long discussion the husband finally agreed but he then set the conditions for trying the new practice, like where on the farm and with which crops. 6% (3) 11% (7) No consultation Margaret had to ask her husband for permission to apply her new knowledge but he refused immediately without further discussion. She could not try the new practice. 12% (6) 2% (1) Jane went straight to the field and started to try out what she learned. She did not consult anyone. 6% (3) 8% (5) Men’s vignettes—buying tree seedlings from the local nursery Men (n = 54) Women (n = 66) Consultation Alex asked his wife what she thought about buying tree seedlings and which species would be best for their farm and where to plant them. 48% (26) 42% (28) Peter decided to buy the seedlings on his own but asked his wife about which species would be best for the farm and where to plant them. 33% (18) 39% (26) No consultation James also decided to buy the seedlings on his own. He came home and informed his wife about the seedlings and where he was going to plant them. 17% (9) 15% (10) Sammy bought the tree seedlings on his own, came home and planted them. He did not consult anyone. 2% (1) 3% (2) - Table 7.
Gender of those involved in: digging the basins, planting and watering the trees, and preparing land using farmer’s usual cultivation practice, grouped by survey respondents’ gender and marital status. Statistics presented: count (%) and Fisher’s exact test (two-sided).
Gender of Those Who Provided Labor p-value Men Only Men and Women Women Only Digging the planting basins Married women (n = 331) 36 (11%) 167 (50%) 128 (39%) < 0.000 Married men (n = 93) 53 (57%) 40 (43%) 0 (0%) Unmarried women (n = 52) 8 (15%) 13 (25%) 31 (60%) — Unmarried men (n = 3) 2 (66%) 1 (33%) 0 (0%) Farmer’s usual cultivation practice Married women (n = 331) 26 (8%) 210 (63%) 95 (29%) 0.002 Married men (n = 94) 41 (45%) 51 (54%) 1 (1%) Unmarried women (n = 50) 5 (10%) 24 (48%) 21 (42%) — Unmarried men (n = 3) 3 (100%) 0 (0%) 0 (0%) Planting the tree seedlings Married women (n = 701) 132 (19%) 225 (32%) 344 (49%) < 0.000 Married men (n = 359) 305 (85%) 51 (14%) 3 (1%) Unmarried women (n = 122) 12 (11%) 33 (27%) 75 (61%) 0.007 Unmarried men (n = 49) 41 (84%) 8 (16%) 0 (0%) Watering the tree seedlings Married women (n = 678) 22 (3%) 251 (37%) 405 (60%) < 0.000 Married men (n = 352) 268 (76%) 78 (22%) 6 (2%) Unmarried women (n = 124) 8 (6%) 26 (21%) 90 (73%) 0.193 Unmarried men (n = 51) 39 (76%) 12 (24%) 0 (0%) Married women Digging the basins (n = 331) 36 (11%) 167 (50%) 128 (39%) < 0.000 Planting the trees (n = 701) 132 (19%) 225 (32%) 344 (49%) Married men Digging the basins (n = 93) 53 (57%) 40 (43%) 0 (0%) < 0.000 Planting the trees (n = 359) 305 (85%) 51 (14%) 3 (1%) - Table 8.
Reported impact of being involved in the tree planting and planting basin planned comparisons on survey respondent’s time spent preparing land for planting and their overall amount of time spent working on their farm. Statistics presented: count (%) and Fisher’s exact test (two-sided).
Increased Decreased Same p-value Impact of basins on time spent preparing land Married women (n = 345) 268 (78%) 58 (17%) 19 (6%) 0.302 Married men (n = 94) 68 (72%) 17 (18%) 9 (10%) Unmarried women (n = 44) 37 (84%) 2 (5%) 5 (11%) — Unmarried men (n = 3) 1 (33%) 2 (66%) 0 (0%) Impact of basins on overall time on farm Married women (n = 345) 195 (57%) 130 (38%) 20 (6%) 0.050 Married men (n = 94) 55 (59%) 28 (30%) 11 (12%) Unmarried women (n = 44) 24 (55%) 13 (30%) 7 (16%) — Unmarried men (n = 3) 1 (33%) 1 (33%) 1 (33%) Impact of trees on overall time on farm Married women (n = 758) 501 (66%) 49 (7%) 208 (27%) < 0.000 Married men (n = 382) 300 (79%) 19 (5%) 63 (16%) Unmarried women (n = 106) 70 (66%) 6 (6%) 30 (28%) 0.427 Unmarried men (n = 47) 36 (77%) 1 (2%) 10 (21%) Impact on overall time on farm: married women Planting basins (n = 345) 195 (57%) 130 (38%) 20 (6%) < 0.000 Tree planting (n = 758) 501 (66%) 49 (7%) 208 (27%) Impact on overall time on farm: unmarried women Planting basins (n = 44) 24 (55%) 13 (30%) 7 (16%) < 0.000 Tree planting (n = 106) 70 (66%) 6 (6%) 30 (28%) Impact on overall time on farm: married men Planting basins (n = 94) 55 (59%) 28 (30%) 11 (12%) < 0.000 Tree planting (n = 382) 300 (79%) 19 (5%) 63 (16%) - Table 9.
Whether survey respondents planned to dig more basins or plant more trees in the next 12 months. Statistics presented: count (%) and Fisher’s exact test (two-sided).
Yes p-value Do you plan to dig more planting basins next season? Married women (n = 345) 304 (88%) 0.856 Married men (n = 94) 84 (89%) Unmarried women (n = 44) 37 (84%) — Unmarried men (n = 3) 1 (33%) Do you plan to plant more trees next season? Married women (n = 758) 571 (75%) 0.770 Married men (n = 382) 291 (76%) Unmarried women (n = 106) 83 (78%) 0.677 Unmarried men (n = 47) 35 (74%) - Table 10.
Ten most frequently used words by survey respondents when explaining why they did not intend to dig more planting basins (n = 60) or plant more trees (n = 316).
Tree Planting Planting Basins Word Frequency Word Frequency Lack 103 Labor 19 Money 78 Intensive 11 Water 68 Time 11 Maintain 48 Season 8 Purchase 46 Consuming 6 Capital 43 Dig 6 Lacks 40 Man 6 Seedlings 31 Power 6 Buy 28 Tedious 6 Funds 28 Lack 5
