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TREE SURVIVAL COUNT-CARE AGROFORESTRY EXTENSION PROJECT (A Survey Conducted In Siaya and South Nyanza)

TITLE

TREE SURVIVAL COUNT -CARE AGROFORESTRY

EXTENSION PROJECT

(A SURVERY CONDUCTED IN SIAYA AND

SOUTH NYANZA DISTICTS)

PREPARED BY Nyamai Daniel Kimondo James

Edited. by Nyamai Daniel

Field Survey carried by KEFRI and Sponsored by CARE. May, 1988

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CONTENTS

1. Background

2. Methodology used in determining survival rates

3. Description of the general land use

4. Geology

5. General observations

6. Results and Discussion

7. General conclusions and recommendations

8. References

3

ACKNOWLEDGEMENTS

We wish to thank all the Lake Basin Development Authority.

Officials in Kisumu office who assisted us during the survey by providing us

with information and documents on land use, physical characteristics of the

area and socio-economic aspects. We also wish to thank the Director KEFRI for

realizing KEFRI staff to conduct the survey.We are most thankful to all the

farmers who spent time answering our questions and taking us round the farms.

We are grateful for the CARE agroforestry extension project staff who made

necessary arrangements to enable us meet the farmers. This survey was financed

by CARE for which we are grateful. This document was typed by Lucy Kirori.

We wish to thank her very much.

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BACKGROUND This report describes a tree survival count exercise covering 1986 ,and 1987

planting seasons in Siaya and South Nyanza where CAREis currently involved in

agroforestry extension. The survival count was conducted by KEFRI upon the

request by CARE to evaluate the survival rates of different species planted in

various ecozones.

At the time of this survey,(March 1988) there were 230 women groups and

200 schools in Siaya District and 64 women groups and 100District participating

in different schools in South nyanza agroforestry systems in different

ecological zones. However,thesurvey revealed that not all these groups and

schools were activelyinvolved in tree planting. The inactive groups (herein

defined asthose already registered with CARE but were still at the nursery

stage raising seedlings for the 1988 planting seasons and/or have planted out

but abandoned their nurseries and tending of the seedlings) were not considered

in this survey.

The survey further showed that each group visited had at least 5 members

who had planted a reasonable number of the various tree species. Sampling of

the members to determine survival rate therefore concentrated on members with

acceptable number of tree Species planted. In both districts, sampling was

carried out along administrative divisional boundaries, which closely followed

the agro-ecological zones. However, as neither all the schools nor the groups

irrespective of the district or ecozones had the same number of schools and

groups participating, the number sampled from each depended on the proportion

of the total schools and groups in each of them ~proportional stratified random

sampling).

One important item noted in this survey is that while CARE agroforestry

extension project was set with agroforestry extension services in mind rather

than research, the fact that several tree species are involved gives it the

dimension of tree species trial experimentation.

This report briefly describes- the methods used in carrying out the

survey, analyses the constraints encountered and summarizes the results and

culminates into a discussion.

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METHODOLOGY USED IN DETERMINING SURVIVAL RATES

The land use systems upon which this project is sited invariably includes

several agroecological zones and different socio-economic structures, and

therefore it was essential to delineate the areas sampled on the basis of

ecozones and the location (District).

specific objectives

The specific objectives of the sampling methodology adopted were as follows:

1.To obtain maximum information relating to the various interacting factors

affecting tree survival so as to verify and sharpen the survival results.

2.Random sampling: this was carried out to give each group or school an equal

chance of selection to assure unbiased estimates of determining mean survival

rates and sampling error.

3.To adopt a sampling intensity/strategy for each group (schools and groups)

that allows no more than 10% sampling error at 5% probability level and also

takes into account the proportion of the total schools and groups involved

(proportional stratified random sampling).

4. To determine the present niches (locations of tree planting on farms),

management practise and farmers perceptions of tree/shrubs in their farms and

their effects or survival rates.

Classification of the areas sampled into axro ecoloRical zones

The division of the areas in Siaya and South Nyanza Districts into

_.agroclimatic/ecological zones was derived from Kenya Soil map..Lake Basin

Development Authority (Five Year Development Plan: 1983-1988) and ICRAF (1987).

all of which are based on rainfall and potential evapo-transpiration. The

survey team decided to focus this exercise in schools and women groups

considered to be representative as much as possible while at the same time take

into consideration other factors such as appropriate infrastructural and

logistical conditions to meet the operational requirements.

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Reviews of backRround information and pre-survey informations

The first methodological step implemented by the survey team examined the

following factors and activities:

1.Review of background information pertainingto the CARE-agroforestry extension

project with special emphasis on the Micro D and D methodology conducted prior

to the implementation of the project in Siaya. Other documents consulted

includes soil maps. agroecological maps and vegetational maps covering Siaya

and South Nyanza (Sources: Kenya Soil map and Lake Basin Development

Authority).Other working documents and government departmental annual reports.

2.Desk analysis based on the information derived from the various documents

mentioned in 1 above. The analysis focused more on the description.

identification and rough classification of key problems likely to affect tree

survival rates. with preliminary quantification of the implications of the

different agroforestry technologies practiced.

3.Informal discussions with some of the farmers in Siaya for a feedback as well as to

interact with CARE - field officers and extension staff for more information regarding the

exercise.At this stage, significant progress had been achieved by the survey team in

understanding the survey. key constrains and other aspects that relate to it. However,

specific issues and information gaps were identified. These were further examined and

analysed at the individual and school level depending on the prevailing circumstances

thereof.

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Formal Survey

A structured questionnaire was developed and field tested to collect data on

pre-planting and post-planting treatments. method of planting. material planted

and the location of planting (see annex 1 for details).

To select a representatibve sample of schools and groups in each ecozone a

random sampling allowing for a 10% sampling error at 5% probability level was

adopted using a crude form of area frame procedure. Within the delineated

ecozones the desired number of sample schools and groups were randomly selected

(see Tables 1-2).No other pre-determined criteria of group/school

indentification was used. Sample size was determined according to the

proportion of the Table land 2. Distribution of Schools and Women Groups

Participating in CARE-Supported Agroforestry Extension Project in Siaya and

S.Nyanza Districts.

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Table 1

SIAYA DISTRICT

Division Number of schools Number of women Groups

Yala 8(2) 8 (2) /12/

Ukwala 30(6) 32 (3) / 7/

Bondo 39(8) 56 (6) /34/

Rarienda 30(6) 54 (5) /21/

Boro 21(4) 15 (3) /22/

Table 2

S.NYANZA

Ecozone Number of schools Number of women Groups High potential (UM) 6(2) 6 /17/ (3)

High potential Sugar zone (LM1) 3(1) 3 /18/ (3)

Sugar zone (LM2) 8(2) 4 /25/ (4)

Marginal sugar zone (LM3) 24(13) 10 /23/ (4)

Key: ()= Indicate the number of either schools or women groups randomly

sampled from each division. // = Total number of members' farms visited.

9

Total schools and groups in each ecozone block.

Out of the total 230 women groups and 200 schools in Siaya district only

165 women groups and 128 schools were considered for sampling. Their

distribution by agroecological zone/division is as shown in Tables 1 and 2.

The survey data was coded for computer analysis using SPSS package at

KARl headquaters in Muguga.The statistical analyses examined basically the

nature of relationship and correlation between the various factors determining

survival and the survival rate itself.

DESCRIPTION OF THE GENERAL LAND USE

The Ecology of the area

Location

Siaya and South Nyanza Districts lies in western part of Kenya in Nyanza

Province (see Fig.1). Siaya and South Nyanza Districts cover an area of 2.520

and 5.793 Kms respectively.Altitude and Land forms Siaya and S. Nyanza is found

in altitude between 1.135m-1500m-1750m respectively. The land form in the two

districts is varied,ranging. from the low plains around the Lake Victoria to

highland areas to the eastern part of the districts.Relatively flat areas (0 to

2% slope) occupy most partsimmeidately bordering the lake. Large parts of the

districts is characterized by mild slopes 2% to 16%. There are few areas of

steeper slopes.

Agro-ecological characteristics

The climate of the two districtrs and indeed the whole of western Kenya is

strongly influenced by the proximity of Lake Victoria and also by the varying

relief. Mean temperatures in the two districts vary from 23-25 o C.

The distribution of annual rainfall in the districts is shown in Fig.1 and

Table 3.

The magnitude of rainfall is strongly influenced by the lake and

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the sorrounding high elevations to the east. The mean annual rainfall ranges

from 800-2000mm for Siaya and 700-1800mm for S.Nyanza District. Rainfall of

1200mm and less occurs in the low-lying plains near the lake. Based on the

incidence of rainfall and potential evaporation. the whole of Siaya and

S.Nyanza have high moisture availabil ity. There are however a few areas along

the southern lake where in S.Nyanza with semi-arid conditions. The transitional

zone area is also quite limited. The rest of the areas fall in humid.sub-humid

and semi-humid zones. WHile rain can occur throughout the year. January.

February and half of March are generally dry. High rainfall occur bimodally.

from March to May (the long rains)and from September to November (the short

rains).There is subdivision of the districts into 3 to 5 agroecological zones

on the basis of rainfall and possibly according to soil types.The details of

these sub-divisions are shown in Fig.2 for South Nyanza only. Because of

bimodal nature of rainfall in the districts. There exists two growing seasons.

In Siaya. the growing season ranges from 175 to 330 days while in S.Nyanza it

ranges from 200 to 310 days

(Table 3).

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13

Table 3 Agroeco1ogical zones in Siaya and S. Nyanza districts

Altitude (m)

Rainfall in mm

60% reliability growing period

Total

Long

short

rains rains

Siaya

l.Bondo 2.Yala 3.Boro 4.Ukwala 5.Rarieda Nyanza

l.Marginal sugar zone (LM3)

2.Sugar zone (LM2) 3.Medium-high potential

sugar zone (LM1)

4.High potential zone UM1 OR UM2

1000-1200 1600-1800 1200-1400 1300-1600 1000-1200 1800-1200 1200-1400 1400-1600 1600-1800

1000-1200 1400-1600 1200-1400 1400-1500 1000-1200 1200-1300 1200-1400 1400-1600 1600-800

600-800 800-1000 700-900 800-1000 600-800 800-1000 800-1000 1000-1200 1000-1200

400-700 600-800 500-700 600-800 400-600 500-700 600-800 800-1000 1000-1200

175-330 - - - -

200-300 - - - -

Source: Adopted from Jaetzold and Schmidt, 1982

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GEOLOGY

Geologic formations in the survey area vary from recent quartenary

sediments to old rocks of archaen age.The most frequent formation is tertiary

volcanics,occurring in most parts of the eastern highlands and lake shore

areas. Most parts of Siaya and South Nyanza have granitic intrusives. Rocks of

Archaeanage, of the Kavirondian and Nyanzian system are confined mainly to

South Nyanza, Siaya and Busia districts. Rocks of quarternary formations are

found in small pockets near Lake Victoria shore.

SOILS

In Siaya District, the major soil types are Orthic ferralsols and

verto-Iuvic phaeozems. Associations of orthic ferralsols and ironstone soils

covers the eastern Siaya (Rangala-Bondo-Yala). They are well drained to

moderately well drained, shallow friable sandy clay loarn underlaid by

petrolinthite. Verto-Iuvic phaeozems are predominant soils of the east-south

Siaya. They are shallow to moderately deep, dark brown, firm clay. Along the

lake shore, lithic phase partly occurs.

However, the soil distributions pattern in South Nyanza is very

complicated unlike in Siaya. The major soil types are eutric regosols, verto-

Iuvic phaeozems gleyic acrisols and chromic vertisols Siderius and Muchena

(1977). Eutric regosols are predominant in Gwasi Hills and in Gembe Hills. The

soils are well drained, shallow, dark brown, friable, rockly and stony clay

loarns. Vertoluvic phaeozems occur in the large central area of the district.

They are moderately well drained, shallow to moderately deep, dark brown to

red,firm clay. They have a deep topsoil rich in organic matter. Gleyic acrisols

are extensive in the southern part of the district. They are imperfectly

drained, moderately deep-brown to dark yellowish brown, mottled, friable,

gravelly sandy clay loam. These three units are less suitable for cropping.

Chromic vertisols are the major soils in Lambwe Valley. They are imperfectly

drained, very deep, slightly saline and sodic crackirig clay. Wetland paddy

would be suitable unless salinity and alkalinity problems exist.

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GENERAL OBSERVATIONS

The methodological detailst procedures and conditions used to carry, out

the tree survival count are described in Chapter 2. The results and

observations from the survey are presented here. This chapter will describe the

statistical treatment of the data from the field and summarizes the

observations carried out in the field.

Treatment of data from survival count:

Statistical analyses of data frdm the survival count were carried out

where applicable for the different variables recorded. However the survival

rate results presented in Tables 4 and 5 are means for species for each

agroecological zone/divisons in the two districts and also for the tree species

irrespective of location. The meam survival rate for all the schools and women

groups participating in agroforestry have also been computed independently from

the districts.

Further statistical analyses were .carried out to determine the

relationship between survivval rate and all the important variables (see annex

1 for details of the variables) influencing it.

In computing analyses of variance to determine the significance of these

parameters on survival ratet a probability of 0.05 or less was accepted as

indicating that the real treatment effects were occurring.

Problems identified

In the course of this survey, a number of problems occurred. These, centred on

poor record keeping and lack of supervision by field. extension personnel.

South Nyanza district was most affected in this way. A decision was later taken

not to sample a group or school who although randomly chosen but lack proper

records on the number of given for planting.In such circumstances ,the next

nearest participating group or school as the case may be with adequate records

was sampled/considered. The other problem was the relatively low

number(sometimes as low as one tree only)_of seedlings planted (i.e. sampling

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from a smaller population size). This category of groups and schools were

however not discarded although they tended to exaggerate the rate of survival

in most cases.

RESULTS AND DISCUSSION

The mean survival rate for all the species currently being planted in the

project are summarized in Table 4. There were major. differences in the survival

rate between the different species and ecozones. The mean survival rate ranged

from 9% to 100% (Tables 4 and 5). Among the first 17 most preferred tree/fruit

species,(Table 5). Among the first 17 most preffered tree/species, (Table 6)

Mangifera indica showed the highest rate of survival (79%) followed by Grevilla

robusta(62%),Citrus lemon(59%, Carcia papaya(58%), Leucaena leucocephala(57%)

and Markhamia platycalyx(52%).The remaining 11 species had survival rates below

50%. The survey showed no significant differences in tree survival rates

between the women groups and the schools participating in different

agroforestry systems (Table 5).

Although the survey showed that the percent survival range is remarkably

high, these results if interpreted on the basis of survival percent alone could

be misleading. On the contrary, the actual numbers of schools and/or groups

participating in the actual planting of the different species and the number

planted per species ffers a much more accurate criteria for the evaluation of

survival rate. For instance, Tables 4 and 5 shows that Persea americans, Tamar

Indus indica and Bombax spp had 100% survival rate.However, when the actual

number of groups/schools planting it was taken into consideration,it was found

that only one group was involved in the planting.Similarity,the lowest survival

rate(9%)recorded on the Anacardium occidentials (Table 5) was probably the

result of considering a small population sample.under these circumstances

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TABLE 5 Tree Survival rates in women groups and schools

Species

Schools

Women groups

Mean

Sl L. Leucocephala 58 56 52 S2 Mark platycalyx 52 52 52 S3 M. azedarach 34 55 45 S4 P. aculeate 43 45 44 S5 T. brownill 45 53 49 S6 T. Mentalis 36 47 42 S7 C. Spectabilis 49 48 4XXXXX S8 C. Siarnea 42 36 39 S9 S. Sesban 20 79 50 S10 S. Bispinosa 35 64 5XXXXX Sll S. Grandiflora 31 71 5XXXXX S12 M. indica 75 82 79 S13 J. Mimosifolia 45 40 43 S14 Eucalyptus Spp; 31 42 3XXXXX S15 C. Megalocarpus 55 34 45 S16 I. peruviena - - S17 C. listanica 46 48 48 S18 P. patula 50 - 50 S20 5. semen 70 31 50 521 C. papaya 71 44 5XXXXX S22 G. robusta 56 56 6XXXXX S23 D. elata 39 41 4XXXXX S24 A. accidentalis 9 - S25 C. 'lemon 68 52 5XXXXX S26 C. sinnensis 100 63 8XXXXX S27 S. nilotica 63 45 5XXXXX S28 E. japonicum - - S29 C. cajan - - S30 C. callophyrsus 46 57 5XXXXX S31 G. pieum 15 25 2XXXXX S32 P. americana - 100 100 S33 T. indica - 100 100 S34 Bombax Spp. - 100 100 S35 C. robusta 42 21 32 S36 c. aqusetifolia 40 27 34 537 T. stens 100 24 62 S38 S. cuminii 70 47 59 S39 A corriaria 70 30 50 S49 E. spp - 65 65 S41 P. chilensis - - - S42 D. regia 45 49 47 S43 A. indica - 48 48 S44 Avocado 100 52 76 545 Aberia coffra 40 72 56

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It would be advisable to base the evaluation of survival rate on larger

population sample only.

Inorder to determine the effects of the various pre-planting and post-

planting treatments. methods of planting. material planted and location of

planting on survival rate, the survival rate data recorded in the field were

submitted to a regression and correlation analyses by using the number of

combination treatments as the independent variable and the survival rate as the

dependent variable.

The results showed that survival rate was significantly linearly

correlated with the number of treatments (Table 7)

From the results of the regression and correlations analyses, it is

evident that the greater the number of pre-planting and post-planting treatment

combinations (plus other treatment fastors)adopted,the higher the survival

rate.This relationship was consistent at both speciec and ecozome levels.

The survey however indicated that certain treatment factors (e.g. method

of planting and material planted) or a combination of some have greater

influence upon the survival rate than others (Table 7); although this

observation seems valid, however. it needs further analyses leading to the

partitioning of the effects if it has to play a great role in influencing the

tending practices to be adopted.

Annex 1 Table 1 lists the management/tending practices currently employed by

the farmers. From this list it is evident that not all of them or a great

number of them can be carried out without a lot of input requirements and

strain on labour resources. This therefore

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TABLE 6

LIST OF TREE SPECIES IN ORDER OF PREFERENCE BY SCHOOLS AND GROUPS

Rank Tree Species/Fruits

No of sampled schools groups planting it

1. Leucaena Leucocephala 18 2. Markhania Platycalyx 17 3. Cassia Spectabilis 17 " Eucalyptus Spp 15 " Carica Papaya 15 4. Jacaranda Mimosifolia 14 5. Cassia .Siamea 13 " Cupressus Lustanica 13 " Meliaa azedarach 13 6. Gravillea robusta 10 7. Parkinsonia aculeata 9 " Mangifera indica 9 " Dolonix alata 9 " Citrus Lemon 9 8. Callistris robusta 8 " Casuarina aqu!setifolia 7 9. Sesbania bispinosa 7 " Samenea Saman 7 10. T. Mentalis 6 " Citrus Sinensis 6 " Sesbania Sasbania 5 " Caliandra Callolthyrsus 5 " Passiflora adulis 5 " Syzygium cumin! 5 11. Croton megalo-carpus 4 " Spathodea nilotica 4 " Tecoma Stans 4 " xxxxxxxx xxx 12. Avocado 4 13. Sesbania grandiflora 3 " Gliricidie Sepium 3 " Albizia corriaria 3 14. Azendiracta indica 2 " Aberia caffra 2 15. Pinus patula 1 " Anacardium Accidentalis 1 " Persea americana 1 " Tamarindus indica 1

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" Bombax Spp 1 " Erythrina Spp. - 16. Thevetia periviana - " Eriobotrium joponicum - " Cajanus cajan - " Prosopis Chilensis -

necessitates that a greater emphasis should be put on identifying and improving

on those important factors that can enhance the chances of survival.

The effects of agroecological zone (rainfall amount) on survival rate was

not clear with the exception of Rarieda which showed relatively lower rates of

survival. Although this survey did not reveal a clear trend on survival rate

with respect to agroecological zone as would be expected, however, it is

emphasized that in order to improve survival zones like Rarieda,LM3(S. Nyanza)

and other relatedsites, improved practices on both pre-planting and post-

planting activities together with better method of planting and correct choice

of planting material will play a greater role in determining survival.

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Table 7 Linear relationship and correlation between survival rate (Y) and treatment factors (X)

Source DF Regression

coefficientRegressionconstant F-ratio S.E.

coefficient ofcorrelation(r)

Pre-planting trmt

4 5.3 2.4 6.7* 2.5 0.6**

Post-planting trmt 6 7.0 1.9 14.6** 1.0 0.7**

Method of planting 3 7.6 4.3 19.7** 3.1 0.8

Material planted

3 8.2 2.3 24.3** 2.0 0.8**

Location of planting 15 1.4 0.5

5.0 0.5NS 0.5**

-

* - F - test is significant at P<O.OS

** - F - test is significant at P<O.OI

NS - F - test is not significant at P<O.OS

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GENERAL CONCLUSIONS AND RECOMMENDATIONS

The success of the CARE-Kenya agroforestry project being undertaken in

South Nyanza and Siaya districts appears to have so many factors determining

it. In the first place, the higher the number of livestock in a homestead, the

lower the tree seedling survival. Also in the high productive areas where

agricultural productivity is high, little time is devoted to seedling raising

and tending. This consequently leads to low planting and survival rate.

Socio-economic factors also played a significant role in determining tree

seedling survival. For instance where both husband and wife were actively

involved in tree planting, high level of seedling tending was observed with

subsequent high survival. This is in contrast to what was observed where the

wife was participating alone but very close to the situation where the husband

only was actively involved. On the other hand, the higher the income in a

family (as observed through buildings,clothings and other properties), the more

seedlings were tended and thus high survival. Locality of the group relative to

the public forest lands also had some influence with groups close to the

forests had few trees were planted by the members and even worse still, little

or no tending was carried out.

Finally, it was pointed out by the extension officers that other non-

governmental organisations to some extent affected the success of the CARE

project. While CARE gave seeds and the necessary implements, thus requiring

total commitment from the members, other organizations gave members of women

groups seedlings rather than seeds and consequently removing the nursery work.

Others paid members cash as an incentive for every establishment seedling.while

all these approaches may appear very attractive to the members,overall they are

detrimental in that they do not cultivate a long term commitment within these

members. Also in some cases they do not allow the appreciation of trees as

personal properties but rather as only a source of cash.

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The extension methods and techniques used also had a role to play in the

survival of the seedlings. Tree species known to be palatable to livestock like

Leucaena were found planted in the boundaries, homestead or pastures where the

animals could easily browse them. This lowered the number of seedlings

observed. Also in other situations members had planted certain species in the

garden and these being shade trees, they had to be uprooted afterwards when

they proved to be interfering with the agricultural crops. This greatly

contributed to the reduced number of seedlings counted.

CARE-Kenya should therefore try to encourage the participation of the

entire family in the seedling planting to ensure better tending of the

seedlings in the field. More emphasis should be placed on those groups away

from the public forests and more so in the marginal areas as opposed to high

potential areas.

Extension workers should at least have the basic training in forest to be

able to advice on what species to be grown in any given locality e.g. pastures,

boundaries homesteads etc. Overall, either complete clean cultivation or spot

weeding as a pre-planting treatment, use of pits and a clean spot weeding as a

post-planting tending method seen as highly successful and are hereby

recommended as future techniques to be used. Where applicable, protection

against livestock especially in the homestead should also be applied.

25

REFERENCES

International Council for Research in Agroforestry (1987).

Lake Basin River Catchment Development Conservation and Rehabilitation

Programme.Report on Phase Π. ICRAF,Nairobi,Kenya.

Jaetzold, R. and Schimdt, H. (1982). Farm Management Handbook of Kenya.

Ministry of Agriculture team, Nairobi, Kenya. Vol II A and B.

Lake Basin Development Authority (1983). Five Year Development Plan:

1983-1988.

Lake Basin Development Authority, Kisumu, Kenya. 69p.

Siderius, W. and Muchena, F.N. (1977). Soils and environmental

Conditions of agricultural research stations in Kenya.

(Miscellaneous soil paper,No.M5) Nairobi, Ministry of agriculture.

26

CODING SYSTEM OR CARE TREE SURVIVAL COUNT Ecozone Al-High potential A2– A3- Medium Potential A4- A5- Low pot.ential Pre-planting treatment B1- Complete clean cultivation B2-Addition of manure B3- Use of fertilizer B4-Watering the pit B5- others Post planting treatment C1-clean weeding C2- Watering C3- Protection - use of pesticides C4- Mulching C5- Micro catchments/specialstructures C6-Protection against livestock Method of planting D1- Pits D2- Trenches D3- Ridges D4- Others Material planted E1-Seeds (direct sowing) E2- Seedlings E3- cuttings Location of planting Fl- Woodlot F2- Alley cropping F3- Fodder banks F4- Fodder banks F5- Boundary/windbreaks F6- Degraded sites/gullies F7- Contours F8- swamps F9- Valley bottoms F10-Roadside F11-Water points F12-Fruit tree orchards F13-Homestead F14-pastures F15-Live fences

27

Annexe 2

DATA SHEET District…………………………………………………………………………………………

School/Farmer…………………………………………………………………………………

Ecozone………………………………………………………………………………………….

Pre-planting treatment………………………………………………………………….

Post-planting treatment…………………………………………………………………

Material planted……………………………………………………………………………

Location of planting……………………………………………………………………..

Species Year of

planting Number of seedling planted initially

Number Of seedlings surviving

Comments

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