Overall Objectives of the Livestock Breed Survey in Oromia Regional State

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To describe, identify and classify the indigenous livestock genetic resources in the region and to obtain reliable estimates of population size and distribution.

• • • • •

In particular:

To describe what breeds or types of animals exist, in what numbers and where they are.

To describe what they look like.

To define the environments in which different breeds are raised in terms of agro-ecological zone, disease, etc.

To say for what purposes they are used, how they are bred and by which farmers.

To determine farmers’ opinions on the main attributes of different breeds, in particular in terms of their adaptation to heat, drought and disease tolerance.

and so on ………………..

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To develop recommendations for utilisation of the livestock resources in Oromia Region

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Not an easy task!

Such a survey requires careful planning to ensure that these objectives can be met.

At least 6 months should be set aside for planning a survey in a region.

This includes: • • • • seeking cooperation of partners agreeing on objectives for the survey planning how the survey will be executed and by whom finding out what ancillary (census) statistics may be available on household numbers, people and livestock.

• • • • organising a sampling frame selecting zones, woredas and peasant associations to sample organising for training of supervisors and enumerators making sure that everyone is clear on final arrangements • planning for data entry and analysis and making arrangements with those to be responsible ………… and so on.

cluster stratified random

Types of sampling

representative convenience purposive

Cluster Sampling

• When sampling a large area it is easier in terms of survey costs and survey administration for the area to be first divided into clusters.

• To do so use can be made of the administrative structure in a country.

• In Ethiopia this is region zone woreda peasant association. Sampling units can be selected at each administrative layer in turn.

Zone Woreda Peasant Association

Cluster sampling

Stratified sampling

• The sampling units within a given administrative layer may vary in relation to a particular characteristic, e.g. agro-ecological zone, livestock density and household size.

• A completely random sample may miss woredas from a certain agro-ecological zone or a particular livestock density. It may also not adequately represent the population of households in a village. • By efficiently stratifying according to agro-ecological zone, livestock density or household size a more precise estimate of the number of livestock in a population can be achieved.

Strata Units selected

Stratified sampling

Sampling frame Definition

The entire list of zones, woredas, peasant associations (P.A.) and households in a region.

• How large should a survey be and how many zones, woredas, P.A.s and households should be sampled?

• This depends on funds available, costs of organising the survey, available manpower, administrative support, means of transport and ease of access to villages.

• Proportionally more units should be sampled at the upper than the lower layers. In the survey in Oromia Region all zones, approximately 30% of woredas, 17% of P.A.s per woreda and 4% of households per P.A. were sampled.

• This meant that approximately 1 in 500 households were sampled in Oromia Region.

Survey design and sampling frame

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The Oromia Region covers a third of Ethiopia

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All 12 zones of Oromia were included in survey Oromia Zone

Survey design and sampling frame

(cont.)

Woreda

• •

Stratification by: agro-ecological zone livestock density

Peasant Association

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Stratification by: agro-ecological zone

Household

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Stratification by: numbers of livestock types of species

Survey design and sampling frame

(cont.) Sampling

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About 30% of woredas in each zone sampled .

Selected woredas (55 in total)

Stratification and selection of woredas in East Wellaga Zone by agro-ecological zone and livestock density.

Sorted by livestock density Woreda Livestock per km 2 Livestock density Name Abe Dongoro Sasiga Wama Boneya Ebantu Limu Amuru Jarte Nunu Kumba Gidda Kiremu Jimma Arjo Guduru Diga Leka Guto Wayu Sibu Sire Bila Sayo Abay Chomen Jimma Horro Jimma Rare No.

15 4 1 11 17 2 14 16 6 12 3 13 7 10 8 5 9 13 14 22 25 35 35 50 52 71 72 73 73 74 76 84 181 241 low low low low medium medium medium medium high high high high high high high very high very high Sorted by agro-ecological zone Woreda Agro-ecological zone (%) Name Sasiga Abe Dongoro Jimma Horro Jimma Arjo Sibu Sire Wama Boneya Abay Chomen Ebantu Limu Bila Sayo Diga Leka Jimma Rare Amuru Jarte Gidda Kiremu Gudure Guto Wayu Nunu Kumba No.

3 7 8 9 13 14 2 11 10 15 16 1 6 12 4 5 17 Woinadega Kolla 100 100 100 100 100 0 0 0 33 33 38 50 50 50 50 50 50 100 0 0 33 33 0 0 0 0 0 47 50 50 40 0 0 0 Dega 0 100 100 33 33 0 0 0 0 0 15 0 0 0 50 50 50

Selected woredas in East Wellaga Zone by agro-ecological zone and livestock density % Woinadega 100 W W W WW Sampled woreda D Dega X Woinadega K W Kolla X Woinadega Woinadega X Woinadega X Dega X Kolla 50 33 K K X D D K X X 0 Low D K Medium High 50 Very High D 100 150 Livestock density (number per km 2 ) 200 D 250

Selection of woredas of East Wellega by agro-ecological zone and livestock density Agro-ecological zone Dega Livestock density Numbers of woredas Selected for sampling very high high 1 1 1 low 1 Woinadega high 2 medium 3 1 Kolla low 1 Agro-ecological zone Dega/Woinadega Dega/Woinadega/Kolla Livestock density Numbers of woredas Selected for sampling very high 1 high 2 1 high 1 1 Woinadega/Kolla high medium low 1 1 1 2

Selection of woredas in East Wellaga zone Summary

• Five woredas selected, one from each of Dega, Dega/Woinadega, Dega/Woinadega/Kolla, Woinadega and Woinadega/Kolla zones.

• One woreda selected from areas of very high (>180), two from areas of high (70-85) and two from areas of medium livestock density (35-55 livestock per km 2 ).

• Representative sampling used to ensure balance in selection of woredas across agro-ecological zone and livestock density strata.

• No element of randomisation.

Selection of P.A.s

• In woredas covering different agro-ecological zones ( e.g. Woinadega/Dega) P.A.s were randomly sampled from within each agro ecological zone.

• In woredas situated entirely with one agro-ecological zone P.A.s were randomly selected from all P.A.s in the woreda.

Limu Gidda Kiremu Jimma Horo zone Woinadega 3 Kolla 0 Woinadega 2 Dega 3 Woreda Diega Leka Sibu Sire Woinadega 1 Dega 2 Woinadega 1 Kolla 1 Dega 0

Selection of woredas and P.A.s for East Wollega Zone Limu (25 P.A.s) Beriso (1339 households) Haro (904) East Wollega (17 woredas) Asbo (741) Jimma Horro (27 P.A.s) Abe Bekel (1022) Bilkiltu S. (776) Balbala Sorgo (886 households) Gidda Kiremu (22 P.A.s) Gendo (662) Diga Leka (21 P.A.s) Chafte Soruma (974) Sibu Sire (14 P.A.s) Efa (486 households) Kersa-Arjo (803) Menga-Kewiso (648) Bikila (1160) Bujura Amuma (1192 households)

Selection of households

• Households selected as far as possible at random to ensure coverage of households with low, medium and high numbers of livestock.

• Ten households selected in turn for cattle, sheep and goats as the primary species.

• All households in each sampled P.A. subsequently categorised into low, medium and high numbers of livestock for each species in turn in order to facilitate estimation of the total numbers of cattle, sheep and goats in the P.A.

Sample selection of households by size category for cattle

Livestock size Haro P.A. in Limu Woreda Cattle numbers Low Medium High Total Households in village (N) (%) Sample size Actual (n) Proportional (n) Ideal (n) a 565 66 7 20 16 216 25 12 7 7 78 9 11 3 7 859 100 30 30 30 a Approximately proportional to stratum size but with extra households in more variable ‘high’ group.

Methods of sampling (1) Random sampling

• Samples drawn completely at random, each with an equal chance of being selected.

• This method generally applied in selection of households in a P.A.

• This method also used to select P.A.s from selected woredas stratified by agro-ecological zone.

• Only method that allows unbiased estimation of population numbers.

Methods of sampling (2) Representative sampling

• Samples selected to be representative of population.

• This method applied at the zone layer.

• Method makes the estimation of overall population numbers in the zone more difficult unless additional ancillary data are available.

Methods of sampling (3) Convenience sampling

• Samples selected to allow, for example, ease of access to a P.A. or household, or to make best use of available manpower.

• Occasional use inevitable in such a survey.

• Document when method used.

• Provided such cases are few, probably reasonable to assume randomness for the purpose of estimation of population numbers.

Methods of sampling (4) Purposive sampling

• Sampling based, for example, on knowledge of known farming system or known breed unique to a certain location.

• Document when method used so that suitability of sample for inclusion in calculation of population estimates can be judged.

Summary

A few recommendations for successful survey design and implementation in Ethiopia.

• Ensure sufficient replication at the upper administrative layers to allow efficient estimates of population numbers and breed distributions to be determined.

• But match this requirement with knowledge of available manpower, resources (transport, etc), adequacy of infrastructure (administration, roads, etc), quality of field staff and size of budget.

Summary (continued)

• Determine what region / zone / woreda / P.A. statistics are already available on numbers of households, people or livestock that may help to improve the efficiency of sample selection and population estimation.

• Use this information to define appropriate strata for the sampling frame.

• Ensure that selections of sampling units at the woreda, P.A. and household levels at least are as far as possible at random.

• Above all, obtain high quality data from a manageable sample of households.