Agro-Ecological Conditions Effect on the Expression of the spatial Chickens Distribution
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1 Scholarly Journal of Agricultural Science Vol. 4(9), pp , September 2014 Available online at ISSN Scholarly-Journals Full Length Research Paper Agro-Ecological Conditions Effect on the Expression of the spatial Chickens Distribution Addisu Hailu Biology department, University of Gondar, Gondar, Ethiopia. Accepted 5 September, 2014 Both poultry egg and meat enrich and contribute a well-balanced diet to satisfy human needs. An average adult human needs about 65g of protein/day, of which only 10% needs to be protein of animal origin. Approximately 20% of protein consumed in developing countries originates from chicken. However, chicken distribution is not uniform throughout different agro-ecological zones. Therefore, to analyses the effect of agro-ecological conditions on the chicken distribution expression, the correlations were tested. Three agro-ecological zones were selected on basis of the elevation, mean annual rainfall, mean annual temperature and local climatic type. Secondary data s from CSA (central statistics agency) series ( ) were collected per each agro- ecological zones. The collected data was subjected to ANOVA, correlation and regression analyses under SPSS ver.16. On average, high number of chicken was found in highland (9,461,790) followed by mid land (3,888,831) and low land (427,751).There were significant differences (p -value<0.05) in chicken distribution across agroecological zones. This implied that the human or agro-ecological factors influence the chicken distribution. Chicken distribution has strong positive correlation with altitude (0.93) and rainfall (0.85). However, it has negative strong correlation with temperature ( -0.82). In general, more chicken were condensed in highland area than midland and lowland areas. Therefore, for action that needs priority depend on chicken number should focus primarily on highland part of Ethiopia. Key words: Chicken abundance, temperature, correlation, regression, altitude, Ethiopia. INTRODUCTION Ethiopia is believed to have the largest chicken population in Africa. This livestock sector has been contributing considerable portion to the economy of the country. The livestock sector contributes 20% to the total GDP, supporting the livelihoods of 70 % of the population and generates about 11% of annual export earnings. Livestock sector are still promising to rally round the economic development of the country (CSA, 2012). Poultry production is an important economic activity in Ethiopia. Besides to its economic and social values, it occupies a unique position in terms of high quality protein food contribution to rural smallholder farming families in Africa and particularly in Ethiopia (Sonaiya et al., 1999; Tadelle and Ogle, 2001). Both poultry egg and meat enrich and contribute a well-balanced diet to satisfy human needs. On average adult human needs about 65g of protein/day, of which only 10% needs to be protein of animal origin (Tadelle et al., 2003). Approximately 20% of protein consumed in developing countries originates from poultry (Askov and Dolberg, 2002). The total chicken population of Ethiopia is about million comprising cocks, cockerels, pullets, laying hens, non-laying hens and chicks (CSA, 2012). Globalization and a growing demand for meat products in developing regions in recent years have led to rapid expansion of the livestock sector, particularly pork and poultry meat (Prosser et al., 2011). With these changes come an increased threat of emerging zoonotic diseases and a need for improved food safety and the implementation of appropriate biosecurity measures and breed improvement. Epidemiological efforts, livestock sector planning, and policy development all require knowledge of livestock distributions and abundance, information that is often difficult to obtain in a consistent spatial format (Prosser et al., 2011). Thus, the spatial distribution of different livestock species in Ethiopia may be more concentrated in some regions or districts than others (Mohammad et al., 2007). Indeed, until now, the achieved studies were carried out in small portions and exclusive of chicken. From this it is
2 Hailu 477 Table 1. Agro-ecological classification of Ethiopia Agro-ecology Mean annual rainfall in mm Mean annual temperature in o C Altitude range in masl General category Wurch <2,200 > 11 3,200 High land Wet Dega 1,400-2, ,300-3,200 Dry & Moist Dega 600-1, ,300-3,200 Wet and Moist WoinaDega 800-1, ,500-2,300 Mid land Dry WoinaDega > ,500-2,300 Wet Upper Kolla < 1, ,500 Low land Moist Upper Kolla 900-1, ,500 Dry Upper Kolla > ,500 Moist Lower Kolla 900-1,400 < 27 > 500 Dry Lower Kolla > 500 < 27 > 500 believed that the altitude plays a major role in the spatial chicken distribution in Ethiopia. Therefore, abundant chicken distribution maps produced in this study are valuable for a variety of uses including epidemiological modeling, guiding policy decisions, livestock management, breed improvement, biosecurity and food safety. OBJECTIVE The goal of this work was to test correlations between spatial chicken distribution and agro-ecological zones MATERIALS AND METHODS Description of Ethiopia The review was conducted in Ethiopia, which is located in 8 00 N Longitude and E altitude and has diversified agro-ecological zones. The natural vegetation and livestock distribution of the country is influenced by altitude, landform, drainage, and edaphical interaction (Tsedeke, 2004). Basically agro-ecology of Ethiopia is divided to three major categories (Table 1). The agro-ecological settings of the country were divided into 18 major zones. In this setting, nearly onethird of the country s land belongs to A1 (hot to warm-arid lowland plains), with M1 (hot to warm, moist lowlands), SM1 (hot to warm, sub-moist lowlands), and M2 (tepid to cool highlands) accounting for approximately 13.1%, 11.7% and 11.2%, respectively. Furthermore, Nearly 68% of the country is in the lowland category, whereas the mid highlands and the sub-afro-alpine and Afro-alpine account for about 30% and less than 2% respectively (Tsedeke, 2004) (Figure 1). Characteristics of sample sites Afar: Afar Regional state is located in the northeastern part of Ethiopia. The total geographical area of the region is about 270,000 km2 (CSA, 2008). It is geographically located between 39 o 34 and 42 o 28 E Longitude and 8 o 49 and 14 o 30 N Latitude. The mean annual rainfall of the region is below 500 mm in the semi-arid western escarpments and decreasing to 150 mm in the arid zones to the east (Afar National Regional State, 2010). Somali: The State of Somali is located in the eastern and south eastern part of Ethiopia. 80% of the region is classified as "Kolla" (lowlands), 5% highland ("Dega"), and 15% of the area falls under temperate ("WoynaDega") category (The Somali National Regional State, 2013). Tigray: Tigray is located on the north part of Ethiopia with the total area of Tigray is about 54, km. The climate of the region is characterized as "Kolla" (semi - arid) 39%, "Woinadega" (warm temperate) 49%, and "Dega" (temperate) 12% (Tigray Region, 2007). SNNPR: The State of Southern Nations, Nationalities and Peoples' comprise 10% of the total area of the country and lies in the southern part of the country. The most characteristic environment of the Region is a relatively fertile and humid midland which contains the densest rural populations of Ethiopia. About 56 % of the total area of the State is found below 1,500 meters elevation, which is categorized largely as hottest low land ("K olla"). The rest 44% is found in the temperate climatic zone. (SNNPR, 2013) Amhara: The Amhara National Regional State extends from 9 to 13 45' N and 36 to 40 30'E. More than 50% of the region constitutes the mid highlands and fringe areas between meters above sea level (Table 2). The remaining 25% are the extensive high plateaus and mountains ( meters altitude) located in the northern, central and northwestern and eastern parts of the region (ANRS, 2013). Oromia: The region has variable topography consisting of a high and rugged central plateau, which is divided into two by the Great East African Rift Valley, and the peripheral lowlands. Elevation in the region ranges from less than 500 to over 4300 m above sea level, with the
3 Scholarly J. Agric. Sci. 478 Figure 1. Agro-ecological classification of Ethiopia (Adopted from Tsedeke, 2004) Table 2. Characteristics of sample sites. Regions mean Annual mean Annual Elevation Local climatic type rainfall range temperature range range Afar arid and semi-arid Somalia arid and semi arid Tigray kola/, weinadega/ °a S.N.N.P.R humid midland Amhara kola/, weinadega/ °a Oromia dry, tropical rainy and temperate rainy climate Sampling framework and data collection highlands constituting about 48% of the region s area. Mean annual temperature ranges from 10 C to 22 C in the highlands1 and from 22 C to 30 C in the lowlands. Annual average rainfall in the region ranges from 200 to over 2100 mm ( ture.htm). Primarily the country was classified systematically in to three major agro-ecologically zones based on altitude, annual rainfall, annual temperature and local climatic type condition. Further, two regions were selected purposively per agro-ecology based on the above criteria s. Then, seven years CSA ( ) recoded data on chicken population were collected per each region. Statically analysis The secondary data was subjected to ANOVA, correlation and regression analysis of SPSS ver.16.regarding the ANOVA, the means comparison was incorporated there according to Tukey test at 5% threshold. Pearson correlation was tested at 5% level. The following model is used in analysis of mean variation. Y ijkl = µ + A i + B j +C k + e ijkl Where,Y ijkl =observed value of trait of interest, A i = fixed effect of altitude, (1,2,3) B j = fixed effect of temperatur e, (0 40 o c) C k = fixed effect of rainfall, ( mm) e ijkl =residual random error. RESULT AND DISCUSSION Effect of the agro-ecological conditions on chicken distribution expression According to the result, agro-ecology has a significant
4 Hailu 479 Table 3. Means classification of livestock population as a function of the altitude (I) agro-ecology (J) agro-ecology Mean Difference (I-J) Std. Error Sig. Low mid E6 * E6.031 Low High E7 * E6.005 Mid high E6 * E6.021 *. The mean difference is significant at the 0.05 level. Figure 2. Relationship of chicken distribution with rainfall, temperate and altitude. impact on chicken distribution. Indeed, large number of chickens was reported in highland agro-ecological zone (in central part of Ethiopia). High agro-ecological zone of Ethiopia mostly found in Oromia, Amhara and southern part of Tigray regions (Figure. 1). Tukey s mean comparison showed that agro-ecologyhas significant impact (p-value<0.05) on chicken distribution pattern. More chickens were condensed in highland than midland and lowland (Table 3). This result is in lined with Nigussie, 2011 who select high altitude areas purposively those had large number of chicken. However, in contradiction large number of poultry is dense in lowland part of china (Prosser et al., 2011). Relationship between the chickens number and elevation, rainfall and temperature The regressions of the chicken number on the elevation, rainfall were positive. However, chicken number and temperature was negatively associated. Chicken number was increased almost linearly as elevation and rainfall increased up to 2800m and 1400mmrespectively. Nevertheless, their number became decreasing and decreasing while temperature increased (Figure 2). More number of chickens was condensed in low temperature areas (temperate, semi temperate) than tropical areas. The peripheral part of Ethiopia (Afar and Somali regions) has smaller number of chicken than midland (SNNPR and Tigray regions) and highland areas (Oromia and Amhara regions). Similarly, according to Pearson s linear correlation, the chicken distribution has strong positive correlation with elevation (0.93) and rainfall (0.85) but strong negative correlation with temperature ( -0.82). The correlation coefficient of chicken distribution with elevation is highly significant as well the correlation level with rainfall and temperature is significant at 0.05 levels (Table 4). As elevation increased rain fall, precipitation and evaporation increased (Tsedeke, 2004). Consequently, forest coverage and climatic condition will more favor for livestock. This might be the reason of more number of chicken were found in highland part of Ethiopia. This result disagrees with a report of Prosser et al., (2011) who reported that poultry densities were generally positively associated with temperature. Furthermore, the author also, describes that chicken distribution is negatively associated with elevation in china. CONCLUSION Ethiopia has diversified agro-ecological zones. This
5 Scholarly J. Agric. Sci. 480 Table 4. The correlation value of chicken distribution with elevation, temperature and rainfall. Chicken number Chicken number altitude temperature rainfall Pearson Correlation ** *.848 * Sig. (2-tailed) **. Correlation is significant at the 0.01 level (2-tailed), *. Correlation is significant at the 0.05 level (2-tailed). diversity has an influence on chicken distribution as well as number. Chicken distribution throughout the country is not uniform. Based on ANOVA, more number of chickens was found in highland part of Ethiopia and less condensed chicken was reported in lowland part of Ethiopia (Afar and Somalia region). The number of chicken has direct relationship with rain fall and altitude but inverse association with temperature. Based on this chicken spatial distribution pattern; epidemiological modeling, guiding policy decisions, livestock management, breed improvement, biosecurity and food safety, and environmental impacts should focused primary in regions that had large number of chicken. REFERENCES Afar National Regional State (2010). Programme of Plan on Adaptation to Climate Change. October 2010, Semera ANRS (Amhara National Regional State), (2013). ANRS Bureau of Finance and Economic development (BoFED) ANRS: Geography and climate. December, 2013 Askov, H. and Dolberg, F. (2002). A Conceptual Framework for Using Poultry as a Tool in Poverty Alleviation.University of Aarhus, Aarhus, Denmark. CSA (central statistical authority), (2008). Agricultural sample survey 2007/08.volume II; statistical bulletin 505. Report on livestock and livestock characteristics, Addis Ababa, March pp CSA (central statistical authority), (2012). Agr icultural sample survey 2011/12.volume II; statistical bulletin 505. Report on livestock and livestock characteristics, Addis Ababa, February pp Mohammad, J., Asfaw, N. and Taye, G. (2007). Geographic distribution of cattle and shoats populations and their market supply sheds in Ethiopia. Discussion Paper No. 2.Improving Market Opportunities. 54pp Prosser, D.J., Junxi, W., Erle, C.E., Fred, G., Thomas, P.V.B., William, W., Tim, R., Xiangming, X., and Marius, G. (2011). Modeling the distribution of chickens, ducks, and geese in China.AgricEcosyst Environ May 1; 141(3-4): doi: /j.agee SNNPR ( Southern Nations, Nationalities and People's Regional), (2013). The Southern Nations, Nationalities and People's Regional State - Ethiopian Government Portal. December, Sonaiya, E.B., Branckaert, R.D.S. and Guèye, E.F. (1999). Research and Development Options for Family Poultry. First INFPD/FAO Electronic Conference on Family Poultry: 7 December March SPSS (stastical software package for social sciences). ( ). Ver. 16, Spssinc. Tadelle, D. and Ogle, B. (2001). Village Poultry Production Systems in the Central Highlands of Ethiopia.Tropical Animal Health and Production. 33(6): Tadelle, D., Nigusie, D., Alemu, Y. and Peters, K.J. (2003). The Feed Resource Base and Its Potentials for Increased Poultry Production in Ethiopia. World's Poultry Sci. J. 58: Cambridge University Press The Somali National Regional State, (2013). The Somali National Regional State - Ethiopian Government Portal. December, 2013 Tigray region, ( 2007). Livelihood Profile Tigray Region, Ethiopia. February 2007 Tsedek (2004). Agro -ecological classification of Ethiopia Nature and causes of land degradation in the Oromiya region: A review of literature. Visited on December 25, 2013.
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