JOURNAL OF DEGRADED AND MINING LANDS MANAGEMENT ISSN: 2339-076X (p); 2502-2458 (e), Volume 5, Number 3 (April 2018): 1217-1235 DOI:10.15243/jdmlm.2018.053.1217

Research Article

Climate variability, communities’ perceptions and land management strategies in Woreda, Northwest

Menberu Teshome1*, Addisu Baye2 1 Department of Geography and Environmental Studies, University, Debre Tabor, Ethiopia. Email: [email protected], PoBox 272 2 Department of Development and Environmental Management Studies, University of , Ethiopia. *corresponding author: [email protected] Received 13 January 2018, Accepted 18 March 2018

Abstract: Climate variability is the fluctuation of climate elements from the normal values making the agrarian communities of Ethiopia the most sensitive social groups to its hazards. The objective of this study is to examine climate variability, local communities’ perceptions and land management strategies in Lay Gayint Woreda, Ethiopia. Primary data were collected from 200 randomly selected households settled in varied ecological areas. Metrology data were gathered from Station from 1979 to 2010. Standardized rainfall anomaly index (SRAI), crop diversification index (CDI) and other descriptive statistics were used to analyze the data. The climate and the survey data revealed an increasing temperature, and decreasing and/or erratic rainfall pattern. 2002 and 2008 were extreme and severe dry years, respectively whist 1984 and 1990 received near normal rainfall amount. Over 87 % of the surveyed households perceived an increase in temperature over the last 20 years. The majority of the households are more likely to adopt land management strategies against climate variability. Terraces and check dams construction and planting trees were the major land management strategies of local communities. However, crop diversification index (CDI) was 0.11 indicating very low CD as the cultivated area is dominated by a single crop there. Although the study area receives inefficient rainfall the rugged topography coupled with poor soil conditions have hindered irrigation practices. Integrated watershed management activities and extension services and information dissemination systems should be strengthened and established to provide reliable weather information for farmers given that their livelihood is dependent on it. Keywords: adaptation strategies, climate variability, crop diversification, Lay Gayint Woreda To cite this article: Teshome, M. and Baye, A. 2018. Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda, Northwest Ethiopia. J. Degrade. Min. Land Manage. 5(3): 1217-1235, DOI: 10.15243/jdmlm. 2018.053.1217.

Introduction including extreme weather events forms an important component of a system’s exposure to Climate variability is the fluctuation of climatic environmental stimuli (Fussel and Klein, 2005; elements from the normal or baseline values Ericksen et al., 2007). Climate change will largely (Smither and Smit, 1997). Climate is inherently affect existing climate variability, including the variable in time and space even within a given frequency, intensity, and location of harmful country.Climate variability is expressed as weather events. Onset, duration, and distribution variations in the mean state and other statistics of of rains as well as increasing unpredictability of the climate on temporal and spatial scales, which extreme weather events are manifestations of may be due to internal processes within the climate variability (Fussel and Klein, 2005; climate system, or anthropogenic external forcing Ericksen et al., 2007). Some inter-seasonal (Intergovernmental panel on climate variability is well understood, but much of the change/IPCC, 2001; Fussel and Klein, 2005). variation over long years is poorly understood and Seasonal and inter-annual climate variability, largely unpredictable. Thus, decisions on climate-

www.jdmlm.ub.ac.id 1217 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda sensitive sectors or activities are usually carried damage to infrastructure, social insecurity, and out under uncertainty or risk (Smithers and Smit, threatens development efforts for many of the 1997). decades (Woldeamlak, 2009) and will continue to Agrarian communities are the most sensitive undermine the overall economic and social social groups to climate variability due to the fact development in the future (Aklilu and Alebachew, that climate change affects the two most important 2009). In fact, most people of the country live in a direct agricultural production inputs such as period of rapid and dramatic ecological and land- rainfall and temperature (Philip et al., 2014). use changes. Indeed, the impact of climate change together Climate change-induced droughts, floods, with other deriving forces poses risks to the epidemics and the resultant famines are very nations’ food security status (IPCC, 2014). These common events in the country (Dereje and impacts are deepening the problems of vulnerable Tamiru, 2009). Frequent meteorological drought- smallholder farmers to poverty in the developing induced crop damage, famine and disease countries though they produce 70 % of the outbreak have claimed the lives of millions of world’s food needs (Campbell and Thornton, people and animals in the northern, southern and 2014; FAO, 2013). Agricultural productivity south-eastern dry-land . Major remained stagnant and low in smallholder flood hazards occurred in 1988, 1993, 1994, 1995, production systems over the last few decades 1996 and 2006 have claimed many lives and (FAO, 2015). In some cases productivity has property in different parts of the country. For already started to decline due to changing rainfall instance, the 2006 catastrophic flood have killed patterns, increasing temperature and frequency of more than 650 people, displaced more than 35,000 droughts, floods and other extreme weather events people and destructed huge infrastructure in Dire (Lipper et al., 2014). Dawa, South Omo and West Shewa (NMSA, Although agriculture is the cornerstone of 2007). the economy and the main source of livelihood in In recognition of these facts, adaptation to many developing countries severe natural climate change has received increasing attention resources degradation, high dependence on rain- in the scientific and policy debates together with fed agriculture, inadequate infrastructure, low mitigation (UNFCCC, 2006). The rational is that levels of technology, and weak governance have the degree of adaptation will determine many of led to low level of adaptive capacity to the the effects of climate change on agriculture impacts of climate-related hazards (Slingo et al., though adaptation itself will be determined by 2005). There is a strong link between climate and farming types (rain-fed or irrigated), income East African countries’ livelihood. Agriculture levels and market structure (Parry et al., 2005). contributes 40% of the region’s gross domestic Adaptation helps farmers to produce food, product (GDP) and provides a living for 80% of generate income and achieve livelihood security the population there (International Food Policy objectives in the dynamics of climate and socio- Research Institute/IFPRI, 2004). However, East economic conditions (Khan and Short, 2001). Africa’s heavy dependence on rain-fed agriculture Different adaptation strategies are being suggested has made rural livelihoods and food security to overcome the challenges of climate change in situations highly vulnerable to climate variability different spatial scales. Yet, such strategies are not (IPCC, 2001). Due to increasing temperature and only expensive but can also have many undesired decreasing precipitation in the region, many areas outcomes (Green Forum, 2008). As climate are being negatively affected. extreme events are expected to increase in As part of East African counties, the frequency and intensity (IPCC 2001) the current economy of Ethiopia is heavily dependent on coping strategies may not be sufficient in the agriculture, contributing about 45% to the GDP, future. This needs more work as adaptation is 60% to food security, and 90% to the export really dynamic and continuous process revenue and 85 % to generate employment for the (Intergovernmental Climate Prediction and work force. About 90% of the total agricultural Applications Centre/ICPAC, 2006). production is being contributed by small-scale In many African countries, including producers. However, the sector is more sensitive Ethiopia, a range of factors may undermine to climate variability and frequent droughts communities’ ability to adapt to climate change causing massive food shortage (Ethiopian Institute (Boko et al., 2007). Knowledge of the factors of Agricultural Research/EIAR, 2005). Climate would assist in targeting intervention windows change increases the likely happenings of towards effective adaptation strategies to reduce environmental hazards thereby affecting the harmful impacts of climate extremes. Despite communities’ livelihoods and ecosystem health in the importance of perceptions and adaptation to Ethiopia. This situation exacerbates poverty, climate variability, a very few studies, for

Journal of Degraded and Mining Lands Management 1218 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda example, Deressa et al. (2006); Yesuf et al. (2008) them plough their land using traditional farming and Woldeamlak (2009) have examined farmers technology (LGWADO, 2014). This has made the perceptions and adaptation to the impact of communities more vulnerable to the impact of climate variability on crop production in the climate variability. context of Ethiopia. Even these few studies were Lay Gayint is one of the food insecure carried out at the macro-level with little micro- woredas of Amhara National Regional State. The level specificity. Unless, the micro-level Woreda covers an area of 1,548.56km2 and sub- community understand the effect of climate divided into 29 rural and two urban Kebeles (the variability and/or climate change, it would be hard lowest administrative unit of Ethiopia). It is to convince and motivate local people to bordered in the North by Ebnat and , in the undertake adaptation actions. The communities south by and , in the west by are using different land management strategies to Estie and Woredas and in the East by reduce the adverse impacts of climate variability Mekiet Woreda of . The based on their local knowledge and persistent absolute location of the Woreda is 11°32’- 12° 16’ practices. Adaptations assessments should be N Latitude to 38° 12’- 38° 20’E Longitude (see conducted with the aim of identifying appropriate Figure 1). The administrative center is Nefas options and understanding the local effects of Mewcha; it is located on the way from Woreta to recent climate trends on crop yields and food Woldia high way which is 226 Kms away from security status of the study area. Therefore, this Gondar city and 175 kms away from the regional study was conducted to assess the current status of capital city, (LGWADO, 2014). climate variability, local communities’ The topography of the woreda is dominated perceptions to climate variability and land by chain of mountains (50 %), hills and valleys (5 management strategies in Lay Gayint woreda, %) extending from Tekeze Gorge (1494 meter) to of , Ethiopia. Guna Mountain Summit having the highest elevation of 3991 meter above sea level (masl). Study Area The flat terrain constitutes only 10 % of the total area. The woreda is divided into four elevation Lay Gayint woreda is located in South Gondar and temperature based agro-ecological zones, Zone of Amhara Region, Ethiopia. namely: lowland/kolla (12.5%), midland/woyna- Geographically, South Gondar Administrative dega) (39.42%), highland/dega (45.39%), and Zone is located between 11° 02' -12° 33' N alpine/wurch (2.71%). Most of the rural latitude and 37° 25' - 38° 43'E longitudes. The population settled in the highlands and plateau zone is bordered in the south by East , in areas. The main soil types are brown (55 %), red the south-west by West Gojjam and Bahir Dar, in (15 %), black (15 %), grey (10 %) and other soil the west by , in the north by North type (5 %) (LGWADO, 2011). The annual mean Gondar, in the north-east by Wag Hemra, in the minimum and maximum temperatures range from east by North Wollo, and in the south-east by 80 C to 290 C respectively. The long-term average South Wollo; the Abbay River separates the zone rainfall is characterized by high variability and from East and West Gojjam administrative Zones uncertainty. Deforestation, overgrazing and lack (Lay Gayint Woreda Office of Agriculture/OoA, of proper soil and water conservation measures 2012). have contributed to the prevalence of drought in The climate of the administrative zone is the woreda. The main rainy season (Meher) more influenced by altitude. Based on the occurs between June and September and the small simplified agro-climatic classification of Ethiopia, rainy season (Belg) occurs between March and it lies within four agro climatic zones. Alpine and May. In most cases, the woreda’s crop production tropical zones account for 2.5% and 16% depends on main rainy season (LWADO, 2010). respectively whereas sub tropical and temperate The woreda has a total population size of climate zones account for 27% and 54% of the 254,130 (128,427 men and 125,703 women), of administrative zone respectively. The zone has which 228,534 (89.14%) were rural and 27,596 bimodal rainfall pattern, summer (June to August) (10.86%) were urban dwellers (CSA, 2007). The is the main rainy season with its peak in July and total area of the woreda is about 154,866 hectares the short rainy season from February to April. with a crude population density of 157 persons Rainfall varies from 900 mm to1599 mm with the per square kilo meter. The area has very steep average annual rainfall of 1300 mm. The average valley and incised stream channels with slopes of temperature is 17°C (LGWADO, 2012).More 0.1% to 38.23% (see Figure 2). than 85% of the farming households engage in mixed farming systems and more than 93% of

Journal of Degraded and Mining Lands Management 1219 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda

Figure 1. Location map of the study area [Computed based on Ethio- GIS database]

Figure 2. Lay Gayint woreda by slope classification

Figure 2 demonstrates that the slope angle of the seasons. The major land use pattern comprises woreda ranges from 0.1 % (least sensitive) to cultivable land (44.32%), grazing land (14.31%), nearly 38.23 % (more sensitive) to severe land forest/bush land (5.26%), water body (2.38%) degradation, land slide, and soil erosion in the infrastructure and settlement (5.92%), and rainy season and mass movement in the dry unproductive land (28.44%) (Refer to Table 1).

Journal of Degraded and Mining Lands Management 1220 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda

Table 1. Distribution of land use types in Lay Materials and Methods Gayint woreda Sampling methods and procedures Land use type Hectare % Lay Gayint woreda has 29 rural kebeles found in Cultivated land (annual 68649 44.32 different agro-ecological areas. The authors used crops) stratified, simple random and systematic sampling Grazing land 22160 14.308 techniques.The kebeles were stratified into three Bush and Shrubs 8150 5.26 categories with respect to their agro-ecological Water body 3665 2.36 zone (dega, woyna-dega and kolla). For the study, Uncultivated land 44041 28.438 three kebeles were selected from each agro- Infrastructure, settlement and 8201 5.29 ecological zone using simple random sampling others technique. These were Moseb Terara (highland), Total 154,866 100.0 Argeberas (midland) and Menteleho (lowland). Source: FEDP, 2010 To determine the sample size of each kebele Agriculture (crop and livestock production) is the administration (KA), the statistical formula was dominant economic activity in the study area. adapted from Israel (1992) and then by using Crop production is mostly rain-fed, except in very systematic random sampling technique, sample few areas where vegetables are cultivated using household heads were drawn from each KA. A traditional small scale irrigation. Both long and total of 200 sample households (70 from Moseb short cycle crops are cultivated in Meher and Belg terara, 78 from Argeberas and 52 from rainy seasons. The most commonly produced Menteleho) were participated in this study. The crops are wheat, teff, maize, sorghum, barely, registered sample populations were obtained from cheek pea, beans and oil crops. Livestock have local development agents (DAs) of the respective great contribution to the households’ income and kebele administrations. One DA interviewee from food security enhancement. The agricultural each kebele, three extension officers and two activity is not productive due to frequent agricultural experts of the woreda Agriculture occurrence of natural calamities which deteriorate Office, were included in the data collection land resources and increase soil erosion and process using purposive sampling method. gullies expansion. Rapid population growth has Moreover, two non-governmental organizations resulted in shrinking of land sizes. Land such as Organization for Development of Amhara degradation, deforestation, moisture stress, water (ORDA) and Food for the Hungry International resource depletions, lose of soil fertility and (FHI) Ethiopia were also participated in providing recurrent drought, landslide, crop pests/disease, the necessary information. livestock diseases and weeds together with Data collection cultural and attitudinal crisis are among the major problems leading the woreda to be one of the food In order to examine climate variability, local insecure areas of Amhara Region (LGWADO, communities’ perceptions and adaptation 2011). Currently, there is one main asphalt road strategies of local communities in Lay Gayint stretching from Woreta to Woldiya crossing woreda, both secondary and primary data were Nefasmewcha town. There are also feeder roads used in this study. The 32 years meteorology data that connect kebele administrations together. (rainfall and temperature) were gathered from There is electricity supply and mobile telephone Nefas Mewcha Station for the period 1979 to services for urban and some rural dwellers. The 2010. In addition, land-use and population data woreda has 2 health centers and 32 health stations were gathered from woreda Office of Agriculture. with the health service coverage of 84% Other published and unpublished literatures were (LGWADO, 2010). Amhara Credit and Saving also consulted in the whole process of the Institution (ACSI) is the dominant finance center research. The most important instruments used to in the woreda. The studied woreda run extension generate relevant primary data were household services by introducing improved technologies, survey, field observation and interview. The increasing agricultural inputs and providing primary data collection methods covered issues technical advices to the farmers in order to about perceptions of farmers on climate increase agricultural productivity. To meet this variability and its effects on crop production as objective, different extension packages have been well as local communities’ adaptation strategies practiced by development agents (DAs) who are used to mitigate the adverse effects of climate working with the rural farmers (LGWADO, change. Each of the primary data collection 2010). instruments are discussed in the sub-sections to come.

Journal of Degraded and Mining Lands Management 1221 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda

Household survey: in this study the household The quantitative data were analyzed using survey was one of the main data collection standardized rainfall anomaly index (SRAI), crop techniques from the sample households regarding diversification index (CDI) and descriptive perceptions of climate variability and land statistics (mean and percentage). Temperature and management strategies used to mitigate the rainfall conditions were briefly analyzed based on negative impact of climate variability on land and historical meteorological data. other resources. The survey questions were Standardized rainfall anomaly index organized into close-ended anchored with open- (SRAI): The patterns of drought over a range of ended forms categorized as basic personal time scales were analyzed by the Standardized information, perception on climate variability, and rainfall anomaly Index (SRAI).The SRAI is of land management strategies. The survey questions course used as a tool to identify and assess were prepared in English and translated in to frequency and severity of drought events under Amharic (local language) and again encoded into climate change in many countries (McKee et al., English during data processing and analysis. To 1993). It is used to determine periods of maintain the validity and reliability of the survey anomalously dry and wet events (World data the questions were thoroughly reviewed by Meteorological Organization/WMO, 2012). experts in the area. To assess whether the According to Christos et al. (2011), drought is the instruments were appropriate to the study, the state of adverse and wide spread hydrological, pretest of questionnaires to 10 households from environmental, social and economic impacts due the three agro-ecological zones were done. to less than anticipated water quantities. The Households who participated in the pretest were primary cause of any drought is precipitation not involved in the actual survey. After pretesting, deficiency. Specifically, the timing, distribution, vague words were rephrased, inappropriate and intensity of this deficiency are related to the questions were replaced and deleted. The authors existing water storage, demand, and use (Christos trained data collectors concerning the survey et al., 2011). techniques and confidentiality issues. After the The probability distribution function is training, the data collectors acquired practical determined from the long-term record by fitting a experience while the author made a face-to-face function to the data. The SRAI which is interview in the actual data collection in the field. developed by McKee et al. (1993) is expressed for The data were collected by the trained data each time scale as: collectors under the close supervision of the SRAI = [1] σ authors in the period of February to March 2013. ୔ି୔୫തതതതത Key informant interviews: For the sake of Where: SRAI refers to rainfall anomaly in depth understanding of historical trend of (irregularity and precipitation deficit) over the rainfall variability, some impacts of climate years, P, is the observed rainfall in the year (1979- variability on crop production and remembered 2010), , refers the mean annual rainfall over climate risks in the study area, in-depth interview the years (1979-2010) and σ, refers the standard was conducted with elders, Kebele administrators, deviationܲ݉തതതത ofത rainfall over the year. religious leaders, women, model farmers and local Drought is a natural hazard measured by shortage experts. The participants were carefully selected of precipitation that threats the environment and in consultation with woreda and kebele level overall development efforts of specific places agriculture officials and data collectors. In this through creating water scarcity. Therefore, regard, checklists were developed to guide key analysis of drought duration, magnitude and informant interviews. severity is highly demanded. McKee et al.(1993) Field observation : Overall information on defined the criteria for a “drought event” for any livelihood settings and topographic features of the of the time steps and classified the standardized study area was captured through field observation. rainfall anomaly index (SRAI) to define various Observation focused on crop farms, land use drought magnitude and intensities (see Table 2). pattern, biophysical characteristics and land Positive SRAI values indicate the presence of management strategies as adaptation mechanisms greater than the normal precipitation, while used at household and community level. It was negative values of the SRAI designate below carried out to cross check the information normal precipitation amount. The trends of gathered questionnaire survey, group discussion variability in rainfall and temperature and other and interview. household survey data were demonstrated by Data analysis graphs and charts. The main advantage of this drought analysis technique is its simplicity and The collected data and were analyzed using temporal flexibility. It will be developed based on quantitative and qualitative analytical techniques.

Journal of Degraded and Mining Lands Management 1222 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda the probability distribution of precipitation and Results and Discussions calculated by fitting a long-term precipitation record for a given station (Khan and Short, 2001). This section presents about the results and The SRAI is mostly used by drought planners. discussion of the study. An attempt was made to Calculating SRAI for a specific time period at any analyze and present communities’ perceptions of location requires a long-term monthly climate variability, trends of rainfall and precipitation database with 30 years or more. temperature based on the meteorology data and land management strategies as adaptation options based on the data obtained from household Table 2. Standardized Precipitation Index (SPI) survey, key-informant interviews and field categories observation. The results are presented in the SPI values Intensity category sections to come. 2.0+ extremely wet Socio-demographic characteristics of 1.5 to 1.99 Very wet respondents 1.0 to 1.49 Moderately wet -0.99 to +0.99 Normal Population size and characteristics have direct -1.0 to -1.49 Moderately dry implications on the supply and demand conditions -1.50 to -1.99 severely dry of basic human necessities such as food, shelter, -2 or less Extremely dry cloth, health and education. The necessities in Source: McKee et al.(1993);WMO(2012) turn, influence the use of improved technologies and farming practices of rural communities directly or indirectly. In this study, 200 rural Crop Diversification Index (CDI) was considered households participated with a response rate of to measure adaptive capacity of rural households 96.9%. The survey result indicates that the based on the area of farmland they owned in majority of respondents, 74.3% in MosebTerara, hectare under each crop, as it was used by Golam 65.4% in Argeberas and 71.2% in Menteleho were and Gopal (2003); male-headed while 25.7% in Moseb Terara, 34.6% in Argeberas and 28.8% in Menteleho were CDI =1/ ((Pa + Pb + Pc +_ _ _+Pn)/Nc []) female-headed household heads (see Figure 3). Age captures farming experience of the rural Where: community members. Through experience, CDI = Crop diversification index farmers perceive and understand the problem of Pa = proportion of sown area under crop a climate variability and/or change and the use of Pb = proportion of sown area under crop different adaptation strategies to reduce the effects b of climate variability and associated risks. Pc = proportion of sown area under crop c Therefore, the age structures of the surveyed Pn = proportion of sown area under crop households were examined in this study and n presented in See Figure 4. It is clear from Figure 4 Nc = number of crops that 12 % of the respondents were aged 18-27 years, 26% of them were aged 28 - 37 years, and If the total cultivated land in the study area is 21% of them found within 48-57 years of age. devoted wholly with one crop, the index value High percentages (29%) of the respondents were will be zero (0) and if it is evenly distributed aged 38 - 47 years. The rest 9.5% and 2.5% of among all crops (i.e., maximum diversification) them belonged to 58 - 67 and above 67 years of the index value approaches one (1). age. People with over 65 years of age often have The qualitative data analysis method was become a burden to the family as most of them used to interpret and discuss the information usually become weaker and have health obtained through FGDs, in-depth interview and complication with increase in age. Thus, the field observations. The collected information was productive family members could not be able to converted into word processing documents. The enhance productivity which could further increase author had taken some interviews and households’ likelihoods vulnerability to climate observational notes transcribed (that, is converting variability and other extreme weather events. interview, discussion and field notes into text data Regarding marital status 75.5% of the surveyed and then translated from local language (Amharic) households were married, 12.5% were divorced to English for answering the ‘why’ and ‘how’ and 6.0% were equally single and widowed. This questions on local communities’ perception and result is similar to Soyebo’s et al. (2005) findings adaptation to climate change. as cited in Mesfin et al. (2011) which state that agriculture is very much practiced by married

Journal of Degraded and Mining Lands Management 1223 Climate variability, communities’ies’ perceptions and land management strategies in Layay GaGayint Woreda peopletomakeendsmeetandand cater for their households who attended gradrade1 -4 constitute 10 children. This in turn, confirmss the realit y of the % and those who attended schochool from grade 5 to rural population that almost allll ffarmers are taking 8accountfor16.5%.Thee rest 5.5% of the the responsibility of farming acactivities after they respondents had completed ggrade 9 and above married. Figure 5 demonstratess ththe distribution of (seeFigure5).Fromthisresusult it is evident that surveyed householdsbyeducaticational status. The there is high illiteracy rate thethere which limits the Figure indicates that 68 % ofthe respondents did farmers’ access to differentt ininformat ion sources notattendanyformaleducationwn when this value is and in turn, results in unwillinlingness to adopt and disaggregated 39.5% of themhem were totally utilize new technologies in their agricultural illiterate with no education of any kind and 28.5% practices. of them were able to readd and write. The

80,0% 74,3% 70,0% 65,4% 71,2%

60,0%

50,0%

40,0% 34,6% Male 30,0% 25.7% 2828,8% Female 20,0% Percent of respondents

10,0%

0,0% Mosebb TTerara Arge Beras Mentelehoho

Sample kebeles

Figure 3. Distributiution of sample household heads by sex (Surveyresult,2lt, 2013 )

35 30 29% 26% 25 21% 20

15 12% 9.5% 10 % of respondents 5 2.5% 0 18-27 28-37 38-47 48-57 58-67 above 67

Figure 3. Distributionn oof sample household heads by age [Source: Survey resuresult, 2013 ]

JournalofDegradedandMininging Lands Management 1224 Climate variability, communities’ies’ perceptions and land management strategies in Layay GaGayint Woreda

39.5%

40 28.5% 30

16.5% 20 10.0% 5.5%5% 10

0 Illitrate Can read and Grade 1-4 Grade 5-8 Grade 9 andnd write above

Figure 5. Educational levlevels of surveyed household heads (Source:Surveyresresult, 2013 )

Educational status of farmersrs is assumed to sizes of the households weree ininvestig ated in this increase their ability to obtain anand use agricultural study (see Figure 6). related information and technologlogy in a better way (Maddison, 2006; Deressa et al.,l., 2009). However, low level of education and high illiteracy rate is typical in developing countriestries like Ethiopia which is one of the socio-econonomic features of households having crucialroles in increasing information about environmenental problems in general and climate in particularlar. It also plays an important role in improving the productivity (at individual and community levevels) by providing people with the skills and knowowledge to actively participate in the economic eendeavors of the society (Eyasu, 2007).Therefoefore, literacy has fundamental effects to impleplement adaptation strategies in order to mitigate ththe harmful effects of climate variability. Accordingingly, the education characteristic of the householdss werew examined in Figure 6. Landholding sizeize of the sample this study (refer Figure 5). household heads ([Surveyey result, 2013 ) Economic characteristics of respespondents Figure 6 presented the summarary of farmland sizes Land is the most economically pproductive natural owned by the surveyed hhouseholds. It is resource on which the livelihoooods of the people understandable from the figureure that the majority directly depends and enhance crocrop production and of the surveyed households (ne(nearly 68 %) owned diversification for the agrarianian communities of too small farmlands of 0.6-1hehectares while 13.8% developing countries. It is the most important of them have less than 0.5,, 112.2% own 1. 1-1.5, agricultural production factor in rural ho useholds. 4.2% have 1.6-2 and about 2.1%.1% have had greater Although the idea of landdist d ribution is to than 2 hectares of farmland. ThThis is an implication allocate land fairly to the landlessless rural population of limited adaptive capacitacity of the rural among the community partiallylly based on family communitiesinthestudyarea.ea. In the light of this size (Desta, 2012) the re-distristribution did not finding, several empirical woworks indicated that include all the landless young fafarmers due to low owning larger farmlandsds provide more availability of cultivated land in AmAmhara Regional opportunities to cultivate morore crops and yield State (Anteneh, 2010). Thereforeore, the landholding though it is noted that labolabor availability and

JournalofDegradedandMininging Lands Management 1225 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda financial capital affect the reality of how much highest mean maximum and minimum land can be cultivated. Barungi and Maonga temperatures were recorded in the Belg season of (2011) found out that less farmland area is often Ethiopia. attributed to increased vulnerability of farming households to climatic risks. Income is also another measure of agrarian communities’ adaptive capacity. Household heads were asked to state their most important sources of income. The great majorities of the local people of Moseb Terara (93 %), Argeberas (99 %) and Menteleho (85 %) reported agriculture as their main source of income. Cereal crops have high contribution to the food security status of the rural households. As crops are major sources of their diet they keep crops for self-consumption and to generate income. Figure 7. Distribution of respondents by A small percentage of households in perception to temperature trends Mentehelo (19. %), Moseb Terara (10.5%), Arge (Survey result, 2013) beras (5.1%) rely on off-farm activities as alternative means of employment creation and In addition to perceptions of communities’ inter- income generation for landless and unemployed annual temperature variability and trend, youth.The situation of off-farm activities were increasing deviation from the long-term average poorly expanded and subjected to the traditional was observed in the study area over the same cultural values and practices. In this regard, the period (1979-2010) with immense potential focus group discussion indicates that engagement environmental and production risks. The average in weaving, fuel-wood sales, black smith, pottery temperature was taken for Lay Gayint worera and and other handcrafts result in social alienation. compared with the hottest and coldest temperature Thus, the absence of off-farm activities would event of each year by calculating the temperature lead households to have limited income deviation using SPI formula based on Mongi et al. diversification and then vulnerability to drought (2010) as observed in the woreda (see Figure 7). and other weather-related shocks. However, Figure 8 demonstrates the maximum and engagement in off-farm activities like working on minimum temperature deviations from the long- others farms, daily laborer and domestic work term average temperatures for the woreda. It is were widely practiced by the surveyed households clear from the figure that in 1979 and 1980 both in recent times. maximum and minimum temperature deviations Local communities’ perception to temperature were slightly above the long-term average change temperatures. In 1981, 1982 and 1983 the two temperatures went in different directions (see In an attempt to investigate whether farmers Figure 8) while from 1984 to 1986 the maximum understand variability in climatic patterns, the and minimum temperatures went down together. respondents were asked questions related to their Indeterminate temperature fluctuation were perception of temperature change. The survey observed from 1987 to 1996 (while the maximum result reveals that out of the total household went up and the minimum went down and vice- heads, 87.5 % perceived that there was an increase versa). Since 1997 both maximum and minimum in temperature over the last 20 years. Only temperature deviations were higher than the long- insignificant proportions (1.0%) noticed the term average temperatures with greater contrary, a decrease in temperature and 7.0% of fluctuations from time to time. The direction of them did not perceive any temperature change. temperature trend in the study area was found in However, the rest (2.5%) do not know any change line with other empirical studies by IPCC (2007) in temperature (see Figure 7). According to the in the tropical regions of the world, Mongi et al. information obtained from the FGDs and key (2010) in Tabora region of Tanzania and Teshome informant interviews, since 20 years ago the (2016, 2017) in Ethiopia found out that both temperature pattern has changed and shown an maximum and minimum temperatures showed increasing trend in amount and intensity. The increasing trends, all of which, pointed out that highest temperatures were perceived in Belg increasing temperature trend in the tropical and (small rainy) season, namely in March, April and sub-tropical regions of the world is very high May. So, the result is consistent with the report of (IPCC, 2007) with adverse impacts on human and NMSA (2007), which states that almost the

Journal of Degraded and Mining Lands Management 1226 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda environmental systems. Also, the results differ seeks serious attention in recent decades. from that of Shinyanga rural District study by Consistently, IPCC (2007) and NMSA (2007) Lyimo and Kangalawe (2010) who reported that reveal that there has been a very high warming both minimum and maximum temperature showed and variable temperature trend over time. IPCC an increasing trend but the minimum temperature (2013) added that globally averaged combined increased sharply while the maximum temperature land and ocean surface temperature data as increased gradually. This implies that different calculated by a linear trend, show a warming of areas experiencing similar climatic conditions can 0.85 [0.65 to 1.06] °C, over the period 1880– experience changes in climate differently. The 2012, when multiple independently produced finding indicates that climate anomalies datasets exist. manifested in temperature rise and variability

Figure 8 Maximum and minimum temperature deviations from the long-term average

The total increase between the average of the pronounced with roughly 0.4° C per decade whilst 1850–1900 and the 2003–2012 periods is 0.78 average precipitation remained fairly stable over [0.72°C to 0.85” °C] based on the single longest the last 50 years in the country (Brohan et al. dataset. Increases in temperature adversely affect 2006; Schneider, et al. 2008). crops especially in tropical and sub tropical areas Local communities’ perception to rainfall where heat has become a limiting factor for crop anomalies production. The increase in temperature also increase evapo-transpiration rate of plants and The perception of households towards rainfall increase chances for severe drought (IPCC, 2007). patterns was measured in the numbers of According to Deressa and Hassan (2009), climate perceived responses. Questions bearing four change will reduce Ethiopian crop yields. Based response options (increasing, decreasing, constant on their studies by using three different models and don’t know) were asked to the selected under different scenarios, income per hectare will households (see Figure 9). Figure 9 presents decrease by 9.71% - 303.27% by 2050 and communities’ perceptions of temporal rainfall 10.3.391-418.01% by 20100. Besides the variability in the study area. It is evident from the increasing temperature trends in the study area Figure that the majority of the respondents (83%) has paramount impact on water, land and perceived a decrease in rainfall amount; 6 % vegetation resources through worsening evapo- perceived an increase in it and 10 % of them transpiration with negative consequences on the perceived a constant distribution pattern. productive capacities of these valuable Meanwhile, 2 % of the farmers interviewed did resources. The IPC (2007) studies using 22/23 not perceive whether there is a change or not in climate models confirm that temperature in rainfall pattern. All the survey result regarding Ethiopia increased at about 0.2° C per decade. perception of households is consistent with the The increase in minimum temperatures is more Journal of Degraded and Mining Lands Management 1227 Climate variability, communities’ies’ perceptions and land management strategies in Layay GaGayint Woreda qualitative information obtaineded from FGDs and shortage of precipitation thatat threats the natural interviews. resources and overall develoelopment efforts of specific places through exexacerbating water shortage for some activity oor for some social groups. Therefore, the differference in temporal patterns of drought, includingdg duration, magnitude andseverity,overarangeoftif time scales is highly demanded for designing apprppropriate adaptation and mitigation measures.s. The long -term standardized rainfall anomaaly index (SRAI) results are illustrated in Figurure 10 for the study area. Figure 10 demonstratestes the standardized rainfall anomaly index (SRARAI) in Lay Gayint woreda. Itisclearfromthethe Figure that the Figure 9. Proportion of responondents by their rainfall is characterized byffluctuation of wet perception to rainfall pattern (SurSurvey result, 2013) anddryyearsinaperiodicpc pattern. Out of 32 years of observation, the yeayears 2002 and 2008 FGD and interview participcipant community were severely and extremelyely dry respectively members as well as expexpert interviewees while the years 1995, 200404 and 2009 were unanimously recognized thee variability and moderately dry. These long-teterm dry conditions changing patternsofrainfallamount, am its timing with precipitation deficiency hhad great influences and distribution in the study arearea over the past 20 on crop yields in the study arearea. On the contrar y, years. Overall, increased tetempera ture and the years 1979, 1986, 199994 and1998 were declining rainfall are the predomominant perceptions moderately wet while the yeayears 1987 and 1989 of the participants in the studyy aareas. In addition were in very wet conditions. OOnly the years 1984 to the perception of the comommunity, drought and 1990 received near normrmal rainfall amount analysis was done using standardardized precipitation (same to the long-termaverageage rainfall). index.Droughtisanaturalhazazard measured by

2,00 1,50 1,00 0,50 0,00 -0,50

-1,00 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 20052005 2006 2007 2008 2009 2010 SPI Values -1,50 -2,00 -2,50 -3,00 Time in Year

Figure 10. Standardized Precipecipitation Anomaly Index (SPI) from 1979-2010 (Sourcurce: NMA, 2011 )

Table 3 presents the statisticalal analysis of da ily followed by August (231.211 wwith 30.77 PCPD), precipitation data (1979 - 2010)0) with 11,322 daily while the lowestwasrecordeded in December (4.33 records. It is clear from the Tabable that month to mm with 3.46 PCPD) closelyly fofollowed by January month rainfall variability is conconsiderable across (4.44 mm with 4.71 PCPD) aand February (5.58 the years in Lay Gayint woredaeda. July (10.8583) mm with 4.57 PCPD). From ththe analysis, it was andAugust(9.7475)hadthee highest standard observed that rainfall is ususually at its peak deviation in the study area. Thee hhigh est amount of between June and Septemberr which receive over average monthly rainfall was alsolso recorded in Ju ly 78.16 % of the rainfall amounount in these months (276.04 mm with 30.66 averagee rrainy days/PCPD) (see Table 3).

JournalofDegradedandMininging Lands Management 1228 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda

Table 3. Statistical Analysis of Daily Precipitation Data (1979 – 2010) Number of years = 32 Number of leap years = 8 [A year, occurring once every four years, which has 366 days including 29 February as an intercalary day] Number of records = 11, 322 Month PCP_MM PCPSTD PCPSKW PR_W1 PR_W2 PCPD January 4.44 0.7663 9.4172 0.062 0.6242 4.71 February 5.8 0.9884 8.8894 0.0796 0.5313 4.57 March 42.78 4.4025 5.9381 0.1909 0.7051 12.89 April 46.09 3.9996 5.5654 0.2065 0.7685 15.06 May 39.91 4.2002 5.6768 0.1861 0.7073 12.89 June 76.25 5.3458 3.5684 0.3824 0.8458 22.23 July 276.04 10.8583 2.0983 0.75 0.9599 30.66 August 231.21 9.7475 2.5199 0.625 0.9629 30.77 September 83.67 4.328 2.6183 0.3189 0.8568 22.74 October 28.96 3.458 6.3218 0.0924 0.6667 7.8 November 14.15 2.3227 7.9265 0.0689 0.6369 5.11 December 4.33 0.9688 10.3122 0.0529 0.5702 3.46 PCP_MM = average monthly precipitation [mm] PCPSTD = standard deviation PCPSKW = skew coefficient PR_W1 = probability of a wet day following a dry day PR_W2 = Probability of a wet day following a wet day PCPD = average number of days of precipitation in month

The standard deviation is important to show the natural disasters (NMA, 2007). Other studies also spread of a probability distribution across months reported the same (Kide, 2014; Lemmi, 2013; and years; it relates directly to the degree of Assefa, 2011; Bryan et al., 2013). Similar results uncertainty (insecurity) associated with predicting were again reported by Maddison (2006) whereby the value of a random variable. High standard a significant number of farmers in eleven African deviation values reflect more uncertainty countries believed that temperatures had increased (insecurity) than low values. When the standard and precipitation had declined. deviation values are examined, it is observed that the values of most months (June, July, and Farming communities’ adaptation strategies August) are higher than other months (see Table to climate change 4). The relation between the standard deviation Rural communities have many ideas on how to and the average values indicate that deviation prepare for future climate variability with a strong from the normal distribution cannot be ignored. motivation to move out of poverty. Similarly, the The study result is in line with Famine Early rural communities of Lay Gayint woreda Warning System Network (2008) study that states implement different physical and institutional after a record harvest in October 2007, Ethiopia adaptation strategies to combat the long-term settled into a drought. Little rainfall was recorded impacts of climate variability and/or climate during the October and November rainy season. change. Adaptation strategies are methods the Rainfall was also predicted to be below normal in local people use to adjust themselves with the the March-to-May rainy season and by the end of existing climate variability and climate change. May 2008, millions of people faced with hunger Adaptation to climate variability is a two-step in eastern Ethiopia as crops failed and food prices process which requires that farmers perceive soared. Two successive seasons of poor rains left climate variability in the first step and respond to eastern Ethiopia in drought, and the effect on variability in the second step through adaptation. vegetation. This finding is also congruent with This is very important to manage future patterns several empirical research findings. For instance, of climate variability. Therefore, the adaptation NMA recognized that food security, water and methods were identified by asking the farmers energy supply, poverty reduction and sustainable about their perceptions of climate variability and development endeavors are being challenged by the actions they take to counteract the negative current climate variability in Ethiopia through impacts of climate variability (Maddison, 2006; aggravating natural resource degradation and

Journal of Degraded and Mining Lands Management 1229 Climate variability, communities’ies’ perceptions and land management strategies in Layay GaGayint Woreda

Mentez et al., 2008;Deressaetat al., 2009; Bryan et the adverse impact of climateate variability and/or al., 2013). climate change and associatediated extreme climatic Physical adaptation stratategies : This study eventssuchasdroughts,floodinoding, hailstorms, and tried to identify the physical adadaptation options soil erosion (refer to Figure 11)). used by the studied rural commumunities to mitigate

64.8% 65.1% 70 52.32.3% 60 45% 50 40 25.5% 31.1% 30 15.5% 14.0% 17%% 18% 20 10 0 % of respondents

Figure 11. Respondents’phphysical adaptation strate gies to climate change [Surveyey result, 2013]

Figure 11 presents the phyhysical adaptation impact of climate variability aand climate change ; practices used by rural commmunities against whereas small scale irrigationn (14.0%) is the least climate variability. Physical adadaptation strategies practiced adaptation strategyy among the major focus on tactic decisions madeade in response to practices identified in the studytudy area. The limited seasonal climate variability. It is clear from the use of irrigation is attributed to the need for more Figure that, 65.1% ofthe respondondents use soil and capital, shortage of water andnd low potential area water conservation measures,6464.8% of them use for irrigation. Ethiopian agricugriculture is heavily soil fertility management and52.52.3% use adjusting dependent on natural rainfafall, with irrigation planting and harvesting dates as their methods of agriculture accounting for lesless than 1% of the adaptation to the negative imimpact of climate total cultivated land in the counountry (FEDP , 2008). variability. This implies thatat soil and water These results suggest that respespondents employed conservation, soil fertilitymanagement m and one form of adaptation strateategy or the other in adjusting planting and harvestinting dates were the ordertoreducetheeffectofof climate change on main physical adaptation measuasures used by the food crop production. The internterview participants farmers. Soil conservation techniqhniques, particularly and observation verify that coconservation tillage, constructing terraces, buildingg check dams and intercropping and crop rotationtation are also employed planting trees were found tobe b the main soil by the households of the stustudy area in their conservation measures used byy ththe community of farming practices. Accordinging to Environmental the study area for the purposesses of avoiding the Protection Authority EPA (201010) of Ethiopia, the risk of flooding and soil erosion. According to the use of these three agronomomic practices will information obtained from FGDGDs, the farmers in enhance the long-term sustainatainability of soils and each kebele were participating in a new system of improve the resilience of croprops to the impact of adapting natural resource conseservation methods , climate variability and/or climlimate change. Smith the so called five men strategyy which participate (2000)addedthatchangesinin cropping systems people for different farming actictivities and natural can offset many of the popotentially negative resource conservation. Five peoeople work in one impacts of climate variabilitility and/or climate group,andthenumberofgroupups in each Kebele change. varies based on the populationlation number reside Institutional adaptationion strategies: Local there. governments are implemlementing different With regard to inter-cropping/mixed institutional adaptation strategtegies in response to cropping and planting differentt varieties of crops, the impact of climate variabiliability and/or climate 31.1% of the respondents use thethem to adapt to the change. The finding shows ththat 53.4 % of the

JournalofDegradedandMininging Lands Management 1230 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda surveyed households received extension service institutional support and decision making (see Table 4) which would enhance efficient opportunities, smallholder farmers are powerless decision-making on the choice of adaptation to respond to the challenges of climate variability. strategies. The household survey indicates that out Mahmud et al (2008) argued that access to future of the total sampled households 48.2% had access climate information, agricultural extension and to credit whilst 51.8% of them were missing this credit services are determinant factors that create opportunity. In order to reduce the negative difference on farmers to take adaptation measures. effects of climate variability and/or climate This was also recognized by Bekele (2003) who change access to climate information deemed noted that farmers with significant extension necessary. However, only 24.6% of the contacts have better chances to be aware of households obtained climate information which changing climatic conditions and adaptation limits the households’ ability to get the necessary measures in response to climate variability. technology and resources. About 32.8% of the Nhemachena and Hassan (2008) in their findings respondents also obtained early warning of the study highlighted that access to affordable information from disaster prevention office of the credit increases financial resources of farmers and study area (see Table 4). their ability to meet transaction costs associated with various adaptation options they might want Table 4. Institutional adaptation strategies to to take. McSweeney et al. (2008) encourages climate variability used by the reactive adaptive measures at national and local respondents levels to combat climate change impacts and to Institutional adaptation Freq. Percentage ensure the nation’s food security. strategies Crop diversification (CD): CD is the most Early warning system 63 32.8 important adaptation method in reducing expected Information on climate 47 24.6 climate variability and/or climate change-induced Access to credit for 93 48.2 risks through reducing both natural and economic purchasing fertilizers uncertainties. A change in cropping pattern Access to extension 103 53.4 implies a change in the proportion of area under service different crops in the farmlands. It is also a shift Access to safety-net 82 42.5 from low-value to high-value agriculture for program enhancing agricultural output. However, the cropping pattern in an area depends mostly up on Source: Survey result, 2013 agro-climatic, technical and institutional factors (Vaidyanathan, 1992). In addition to reducing Over 42 % of the respondents reported access to natural and economic uncertainties CD is very social security program (Safety net program) much important to enhance nitrogen in the soil to indicating the severity of climate-induced hazards replenish the soil fertility and to provide a like recurrent droughts, flooding, hailstorms and reasonable quantity of the costly organic different crop, animal and human disease. In line fertilizers for farming communities (Hussain, with this survey report the FGDs and interview 2009). Households who have cultivated diverse participants reported that the government supports crops can also stagger his/her income all over the those 42.5 % critically food insecure households year and positively influence the adaptation have been beneficiaries of the productive safety decision. In the light of this, Smith (2000) states net program starting from 2005. Institutional that income source diversification is an adaptation adaptation strategies focus on strategic national strategy which has the potential to reduce decisions and policies on local to regional scales vulnerability to climate related asset losses.The taking into account long-term variability and survey result indicated that the major source of change in climatic conditions. Strengthening the respondents’ income is agriculture, mainly access to extension and credit services were the crop production. This finding is supported by dominant institutional adaptation strategies given Lemmi (2013) which indicated that the major to the farmers in the study area. Lipper et al. source of the households’ income was agriculture. (2014) noted the importance of institutional Mahmud et al. (2008) in his study pointed out that adaptation measures to the most vulnerable crop is the major staple food, foreign exchange smallholder farmers to cope with the impact of earner and source of income for the majority of climate variability as they lack financial, technical the people in Ethiopia. Therefore, farming and political means to support adaptation efforts. communities should be encouraged to adopt CD Same authors stressed that without access to to reverse the harmful impact of current and future information, technology, markets, finance, climate variability and/or climate change. Although the application of CD in the study area

Journal of Degraded and Mining Lands Management 1231 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda is too small its use is associated with low cost and farmers only depend on one type of crop for their ease of access by farmers. This argument has been livelihood in Ethiopia. According to Aberra supported by previous studies (Lemmi, 2013; (2002), access to farmland is affected by the rapid Meseret, 2009). population growth which resulted in diminution of Taking into account the multidimensional farm sizes, increase landlessness and food benefits of CD in managing risks and ensuring insecurity in many developing countries. Similar food security, this study investigated the patterns, to most highlands of the country, the landholding trends and determinants of CD in the study area of farmers in the study area is very small. This using primary data for a period of one year (2010- study is congruent with that of Growth and 2011).The result found out 0.11 CDI showing that Transformation Plan/GTP (2016) of Ethiopia that the cultivated land is dominated by one or few the majority of smallholder farmers are practicing crops in the study area (refer Table 5). This might subsistence farming on less than one hectare of be due to various inter-related factors. Although land. According to the information obtained from the majority of the local people are engaged in the interviewed famers and extension agents in the crop production as their main source of income study sites land size positively influence the result of crop diversification index (CDI) was households’ crop diversification decisions. The very small (0.11 index score) indicating that the more the land size owned by the farmers the more cultivated land is dominated by few crops in the the probability of diversifying crops. In fact, study area (see Table 5). larger farm sizes may enable households to allot their land to multiple crops than smaller holdings. Table 5. Average area coverage of crops in the Other previous studies also indicated that land year 2011/12 size positively affected crop diversification Major Area coverage in Percentage (Bonham et al., 2012). On the contrary, the study crops hectare in eastern Hararghe highlands of Ethiopia Wheat 58.97 32.28 revealed that CD has shown an increasing trend Teff 30.42 16.65 from 2004 to 2009 production periods (Mesfin, Barely 26.88 14.71 2012). Pea 24.99 13.68 Beans 15.38 8.42 Conclusions Lentil 11.94 6.53 Sorghum 8.00 4.38 Both the meteorological data and local Cheek pea 2.75 1.51 communities’ perception showed considerable Haricot been 2.00 1.09 long-term climate variability from the period 1979 Sunflower 1.38 0.76 to 2010. The majority of the rural households Index - 0.11 indicated that they had observed increased Source: Survey result, 2013 temperature and drought and decreased rainfall amount and/or erratic in distribution. This implies The rugged natures of the topography, land that the impact of climate variability and/or shortage, rainfall variability, poor soil conditions change in the study area is at the community and in turn limited irrigation facilities have level. The standardized precipitation anomaly influenced CD. In the light of this, Kankwamba et index (SPI) characterized the woreda rainfall by al. (2012) stated that CD is determined by rainfall fluctuation of wet and dry years in a periodic distribution. Bhattacharyya (2008) realized that pattern. Extremely and severely dry years were CD is more prominent in rain-fed areas than in observed in 2002 and 2008 respectively with great irrigated ones. This implies that there is need to impact on crop yields in the study area whilst only encourage farmers to do their tillage during the the years 1984 and 1990 received near normal rainy season by the help of extension workers. rainfall amount. In response to long term There is also a need for substantial investment in perceived changes, farmers have adopted different reliable weather information dissemination strategies to cope up with the consequences of systems pertaining to climatic conditions to climate variability and to manage future patterns reduce the adverse effects of unpredictable rainfall in climate variability. In this study, adaptation patterns. measures have been placed in two main The sources of livelihood for the rural categories: physical and institutional adaptation communities is highly attached to farmland and strategies. Soil and water conservation, soil related resources. The size of farmland has fertility management and adjusting planting and affected communities’ food security status. harvesting dates were the main adaptation Rehima et al. (2013) report that smallholder measures used by the farmers in the first (a)

Journal of Degraded and Mining Lands Management 1232 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda category. Although some local communities’ Bekele, S. 2003. Resource degradation and adoption of adaptation strategies to climate change are not land conservation technologies in the Ethiopian sufficiently supported by extension service, credit, Highlands: A case study in Andit Tid, North Shewa. small-scale irrigation, and safety-net program Agricultural Economics. Bewket, W. 2009. Mainstreaming climate change were the major institutional adaptation strategies adaptation into project planning and programming. given to the farmers. Crop diversification index is Paper submitted to Norwegian Church Aid-Ethiopia found very low (0.11) indicating that the (DCA-E), Addis Ababa. cultivated land of the study area is dominated by Boko, M., Niang, A. Nyong, C. Vogel, A. Githeko, M. one crop due to small land holding size, limited Medany, B. Osman-Elasha, R Tabo, and P. Yanda. irrigation facilities, rainfall variability, rugged 2007. Climate Change: Impacts, Adaptation, and topography and poor soil. In conclusion, Vulnerability. ecologically designed agricultural systems that Bonham, C.A., Gotor, E., Beniwal, B.R., Canto, G.B., can provide a buffer against extreme events need Ehsan, M.D. and Mathur, P. 2012. The patterns of use and determinants of crop diversity by pearl to be the primary concerns of the State millet (Pennisetum glaucum (L.) R. Br.) farmers in government to minimize climate-induced risks on Rajasthan. Indian Journal of Plant Genetic the livelihoods of rural households. Local leaders Resources 25(1): 85-96. should enforce integrated land management Brohan, P., Kennedy, J.J., Harris, I., Tett, S.F.B. and practices that enable to regulate the local climate Jones, P.D. 2006. 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Journal of Degraded and Mining Lands Management 1234 Climate variability, communities’ perceptions and land management strategies in Lay Gayint Woreda

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