© Kamla-Raj 2014 J Hum Ecol, 47(2): 111-116 (2014)

Factors that Influence Choice of Drought Coping Strategiesin Limpopo Province, South Africa

M. Rakgase1 and D. Norris2

1University of the Free State, P.O. Box 339, Bloemfontein 9300, South Africa2University of Limpopo, Private Bag X1106, Sovenga 0727, South Africa

E-mail: 1<rakgasema@gmail.com>, 2< David.Norris@ul.ac.za>

KEYWORDS Multinomial Regression. Farmers. Socio-economic Characteristics

ABSTRACT Strategies for effectively managing risks and adapting to climate change involve adjustments tocurrent activities. The objective of this study was to investigate the association between the socio-economicprofile of farmers and their choice of drought-coping strategies. Multinominal logistic regression analysis was used.Descriptive statistics showed low level of education and literacy among the farmers with three-quarters of thefarmers being male. Most farmers had access to extension services, which is a positive finding. Results of themultinominal regression analysis on the link between farmers’ socio-economic profiles and drought coping strategiesshowed that farm type and literacy level influenced the choice of drought-coping strategies. Improvement inliteracy levels through extension or informal education should be prioritised to increase knowledge in drought-preparedness and mitigation. Particular attention should be paid to SLAG and communal land farmers.

INTRODUCTION

Drought is one of the most frequent and dev-astating phenomena that occur in South Africa(Austin 2008). Ngaka (2012) indicates thatdrought in South Africa is a major disaster interms of total economic loss and number of peo-ple adversely affected. About half of the surfacearea of South Africa is arid and experiences highlyvariable rainfall and frequent droughts. The fre-quency and impact of natural disasters in thefarming community in South Africa have in-creased significantly in the last decade, withdrought notable as one of the most commontype of disaster (Olaleye 2010). Nhemachema(2008) reports that Southern Africa is expectedto experience increases in temperature and re-duction in rainfall coupled with increased fre-quency of droughts and floods as a conse-quence of changes in climate conditions. Ac-cording to Maponya and Mpandeli (2012), theWorld Bank has reported that South Africa hasbeen getting hotter over the past four decadeswith increases in the number of warmer daysand a decline in the number of cooler days. Ag-riculture, which is highly dependent on climaticvariables of temperature, humidity and precipi-tation, is expected to be highly affected by thesechanges in climatic conditions (IPCC 2012). Ex-posure and vulnerability to climate extremes aredynamic, varying across temporal and spatialscales, and depending on economic, social, geo-graphical, cultural, institutional, governance and

environmental factors (IPCC 2012). People liv-ing in rural areas and resource-poor farmers, whoare largely dependent on agriculture, are oftencited as more vulnerable to the impact of drought(Olaleye 2010).

Drought losses have long been attributed topoor vegetation, soil and water management andthe absence of a sufficiently complete manage-ment strategy has been pointed out as beingresponsible for exacerbating the negative im-pacts of drought (Seymour and Desmet 2009).Communities which inhabit drought-prone ar-eas have demonstrated intricate and diverseadaptation strategies to drought. These com-munities respond to drought by evasion (sea-sonal migration) or endurance (for example,through forage management, changing livestocktypes and numbers, water and soil conservationand finding alternative sources of income (Sey-mour and Desmet 2009).

Improvement of drought management strat-egies by farmers, especially the resource-poorfarmers, requires an understanding of the farm-ers’ perceptions on drought and their drought-coping strategies. The factors that influence theirperceptions and how they cope with droughtsituations need to be understood so that theirdrought mitigation plans could be enhanced and,as a consequence, preserve their livelihoods.The appropriateness and effectiveness of ad-justments by farmers in response to drought sit-uations depend on a number of factors, such asinformation, knowledge and skills of individual

112 M. RAKGASE AND D. NORRIS

farmers. An understanding of the socio-econom-ic impact of drought and of farmers’ coping mech-anisms is critical in designing technological andpolicy interventions for more effective droughtmitigation.

Objectives

The objective of the study was to determineif there is an association between the socio-eco-nomic profile of farmers and their choice ofdrought-coping strategies.

METHODOLOGY

Study Area

The study was conducted at five local munic-ipalities (Molemole, Aganang, Blouberg, Polok-wane and Lephalale) of the Limpopo Province.

Data Collection

The primary data was collected by using astructured questionnaire survey and focus groupdiscussions. Information captured on the so-cio-economic characteristics of farmers includ-ed sex, age, education level, literacy level, farm-ing experience, access to agricultural extension,farm income, off-farm income, farm organization,farm size, farm type and location (municipality).Purposive and random sampling procedureswere used to select the sample.

Data Analysis

This study employed a multinominal logit(MNL) model (Greene 2003) to analyse factorsinfluencing choice of drought-coping strategy.Multinominal logistic regression uses a linearpredictor function to predict the probability thatobservation i has outcome k, of the followinggeneral form:

f (k, i) = βo,k + β1,kX1,i + β2,k X2,i + …+ βM,kXM,i,where βmk is a regression coefficient associ-

ated with the mth explanatory variable (age, sex,education etc) and the kth outcome (rank score).The regression coefficients and explanatory vari-ables are normally grouped into vectors of sizeM+1, so that the predictor function can be writ-ten more compactly:

f (k, i) = βk . Xi,

where βk is the set of regression coefficientsassociated with outcome k, and Xi is the set ofexplanatory variables associated with observa-tion i. The dependent variables in the empiricalestimation are adaptation strategies that are cho-sen by the sample households

The MLN has model has response probabil-ities:

Where y denote a random variable taking onthe values {1,2….j} for choices j, and x denote aset of conditioning variables. In this case, y rep-resents the adaptation measure chosen by thelivestock farmers while x represents a number ofsocio-economic characteristics of householdsand other factors.

Statistical Package for Social Sciences (SPSS)was used for data analysis.

RESULTS AND DISCUSSION

The summary of descriptive statistics forsocio-economic profiles of the farmers is pre-sented in Table 1. The profile of the farmers ischaracterised by a large number of older farmersand low levels of education and literacy. Mostof the farmers (over three-quarters) were male.Extension services seem to reach many farmersas 95% reported to have access to extensionservices. Ninety seven percent of farmers re-ported to have access to TV, which could be anindication of improved living standards. Fewfarmers had access to credit, which could be animpediment to growth and development of theirfarming operations.

The results of the association between farm-er socio-economic profiles and drought-copingmechanisms are presented in Table 2. Most ofthe socio-economic characteristics of the farm-ers and associated farm characteristics (farm size,farm type) had no influence (P>0.05) on the farm-ers’ choice of drought coping strategies. Thereis varying information in literature as to the in-fluence of socio-economic profiles of farmerson their drought-coping strategies. Ajao andOgunniyi (2011) found influence of age, farmsize, access to extension, gender and non-farmincome on the choice of drought coping strate-gies. The study by Moyo et al. (2013) observedfew explanatory variables as having influenceon the coping strategies. Household herd size,household total income and household access

FARMERS ON THE CHOICE OF DROUGHT COPING STRATEGIES 113

aptation to climate change was influenced byeducation, household size, gender, livestockownership, access to extension service, avail-ability of credit and environmental temperature.Smithers and Smit (1997) reported that the ca-pacity of households to adapt to droughts wasinfluenced by resource availability and govern-ment policy. In the study by Ofuoku (2011), themajor barriers to climate adaptation were lack ofinformation, lack of money and inadequate land.

However, the present study showed that farmtype and literacy level had influence (P<0.05) onfarmers’ choice of drought mitigating plans. Aunit increase in the variable literacy level (1.095)is associated with an increase of 2.99 in the logodds of farmers selling their assets to mitigatethe effect of drought. This was also observedwith respect to selling and culling of animals; aunit increase in the variable literacy level (3.14)is associated with an increase of 2.39 in the logodds of farmers selling or culling their livestock.With respect to farm type, a unit ‘decrease’ inthis variable (-0.75*) is associated with a decreaseof 0.47 in the relative log odds of farmers optingto move their livestock. In this instance, farmersin LRAD (Land Redistribution for AgriculturalDevelopment) farms are less likely to adopt herdmovement as a strategy to cope against droughteffects. Most of these were farmers who wereoperating as individuals and not groups. Farm-ers in communal farms and farmer groups inSLAG (Settlement Land Acquisition Grant) farmswere more likely to move their herds duringdrought periods.

The study by John et al. (2011) showed thatfarm experience, farm income and farm size hadan impact on drought coping strategies whileage, education level and extension had no ef-fect. In a study on climate change adaptationstrategies, Tazeze et al. (2012) observed that sexof the household head, age of the householdhead and education of the household head, fam-ily size, livestock ownership, household farmincome, non/off-farm income, access to credit,distance to the market center, access to farmer-to-farmer extension, agro-ecological zones, ac-cess to climate information, and extension con-tact, had a significant impact on choice of cli-mate change adaptation strategies.

Legesse et al. (2012) investigated the small-holder farmers’ perception and adaptation to cli-mate variability and climate change in Ethiopiaand the results of the study showed that agro-ecological location, sex of household head, family

Table 1: Descriptive information on farmers

Characteristic Percentage

Age<30 1.230-40 4.841-50 1.751-60 32.7>60 44.2

SexMale 77Female 23

EducationNo education 13.7Primary 31.5Secondary 35.8Certificate 7.9Diploma 10.9

Literacy LevelInnumeracy 18.2Illiterate 9.1Partial Illiterate 30.9Literate 41.8

Farming Experience (yrs)0-10 27.911-20 30.921-30 17.0>31 24.2

Farm Size (ha)0-1000 38.81001-2000 13.32001-3000 11.5>3000 36.4

Access to Agricultural Extension ServicesYes 95.2No 4.8

Access to CreditYes 18.2No 81.8

Access to TVYes 97.0No 3.0

to relief grazing farms affected choice of copingstrategies while age, gender and education lev-el had no effect. Nti (2008) observed that litera-cy level, membership with a farmer organization,household income, and location of householdshad positive and significant impacts on adapta-tion to drought.

Al Hassan et al. (2013) reported that the pres-ence of markets, informal credit from friends andrelatives, location of farmer, farmer-to-farmer ex-tension, noticing of decrease in rainfall and no-ticing of increase in temperature, influencedfarmers’ choice of indigenous climate- relatedstrategies in Ghana. In the study by Opie (2011),coping strategies were associated with house-hold size, age, sex of household head and house-hold assets such as land, livestock and otherassets. Deressa et al. (2010) observed that ad-

114 M. RAKGASE AND D. NORRISTa

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FARMERS ON THE CHOICE OF DROUGHT COPING STRATEGIES 115

size, off-farm income, herd size, frequency ofextension contact and training, were determinantfactors influencing adaptation strategies. Der-essa et al. (2008) observed that wealth (on-farmincome, off-farm income and livestock owner-ship) and household characteristics, such as lev-el of education, age of household head andhousehold size, increased the probability of ad-aptation to drought. Farm location also influ-enced farmers’ adaptation to climate change.

Gunn et al. (2012) assessed farmers’ psycho-logical distress and coping in a time of droughtand observed that age, gender and type of stres-sor had influence on the type of coping strate-gy. The authors concluded that it is critical todevelop tailored interventions to assist farmersto cope more effectively during future droughts.This further supports the importance of attun-ing the mitigation strategies to socio-economicprofiles of farmers.

CONCLUSION

Most of the socio-economic characteristics(sex, age, farming experience, access to agricul-tural extension, farm income, off-farm income,farm organization, farm size and location (mu-nicipality) were not important as predictors ofchoice of drought-coping strategies. This dif-fers from other studies that observed relation-ships between most socio-economic character-istics (such as education level, age, farming ex-perience, gender, farm income) and drought-cop-ing strategies. However, farm type and literacylevel showed an association between farmer pro-files and drought-coping strategies.

RECOMMENDATIONS

The findings have extension and policy im-plications. Improvement in literacy level throughextension or informal education (especially thatthe age profile of farmers showed that most ofthem were elderly), should be prioritised to in-crease knowledge in drought-preparedness andmitigation. Information on grazing managementand drought preparedness should be shared withfarmers especially those in communal and SLAGfarming systems.

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