Presentation by John Bosco Baguri Sumani

UDSWa Campus

During the a GGA/GGTA Conference at KNUST from 1-4th August, 2012

Presentation Outline

IntroductionBrief Literature ReviewProblem statementStudy objectivesStudy area and methodologyResults Conclusion and RecommendationsReferences

Introduction

Successive gov’ts have initiated policies, programs, plans and initiatives to manage out-migration since independence

Literature surveyed revealed that out-migration has been increasing in the Upper West Region

Factors accounting for migration is a subject of debate (Suhrke, 1993, Akokpari, 1998; Perch-Nielson, 2004; Mcleman and Smit, 2006)

Brief Literature survey

• Migration as a developmental challenge (Davidson et al (2003 and Mcleman and Smit, 2006)

• No agreement on causes of migration (suhrke, 1993 ; Akokpari, 1998 and Perch-Nielson, 2004)

• Neo-classical views dominate (Massey, 1993)• Environmental degradation is often mentioned as

physical factors (Suhrke, 1993; Bilsboro, 1991)• Climate is hardly mentioned or only mentioned

tangentially (Perch-Nielsen, 2004)• Hence the design of this

Problem statementNadowli District has been experiencing out-

migration since its creationsReasons for migration:EconomicSocio- culturalPopulation pressureConflicts/warsEnvironmental conditions hardly mentionedEnvironment-migration relations at the general

level without disaggregating the various factors

• However, climatic variables are indispensable resources for agric productivity and production

Climate variability/change has been blame elsewhere for migration (Adelekan and Afolayan, 1999; Magadza,2000; Meze-Hausken, 2000 and Mcleman and Smit,2006)

• Hence, this study was designed to determine the influence of climate variability on human migration

Study objectives

• Main objectivei. To find out the influence of climate variability

on human migration in Nadowli District• Specific objectives:i. Climatic (key variables) trends over the yearsii. Causes of migration

iii The relationships between climatic trends and migration

iv The relationship between migration and sexv The relationship between migration and age,

and finallyvi The socio-economic effects of out-migration

on the source region

Study Approach and Methodology

• The study area is Nadowli District• Data sourcesi. Primaryii. Secondary• Sampling techniquesNon-Probabilityi. Purposive ( GMA and Returned migrants)

• Probability samplingi. Cluster sampling (3 clusters)ii. Western- Sankana & Charikpong; Central- Duong

& Daffiamah and Eastern- Naro & Fian iii.Systematic sampling (25hh in each c’ty)- sample

size of 150• Data collection instruments:i. Questionnaire administrationii. Face –to- interviews iii.FGD

Conceptual Framework

• Climate and migration variables are difficult to bring under 1 framework (Perch-Nielson ,2004 and Mcleman and Smit, 2006)

• This study modified Mcleman and Smit (2006) model with ideas from Meze-Hausken (2000) and Perch-Nielson (2004)

• According to Mcleman and Smit, V=f(Eslit +ACslit)

Conceptual framework in response to climate variability

Causes of migration

Economic Socio-cultural Environmental Population Conflict/wars

Climate variability Climatic conditions

Agric performance

Hsehold decisionCan cope?

Yes, no migration No, Out-migration

Perceived favourable destination Seasonal Permanent

Modified C’ties:.Previous membersReturn migrants

Results

Community Description of Temperature

Temperature

Pre-2000 Post-2000 Future

Description Frequency (%) Frequency (%) Frequency Percentage

cool 130 87 0 0 0 0

warm 18 12 150 100 99 66

Don't know 2 1 0 0 51 34

Total 150 100 150 100 150 100

Source: Field notes. 2011

Rain Days

Community description of rainfall

Table 4.11: Community description of rainfall

Rainfall

Pre-2000 period Post-2000 period

Description Frequency Percent (%) Frequency Percentage (%)

Adequate 139 97 2 1

Inadequate 11 3 148 99

Don't know 0 0 0 0

Total 150 100 150 100

Source: Field notes, 2011

Causes of migration

%

Destination of migrants

Duration of migrants?

Sex of migrants

Socio-economic effect of migration

Consequence Frequency Percentage (%)

Beneficial 131 87

Negative 9 6

Neutral 10 7

Total 150 100

Conclusion

• Over 90% of the people of the study area are peasant farmers and therefore climate-dependent

• Climate variability is the major cause of out-migration in the Nadowli District

• Out-migration is the last resort • There is an inverse relationship between MAR

and MAT

• Climate- induced migration is affects men decision to migrate than women

• There is an emerging pattern and trend of migration (destination and duration)

• Out-migration is generally beneficial with minor negative consequences

Recommedations

1. Vigorous public education on adaptation and mitigation strategies

2. Construction of irrigation dams/dug outs3. Provision of improved seeds and crop varieties4. Provision of micro-credits to peasant farmers,

especially women5. Cultivation of non-traditional crops and

livestock rearing

6. Improved climate prediction and weather forecasting

7. Formulation and implementation of migration policy

References

• Abdul-Korah, G.B. (2007). ‘Where is not home?’: Dagaaba migrants in the Brong Ahafo Region, 1980 to the present. African Affairs, 106, 71-94.

• Adelekan, I. O. & Afolayan, A. (1999). The role of climatic variations on migration and human health in Africa. The Environmentalist, 18(4), 213-218.

• Adiku, S. G. K., Dayananda, P. W. A., Rose, C. W. & Dowuona, G. N. N. (1997). An analysis of the within-season rainfall characteristics and simulation of the daily rainfall in two savanna zones in Ghana. Agricultural and Forest Meteorology, 86, 51-62.

• Akokpari, J. K., (1998). The State, refugees and migration in Sub-Saharan Africa. International migration, 36, 211-234.

• McLeman, R. and Smit, B. (2006). Migration as an adaptation to climate change. Climatic Change, 76, 31-53.

• Nabila, J.S. (1974). The migration of the Frafra of northern Ghana: A case study of cyclical labor migration in West Africa .Unpublished doctoral dissertation, Michigan State University, East Lansing.