Adaptation choices, community perceptions, livelihood linkages and income dynamics for district producer communities surrounding Nyatana Game Park in Zimbabwe
- Authors: Taruvinga, Amon
- Date: 2011
- Subjects: Game reserves -- Zimbabwe , Wildlife conservation -- Zimbabwe , Wildlife management -- Zimbabwe , Sustainable development -- Zimbabwe , Game farms -- Zimbabwe , Rural poor -- Zimbabwe
- Language: English
- Type: Thesis , Doctoral , PhD (Agricultural Economics)
- Identifier: vital:11154 , http://hdl.handle.net/10353/476 , Game reserves -- Zimbabwe , Wildlife conservation -- Zimbabwe , Wildlife management -- Zimbabwe , Sustainable development -- Zimbabwe , Game farms -- Zimbabwe , Rural poor -- Zimbabwe
- Description: This thesis explores human-wildlife interactions under community managed game parks. The thesis consists of an introductory chapter, study location chapter and four self-contained studies based on different samples from created clusters surrounding Nyatana Game Park, which make up the rest of the thesis chapters. Chapter one presents an introductory overview of wildlife management in Zimbabwe, specifically looking at human-wildlife interactions under CAMPFIRE projects, welfare dynamics and conservation implications for the surrounding communities who share boundaries with community-managed game parks. The chapter concludes by highlighting the challenges facing community-based wildlife conservation in Zimbabwe as well as the key concepts that will be the subject of the rest of the thesis. Chapter two presents the study location; it highlights the road map to the study area, starting with the provincial location, and indicates the specific districts from which respondents were selected. A brief agro-ecological summary of the study area is also presented; it looks specifically at climate, vegetation and a demographic data of the study area. Chapter three: Can game parks be trusted as livelihood sources? To answer this topical question, Chapter three explores livelihood adaptation strategies for households who share boundaries with Nyatana Game Park. Most of the community managed game parks, under CAMPFIRE principles in Zimbabwe, were established with the primary objective of generating revenue for the surrounding communities; this was done in the hope of using positive returns from game farming to promote the conservation of wildlife. Has this materialised in practice? Descriptive results from this study seem to suggest otherwise, where mixed farming and gold panning were the major livelihood adaptation choices reported by most households. The revenue from game farming was reported to be too low and inconsistent, to such an extent that the majority of the community regarded it as risky and unreliable. A multinomial logistic regression model for correlates of adaptation choices indicated that access to credit, markets, and extension may be some of the current institutional constraints inhibiting households from accessing off-farm sources for their livelihoods. In addition, household size, gender and age may enhance the adaptive capacity of households to move out of risky crop faming into other off-farm portfolio diversifications. The study, therefore, suggests that game parks, according to the evidence uncovered by the study, may not be trusted as a reliable and sustainable livelihood source. If local communities who share boundaries with game parks do not view them as reliable and sustainable livelihood sources, as concluded in Chapter three, how can they (local communities) be trusted to conserve them? To assess their perceptions of game parks, Chapter four presents a multinomial logistic regression model for perceptions of society on game parks using the African elephant as a typical example. The results suggest that Problem Animal Control (PAC) perceptions, livestock predation and issues of low and poor revenue distribution may be some of the critical perceptions capable of influencing surrounding communities to negatively participate in the conservation of wildlife. The results further suggest that using wildlife proceeds to finance observable local common pool infrastructure may positively influence the surrounding communities to conserve wildlife. The chief conclusion regarding game parks, therefore, was that the surrounding communities were in favour of the obliteration pathway, although minimal conservation perceptions were also available. Given the negative conclusions regarding game parks, as suggested in Chapters three and four, citizens would then wonder if any meaningful hope for community managed game parks exists. Chapter five probes the buffer zone livelihood link under community managed game parks, using evidence from the Nyatana Game Park. The binary logistic regression model results, for buffer zone participation and resource extraction combinations by surrounding communities, suggest that resource extraction may be market driven rather than focussing on domestic consumption. The study therefore concludes that the buffer zone livelihood link as currently practiced, though potential, may fail to address the livelihood expectations of the sub-district producer communities. The study therefore calls for extreme caution whenever the buffer zone livelihood link is considered, because several institutional and design conflicts exist within this dynamic. In Chapter six, the study further probed the buffer zone income dynamics for the sub-district producer community. The results of descriptive statistics suggest that the contribution of buffer zone activities to household income may be significant with a positive correlation to household agricultural income for communities who reside inside or close to the park (primary sub-district producer community). Using the Gini decomposition approach and Lorenz curves, the study concluded that a buffer zone income may be capable of contributing to more equally distributed incomes for rural communities who share boundaries with game parks. With respect to the correlates of household income, the results suggest that household size and age may negatively influence income from buffer zone activities, while gender may have a positive effect. This was also true for education and Livestock Units (LUs) with respect to income from self employment; the former positively and the latter negatively related. The results further suggest that land size may also be positively significant in order to explain income from agriculture as well as total income. With regard to the distance from the buffer zone, the results suggest a negative influence with respect to the buffer zone, agriculture and total income. The implied message therefore suggests that buffer zones may provide active livelihood sources which are capable of financing rural household agriculture. The income equalizing effect which is portrayed may also further imply that, if correctly targeted and promoted, a buffer zone income could possibly address the current income inequality which is generic in rural areas. However, this potential may not be realized due to the current buffer zone design status (created for local secondary use as opposed to commercial primary use), restrictive policies and poor institutional support. With this dilemma facing community managed game parks (threats as summarised in Chapters three and four amid the potential hope summarized in Chapters five and six), Chapter 7 concludes the study by suggesting that the human-wildlife interaction model, though currently theoretical, may have significant practical potential in addressing the livelihoods of the surrounding communities as well as promoting the conservation of wildlife. This could be possible if available challenges that range from low revenue, insecure property rights, high human-elephant conflict and institutional design conflict for buffer zone utilization are corrected by means of the free market system. This would allow market forces to deliver on the expectations of the ―human-wildlife interactions model‖ – sustainable livelihoods for the former and intergenerational conservation for the latter.
- Full Text:
- Authors: Taruvinga, Amon
- Date: 2011
- Subjects: Game reserves -- Zimbabwe , Wildlife conservation -- Zimbabwe , Wildlife management -- Zimbabwe , Sustainable development -- Zimbabwe , Game farms -- Zimbabwe , Rural poor -- Zimbabwe
- Language: English
- Type: Thesis , Doctoral , PhD (Agricultural Economics)
- Identifier: vital:11154 , http://hdl.handle.net/10353/476 , Game reserves -- Zimbabwe , Wildlife conservation -- Zimbabwe , Wildlife management -- Zimbabwe , Sustainable development -- Zimbabwe , Game farms -- Zimbabwe , Rural poor -- Zimbabwe
- Description: This thesis explores human-wildlife interactions under community managed game parks. The thesis consists of an introductory chapter, study location chapter and four self-contained studies based on different samples from created clusters surrounding Nyatana Game Park, which make up the rest of the thesis chapters. Chapter one presents an introductory overview of wildlife management in Zimbabwe, specifically looking at human-wildlife interactions under CAMPFIRE projects, welfare dynamics and conservation implications for the surrounding communities who share boundaries with community-managed game parks. The chapter concludes by highlighting the challenges facing community-based wildlife conservation in Zimbabwe as well as the key concepts that will be the subject of the rest of the thesis. Chapter two presents the study location; it highlights the road map to the study area, starting with the provincial location, and indicates the specific districts from which respondents were selected. A brief agro-ecological summary of the study area is also presented; it looks specifically at climate, vegetation and a demographic data of the study area. Chapter three: Can game parks be trusted as livelihood sources? To answer this topical question, Chapter three explores livelihood adaptation strategies for households who share boundaries with Nyatana Game Park. Most of the community managed game parks, under CAMPFIRE principles in Zimbabwe, were established with the primary objective of generating revenue for the surrounding communities; this was done in the hope of using positive returns from game farming to promote the conservation of wildlife. Has this materialised in practice? Descriptive results from this study seem to suggest otherwise, where mixed farming and gold panning were the major livelihood adaptation choices reported by most households. The revenue from game farming was reported to be too low and inconsistent, to such an extent that the majority of the community regarded it as risky and unreliable. A multinomial logistic regression model for correlates of adaptation choices indicated that access to credit, markets, and extension may be some of the current institutional constraints inhibiting households from accessing off-farm sources for their livelihoods. In addition, household size, gender and age may enhance the adaptive capacity of households to move out of risky crop faming into other off-farm portfolio diversifications. The study, therefore, suggests that game parks, according to the evidence uncovered by the study, may not be trusted as a reliable and sustainable livelihood source. If local communities who share boundaries with game parks do not view them as reliable and sustainable livelihood sources, as concluded in Chapter three, how can they (local communities) be trusted to conserve them? To assess their perceptions of game parks, Chapter four presents a multinomial logistic regression model for perceptions of society on game parks using the African elephant as a typical example. The results suggest that Problem Animal Control (PAC) perceptions, livestock predation and issues of low and poor revenue distribution may be some of the critical perceptions capable of influencing surrounding communities to negatively participate in the conservation of wildlife. The results further suggest that using wildlife proceeds to finance observable local common pool infrastructure may positively influence the surrounding communities to conserve wildlife. The chief conclusion regarding game parks, therefore, was that the surrounding communities were in favour of the obliteration pathway, although minimal conservation perceptions were also available. Given the negative conclusions regarding game parks, as suggested in Chapters three and four, citizens would then wonder if any meaningful hope for community managed game parks exists. Chapter five probes the buffer zone livelihood link under community managed game parks, using evidence from the Nyatana Game Park. The binary logistic regression model results, for buffer zone participation and resource extraction combinations by surrounding communities, suggest that resource extraction may be market driven rather than focussing on domestic consumption. The study therefore concludes that the buffer zone livelihood link as currently practiced, though potential, may fail to address the livelihood expectations of the sub-district producer communities. The study therefore calls for extreme caution whenever the buffer zone livelihood link is considered, because several institutional and design conflicts exist within this dynamic. In Chapter six, the study further probed the buffer zone income dynamics for the sub-district producer community. The results of descriptive statistics suggest that the contribution of buffer zone activities to household income may be significant with a positive correlation to household agricultural income for communities who reside inside or close to the park (primary sub-district producer community). Using the Gini decomposition approach and Lorenz curves, the study concluded that a buffer zone income may be capable of contributing to more equally distributed incomes for rural communities who share boundaries with game parks. With respect to the correlates of household income, the results suggest that household size and age may negatively influence income from buffer zone activities, while gender may have a positive effect. This was also true for education and Livestock Units (LUs) with respect to income from self employment; the former positively and the latter negatively related. The results further suggest that land size may also be positively significant in order to explain income from agriculture as well as total income. With regard to the distance from the buffer zone, the results suggest a negative influence with respect to the buffer zone, agriculture and total income. The implied message therefore suggests that buffer zones may provide active livelihood sources which are capable of financing rural household agriculture. The income equalizing effect which is portrayed may also further imply that, if correctly targeted and promoted, a buffer zone income could possibly address the current income inequality which is generic in rural areas. However, this potential may not be realized due to the current buffer zone design status (created for local secondary use as opposed to commercial primary use), restrictive policies and poor institutional support. With this dilemma facing community managed game parks (threats as summarised in Chapters three and four amid the potential hope summarized in Chapters five and six), Chapter 7 concludes the study by suggesting that the human-wildlife interaction model, though currently theoretical, may have significant practical potential in addressing the livelihoods of the surrounding communities as well as promoting the conservation of wildlife. This could be possible if available challenges that range from low revenue, insecure property rights, high human-elephant conflict and institutional design conflict for buffer zone utilization are corrected by means of the free market system. This would allow market forces to deliver on the expectations of the ―human-wildlife interactions model‖ – sustainable livelihoods for the former and intergenerational conservation for the latter.
- Full Text:
Economics of land reform models used in Mashonaland Central Province of Zimbabwe
- Authors: Musemwa, Lovemore
- Date: 2011
- Subjects: Land reform -- Zimbabwe , Agricultural productivity -- Zimbabwe , Land tenure -- Zimbabwe , Infrastructure (Economics) -- Government policy -- Zimbabwe , Land reform beneficiaries -- Zimbabwe , Land use -- Economic aspects -- Zimbabwe , Field crops -- Zimbabwe , Data envelopment analysis -- Zimbabwe , Land settlement -- Zimbabwe
- Language: English
- Type: Thesis , Doctoral , PhD (Agricultural Economics)
- Identifier: vital:11168 , http://hdl.handle.net/10353/435 , Land reform -- Zimbabwe , Agricultural productivity -- Zimbabwe , Land tenure -- Zimbabwe , Infrastructure (Economics) -- Government policy -- Zimbabwe , Land reform beneficiaries -- Zimbabwe , Land use -- Economic aspects -- Zimbabwe , Field crops -- Zimbabwe , Data envelopment analysis -- Zimbabwe , Land settlement -- Zimbabwe
- Description: The land reform that has unfolded in Zimbabwe since 1980 used different models and had diverse consequences. Since the implementation of the fast tract land reform programme in 2000, Zimbabwe experienced heavy reduction in yield and output at farm level that led to a 70% shortfall in production to meet annual food requirements (Richardson, 2005). The economic crisis in Zimbabwe has been characterized by worsening food insecurity especially in the rural areas where harvests continue to be poor. In the beef sector, Zimbabwe has failed to meet its export quota to the EU. The shortfall in production to meet annual food requirements shows a very grim situation but do not tell us about the performance of resettled farmers who now occupy much of the productive land. The broad objective of the study was to determine and compare the production efficiency of resettled farmers in Zimbabwe across land reform models. In addition, the study determined land use intensity. The study was conducted in the Mashonaland Central Province of Zimbabwe mainly because a wide variety of field crops were grown by resettled farmers. The respondents were stratified into three groups. These were: beneficiaries of land reform before 2000 (resettle scheme), fast track A1 model and fast track A2 model. The three models differ on how they were implemented and supported and this might result in different efficiencies of the models. A total of 245 copies structured questionnaire were administered on the resettled farmers from June to September 2010. Descriptive statistics was applied to the basic characteristics of the sampled households. The effect of model of land reform, gender of the household head, marital status, age of the household head, education, household size, religion, dependence ratio, whether the farmer was fulltime or part-time in farming, experience of the farmers in farming at that environment, total land size owned by the farmers and soil type on revenue per hectare and land use rate were determined using the GLM procedure of SAS (2003). Significance differences between least-square group means were compared using the PDIFF test of SAS (2003). The relationship between Revenue and land utilization was examined using the Pearson‟s correlations analysis. Dependance between response variables that had an effect on either revenue per hectare or land utilization with all the other response variables was tested using the Chi-square test for dependance. To find the effect of arable land used and herd size on revenue per hectare and land use the RSREG Procedure of SAS (2003) was used. Input oriented DEA model under the assumption of constant return to scale was used to estimate efficiency in this study. To identify factors that influence efficiency, a Tobit model censored at zero was selected. The mean land use rate varied significantly (p<0.05) with the land reform model with A2 having highest land use rate of 67%. The A1 and old resettlement households had land use rates of 53% and 46%, respectively. Sex, marital status, age of the household head, education and household size significantly affected land use (P<0.05). Revenue per hectare was not affected by any the factors that were inputted in the model. Results from the DEA approach showed that A2 farmers (large land owners) had an average technical efficiency score of 0.839, while the lowest ranking model (A1) had an average score of 0.618. Small land holders (A1 and the old resettled farmers) are on average less cost-efficient than large land owners, with a score of 0.29 for the former compared with 0.45 for the latter. From the factors that were entered in the Tobit model, age of household head, excellent production knowledge and farmer status affected technical efficiency whereas allocative efficiency was only affected by good production knowledge, farm size, arable land owned and area under cultivation. Factors which affected economic efficiency of the resettled farmers are secondary education, household size, farm size, cultivated area and arable land owned. None of the included socio-economic variables has significant effects on the allocative and economic efficiency of the resettled farmers. Thus, the allocative and economic inefficiencies of the farmers might be accounted for by other natural and environmental factors which were not captured in the model.
- Full Text:
- Authors: Musemwa, Lovemore
- Date: 2011
- Subjects: Land reform -- Zimbabwe , Agricultural productivity -- Zimbabwe , Land tenure -- Zimbabwe , Infrastructure (Economics) -- Government policy -- Zimbabwe , Land reform beneficiaries -- Zimbabwe , Land use -- Economic aspects -- Zimbabwe , Field crops -- Zimbabwe , Data envelopment analysis -- Zimbabwe , Land settlement -- Zimbabwe
- Language: English
- Type: Thesis , Doctoral , PhD (Agricultural Economics)
- Identifier: vital:11168 , http://hdl.handle.net/10353/435 , Land reform -- Zimbabwe , Agricultural productivity -- Zimbabwe , Land tenure -- Zimbabwe , Infrastructure (Economics) -- Government policy -- Zimbabwe , Land reform beneficiaries -- Zimbabwe , Land use -- Economic aspects -- Zimbabwe , Field crops -- Zimbabwe , Data envelopment analysis -- Zimbabwe , Land settlement -- Zimbabwe
- Description: The land reform that has unfolded in Zimbabwe since 1980 used different models and had diverse consequences. Since the implementation of the fast tract land reform programme in 2000, Zimbabwe experienced heavy reduction in yield and output at farm level that led to a 70% shortfall in production to meet annual food requirements (Richardson, 2005). The economic crisis in Zimbabwe has been characterized by worsening food insecurity especially in the rural areas where harvests continue to be poor. In the beef sector, Zimbabwe has failed to meet its export quota to the EU. The shortfall in production to meet annual food requirements shows a very grim situation but do not tell us about the performance of resettled farmers who now occupy much of the productive land. The broad objective of the study was to determine and compare the production efficiency of resettled farmers in Zimbabwe across land reform models. In addition, the study determined land use intensity. The study was conducted in the Mashonaland Central Province of Zimbabwe mainly because a wide variety of field crops were grown by resettled farmers. The respondents were stratified into three groups. These were: beneficiaries of land reform before 2000 (resettle scheme), fast track A1 model and fast track A2 model. The three models differ on how they were implemented and supported and this might result in different efficiencies of the models. A total of 245 copies structured questionnaire were administered on the resettled farmers from June to September 2010. Descriptive statistics was applied to the basic characteristics of the sampled households. The effect of model of land reform, gender of the household head, marital status, age of the household head, education, household size, religion, dependence ratio, whether the farmer was fulltime or part-time in farming, experience of the farmers in farming at that environment, total land size owned by the farmers and soil type on revenue per hectare and land use rate were determined using the GLM procedure of SAS (2003). Significance differences between least-square group means were compared using the PDIFF test of SAS (2003). The relationship between Revenue and land utilization was examined using the Pearson‟s correlations analysis. Dependance between response variables that had an effect on either revenue per hectare or land utilization with all the other response variables was tested using the Chi-square test for dependance. To find the effect of arable land used and herd size on revenue per hectare and land use the RSREG Procedure of SAS (2003) was used. Input oriented DEA model under the assumption of constant return to scale was used to estimate efficiency in this study. To identify factors that influence efficiency, a Tobit model censored at zero was selected. The mean land use rate varied significantly (p<0.05) with the land reform model with A2 having highest land use rate of 67%. The A1 and old resettlement households had land use rates of 53% and 46%, respectively. Sex, marital status, age of the household head, education and household size significantly affected land use (P<0.05). Revenue per hectare was not affected by any the factors that were inputted in the model. Results from the DEA approach showed that A2 farmers (large land owners) had an average technical efficiency score of 0.839, while the lowest ranking model (A1) had an average score of 0.618. Small land holders (A1 and the old resettled farmers) are on average less cost-efficient than large land owners, with a score of 0.29 for the former compared with 0.45 for the latter. From the factors that were entered in the Tobit model, age of household head, excellent production knowledge and farmer status affected technical efficiency whereas allocative efficiency was only affected by good production knowledge, farm size, arable land owned and area under cultivation. Factors which affected economic efficiency of the resettled farmers are secondary education, household size, farm size, cultivated area and arable land owned. None of the included socio-economic variables has significant effects on the allocative and economic efficiency of the resettled farmers. Thus, the allocative and economic inefficiencies of the farmers might be accounted for by other natural and environmental factors which were not captured in the model.
- Full Text:
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