Determinants of Decision Making by Smallholder Farmers on Land Allocation for Small-Scale Forest Management in Northwestern Ethiopian Highlands
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Methods
Sampling Technique
2.3. Data Analysis
Econometric Analysis
3. Results
3.1. Trends in Small-Scale Forest Management
3.2. Land Allocation for Small-Scale Forest Management
3.3. Motivation of Farmers in Small-Scale Forest Management
3.4. Determinants of Proportions of Land Allocated for Small-Scale Forest Management
4. Discussion
4.1. Trends in Small-Scale Forest Management
4.2. Land Allocation for Small-Scale Forest Management
4.3. Farmers’ Motivation on Small-Scale Forest Management
4.4. Determinants of Proportions of Land Allocated for Small-Scale Forest Management
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- FAO (United Nation’s Food and Agriculture Organization). Global Forest Resources Assessment 2015: How Are the World’s Forests Changing? FAO: Rome, Italy, 2015. [Google Scholar]
- MEA (Millennium Ecosystem Assessment). Ecosystems and Human Wellbeing; Biodiversity Synthesis World Resource Institute: Washington, DC, USA, 2005. [Google Scholar]
- Lemenih, M.; Kassa, H. Re-Greening Ethiopia: History, Challenges and Lessons. Forests 2014, 5, 1896–1909. [Google Scholar] [CrossRef]
- Antwi, K.; Bas, O.; Boateng, A. Farmers’ Motivations to Plant and Manage On-Farm Trees in Ghana. Small-Scale For. 2018, 17, 393–410. [Google Scholar] [CrossRef]
- Arvola, A.; Malkamäki, A.; Penttilä, J.; Toppinen, A. Mapping the Future Market Potential of Timber from Small-Scale Tree Farmers: Perspectives from the Southern Highlands in Tanzania. Small-Scale For. 2019, 18, 189–212. [Google Scholar] [CrossRef] [Green Version]
- Ndayambaje, J.D.; Heijman, W.J.M.; Mohren, G.M.J. Farm Woodlots in Rural Rwanda: Purposes and Determinants. Agrofor. Syst. 2013, 87, 797–814. [Google Scholar] [CrossRef]
- Ellis, F. Peasant Economics: Farm Households and Agrarian Development, 2nd ed.; Cambridge University Press: Cambridge, UK, 1993. [Google Scholar]
- Henrich, J.; McElreath, R. Are Peasants Risk-Averse Decision Makers? Curr. Anthropol. 2002, 43, 172–181. [Google Scholar] [CrossRef] [Green Version]
- Mendola, M. Farm Households’ Production Theories: A Review of ‘Institutional’ and ‘Behavioral’ Responses. Asian Dev. Rev. 2007, 24, 49–68. [Google Scholar] [CrossRef] [Green Version]
- Belayneh, Y.; Ru, G.; Guadie, A.; Teffera, Z.L.; Tsega, M. Forest Cover Change and Its Driving Forces in FagitaLekoma District, Ethiopia. J. For. Res. 2020, 31, 1567–1582. [Google Scholar] [CrossRef]
- Diogo, V.; Koomen, E.; Kuhlman, T. An Economic Theory-Based Explanatory Model of Agricultural Land-Use Patterns: The Netherlands as a Case Study. Agric. Syst. 2015, 139, 1–16. [Google Scholar] [CrossRef]
- Senkondo, E. Risk Attitude and Risk Perception in Agroforestry Decisions: The Case of Babati, Tanzania. Ph.D. Thesis, Wageningen Agricultural University, Wageningen, The Netherlands, 2000. [Google Scholar]
- Nigussie, Z.; Tsunekawa, A.; Haregeweyn, N.; Adgo, E.; Nohmi, M.; Tsubo, M.; Aklog, D.; Meshesha, D.T.; Abele, S. Factors Affecting Small-Scale Farmers’ Land Allocation and Tree Density Decisions in an Acacia Decurrens-Based Taungya System in FagitaLekoma District, North-Western Ethiopia. Small-Scale For. 2018, 16, 219–233. [Google Scholar] [CrossRef]
- Buyinza, M.; Banana, A.Y.; Nabanoga, G.; Ntakimanye, A. Social-Economic Determinants of Farmers’ Adoption of Rotational Woodlot Technology in Kigorobya Sub-County of Hoima District, Uganda. South Afr. J. Agric. Ext. 2008, 37, 1–16. [Google Scholar]
- Nsiaha, B.; Pretzscha, J. The Contribution of Smallholder Forest Plantation Development to the Livelihood of Farm Households in the High Forest Zone of Ghana. Ph.D. Thesis, Technische Universitat Dresden, Dresden, Germany, 2010. [Google Scholar]
- Fahmi, M.K.M.; Mohamed, E.S.; Kanninen, M.; Luukkanen, O.; Kalame, F.B.; Eltayeb, A.M. Determinants and Constraints of Integrating Natural Acacias into Mechanised Rain-Fed Agricultural Schemes Sennar State, Sudan. Geo-J. 2015, 80, 555–567. [Google Scholar] [CrossRef]
- Matthies, B.D.; Karimov, A.A. Financial Drivers of Land Use Decisions: The Case of Smallholder Woodlots in Amhara, Ethiopia. Land Use Policy 2014, 41, 474–483. [Google Scholar] [CrossRef]
- Jenbere, D.; Lemenih, M.; Kassa, H. Expansion of Eucalypt Farm Forestry and Its Determinants in ArsiNegelle District, South Central Ethiopia. Small-Scale For. 2012, 11, 389–405. [Google Scholar] [CrossRef] [Green Version]
- Ayele, Z.E. Smallholder Farmers’ Decision Making in Farm Tree Growing in the Highlands of Ethiopia. Ph.D. Thesis, Oregon State University, Corvallis, OR, USA, 2008. [Google Scholar]
- Negussie, A.D. Farm Forestry Decision-Making Strategies of the GuragheHousholds, Southern-Central Highlands of Ethiopia. Ph.D. Thesis, TechnischeUniversitat Dresden, Dresden, Germany, 2004. [Google Scholar]
- Yitaferu, B.; Abewa, A.; Amare, T. Expansion of Eucalyptus Woodlots in the Fertile Soils of the Highlands of Ethiopia: Could It Be a Treat on Future Cropland Use? J. Agric. Sci. 2013, 5, 97–107. [Google Scholar] [CrossRef]
- Achamyeleh, K. Integration of Acacia Decurrens (J.C. Wendl.) Willd. into the Farming System, It’s Effects on Soil Fertility and Comparative Economic Advantages in North Western Ethiopia. Ph.D. Thesis, Bahir Dar University, Bahir Dar, Ethiopia, 2015. [Google Scholar]
- Nair, P.K.R. An Introduction to Agroforestry; Kluwer Academic Publishers: Dordrecht, The Netherlands, 1993; ISBN 0-79232134-0. [Google Scholar]
- Bryman, A. Integrating quantitative and qualitative research: How is it done? Qual. Res. 2006, 6, 97–113. [Google Scholar] [CrossRef] [Green Version]
- Yin, R.K. Case Study Research: Design and Methods; Sage Publications Inc.: Thousand Oaks, CA, USA, 2003; pp. 1–181. [Google Scholar]
- De Vaus, D.A. Surveys in Social Research, 4th ed.; UCL Press: London, UK, 1996. [Google Scholar]
- Neuman, W.L. Social Research Methods: Qualitative and Quantitative Approaches, 4th ed.; Allyn and Bacon: Boston, MA, USA, 2000. [Google Scholar]
- Green, S.B.; Green, S.B. How many subjects does it take to do a regression analysis. Multivar. Behav. Res. 1991, 26, 499–510. [Google Scholar] [CrossRef]
- Baum, C.F. Stata Tip 63: Modeling Proportions. Stata J. 2008, 8, 299–303. [Google Scholar] [CrossRef] [Green Version]
- Papke, L.E. Econometric Methods for Fractional Response Variables with an Application to 401 (k) Plan Participation Rates. J. Appl. Econom. 1996, 11, 619–632. [Google Scholar] [CrossRef] [Green Version]
- Ramalho, E.A.; Ramalho, J.J.S.; Murteira, J.M.R. Alternative Estimating and Testing Empirical Strategies for Fractional Regression Models. J. Econ. Surv. 2011, 25, 19–68. [Google Scholar] [CrossRef]
- Nigussie, Z.; Tsunekawa, A.; Haregeweyn, N.; Adgo, E.; Tsubo, M.; Ayalew, Z.; Abele, S. Economic and Financial Sustainability of an Acacia Decurrens-Based Taungya System for Farmers in the Upper Blue Nile Basin, Ethiopia. LandUsePolicy 2020, 90, 104331. [Google Scholar] [CrossRef]
- Sood, K.K.; Mitchell, C.P. Identifying Important Biophysical and Social Determinants of On-Farm Tree Growing in Subsistence-Based Traditional Agroforestry Systems. Agrofor. Syst. 2009, 75, 175–187. [Google Scholar] [CrossRef]
- Mukundente, L.; Ndunda, E.; Gathuru, G. Socio-Economic and Institutional Factors Affecting Smallholders Farmers to Adopt Agroforestry Practices in Southern Province of Rwanda. Int. J. Agric. Sci. Food Technol. 2020, 6, 68–74. [Google Scholar] [CrossRef]
Independent Variable | Expected Sign | Description | Sources |
---|---|---|---|
Gender(male) | + | Sexual category of respondent (0 female, 1 male) | [12,13,14,18,19,20]. |
Age | +/− | Age of respondent in years | [13,15,20] |
Wealth | + | Wealth status of respondent (0 poor, 1 medium, 2 rich) | [10,13,18,19,20] |
Adult equivalent | + | Index of household active and inactive labor force | [15] |
Total land size | +/− | Respondents total size of land holding in ha | [12,13,15,18,19,20] |
Tropical livestock unit | − | Index of household various livestock number | [19] |
Distance of woodlot to main road | − | Distance of woodlots to main road measure in km | [10,19] |
Distance of woodlot to market | − | Distance of woodlot to nearest market measured in km | [13] |
Soil fertility | +/− | Soil fertility of field (0 poor, 1 medium, 2 high) | [13,17] |
Annual crop risk perception | + | Farmers’ perception on annual crop production risk (0 no, 1 yes) | [12,19] |
Woodlot production risk | − | Farmers’ perception on woodlot production risk (0 no, 1 yes) | [12,19] |
Woodlot products market risk | − | Farmers’ perception on woodlot products market risk | [12,15,19] |
Perception on comparative socio-economic benefits of woodlots | + | Farmers’ perception on comparative socio-economic benefits of woodlots (0 no, 1 yes) | [10,15] |
Description | Guna Begemidir (n = 15) | % of KIs | North Mecha (n = 15) | % of KIs | FagtaLekoma (n = 15) | % of KIs |
---|---|---|---|---|---|---|
Trend of expansion and management ofsmall-scale forest | During 1987–1998 only in the form of boundary planting(low expansion). | 100 | Boundary planting 30 years ago (1987–1998). | 93.3 | Expansion of A. decurrens woodlot started in 1998 (15years ago). | 53.3 |
1998–2009 significant expansion. | 86.6 | Significant expansion during 1998–2009. | 100 | Expansion of A. decurrens woodlot started before 20years. | 46.7 | |
High expansion observed during 2009–2020. | 100 | Massive exposition has been during period 2009–2020. | 100 | Massive exposition has been during period 2009–2020. | 100 | |
Female-headed households are less likely to be engaged in woodlot management. | 80 | Currently, almost all farmers except female-headed households have woodlots. | 100 | Female-headed households are less likely to be engaged in woodlot management. | 93.3 | |
Farmers sell their woodlot products at stand level and after processing. | 93.3 | Farmers sell their woodlot products at stand level and after processing. | 100 | The majority of farmers sell their woodlot products after processing to charcoal. | 100 | |
Motivating factors for small-scale forest management | High demand of wood products. | 86.7 | Adverse impact of adjacent woodlot. | 86.7 | Land degradation and decline in crop productivity. | 80 |
Land degradation and decline in productivity. | 93.3 | High demand of wood products. | 80 | High demand for charcoal. | 80 | |
Adverse effect of others eucalyptus woodlot on adjacent crop lands. | 86.7 | High profitability of woodlots. | 93.3 | Special intrinsic and ascribed attributes of A. decurrens. | 80 | |
High profitability. | 80 | Comparative socio-economic benefits of woodlots. | 6.7 | High profitability. | 73.2 | |
Comparative socio-economic benefits of woodlots. | 20 | Comparative socio-economic benefits of woodlots. | 13.3 | |||
Soil fertility enhancement. | 13.3 | |||||
Soil and water conservation. | 6.7 |
Guna Begemidir District (n = 125). | ||||
---|---|---|---|---|
Land Use | Wealth Category | p Value | ||
Poor | Medium | Rich | ||
Cropland | 0.26 ± 0.19 a | 0.53 ± 0.28 b | 0.91 ± 0.32 c | 0.000 |
Small-scale forest management | 0.07 ± 0.03 a | 0.13 ± 0.07 b | 0.48 ± 0.18 c | 0.000 |
Grazing land | 0.06 ± 0.03 a | 0.08 ± 0.04 a | 0.19 ± 0.16 b | 0.000 |
North Mecha District (n = 125) | ||||
Land Use | Wealth Category | p Value | ||
Poor | Medium | Rich | ||
Crop land | 0.42 ± 0.15 a | 0.70 ± 0.30 b | 0.94 ± 0.30 c | 0.000 |
Small-scale forest management | 0.30 ± 0.18 a | 0.58 ± 0.21 b | 0.90 ± 0.28 c | 0.000 |
Grazing land | 0.25 (na) | 0.15 ± 0.10 | 0.26 ± 0.16 | 0.538 |
Fagta Lekoma District (n = 125) | ||||
Land Use | Wealth Category | p Value | ||
Poor | Medium | Rich | ||
Crop land | 0.24 ± 0.12 a | 0.51 ± 0.23 b | 0.89 ± 0.33 c | 0.000 |
Small-scale forest management | 0.32 ± 0.22 a | 0.53 ± 0.24 b | 1.14 ± 0.55 c | 0.000 |
Grazing land | 0.19 ± 0.09 a | 0.31 ± 0.14 b | 0.50 ± 0.15 c | 0.000 |
Land Allocation Type | Guna Begemidir | North Mecha | Fagta Lekoma | p Value |
---|---|---|---|---|
Proportion of land allocated to small-scale forest in 2020 | 0.25 ± 0.14 a | 0.41 ± 0.15 b | 0.43 ± 0.17 b | 0.000 |
Proportion of land allocated to crop in 2020 | 0.65 ± 0.14 a | 0.51 ± 0.17 b | 0.39 ± 0.15 c | 0.000 |
Proportion of land allocated for crop before 10 years (2010) | 0.81 ± 0.16 a | 0.86 ± 0.17 a | 0.64 ± 0.26 b | 0.000 |
Proportion of land allocated for small-scale forest before 10years (2020) | 0.1 8± 0.11 a | 0.30 ± 0.13 b | 0.40 ± 0.23 c | 0.000 |
Proportion of land allocated for small-scale forest before 5 years (2016) | 0.22 ± 0.92 a | 0.31 ± 0.14 b | 0.41 ± 0.17 c | 0.000 |
Independent Variable | Guna Begemidir Guna Begemidir (n = 125, Wald chi2 (15) = 1277.92, Prob > chi2 = 0.0000) | North Mecha (n = 125, Wald chi2(15) = 1512.60, Prob > chi2 = 0.0000) | Fagta Lekoma (n = 125, Wald chi2 (15) = 676.74, Prob > chi2 = 0.0000) | |||
---|---|---|---|---|---|---|
dy/dx | Std. Err | dy/dx | Std. Err | dy/dx | Std. Err | |
Gender | 0.005 | 0.021 | 0.018 | 0.017 | 0.048 * | 0.027 |
Age | 0.000 | 0.000 | −0.000 | 0.001 | −0.000 | 0.001 |
Wealth Medium Rich | 0.000 | 0.014 | 0.003 | 0.003 | −0.080 *** | 0.029 |
0.056 *** | 0.021 | 0.002 | 0.024 | −0.063 | 0.038 | |
Adult equivalent | 0.004 | 0.003 | 0.005 | 0.006 | −0.019 *** | 0.007 |
Total land size | −0.051 *** | 0.012 | 0.005 | 0.012 | −0.000 | 0.017 |
Tropical livestock unit | 0.001 | 0.003 | −0.004 | 0.003 | 0.001 | 0.003 |
Distance of woodlot to main road | −0.005 | 0.005 | −0.060 *** | 0.020 | −0.015 | 0.021 |
Distance of woodlot to market | −0.079 *** | 0.010 | −0.035 *** | 0.007 | −0.067 *** | 0.023 |
Soil fertility Medium High | −0.037 *** | 0.008 | 0.025 ** | 0.012 | −0.028 | 0.022 |
−0.014 | 0.011 | 0.013 | 0.024 | −0.022 | 0.036 | |
Annual crop risk perception | 0.051 *** | 0.015 | −0.000 | 0.016 | −0.026 | 0.030 |
Woodlot production risk | 0.018 | 0.055 | −0.006 | 0.020 | 0.002 | 0.023 |
Woodlot products market risk | 0.055 | 0.052 | 0.023 | 0.018 | −0.023 | 0.017 |
Perception on comparative socio-economic benefits of woodlots | 0.049 *** | 0.016 | 0.044 ** | 0.017 | 0.065 * | 0.038 |
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Mulu, S.; Asfaw, Z.; Alemu, A.; Teketay, D. Determinants of Decision Making by Smallholder Farmers on Land Allocation for Small-Scale Forest Management in Northwestern Ethiopian Highlands. Land 2022, 11, 838. https://doi.org/10.3390/land11060838
Mulu S, Asfaw Z, Alemu A, Teketay D. Determinants of Decision Making by Smallholder Farmers on Land Allocation for Small-Scale Forest Management in Northwestern Ethiopian Highlands. Land. 2022; 11(6):838. https://doi.org/10.3390/land11060838
Chicago/Turabian StyleMulu, Solomon, Zebene Asfaw, Asmamaw Alemu, and Demel Teketay. 2022. "Determinants of Decision Making by Smallholder Farmers on Land Allocation for Small-Scale Forest Management in Northwestern Ethiopian Highlands" Land 11, no. 6: 838. https://doi.org/10.3390/land11060838
APA StyleMulu, S., Asfaw, Z., Alemu, A., & Teketay, D. (2022). Determinants of Decision Making by Smallholder Farmers on Land Allocation for Small-Scale Forest Management in Northwestern Ethiopian Highlands. Land, 11(6), 838. https://doi.org/10.3390/land11060838