Blue over Green? Defining Typologies of Rural Landowners Growing Blueberry in Place of Forests in Georgia, United States
- 111 Downloads
Ricardian Rent Theory is typically used for analyzing land use change decisions of rural landowners. However, to the best of our knowledge no study focuses on the motivations of landowners for their land use change decisions in general and deforestation in particular. This information is important for southern Georgia, where more than 6,000 ha of evergreen forestland were moved into blueberry production between 2010 and 2017. We surveyed 34 family landowners who had moved to blueberry production to ascertain their motivations and analyzed the data using Q-methodology to categorize them into four typologies: Family Oriented landowners grow blueberry as a family legacy; Value Seeking landowners want higher value over time from their land; Environmental Cautious landowners grow blueberry for profit, but recognize a link between deforestation and blueberry expansion; finally, Profit Motivated landowners grow blueberry for higher profits in a short period and clearly recognize forestry as a long-term investment. The majority of surveyed blueberry farmers suggested that with appropriate financial incentives, they would practice forestry rather than higher risk blueberry farming. Our findings provide insights for policymakers in designing incentives for achieving sustainable land management and ensuring the multifunctionality of rural landscapes in Georgia and surrounding states facing similar issues.
KeywordsDeforestation Land-use change motivations Family landowners Q method Blueberry farming Southern Georgia
We thank the University of Georgia Extension personnel and participating farmers for their participation allowing the successful completion of this study.
Compliance with Ethical Standards
Conflict of Interest
The authors declare they have no conflict of interest.
An approval (#STUDY00005446) from the University of Georgia’s Institutional Review Board was obtained before undertaking surveys.
- Alig, R., Stewart, S., Wear, D., Stein, S., (2010). Conversions of forest land : Trends , determinants , projections , and policy considerations, in: Pye, John M.; Rauscher, H. Michael; Sands, Yasmeen; Lee, Danny C.; Beatty, J.S. (Ed.), Advances in Threat Assessment and Their Application to Forest and Rangeland Management. U.S. Department of Agriculture, Forest Service, Pacific Northwest and Southern Research Stations, Gen. Tech. Rep. PNW-GTR-802. Portland, OR, pp. 1–26.Google Scholar
- Barnes, A. P., Willock, J., Toma, L., and Hall, C. (2011). Utilising a Farmer Typology to Understand Farmer Behaviour Towards Water Quality Management: Vulnerable Nitrate Zones in Scotland. Journal of Environmental Planning and Management 54: 477–494. https://doi.org/10.1080/09640568.2010.515880.CrossRefGoogle Scholar
- Walker, B. B., Lin, Y., Mccline, R. M., and Stephenson, W. (2018). Q methodology and Q-Perspectives® Online: Innovative Research Methodology and Instructional Technology Q Methodology overview First Conceived of Q Methodology as Means of Objectively Measuring Subjectivity. TechTrends 62: 450−461. https://doi.org/10.1007/s11528-018-0314-5.CrossRefGoogle Scholar
- Butler, B. J., and Wear, D. N. (2013). Forest ownership dynamics of southern forests. In Wear, D. N., and Greis, J. G. (eds.), The southern Forest future project: Technical report, Asheville, NC, pp. 103–121.Google Scholar
- Butler, B. J., Hewes, J. H., Dickinson, B. J., Andrejczyk, K., Butler, S. M., and Markowski-Lindsay, M. (2016). Family Forest Ownerships of the United States, 2013: Findings from the USDA Forest Service’s National Woodland Owner Survey. Journal of Forestry 114: 638–647. https://doi.org/10.5849/jof.15-099.CrossRefGoogle Scholar
- Dayton, W.B., (2000). Policy Frames, Policy Making and the Global Climate Change Discourse, in: Social Discourse and Environmental Policy: An application of Q methodology. Edward Elgar, Northampton, pp. 71–99.Google Scholar
- de Graaff, J., Amsalu, A., Bodnar, F., Kessler, A., Posthumus, H., and Tenge, A. (2008). Factors Influencing Adoption and Continued use of Long-Term Soil and Water Conservation Measures in five Developing Countries. Applied Geography 28: 271–280. https://doi.org/10.1016/j.apgeog.2008.05.001.CrossRefGoogle Scholar
- Fonsah, E.G., Massonnat, J., Wiggins, L., Krewer, G., Stanaland, D., Smith, J.E., (2013). Southern Highbush Blueberry Marketing and Economics (No.1413), UGA Cooperative Extension Bulletin, University of Georgia Cooperative Extension Bulletin. Athens,GA.Google Scholar
- Geist, H. J., and Lambin, E. F. (2002). Proximate Causes and Underlying Driving Forces of Tropical Deforestation. Bioscience 52: 143–150. https://doi.org/10.1641/0006-3568(2002)052[0143:PCAUDF]2.0.CO;2.CrossRefGoogle Scholar
- Georgia Info, (2015). Economy - blueberries [WWW document]. URL http://georgiainfo.galileo.usg.edu/topics/economy/article/blueberries (accessed 8.16.16).
- Georgia Institute of Technology, (2016). Economic benefits of the forest industry in Georgia : 2016.Google Scholar
- Goyke, N., Dwviedi, P., Hitchner, S., Schelhas, J., and Thomas, M. (2019). Exploring Diversity in Forest Management Outlooks of African American Family Forest Landowners for Ensuring Sustainability of Forestry Resources in the Southern United States. Human Ecology 47(2): 263–274.CrossRefGoogle Scholar
- Greiner, R., and Gregg, D. (2011). Farmers’ Intrinsic Motivations, Barriers to the Adoption of Conservation Practices and Effectiveness of Policy Instruments: Empirical Evidence from Northern Australia. Land Use Policy 28: 257–265. https://doi.org/10.1016/j.landusepol.2010.06.006.CrossRefGoogle Scholar
- Hosonuma, N., Herold, M., De Sy, V., De Fries, R. S., Brockhaus, M., Verchot, L., Angelsen, A., and Romijn, E. (2012). An Assessment of Deforestation and Forest Degradation Drivers in Developing Countries. Environmental Research Letters 7: 12pp. https://doi.org/10.1088/1748-9326/7/4/044009.CrossRefGoogle Scholar
- Kurtz, W. B., and Lewis, B. J. (1981). Decision-Making Framework for Forest Nonindustrial Private Owners : An Application in the Missouri Ozarks. Journal of Forestry 79: 285–288.Google Scholar
- Lambin, E. F., Turner, B. L., Geist, H. J., Agbola, S. B., Angelsen, A., Bruce, J. W., Coomes, O. T., Dirzo, R., Fischer, G., Folke, C., George, P. S., Homewood, K., Imbernon, J., Leemans, R., Li, X., Moran, E. F., Mortimore, M., Ramakrishnan, P. S., Richards, J. F., Skånes, H., Steffen, W., Stone, G. D., Svedin, U., Veldkamp, T. A., Vogel, C., and Xu, J. (2001). The Causes of Land-Use and Land-Cover Change: Moving Beyond the Myths. Global Environmental Change 11: 261–269. https://doi.org/10.1016/S0959-3780(01)00007-3.CrossRefGoogle Scholar
- Oswalt, S.N., Miles, P.D., Pugh, S.A., Smith, W.B., 2018. Forest resources of the United States, 2017: A technical document supporting the Forest Service 2020 update of the RPA assessment, U.S. for. Serv., Gen. Tec. Rep. NC-219. Washington D.C. https://doi.org/10.1126/science.3.72.734-a
- Parker, D. C., Manson, S. M., Janssen, M. a., Hoffmann, M. J., and Deadman, P. (2003). Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review - Annals of the Association of American Geographers. Annals of the Association of American Geographers 93: 314–337. https://doi.org/10.1111/1467-8306.9302004.CrossRefGoogle Scholar
- Rueda, X., Velez, M. A., Moros, L., and Rodriguez, L. A. (2019). Beyond Proximate and Distal Causes of Land-Use Change: Linking Individual Motivations to Deforestation in Rural Contexts. Ecology and Society 24. https://doi.org/10.5751/ES-10617-240104Research.
- Sæbjørnsen, S.E.N., Ellingsen, I.T., Good, J.M.M., Ødegård, A., 2016. Combining a Naturalistic and Theoretical Q Sample Approach: An Empirical Research Illustration. Operant Subj. Int. J. Q Methodol. 38, 15–32. https://doi.org/10.15133/j.os.2016.005
- Schwarz, I., Mcrae-Williams, P., and Park, D. (2009). Identifying and Utilising a Farmer Typology for Targeted Practice CHANGE PROgrams: A Case Study of Changing Water Supply in the Wimmera Mallee. Ext. Farming Syst. J. 5: 33–42.Google Scholar
- Sorice, M. G., Kreuter, U. P., Wilcox, B. P., and Fox, W. E. (2012). Classifying Land-Ownership Motivations in Central, Texas. USA: A first step in understanding drivers of large-scale land cover change. J. Arid Environ. 80: 56–64. https://doi.org/10.1016/j.jaridenv.2012.01.004.CrossRefGoogle Scholar
- USDA National Agricultural Statistics Service Cropland Data Layer, (2018). Published crop-specific data layer [WWW document]. URL https://nassgeodata.gmu.edu/CropScape/ (accessed 8.20.18).
- Wear, D. N. (2013). Forecasts of Land Uses. The Southern Forest Futures Project 45–69. https://doi.org/10.1017/CBO9781107415324.004.