Analyzing the drivers of tree planting in Yunnan, China, with Bayesian networks

Land Use Policy

Volumn 36, Issue , 2014, Pages 248-258

  Frayer, Jens ^a   Sun, Zhanli ^a   Müller, Daniel ^a,b   Munroe, Darla K ^c   Xu, Jianchu ^d  

^a LEIBNIZ INSTITUTE OF AGRICULTURAL DEVELOPMENT IN TRANSITION ECONOMIES IAMO   (Germany)

^b HUMBOLDT UNIVERSITY   (Germany)

^c OHIO STATE UNIVERSITY   (United States)

^d WORLD AGROFORESTRY CENTRE ICRAF   (Kenya)

Author keywords

Afforestation; Bayesian belief network; China; Forest transition; Land use change; SLCP

Indexed keywords

AFFORESTATION; BAYESIAN ANALYSIS; FOREST COVER; LAND MANAGEMENT; LAND USE CHANGE; LAND USE LOCATION; LAND USE PLANNING; QUALITATIVE ANALYSIS; QUANTITATIVE ANALYSIS; STAKEHOLDER; TREE PLANTING;

CHINA; YUNNAN;

EID: 84884197900     PISSN: 02648377     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.landusepol.2013.08.005     Document Type: Article

References (72)

1. Aalders I. Modeling land-use decision behavior with Bayesian belief networks. Ecol. Soc. 2008, 13:16. http://www.ecologyandsociety.org/vol13/iss11/art16/.
2. Aguilera P.A., Fernández A., Fernández R., Rumí R., Salmerón A. Bayesian networks in environmental modelling. Environ. Model. Softw. 2011, 26:1376-1388.
3. Aitkenhead M.J., Aalders I.H. Predicting land cover using GIS, Bayesian and evolutionary algorithm methods. J. Environ. Manage. 2009, 90:236-250.
4. Alix-Garcia J., Kuemmerle T., Radeloff V.C. Prices, land tenure institutions, and geography: a matching analysis of farmland abandonment in post-socialist Eastern Europe. Land Econ. 2012, 88:425-443.
5. Andam K.S., Ferraro P.J., Pfaff A., Sanchez-Azofeifall G.A., Robalino J.A. Measuring the effectiveness of protected area networks in reducing deforestation. Proc. Natl. Acad. Sci. U.S.A. 2008, 105:16089-16094.
6. Arhonditsis G.B., Stow C.A., Steinberg L.J., Kenney M.A., Lathrop R.C., McBride S.J., Reckhow K.H. Exploring ecological patterns with structural equation modeling and Bayesian analysis. Ecol. Model. 2006, 192:385-409.
7. Baoshan Statistical Bureau Baoshan Statistical Yearbook 2005, Baoshan Statistcal Bureau, Baoshan.
8. Barbier E.B., Burgess J.C., Grainger A. The forest transition: towards a more comprehensive theoretical framework. Land Use Policy 2010, 27:98-107.
9. Bennett M.T. China's sloping land conversion program: institutional innovation or business as usual?. Ecol. Econ. 2008, 65:699-711.
10. ® to develop Bayesian networks as an aid to integrated water resource planning. Environ. Model. Softw. 2005, 20:231-242.
11. Central Intelligence Agency The World Factbook 2013, https://www.cia.gov/library/publications/the-world-factbook/fields/2046.html (last accessed 28.01.13).
12. Charniak E. Bayesian networks without tears. AI Mag. 1991, 12:50-63.
13. Chen S.H., Pollino C.A. Good practice in Bayesian network modelling. Environ. Model. Softw. 2012, 37:134-145.
14. Chen X., Zhang X., Zhang Y., Wan C. Carbon sequestration potential of the stands under the Grain for Green Program in Yunnan Province, China. For. Ecol. Manage. 2009, 258:199-206.
15. China Statistical Bureau China Statistical Yearbook 2010, China Statistical Press, Beijing.
16. Conservation International Mountains of Southwest China 2007, http://www.conservation.org/where/priority_areas/hotspots/asia-pacific/Mountains-of-Southwest-China (last accessed 15.02.12).
17. Dlamini W.M. A Bayesian belief network analysis of factors influencing wildfire occurrence in Swaziland. Environ. Model. Softw. 2010, 25:199-208.
18. Ediger L. Economic integration and rural transformation: state-driven afforestation in Yunnan, China and the implications for landscapes and livelihoods 2006, University of Georgia, Athens, Georgia, (PhD thesis).
19. Ediger L., Chen H. Upland China in transition: the impacts of afforestation on landscape patterns and livelihoods. Mount. Res. Dev. 2006, 26:220-226.
20. Fielding A.H., Bell J.F. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ. Conserv. 1997, 24:38-49.
21. Groom B., Palmer C. REDD+ and rural livelihoods. Biol. Conserv. 2012, 154:42-52.
22. Hanley J.A., McNeil B.J. The meaning and the use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982, 143:29-36.
23. Heckerman D. A Tutorial on Learning With Bayesian Networks, Technical Report 1996, Microsoft Research, Redmond, WA.
24. Heckerman D., Geiger D., Chickering D. Learning Bayesian networks: the combination of knowledge and statistical data. Mach. Learn. 1995, 20:197-243.
25. Heckerman D., Mamdani A., Wellman M.P. Real-world applications of Bayesian networks. Commun. ACM 1995, 38:24-26.
26. Hu Poverty standardises to record high. China Daily 2012, 05.25.
27. Hyde W.F., Amacher G.S., Magrath W. Deforestation and forest land use: theory, evidence, and policy implications. World Bank Res. Obs. 1996, 11:223-248.
28. Jensen F. Bayesian Networks and Decision Graphs 2002, Springer, New York.
29. Kinzig A., Starrett D. Coping with uncertainty: a call for a new science-policy forum. Ambio 2003, 32:330-335.
30. Kotsiantis S., Kanellopoulos D. Discretization techniques: a recent survey. GESTS Int. Trans. Comput. Sci. Eng. 2006, 32:47-58.
31. Lambin E.F., Geist H.J., Lepers E. Dynamics of land-use and land-cover change in tropical regions. Annu. Rev. Environ. Resour. 2003, 28:205-241.
32. Lambin E.F., Meyfroidt P. Land use transitions: socio-ecological feedback versus socio-economic change. Land Use Policy 2010, 27:108-118.
33. Li J., Feldman M.W., Li S., Daily G.C. Rural household income and inequality under the sloping land conversion program in western China. Proc. Natl. Acad. Sci. U.S.A. 2011, 108:7721-7726.
34. Lijiang Statistical Bureau Lijiang Statistical Yearbook 2005 2005, Lijiang Statistical Bureau, Lijiang.
35. Liu C., Lu J., Yin R. An estimation of the effects of China's priority forestry programs on farmers' income. Environ. Manage. 2010, 45:526-540.
36. Liu J., Li S., Ouyang Z., Tam C., Chen X. Ecological and socioeconomic effects of China's policies for ecosystem services. Proc. Natl. Acad. Sci. 2008, 105:9477-9482.
37. Marcot B.G. Characterizing species at risk I: Modeling rare species under the northwest forest plan. Ecol. Soc. 2006, 11:10. http://www.ecologyandsociety.org/vol11/iss12/art10/.
38. Marcot B.G. Metrics for evaluating performance and uncertainty of Bayesian network models. Ecol. Model. 2012, 230:50-62.
39. Marcot B.G., Holthausen R.S., Raphael M.G., Rowland M.M., Wisdom M.J. Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement. For. Ecol. Manage. 2001, 153:29-42.
40. Marcot B.G., Steventon J.D., Sutherland G.D., McCann R.K. Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation. Can. J. For. Res. 2006, 36:3063-3074.
41. Mather A.S. The forest transition. Area 1992, 4:367-379.
42. Metz C.E. Basic principles of ROC analysis. Semin. Nucl. Med. 1978, 8:283-298.
43. Meyfroidt P. Environmental cognitions, land change and social-ecological feedbacks: local case studies of forest transition in Vietnam. Hum. Ecol. 2013, 41:367-392.
44. Mullan K., Kontoleon A. Participation in Payments for Ecosystem Services programmes in developing countries: The Chinese Sloping Land Conversion Programme. Discussion Paper Series Number 42. 2009 2009, University of Cambridge.
45. Nadkarni S., Shenoy P.P. A Bayesian network approach to making inferences in causal maps. Eur. J. Oper. Res. 2001, 128:479-498.
46. Newton A.C., Marshall E., Schreckenberg K., Golicher D., te Velde D.W., Eduardo F., Arancibia E. Use of a Bayesian belief network to predict the impacts of commercializing non-timber forest products on livelihoods. Ecol. Soc. 2006, 11:24. http://www.ecologyandsociety.org/vol11/iss22/art24/.
47. Newton A.C., Stewart G.B., Diaz A., Golicher D., Pullin A.S. Bayesian belief networks as a tool for evidence-based conservation management. J. Nat. Conserv. 2007, 15:144-160.
48. Norsys Software Cooperation Netica Version 4.08 2008.
49. Pearl J. Causality: Models, Reasoning, and Interference 2009, Cambridge University Press, Cambridge. 2nd ed.
50. Perez R.M., Belcher B., Fu M., Yang X. Looking through the bamboo curtain: an analysis of the changing role of forest and farm income in rural livelihoods in China. Int. For. Rev. 2004, 6:306-317.
51. Pollino C.A., Woodberry O., Nicholson A., Korb K., Hart B.T. Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment. Environ. Model. Softw. 2007, 22:1140-1152.
52. Rudel T.K. Tree farms: driving forces and regional patterns in the global expansion of forest plantations. Land Use Policy 2009, 26:545-550.
53. Rudel T.K., Coomes O.T., Moran E., Achard F., Angelsen A., Xu J., Lambin E. Forest transitions: towards a global understanding of land use change. Glob. Environ. Change 2005, 15:23-31.
54. SFA State Forestry Administration People's Republic of China, People's Republic of China Forestry Outlook Study. Asia-Pacific Forestry Sectors Outlook Study 2009, FAO, Bangkok. FAO (Ed.).
55. Smith C.S., Howes A.L., Price B., McAlpine C.A. Using a Bayesian belief network to predict suitable habitat of an endangered mammal-the Julia Creek dunnart (Sminthopsis douglasi). Biol. Conserv. 2007, 139:333-347.
56. Song C., Zhang Y. Forest cover in China from 1949 to 2006. Reforesting Landscapes 2010, 341-356. Springer, Dordrecht. H. Nagendra, J. Southworth (Eds.).
57. Sun Z., Müller D. A framework for modeling payments for ecosystem services with agent-based models, Bayesian belief networks and opinion dynamics models. Environ. Model. Softw. 2013, 45:15-28.
58. Ticehurst J.L., Curtis A., Merritt W.S. Using Bayesian networks to complement conventional analyses to explore landholder management of native vegetation. Environ. Model. Softw. 2011, 26:52-65.
59. Uchida E., Rozelle S., Xu J. Conservation payments, liquidity constraints, and off-farm labor: impact of the grain-for-green program on rural households in China. Am. J. Agric. Econ. 2009, 91:70-86.
60. Uusitalo L. Advantages and challenges of Bayesian networks in environmental modelling. Ecol. Model. 2007, 203:312-318.
61. Wilson A. Forest conversion and land use change in rural northwest Yunnan, China. Mount. Res. Dev. 2006, 26:227-236.
62. Xu J. Chinas forests aren't as green as they seem. Nature 2011, 477:371.
63. Xu J., Ai X., Deng X. Exploring the spatial and temporal dynamics of land use in Xizhuang watershed of Yunnan, southwest China. Int. J. Appl. Earth Observ. Geoinform. 2005, 7:299-309.
64. Xu J., Jiang X. Collective Forest Tenure Reform in China: Outcomes and Implications 2009, World Bank Conference on Land Governance, Washington, DC.
65. Xu J., Ribot J.C. Decentralization and accountability in forest management: case from Yunnan, Southwest China. Eur. J. Dev. Res. 2004, 14:153-173.
66. Xu J., Yang Y., Fox J., Xuefei Y. Forest transition, its causes and environmental consequences: empirical evidence from Yunnan of Southwest China. Trop. Ecol. 2007, 48:137-150.
67. Yin R., Yao S., Huo X. China's forest tenure reform and institutional change in the new century: what has been implemented and what remains to be pursued?. Land Use Policy 2013, 30:825-833.
68. Yin R., Yin G. China's primary programs of terrestrial ecosystem restoration: initiation, implementation, and challenges. Environ. Manage. 2010, 45:429-441.
69. Yunnan Government Lijiang Efforts to Reduce Poverty, Lijiang, China 2012, (in Chinese).
70. Zhang Y. Deforestation and forest transition: theory and evidence in China. World Forests From Deforestation to Transition 2000, 41-65. Kluwer Academic Publishers, Dordrecht. M. Palo, H. Vanhanen (Eds.).
71. Zhang Y., Song C. Impacts of afforestation, deforestation, and reforestation on forest cover in China from 1949 to 2003. J. Forestry 2006, 104:383-387.
72. Ziegler A.D., Fox J.M., Xu J. The rubber juggernaut. Science 2009, 324:1024-1025.