Spatial differentiation in forest transition was measured in terms of space transition and function transition using the exploratory spatial data analysis method (ESDA) and data from 2004—2014 for Zunyi city, Guizhou province, China. The validity of factors affecting forest transition was analyzed by constructing radial basis function neural networks (RBFNN) based on the data processing system (DPS). Our results will provide references for scientific understanding of the potential mechanism underlying forest transition in mountainous areas. We found that Global Moran’s I of space transition and function transition of forest land was 0.0336 and 0.2323, respectively. This suggests a significant positive correlation in spatial distribution of space transition and function transition of forest land, and significant spatial aggregation. The Global Moran’s I of function transition was higher than that of space transition, and the spatial aggregation characteristics of function transition were more significant than for space transition. The Global Moran’s I at each time period tended to increase, and the spatial aggregation degree of the function transition and space transition was further enhanced. Hot and cold spots of space transition of forest land stably evolved, suggesting a minor spatial difference in forest land among different administrative units at the county level. The number of hot spots at the county level in function transition increased. Hot spots were intensively distributed at the western edge and continuously distributed in the northeast. The space transition and function transition of forest land were both greatly influenced by urbanization rate and second and third industries. The development of urbanization and industrialization was the main factor driving forest transition, suggesting a positive role of economic growth on forest transition in mountainous areas. The development of urbanization and industrialization is an effective approach to forest transition in mountainous areas.
DONG Shunzhou, ZHAO Yuluan, LI Xiubin
. Spatial Differentiation Characteristics and Driving Forces of Forest Transition: A Case Study of Zunyi City, Guizhou[J]. Journal of Resources and Ecology, 2018
, 9(4)
: 341
-351
.
DOI: 10.5814/j.issn.1674-764x.2018.04.002
[1] Anselin L.1995. Local Indicators of Spatial Association LISA.Geographical Analysis, 27(2): 93-115.
[2] Anselin L, Syabri I, Kho Y.2006. GeoDa: an introduction to spatial data analysis.Geographical analysis, 38(1): 5-22.
[3] Bruggeman D, Meyfroidt P, Lambin E F.2016. Forest cover changes in Bhutan: Revisiting the forest transition.Applied Geography, 67: 49-66.
[4] Barbier E B, Burgess J C.2001. The Economics of Tropical Deforestation.Journal of Economic Surveys, 15(3): 413-433.
[5] Barbier E B, Burgess J C, Grainger A.2010. The forest transition: towards a more comprehensive theoretical framework.Land Use Policy, 27: 98-107.
[6] Bobylev S.1981. Means of improving the utilization of land resources.Problem of Economics, 24(5): 78-95.
[7] Carmo J L, Rodrigues A J.2004. Adaptive forecasting of irregular demand processes.Engineering Application of Artificial Intelligence, 17(2): 137-143.
[8] Dan K.2003. Forest Transition in Mexico: Institutions and Forests in a Globalized Countryside.Professional Geographer, 55(2): 227-237.
[9] Foster D R, Motzkin G, Slater B.1998. Land-use history as long-term broad-scale disturbance: Regional forest dy-namics in central New England.Ecosystems, 1(1): 96-119.
[10] Fang J, Chen A, Peng C et al.Peng C 2001. Change in Forest Biomass Carbon Storage in China between 1949 and 1198.Science, 292: 2320-2322.
[11] Grainger A.1995. The forest Transition: An Alternative Approach.Area, 27(3): 242-251.
[12] Getis A, Ord J K.1992. The analysis of spatial association by the use of distance statistics.Geographical Analysis, 24(3): 189-206.
[13] Hammett A L, Sun X F, Barany M.2001. Industries in transition: forestry and forest products in china.Journal of Forestry, 99(7): 4-10.
[14] Lambin E F, Meyforidt P.2010. Land Use Transitions: Socio-ecological Feedback versus Socio-economic Change.Land Use Policy, 27(2): 108-118.
[15] Lambin E F, Meyforidt P.2011. Global Land Use Change, Economic Globalization, and the Looming Land Scarcity.Proceedings of the National Academy of Sciences, 108(9): 3465-3472.
[16] Long H, Liu Y, Hou X et al.Hou X 2014. Effects of land use transitions due to rapid urbanization on ecosystem services: Implications for urban planning in the new developing area of China.Habitat International, 44: 536-544.
[17] Li X B, Zhao Y L.2011. Forest transition, agricultural land marginalization and ecological restoration.China Population, Resources and Environment, 21(10): 91-95. (in Chinese)
[18] Li Y, Vina A, Yang W, Chen X et al.Chen X 2013. Effects of conservation policies on forest cover change in giant panda habitat regions, China.Land Use Policy, 33: 42-53.
[19] Mather AS.1992. The Forest Transition.Area, 24(4): 367-379.
[20] Mather AS, Needle C L.1998. The Forest Transition: a Theoretical Basis. Area, 30: 117-124.
[21] Moody J, Darken C.1989. Fast learning in networks of locally-tuned processing units.Neural Computation, 1(2): 281-294.
[22] Marisol T, Poorter L, Peña-Claros M.2010. Climate is a stronger driver of tree and forest growth rates than soil and disturbance.Journal of Ecology, 99(1): 254-264.
[23] Ma X Z, Wang Z.2011. Estimation of provincial forest carbon sink capacities in Chinese mainland.Science Bulletin, 56(9): 433-439.
[24] Rudel T, Coomes O T, Moran E et al.Moran E 2005. Forest Transitions: Towards a Global Understanding of Land Use Change.Global Environmental Change, 15(1): 23-31.
[25] Silva RFBD, Batistella M, Moran E F.2016. Drivers of land change: Human-environment interactions and the Atlantic forest transition in the Paraíba Valley, Brazil.Land Use Policy, 58(1): 133-144.
[26] Totman C.1986. Plantation forestry in early modern Japan: Economic aspects of its emergence.Agricultural History, 60(3): 23-51.
[27] Tan K K, Huang S N, Seet H L.2000. Geometrical error compensation of precision motion systems using Radial basis function.IEEE Instrumentation and Measurement, 49(5): 984-991.
[28] Xie H L, Kung C C, Zhao Y L.2012. Spatial disparities of regional forest land change based on ESDA and GIS at the county level in Beijing-Tianjin-Hebei area.Frontiers of Earth Science, 6(4): 445-452.
[29] Xiang J W, Li J F, Zeng J.2016. Spatial difference and its influence factors of cultivated land transition of poverty counties in west of Hubei.Transaction of the Chinese Society of Agricultural Engineering, 32(1): 272-279. (in Chinese)
[30] Wieand K.1987. An extension of the monocentric urban spatial equilibrium model to a multi-center setting: The case of the two-center city.Journal of Urban Economics, 21(3): 259-271.
[31] Yu D Y, Shi P J, Han G Y et al . .2011. Forest ecosystem restoration due to a national conservation plan in China.Ecological Engineering, 37(9): 1387-1397.
[32] Zhang W, Wang X K, Liu B et al.2013. Analysis on the dynamic change of Sichuan forest resources in the last thirty years (1979 to 2007).Sichuan Forestry Exploration & Design, 1: 7-12. (in Chinese)
[33] Zhao Y L, Ge Y J, Kuang C H, et al. 2018. The path of forest transformation in mountainous areas in Guizhou province under the strategy of rural revitalization. Journal of Guizhou Normal University (Natural Sciences), 36(1): 1-7.
[34] Zhao Y L, Li X B.2016. Spatial Correlation between type of mountain area and land use degree in Guizhou province, China.Sustainability, 8: 849.
[35] Zhao Y L, Zhang M, Li X B et al.2016. Farmland Marginalization and Policy Implications in Mountainous Areas: A Case Study of Renhuai City, Guizhou.Journal of Resources & Ecology, 7(1): 61-67.
