Journal of Geographical Sciences ›› 2018, Vol. 28 ›› Issue (11): 1715-1732.doi: 10.1007/s11442-018-1539-0
• Special Issue: Land system dynamics: Pattern and process • Previous Articles
Yue DOU1, Felipe Bicudo da SILVA Ramon2, Hongbo YANG1, Jianguo LIU1,*()
Received:
2017-09-01
Accepted:
2018-01-15
Online:
2018-11-20
Published:
2018-11-20
Contact:
Jianguo LIU
E-mail:liuji@msu.edu
About author:
Author: Dou Yue (1987-), Postdoctoral Research Associate, specialized in land use and land cover changes and modeling. E-mail: yuedou@msu.edu
Supported by:
Yue DOU, Felipe Bicudo da SILVA Ramon, Hongbo YANG, Jianguo LIU. Spillover effect offsets the conservation effort in the Amazon[J].Journal of Geographical Sciences, 2018, 28(11): 1715-1732.
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
Figure 1
Spillover effects to Cerrado biome. The flow between sending and receiving systems is regulated by the agreements, but not the flow between spillover and receiving systems. We hypothesized the implementation of the conservation policies and agreements in the sending system may have increased the flow of information from sending system to the spillover system, causing more deforestation in the Cerrado than before as a spillover. Explanation of variables can be found in the following section."
Table 1
Contexts and methods used to study deforestation and land use in Brazil in current literatures"
Reference | Region | Temporal period | Land use and land cover changes | Control variables | Model or method | Analytical framework |
---|---|---|---|---|---|---|
Macedo et al., 2012 | Mato Grosso | 2001-2010 | Post-deforestation land use, indirect land use | Market trends Climate variability Yield Cost of production | Correlation | No framework used, identified policies and market trends as external factors to land use changes in MT. |
Richards et al., 2014 | Amazon | 2002-2011 | Deforestation, indirect land use | Market trends Local effects Indirect agricultural influence | Spatial regression | No framework used, indirect influence was calculated as weighted distance. |
Arima et al., 2011 | Legal Amazon | 2003-2008 | Deforestation, indirect land use | Soybean planted area Cattle herd Precipitation Farm gate price for cattle | Fixed effect spatial regression | No framework used, distance was measured in the regression. |
Barona et al., 2010 | Legal Amazon | 2001-2006 | Deforestation, indirect land use | Pasture land change, Cropland change | Linear regression | No framework |
Spera et al., 2014 | Mato Grosso | 2001-2011 | Land use transition | Land characters | t-test | No framework |
Table 2
Significance and coefficient of variables to deforestation in sending (Pará) and spillover (Tocantins) systems"
PA coefficient | P-value | TO coefficient | P-value | |
---|---|---|---|---|
(Intercept) | -2.44 | *** | -0.46 | |
Soybean price lagged | -0.30 | 0.12 | ||
Soybean price current | 0.78 | * | -3.35 | *** |
Post2006 | 0.46 | -0.70 | ** | |
Soybean price lagged: Post2006 | 0.59 | -0.84 | ||
Soybean price current: Post2006 | -1.74 | *** | 4.05 | *** |
Beef price current | 0.06 | -0.04 | ||
Beef price lagged | -0.10 | * | -0.19 | ** |
Post2009 | -0.59 | * | -0.85 | ** |
Beef price current: Post2009 | -0.10 | 0.01 | ||
Beef price lagged: Post2009 | 0.18 | . | 0.29 | *** |
Road density | 0.61 | *** | -1.32 | * |
Distance to closest major ports | 0.00 | *** | 0.00 | |
Available area | 0.39 | *** | 0.76 | *** |
R-square | 0.53 | 0.34 |
Figure 8
Possible deforestation processes before and after agreements in the sending (Pará) and spillover (Tocantins) systems. F is short for Forest, P for Pasture land, and S for Soybean land. The left section is the land use processes in Pará, the Amazon biome while on the right is the land use processes in Tocantins, the Cerrado biome, with pattern filling indicating displaced soybean land use (or saved forest) and underline indicating displaced pasture."
Table 4
Alternative models of deforestation"
Sending (Pará) | Sample size | Soybean yield impact | R2 |
---|---|---|---|
Current model | 748 | Not applicable | 0.59 |
Soybean yield | 203 | Not significant | 0.63 |
GDP industry t & t-1 | 543 | Not significant | 0.59 |
Spillover (Tocantins) | Sample size | Soybean yield impact | R2 |
Current model | 1186 | Not applicable | 0.35 |
Soybean yield | 580 | Not significant | 0.36 |
GDP industry t & t-1 | 782 | Not significant | 0.32 |
[1] | Almeida L B, 2012. Zoneamento Geoambiental do Estado do Tocantins. Rio Claro, Sao Paulo. |
[2] |
Arima E Y, Richards P, Walker R et al., 2011. Statistical confirmation of indirect land use change in the Brazilian Amazon.Environmental Research Letters, 6(2): 1-7.
doi: 10.1088/1748-9326/6/2/024010 |
[3] | Assunção J, Gandour C, Rocha R, 2015. Deforestation slowdown in the Brazilian Amazon: Prices or policies? Pages 1-5 Environment and Development Economics. |
[4] | Bastos T X, Pachêco N A, 2005. Freqüências de Chuva no Estado do Pará no Plano Microrregional. Page Boletim de Pesquisa e Desenvolvimento. Belem, Para. |
[5] |
Bond W J, Parr C L, 2010. Beyond the forest edge: Ecology, diversity and conservation of the grassy biomes.Biological Conservation, 143(10): 2395-2404.
doi: 10.1016/j.biocon.2009.12.012 |
[6] |
Brando P M, Coe M T, DeFries R et al., 2013. Ecology, economy and management of an agroindustrial frontier landscape in the southeast Amazon.Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 368(1619): 1-9.
doi: 10.1098/rstb.2012.0152 pmid: 3638423 |
[7] |
Deines J M, Liu X, Liu J, 2015. Telecoupling in urban water systems: An examination of Beijing’s imported water supply.Water International, 41(2): 251-270.
doi: 10.1080/02508060.2015.1113485 |
[8] |
Foley J A, Defries R, Asner G P et al., 2005. Global consequences of land use.Science, 309(5734): 570-574.
doi: 10.1126/science.1111772 |
[9] | Furtado A M M, Ponte F C, 2013. Mapeamento de Unidades de Relevo do Estado do Pará.Revista GeoAmazônica, 2(2): 56-67. |
[10] |
Garrett R D, Rausch L L, 2016. Green for gold: Social and ecological tradeoffs influencing the sustainability of the Brazilian soy industry.The Journal of Peasant Studies, 43(2): 461-493.
doi: 10.1080/03066150.2015.1010077 |
[11] |
Gibbs H K, Munger J, L’Roe J et al., 2016. Did Ranchers and slaughterhouses respond to zero-deforestation agreements in the Brazilian Amazon?Conservation Letters, 9(1): 32-42.
doi: 10.1111/conl.12175 |
[12] |
Gibbs H K, Rausch L, Munger J et al., 2015. Brazil’s Soy Moratorium.Science, 347(6220): 377-378.
doi: 10.1126/science.aaa0181 |
[13] | Hulina J, Bocetti C, Campa III H et al., 2017. Telecoupling framework for research on migratory species in the Anthropocene.Elementa Science of the Anthroponcene, 5(5): 23. |
[14] |
Klink C A, Machado R B, 2005. Conservation of the Brazilian Cerrado.Conservation Biology, 19(3): 707-713.
doi: 10.1111/j.1523-1739.2005.00702.x |
[15] |
Lambin E F, Gibbs H K, Ferreira L et al., 2013. Estimating the world’s potentially available cropland using a bottom-up approach.Global Environmental Change, 23(5): 892-901.
doi: 10.1016/j.gloenvcha.2013.05.005 |
[16] |
Lambin E F, Meyfroidt P, 2011. Global land use change, economic globalization, and the looming land scarcity.Proceedings of the National Academy of Sciences, 108(9): 3465-3472.
doi: 10.1073/pnas.1100480108 |
[17] |
Lapola D M, Martinelli L A, Peres C A et al., 2014. Pervasive transition of the Brazilian land-use system.Nature Climate Change, 4(1): 27-35.
doi: 10.1038/nclimate2056 |
[18] |
Lapola D M, Schaldach R, Alcamo J et al., 2010. Indirect land-use changes can overcome carbon savings from biofuels in Brazil.Proceedings of the National Academy of Sciences, 107(8): 3388-3393.
doi: 10.1073/pnas.0907318107 |
[19] |
Liu J, Dietz T, Carpenter S R et al., 2007. Complexity of coupled human and natural systems.Science, 317(5844): 1513-1516.
doi: 10.1126/science.1144004 pmid: 17872436 |
[20] |
Liu J, Dou Y, Batistella M et al., 2018. Spillover systems in a telecoupled Anthropocene: Typology, methods, and governance for global sustainability.Current Opinion in Environmental Sustainability, 33: 58-69.
doi: 10.1016/j.cosust.2018.04.009 |
[21] | Liu J, Hull V, Batistella M et al., 2013. Framing sustainability in a telecoupled world.Ecology and Society, 18(2): 26. |
[22] | Liu J, Hull V, Luo J et al., 2015a. Multiple telecouplings and their complex interrelationships.Ecology and Society, 20(3): 44. |
[23] |
Liu J, Mooney H, Hull V et al., 2015b. Systems integration for global sustainability.Science, 347(6225): 963-973.
doi: 10.1126/science.1258832 pmid: 25722418 |
[24] |
Liu J, Yang W, Li S, 2016. Framing ecosystem services in the telecoupled Anthropocene.Frontiers in Ecology and the Environment, 14(1): 27-36.
doi: 10.1002/16-0188.1 |
[25] |
Macedo M N, DeFries R S, Morton D C et al., 2012. Decoupling of deforestation and soy production in the southern Amazon during the late 2000s.Proceedings of the National Academy of Sciences, 109(4): 1341-1346.
doi: 10.1073/pnas.1111374109 pmid: 22232692 |
[26] |
Meyfroidt P, Lambin E F, 2009. Forest transition in Vietnam and displacement of deforestation abroad.Proceedings of the National Academy of Sciences, 106(38): 16139-16144.
doi: 10.1073/pnas.0904942106 pmid: 19805270 |
[27] |
Morton D C, DeFries R S, Shimabukuro Y E et al., 2006. Cropland expansion changes deforestation dynamics in the southern Brazilian Amazon.Proceedings of the National Academy of Sciences of the United States of America, 103(39): 14637-14641.
doi: 10.1073/pnas.0606377103 |
[28] |
Nepstad D, Mcgrath D, Stickler C et al., 2014. Slowing Amazon deforestation through public policy and interventions in beef and soy supply chains.Science, 344(6188): 1118-1123.
doi: 10.1126/science.1248525 pmid: 24904156 |
[29] |
Santopuoli G, Marchetti M, Giongo M, 2016. Supporting policy decision makers in the establishment of forest plantations, using SWOT analysis and AHPs analysis: A case study in Tocantins (Brazil).Land Use Policy, 54: 549-558.
doi: 10.1016/j.landusepol.2016.03.013 |
[30] |
Santos C A C, Oliveira V G, 2017. Trends in extreme climate indices for Pará State, Brazil.Revista Brasileira de Meteorologia, 32(1): 13-24.
doi: 10.1590/0102-778632120150053 |
[31] |
Silva R F B D, 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: 133-144.
doi: 10.1016/j.landusepol.2016.07.021 |
[32] |
Soares-filho B, Rajão R, Macedo M et al., 2014. Cracking Brazil’s forest code.Science, 344(6182): 363-364.
doi: 10.1126/science.1246663 |
[33] |
Sun J, Mooney H, Wu W B et al., 2018. Importing food damages domestic environment: Evidence from global soybean trade.PNAS, 115(21): 5415-5419.
doi: 10.1073/pnas.1718153115 pmid: 29735661 |
[34] |
Sun J, Tong Y, Liu J, 2017. Telecoupled land-use changes in distant countries.Journal of Integrative Agriculture, 16(2): 368-376.
doi: 10.1016/S2095-3119(16)61528-9 |
[35] |
Wang F, Liu J, 2016. Conservation planning beyond giant pandas: The need for an innovative telecoupling framework.Science China Life Sciences, 60(5): 1-4.
doi: 10.1007/s11427-016-0349-0 pmid: 28303460 |
[36] |
Wu W, Tang H, Yang P et al., 2011. Scenario-based assessment of future food security.Journal of Geographical Sciences, 21(1): 3-17.
doi: 10.1007/s11442-011-0825-x |
[37] | Yang W, Hyndman D W, Winkler J A et al., 2016. Urban water sustainability: Framework and application.Ecology and Society, 21(4): 14. |
[38] |
Yao Z, Zhang L, Tang S et al., 2017. The basic characteristics and spatial patterns of global cultivated land change since the 1980s.Journal of Geographical Sciences, 27(7): 771-785.
doi: 10.1007/s11442-017-1405-5 |
[39] |
Zhang J, Zhao N, Liu X et al., 2016. Global virtual-land flow and saving through international cereal trade.Journal of Geographical Sciences, 26(5): 619-639.
doi: 10.1007/s11442-016-1289-9 |
[1] | WANG Zhenbo, LI Jiaxin, LIANG Longwu. Identifying the scope of the Lhasa Metropolitan Area based on a spatial field energy model [J]. Journal of Geographical Sciences, 2021, 31(2): 245-264. |
[2] | DONG Yin, JIN Gui, DENG Xiangzheng, WU Feng. Multidimensional measurement of poverty and its spatio-temporal dynamics in China from the perspective of development geography [J]. Journal of Geographical Sciences, 2021, 31(1): 130-148. |
[3] | CHEN Fahu, WU Shaohong, CUI Peng, CAI Yunlong, ZHANG Yili, YIN Yunhe, LIU Guobin, OUYANG Zhu, MA Wei, YANG Linsheng, WU Duo, LEI Jiaqiang, ZHANG Guoyou, ZOU Xueyong, CHEN Xiaoqing, TAN Minghong, WANG Xunming, BAO Anming, CHENG Weixin, DANG Xiaohu, WEI Binggan, WANG Guoliang, WANG Wuyi, ZHANG Xingquan, LIU Xiaochen, LI Shengyu. Progress and prospects of applied research on physical geography and the living environment in China over the past 70 years (1949-2019) [J]. Journal of Geographical Sciences, 2021, 31(1): 3-45. |
[4] | WANG Chengjin, LI Xumao, CHEN Peiran, XIE Yongshun, LIU Weidong. Spatial pattern and developing mechanism of railway geo-systems based on track gauge: A case study of Eurasia [J]. Journal of Geographical Sciences, 2020, 30(8): 1283-1306. |
[5] | YE Chao, LI Simeng, ZHANG Zhao, ZHU Xiaodan. A comparison and case analysis between domestic and overseas industrial parks of China since the Belt and Road Initiative [J]. Journal of Geographical Sciences, 2020, 30(8): 1266-1282. |
[6] | GE Dazhuan, ZHOU Guipeng, QIAO Weifeng, YANG Mengqi. Land use transition and rural spatial governance: Mechanism, framework and perspectives [J]. Journal of Geographical Sciences, 2020, 30(8): 1325-1340. |
[7] | YANG Ren, PAN Yuxin, XU Qian. Space diversification process and evolution mechanism of typical village in the suburbs of Guangzhou: A case study of Beicun [J]. Journal of Geographical Sciences, 2020, 30(7): 1155-1178. |
[8] | ZHOU Liang, ZHOU Chenghu, CHE Lei, WANG Bao. Spatio-temporal evolution and influencing factors of urban green development efficiency in China [J]. Journal of Geographical Sciences, 2020, 30(5): 724-742. |
[9] | JIN Gui, SHI Xin, HE Dawei, GUO Baishu, LI Zhaohua, SHI Xianbin. Designing a spatial pattern to rebalance the orientation of development and protection in Wuhan [J]. Journal of Geographical Sciences, 2020, 30(4): 569-582. |
[10] | YANG Wenjie, GONG Qianwen, ZHANG Xueyan. Surplus or deficit? Quantifying the total ecological compensation of Beijing-Tianjin-Hebei Region [J]. Journal of Geographical Sciences, 2020, 30(4): 621-641. |
[11] | LIU Haimeng, FANG Chuanglin, FANG Kai. Coupled Human and Natural Cube: A novel framework for analyzing the multiple interactions between humans and nature [J]. Journal of Geographical Sciences, 2020, 30(3): 355-377. |
[12] | LIU Wenchao, LIU Jiyuan, KUANG Wenhui. Spatio-temporal characteristics of soil protection efforts of the Grain for Green Project in northern Shaanxi Province [J]. Journal of Geographical Sciences, 2020, 30(3): 401-422. |
[13] | ZHANG Chengming, WENG Shixiu, BAO Jigang. The changes in the geographical patterns of China’s tourism in 1978-2018: Characteristics and underlying factors [J]. Journal of Geographical Sciences, 2020, 30(3): 487-507. |
[14] | ZHOU Yannan, YANG Yu, SONG Zhouying, HE Ze, XIA Siyou, REN Yawen. Dynamic transition mechanism analysis of the impact of energy development on urbanization in Central Asia [J]. Journal of Geographical Sciences, 2020, 30(11): 1825-1848. |
[15] | Jie GONG, Yuchu XIE, Erjia CAO, Qiuyan Huang, Hongying LI. Integration of InVEST-habitat quality model with landscape pattern indexes to assess mountain plant biodiversity change: A case study of Bailongjiang watershed in Gansu Province [J]. Journal of Geographical Sciences, 2019, 29(7): 1193-1210. |
|