The impact of changes in agricultural technology on long-term trends in deforestation

被引:13
|
作者
Grainger, A [1 ]
Francisco, HA
Tiraswat, P
机构
[1] Univ Leeds, Sch Geog, Leeds LS2 9JT, W Yorkshire, England
[2] Univ Philippines, Coll Econ & Management, Los Banos 4031, Laguna, Philippines
[3] Chulalongkorn Univ, Inst Populat Studies, Bangkok 10330, Thailand
关键词
tropical deforestation; technological change; regression models; spatial deforestation models; political economy; agricultural extension; agricultural policy; food policy; GM crops;
D O I
10.1016/S0264-8377(03)00009-7
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
To overcome the limitations of existing aggregated national deforestation models in explaining the impact of changes in agricultural technological on deforestation a two-zone national political economy model is outlined and illustrated by examples from the Philippines and Thailand. It suggests that deforestation trends depend on where and when new technologies are adopted and by whom. In particular, they are sensitive to the balance between adoption in the highly productive Core and the less fertile Periphery where remaining forest concentrates as a country develops. Without parallel adoption in the Periphery, rising yields in the Core alone may not control deforestation. State intervention can help to overcome adoption bias but is still limited by state-elite-corporate links. Five criteria are proposed to assess the likely effectiveness of agricultural policies to control deforestation: (1) improve sustainable farm productivity in the Core, (2) improve sustainable farm productivity in the Periphery, (3) generate sufficient manufacturing/service jobs for ex-farmers, (4) reform land tenure and (5) decentralize state agriculture departments to promote the participation of farmers in the design of appropriate technologies. Deforestation is likely to continue if criteria 1-3 are not met. (C) 2003 Elsevier Ltd. All rights reserved.
引用
收藏
页码:209 / 223
页数:15
相关论文
共 50 条
  • [41] Trends in Long-Term Drought Changes in the Mekong River Delta of Vietnam
    Vu Hien Phan
    Vi Tung Dinh
    Su, Zhongbo
    REMOTE SENSING, 2020, 12 (18)
  • [42] The Clinical Impact of New Long-Term Oxygen Therapy Technology
    Dunne, Patrick J.
    RESPIRATORY CARE, 2009, 54 (08) : 1100 - 1111
  • [43] Long-term trends in the distribution, abundance and impact of native "injurious" weeds
    Maskell, Lindsay C.
    Henrys, Peter
    Pescott, Oliver L.
    Smart, Simon M.
    APPLIED VEGETATION SCIENCE, 2020, 23 (04) : 635 - 647
  • [44] Whither European diplomacy? Long-term trends and the impact of the Lisbon Treaty
    Bicchi, Federica
    Schade, Daniel
    COOPERATION AND CONFLICT, 2022, 57 (01) : 3 - 24
  • [45] Long-Term Impact
    Weiss, Paul S.
    Willson, C. Grant
    Bonnell, Dawn A.
    Lewis, Penelope A.
    Hammond, Paula T.
    ACS NANO, 2008, 2 (12) : 2425 - 2426
  • [46] The Impact of Migration on Long-Term European Population Trends, 1850 to Present
    Murphy, Michael
    POPULATION AND DEVELOPMENT REVIEW, 2016, 42 (02) : 224 - 244
  • [47] Impact of NOx reduction on long-term ozone trends in an urban atmosphere
    Itano, Yasuyuki
    Bandow, Hiroshi
    Takenaka, Norimichi
    Saitoh, Yoshiyuki
    Asayama, Atsushi
    Fukuyama, Joji
    SCIENCE OF THE TOTAL ENVIRONMENT, 2007, 379 (01) : 46 - 55
  • [48] Impact of prescribed SSTs on climatologies and long-term trends in CCM simulations
    Garny, H.
    Dameris, M.
    Stenke, A.
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2009, 9 (16) : 6017 - 6031
  • [49] Prediction of agricultural water deficiency and its management using long-term rainfall trends
    Gorai, Sanjoy
    Ratha, Dwarikanath
    Dhir, Amit
    SUSTAINABLE WATER RESOURCES MANAGEMENT, 2023, 9 (04)
  • [50] Prediction of agricultural water deficiency and its management using long-term rainfall trends
    Sanjoy Gorai
    Dwarikanath Ratha
    Amit Dhir
    Sustainable Water Resources Management, 2023, 9