The Underlying Cause of Tropical Deforestation: Rural Migration and Environmental Degradation in Guatemala

热带森林砍伐的根本原因：危地马拉的农村移民和环境退化

• 批准号: 0525592
• 负责人: David Lopez-Carr
• 金额: $ 11.64万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0525592&HistoricalAwards=false
• 关键词: Underlying; Cause; Tropical; Deforestation; Rural

The primary cause of deforestation worldwide is agricultural expansion, mostly by small-farm families migrating to forest frontiers (Houghton 1994; Myers 1994; Geist and Lambdin 2001). Yet in studying forest clearing and land use, scholars of human-induced environmental change have focused almost exclusively on land use and degradation on the frontier, without considering why settler families end up there in the first place (Carr, 2004). At the same time, virtually all research on migration in the developing world has focused on rural-urban migration and international migration, which are only peripherally related to deforestation. The objective of the project is to investigate the determinants of the rural out-migration that underlies the deforestation and land use/land cover change (LUCC) in Guatemala's Peten, particularly in the Maya Biosphere Reserve (MBR). While household decision-making is key to examining migration, households do not make these decisions in a vacuum; local, regional, and national contexts matter. The PIs therefore propose a research plan that involves multiple data sources and methods. Multiple scale data include proposed: 1) community and municipio-level data; 2) surveys of several thousand households in origin communities; and 3) Municipio-level data from Geographic Information System (GIS) data layers derived from remotely sensed Landsat TM images and from the Guatemalan population and agricultural censuses of 2003. Research questions will be examined through the novel application of a four-level hierarchical statistical model. The model will be used to determine the relative contributions of individual, household, community, and municipio factors to migration, and to illustrate the importance of spatial scale. The PI has enjoyed an ongoing collaboration with scholars at the National Statistics Institute and other major research institutes in Guatemala and will have full access to these data sets The proposed research makes novel contributions to 1) human dimensions of global environmental change research and 2) the integration of multi-scale spatial and survey quantitative and qualitative methods. The intellectual merit of this project is the combination of a novel conceptual and methodological contribution to human-environment and spatial social science research. The project will enhance understanding of linkages between rural-frontier migration and tropical deforestation, the most salient form land cover change in the world. The PIs believe it is the first to link deforestation on the agricultural frontier to a major underlying cause, out-migration from areas of origin. It is also pioneering in using both survey and spatial data in areas of migrant origin, and in examining the determinants of rural-rural migration using a 4-level hierarchical random effects model. The research also makes broader impacts by fostering international collaborations - including those from underrepresented groups - that will strengthen pedagogy on demography in Guatemala, produce quality scholarly publications, and influence polity policy interventions for ameliorating rural poverty and conserving Mesoamerica's tropical forests.

全球森林砍伐的主要原因是农业扩张，主要是小农场家庭迁移到森林边界（Houghton 1994；Myers 1994；Geist 和 Lambdin 2001）。然而，在研究森林砍伐和土地利用时，研究人类引起的环境变化的学者几乎只关注边境地区的土地利用和退化，而没有考虑为什么定居者家庭最终会来到那里（Carr，2004）。与此同时，几乎所有关于发展中国家移民的研究都集中在农村到城市的移民和国际移民上，而这些与森林砍伐只有外围关系。该项目的目标是调查导致危地马拉佩滕（特别是玛雅生物圈保护区（MBR））森林砍伐和土地利用/土地覆盖变化（LUCC）的农村人口外迁的决定因素。虽然家庭决策是审查移民的关键，但家庭并不是在真空中做出这些决定的。地方、区域和国家背景都很重要。因此，PI 提出了一项涉及多种数据源和方法的研究计划。多尺度数据包括：1）社区和市级数据； 2）对原籍社区数千户家庭进行调查； 3) 来自地理信息系统 (GIS) 数据层的市政级数据，该数据层源自遥感 Landsat TM 图像以及 2003 年危地马拉人口和农业普查。研究问题将通过四级分层统计的新颖应用进行审查模型。该模型将用于确定个人、家庭、社区和市政因素对移民的相对贡献，并说明空间尺度的重要性。 PI 与危地马拉国家统计研究所和其他主要研究机构的学者保持着持续的合作，并将完全访问这些数据集。拟议的研究对 1) 全球环境变化研究的人类层面和 2) 做出了新的贡献。多尺度空间和调查定量和定性方法的整合。该项目的智力价值在于对人类环境和空间社会科学研究的新颖概念和方法论贡献的结合。该项目将加深对农村边境移民与热带森林砍伐之间联系的了解，热带森林砍伐是世界上最突出的土地覆盖变化形式。 PI认为，这是第一个将农业边境的森林砍伐与原籍地区的人口外迁联系起来的一个主要根本原因。它还在使用移民来源地区的调查和空间数据以及使用四级分层随机效应模型研究农村人口流动的决定因素方面处于领先地位。 该研究还通过促进国际合作（包括来自代表性不足群体的合作）产生更广泛的影响，这将加强危地马拉的人口学教育，出版高质量的学术出版物，并影响改善农村贫困和保护中美洲热带森林的政治政策干预。