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

全世界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（霍顿1994年;迈尔斯1994年; Geist和Lambdin 2001年）。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，而没有考虑定居者家庭最初为什么会在那里定居（卡尔，2004年）。与此同时，几乎所有关于发展中世界移徙问题的研究都集中在农村向城市的移徙和国际移徙上，而这些移徙与森林砍伐的关系不大。该项目的目标是调查危地马拉佩滕，特别是玛雅生物圈保护区毁林和土地利用/土地覆盖变化背后的农村人口外流的决定因素。虽然家庭决策是审查移徙问题的关键，但家庭并不是在真空中作出这些决定的;地方、区域和国家的情况很重要。因此，PI提出了一个涉及多个数据源和方法的研究计划。多尺度数据包括拟议的：（1）社区和市一级数据;（2）对原籍社区几千户家庭的调查;（3）来自地理信息系统数据层的市一级数据，这些数据来自遥感大地卫星TM图像和2003年危地马拉人口和农业普查。研究问题将通过一个四层次的统计模型的新应用程序进行检查。该模型将用于确定个人、家庭、社区和市镇因素对移民的相对贡献，并说明空间规模的重要性。 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进行了持续的合作，并将充分利用这些数据集。拟议的研究对以下方面作出了新的贡献：1）全球环境变化研究的人的方面; 2）多尺度空间和调查定量和定性方法的整合。该项目的智力价值是对人类环境和空间社会科学研究的新概念和方法贡献的结合。该项目将增进对农村向边境移徙与热带森林砍伐之间联系的了解，这是世界上最突出的土地覆盖变化形式。PI认为，这是第一次将农业前沿的森林砍伐与一个主要的根本原因联系起来，即从原籍地区向外移民。它还率先在移徙者原籍地区使用调查和空间数据，并使用四级分层随机效应模型审查农村-农村移徙的决定因素。 该研究还通过促进国际合作（包括代表性不足的群体）产生更广泛的影响，这将加强危地马拉人口学的教学，制作高质量的学术出版物，并影响政治政策干预措施，以改善农村贫困和保护中美洲的热带森林。

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.