Regional patterns of agricultural land use and deforestation in Colombia
Regional patterns of agricultural land use and deforestation in Colombia
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DOI：
10.1016/j.agee.2005.11.013
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发表时间：
2006-06-01
影响因子：
6.6
通讯作者：
Possingham, HP
中科院分区：
文献类型：
--
作者：
Etter, A;McAlpine, C;Possingham, HP
不断增长的人口和对商品和服务的相关需求继续对生态系统施加越来越大的压力。尽管自1960年以来，农业用地的扩张速度已经放缓，但在包括哥伦比亚在内的许多热带国家，森林砍伐仍然迅速。然而，热带国家内森林砍伐的地点和程度以及相关的生态影响往往不为人所知。这项研究的主要目的是获得在哥伦比亚的农业用地的森林转换的空间格局的理解。我们在区域和国家层面上使用逻辑回归和分类树在哥伦比亚本土森林转换建模。我们研究了忽略模型参数的区域变异性的影响，并确定了最能解释当前森林覆盖空间格局和区域间变化的生物物理和社会经济因素。我们使用MODIS卫星图像验证了我们对亚马逊地区的预测。考虑区域异质性的区域级分类树具有最大的区分能力。与可达性有关的因素（到公路和城镇的距离）与森林覆盖的存在有关，尽管这种关系因区域而异。为了确定森林砍伐风险高的地区，我们使用了最佳模型的预测，并根据农村人口增长率> 2%的地区进行了优化。我们对森林生态系统类型进行了转换威胁程度的排名。我们的研究结果提供了有用的投入，规划在哥伦比亚的生物多样性保护，通过确定地区和生态系统类型，是脆弱的森林砍伐。一些预测的森林砍伐热点与生物多样性价值突出的地区相吻合。(c)2005 Elsevier B.V.保留所有权利。
An expanding human population and associated demands for goods and services continues to exert an increasing pressure on ecological systems. Although the rate of expansion of agricultural lands has slowed since 1960, rapid deforestation still occurs in many tropical countries, including Colombia. However, the location and extent of deforestation and associated ecological impacts within tropical countries is often not well known. The primary aim of this study was to obtain an understanding of the spatial patterns of forest conversion for agricultural land uses in Colombia. We modeled native forest conversion in Colombia at regional and national-levels using logistic regression and classification trees. We investigated the impact of ignoring the regional variability of model parameters, and identified biophysical and socioeconomic factors that best explain the current spatial pattern and inter-regional variation in forest cover. We validated our predictions for the Amazon region using MODIS satellite imagery. The regional-level classification tree that accounted for regional heterogeneity had the greatest discrimination ability. Factors related to accessibility (distance to roads and towns) were related to the presence of forest cover, although this relationship varied regionally. In order to identify areas with a high risk of deforestation, we used predictions from the best model, refined by areas with rural population growth rates of > 2%. We ranked forest ecosystem types in terms of levels of threat of conversion. Our results provide useful inputs to planning for biodiversity conservation in Colombia, by identifying areas and ecosystem types that are vulnerable to deforestation. Several of the predicted deforestation hotspots coincide with areas that are outstanding in terms of biodiversity value. (c) 2005 Elsevier B.V. All rights reserved.