Forest recovery in a tropical landscape: what is the relative importance of biophysical, socioeconomic, and landscape variables?
Forest recovery in a tropical landscape: what is the relative importance of biophysical, socioeconomic, and landscape variables?
复制标题
DOI：
10.1007/s10980-009-9338-8
复制
发表时间：
2009-05-01
影响因子：
5.2
通讯作者：
Flynn, Dan
中科院分区：
文献类型：
--
作者：
Crk, Tanja;Uriarte, Maria;Flynn, Dan
热带许多地区的社会经济变化导致城市化加剧、农业废弃和森林重新生长。虽然这些模式都有详细记录，但很少有研究审查导致森林一级恢复的驱动因素以及由此产生的次生林空间结构。自1940年代以来，波多黎各岛的土地覆盖从农业用地向次生林的过渡一直在进行。这项研究是对1991年至2000年这一景观水平趋势的一瞥。首先，我们依靠陆地卫星图像来描述森林、城市和农业土地类别景观结构的变化。我们发现，虽然森林覆盖率在这一时期有所增加，但森林变得越来越分散，而城市覆盖面积的扩展速度更快，变得更加集中。其次，我们使用逻辑回归来评估向森林过渡与21个生物物理，社会经济和景观变量之间的关系。我们发现，森林覆盖率在100米半径的一个点，距离主要道路和自然保护区，坡度和方面是最重要的预测森林恢复。由此产生的模型预测森林恢复的空间格局与准确性（AUC-ROC = 0.798）。总之，我们的研究结果表明，森林恢复在波多黎各已经放缓，城市化的压力越来越大，可能是决定未来景观水平的森林恢复的关键。这些结果与其他正在经历快速经济发展的热带地区有关。
Socioeconomic changes in many areas in the tropics have led to increasing urbanization, abandonment of agriculture, and forest re-growth. Although these patterns are well documented, few studies have examined the drivers leading to landscape-level forest recovery and the resulting spatial structure of secondary forests. Land cover transitions from agricultural lands to secondary forest in the island of Puerto Rico have been ongoing since the 1940s. This study is a glimpse into this landscape level trend from 1991 to 2000. First, we relied on Landsat images to characterize changes in the landscape structure for forest, urban, and agricultural land classes. We found that although forest cover has increased in this period, forest has become increasingly fragmented while the area of urban cover has spread faster and become more clustered. Second, we used logistic regression to assess the relationship between the transition to forest and 21 biophysical, socioeconomic, and landscape variables. We found that the percentage of forest cover within a 100 m radius of a point, distance to primary roads and nature reserves, slope, and aspect are the most important predictors of forest recovery. The resulting model predicts the spatial pattern of forest recovery with accuracy (AUC-ROC = 0.798). Together, our results suggest that forest recovery in Puerto Rico has slowed down and that increasing pressure from urbanization may be critical in determining future landscape level forest recovery. These results are relevant to other areas in the tropics that are undergoing rapid economic development.