Department of Ecology and Ecosystem Sciences, School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.
Institute of International Forestry and Forest Economics, Johann Heinrich von Thünen Institute, Hamburg, Germany.
PLoS One. 2020 Jan 29;15(1):e0226830. doi: 10.1371/journal.pone.0226830. eCollection 2020.
A better understanding of deforestation drivers across countries and spatial scales is a precondition for designing efficient international policies and coherent land use planning strategies such as REDD+. However, it is so far unclear if the well-studied drivers of tropical deforestation behave similarly across nested subnational jurisdictions, which is crucial for efficient policy implementation. We selected three countries in Africa, America and Asia, which present very different tropical contexts. Making use of spatial econometrics and a multi-level approach, we conducted a set of regressions comprising 3,035 administrative units from the three countries at micro-level, plus 361 and 49 at meso- and macro-level, respectively. We included forest cover as dependent variable and seven physio-geographic and socioeconomic indicators of well-known drivers of deforestation as explanatory variables. With this, we could provide a first set of highly significant econometric models of pantropical deforestation that consider subnational units. We identified recurrent drivers across countries and scales, namely population pressure and the natural condition of land suitability for crop production. The impacts of demography on forest cover were strikingly strong across contexts, suggesting clear limitations of sectoral policy. Our findings also revealed scale and context dependencies, such as an increased heterogeneity at local scopes, with a higher and more diverse number of significant determinants of forest cover. Additionally, we detected stronger spatial interactions at smaller levels, providing empirical evidence that certain deforestation forces occur independently of the existing de jure governance boundaries. We demonstrated that neglecting spatial dependencies in this type of studies can lead to several misinterpretations. We therefore advocate, that the design and enforcement of policy instruments-such as REDD+-should start from common international entry points that ensure for coherent agricultural and demographic policies. In order to achieve a long-term impact on the ground, these policies need to have enough flexibility to be modified and adapted to specific national, regional or local conditions.
更好地了解各国和各空间尺度的森林砍伐驱动因素是设计有效的国际政策和连贯的土地利用规划策略(如 REDD+)的前提条件。然而,到目前为止,还不清楚在嵌套的次国家管辖范围内,热带森林砍伐的研究充分的驱动因素是否表现出相似的行为,这对于有效的政策实施至关重要。我们选择了非洲、美洲和亚洲的三个国家,这些国家呈现出非常不同的热带环境。我们利用空间计量经济学和多层次方法,在微观层面上对来自这三个国家的 3035 个行政单位进行了一组回归,在中观和宏观层面上分别对 361 个和 49 个单位进行了回归。我们将森林覆盖率作为因变量,将七个已知的森林砍伐驱动因素的生理地理和社会经济指标作为解释变量。通过这种方式,我们可以提供一组首次考虑次国家单位的泛热带森林砍伐的高度显著的计量经济学模型。我们确定了在国家和尺度上普遍存在的驱动因素,即人口压力和土地对作物生产的自然适宜性。人口对森林覆盖的影响在不同的背景下都非常显著,这表明部门政策存在明显的局限性。我们的研究结果还揭示了尺度和背景的依赖性,例如在地方范围内的异质性增加,对森林覆盖有更多样化和更显著的决定因素。此外,我们还在较小的尺度上检测到更强的空间相互作用,为某些森林砍伐力量独立于现有法定治理边界发生提供了经验证据。我们表明,在这类研究中忽略空间依赖性可能会导致一些误解。因此,我们主张,政策工具的设计和执行,如 REDD+,应该从确保连贯的农业和人口政策的共同国际切入点开始。为了在实地产生长期影响,这些政策需要有足够的灵活性,以便根据具体的国家、地区或地方条件进行修改和调整。