Department of Earth & Environment, Boston University, Boston, MA 02215
Proc Natl Acad Sci U S A. 2020 Nov 24;117(47):29577-29583. doi: 10.1073/pnas.2012865117. Epub 2020 Nov 9.
The justification and targeting of conservation policy rests on reliable measures of public and private benefits from competing land uses. Advances in Earth system observation and modeling permit the mapping of public ecosystem services at unprecedented scales and resolutions, prompting new proposals for land protection policies and priorities. Data on private benefits from land use are not available at similar scales and resolutions, resulting in a data mismatch with unknown consequences. Here I show that private benefits from land can be quantified at large scales and high resolutions, and that doing so can have important implications for conservation policy models. I developed high-resolution estimates of fair market value of private lands in the contiguous United States by training tree-based ensemble models on 6 million land sales. The resulting estimates predict conservation cost with up to 8.5 times greater accuracy than earlier proxies. Studies using coarser cost proxies underestimate conservation costs, especially at the expensive tail of the distribution. This has led to underestimations of policy budgets by factors of up to 37.5 in recent work. More accurate cost accounting will help policy makers acknowledge the full magnitude of contemporary conservation challenges and can help improve the targeting of public ecosystem service investments.
保护政策的合理性和针对性取决于对竞争土地利用的公共和私人利益的可靠衡量。地球系统观测和建模的进步使得在前所未有的规模和分辨率上对公共生态系统服务进行绘图成为可能,从而提出了新的土地保护政策和优先事项建议。土地利用的私人利益数据无法在类似的规模和分辨率上获得,导致数据不匹配,其后果未知。在这里,我表明可以在大规模和高分辨率上量化土地的私人利益,并且这样做可能对保护政策模型产生重要影响。我通过对 600 万笔土地销售数据进行基于树的集成模型训练,得出了美国大陆地区私人土地的公平市场价值的高分辨率估计值。由此产生的估计值可以预测保护成本,其准确性比早期的代理指标高出 8.5 倍。使用较粗糙成本代理的研究低估了保护成本,尤其是在分布的昂贵尾部。这导致最近的研究工作中对政策预算的低估高达 37.5 倍。更准确的成本核算将帮助政策制定者认识到当代保护挑战的全部规模,并有助于改善公共生态系统服务投资的针对性。