Population change is a main driver behind global environmental change, including urban land expansion. In future scenario modeling, assumptions regarding how populations will change locally, despite identical global constraints of Shared Socioeconomic Pathways (SSPs), can have dramatic effects on subsequent regional urbanization. Using a spatial modeling experiment at high resolution (1 km), this study compared how two alternative US population projections, varying in the spatially explicit nature of demographic patterns and migration, affect urban land dynamics simulated by the Spatially Explicit, Long-term, Empirical City development (SELECT) model for SSP2, SSP3, and SSP5. The population projections included: (1) newer downscaled state-specific population (SP) projections inclusive of updated international and domestic migration estimates, and (2) prevailing downscaled national-level projections (NP) agnostic to localized demographic processes. Our work shows that alternative population inputs, even those under the same SSP, can lead to dramatic and complex differences in urban land outcomes. Under the SP projection, urbanization displays more of an extensification pattern compared to the NP projection. This suggests that recent demographic information supports more extreme urban extensification and land pressures on existing rural areas in the US than previously anticipated. Urban land outcomes to population inputs were spatially variable where areas in close spatial proximity showed divergent patterns, reflective of the spatially complex urbanization processes that can be accommodated in SELECT. Although different population projections and assumptions led to divergent outcomes, urban land development is not a linear product of population change but the result of complex relationships between population, dynamic urbanization processes, stages of urban development maturity, and feedback mechanisms. These findings highlight the importance of accounting for spatial variations in the population projections, but also urbanization process to accurately project long-term urban land patterns.

中文翻译：

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共享社会经济路径内替代人口预测下不同的城市土地轨迹

人口变化是全球环境变化（包括城市土地扩张）背后的主要驱动力。在未来的情景模型中，尽管共享社会经济路径（SSP）具有相同的全球约束，但关于当地人口如何变化的假设可能会对随后的区域城市化产生巨大影响。本研究使用高分辨率（1 公里）的空间建模实验，比较了两种不同的美国人口预测（人口模式和移民的空间显性性质不同）如何影响由空间显性、长期、经验模型模拟的城市土地动态。 SSP2、SSP3 和 SSP5 的城市发展 (SELECT) 模型。人口预测包括：(1) 新的缩小规模的特定州人口 (SP) 预测，包括更新的国际和国内移民估计，以及 (2) 与当地人口过程无关的现行缩小规模的国家级预测 (NP)。我们的工作表明，不同的人口投入，即使是在同一 SSP 下的人口投入，也可能导致城市土地结果出现巨大而复杂的差异。与 NP 投影相比，SP 投影下的城市化更多地表现出扩张模式。这表明，最近的人口信息支持美国现有农村地区的城市扩张和土地压力比之前预期的更为极端。城市土地对人口投入的影响在空间上是可变的，其中空间接近的区域表现出不同的模式，反映了 SELECT 中可以容纳的空间复杂的城市化过程。虽然不同的人口预测和假设会导致不同的结果，但城市土地开发并不是人口变化的线性产物，而是人口、动态城市化进程、城市发展成熟阶段和反馈机制之间复杂关系的结果。这些发现凸显了人口预测中考虑空间变化的重要性，以及准确预测长期城市土地格局的城市化进程的重要性。