转载自“Landscape Ecology”
图3 改进的LUSD-urban模型结构
Fig.3 The structure of the improved LUSD-urban model
中文摘要
背景：有效评估中国未来城市扩展过程对自然生境的影响，对于实现可持续发展目标具有重要意义。然而，现有模型难以可靠且有效地模拟中国未来城市扩展过程，使得未来城市扩展过程对自然生境的影响评估结果仍存在较大的不确定性。
目的：本研究旨在模拟中国未来城市扩展过程，并评估其对自然生境的影响。
方法：本文首先基于本地化共享社会经济路径（Shared Socioeconomic Pathways, SSPs）和卷积神经网络（Convolutional Neural Network, CNN）改进了LUSD-urban（Land Use Scenario Dynamics-urban）模型。然后，利用改进后的 LUSD-urban模型模拟了中国2020-2050年城市扩展过程。最后，评估了未来城市扩展过程对自然生境的可能影响。
结果：结合本地化SSPs情景能够有效表达中国未来社会经济发展趋势的优势以及卷积神经网络能够有效表达非城市像元周边区位信息的优势，改进的LUSD-urban模型能够更加可靠地模拟中国城市扩展过程，模拟精度提升了15~32%。2020-2050年，中国城市土地将增长6.84（3.94~9.03）×104 km²，将导致自然生境损失2.21（1.23~2.95）×104 km²。与1990-2020年相比，未来城市扩展过程对自然生境的影响将加剧。在未来城市扩展过程影响下，自然生境损失量是1990-2020年自然生境损失量的1.23（1.22~1.64）倍。其中，草地是未来损失加剧最为严重的生境类型。
结论：我们建议应加强城市土地的集约利用，保护重要的自然生境，促进中国可持续发展目标和生物多样性保护目标的实现。
Title
Impacts of future urban expansion on natural habitats will intensify in China: scenario analysis with the improved LUSD‑urban model
Abstract
Context
Evaluating the impacts of future urban expansion on natural habitats in China is important for achieving sustainable development goals. However, existing models cannot reliably and effectively simulate future urban expansion in China, which causes great uncertainties in evaluating the impacts of future urban expansion on natural habitats.
Objectives
The objective of this study was to simulate future urban expansion and evaluate its impacts on natural habitats in China.
Methods
First, the Land Use Scenario Dynamics-urban (LUSD-urban) model was improved by coupling localized Shared Socioeconomic Pathways (SSPs) and a convolutional neural network (CNN). Then, urban expansion in China was simulated from 2020 to 2050 by using the improved LUSD-urban model. Finally, we evaluated the potential impacts of future urban expansion on natural habitats.
Results
The localized SSPs could more reliably represent future socioeconomic development trends in China, and the CNN could fully extract the multiscale neighborhood information of nonurban pixels. By combining the advantages of the localized SSPs and the CNN, the simulation accuracy of the improved LUSD-urban model increased by 15–32% compared with that of other models. From 2020 to 2050, urban land is projected to increase by 6.84 (3.94–9.03) × 104 km² and cause a 2.21 (1.23–2.95) × 104 km² loss of natural habitat. Compared with the 1990–2020 period, the impacts of future urban expansion on natural habitats will intensify. Natural habitat loss during 2020–2050 will be 1.23 (1.22 to 1.64) times greater than that during 1990–2020. In addition, grasslands will experience the most serious losses under the influence of future urban expansion.
Conclusions
We suggest that relevant policies be issued to protect important natural habitats during urbanization to achieve Sustainable Development Goals and biodiversity conservation targets in China.
编者评
自然生境对于维持生物多样性具有重要意义，是提升人类福祉、实现可持续发展的重要基础。改革开放以来，随着快速的经济发展和人口增长，中国经历了显著的城市扩展过程，导致自然栖息地和生物多样性出现明显损失。因此，有效评估中国未来城市扩展过程对自然生境的影响，对于保护生物多样性和实现可持续发展目标具有重要意义。已有相关研究多采用全球尺度的未来发展情景，难以有效表达中国未来社会经济发展情况，使得在未来城市土地需求量预测的可靠性上存在不足。此外，现有模型在模拟城市土地空间扩展过程的精度上仍有提升空间。
针对上述不足，本文的创新主要体现在两个方面：（1）选用本地化共享社会经济路径改进了现有研究难以有效表达中国未来社会经济发展情况的问题。本地化SSPs情景是在全球SSPs情景基础上综合考虑了中国的人口和经济发展情况，重新率定了多个关键参数，为预测中国未来城市土地需求量提供了可靠的本地化情景。（2）采用CNN提升了模型的模拟精度。CNN是深度学习算法中应用最广泛的模型之一，能够更好地利用和表达图像中各像元的邻域和区位信息，进而有效提高城市土地空间扩展过程的模拟精度。本研究有效提高了城市扩展过程的模拟能力，并得出了中国未来城市扩展过程对自然生境的影响将加剧的重要结论，可为城市规划、生物多样性保护与可持续发展目标的实现提供参考。
Lu, W., Zhang, D., Ren, Q., et al. Impacts of future urban expansion on natural habitats will intensify in China: scenario analysis with the improved LUSD-urban model. Landscape Ecology (2023).
https://doi.org/10.1007/s10980-023-01740-9
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