Modeling the effects of urban expansion on natural capital stocks and ecosystem service flows: A case study in the Puget Sound, Washington, USA
Modeling the effects of urban expansion on natural capital stocks and ecosystem service flows: A case study in the Puget Sound, Washington, USA
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DOI：
10.1016/j.landurbplan.2016.01.004
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发表时间：
2016-05
影响因子：
9.1
通讯作者：
Benjamin Zank;K. Bagstad;B. Voigt;F. Villa
中科院分区：
文献类型：
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作者：
Benjamin Zank;K. Bagstad;B. Voigt;F. Villa
城市扩展及其相关的景观改造是生态系统服务功能变化的重要驱动力。本研究探讨了两种替代土地利用变化的发展方案在普吉特湾地区的华盛顿州自然资本存量和ES流量的影响。土地利用变化模型的输出作为使用人工智能生态系统服务平台开发的五个ES模型的输入。虽然在有管理的发展情景下（1.3-5.8%）和无管理的发展情景下（2.8-11.8%）自然资本存量下降，但环境服务流量分别增加了18.5-56%和23.2- 55.7%。人类对自然景观的开发降低了它们提供服务的能力，但同时增加了受益者，特别是沿着城市边缘地区。使用全球和当地的莫兰的我，我们确定了三种不同的模式，由于预计土地利用变化的ES的变化。对于受益者依赖于位置的服务-开放空间接近度，视野和洪水调节-城市化导致集群和热点强度增加。ES流量是最大的管理的土地利用变化的情况下，开放空间的接近和洪水调节，并在未管理的土地利用变化的情况下的观景台的结果，不同的ES流机制支持这些服务。我们观察到第三种模式-服务提供的普遍下降-碳储存和沉积物保留，我们分析中的受益者不依赖于位置。与过去作者在城市化下ES下降的发现相反，一个更细致的分析，绘制和量化ES供应，受益者和流量，更好地确定收益和损失的特定ES受益者作为城市地区的扩展。
Urban expansion and its associated landscape modifications are important drivers of changes in ecosystem service (ES). This study examined the effects of two alternative land use-change development scenarios in the Puget Sound region of Washington State on natural capital stocks and ES flows. Land-use change model outputs served as inputs to five ES models developed using the Artificial Intelligence for Ecosystem Services (ARIES) platform. While natural capital stocks declined under managed (1.3–5.8%) and unmanaged (2.8–11.8%) development scenarios, ES flows increased by 18.5–56% and 23.2–55.7%, respectively. Human development of natural landscapes reduced their capacity for service provision, while simultaneously adding beneficiaries, particularly along the urban fringe. Using global and local Moran’s I, we identified three distinct patterns of change in ES due to projected landuse change. For services with location-dependent beneficiaries – open space proximity, viewsheds, and flood regulation – urbanization led to increased clustering and hot-spot intensities. ES flows were greatest in the managed land-use change scenario for open space proximity and flood regulation, and in the unmanaged land-use change scenario for viewsheds—a consequence of the differing ES flow mechanisms underpinning these services. We observed a third pattern – general declines in service provision – for carbon storage and sediment retention, where beneficiaries in our analysis were not location dependent. Contrary to past authors’ finding of ES declines under urbanization, a more nuanced analysis that maps and quantifies ES provision, beneficiaries, and flows better identifies gains and losses for specific ES beneficiaries as urban areas expand.