Centre for Smart Green Cities, Department of Biological Sciences, Macquarie University, North Ryde, Sydney, NSW, 2109, Australia.
United States Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, USA.
Sci Total Environ. 2018 Oct 15;639:1164-1174. doi: 10.1016/j.scitotenv.2018.05.237. Epub 2018 May 26.
The extent of urban ecological homogenization depends on how humans build, inhabit, and manage cities. Morphological and socio-economic facets of neighborhoods can drive the homogenization of urban forest cover, thus affecting ecological and hydrological processes, and ecosystem services. Recent evidence, however, suggests that the same biophysical drivers differentiating composition and structure of natural forests can further counteract the homogenization of urban forests. We hypothesize that climate can differentiate forest structure across residential macrosystems at regional-to-continental spatial scales. To test this hypothesis, forest structure (tree and shrub cover and volume) was measured using LiDAR data and multispectral imagery across a residential macrosystem composed 1.4 million residential parcels contained in 9 cities and 1503 neighborhoods. Cities were selected along an evapotranspiration (ET) gradient in the conterminous United States, ranging from the colder continental climate of Fargo, North Dakota (ET = 464.43 mm) to the hotter subtropical climate of Tallahassee, Florida (ET = 1000.47 mm). The relative effects of climate, urban morphology, and socio-economic variables on residential forest structure were assessed by using generalized linear models. Climate differentiated forest structure of the residential macrosystem as hypothesized. Average forest cover doubled along the ET gradient (0.39-0.78 m m), whereas average forest volume had a threefold increase (2.50-8.12 m m). Forest volume across neighborhoods increased exponentially with forest cover. Urban morphology had a greater effect in homogenizing forest structure on residential parcels compared to socio-economics. Climate and urban morphology variables best predicted residential forest structure, whereas socio-economic variables had the lowest predictive power. Results indicate that climate can differentiate forest structure across residential macrosystems and may counteract the homogenizing effects of urban morphology and socio-economic drivers at city-wide scales. This resonates with recent empirical work suggesting the existence of complex multi-scalar mechanisms that regulate ecological homogenization and ecosystem convergence among cities. The study initiates high-resolution assessments of forest structure across entire urban macrosystems and breaks new ground for research on the ecological and hydrological significance of urban vegetation at subcontinental scale.
城市生态同质化的程度取决于人类如何建设、居住和管理城市。邻里的形态和社会经济方面可以推动城市森林覆盖的同质化，从而影响生态和水文过程以及生态系统服务。然而，最近的证据表明，区分自然森林组成和结构的相同生物物理驱动因素可以进一步抵消城市森林的同质化。我们假设气候可以在区域到大陆的空间尺度上区分住宅宏观系统中的森林结构。为了检验这一假设，我们使用 LiDAR 数据和多光谱图像测量了一个由 9 个城市和 1503 个街区组成的住宅宏观系统中的森林结构（树木和灌木覆盖和体积）。这些城市是沿着美国连续体的蒸散（ET）梯度选择的，范围从北达科他州法戈的较冷大陆性气候（ET=464.43mm）到佛罗里达州塔拉哈西的较热亚热带气候（ET=1000.47mm）。通过广义线性模型评估了气候、城市形态和社会经济变量对住宅森林结构的相对影响。正如假设的那样，气候区分了住宅宏观系统的森林结构。森林覆盖的平均值沿着 ET 梯度增加了一倍（0.39-0.78mm），而森林体积增加了三倍（2.50-8.12mm）。森林覆盖面积越大，社区内的森林覆盖面积就越大。与社会经济相比，城市形态对住宅地块森林结构的同质化影响更大。气候和城市形态变量最能预测住宅森林结构，而社会经济变量的预测能力最低。结果表明，气候可以区分住宅宏观系统中的森林结构，并可能在城市范围内抵消城市形态和社会经济驱动因素的同质化效应。这与最近的实证研究结果相呼应，这些研究结果表明，存在复杂的多尺度机制，可以调节城市之间的生态同质化和生态系统趋同。该研究首次对整个城市宏观系统的森林结构进行了高分辨率评估，并为亚大陆尺度城市植被的生态和水文意义研究开辟了新的道路。
