Intensifier of urban economic resilience: Specialized or diversified agglomeration?
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ABSTRACT:
SUBMITTER: Zhang M
PROVIDER: S-EPMC8629248 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Many countries promote urban agglomeration to enhance economic competitiveness, but the impacts of this strategy on local climate adaptation remain poorly understood. Here, we use variation in greenspaces to test the effectiveness of climate adaptation policy across climate impacts and vulnerability dimensions. Using satellite imagery and logistic regression, we analyze spatiotemporal correlation between greenspace and climate vulnerability in the Guangdong-Hong Kong-Macau Greater Bay Area, an area comprising ~ 70 million people and 11 cities, making it a useful natural experiment for our study. We find that while greenspace increases proportionally with climate exposure and sensitivity, many cities exhibit discrepancies between greenspace variation and climate vulnerability. Green adaptation funnels into wealthier, less vulnerable areas while bypassing more vulnerable ones, increasing their climate vulnerability and undermining the benefits of urban agglomeration. The results suggest that centrally-planned climate adaptation policy must accommodate local heterogeneity to improve urban sustainability. By neglecting local heterogeneity, urban agglomeration policy risks exacerbating spatial inequalities in climate adaptation.
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Project description:The urban community faces a significant obstacle in effectively utilising Earth Observation (EO) intelligence, particularly the Copernicus EO program of the European Union, to address the multifaceted aspects of urban sustainability and bolster urban resilience in the face of climate change challenges. In this context, here we present the efforts of the CURE project, which received funding under the European Union's Horizon 2020 Research and Innovation Framework Programme, to leverage the Copernicus Core Services (CCS) in supporting urban resilience. CURE provides spatially disaggregated environmental intelligence at a local scale, demonstrating that CCS can facilitate urban planning and management strategies to improve the resilience of cities. With a strong emphasis on stakeholder engagement, CURE has identified eleven cross-cutting applications between CCS that correspond to the major dimensions of urban sustainability and align with user needs. These applications have been integrated into a cloud-based platform known as DIAS (Data and Information Access Services), which is capable of delivering reliable, usable and relevant intelligence to support the development of downstream services towards enhancing resilience planning of cities throughout Europe.
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Project description:Abstract Aim Urbanization exposes species to novel ecological conditions. Some species thrive in urban areas, whereas many others are excluded from these human‐made environments. Previous analyses suggest that the ability to cope with rapid environmental change is associated with long‐term patterns of diversification, but whether the suite of traits associated with the ability to colonize urban environments is linked to this process remains poorly understood. Location World. Time period Current. Major taxa studied Passerine birds. Methods We applied macroevolutionary models to a large dataset of passerine birds to compare the evolutionary history of urban‐tolerant species with that of urban‐avoidant species. Specifically, we examined models of state‐dependent speciation and extinction to assess the macroevolution of urban tolerance as a binary trait, in addition to models of quantitative trait‐dependent diversification based on relative urban abundance. We also ran simulation‐based model assessments to explore potential sources of bias. Results We provide evidence that historically, species with traits promoting urban colonization have undergone faster diversification than urban‐avoidant species, indicating that urbanization favours clades with a historical tendency towards rapid speciation or reduced extinction. In addition, we find that past transitions towards states that currently impede urban colonization by passerines have been more frequent than in the opposite direction. Furthermore, we find a portion of urban‐avoidant passerines to be recent and to undergo fast diversification. All highly supported models give this result consistently. Main conclusions Urbanization is mainly associated with the loss of lineages that are inherently more vulnerable to extinction over deep time, whereas cities tend to be colonized by less vulnerable lineages, for which urbanization might be neutral or positive in terms of longer‐term diversification. Urban avoidance is associated with high rates of recent diversification for some clades occurring in regions with relatively intact natural ecosystems and low current levels of urbanization.
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Project description:With the advancement of society and the economy, environmental problems have increasingly emerged, in particular, problems with urban CO2 emissions. Exploring the driving forces of urban CO2 emissions is necessary to gain a better understanding of the spatial patterns, processes, and mechanisms of environmental problems. Thus, the purpose of this study was to quantify the driving forces of urban CO2 emissions from 2000 to 2015 in China, including explicit consideration of a comparative analysis between national and urban agglomeration levels. Urban CO2 emissions with a 1-km spatial resolution were extracted for built-up areas based on the anthropogenic carbon dioxide (ODIAC) fossil fuel emission dataset. Six factors, namely precipitation, slope, temperature, population density, normalized difference vegetation index (NDVI), and gross domestic product (GDP), were selected to investigate the driving forces of urban CO2 emissions in China. Then, a probit model was applied to examine the effects of potential factors on urban CO2 emissions. The results revealed that the population, GDP, and NDVI were all positive driving forces, but that temperature and precipitation had negative effects on urban CO2 emissions at the national level. In the middle and south Liaoning urban agglomeration (MSL), the slope, population density, NDVI, and GDP were significant influencing factors. In the Pearl River Delta urban agglomeration (PRD), six factors had significant impacts on urban CO2 emissions, all of which were positive except for slope, which was a negative factor. Due to China's hierarchical administrative levels, the model results suggest that regardless of which level is adopted, the impacts of the driving factors on urban CO2 emissions are quite different at the national compared to the urban agglomeration level. The degrees of influence of most factors at the national level were lower than those of factors at the urban agglomeration level. Based on an analysis of the forces driving urban CO2 emissions, we propose that it is necessary that the environment play a guiding role while regions formulate policies which are suitable for emission reductions according to their distinct characteristics.
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