Abstract
The global urbanization rate is accelerating; however, data limitations have far prevented robust estimations of either global urban expansion or its effects on terrestrial net primary productivity (NPP). Here, using a high resolution dataset of global land use/cover (GlobeLand30), we show that global urban areas expanded by an average of 5694 km2 per year between 2000 and 2010. The rapid urban expansion in the past decade has in turn reduced global terrestrial NPP, with a net loss of 22.4 Tg Carbon per year (Tg C year−1). Although small compared to total terrestrial NPP and fossil fuel carbon emissions worldwide, the urbanization-induced decrease in NPP offset 30% of the climate-driven increase (73.6 Tg C year−1) over the same period. Our findings highlight the urgent need for global strategies to address urban expansion, enhance natural carbon sinks, and increase agricultural productivity.
Highlights
The global urbanization rate is accelerating; data limitations have far prevented robust estimations of either global urban expansion or its effects on terrestrial net primary productivity (NPP)
We found that global urban expansion remarkably reduced the terrestrial NPP over the period 2000–2010 (22.4 Tg C year−1), which offset 30% of the climate-variability-driven NPP increase
We found that global urban lands expanded much faster than expected between 2000 and 201022
Summary
The global urbanization rate is accelerating; data limitations have far prevented robust estimations of either global urban expansion or its effects on terrestrial net primary productivity (NPP). As one of the important components of human-associated disturbance, urban land expansion and its effects on terrestrial NPP have been widely examined using a case-based approach[9,10,11,12]. These interactions cannot be accurately estimated at a global scale due to the lack of reliable global land-use data with a high spatiotemporal resolution[13,14]. We estimated global terrestrial NPP using the Moderate Resolution Imaging Spectrometer (MODIS) NPP dataset (MOD17A3), the Carnegie–Ames–Stanford Approach (CASA)[19,20] and one of the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-Hydrology)[21]. In doing so we provide a comprehensive assessment of urbanization-induced NPP change in comparison with climate-variability-driven change
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