Temporal consistency between gross primary production and solar-induced chlorophyll fluorescence in the ten most populous megacity areas over years

Abstract

The gross primary production (GPP) of vegetation in urban areas plays an important role in the study of urban ecology. It is difficult however, to accurately estimate GPP in urban areas, mostly due to the complexity of impervious land surfaces, buildings, vegetation, and management. Recently, we used the Vegetation Photosynthesis Model (VPM), climate data, and satellite images to estimate the GPP of terrestrial ecosystems including urban areas. Here, we report VPM-based GPP (GPP_vpm) estimates for the world's ten most populous megacities during 2000-2014. The seasonal dynamics of GPP_vpm during 2007-2014 in the ten megacities track well that of the solar-induced chlorophyll fluorescence (SIF) data from GOME-2 at 0.5° × 0.5° resolution. Annual GPP_vpm during 2000-2014 also shows substantial variation among the ten megacities, and year-to-year trends show increases, no change, and decreases. Urban expansion and vegetation collectively impact GPP variations in these megacities. The results of this study demonstrate the potential of a satellite-based vegetation photosynthesis model for diagnostic studies of GPP and the terrestrial carbon cycle in urban areas.

Figure 1

The geographic distributions of the ten most populous megacities in the world: Tokyo (Japan), Osaka (Japan), Beijing (China), Shanghai (China), Delhi (India), Mumbai (India), São Paulo (Brazil), Mexico City (Mexico), Cairo (Egypt), and New York–Newark (USA). These megacities are within two to nine gridcells of 0.5° (latitude/longitude) spatial resolution. These ten cities comprise a total of 40 gridcells. The numbers within individual urban gridcells (red frames) represent the urban area percentage (%) within a gridcell, derived from the land cover map used in the GPP_mod17 data product^,. The color within the urban gridcells indicate the annual GPP in 2000. Map was generated using ArcGIS 10.1 software (http://www.esri.com/arcgis/about-arcgis).

Figure 2

Seasonal dynamics and interannual variation of GOME-2 SIF, GPP_vpm, and GPP_mod17 for the ten megacities during 2007–2014. The light gray bar represents GOME-2 SIF; the orange line represents GPP_vpm; and the blue line represents GPP_mod17.

Figure 3

Scatterplots of monthly GPP_vpm and GPP_mod17 versus SIF in the world’s top ten megacities during 2007–2014. Orange dots and fit-lines represent the relationship between SIF and GPP_vpm. Blue dots and fit-lines represent the relationship between SIF and GPP_mod17. The results of each analysis are statistically significant (n = 96, p < 0.001).

Figure 4

Interannual variations of annual GPP (blue), daily maximum GPP (GPP_max, orange), and carbon uptake period (CUP, grey) in the world’s top ten megacities from 2000 to 2014. GPP_max is the maximum daily GPP in a year; CUP is defined as the number of days with GPP >= 1.0 gC m⁻² day⁻¹ in a year^,; and GPP_max is estimated by the Savitzky-Golay fitting method.

Figure 5

Interannual variations of annual GPP (blue) and Enhanced Vegetation Index (EVI) (orange) in the ten megacities from 2000 to 2014. EVI is the mean EVI within a plant growing period (from April to October or from January to December).

Figure 6

Interannual variation of annual gross primary production (TgC year⁻¹) in the ten largest megacities from 2000 to 2014.

Figure 7

The quantitative relationships between annual GPP trend and GPP_max, CUP, EVI, population, and nighttime lights trends during 2000–2014 as well as urban area percentage in 2000 (which represented the initial condition for this urban analysis).