Effects of urbanization on productivity of terrestrial ecological systems based on linear fitting: a case study in Jiangsu, eastern China

Abstract

The terrestrial ecosystem productivity and foundation of regional ecosystem services have been significantly influenced by recent urbanization processes. This study assesses the changes in terrestrial ecosystem productivity in Jiangsu from the years of 2000 to 2015 in response to the urbanization. A linear model that incorporates the traditional equalization method is proposed to improve the estimation accuracy of net primary productivity (NPP) loss. Results revealed that the land area of urban construction expanded rapidly during the research period to encompass an area of 8672.8 km2. The rate of expansion was highest during 2005–2010. Additionally, the expansion rate of urban construction land was considerably higher in southern Jiangsu compared to the northern areas. The NPP exhibited a rising tendency from the year of 2000 to 2015, and varied from 33.30 to 40.23 Tg C/y. It was higher in the central parts, which include the cities of Yancheng and Nantong. The increase in urban construction land has resulted in a significant reduction in the terrestrial ecosystem productivity, i.e. a cumulative NPP loss of 2.55–2.88 Tg C during the research period. The NPP losses due to the conversion from cropland to constrction land were the highest, followed by the wetland. The work in this paper indicates that the rate of future productivity losses in terrestrial ecosystem in northern Jiangsu would be faster than the southern areas.

Responses of the Terrestrial Ecosystem Productivity to Droughts in China

“…Second, at shorter timescales, human activities play some important roles in driving NPP variations. In the developing world, the rapid urbanization has an obviously negative impact on regional NPP changes (Li et al, 2019b). Under the processes of urbanization, large amounts of farmlands, wetlands, and forests are overall replaced with poorly permeable surfaces of cement and asphalt that result in the NPP reduction.…”

Determining the dominant factors determining the variability of terrestrial ecosystem productivity in China during the last two decades

“…The NPP in China during the study period was estimated using the modified Carnegie‐Ames‐Stanford Approach (CASA) proposed by Zhu, Pan, Hao, Deyong, and Haibo (). This model is based on the following equation (Li et al, ), where NPP(x) denotes the NPP of pixel x (g C m 2 yr), APAR(x,t) denotes the photosynthetically active radiation in a month, t , in pixel, x (g C m 2 month), and ε(x, t) denotes the active light use efficiency in month t in pixel x (g C/MJ). SOL(x,t) denotes the total solar radiation in month t in pixel x (MJ m 2 month).…”

“…The NPP in China during the study period was estimated using the modified Carnegie-Ames-Stanford Approach (CASA) proposed by Zhu, Pan, Hao, Deyong, and Haibo (2006). This model is based on the following equation (Li et al, 2019),…”

“…In addition, existing results suggest that anthropogenic factors played a major role in the NPP variation across China, and these factors are expected to become more significant in the future (Mu, Zhou et al, ; Wu et al, ). Previous studies have shown that rapid urbanization in agricultural zones and densely populated zones play an important role in driving the variability of NPP (Li et al, ; Wu et al, ). For example, Mongolia of northern China, human activities and climate change are responsible for 80.23 and 19.77% of grassland NPP changes, respectively (Mu, Zhou, et al, ).…”

Monitoring for Changes in Spring Phenology at Both Temporal and Spatial Scales Based on MODIS LST Data in South Korea

“…Land use pattern can account for much of the temperature variation [28]. In particular, urbanization is increasingly having an important anthropogenic impact on climate and has significantly influenced terrestrial ecosystems [29][30][31][32]. It can modify the local climate on daily, seasonal, and annual scales [33][34][35][36].…”