Affiliation:
1. School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Abstract
Net primary productivity (NPP) is an important index with which to evaluate the safety and quality of regional carbon sinks. Based on the improved CASA model, climate data, social data, remote-sensing ecological data, and other multi-source data types, this article took a Chinese city, Yangzhou, as the research object, used Theil–Sen medium-trend analysis and the Hurst index to analyze its spatial–temporal-evolution characteristics and future change trends, and used geographical detectors to analyze the impact of climate, social, ecological, and other factors on the change in NPP in the study area, with the intention of providing a theoretical exploration and practical basis for achieving the “dual carbon” goals in the region. The results showed that the annual average NPP levels of the vegetation in Yangzhou in the five sampling years were 445.343 gc/m2·a, 447.788 gc/m2·a, 427.763 gc/m2·a, 398.687 gc/m2·a, and 420.168 gc/m2·a, respectively, exhibiting a trend that first decreases and then increases, with a slight overall decrease from 2000 to 2020. The area in which the vegetation in Yangzhou had the higher grades of NPP increased by 203,874 km², and an increase of 321,769 km² in the lower levels was observed. The NPP level of vegetation showed polarization, with relatively high levels in the surrounding farmland and mountain–forest areas and relatively low levels in densely populated urban areas. The ranking was highest in Baoying and lowest in Gaoyou. From the average NPP of all the land types in the study area, the following trend was exhibited: forest land > farmland > bare soil > impermeable surface > water. The future change in vegetation NPP in Yangzhou City will mainly follow the trend of the past 20 years, with a slow decrease. The NDVI (q = 0.728) and LUCC (q = 0.5601) were the leading driving factors of vegetation NPP change in Yangzhou City, and the interaction effect of double driving factors was greater than that of single driving factors.
Funder
National Key R&D Plan of China, Rural Ecological Landscape Creation Model
aforementioned fund
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
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