Spatial–Temporal Changes and Driving Factor Analysis of Net Ecosystem Productivity in Heilongjiang Province from 2010 to 2020

Hui Zhang, Zhenghong He (), Liwen Zhang, Rong Cong and Wantong Wei
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Hui Zhang: School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China
Zhenghong He: Xinjiang Water Conservancy and Hydropower Survey Design Institute Co., Ltd., Urumqi 830000, China
Liwen Zhang: School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China
Rong Cong: Security Management Department, Inner Mongolia University for Nationalities, Tongliao 028000, China
Wantong Wei: School of Public Administration and Law, Northeast Agricultural University, Harbin 150030, China

Land, 2024, vol. 13, issue 8, 1-16

Abstract: Net ecosystem productivity (NEP) is an important indicator for the quantitative evaluation of carbon sources/sinks in terrestrial ecosystems. An improved CASA model and soil respiration model, combined with MODIS and meteorological data, are utilized to estimate vegetation NEP from 2010 to 2020. A Theil–Sen trend analysis, a Mann–Kendall test, the Hurst index, and geographical detector methods were employed to analyze the spatiotemporal variations in NEP in Heilongjiang Province and its driving factors. The results show the following: (1) The overall NEP in Heilongjiang Province exhibited a fluctuating upward trend from 2010 to 2020, with a growth rate of 4.74 g C·m −2 ·yr −1 , and an average annual NEP of 404 g C·m −2 ·yr −1 . Spatially, NEP exhibits a distribution pattern of “low from east to west to high from north to south in the central region”, with 99.27% of the area being a carbon sink. (2) Significant regional differences were observed in the spatial trend of NEP changes, with 78.39% of regions showing increasing trends and 17.53% showing decreasing trends. Future NEP changes are expected to continue, with regions showing a persistent increase (58.44%), potential decrease (19.95%), potential increase (5.65%), and persistent decrease (11.88%). (3) The geographical detector results indicate that altitude is the dominant factor affecting NEP, followed by slope, temperature, population density, etc. The interaction-detector results show that the interaction between each factor shows an increasing trend, and the interaction between any two factors is higher than that of a single factor. The research results can provide scientific references for reducing emissions, increasing sinks, and protecting ecosystems in Heilongjiang Province.

Keywords: net ecosystem productivity (NEP); CASA model; driving factors; geographical detector; Heilongjiang Province (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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