Multilevel analysis of factors affecting participants’ land reconversion willingness after the Grain for Green Program
Author(s) -
Xutong Wu,
Shuai Wang,
Bojie Fu
Publication year - 2021
Publication title -
ambio
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.564
H-Index - 127
eISSN - 1654-7209
pISSN - 0044-7447
DOI - 10.1007/s13280-020-01475-w
Subject(s) - sustainability , ecosystem services , affect (linguistics) , payment , multilevel model , nonfarm payrolls , business , land use , willingness to pay , willingness to accept , environmental resource management , ecosystem , natural resource economics , economics , geography , agriculture , psychology , ecology , communication , finance , archaeology , machine learning , computer science , microeconomics , biology
Understanding the postprogram land use plans of participants is necessary for the sustainability of the conservation achievements from payments for ecosystem services (PES) programs. Previous studies have analyzed many individual factors affecting participants' reconversion plans after PES programs. However, whether the regional ecosystem services changes caused by PES programs affect reconversion willingness remains elusive. Here, we used the multilevel linear model to determine the effects of regional ecosystem services changes and individual characteristics on participants' land reconversion willingness after the Grain for Green Program (GFGP) in the Yanhe watershed of the Loess Plateau. We found that household income, ecological awareness, and employment changes negatively affected reconversion willingness, while nonfarm employment positively affected it at the individual level. At the regional level, the grain production and water yield changes could influence the reconversion willingness of respondents with different individual characteristics. With improved understanding of the factors affecting reconversion willingness, several suggestions to improve the sustainability of the GFGP were proposed. Our study provides a template for analyzing the multilevel factors that affect the sustainability of other PES programs.
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