Herders’ willingness to accept versus the public sector’s willingness to pay for grassland restoration in the Xilingol League of Inner Mongolia, China
Bibliographic Data
This paper describes two payment for ecosystem services (PES) programs to restore grassland ecosystems in Inner Mongolia in Northern China. A key challenge is to sustain the livelihood of local residents, who earn most of their income from traditional animal husbandry. We surveyed 240 herders and 36 government representatives in 2 years. We used contingent valuation and logistic regression to analyze the resulting data. Since the PES implementation, income from cultivation and animal grazing decreased, whereas income from compensation and off-farm activities increased. The herders preferred an annual payment of 625 Chinese yuan (CNY ) ha-1 for participating in conservation activities, but the government prefers to provide 528 CNY ha-1, resulting in an annual gap of 97 CNY ha-1. The current too-low payments may lead some herders to expand their grazing into restricted grassland or increase their number of animals, particularly if either payment program ends. The herders were most concerned about their economic loss, whereas the government considered both grassland restoration and income protection to be important. To create an improved and sustainable PES scheme, we recommend solutions that will let the herders sustain their livelihood while conserving the grasslands. Our findings will help to establish more effective PES schemes for the grasslands of Inner Mongolia and similar regions
Agricultural economics · Agriculture · Business · China · Direct Payments · Economics · Ecosystem · Ecosystem services · Geography · Government (linguistics · Grassland · Household income · Livelihood · Natural resource economics · Payment · Payment for ecosystem services · Socioeconomics · Willingness to accept · Willingness to pay · Conservation, Biodiversity, and Resource Management · Economic and Environmental Valuation · Land Use and Ecosystem Services · Ecology · Finance
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| Citations per year | 1.5 |
|---|---|
| Citation span | 2016 - 2026 (11) |
| Highly cited | No |