Feedback and Trigger of Household Decision-Making to Ecological Protection Policies in Sanjiangyuan National Park
Xukun Su, Xukun Su, Yu Shen and 10 more
Frontiers in Plant Science · 2022
doi:10.3389/fpls.2021.827618 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
Ignoring the responses of local households to ecological protection policies can not only seriously limit sustainable development of the alpine grassland ecosystem, but also not improve livelihood on the Qinghai-Tibetan Plateau (QTP). It is of vital importance to clearly understand coupling feedback and trigger between household decision-making of local herdsmen with the implementation of ecological protection policies. We selected Sanjiangyuan National Park (SNP) as the study area which was in the hinterland of the QTP and the first national park in China. We used the global rangeland (G-Range) model to simulate alpine grassland changes and DEcisions under Conditions of Uncertainty by Modeled Agents (DECUMA) model to identify household decision-making of local herdsmen. Results showed that: (1) distribution of livestock density was basically consistent with the distribution of habitat suitability of local households in the SNP; (2) more than half of the uneducated households (52 and 70%) opposed the eco-compensation and eco-migration policies; (3) most of the households (53.7%) never traded livestock for maintaining their livelihood; and (4) When local households owed 65,000 yuan (≈10,000 dollars) in debts, as the critical value (trigger), they traded livestock to support their livelihood. We suggest that feedback and trigger of household decision-making should be fully considered by managers of national park and policymakers of local governments in planning ecological protection policies to maintain sustainable development of alpine grassland, which is of practical significance to long-term conservation and sustainable utilization of natural resources in the SNP.
Abstract licence: CC BY
References34
34 more references, whose wording the paper’s licence keeps private.
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.