Improving Traditional Metrics: A Hybrid Framework for Assessing the Ecological Carrying Capacity of Mountainous Regions

Rui Luo, Jiwei Leng, Daming He (), Yanbo Li (), Kai Ma, Ziyue Xu, Kaiwen Zhang and Yun Luo
Additional contact information
Rui Luo: Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China
Jiwei Leng: Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China
Daming He: Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China
Yanbo Li: Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China
Kai Ma: Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China
Ziyue Xu: Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China
Kaiwen Zhang: Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China
Yun Luo: Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China

Land, 2025, vol. 14, issue 3, 1-20

Abstract: Ecological carrying capacity (ECC) is a crucial indicator for assessing sustainable development capabilities. However, mountain ecosystems possess unique complexities due to their diverse topography, high biodiversity, and fragile ecological environments. Addressing the current shortcomings in mountain ECC assessments, this paper proposes a novel hybrid evaluation framework that integrates improved ecological footprint (EF) and ecosystem service value (ESV) approaches with spatial econometric models. This framework allows for a more comprehensive understanding of the dynamic changes and driving factors of the mountain ecological carrying capacity index (ECCI), using Pingbian County as a case study. The results indicate the following: (1) Land use changes and biodiversity exert varying impacts on the ECCI across different regions. The ECCI decreased by 42% from 2003 to 2021 (from 4.41 to 2.54), exhibiting significant spatial autocorrelation and heterogeneity. (2) The ecological service value coefficient is the main factor increasing the ECCI, while the energy consumption value and per capita consumption value inhibited the increase in the ECCI. For every 1% increase in the ecosystem service value coefficient, the ECCI increased by 0.66%, whereas every 1% increase in energy consumption value and per capita consumption value reduced the ECCI by 0.18% and 0.28%, respectively. (3) The overall spatial distribution pattern of the ECCI is primarily “southwest to northeast”, with the distance of centroid migration expanding over time. Based on these key findings, implementing differentiated land use practices and ecological restoration measures can effectively enhance the mountain ECCI, providing scientific support for the sustainable management of mountain areas.

Keywords: comprehensive evaluation; spatial autocorrelation; driving factors; management strategies (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2073-445X/14/3/549/pdf (application/pdf)
https://www.mdpi.com/2073-445X/14/3/549/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:14:y:2025:i:3:p:549-:d:1606208

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().