WeChat Mini Program
Old Version Features

    • Study on Methodology of Assessing Synergy Between Conservation and Development of Karst Protected Area in the Case of the Diehong Bridge Scenic Area of Jiuxiang Gorge Cave Geopark, Yunnan, China

    Li Yuhui,Li Maocheng,Ding Zhiqiang

    Environment Development and Sustainability（2021）

    Yunnan Normal University

    Cited 4|Views3
    Abstract
    The synergy between conservation and development of the protected area is involved in stakeholders’ trade-off for the future of the protected area. The paper designed the methodology of assessing the synergy featuring three groups of attributes’ index, being naturalness index, functionality one and territoriality one, respectively, and was practiced in the Diehong Bridge Scenic Area (DBSA) of the Jiuxiang Gorge Cave Geopark of Yunnan Province(China). The DBSA is characteristic of the integration of surficial landscapes with underground ones as well as Yi nationality culture and is of significance in karst geomorphology and regional resource environment. The DBSA’s naturalness index of 7.30 revealed it was mainly composed of the secondary landscapes. Its functionality index of 7.58 implied that it was a developing scenic area in contribution to regional development and nature conservation. And its territoriality index of 6.8 demonstrated that its industry was at transitional phase in contribution to communities and residents’ well being. The assessed results gave new directions for improving the DBSA’s management that is naturalizing the managed landscapes focusing on secondary vegetation, and perfecting industry structure of tourist six elements especially in local characteristic products and local service, improving local residents’ participation in both management and products development of local cultural and special product resources.
    More
    Translated text
    Key words
    Karst protected area,Geoheritages,Sustainable development,Residents,Well being
    上传PDF
    View via Publisher
    Bibtex
    收藏
    AI Read Science
    AI Summary
    AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
    Example
    Background
    Key content
    Introduction
    Methods
    Results
    Related work
    Fund
    Key content
    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
    • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
    Upload PDF to Generate Summary
    Must-Reading Tree
    Example
    Generate MRT to find the research sequence of this paper
    Data Disclaimer
    The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
    Chat Paper
    Summary is being generated by the instructions you defined