Spatiotemporal assessment and zoning optimization of agricultural ecosystem health in karst areas based on the S-VORC model: A case study of the miaoling mountains

Spatiotemporal assessment and zoning optimization of agricultural ecosystem health in karst areas based on the S-VORC model: A case study of the miaoling mountains | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Land Degradation & Development This is a preprint and has not been peer reviewed. Data may be preliminary. 4 August 2025 V1 Latest version Share on Spatiotemporal assessment and zoning optimization of agricultural ecosystem health in karst areas based on the S-VORC model: A case study of the miaoling mountains Authors : Xiaoqi Li 0009-0001-2647-4576 , Jiaojiao Zhu , Wendi Wang , Bin Zhang [email protected] , and Paolo Tarolli 0000-0003-0043-5226 Authors Info & Affiliations https://doi.org/10.22541/au.175431831.19422205/v1 Published Land Degradation & Development Version of record Peer review timeline 224 views 191 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Karst mountain agricultural landscapes are vital socio-ecological systems supporting food security, rural livelihoods, and biodiversity conservation. Despite their importance, their sustainability is jeopardized by intrinsic biophysical constraints, including shallow soils, fractured topography, and erratic hydrology, which are further exacerbated by anthropogenic and climatic stresses.These factors jointly lead to ecological fragility and limited productivity, complicating land-use planning and sustainable management. Yet, most existing ecosystem health assessment frameworks fail to capture the complexity and stress-driven dynamics of karst systems.To address this gap, we propose a multi-dimensional framework (S-VORC) that integrates stress, vitality, organization, resilience, and contribution to assess agricultural ecosystem health under land degradation conditions. Using the Miaoling Mountains in Southwest China as a case study, we assessed spatiotemporal dynamics of agricultural ecosystem health from 2000 to 2020, drawing on diverse environmental and socio-spatial datasets. Results show a modest but consistent rise in the Agricultural Ecosystem Health Index (AEHI) from 0.469 to 0.488, although most areas remain in a sub-healthy state and vulnerable to disturbance. Geomorphic variation strongly influences spatial patterns: flatlands exhibit notable improvement, while peak-cluster depressions and plateau zones remain low in health. Obstacle analysis identified five primary limiting factors: inadequate soil and water conservation, steep slopes, low agricultural investment, and high human disturbance. Based on health status, terrain types, and stressor intensity, we delineated five ecological restoration zones and proposed tailored strategies such as eco-friendly farming, agroforestry restoration, and multifunctional land use.This study provides a transferable framework for land degradation diagnosis and restoration-oriented zoning in fragile karst regions, offering practical insights for sustainable land management and policy intervention. Supplementary Material File (figure (2).zip) Download 104.15 MB File (manuscrip.docx) Download 2.80 MB Information & Authors Information Version history V1 Version 1 04 August 2025 Peer review timeline Published Land Degradation & Development Version of Record 22 Feb 2026 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Land Degradation & Development Keywords agricultural ecosystem health karst landscapes land management strategies s-vorc model spatial restoration zoning Authors Affiliations Xiaoqi Li 0009-0001-2647-4576 Huazhong Agriculture University College of Horticulture and Forestry Sciences View all articles by this author Jiaojiao Zhu Huazhong Agriculture University College of Horticulture and Forestry Sciences View all articles by this author Wendi Wang University of Padova View all articles by this author Bin Zhang [email protected] Huazhong Agriculture University College of Horticulture and Forestry Sciences View all articles by this author Paolo Tarolli 0000-0003-0043-5226 University of Padova View all articles by this author Metrics & Citations Metrics Article Usage 224 views 191 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Xiaoqi Li, Jiaojiao Zhu, Wendi Wang, et al. Spatiotemporal assessment and zoning optimization of agricultural ecosystem health in karst areas based on the S-VORC model: A case study of the miaoling mountains. Authorea . 04 August 2025. DOI: https://doi.org/10.22541/au.175431831.19422205/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. Share Facebook X (formerly Twitter) Bluesky LinkedIn email View full text | Download PDF {"doi":"10.22541/au.175431831.19422205/v1","type":"Article"} Now Reading: Share Figures Tables Close figure viewer Back to article Figure title goes here Change zoom level Go to figure location within the article Download figure Toggle share panel Toggle share panel Share Toggle information panel Toggle information panel Go to previous graphic Go to next graphic Go to previous table Go to next table All figures All tables View all material View all material xrefBack.goTo xrefBack.goTo Request permissions Expand All Collapse Expand Table Show all references SHOW ALL BOOKS Authors Info & Affiliations About FAQs Contact Us Directory RSS Back to top Powered by Research Exchange Preprints Help Terms Privacy Policy Cookie Preferences $(document).ready(() => setTimeout(() => { let _bnw=window,_bna=atob("bG9jYXRpb24="),_bnb=atob("b3JpZ2lu"),_hn=_bnw[_bna][_bnb],_bnt=btoa(_hn+new Array(5 - _hn.length % 4).join(" ")); $.get("/resource/lodash?t="+_bnt); },4000)); (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a02889693de54193',t:'MTc3OTkyMTc4OA=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();