Performance of multiscale landscape metrics as indicators of soil C, N, P, and physicochemical properties of NFV in ML reaches of Yellow River Basin, China
{"title":"Performance of multiscale landscape metrics as indicators of soil C, N, P, and physicochemical properties of NFV in ML reaches of Yellow River Basin, China","authors":"Chenhui Wei, Kaili Chen, Zhan Yang, Siqi Yao, Chen He, Lin Zhang","doi":"10.1016/j.ecolind.2025.113391","DOIUrl":null,"url":null,"abstract":"<div><div>Landscape metrics are significant indicators of ecological functions. However, limited data are available regarding the relationship between landscape metrics and soil ecological functions. In this study, using 99 National Forest Villages (NFVs) in the middle and lower reaches of the Yellow River Basin as study objects, landscape metrics were computed for circular areas of ten extents in FRAGSTATS. Differences in soil carbon (C), nitrogen (N), phosphorus (P), physicochemical properties, and landscape metrics between the middle and lower reaches were compared using a one-way ANOVA. Multiscale performance of 14 forest landscape metrics as indicators of 10 soil parameters was explored using several methods: partial correlation, linear mixed model, linear mixed-effects model, and threshold model. The results showed that NFVs in the middle reaches had higher soil C and N and better physicochemical properties, but lower soil P than the lower reaches. The landscape pattern showed large variations between the middle and lower reaches. Soil C and N were positively correlated with patch number and shape metrics, respectively, before the threshold. Soil P and physicochemical properties were negatively correlated with forest area metrics before and after the threshold. The correlation between landscape metrics and soil parameters depended on kilometer scale. Our findings highlight that soil characteristics and forest landscape patterns of National Forest Villages are linked, and landscape regulation can improve forest soil C and N, as well as the physicochemical properties. The insights from this study are vital for informing land management decisions aimed at enhancing carbon sequestration, mitigating climate change, and maintaining soil fertility. Ultimately, this research provides a reference for other river basins and landscapes, and future research should consider human activities at larger kilometer scales to predict soil properties.</div></div>","PeriodicalId":11459,"journal":{"name":"Ecological Indicators","volume":"173 ","pages":"Article 113391"},"PeriodicalIF":7.0000,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Indicators","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1470160X25003218","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Landscape metrics are significant indicators of ecological functions. However, limited data are available regarding the relationship between landscape metrics and soil ecological functions. In this study, using 99 National Forest Villages (NFVs) in the middle and lower reaches of the Yellow River Basin as study objects, landscape metrics were computed for circular areas of ten extents in FRAGSTATS. Differences in soil carbon (C), nitrogen (N), phosphorus (P), physicochemical properties, and landscape metrics between the middle and lower reaches were compared using a one-way ANOVA. Multiscale performance of 14 forest landscape metrics as indicators of 10 soil parameters was explored using several methods: partial correlation, linear mixed model, linear mixed-effects model, and threshold model. The results showed that NFVs in the middle reaches had higher soil C and N and better physicochemical properties, but lower soil P than the lower reaches. The landscape pattern showed large variations between the middle and lower reaches. Soil C and N were positively correlated with patch number and shape metrics, respectively, before the threshold. Soil P and physicochemical properties were negatively correlated with forest area metrics before and after the threshold. The correlation between landscape metrics and soil parameters depended on kilometer scale. Our findings highlight that soil characteristics and forest landscape patterns of National Forest Villages are linked, and landscape regulation can improve forest soil C and N, as well as the physicochemical properties. The insights from this study are vital for informing land management decisions aimed at enhancing carbon sequestration, mitigating climate change, and maintaining soil fertility. Ultimately, this research provides a reference for other river basins and landscapes, and future research should consider human activities at larger kilometer scales to predict soil properties.
期刊介绍:
The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published.
• All aspects of ecological and environmental indicators and indices.
• New indicators, and new approaches and methods for indicator development, testing and use.
• Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources.
• Analysis and research of resource, system- and scale-specific indicators.
• Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs.
• How research indicators can be transformed into direct application for management purposes.
• Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators.
• Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.