Spatial correlations between landscape patterns and net primary productivity: A case study of the Shule River Basin, China

Human activities and environmental degradation have resulted in landscape pattern changes and can eventually profoundly affect net primary productivity (NPP) at different scales worldwide. A comprehensive understanding of how the relationship between landscape patterns (composition and configuration...

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Autores principales:	Yanyan Zhou, Dongxia Yue, Jianjun Guo, Guanguang Chen, Dong Wang
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Net primary productivity Landscape metrics Scale effect Spatial correlation Shule River Basin Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/83be242cecb3442a823e7d849369b5f1
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spelling	oai:doaj.org-article:83be242cecb3442a823e7d849369b5f12021-12-01T04:58:45ZSpatial correlations between landscape patterns and net primary productivity: A case study of the Shule River Basin, China1470-160X10.1016/j.ecolind.2021.108067https://doaj.org/article/83be242cecb3442a823e7d849369b5f12021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21007329https://doaj.org/toc/1470-160XHuman activities and environmental degradation have resulted in landscape pattern changes and can eventually profoundly affect net primary productivity (NPP) at different scales worldwide. A comprehensive understanding of how the relationship between landscape patterns (composition and configuration) and NPP changes across scales, is helpful for landscape planning and ecological protection and restoration. However, relevant research is currently understudied. Therefore, this study selected 39 landscape metrics and 5 types of land use in the Shule River Basin (SRB), and analysed their correlation under eight different scales via multiple linear regression models, aiming to determine the core landscape metrics to assess the NPP. Results indicate obvious spatial variations in the landscape metrics. At the same time, NPP in SRB was relatively small and showed obvious spatial heterogeneity. Landscape metrics and NPP showed different degrees of positive or negative correlation at different grid scales, and there were higher correlation at the 30 km scale. The increase in patch fragmentation and diversity promoted an increase in NPP. The correlation between landscape metrics and NPP was higher and more significant at the class level than at the landscape level, except in the case of unused land. Configuration metric (patch density and patch richness) explained 68% of the variation in NPP at the landscape level. At the class level, composition metrics (class area and percentage of landscape) played an important role in farmland, forestland, and grassland, while edge density (configuration metric) played an absolute role in the built-up land and unused land; overall, the effectiveness of the model was stronger at the class level than at the landscape level. The generated regression model allows us to quantitatively understand how to characterize changes in NPP through changes in landscape patterns. Appropriate landscape pattern and optimal scale should be considered in landscape planning and land use management to reduce the expected ecological impact.Yanyan ZhouDongxia YueJianjun GuoGuanguang ChenDong WangElsevierarticleNet primary productivityLandscape metricsScale effectSpatial correlationShule River BasinEcologyQH540-549.5ENEcological Indicators, Vol 130, Iss , Pp 108067- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Net primary productivity Landscape metrics Scale effect Spatial correlation Shule River Basin Ecology QH540-549.5
spellingShingle	Net primary productivity Landscape metrics Scale effect Spatial correlation Shule River Basin Ecology QH540-549.5 Yanyan Zhou Dongxia Yue Jianjun Guo Guanguang Chen Dong Wang Spatial correlations between landscape patterns and net primary productivity: A case study of the Shule River Basin, China
description	Human activities and environmental degradation have resulted in landscape pattern changes and can eventually profoundly affect net primary productivity (NPP) at different scales worldwide. A comprehensive understanding of how the relationship between landscape patterns (composition and configuration) and NPP changes across scales, is helpful for landscape planning and ecological protection and restoration. However, relevant research is currently understudied. Therefore, this study selected 39 landscape metrics and 5 types of land use in the Shule River Basin (SRB), and analysed their correlation under eight different scales via multiple linear regression models, aiming to determine the core landscape metrics to assess the NPP. Results indicate obvious spatial variations in the landscape metrics. At the same time, NPP in SRB was relatively small and showed obvious spatial heterogeneity. Landscape metrics and NPP showed different degrees of positive or negative correlation at different grid scales, and there were higher correlation at the 30 km scale. The increase in patch fragmentation and diversity promoted an increase in NPP. The correlation between landscape metrics and NPP was higher and more significant at the class level than at the landscape level, except in the case of unused land. Configuration metric (patch density and patch richness) explained 68% of the variation in NPP at the landscape level. At the class level, composition metrics (class area and percentage of landscape) played an important role in farmland, forestland, and grassland, while edge density (configuration metric) played an absolute role in the built-up land and unused land; overall, the effectiveness of the model was stronger at the class level than at the landscape level. The generated regression model allows us to quantitatively understand how to characterize changes in NPP through changes in landscape patterns. Appropriate landscape pattern and optimal scale should be considered in landscape planning and land use management to reduce the expected ecological impact.
format	article
author	Yanyan Zhou Dongxia Yue Jianjun Guo Guanguang Chen Dong Wang
author_facet	Yanyan Zhou Dongxia Yue Jianjun Guo Guanguang Chen Dong Wang
author_sort	Yanyan Zhou
title	Spatial correlations between landscape patterns and net primary productivity: A case study of the Shule River Basin, China
title_short	Spatial correlations between landscape patterns and net primary productivity: A case study of the Shule River Basin, China
title_full	Spatial correlations between landscape patterns and net primary productivity: A case study of the Shule River Basin, China
title_fullStr	Spatial correlations between landscape patterns and net primary productivity: A case study of the Shule River Basin, China
title_full_unstemmed	Spatial correlations between landscape patterns and net primary productivity: A case study of the Shule River Basin, China
title_sort	spatial correlations between landscape patterns and net primary productivity: a case study of the shule river basin, china
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/83be242cecb3442a823e7d849369b5f1
work_keys_str_mv	AT yanyanzhou spatialcorrelationsbetweenlandscapepatternsandnetprimaryproductivityacasestudyoftheshuleriverbasinchina AT dongxiayue spatialcorrelationsbetweenlandscapepatternsandnetprimaryproductivityacasestudyoftheshuleriverbasinchina AT jianjunguo spatialcorrelationsbetweenlandscapepatternsandnetprimaryproductivityacasestudyoftheshuleriverbasinchina AT guanguangchen spatialcorrelationsbetweenlandscapepatternsandnetprimaryproductivityacasestudyoftheshuleriverbasinchina AT dongwang spatialcorrelationsbetweenlandscapepatternsandnetprimaryproductivityacasestudyoftheshuleriverbasinchina
_version_	1718405612133416960

Spatial correlations between landscape patterns and net primary productivity: A case study of the Shule River Basin, China

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