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Spatial multi-scale relationships of ecosystem services: A case study using a geostatistical methodology
Adequately understanding the spatial multi-scale relationships of ecosystem services (ES) is an important step for environmental management decision-making. Here, we used spatially explicit methods to estimate five critical ES (nitrogen and phosphorous purifications, crop production, water supply an...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573410/ https://www.ncbi.nlm.nih.gov/pubmed/28842616 http://dx.doi.org/10.1038/s41598-017-09863-1 |
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author | Liu, Yang Bi, Jun Lv, Jianshu Ma, Zongwei Wang, Ce |
author_facet | Liu, Yang Bi, Jun Lv, Jianshu Ma, Zongwei Wang, Ce |
author_sort | Liu, Yang |
collection | PubMed |
description | Adequately understanding the spatial multi-scale relationships of ecosystem services (ES) is an important step for environmental management decision-making. Here, we used spatially explicit methods to estimate five critical ES (nitrogen and phosphorous purifications, crop production, water supply and soil retention) related to non-point source (NPS) pollution in the Taihu Basin region of eastern China. Then a factorial kriging analysis and stepwise multiple regression were performed to identify the spatial multi-scale relationships of ES and their dominant factors at each scale. The spatial variations in ES were characterized at the 12 km and 83 km scales and the result indicated that the relationships of these services were scale dependent. It was inferred that at the 12 km scale, ES were controlled by anthropogenic activities and their relationships were dependent on socio-economic factors. At the 83 km scale, we suggested that ES were primarily dominated by the physical environment. Moreover, the policy implications of ES relationships and their dominant factors were discussed for the multi-level governance of NPS pollution. Overall, this study presents an optimized approach to identifying ES relationships at multiple spatial scales and illustrates how appropriate information can help guide water management. |
format | Online Article Text |
id | pubmed-5573410 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-55734102017-09-01 Spatial multi-scale relationships of ecosystem services: A case study using a geostatistical methodology Liu, Yang Bi, Jun Lv, Jianshu Ma, Zongwei Wang, Ce Sci Rep Article Adequately understanding the spatial multi-scale relationships of ecosystem services (ES) is an important step for environmental management decision-making. Here, we used spatially explicit methods to estimate five critical ES (nitrogen and phosphorous purifications, crop production, water supply and soil retention) related to non-point source (NPS) pollution in the Taihu Basin region of eastern China. Then a factorial kriging analysis and stepwise multiple regression were performed to identify the spatial multi-scale relationships of ES and their dominant factors at each scale. The spatial variations in ES were characterized at the 12 km and 83 km scales and the result indicated that the relationships of these services were scale dependent. It was inferred that at the 12 km scale, ES were controlled by anthropogenic activities and their relationships were dependent on socio-economic factors. At the 83 km scale, we suggested that ES were primarily dominated by the physical environment. Moreover, the policy implications of ES relationships and their dominant factors were discussed for the multi-level governance of NPS pollution. Overall, this study presents an optimized approach to identifying ES relationships at multiple spatial scales and illustrates how appropriate information can help guide water management. Nature Publishing Group UK 2017-08-25 /pmc/articles/PMC5573410/ /pubmed/28842616 http://dx.doi.org/10.1038/s41598-017-09863-1 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Liu, Yang Bi, Jun Lv, Jianshu Ma, Zongwei Wang, Ce Spatial multi-scale relationships of ecosystem services: A case study using a geostatistical methodology |
title | Spatial multi-scale relationships of ecosystem services: A case study using a geostatistical methodology |
title_full | Spatial multi-scale relationships of ecosystem services: A case study using a geostatistical methodology |
title_fullStr | Spatial multi-scale relationships of ecosystem services: A case study using a geostatistical methodology |
title_full_unstemmed | Spatial multi-scale relationships of ecosystem services: A case study using a geostatistical methodology |
title_short | Spatial multi-scale relationships of ecosystem services: A case study using a geostatistical methodology |
title_sort | spatial multi-scale relationships of ecosystem services: a case study using a geostatistical methodology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573410/ https://www.ncbi.nlm.nih.gov/pubmed/28842616 http://dx.doi.org/10.1038/s41598-017-09863-1 |
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