Jianshu Lv

Dr. Jianshu Lv

1. College of Geography and Environment, Shandong Normal University, Jinan 250014, China;
+1

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2013 in Journal of Hazardous Materials
Verified
Journal Article
Closed access
JLJianshu Lv
Jianshu Lv
YLYang Liu
Yang Liu
ZZZulu Zhang
Zulu Zhang
JDJierui Dai
Jierui Dai

29 July 2014 in Journal of Soils and Sediments
Verified
Journal Article
Closed access
PDF file
JLJianshu Lv
Jianshu Lv
YLYang Liu
Yang Liu
ZZZulu Zhang
Zulu Zhang
JDJierui Dai
Jierui Dai
BDBin Dai
Bin Dai
YZYuchi Zhu
Yuchi Zhu

1 January 2019 in Science of The Total Environment
Verified
Journal Article
Closed access
JLJianshu Lv
Jianshu Lv
YLYang Liu
Yang Liu

1 March 2020 in Chemosphere
Verified
Journal Article
Closed access
YWYameng Wang
Yameng Wang
LZLixia Zhang
Lixia Zhang
JWJining Wang
Jining Wang
JLJianshu Lv
Jianshu Lv

25 August 2017 in Scientific Reports
Verified
Journal Article
Open access
PDF file
YLYang Liu
Yang Liu
JBJun Bi
Jun Bi
JLJianshu Lv
Jianshu Lv
Zongwei MaZongwei Ma
Zongwei Ma
CWCe Wang
Ce Wang
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.