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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

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Front. Earth Sci.    2020, Vol. 14 Issue (1) : 124-139    https://doi.org/10.1007/s11707-019-0759-7
RESEARCH ARTICLE
Spatial patterns of net primary productivity and its driving forces: a multi-scale analysis in the transnational area of the Tumen River
Jianwen WANG1, Da ZHANG1(), Ying NAN1, Zhifeng LIU2,3, Dekang QI1
1. Department of Geography, Yanbian University, Yanji 133002, China
2. Center for Human-Environment System Sustainability (CHESS), State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
3. School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
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Abstract

Analyzing the spatial patterns of net primary productivity (NPP) and its driving forces in transnational areas provides a solid basis for understanding regional ecological processes and ecosystem services. However, the spatial patterns of NPP and its driving forces have been poorly understood on multiple scales in transnational areas. In this study, the spatial patterns of NPP in the transnational area of the Tumen River (TATR) in 2016 were simulated using the Carnegie Ames Stanford Approach (CASA) model, and its driving forces were analyzed using a stepwise multiple linear regression model. We found that the total amount of NPP in the TATR in 2016 was approximately 14.53 TgC. The amount of NPP on the Chinese side (6.23 TgC) was larger than those on the other two sides, accounting for 42.88% of the total volume of the entire region. Among different land-use and land-cover (LULC) types, the amount of NPP of the broadleaf forest was the largest (11.22 TgC), while the amount of NPP of the bare land was the smallest. The NPP per unit area was about 603.21 gC/(m2·yr) across the entire region, while the NPP per unit area on the Chinese side was the largest, followed by the Russian side and the DPRK’s side. The spatial patterns of NPP were influenced by climate, topography, soil texture, and human activities. In addition, the driving forces of the spatial patterns of NPP in the TATR had an obvious scaling effect, which was mainly caused by the spatial heterogeneity of climate, topography, soil texture, and human activities. We suggest that effective land management policies with cooperation among China, the DPRK, and Russia are needed to maintain NPP and improve environmental sustainability in the TATR.
Keywords transnational area of the Tumen River      NPP      spatial pattern      driving force      multiple scale     
Corresponding Author(s): Da ZHANG   
Just Accepted Date: 26 July 2019   Online First Date: 04 September 2019    Issue Date: 24 March 2020
 Cite this article:   
Jianwen WANG,Da ZHANG,Ying NAN, et al. Spatial patterns of net primary productivity and its driving forces: a multi-scale analysis in the transnational area of the Tumen River[J]. Front. Earth Sci., 2020, 14(1): 124-139.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-019-0759-7
https://academic.hep.com.cn/fesci/EN/Y2020/V14/I1/124
Satellite Sensor Path/Row Date
Landsat 8 OLI 114/30 12 October 2016
114/31 12 October 2016
115/30 28 May 2016
115/31 28 May 2016
  Table A1 Information on the Landsat data used in this study
LULC Maximum light use efficiency Source
Broadleaf forest 0.838 Zhu et al. (2006)
Mixed forest 0.475 Zhu et al. (2006)
Coniferous forest 0.375 Zhu et al. (2006)
Grassland 0.608 Running et al. (2000)
Dry farmland 0.604 Running et al. (2000)
Paddy field 0.604 Running et al. (2000)
Marsh 0.542 Zhu et al. (2006)
Urban land 0.389 Running et al. (2000)
Rural settlements 0.389 Running et al. (2000)
River 0.389 Running et al. (2000)
Lake 0.389 Running et al. (2000)
Bare land 0.389 Running et al. (2000)
  Table A2 Values of maximum light use efficiency
Driving forces LULC
Broadleaf forest Mixed forest Coniferous forest Grassland Dry farmland Paddy field Urban land Rural settlements
Temperature — 0.10*** — — 0.36*** — 0.54*** 0.14**
Precipitation 0.12*** — — 0.21*** -0.29*** — — —
Altitude 0.15*** — 0.18*** 0.12*** 0.21*** — — 0.24***
Slope 0.06*** — — — 0.26*** 0.24*** 0.29*** 0.31***
Aspect — -0.10** — — — — —
Soil silt content 0.17*** 0.10*** 0.10** 0.19*** 0.16*** — — 0.12**
Soil sand content 0.28*** 0.14*** — 0.39*** 0.24*** — — 0.32***
Soil clay content 0.39*** 0.11** — 0.53*** 0.09*** — — 0.19***
Distance to coastline -0.08*** — -0.26*** — -0.29*** 0.11* — -0.30***
Distance to the nearest road 0.10*** 0.14*** -0.09** — 0.10*** — — -0.11**
Population -0.03*** -0.36*** — — -0.09*** — -0.23*** -0.08*
Light intensity -0.09*** — -0.06* -0.05* — — -0.45*** -0.18***
  Table A3 The standardized partial regression coefficients of driving forces of spatial pattern of NPP in the entire region
Driving forces LULC
Broadleaf forest Mixed forest Coniferous forest Grassland Dry farmland Paddy field Urban land Rural settlements
Temperature — — — — — — — -0.22**
Precipitation — 0.12* -0.12* — — — — —
Altitude 0.14*** -0.15* 0.22*** 0.31*** 0.18*** — — 0.39***
Slope 0.05*** — — 0.21*** 0.32*** 0.36*** 0.20** 0.30***
Aspect — -0.12* — — — — — —
Soil silt content -0.08*** — — — — — — —
Soil sand content 0.17*** — — — 0.21*** — — —
Soil clay content 0.05*** — 0.16*** — — — — 0.14*
Distance to coastline -0.22*** — -0.25*** -0.14* -0.24*** — — -0.34***
Distance to the nearest road 0.09*** 0.22*** -0.13** 0.19** 0.15*** — 0.16* -0.14*
Population -0.07*** — — — — — — —
Light intensity -0.14*** — — -0.13* -0.11*** — -0.38*** -0.19***
  Table A4 The standardized partial regression coefficients of driving forces of spatial pattern of NPP on the Chinese side
Driving forces LULC
Broadleaf forest Mixed forest Coniferous forest Grassland Dry farmland Paddy field Urban land Rural settlements
Temperature — — — — — — — —
Precipitation 0.19*** 0.49*** — 0.22*** — — — —
Altitude 0.17*** — — — 0.32*** — — —
Slope 0.08*** — — — 0.31*** 0.30*** 0.45*** 0.43***
Aspect — — — — — — — —
Soil silt content — — — — — — — —
Soil sand content — -0.28*** — 0.34*** — — — —
Soil clay content 0.27*** 0.27*** — 0.24** 0.12*** — — —
Distance to coastline -0.15*** — -0.13** — -0.32*** — — —
Distance to the nearest road 0.06*** 0.08* — — 0.07** — — —
Population — -0.73*** — — -0.07*** — — —
Light intensity -0.10*** — — -0.15** -0.10*** — -0.40*** -0.31***
  Table A5 The standardized partial regression coefficients of driving forces of spatial pattern of NPP on the DPRK’s side
Driving factors LULC
Broadleaf forest Mixed forest Coniferous forest Grassland Dry farmland Paddy field Urban land Rural settlements
Temperature — — — — — — — —
Precipitation 0.22*** 0.43*** — 0.22*** — — 0.17** 0.09*
Altitude 0.12*** — — 0.07** 0.12** — 0.27*** 0.16**
Slope 0.04*** — — — — — — 0.22***
Aspect — — — — — — — —
Soil silt content 0.26*** — 0.77** 0.22*** — — 0.16* 0.17**
Soil sand content 0.44*** — — 0.41*** — — — 0.39***
Soil clay content 0.53*** — — 0.48*** — 0.78** — 0.26***
Distance to coastline 0.08*** — — — — — — —
Distance to nearest road 0.06*** — — — — — — —
Population — — — -0.08** — — -0.21*** —
Light intensity -0.07*** — — — — — -0.50*** -0.22***
  Table A6 The standardized partial regression coefficients of driving forces of spatial pattern of NPP on the Russian side
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