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Journal of Arid Land
Journal of Arid Land  2026, Vol. 18 Issue (1): 34-55    DOI: 10.1016/j.jaridl.2026.01.004     CSTR: 32276.14.JAL.20250149
Research article     
Spatiotemporal evolution of net ecosystem productivity and the driving mechanisms in Horqin Sandy Land, China
XU Xiaona1, ZHANG Huayong1,2,*()
1Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China
2Theoretical Ecology and Engineering Ecology Research Group, School of Life Sciences, Shandong University, Qingdao 266237, China
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Abstract  

Vegetation in terrestrial ecosystems as a carbon sink is a crucial factor in mitigating global warming and reaching carbon neutrality targets, although the drivers of net ecosystem productivity (NEP) under combined human and environmental pressures remain poorly understood. In this study, we analyzed the spatiotemporal evolution of NEP in the Horqin Sandy Land, China from 2000 to 2020, and observed the variation in NEP across different land use types. We further identified and quantified the effects of human activities, topographical features, climatic conditions, and soil properties on NEP through the application of structural equation modeling (SEM) and boosted regression trees (BRT). The results showed that the multi-year average NEP ranged from -137.79 to 461.96 g C/m2 in the Horqin Sandy Land, with 88.21% of the area showing a significant increasing trend. Among different land use types, forestland exhibited the highest NEP values, followed by cropland, grassland, impervious land, and unused land. The NEP in carbon sink areas was primarily regulated by potential evapotranspiration (negatively correlated) and precipitation (positively correlated). Slope was identified as the most significant positive determinant in carbon source areas. Forestland exhibited climate-topography interactions driving NEP, whereas cropland and grassland relied on temperature; unused land and impervious land were susceptible to land use/cover change and human footprint. This study has significant implications for maintaining the carbon sink function and promoting ecological engineering programs that aim to enhance the capacity of terrestrial carbon sinks in the semi-arid agro-pastoral ecotone.

Key words： net ecosystem productivity (NEP)      land use/cover change (LUCC)      carbon sink      climate change      human activities      structural equation modeling (SEM)      semi-arid agro-pastoral ecotone     
Received: 09 April 2025      Published: 31 January 2026
Corresponding Authors: *ZHANG Huayong (E-mail: rceens@ncepu.edu.cn)
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XU Xiaona, ZHANG Huayong. Spatiotemporal evolution of net ecosystem productivity and the driving mechanisms in Horqin Sandy Land, China. Journal of Arid Land, 2026, 18(1): 34-55.

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http://jal.xjegi.com/10.1016/j.jaridl.2026.01.004     OR     http://jal.xjegi.com/Y2026/V18/I1/34

Fig. 1 Overview of the Horqin Sand Land based on digital elevation model (DEM; a) and spatial distribution of land use in 2000 (b)
Fig. S1 Spatial distribution of multi-year average temperature (a), precipitation (b), and potential evapotranspiration (PET; c) in the Horqin Sandy Land during 2000-2020
Fig. S2 Land use distribution of the Horqin Sandy Land in 2005 (a), 2010 (b), 2015 (c), and 2020 (d)
Sen's slope (β) P Z Trend
β<0 P<0.010 |Z|>2.58 Extremely significant decrease
β<0 0.010≤P<0.050 1.96<|Z|≤2.58 Significant decrease
β<0 P≥0.050 |Z|≤1.96 No significant decrease
β>0 P≥0.050 |Z|≤1.96 No significant increase
β>0 0.010≤P<0.050 1.96<|Z|≤2.58 Significant increase
β>0 P<0.010 |Z|>2.58 Extremely significant increase
Table 1 Classification criteria of net ecosystem productivity (NEP) trends
Fig. 2 Spatial distribution characteristics of net ecosystem productivity (NEP; a), Sen's slope of NEP (b), trend of NEP (c), and annual variation in NEP (d) in the Horqin Sandy Land during 2000-2020
Fig. 3 Interannual variation and spatial dynamics of NEP across cropland (a and b), forestland (c and d), grassland (e and f), unused land (g and h), and impervious land (i and j) in the Horqin Sandy Land during 2000-2020
Fig. S3 Violin plots of multi-year average net ecosystem productivity (NEP) across different land use types in the Horqin Sandy Land during 2000-2020. The violin shape outlines the probability density of the data. The small square inside the box indicates the mean value, while the upper and lower boundaries of the box correspond to the 25th and 75th percentiles, respectively. The box extends lines to 1.5 times the interquartile range.
Fig. 4 Sankey diagram (a) and spatial variations of land use transitions (b) in the Horqin Sandy Land from 2000 to 2020. The numbers of 1-6 in panel (b) represent cropland, forestland, glassland, water body, unused land, and impervious land, respectively.
2000 2020 Total
Cropland Forestland Grassland Water body Unused land Impervious land
Cropland 37,089 104 10,999 28 201 606 49,027
Forestland 98 7115 71 0 0 3 7287
Grassland 9868 946 48,480 17 1060 496 60,867
Water body 257 1 101 233 44 64 700
Unused land 226 0 2605 6 2704 65 5606
Impervious land 6 0 1 7 0 2165 2179
Total 47,544 8166 62,257 291 4009 3399 125,666
Table 2 Land use transition matrix for the Horqin Sandy Land from 2000 to 2020 (unit: km2)
Fig. 5 Relative contributions of environmental factors and human activities to NEP in carbon sink (a) and carbon source (b) areas. Tem, temperature; PET, potential evapotranspiration; Pre, precipitation; GDP, gross domestic product; HFP, human footprint; TK, total potassium; TN, total nitrogen; TP, total phosphorus, SOM, soil organic matter; LUCC, land use/cover change. The pie chart shows the relative contributions of climate, soil, topography, and human activities to NEP.
Fig. 6 Relative contributions of environmental factors and human activities to NEP in cropland (a), forestland (b), grassland (c), unused land (d), and impervious land (e). The pie chart shows the relative contributions of climate, soil, topography, and human activities to NEP.
Fig. 7 Structural equation modeling (SEM) for the NEP and standardized total effects in carbon sink (a and b) and carbon source (c and d) areas. df, degree of freedom. Dotted arrows represent non-significant relationships. The numbers labeled near the path arrows represent standardized path coefficients. The number adjacent to each factor indicates the standardized coefficient of the indicator on the latent variable. *** indicates P<0.001 level. R2 represents the proportion of variance explained by the SEM.
Carbon sink areas Path Effect coefficient
Direct effect NEP~Climate 0.64
NEP~Soil 0.17
NEP~Topography 0.19
NEP~Human activities -0.10
Indirect effect Climate→Soil→NEP 0.10
Topography→Climate→NEP 0.29
Topography→Climate→Soil→NEP 0.05
Topography→Soil→NEP 0.03
Human activities→Climate→NEP 0.23
Human activities→Climate→Soil→NEP 0.04
Human activities→Topography→NEP 0.07
Human activities→Topography→Climate→NEP 0.11
Human activities→Topography→Climate→Soil→NEP 0.02
Human activities→Topography→Soil→NEP 0.01
Carbon source areas Path Effect coefficient
Direct effect NEP~Soil 0.14
NEP~Topography 0.28
NEP~Human activities 0.19
Indirect effect Climate→Soil→NEP 0.03
Topography→Climate→Soil→NEP 0.01
Topography→Soil→NEP 0.04
Human activities→Climate→Soil→NEP 0.00
Human activities→Soil→NEP 0.01
Human activities→Topography→NEP 0.02
Human activities→Topography→Climate→Soil→NEP 0.00
Human activities→Topography→Soil→NEP 0.00
Cropland Path Effect coefficient
Direct effect NEP~Climate 0.48
NEP~Topography 0.20
NEP~Human activities 0.33
Indirect effect Topography→Climate→NEP 0.02
Human activities→Climate→NEP -0.02
Human activities→Topography→NEP 0.01
Human activities→Topography→Climate→NEP 0.00
Forestland Path Effect coefficient
Direct effect NEP~Climate 0.62
NEP~Soil 0.12
NEP~Topography 0.25
Indirect effect Climate→Soil→NEP 0.05
Topography→Climate→NEP 0.42
Topography→Climate→Soil→NEP 0.04
Topography→Soil→NEP -0.04
Human activities→Climate→NEP 0.17
Forestland Path Effect coefficient
Indirect effect Human activities→Climate→Soil→NEP 0.08
Human activities→Soil→NEP -0.02
Human activities→Topography→NEP 0.08
Human activities→Topography→Climate→NEP 0.13
Human activities→Topography→Climate→Soil→NEP 0.01
Human activities→Topography→Soil→NEP -0.01
Grassland Path Effect coefficient
Direct effect NEP~Climate 0.68
NEP~Soil 0.17
NEP~Topography 0.18
NEP~Human activities -0.14
Indirect effect Climate→Soil→NEP 0.10
Topography→Climate→NEP 0.40
Topography→Climate→Soil→NEP 0.06
Topography→Soil→NEP 0.02
Human activities→Climate→NEP 0.25
Human activities→Climate→Soil→NEP 0.04
Human activities→Topography→NEP 0.07
Human activities→Topography→Climate→NEP 0.16
Human activities→Topography→Climate→Soil→NEP 0.02
Human activities→Topography→Soil→NEP 0.01
Unused land Path Effect coefficient
Direct effect NEP~Climate 0.15
NEP~Soil 0.12
NEP~Topography 0.18
NEP~Human activities 0.49
Indirect effect Topography→Climate→NEP 0.09
Topography→Soil→NEP 0.04
Human activities→Topography→NEP 0.02
Human activities→Topography→Climate→NEP 0.01
Human activities→Topography→Soil→NEP 0.01
Impervious land Path Effect coefficient
Direct effect NEP~Climate 0.16
NEP~Soil 0.18
NEP~Topography 0.16
NEP~Human activities 0.34
Indirect effect Climate→Soil→NEP -0.02
Topography→Climate→NEP -0.03
Topography→Climate→Soil→NEP 0.00
Human activities→Climate→NEP -0.02
Human activities→Climate→Soil→NEP 0.00
Human activities→Soil→NEP 0.03
Human activities→Topography→NEP 0.03
Human activities→Topography→Climate→NEP -0.01
Human activities→Topography→Climate→Soil→NEP 0.00
Table S1 Detailed structural equation modeling (SEM) calculations (significant paths only) for the net ecosystem productivity (NEP) in carbon sink areas, carbon source areas, cropland, forestland, grassland, unused land, and impervious land
Fig. 8 SEM for the NEP and standardized total effects in cropland (a and b), forestland (c and d), grassland (e and f), unused land (g and h), and impervious land (i and j). Dotted arrows represent non-significant relationships. The numbers labeled near the path arrows represent standardized path coefficients. The number adjacent to each factor indicates the standardized coefficient of the indicator on the latent variable. ** indicates P<0.010 level; *** indicates P<0.001 level.
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