Spatiotemporal Variation and Driving Analysis of Net Primary Productivity of Vegetation in Southern Part of Taihang Mountain, China

Authors

  • Taiyi Cai

    Institute of Quantitative Remote Sensing & Smart Agriculture, Henan Polytechnic University, Jiaozuo 454003, China
  • ChengLong He

    School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China
  • Ammara Gill

    School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China
  • Chao Ma

    1. School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China; 2. Key Laboratory of Spatio-temporal Information and Ecological Restoration of Mines (MNR), Henan Polytechnic University, Jiaozuo 454003, China; 3. Research Centre of Arable Land Protection and Urban-rural High-quality Development in Yellow River Basin, Henan Polytechnic University, Jiaozuo 454003, China

DOI:

https://doi.org/10.30564/jees.v7i1.7137
Received: 26 August 2024 | Revised: 20 October 2024 | Accepted: 28 October 2024 | Published Online: 14 January 2025

Abstract

The net primary productivity of vegetation (NPP) is an important index to evaluate the carbon sequestration capacity of vegetation and land use change. Using MOD17N3HGF NPP data, climate data and night-time light data from 2000 to 2020, this study explored the relationship between NPP and urban expansion, land use and climate change in the Southern Part of Taihang Mountain through brightness gradient method, trend analysis, partial correlation analysis and contribution analysis. It aims to provide information support for urban and rural planning and ecological management in this region. Key findings include: Over the past 20 years, NPP in mountain areas has shown an overall fluctuating upward trend, with an "N" pattern related to altitude. The human activity area expanded by 9.9%, with expansion of highly active areas holding back NPP growth and moderately active areas contributing to it. The trend of climate change is gradually warming and wetting, and the correlation between precipitation and NPP is strong, while the correlation between temperature and NPP is weak. Compared with human activities (19.9%), precipitation was the main driver of NPP change, contributing significantly up to 79.5%. In the past 20 years, the ecological quality of the south Taihang Mountain region has improved significantly and actively responded to climate change, but human activities have led to spatial and temporal ecological differences.

Keywords:

Climate Change; MODIS NPP; Man-Land Relationship; Southern Part of Taihang Mountain

References

[1] Lieth, H., 1973. Primary production: Terrestrial ecosystems. Human Ecology. 1(4), 303–332. DOI: https://doi.org/10.1007/BF01536729

[2] Chen, X., Zhang, Y., 2023. Impacts of climate, phenology, elevation and their interactions on the net primary productivity of vegetation in Yunnan, China under global warming. Ecological Indicators. 154, 110533. DOI: https://doi.org/10.1016/j.ecolind.2023.110533

[3] Lyu, J., Fu, X., Lu, C., et al., 2023. Quantitative assessment of spatiotemporal dynamics in vegetation NPP, NEP and carbon sink capacity in the Weihe River Basin from 2001 to 2020. Journal of Cleaner Production. 428, 139384. DOI: https://doi.org/10.1016/j.jclepro.2023.139384

[4] Koju, U.A., Zhang, J., Maharjan, S., et al., 2020. Analysis of spatiotemporal dynamics of forest Net Primary Productivity of Nepal during 2000–2015. International Journal of Remote Sensing, 41(11), 4336–4364. DOI: https://doi.org/10.1080/01431161.2020.1717667

[5] Gu, G., Adler, R.F., 2023. Observed variability and trends in global precipitation during 1979–2020. Climate Dynamics. 61(1), 131–150. DOI: https://doi.org/10.1007/s00382-022-06567-9

[6] Chen, S., Ma, M., Wu, S., et al., 2023. Topography intensifies variations in the effect of human activities on forest NPP across altitude and slope gradients. Environmental Development. 45, 100826. DOI: https://doi.org/10.1016/j.envdev.2023.100826

[7] Xuan, W., Rao, L., 2023, Spatiotemporal dynamics of net primary productivity and its influencing factors in the middle reaches of the Yellow River from 2000 to 2020. Frontiers in Plant Science. 14. DOI: https://doi.org/10.3389/fpls.2023.1043807

[8] Xue, S., Ma, B., Wang, C., et al., 2023. Identifying key landscape pattern indices influencing the NPP: A case study of the upper and middle reaches of the Yellow River. Ecological Modelling. 484, 110457. DOI: https://doi.org/10.1016/j.ecolmodel.2023.110457

[9] Hou, G, Wu, S, Long, W, et al., 2023. Quantitative analysis of the impact of climate change and oasification on changes in net primary productivity variation in mid-Tianshan Mountains from 2001 to 2020. Ecological Indicators. 154, 110820. DOI: https://doi.org/10.1016/j.ecolind.2023.110820

[10] Wang, T., Yang, M., Yan, S., et al., 2021. Effects of temperature and precipitation on spatiotemporal variations of net primary productivity in the Qinling Mountains, China. Polish Journal of Environmental Studies. 30(1), 409–422. DOI: https://doi.org/10.15244/pjoes/122839

[11] Ma, B., Jing, J., Liu, B., et al., 2022. Quantitative assessment of the relative contributions of climate change and human activities to NPP changes in the Southwest Karst area of China. Environmental Science and Pollution Research. 29(53), 80597–80611. DOI: https://doi.org/10.1007/s11356-022-21433-1

[12] Zhang, H., Sun, R., Peng, D., et al., 2021. Spatiotemporal dynamics of net primary productivity in China's urban lands during 1982–2015. Remote Sensing. 13, 400. DOI: https://doi.org/10.3390/rs13030400

[13] Azhdari, Z., Sardooi, E.R., Bazrafshan, O., et al., 2020. Impact of climate change on net primary production (NPP) in south Iran. Environmental monitoring and assessment. 192(6), 409. DOI: https://doi.org/10.1007/s10661-020-08389-w

[14] Zarei, A., Chemura, A., Gleixner, S., et al., 2021. Evaluating the grassland NPP dynamics in response to climate change in Tanzania. Ecological Indicators. 125, 107600. DOI:https://doi.org/10.1016/j.ecolind.2021.107600

[15] Ivan, K., Holobaca, I.-H., Benedek, J., et al., 2020. Potential of night-time lights to measure regional inequality. Remote Sensing. 12(1), 33. DOI: https://doi.org/10.3390/rs12010033

[16] Bagan, H., Borjigin, H., Yamagata, Y., 2018. Assessing nighttime lights for mapping the urban areas of 50 cities across the globe. Environment and Planning B: Urban Analytics and City Science. 46, 239980831775292. DOI: http://dx.doi.org/10.1177/2399808317752926

[17] Ghosh, T., Anderson, S.J., Elvidge, C.D., et al., 2013. Using nighttime satellite imagery as a proxy measure of human well-being. Sustainability. 5(12), 4988–5019. DOI: https://doi.org/10.3390/su5124988

[18] Peng, S., 2020. 1-km monthly mean temperature dataset for china (1901–2022). DOI: https://dx.doi.org/10.11888/Meteoro.tpdc.270961

[19] Peng, S., 2020. 1-km monthly precipitation dataset for China (1901–2022). DOI: https://dx.doi.org/10.5281/zenodo.3185722

[20] Zhang, L., Chen, B., Fu, H., et al., 2021. A Prolonged Artificial Nighttime-light Dataset of China (1984–2020). DOI: https://dx.doi.org/10.11888/Socioeco.tpdc.271202

[21] Yang, J., Huang, X., 2021. The 30 m annual land cover datasets and its dynamics in China from 1990 to 2020. DOI: https://doi.org/10.5281/zenodo.5210928

[22] Ma, T., Zhou, Y., Zhou, C., et al., 2015. Night-time light derived estimation of spatio-temporal characteristics of urbanization dynamics using DMSP/OLS satellite data. Remote Sensing of Environment. 158, 453–464. DOI: https://doi.org/10.1016/j.rse.2014.11.022

[23] Li, Y., Qin, Y., 2019. The response of Net Primary Production to climate change: A case study in the 400 mm annual precipitation fluctuation zone in China. International Journal of Environmental Research and Public Health. 16(9), 1497. DOI: https://doi.org/10.3390/ijerph16091497

[24] Tang, R., Zhao, X., Zhou, T., et al., 2018. Assessing the impacts of urbanization on albedo in Jing-Jin-Ji region of China. Remote Sensing. 10(7). DOI: https://doi.org/10.3390/rs10071096

[25] Forzieri, G., Alkama, R., Miralles, D.G., et al., 2017. Satellites reveal contrasting responses of regional climate to the widespread greening of Earth. Science. 356(6343), 1180–1184. DOI: https://doi.org/10.1126/science.aal1727

[26] Zhao, L., Chen, Y., Wang, X., et al., 2022. Spatiotemporal changes in net primary productivity before and after the development of unused land in the hilly areas of Hebei, China. PlOS ONE. 17(6), e0270010. DOI: https://doi.org/10.1371/journal.pone.0270010

[27] Yang, A., Zhang, H., Yang, X., et al., 2022. Quantitative analysis of the impact of climate change and human activities on vegetation NPP in the Qilian Mountain. Human and Ecological Risk Assessment: An International Journal. 29, 202–221. DOI: https://doi.org/10.1080/10807039.2022.2152774

[28] Xu, Y., Xu, X., Tang, Q., 2016. Human activity intensity of land surface: Concept, methods and application in China. Journal of Geographical Sciences. 26, 1349–1361. DOI: https://doi.org/10.1007/s11442-016-1331-y

[29] Linger, E., Hogan, J.A., Cao, M., et al., 2020. Precipitation influences on the net primary productivity of a tropical seasonal rainforest in Southwest China: A 9-year case study. Forest Ecology and Management. 467, 118153. DOI: https://doi.org/10.1016/j.foreco.2020.118153

[30] Wang, X.C., Wang, S.D., Zhang, H.B., 2013, Spatiotemporal pattern of vegetation net primary productivity in Henan Province of China based on MOD17A3. Chinese Journal of Ecology. 32, 2797–2805. DOI: https://doi.org/10.13292/j.1000-4890.2013.0314

[31] Li, J., Liu, Y., Cao, M., et al., 2015. Space-time characteristics of vegetation cover and distribution: Case of the Henan Province in China. Sustainability. 7, 11967–11979. DOI: https://doi.org/10.3390/su70911967

[32] Luo, Y., Zhou, M., Jin, S., et al., 2023. Changes in phylogenetic structure and species composition of woody plant communities across an elevational gradient in the southern Taihang Mountains, China. Global Ecology and Conservation. 42, e02412. DOI: https://doi.org/10.1016/j.gecco.2023.e02412

[33] Li, T., Guo, Z., Chao, M., 2022. Dynamic characteristics of urbanization based on nighttime light data in China's “plain–mountain transition zone”. International Journal of Environmental Research and Public Health. 19, 9230. DOI: https://doi.org/10.3390/ijerph19159230

[34] Wang, Q., Liu, K., Ni, X., et al., 2023. Extreme climate change and contemporary analogs for cities in mainland China in a 2.0 °C warmer climate. Climate Services. 30, 100348. DOI: https://doi.org/10.1016/j.cliser.2023.100348

Downloads

How to Cite

Cai, T., He, C., Gill, A., & Ma, C. (2025). Spatiotemporal Variation and Driving Analysis of Net Primary Productivity of Vegetation in Southern Part of Taihang Mountain, China. Journal of Environmental & Earth Sciences, 7(1), 611–624. https://doi.org/10.30564/jees.v7i1.7137

Issue

Vol. 7 , Iss. 1 (January 2025)

Article Type

Article

License

Copyright © 2025 Taiyi Cai, ChengLong He, Ammara Gill, Chao Ma

Creative Commons License

This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.

Crossref
Scopus
Google Scholar
Europe PMC