IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i6p778-d823613.html
   My bibliography  Save this article

Contribution of Incorporating the Phosphorus Cycle into TRIPLEX-CNP to Improve the Quantification of Land Carbon Cycle

Author

Listed:
  • Juhua Ding

    (Center for Ecological Forecasting and Global Change, College of Forestry, Northwest A&F University, Xianyang 712100, China)

  • Qiuan Zhu

    (College of Hydrology and Water Resources, Hohai University, Nanjing 210000, China
    National Earth System Science Data Center, National Science & Technology Infrastructure of China, Beijing 100015, China)

  • Hanwei Li

    (Center for Ecological Forecasting and Global Change, College of Forestry, Northwest A&F University, Xianyang 712100, China)

  • Xiaolu Zhou

    (Center for Ecological Forecasting and Global Change, College of Forestry, Northwest A&F University, Xianyang 712100, China)

  • Weiguo Liu

    (Center for Ecological Forecasting and Global Change, College of Forestry, Northwest A&F University, Xianyang 712100, China)

  • Changhui Peng

    (Center for Ecological Forecasting and Global Change, College of Forestry, Northwest A&F University, Xianyang 712100, China
    Department of Biology Sciences, Institute of Environment Sciences, University of Quebec at Montreal, Montreal, QC H3G 1J5, Canada)

Abstract

Phosphorus (P) is a key and a limiting nutrient in ecosystems and plays an important role in many physiological and biochemical processes, affecting both terrestrial ecosystem productivity and soil carbon storage. However, only a few global land surface models have incorporated P cycle and used to investigate the interactions of C-N-P and its limitation on terrestrial ecosystems. The overall objective of this study was to integrate the P cycle and its interaction with carbon (C) and nitrogen (N) into new processes model of TRIPLEX-CNP. In this study, key processes of the P cycle, including P pool sizes and fluxes in plant, litter, and soil were integrated into a new model framework, TRIPLEX-CNP. We also added dynamic P:C ratios for different ecosystems. Based on sensitivity analysis results, we identified the phosphorus resorption coefficient of leaf (rpleaf) as the most influential parameter to gross primary productivity (GPP) and biomass, and determined optimal coefficients for different plant functional types (PFTs). TRIPLEX-CNP was calibrated with 49 sites and validated against 116 sites across eight biomes globally. The results suggested that TRIPLEX-CNP performed well on simulating the global GPP and soil organic carbon (SOC) with respective R 2 values of 0.85 and 0.78 (both p < 0.01) between simulated and observed values. The R 2 of simulation and observation of total biomass are 0.67 ( p < 0.01) by TRIPLEX-CNP. The overall model performance had been improved in global GPP, total biomass and SOC after adding the P cycle comparing with the earlier version. Our work represents the promising step toward new coupled ecosystem process models for improving the quantifications of land carbon cycle and reducing uncertainty.

Suggested Citation

  • Juhua Ding & Qiuan Zhu & Hanwei Li & Xiaolu Zhou & Weiguo Liu & Changhui Peng, 2022. "Contribution of Incorporating the Phosphorus Cycle into TRIPLEX-CNP to Improve the Quantification of Land Carbon Cycle," Land, MDPI, vol. 11(6), pages 1-22, May.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:6:p:778-:d:823613
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/6/778/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/11/6/778/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yuanyuan Huang & Phillipe Ciais & Daniel S. Goll & Jordi Sardans & Josep Peñuelas & Fabio Cresto-Aleina & Haicheng Zhang, 2020. "The shift of phosphorus transfers in global fisheries and aquaculture," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    2. Alistair W. R. Seddon & Marc Macias-Fauria & Peter R. Long & David Benz & Kathy J. Willis, 2016. "Sensitivity of global terrestrial ecosystems to climate variability," Nature, Nature, vol. 531(7593), pages 229-232, March.
    3. Gilhespy, Sarah L. & Anthony, Steven & Cardenas, Laura & Chadwick, David & del Prado, Agustin & Li, Changsheng & Misselbrook, Thomas & Rees, Robert M. & Salas, William & Sanz-Cobena, Alberto & Smith, , 2014. "First 20 years of DNDC (DeNitrification DeComposition): Model evolution," Ecological Modelling, Elsevier, vol. 292(C), pages 51-62.
    4. Wang, Fugui & Mladenoff, David J. & Forrester, Jodi A. & Keough, Cindy & Parton, William J., 2013. "Global sensitivity analysis of a modified CENTURY model for simulating impacts of harvesting fine woody biomass for bioenergy," Ecological Modelling, Elsevier, vol. 259(C), pages 16-23.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Meng Luo & Shengwei Zhang & Lei Huang & Zhiqiang Liu & Lin Yang & Ruishen Li & Xi Lin, 2022. "Temporal and Spatial Changes of Ecological Environment Quality Based on RSEI: A Case Study in Ulan Mulun River Basin, China," Sustainability, MDPI, vol. 14(20), pages 1-19, October.
    2. Mack, Sarah K. & Lane, Robert R. & Deng, Jia & Morris, James T. & Bauer, Julian J., 2023. "Wetland carbon models: Applications for wetland carbon commercialization," Ecological Modelling, Elsevier, vol. 476(C).
    3. Sharaniya Vijitharan & Nophea Sasaki & Manjunatha Venkatappa & Nitin Kumar Tripathi & Issei Abe & Takuji W. Tsusaka, 2022. "Assessment of Forest Cover Changes in Vavuniya District, Sri Lanka: Implications for the Establishment of Subnational Forest Reference Emission Level," Land, MDPI, vol. 11(7), pages 1-25, July.
    4. Li Yang & Yue Xu & Junqi Zhu & Keyu Sun, 2024. "Research on Water Ecological Resilience Measurement and Influencing Factors: A Case Study of the Yangtze River Economic Belt, China," Sustainability, MDPI, vol. 16(16), pages 1-23, August.
    5. Kai Yin & Dengsheng Lu & Yichen Tian & Qianjun Zhao & Chao Yuan, 2014. "Evaluation of Carbon and Oxygen Balances in Urban Ecosystems Using Land Use/Land Cover and Statistical Data," Sustainability, MDPI, vol. 7(1), pages 1-27, December.
    6. Nittaya Cha-un & Amnat Chidthaisong & Kazuyuki Yagi & Sirintornthep Towprayoon, 2021. "Simulating the Long-Term Effects of Fertilizer and Water Management on Grain Yield and Methane Emissions of Paddy Rice in Thailand," Agriculture, MDPI, vol. 11(11), pages 1-22, November.
    7. Shulin Chen & Zhenghao Zhu & Xiaotong Liu & Li Yang, 2022. "Variation in Vegetation and Its Driving Force in the Pearl River Delta Region of China," IJERPH, MDPI, vol. 19(16), pages 1-15, August.
    8. Huang, Ze & Liu, Yu & Qiu, Kaiyang & López-Vicente, Manuel & Shen, Weibo & Wu, Gao-Lin, 2021. "Soil-water deficit in deep soil layers results from the planted forest in a semi-arid sandy land: Implications for sustainable agroforestry water management," Agricultural Water Management, Elsevier, vol. 254(C).
    9. Han, Huanhao & Gao, Rong & Cui, Yuanlai & Gu, Shixiang, 2022. "A semi-empirical semi-process model of ammonia volatilization from paddy fields under different irrigation modes and urea application regimes," Agricultural Water Management, Elsevier, vol. 272(C).
    10. Stephen C. Hagen & Grace Delgado & Peter Ingraham & Ian Cooke & Richard Emery & Justin P. Fisk & Lindsay Melendy & Thomas Olson & Shawn Patti & Nathanael Rubin & Beth Ziniti & Haixin Chen & William Sa, 2020. "Mapping Conservation Management Practices and Outcomes in the Corn Belt Using the Operational Tillage Information System (OpTIS) and the Denitrification–Decomposition (DNDC) Model," Land, MDPI, vol. 9(11), pages 1-23, October.
    11. Zhao, Zheng & Cao, Linkui & Deng, Jia & Sha, Zhimin & Chu, Changbin & Zhou, Deping & Wu, Shuhang & Lv, Weiguang, 2020. "Modeling CH4 and N2O emission patterns and mitigation potential from paddy fields in Shanghai, China with the DNDC model," Agricultural Systems, Elsevier, vol. 178(C).
    12. Yuhao Jin & Han Zhang & Yuchao Yan & Peitong Cong, 2020. "A Semi-Parametric Geographically Weighted Regression Approach to Exploring Driving Factors of Fractional Vegetation Cover: A Case Study of Guangdong," Sustainability, MDPI, vol. 12(18), pages 1-19, September.
    13. Henry R. Scharf & Ann M. Raiho & Sierra Pugh & Carl A. Roland & David K. Swanson & Sarah E. Stehn & Mevin B. Hooten, 2022. "Multivariate Bayesian clustering using covariate‐informed components with application to boreal vegetation sensitivity," Biometrics, The International Biometric Society, vol. 78(4), pages 1427-1440, December.
    14. Cecilia Parracciani & Robert Buitenwerf & Jens-Christian Svenning, 2023. "Impacts of Climate Change on Vegetation in Kenya: Future Projections and Implications for Protected Areas," Land, MDPI, vol. 12(11), pages 1-20, November.
    15. Hasibuan, Abdul Muis & Gregg, Daniel & Stringer, Randy, 2020. "Accounting for diverse risk attitudes in measures of risk perceptions: A case study of climate change risk for small-scale citrus farmers in Indonesia," Land Use Policy, Elsevier, vol. 95(C).
    16. Shuang Liu & Xuefei Li & Long Chen & Qing Zhao & Chaohui Zhao & Xisheng Hu & Jian Li, 2022. "A New Approach to Investigate the Spatially Heterogeneous in the Cooling Effects of Landscape Pattern," Land, MDPI, vol. 11(2), pages 1-21, February.
    17. Yi-ping Fang & Fu-biao Zhu & Shu-hua Yi & Xiao-ping Qiu & Yong-jiang Ding, 2021. "Ecological carrying capacity of alpine grassland in the Qinghai–Tibet Plateau based on the structural dynamics method," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 12550-12578, August.
    18. Thaís Pacheco Kasecker & Mario Barroso Ramos-Neto & Jose Maria Cardoso Silva & Fabio Rubio Scarano, 2018. "Ecosystem-based adaptation to climate change: defining hotspot municipalities for policy design and implementation in Brazil," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(6), pages 981-993, August.
    19. Yu-Pin Lin & Chi-Ju Chen & Wan-Yu Lien & Wen-Hao Chang & Joy R. Petway & Li-Chi Chiang, 2019. "Landscape Conservation Planning to Sustain Ecosystem Services under Climate Change," Sustainability, MDPI, vol. 11(5), pages 1-18, March.
    20. Meng Wang & Zhengfeng An, 2022. "Regional and Phased Vegetation Responses to Climate Change Are Different in Southwest China," Land, MDPI, vol. 11(8), pages 1-21, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:11:y:2022:i:6:p:778-:d:823613. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.