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InVEST Soil Carbon Stock Modelling of Agricultural Landscapes as an Ecosystem Service Indicator

Author

Listed:
  • Lyndré Nel

    (Environmental Science Doctoral School, Hungarian University of Agriculture and Life Sciences, Páter Károly Str. 1, Pest, 2100 Gödöllő, Hungary)

  • Ana Flávia Boeni

    (Festetics Doctoral School, Hungarian University of Agriculture and Life Sciences, Deák Ferenc Str. 16, Zala, 8360 Keszthely, Hungary
    Ecology and Forest Restoration Laboratory, Luiz de Queiroz College of Agriculture, University of Sao Paulo, Padua Dias Av. 11, Piracicaba 13418-900, Sao Paulo State, Brazil)

  • Viola Judit Prohászka

    (Doctoral School of Landscape Architecture and Landscape Ecology, Hungarian University of Agriculture and Life Sciences, Villányi Rd. 29–43, 1118 Budapest, Hungary)

  • Alfréd Szilágyi

    (Environmental Science Doctoral School, Hungarian University of Agriculture and Life Sciences, Páter Károly Str. 1, Pest, 2100 Gödöllő, Hungary)

  • Eszter Tormáné Kovács

    (Department of Nature Conservation and Landscape Management, Institute for Wildlife Management and Nature Conservation, Hungarian University of Agriculture and Life Sciences, Páter Károly Str. 1, Pest, 2100 Gödöllő, Hungary)

  • László Pásztor

    (Centre for Agricultural Research, Department of Soil Mapping and Environmental Informatics, Institute for Soil Sciences, Herman Ottó Rd. 15, 1022 Budapest, Hungary)

  • Csaba Centeri

    (Department of Nature Conservation and Landscape Management, Institute for Wildlife Management and Nature Conservation, Hungarian University of Agriculture and Life Sciences, Páter Károly Str. 1, Pest, 2100 Gödöllő, Hungary)

Abstract

Soil carbon storage results from interactions between ecological processes and contributes to the global chemical regulation of the atmosphere, a vital ecosystem service. Within the ecosystem services approach, measuring soil carbon stock is used as an indicator of landscapes that function as terrestrial carbon sinks and sources. Soil carbon stock models of agricultural landscapes use national carbon stock data and are used to determine environmental benchmarks and develop land-use management strategies for improved landscape-scale carbon sequestration. The InVEST Carbon Storage model has been used as a tool to map carbon stock based on these data. However, the accuracy of the national carbon inventories of Hungary is unknown. In this study, the InVEST soil carbon stock models of two agricultural landscapes in Hungary were produced based on national soil carbon stock data and in-field collected soil sample carbon stock data. Carbon stock inventories were collated and used as InVEST carbon model inputs, and the models were mapped, compared, and evaluated to determine their usefulness in the planning of maximizing soil carbon storage in sustainable land-use management and policy development. Five InVEST soil carbon stock spatial models were produced for both agricultural landscapes, which showed great variation based on the data used to develop it. Aggregate carbon stock potentially stored in the landscape-scale study areas also varied between datasets used. Integrating soil sample data along with national carbon stock data shows prospective applicability in assessing contextual landscape-scale potential soil carbon stock storage.

Suggested Citation

  • Lyndré Nel & Ana Flávia Boeni & Viola Judit Prohászka & Alfréd Szilágyi & Eszter Tormáné Kovács & László Pásztor & Csaba Centeri, 2022. "InVEST Soil Carbon Stock Modelling of Agricultural Landscapes as an Ecosystem Service Indicator," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:9808-:d:883844
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    References listed on IDEAS

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    Cited by:

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    2. Jiayu Wang & Tian Chen, 2022. "A Multi-Scenario Land Expansion Simulation Method from Ecosystem Services Perspective of Coastal Urban Agglomeration: A Case Study of GHM-GBA, China," Land, MDPI, vol. 11(11), pages 1-23, October.
    3. Tong Lin & Dafang Wu & Muzhuang Yang & Peifang Ma & Yanyan Liu & Feng Liu & Ziying Gan, 2022. "Evolution and Simulation of Terrestrial Ecosystem Carbon Storage and Sustainability Assessment in Karst Areas: A Case Study of Guizhou Province," IJERPH, MDPI, vol. 19(23), pages 1-19, December.
    4. Yonghua Li & Song Yao & Hezhou Jiang & Huarong Wang & Qinchuan Ran & Xinyun Gao & Xinyi Ding & Dandong Ge, 2022. "Spatial-Temporal Evolution and Prediction of Carbon Storage: An Integrated Framework Based on the MOP–PLUS–InVEST Model and an Applied Case Study in Hangzhou, East China," Land, MDPI, vol. 11(12), pages 1-22, December.
    5. István Kristó & Marianna Vályi-Nagy & Attila Rácz & Katalin Irmes & Lajos Szentpéteri & Márton Jolánkai & Gergő Péter Kovács & Mária Ágnes Fodor & Apolka Ujj & Klára Veresné Valentinyi & Melinda Tar, 2023. "Effects of Nutrient Supply and Seed Size on Germination Parameters and Yield in the Next Crop Year of Winter Wheat ( Triticum aestivum L.)," Agriculture, MDPI, vol. 13(2), pages 1-17, February.
    6. Tiantian Ma & Qingbai Hu & Changle Wang & Jungang Lv & Changhong Mi & Rongguang Shi & Xiaoli Wang & Yanying Yang & Wenhao Wu, 2022. "Exploring the Relationship between Ecosystem Services under Different Socio-Economic Driving Degrees," IJERPH, MDPI, vol. 19(23), pages 1-17, December.
    7. Jian Chen & Kai Wang & Maomao Li & Xianzhi Wang & Xiaoxiao Zhang & Lixin Niu & Yanlong Zhang, 2023. "Prediction and Evolution of Carbon Storage of Terrestrial Ecosystems in the Qinling Mountains North Slope Region, China," Land, MDPI, vol. 12(11), pages 1-17, November.
    8. Eszter Tormáné Kovács & Csaba Centeri, 2023. "Assessment of Ecosystem Services at Different Scales," Sustainability, MDPI, vol. 15(24), pages 1-5, December.

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