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A New Approach to Monitor Soil Microbial Driven C/N Ratio in Temperate Evergreen Coniferous Forests Managed via Sentinel-2 Spectral Imagery

Author

Listed:
  • Lizardo Reyna

    (Facultad de Ingeniería Agrícola, Universidad Técnica de Manabí, Lodana 130401, Ecuador)

  • Jarosław Lasota

    (Department of Ecology and Silviculture, Faculty of Forestry, University of Agriculture in Krakow, Al. 29 Listopada 46, 31-425 Krakow, Poland)

  • Lizardo Reyna-Bowen

    (Facultad de Ingeniería Agrícola, Escuela Superior Politécnica Agropecuaria de Manabí MFL, Calceta 130602, Ecuador)

  • Lenin Vera-Montenegro

    (Facultad de Ingeniería Agrícola, Escuela Superior Politécnica Agropecuaria de Manabí MFL, Calceta 130602, Ecuador)

  • Emil Cristhian Vega-Ponce

    (Facultad de Ingeniería Agrícola, Universidad Técnica de Manabí, Lodana 130401, Ecuador)

  • Maria Luisa Izaguirre-Mayoral

    (Facultad de Ingeniería Agrícola, Universidad Técnica de Manabí, Lodana 130401, Ecuador)

  • Ewa Błońska

    (Department of Ecology and Silviculture, Faculty of Forestry, University of Agriculture in Krakow, Al. 29 Listopada 46, 31-425 Krakow, Poland)

Abstract

Forests are key ecosystems for climate change mitigation, playing a pivotal role in C and N land sequestering and storage. However, the sustainable management of forests is challenging for foresters who need continuous and reliable information on the status of soil conditions. Yet, the monitoring of soils in temperate evergreen forests, via satellite data, is jeopardized by the year round prevailing heavily dense canopy. In this study, the Sentinel-2 spectral imagery derived normalized difference vegetation index (NDVI), proved to be a reliable tool to determine the C/N ratio in two managed pine-dominated forests, in southern Poland. Results showed a strong negative correlation between NDVI values and the on-site C/N ratios measured at the upper soil horizons in 100 and 99 randomly distributed sampling points across the Kup (r 2 = −0.8019) and Koniecpol (r 2 = −0.7281) forests. This indicates the feasibility of using the NDVI to predict the microbial driven soil C/N ratio in evergreen forests, and to foresee alterations in the vegetation patterns elicited by microbial hindering soil abiotic or biotic factors. Spatial/temporal variations in C/N ratio also provide information on C and N soil dynamics and land ecosystem function in a changing climate.

Suggested Citation

  • Lizardo Reyna & Jarosław Lasota & Lizardo Reyna-Bowen & Lenin Vera-Montenegro & Emil Cristhian Vega-Ponce & Maria Luisa Izaguirre-Mayoral & Ewa Błońska, 2023. "A New Approach to Monitor Soil Microbial Driven C/N Ratio in Temperate Evergreen Coniferous Forests Managed via Sentinel-2 Spectral Imagery," Land, MDPI, vol. 12(2), pages 1-8, January.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:2:p:284-:d:1040615
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    References listed on IDEAS

    as
    1. Akhlaq Amin Wani & Amir Farooq Bhat & Aaasif Ali Gatoo & Shiba Zahoor & Basira Mehraj & Naveed Najam & Qaisar Shafi Wani & M A Islam & Shah Murtaza & Moonisa Aslam Dervash & P K Joshi, 2021. "Assessing relationship of forest biophysical factors with NDVI for carbon management in key coniferous strata of temperate Himalayas," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 26(1), pages 1-22, January.
    2. Xiaoxiao Li & Man Yu & Jing Ma & Zhanbin Luo & Fu Chen & Yongjun Yang, 2018. "Identifying the Relationship between Soil Properties and Rice Growth for Improving Consolidated Land in the Yangtze River Delta, China," Sustainability, MDPI, vol. 10(9), pages 1-14, August.
    3. Speranza Claudia Panico & Valeria Memoli & Lucia Santorufo & Stefania Aiello & Rossella Barile & Anna De Marco & Giulia Maisto, 2022. "Soil Biological Responses under Different Vegetation Types in Mediterranean Area," IJERPH, MDPI, vol. 19(2), pages 1-17, January.
    4. Antonio Comparetti & Jose Rafael Marques da Silva, 2022. "Use of Sentinel-2 Satellite for Spatially Variable Rate Fertiliser Management in a Sicilian Vineyard," Sustainability, MDPI, vol. 14(3), pages 1-18, February.
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