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Carbon Storage Patterns and Landscape Sustainability in Northeast Portugal: A Digital Mapping Approach

Author

Listed:
  • Matheus B. Patrício

    (Advanced Science Research Centre, University of A Coruña, Elviña Campus, 15071 A Coruña, Spain)

  • Marcos Lado

    (Advanced Science Research Centre, University of A Coruña, Elviña Campus, 15071 A Coruña, Spain)

  • Tomás de Figueiredo

    (Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
    Laboratório Associado Para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal)

  • João C. Azevedo

    (Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
    Laboratório Associado Para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal)

  • Paulo A. A. Bueno

    (Federal Technological University of Paraná, Campo Mourão Campus, Campo Mourão 87301-899, Brazil)

  • Felícia Fonseca

    (Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal
    Laboratório Associado Para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal)

Abstract

This study investigated the impact of regional land abandonment in northeast Portugal. It specifically focused on carbon sequestration opportunities in the Upper Sabor River Watershed, situated in the northeast of Portugal, amidst agricultural land abandonment. The study involved mapping the distribution of soil organic carbon (SOC) across four soil layers (0–5 cm, 5–10 cm, 10–20 cm, and 20–30 cm) at 120 sampling points. The quantification of SOC storage (measured in Mg C ha −1 ) allowed for an analysis of its relationship with various landscape characteristics, including elevation, land use and land cover (LULC), normalized difference vegetation index (NDVI), modified soil-adjusted vegetation index (MSAVI), topographic wetness index (TWI), and erosion risk (ER). Six statistical tests were employed, including multivariate approaches like Cubist and Random Forest, within different scenarios to assess carbon distribution within the watershed’s soils. These modeling results were then utilized to propose strategies aimed at enhancing soil carbon storage. Notably, a significant discrepancy was observed in the carbon content between areas at higher elevations (>1000 m) and those at lower elevations (<800 m). Additionally, the study found that the amount of carbon stored in agricultural soils was often significantly lower than in other land use categories, including forests, mountain herbaceous vegetation, pasture, and shrub communities. Analyzing bi- and multivariate scenarios, it was determined that the scenario with the greatest number of independent variables (set 6) yielded the lowest RMSE (root mean squared error), serving as a key indicator for evaluating predicted values against observed values. However, it is important to note that the independent variables used in set 4 (elevation, LULC, and NDVI) had reasonably similar values. Ultimately, the spatialization of the model from scenario 6 provided actionable insights for soil carbon conservation and enhancement across three distinct elevation levels.

Suggested Citation

  • Matheus B. Patrício & Marcos Lado & Tomás de Figueiredo & João C. Azevedo & Paulo A. A. Bueno & Felícia Fonseca, 2023. "Carbon Storage Patterns and Landscape Sustainability in Northeast Portugal: A Digital Mapping Approach," Sustainability, MDPI, vol. 15(24), pages 1-27, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:24:p:16853-:d:1300346
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    References listed on IDEAS

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    1. Markus Reichstein & Michael Bahn & Philippe Ciais & Dorothea Frank & Miguel D. Mahecha & Sonia I. Seneviratne & Jakob Zscheischler & Christian Beer & Nina Buchmann & David C. Frank & Dario Papale & An, 2013. "Climate extremes and the carbon cycle," Nature, Nature, vol. 500(7462), pages 287-295, August.
    2. Xinghui Wang & Yuman Sun & Weiwei Jia & Hezhi Wang & Wancai Zhu, 2023. "Coupling of Forest Carbon Densities with Landscape Patterns and Climate Change in the Lesser Khingan Mountains, Northeast China," Sustainability, MDPI, vol. 15(20), pages 1-17, October.
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    Cited by:

    1. Jin Wang & Jingren Yu & Manjuan Shen & Shengquan Che, 2024. "Study on the Optimization of Carbon Sequestration in Shanghai’s Urban Artificial Wetlands: The Cases of Shanghai Fish and Dishui Lake," Land, MDPI, vol. 13(12), pages 1-20, December.

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