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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
28/04/2025 |
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Data da última atualização: |
28/04/2025 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
GONÇALVES, D. R. P.; INAGAKI, T. M.; BARIONI, L. G.; SCALA JUNIOR, N. L.; CHERUBIN, M. R.; SÁ, J. C. de M.; CERRI, C. E. P.; ANSELMI, A. |
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Afiliação: |
DANIEL RUIZ POTMA GONÇALVES, UNIVERSIDADE ESTADUAL DE PONTA GROSSA; THIAGO MASSAO INAGAKI, NORWEGIAN INSTITUTE OF BIOECONOMY RESEARCH; LUIS GUSTAVO BARIONI, CNPTIA; NEWTON LA SCALA JUNIOR, UNIVERSIDADE ESTADUAL PAULISTA "JÚLIO DE MESQUITA FILHO"; MAURÍCIO ROBERTO CHERUBIN, UNIVERSIDADE DE SÃO PAULO; JOÃO CARLOS DE MORAES SÁ, THE OHIO STATE UNIVERSITY; CARLOS EDUARDO PELLEGRINO CERRI, UNIVERSIDADE DE SÃO PAULO; ADRIANO ANSELMI, BAYER CROP SCIENCE. |
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Título: |
Accessing and modelling soil organic carbon stocks in Prairies, Savannas, and forests. |
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Ano de publicação: |
2024 |
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Fonte/Imprenta: |
Catena, v. 243, 108219, 2024. |
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ISSN: |
0341-8162 |
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DOI: |
https://doi.org/10.1016/j.catena.2024.108219 |
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Idioma: |
Inglês |
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Conteúdo: |
Soils are the third largest carbon pool on Earth and play a crucial role in mitigating climate change. Therefore, understanding and predicting soil carbon sequestration is of major interest to mitigate climate change globally, especially in countries with strong agricultural backgrounds. In this study, we used a new database composed of 5029 samples collected up to 1-meter depth in three biomes that are most representative of agriculture, Pampas (Prairie), Cerrados (Savanna), and Atlantic Forest (Forest), to explore soil organic carbon (SOC) stocks and its environmental drivers. The Cerrado (Savanna) biome was the only one where croplands presented higher SOC stocks than native vegetation (Native vegetation 121.23 Mg/ha and croplands 127.85 Mg/ha or 5 % higher). From the tested models, the Random Forest outperformed the others, achieving an R2 of 0.64 for croplands and 0.56 for native vegetation. The accuracy of the models varied with soil depth, showing better predictions in shallow layers for croplands and deeper layers for native vegetation. Our results highlight the importance of clay content, precipitation, net primary production (NPP), and temperature as key predictors for soil carbon stocks in the studied biomes. The findings emphasize the importance of protecting the surface layers, especially in the Cerrado biome, to enhance SOC stocks and promote sustainable land management practices. Moreover, the results provide valuable insights for the development of nature-based carbon markets and suggest potential strategies for climate change mitigation. Enhancing our understanding of SOC dynamics and adopting precise environmental predictors will contribute to the formulation of targeted soil management strategies and accelerate progress toward achieving climate goals. MenosSoils are the third largest carbon pool on Earth and play a crucial role in mitigating climate change. Therefore, understanding and predicting soil carbon sequestration is of major interest to mitigate climate change globally, especially in countries with strong agricultural backgrounds. In this study, we used a new database composed of 5029 samples collected up to 1-meter depth in three biomes that are most representative of agriculture, Pampas (Prairie), Cerrados (Savanna), and Atlantic Forest (Forest), to explore soil organic carbon (SOC) stocks and its environmental drivers. The Cerrado (Savanna) biome was the only one where croplands presented higher SOC stocks than native vegetation (Native vegetation 121.23 Mg/ha and croplands 127.85 Mg/ha or 5 % higher). From the tested models, the Random Forest outperformed the others, achieving an R2 of 0.64 for croplands and 0.56 for native vegetation. The accuracy of the models varied with soil depth, showing better predictions in shallow layers for croplands and deeper layers for native vegetation. Our results highlight the importance of clay content, precipitation, net primary production (NPP), and temperature as key predictors for soil carbon stocks in the studied biomes. The findings emphasize the importance of protecting the surface layers, especially in the Cerrado biome, to enhance SOC stocks and promote sustainable land management practices. Moreover, the results provide valuable insights for the development of nature-bas... Mostrar Tudo |
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Palavras-Chave: |
Aprendizado de máquina; Atlantic forest; Cerrados; Floresta Atlântica; Machine learning; Pampa; Soil carbon prediction. |
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Thesagro: |
Uso da Terra. |
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Thesaurus Nal: |
Land use change. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02772naa a2200337 a 4500
001 2175183
005 2025-04-28
008 2024 bl uuuu u00u1 u #d
022 $a0341-8162
024 7 $ahttps://doi.org/10.1016/j.catena.2024.108219$2DOI
100 1 $aGONÇALVES, D. R. P.
245 $aAccessing and modelling soil organic carbon stocks in Prairies, Savannas, and forests.$h[electronic resource]
260 $c2024
520 $aSoils are the third largest carbon pool on Earth and play a crucial role in mitigating climate change. Therefore, understanding and predicting soil carbon sequestration is of major interest to mitigate climate change globally, especially in countries with strong agricultural backgrounds. In this study, we used a new database composed of 5029 samples collected up to 1-meter depth in three biomes that are most representative of agriculture, Pampas (Prairie), Cerrados (Savanna), and Atlantic Forest (Forest), to explore soil organic carbon (SOC) stocks and its environmental drivers. The Cerrado (Savanna) biome was the only one where croplands presented higher SOC stocks than native vegetation (Native vegetation 121.23 Mg/ha and croplands 127.85 Mg/ha or 5 % higher). From the tested models, the Random Forest outperformed the others, achieving an R2 of 0.64 for croplands and 0.56 for native vegetation. The accuracy of the models varied with soil depth, showing better predictions in shallow layers for croplands and deeper layers for native vegetation. Our results highlight the importance of clay content, precipitation, net primary production (NPP), and temperature as key predictors for soil carbon stocks in the studied biomes. The findings emphasize the importance of protecting the surface layers, especially in the Cerrado biome, to enhance SOC stocks and promote sustainable land management practices. Moreover, the results provide valuable insights for the development of nature-based carbon markets and suggest potential strategies for climate change mitigation. Enhancing our understanding of SOC dynamics and adopting precise environmental predictors will contribute to the formulation of targeted soil management strategies and accelerate progress toward achieving climate goals.
650 $aLand use change
650 $aUso da Terra
653 $aAprendizado de máquina
653 $aAtlantic forest
653 $aCerrados
653 $aFloresta Atlântica
653 $aMachine learning
653 $aPampa
653 $aSoil carbon prediction
700 1 $aINAGAKI, T. M.
700 1 $aBARIONI, L. G.
700 1 $aSCALA JUNIOR, N. L.
700 1 $aCHERUBIN, M. R.
700 1 $aSÁ, J. C. de M.
700 1 $aCERRI, C. E. P.
700 1 $aANSELMI, A.
773 $tCatena$gv. 243, 108219, 2024.
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Embrapa Agricultura Digital (CNPTIA) |
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| 3. |  | ZIMMERMANN, F. J. P. Bases teóricas da estatística experimental. In: MELO, L. C. (ed.). Procedimentos para condução de experimentos de Valor de Cultivo e Uso em feijoeiro comum. Santo Antônio de Goiás: Embrapa Arroz e Feijão, 2009. p. 83-90. (Embrapa Arroz e Feijão. Documentos, 239).| Tipo: Capítulo em Livro Técnico-Científico |
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