Influence of high Andean grasslands on landslide reduction in Peru
Agricultural and urban expansion has caused considerable degradation of ecosystems. In the case of Peruvian high Andean grasslands, it was reported that between 2000 and 2009, this ecosystem was reduced by 7%. The limited or no protection they receive is partly due to the fact that the benefits of e...
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| Format: | Article |
| Language: | English |
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Universidad Nacional de Trujillo
2024-09-01
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| Series: | Scientia Agropecuaria |
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| Online Access: | https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5415 |
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| author | Albert Franco Cerna-Cueva Katherin Lourdes Uriarte-Barraza Grecia Isabel Lobatón-Tarazona Wensty Saenz-Corrales Casiano Aguirre-Escalante Peter Coaguila-Rodriguez Manuel Reategui-Inga |
| author_facet | Albert Franco Cerna-Cueva Katherin Lourdes Uriarte-Barraza Grecia Isabel Lobatón-Tarazona Wensty Saenz-Corrales Casiano Aguirre-Escalante Peter Coaguila-Rodriguez Manuel Reategui-Inga |
| author_sort | Albert Franco Cerna-Cueva |
| collection | DOAJ |
| description | Agricultural and urban expansion has caused considerable degradation of ecosystems. In the case of Peruvian high Andean grasslands, it was reported that between 2000 and 2009, this ecosystem was reduced by 7%. The limited or no protection they receive is partly due to the fact that the benefits of ecosystem services are not widely known. This research aims to establish and predict the influence of high Andean grasslands on the annual occurrence of landslides. To do so, we identified occurrences of landslides, falls, huaycos, avalanches, and alluviums in high Andean grasslands. We also examined urban areas and agricultural zones of Peru for the period from 2003 to 2016. Subsequently, we extracted data on precipitation, temperature, slopes, soil types, and geographical variables. This data was used to train a machine learning model. The results show that 96% of landslides occurred in human-intervened areas, and only 4% in high Andean grasslands. Precipitation and slope thresholds for landslide occurrence are higher in high Andean grasslands compared to agricultural and urban areas. The best-performing machine learning models were linear regression, Gaussian processes, random forest, and support vector machine. They had coefficients of determination of R² = 0.80, 0.80, 0.66, and 0.64, respectively. Predictions show that if agricultural or urban areas are established in wet or dry puna grasslands, the average number of occurrences multiplies. The multiplier factors are 2.1 and 7.08, the number of deaths by 2.8 and 10.49, the number of houses destroyed by 2.4 and 7.51, and the number of roads destroyed by 2.2 and 7.37, respectively. The study demonstrates that conserving high Andean grasslands significantly reduces landslides compared to urban or agricultural areas. |
| format | Article |
| id | doaj-art-79ebe056cba44ec59a7684b54c13c2ae |
| institution | DOAJ |
| issn | 2077-9917 2306-6741 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Universidad Nacional de Trujillo |
| record_format | Article |
| series | Scientia Agropecuaria |
| spelling | doaj-art-79ebe056cba44ec59a7684b54c13c2ae2025-08-20T02:49:05ZengUniversidad Nacional de TrujilloScientia Agropecuaria2077-99172306-67412024-09-01153333348https://doi.org/10.17268/sci.agropecu.2024.025Influence of high Andean grasslands on landslide reduction in PeruAlbert Franco Cerna-Cueva0https://orcid.org/0000-0001-7448-558XKatherin Lourdes Uriarte-Barraza1https://orcid.org/0000-0001-7450-5528Grecia Isabel Lobatón-Tarazona2https://orcid.org/0000-0002-8567-0606Wensty Saenz-Corrales3https://orcid.org/0000-0001-8160-5033Casiano Aguirre-Escalante4https://orcid.org/0000-0002-6109-4237Peter Coaguila-Rodriguez5https://orcid.org/0009-0002-2117-5240Manuel Reategui-Inga6https://orcid.org/0000-0002-5417-6509Escuela Profesional de Ingeniería Ambiental, Universidad Nacional Agraria de la Selva, Perú.Escuela Profesional de Ingeniería Ambiental, Universidad Nacional Agraria de la Selva, Perú.Escuela Profesional de Ingeniería Ambiental, Universidad Nacional Agraria de la Selva, Perú.Escuela Profesional de Ingeniería Ambiental, Universidad Nacional Agraria de la Selva, Perú.Escuela Profesional de Ingeniería en Recursos Naturales Renovables, Universidad Nacional Agraria de la Selva, Perú.Escuela Profesional de Ingeniería en Recursos Naturales Renovables, Universidad Nacional Agraria de la Selva, Perú.Escuela Profesional de Ingeniería Ambiental, Universidad Nacional Intercultural de la Selva Central Juan Santos Atahualpa, Perú.Agricultural and urban expansion has caused considerable degradation of ecosystems. In the case of Peruvian high Andean grasslands, it was reported that between 2000 and 2009, this ecosystem was reduced by 7%. The limited or no protection they receive is partly due to the fact that the benefits of ecosystem services are not widely known. This research aims to establish and predict the influence of high Andean grasslands on the annual occurrence of landslides. To do so, we identified occurrences of landslides, falls, huaycos, avalanches, and alluviums in high Andean grasslands. We also examined urban areas and agricultural zones of Peru for the period from 2003 to 2016. Subsequently, we extracted data on precipitation, temperature, slopes, soil types, and geographical variables. This data was used to train a machine learning model. The results show that 96% of landslides occurred in human-intervened areas, and only 4% in high Andean grasslands. Precipitation and slope thresholds for landslide occurrence are higher in high Andean grasslands compared to agricultural and urban areas. The best-performing machine learning models were linear regression, Gaussian processes, random forest, and support vector machine. They had coefficients of determination of R² = 0.80, 0.80, 0.66, and 0.64, respectively. Predictions show that if agricultural or urban areas are established in wet or dry puna grasslands, the average number of occurrences multiplies. The multiplier factors are 2.1 and 7.08, the number of deaths by 2.8 and 10.49, the number of houses destroyed by 2.4 and 7.51, and the number of roads destroyed by 2.2 and 7.37, respectively. The study demonstrates that conserving high Andean grasslands significantly reduces landslides compared to urban or agricultural areas.https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5415high andean grasslandslandslidemachine learningecosystem servicesclimate change |
| spellingShingle | Albert Franco Cerna-Cueva Katherin Lourdes Uriarte-Barraza Grecia Isabel Lobatón-Tarazona Wensty Saenz-Corrales Casiano Aguirre-Escalante Peter Coaguila-Rodriguez Manuel Reategui-Inga Influence of high Andean grasslands on landslide reduction in Peru Scientia Agropecuaria high andean grasslands landslide machine learning ecosystem services climate change |
| title | Influence of high Andean grasslands on landslide reduction in Peru |
| title_full | Influence of high Andean grasslands on landslide reduction in Peru |
| title_fullStr | Influence of high Andean grasslands on landslide reduction in Peru |
| title_full_unstemmed | Influence of high Andean grasslands on landslide reduction in Peru |
| title_short | Influence of high Andean grasslands on landslide reduction in Peru |
| title_sort | influence of high andean grasslands on landslide reduction in peru |
| topic | high andean grasslands landslide machine learning ecosystem services climate change |
| url | https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/5415 |
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