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Título : Urban soil management in the strategies for adaptation to climate change of cities in the Tropical Andes
Autor : Bonilla Bedoya, Santiago
Herrera, Miguel Ángel
Vaca, Angélica
Salazar, Laura
Zalakeviciute, Rasa
López Ulloah, Magdalena
Mejía, Danilo
Palabras clave : Climate change
Volcano cities
Urban soils
Soil organic carbon
Adaptation strategies
Fecha de publicación : 2022
Editorial : Scopus
Citación : Santiago Bonilla-Bedoya, Miguel Ángel Herrera, Angélica Vaca, Laura Salazar, Rasa Zalakeviciute, Danilo Mejía, Magdalena López-Ulloa, Urban soil management in the strategies for adaptation to climate change of cities in the Tropical Andes, Geoderma, Volume 417, 2022, 115840, ISSN 0016-7061, https://doi.org/10.1016/j.geoderma.2022.115840.
Citación : PRODUCCIÓN CIENTÍFICA- ARTÍCULOS CIENTÍFICOS;A-IKIAM-000368
Resumen : The unique characteristics of a city amplify the impacts of climate change; therefore, urban planning in the 21st century is challenged to apply mitigation and adaptation strategies that ensure the collective well-being. Despite advances in monitoring urban environmental change, research on the application of adaptation-oriented criteria remains a challenge in urban planning in the Global South. This study proposes to include urban land management as a criterion and timely strategy for climate change adaptation in the cities of the Tropical Andes. Here, we estimate the distribution of the soil organic carbon stock (OCS) of the city of Quito (2,815 m.a.s.l.; population 2,011,388; 197.09 km2) in the following three methodological moments: i) field/laboratory: city-wide sampling design established to collect 300 soil samples (0–15 cm) and obtain data on organic carbon (OC) concentrations in addition to 30 samples for bulk density (BD); ii) predictors: geographic, spectral and anthropogenic dimensions established from 17 co-variables; and iii) spatial modeling: simple multiple regression (SMRM) and random forest (RFM) models of organic carbon concentrations and density as well as OCS stock estimation. We found that the spatial modeling techniques were complementary; however, SMRM showed a relatively higher fit both (OC: r2 = 20%, BD: r2 = 16%) when compared to RFM (OC: r2 = 8% and BD: r2 = 5%). Thus, soil carbon stock (0–0.15 m) was estimated with a spatial variation that fluctuated between 9.89 and 21.48 kg/m2; whereas, RFM showed fluctuations between 10.38 and 17.67 kg/m2. We found that spatial predictors (topography, relative humidity, precipitation, temperature) and anthropogenic predictors (population density, roads, vehicle traffic, land cover) positively influence the model, while spatial predictors have little influence and show multicollinearity with relative humidity. Our research suggests that urban land management in the 21st century provides key information for adaptation and mitigation strategies aimed at coping with global and local climate variations in the cities of the Tropical Andes.
URI : http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/527
ISSN : https://doi.org/10.1016/j.geoderma.2022.115840.
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