A Pedotransfer Function to Map Soil Bulk Density from Limited Data

Rodríguez‐Lado, Luis; Rial, Marcela; Rodríguez, Teresa Taboada; Cortizas, Antonio Martı́nez

doi:10.1016/j.proenv.2015.07.112

Cited by 31 publications

(19 citation statements)

References 12 publications

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“…2016 DOI: 10.1590/S0100-204X2016000900041 área e é, portanto, obrigatória para comparar diferentes tipos de uso do solo, quanto ao potencial de sequestro de carbono (Brahim et al, 2012). Além disso, Ellert et al (2002) (Benites et al, 2007;Suuster et al, 2011;Brahim et al, 2012;Carvalho Junior et al, 2013;Nanko et al, 2014;Nasri et al, 2015;Rodríguez-Lado et al, 2015). Assim, os modelos estatísticos têm sido amplamente empregados para estimar o valor de algum atributo, ao invés de realizar a análise propriamente dita.…”

Section: Introductionunclassified

Regressão linear múltipla e modelo Random Forest para estimar a densidade do solo em áreas montanhosas

Carvalho

Filho

Chagas

et al. 2016

Pesq. agropec. bras.

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Resumo -O objetivo deste trabalho foi o desenvolvimento de modelos com diferentes conjuntos de dados, para estimar a densidade de solos de regiões tropicais montanhosas, a partir de atributos de solos comumente encontrados nas análises de perfis de solos descritos nos levantamentos regionais. O conjunto total de dados compõe-se de 163 amostras e foi dividido em seis grupamentos, dos quais três com 73 amostras, com o máximo de 32 covariáveis, e três com 163 amostras, com o máximo de 18 covariáveis. Testaram-se modelos de regressão linear múltipla (RLM) e randomForest (RF). A menor incerteza entre os modelos foi alcançada pelo RLM2, com R 2 de 0,56, 13 covariáveis e 73 amostras. Nos grupamentos com 163 amostras, os melhores modelos foram os RF, com R 2 médio de 0,48. A raiz quadrada da média do erro ao quadrado variou entre 0,09 e 0,14. As covariáveis mais importantes no modelo RF foram: carbono orgânico, hidrogênio, areia fina e grossa, saturação por bases e capacidade de troca catiônica. Pelo método "stepwise regression", as variáveis mais importantes foram: a relação silte/argila; areia grossa e fina; carbono orgânico; saturação por bases; e potássio.Termos para indexação: estoque de carbono, funções de pedotransferência, modelos dirigidos pelos dados, stepwise. Multiple linear regression and Random Forest model to estimate soil bulk density in mountainous regionsAbstract -The objective of this work was the development of models with different sets of data for estimating soil bulk density in tropical mountainous regions, from soil attributes commonly found in the analyses of soil profiles described in regional surveys. The complete dataset is composed of 163 samples and it was divided into six groups, of which three groups have 73 samples and the maximum of 32 covariables, and three have 163 samples and the maximum of 18 covariables. The linear regression (RLM) and randomForest (RF) models were tested. The lowest uncertainty between the models was achieved by RLM2, with R 2 of 0.56, 13 covariables, and 73 samples. Considering the groups with 163 samples, the best models were the RFs with mean R 2 of 0.48. The root mean squared error ranged between 0.09 and 0.14. The most important covariables in the RF model were: organic carbon, hydrogen, fine and coarse sand, base saturation, and cation exchange capacity. By the stepwise backward regression, the main covariables were: silt and clay relation; fine and coarse sand; organic carbon; base saturation; and potassium.

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Section: Introductionunclassified

Regressão linear múltipla e modelo Random Forest para estimar a densidade do solo em áreas montanhosas

Carvalho

Filho

Chagas

et al. 2016

Pesq. agropec. bras.

View full text Add to dashboard Cite

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“…Additionally, these changes enable insects to escape regulation by their natural enemies [31]. Soil bulk density is a key soil parameter that is directly related to many soil properties and processes, including porosity, soil moisture, and erodibility [32]. Soil bulk density can be estimated from the organic matter content of soil, because these variables are negatively correlated [33].…”

Section: Discussionmentioning

confidence: 99%

Stand Characteristics and Soil Properties Affecting the Occurrence of Kunyushan Web-Spinning Sawfly (Cephalcia kunyushanica Xiao) in Japanese Red Pine (Pinus densiflora) Pure Forests in the Kunyushan Mountains, China

Ruirui

Liang

Xie

et al. 2018

Forests

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: The Kunyushan web-spinning sawfly (Cephalcia kunyushanica) is a major pest in the Japanese red pine (JRP, Pinus densiflora) pure forests in the Kunyushan Mountains of China. In this study, four stand types (ST1–4) were identified in plots of JRP pure forests, based on the pest severity index (PSI; ranging from 0–100). The order of infestation ratio in the four type stands was as follows: ST4 > ST3 > ST2 > ST1. We investigated the correlation of C. kunyushanica occurrence with stand characteristics and soil physicochemical properties in the four stand types. The results showed that all stand characteristics were different among the four stand types. Compared with infested plots, healthy (ST1) plots had a higher soil bulk density, and the differences among the groups were significant. Differences in soil water content, non-capillary porosity, and total porosity were significant among the four ST groups. The average organic matter content, total nitrogen (N), and available N were lower in ST1 plots, whereas total potassium (K) was higher compared with other ST groups. In addition, a redundancy analysis suggested that seven (total N, diameter at breast height (DBH), soil water content, bulk density, available K, zinc ion (Zn2+), and stem density) of 24 environmental variables were significantly correlated with the ordinations of C. kunyushanica occurrence. The results provide theoretical guidance for the ecological control of C. kunyushanica, and are also useful for the management of forests in areas where C. kunyushanica is a major pest and where site and stand conditions are similar.

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“…Due to the practical constraints, the BD samples were not available for the 100–500 cm soil layers. Considering that the BD and SOC were significant correlated (Conforti, Lucà, Scarciglia, Matteucci, & Buttafuoco, ; Telles et al, ), we established pedotransfer functions using SOC as a predictor of soil BD at 0–100 cm (Figure S2; Benites, Machado, Fidalgo, Coelho, & Madari, ; Rodríguez‐Lado, Rial, Taboada, & Cortizas, ); then, we used the SOC content in the 100–500 cm layer to estimate the soil BD for the 100–500 cm soil depth.…”

Section: Methodsmentioning

confidence: 99%

Shrub encroachment increases soil carbon and nitrogen stocks in temperate grasslands in China

Shen

Zhou

et al. 2019

Land Degrad Dev

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Shrub encroachment has significant impacts on carbon (C) and nitrogen (N) dynamics of grassland ecosystems, but, how it influences soil organic C (SOC) and soil total N (STN) stocks of grasslands is not well documented, especially in deep soils. Here, we examined these effects by investigating the SOC density (SOCD) and the STN density (STND) at depths of up to 5 m in shrub patches and grassy matrix at 18 grassland sites in Inner Mongolia, China. Our results revealed that 44.0–54.1% of SOC and 65.5–74.8% of STN were stored in soil layers of 100 cm to 500 cm, and that shrub encroachment resulted in a significant accumulation of SOC and STN in shrub patches. The mean SOCD at 0–500 cm soil layers in shrub patches and grassy matrix was 11.34 and 8.39 kg C m−2, respectively, and the mean STND was 2.45 and 2.13 kg N m−2, respectively. These differences between the shrub patches and grassy matrix were equivalent to an increase in the mean SOC and STN stocks of 2.95 kg C m−2 and 0.32 kg N m−2, respectively. Increases in SOCD and STND mainly occurred in 30–300 cm soil layers, and varied between typical grassland and desert grassland. The changes in SOCD and STND exhibited significant negative correlations with temperature and pH and positive correlations with precipitation and plant biomass. Our findings suggest that shrub encroachment can significantly accumulate SOC and STN in deep soils in temperate grasslands, which helps to understand soil C and N dynamics in shrub‐encroached grasslands.

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A Pedotransfer Function to Map Soil Bulk Density from Limited Data

Cited by 31 publications

References 12 publications

Regressão linear múltipla e modelo Random Forest para estimar a densidade do solo em áreas montanhosas

Regressão linear múltipla e modelo Random Forest para estimar a densidade do solo em áreas montanhosas

Stand Characteristics and Soil Properties Affecting the Occurrence of Kunyushan Web-Spinning Sawfly (Cephalcia kunyushanica Xiao) in Japanese Red Pine (Pinus densiflora) Pure Forests in the Kunyushan Mountains, China

Shrub encroachment increases soil carbon and nitrogen stocks in temperate grasslands in China

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