Investigating spatial relationships of soil friability and driving factors through co-regionalization with state-space analysis in a subtropical watershed
Introduction
Soil friability is a sensitivity indicator of the structural conditions of a soil, which can be used for assessing the environmental impact of different soil management practices and land uses. Friable soil is desirable to establish a proper seedbed, enable the growth of seedlings and the adequate development of root system (Watts and Dexter, 1998). In this context, friability is considered as an indicator of soil workability, which means the ease with which soil can be treated in order to produce smaller fragments that provide optimum conditions for plant growth (Obour et al., 2019).
Soil friability (F) is a dimensionless parameter that is related to the aggregates’ tendency to fracture at weak points (Dexter and Watts, 2000). While a higher F value indicates the rupture of large and friable aggregates into small and strong aggregates, a low F value is attributed to overall weak aggregates, independent of size. Hence, a higher F indicates suitable aggregate size distribution and better soil aggregation. The occurrence and nature of fractures between aggregates depend on clay mineralogy and organic matter content (Schjønning et al., 2012), the presence of oxides (Imhoff et al., 2002), soil moisture conditions (Utomo and Dexter., 1981), soil porosity (Munkholm et al., 2012), and the adopted soil management practices which can cause compaction by traffic of heavy machines or by grazing which directly affects the soil structural conditions (Avila et al., 2017; Munkholm et al., 2012). As examples, studies carried out by Munkholm and Kay (2002) and Obour et al. (2018) showed that an increase in bulk density due to compaction processes in agricultural and grassland areas tends to decrease F, while Tormena et al. (2008) showed that increasing organic matter content in native forest areas tends to increase friability. However, the mentioned studies focused on the processes at plot scale and thus studied specific sites and cropping systems, limited to temperate and tropical climate conditions (Munkholm and Kay, 2002; Koehn et al., 2014). To the best of our knowledge, no studies have been carried out to assess the spatial relationships among soil friability and its driving factors at watershed scale.
Several methodologies have been developed to make friability measurable from qualitative methods performed in the field through morphological descriptions (Ball et al., 2007; Fao, 2009) to quantitative methods by estimating the tensile strength of the aggregates (Dexter and Kroesbergen, 1985). These methodologies require specialized field skills and sophisticated equipment for determining the soil friability (Munkholm, 2011). Soil friability is mathematically determined through the coefficient of variation of tensile strength values (Dexter and Kroesbergen, 1985). To our knowledge, few models have been developed to estimate soil friability from easily available soil attributes. One of them is the mathematical model developed by Macks et al. (1996) where F is estimated from soil bulk density and soil organic carbon content. However, that multiple linear regression model does not consider the spatial correlation of F and further attributes since it is based on the presupposition that the mean value of each data set is constant through the studied area. According to Nielsen and Alemi (1989), this can lead to the misinterpretation of the outputs when it comes to assess e.g. how soil management practices and land uses affect the spatial variability of soil friability and further attributes at watershed scale.
The state-space model has been widely and successfully applied in many studies at small scales to describe the local spatial association among a response variable and its driving factors (Aquino et al., 2014; She et al., 2014; Duan et al., 2016; Zhang et al., 2017; Qiao et al., 2018; among others). To our knowledge, the performance of state-space models in describing the spatial association of soil friability and its further factors at the watershed scale has not been assessed yet. More specifically, no known study has addressed the influence of soil and topographic attributes and land use systems on the friability of a soil using co-regionalization with state-space analysis. However, this approach could be useful in predicting soil mechanical conditions under adequate soil management practices (plowing, harrowing, sowing and cultivation) and analyzing the effects of different land use systems on the friability of a soil. Therefore, the state-space approach is a promising tool for the description and quantification of soil friability and its influencing factors and its results might be used to help farmers choosing adequate land and soil management.
The study of the Micaela River watershed (MRW) is strategic for the south of the federal state Rio Grande do Sul (RS), Brazil, since the MRW suffers from the impact of human activities and is susceptible to water erosion and floods, causing economic and social damage through the subsequent loss of soil. The MRW is dominated by family farming systems characterized by small production areas under intensive cultivation without crop rotation where the minimum tillage system has been adopted widely. For these regions, plot-scaled information can be tremendously improved by spatially corrected information on soil friability in dependence of land use systems, such as native grassland, native forest, cultivated pasture and cropland. The results then can aid farmers choosing suitable agricultural practices and soil management in order to improve soil structural quality.
Therefore, the objectives of this study were (i) to characterize the spatial variability of friability and further soil (soil total porosity, macroporosity, bulk density and soil organic matter) and topographic attributes (elevation and slope) as well as land use systems across a spatial transect of 11.2 km in length established in the Micaela watershed, Southern Brazil, (ii) to characterize and quantify the spatial relationships of soil friability and co-regionalized factors along the spatial transect using the state-space approach, and (iii) to compare the performance of state-space models with that of corresponding linear and multiple regression models.
Section snippets
Study area
The study was carried out in the Micaela River watershed (MRW) (31°37′50.32″S - 52°31′28.15″W) with an elevation ranging from 33 m to 259 m and a drainage area of 37 km2, located in Pelotas, Rio Grande do Sul, Southern Brazil. This region is characterized by humid subtropical climate (Cfa), according to the Köppen classification (Kuinchtner and Buriol, 2001), with a mean annual rainfall and temperature of 1,386 mm and 17.8 °C, respectively. The main soil types in the MRW were classified by
Exploratory analysis and spatial patterns of data sets
Observed values of soil friability ranged from 0.33 to 0.97 across the 11.2 km- spatial transect in the MRW with a mean value of 0.56 (Fig. 2 and Table 1). Imhoff et al. (2002) proposed a classification for F values as: F < 0.1 = not friable, 0.1–0.2 = slightly friable, 0.2–0.5 = friable, 0.5–0.8 = very friable and F > 0.8 = mechanically unstable. Consequently, the average friability of the 0−0.10 soil layer across the spatial transect was classified as very friable, though close to being a
Conclusions
The highest spatial variability along the transect was found in topographic attributes (soil slope and elevation) and in the soil attributes (clay content, macroporosity and friability - F). All driving attributes showed significant relationship with F, except for the silt content. Total porosity and bulk density showed the strongest positive and negative correlations, respectively.
State-space models (SSM) were shown to be an effective tool for describing the spatial relationships between F and
Declaration of Competing Interest
The authors declare that they have no conflict of interest.
Acknowledgments
We acknowledge and are grateful for the financial support and scholarships provided by the Brazilian National Council for Scientific and Technological Development (CNPq) and the Coordination for the Improvement of Higher Education Personnel - Brazil (CAPES), Finance Code 001, for scholarships.
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