Developing scoring functions to assess soil quality at a regional scale in rangelands of SW Spain

SUMMARYSoil quality integrates the effects of soil physical, chemical and biological attributes. Some of them are dynamic in nature and behave differentially in various agro-ecosystems (AESs) and are quantified in terms of a soil quality index (SQI). An attempt has been made in this paper to develop an SQI based on a minimum data set (MDS), which could be used to evaluate the sustainability of the crop production in three varying AESs in India, namely sub-humid, semi-arid and arid. Thirteen indicators were utilized to develop the SQI from the properties measured from the surface soil layer (0–15 cm). Each indicator of the MDS was transformed into a dimensionless score based on scoring functions (linear and non-linear) and integrated into four SQIs. The weighted non-linear index (WNLI) was identified as the most sensitive for all the AESs and was recommended as an index for future assessments. Based on this index, the quantification of soil quality under several cropping systems was carried out for sub-humid, semi-arid and arid AESs and the most suitable cropping system was identified. WLNI was positively and significantly correlated (R2= 0.79,p< 0.01) with wheat equivalent yield for all the cropping systems. This clearly indicated that the index may be used satisfactorily for quantifying soil quality.

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Soil quality index for paddy fields based on standard scoring functions and weight allocation method

Archives of Agronomy and Soil Science ◽

10.1080/03650340.2019.1610880 ◽

2019 ◽

Vol 66 (3) ◽

pp. 301-315 ◽

Cited By ~ 2

Author(s):

Orhan Dengiz

Keyword(s):

Soil Quality ◽

Quality Index ◽

Paddy Fields ◽

Scoring Functions ◽

Soil Quality Index ◽

Allocation Method ◽

Weight Allocation

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The Impact of Heavy Grazing on Soil Quality and Pasture Production in Rangelands of SW Spain

Land Degradation and Development ◽

10.1002/ldr.2501 ◽

2016 ◽

Vol 29 (2) ◽

pp. 219-230 ◽

Cited By ~ 64

Author(s):

Manuel Pulido ◽

Susanne Schnabel ◽

Joaquín Francisco Lavado Contador ◽

Javier Lozano-Parra ◽

Francisco González

Keyword(s):

Soil Quality ◽

Pasture Production ◽

Sw Spain ◽

Heavy Grazing ◽

The Impact

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Soil Quality and Evaluation of Spatial Variability in a Semi-Arid Ecosystem in a Region of the Southeastern Iberian Peninsula (Spain)

Land ◽

10.3390/land11010005 ◽

2021 ◽

Vol 11 (1) ◽

pp. 5

Author(s):

Fernando Santos-Francés ◽

Antonio Martínez-Graña ◽

Carmelo Ávila-Zarza ◽

Marco Criado ◽

Yolanda Sánchez-Sánchez

Keyword(s):

Organic Carbon ◽

Soil Properties ◽

Soil Quality ◽

Water Retention ◽

Mediterranean Ecosystem ◽

Arid Ecosystem ◽

Scoring Functions ◽

Data Set ◽

Preliminary Estimation ◽

Semi Arid

In the last two decades, as the importance of soil has been recognized as a key component of any ecosystem, there has been an increased global demand to establish criteria for determining soil quality and to develop quantitative indices that can be used to classify and compare that quality in different places. The preliminary estimation of the attributes involved in soil quality was made taking into account the opinion of the experts and our own experience in a semi-arid ecosystem. In this study, 16 soil properties have been selected as potential indicators of soil quality, in a region between Campo de Montiel and Sierra de Alcaraz (Spain): sand and clay percentage, pH, electrical conductivity (EC), soil organic carbon (OC), extractables bases of change (Na, K, Ca and Mg), cationic exchange capacity (CEC), carbonate calcium equivalent (CCE), bulk density (BD), water retention at 33 kPa field capacity and 1500 kPa permanent wither point (GWC33 kPa and GWC1500 kPa), coefficient of linear extensibility (COLE) and factor of soil erodibility (K). The main objective has been to develop an adequate index to characterize the quality of the soils in a semi-arid Mediterranean ecosystem. The preliminary estimation of the attributes involved in soil quality was made considering the opinion of the experts and our own experience in semi-arid ecosystems. Two indicator selection approaches have been used to develop the Soil Quality Index (SQI) (total data set -TDS- and minimum data set -MDS-), scoring functions (linear -L- and nonlinear -NL-) and methods (additive -A-, additive weighted -W- and Nemoro -N-. The quality indices have been calculated, considering the properties of the soil control section (between 0 and 100 cm depth), using 185 samples, belonging to horizons A, B and C of 51 soil profiles. The results have shown that the election of the soil properties, both of the topsoil and subsoil, is an important help in establishing a good relationship between quality, soil functions and agricultural management. The Kriging method has been used to determinate the spatial distribution of the soil quality grades. The indices that best reflect the state of soil quality are the TDS-L-W and TDS-L-A should go as sub-indices, as they are the most accurate indices and provide the most consistent results. These indices are especially indicated when carrying out detailed or semi-detailed studies. However, the MDS-L-W and MDS-L-A should go as sub-indices, which use only a limited number of indicators, are best for large-scale studies. The indicators with the greatest influence on soil quality for different land uses and those developed on different rocks, using linear scoring functions, are the following: (Clay), (GWC1500 kPa) and (Ca). These results can also be expressed as follows: the best soils in this region are deep soils, with a clay texture, with high water retention and a neutral or slightly basic pH. However, the indicators with the greatest influence on soil quality, using nonlinear scoring functions, are: (OC Stock), (Ca) and (CaCO3). In other words, the most important indicator is the organic carbon content, which is not logical in the case of a region in which the soils have an excessively low SOC content (0.86%).

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Selecting indicators for assessing soil quality and degradation in rangelands of Extremadura (SW Spain)

Ecological Indicators ◽

10.1016/j.ecolind.2016.11.016 ◽

2017 ◽

Vol 74 ◽

pp. 49-61 ◽

Cited By ~ 35

Author(s):

Manuel Pulido ◽

Susanne Schnabel ◽

J. Francisco Lavado Contador ◽

Javier Lozano-Parra ◽

Álvaro Gómez-Gutiérrez

Keyword(s):

Soil Quality ◽

Sw Spain

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Provincial soil-quality monitoring networks in the Netherlands as an instrument for environmental protection

Netherlands Journal of Geosciences – Geologie en Mijnbouw ◽

10.1017/s0016774600021922 ◽

2000 ◽

Vol 79 (4) ◽

pp. 429-440 ◽

Cited By ~ 2

Author(s):

E.R.V. Busink ◽

S. Postma

Keyword(s):

The Netherlands ◽

Environmental Protection ◽

Soil Quality ◽

Rural Areas ◽

Regional Scale ◽

Quality Monitoring ◽

Natural Soil ◽

Monitoring Networks ◽

The Individual ◽

Soil Quality Monitoring

AbstractSince 1991, several provinces in the Netherlands have put much effort in establishing soil-quality monitoring networks. The purpose of these networks is to provide insight in the trends in (geochemical) soil quality, on which new policies for environmental protection can be based, such as restrictions in certain landuse types and cleaner production processes. The soil quality networks are yet too young to serve this goal. Monitoring efforts are concentrated on micro- and macro-elements, particularly in the top layer of the soil (mainly heavy metals and PAH) as well as phreatic groundwater (mainly nitrates and phosphates) in the various regions of a province. The regional soil-quality monitoring networks focus explicitly on diffuse environmental pollution in the rural areas, which means that sample sites influenced by soil pollution caused by local sources are excluded. Regional differences in soil quality in the rural areas are primarily caused by chemical and physical differences in the natural soil composition and by differences in deposition loads (direct and indirect). Hydrological conditions can also exert a large influence, particularly for nitrate leaching. This leads to three major criteria which the network design is based upon: (1) soil type, (2) landuse (assumed to be representative for deposition), and (3) groundwater tables. Subregions are formed by combining these criteria. Subregions are considered to be more or less homogeneous at a regional scale with respect to the criteria named. Within each region, a pre-calculated number of sites, based on variability of present concentrations, have been sampled and the sample material has been analyzed. Descriptive statistical parameters could thus computed; they are the base for the geochemical soil mapping of the individual, homogeneous subregions.A recent evaluation of all operational soil-quality monitoring networks shows that these networks are effective instruments to gain insight into the differences in quality of the soil and the phreatic groundwater between the various regions. The understanding of these differences and the processes that caused them provide the provincial authorities with valuable information for policy making and environmental management. The evaluation also reveals differences in network designs, mostly due to local differences in physical-chemical properties and political choices.It can be concluded from the first results of the networks that the relative high loads of zinc and copper, caused by spreading manure on the farmlands in areas of intensive agricultural landuse, have led to notably higher concentrations of these elements in the top layer of the soil compared to more natural lands like forested areas. The fact that the intensive agricultural landuse is mainly situated on relatively highly permeable sandy soils results in high nitrate concentrations in the phreatic groundwater, up to concentrations far beyond EG drinking-water target levels. First monitoring results signalled several environmental problems of which most of the policy makers were already aware, but could not quantify. Delineation of the most vulnerable areas and/or areas with unacceptably high loads and quantification of concentrations of different elements enable regional governments to take appropriate measures.The soil-quality monitoring networks will focus in the coming years on the effectiveness of the measures taken in the various areas. Efforts are being made to integrate the relatively new soil-quality monitoring networks and the longer existing groundwater-quality monitoring networks to achieve a better understanding of the (bio)geochemical cycling processes. Tuning the individual regional soil-quality monitoring networks of the various provinces will enable the provision of additional information about soil quality at a larger scale.

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