Cladistic analysis of Chinese Soil Taxonomy

Geoderma Regional 10 (2017) 11–20

Contents lists available at ScienceDirect

Geoderma Regional journal homepage: www.elsevier.com/locate/geodrs

Cladistic analysis of Chinese Soil Taxonomy J. Huang ⁎, M.C. Ebach, J. Triantafilis Palaeontology, Geobiology and Earth Archives Research Centre (PANGEA), School of Biological, Earth and Environmental Sciences, UNSW Sydney, Kensington, NSW 2052, Australia

a r t i c l e

i n f o

Article history: Received 10 March 2016 Received in revised form 17 February 2017 Accepted 21 March 2017 Available online 22 March 2017 Keywords: Natural classification Pedogenesis Soil genesis Genetic soil classification Soil taxonomy World reference base Spodosols Andosols Gleyosols Isohumosols Aridisols Cambosols

a b s t r a c t This study attempts to revise the search for natural groups and soil properties in Chinese soils based on the ideas of biological classification and soil genesis. Previous attempts at natural soil classification include the former Russian genetic soil classification, which classifies soils mainly based on soil forming factors. These attempts had resulted in classifications not ideally suited to soil identification. The US Soil Taxonomy (ST), however, has moved away from natural classifications and towards a robust key-based classification to identify soil Orders and groups. The current Chinese Soil Taxonomy (CST) system follows the ST. However, it remains unknown if the CST contains part of a natural classification (i.e. homologous properties or monophyletic groups). In this study, cladistics analysis was used to assess the 14 soil Orders and 39 Suborders of the CST using 44 morphological and numeric soil properties. Results show that it consists of a number of non-monophyletic groups. In order to test for monophyletic (i.e., natural) soil properties, all the non-homologous properties (e.g., moisture regimes, Mollic epipedon, Hydragric horizon) and numerical properties (e.g., n value and base saturation), were removed. The results indicated, Spodosols, Andosols, Gleyosols and Isohumosols Orders and Udic Vertosols and Anthric Primosols Suborders were more closely related to each other and may suggest a potential Superorder of mountainous and humid soils. Similarly, closely related Aridisols and Cambosols may indicate a potential Superorder of arid soils. However, some non-monophyletic Orders (e.g., Vertosols, Primosols) need revising based on their parent materials. Several aphyletic Orders (e.g., Anthrosols, Ferrosols, and Halosols) were identified due to insufficient information, which suggests additional morphological properties (e.g. pH) or other soil forming factors should be considered. We conclude that cladistic analysis can be also applied to extract information from the Russian soil classification, the ST and the World Reference Base to provide guidance for establishing a world-wide natural soil classification scheme. © 2017 Elsevier B.V. All rights reserved.

1. Introduction The underlying foundations of natural classification have undergone a reformation during the 1970s and 1980s, in which a new form classification, called cladistics, was formulated (Nelson and Platnick, 1981; Williams and Ebach, 2007). The reformation was a response to the Modern Synthesis and the notion that natural classification was “essentialist” in its pursuit of idealistic taxonomic groups (herein taxa) that were based on uniquely shared characteristics (Cain, 1958; Mayr, 1968). The rise of essentialism led many biologists to reject taxonomic groups in favor of fluid or dynamic populations in which no hard boundaries between species or genera existed (Winsor, 2003). However, phylogenetic systematics (i.e. cladistics) showed that any stable or fluid population may be represented by shared derived characteristics to find hard boundaries between taxa in a hierarchical classification (Hennig, 1966). This is because cladistics has the ability to discover

⁎ Corresponding author. E-mail address: [email protected] (J. Huang).

http://dx.doi.org/10.1016/j.geodrs.2017.03.001 2352-0094/© 2017 Elsevier B.V. All rights reserved.

informative characteristics (i.e., properties) and taxonomic groups within a natural system. However, by the time the cladistic revolution had begun, the US Soil Taxonomy (1951) had established itself on the essentialism story in which “we carefully hid most of our assumptions about the genesis of the various diagnostic properties that are used in classifying soil. This was hidden to prevent the freezing of the taxonomy into a sterile system based on some genetic assumptions that might or might not be correct” (Smith, 1986: 16). Although the “final” version of US Soil Taxonomy that was published in 1975 showed a subtle shift back towards the factorial-genetic approach of soil classification as compared to the 7th Approximation published in 1960 (Bockheim et al., 2014), the decision of making US Soil Taxonomy less cladistic had led to previous natural classification systems to be shelved (e.g., Marbut, 1951; Basinski, 1959). This occurred even though both philosophers and evolutionary biologists have rejected the essentialism story since the 1970s due to historical and logical inaccuracies (Winsor, 2006a,b). One of the earliest natural classifications of soil was espoused by Russian pedologists who placed importance on soil forming factors, such as climate (Dokuchaev, 1879, 1893; Sibirtzev, 1895), and parent

12

J. Huang et al. / Geoderma Regional 10 (2017) 11–20

material (Glinka, 1914) and various pedogenetic (Glinka, 1924) processes (e.g., lateritic, podzolic). Given the capability of the Russian system to account for genetic processes and inter-relationships, these ideas were adopted by soil scientists from Western Europe (e.g., Ramann, 1918; Robinson, 1932) and North America (e.g., Coffey, 1912; Marbut, 1927). Alternatively, Baldwin et al. (1938) and later Riecken and Smith (1949) and Thorp and Smith (1949), aimed at sorting soil using diagnostic horizons and features. Because of the emphasis placed on characteristic horizons and sequences, the Soil Taxonomy (ST) was developed (Soil Survey Staff, 1975). Soil classification in China has a longer history. Some four thousand years ago, the Chinese classified their soils based on properties like fertility, color, texture, moisture and vegetation and as a basis for tax assessment (Lee, 1921; Gong et al., 2003). The modern history of Chinese soil classification can be divided into three distinct eras: 1) 1930s to 1950s - Marbut system in combination with experiences from local soil scientists; 2) 1950s to 1980s - the genetic soil classification of China (GSCC) based on the soil classification system of the Soviet Union; and, 3) post 1980s - the Chinese Soil Taxonomy (CST) based on the ST. Although Chinese have changed their soil classification from a qualitative (i.e., GSCC) to a quantitative scheme (i.e., CST), both are still in use because of the extensive knowledge and experience accumulated in association with GSCC (Shi et al., 2006a,b). Due to the rapid industrial developments and economic growth of China, increasing concerns have arisen with regard to the deteriorating environment, especially the nation-wide pollution of air (e.g., Chan and Yao, 2008), water (e.g., Qu and Fan, 2010) and soil (e.g., Wei and Yang, 2010; Li et al., 2014). As such, mapping Chinese soil is required for securing the resource for sustained agricultural and ecological benefits (McBratney et al., 2014) or as a contribution to the international collaboration for global environmental protection (e.g., Global Digital Soil Property Map project, Minasny and McBratney, 2010). To assist and improve soil mapping in China, the CST system has been widely used to map carbon (e.g., Yu et al., 2007; Shi et al., 2015) and salinity (e.g., Sheng et al., 2010) as well as class identification and prediction (e.g., Zhu et al., 2010; Sun et al., 2011). However, compared with the extensive research using the CST system to map Chinese soil, the CST has been little studied from a perspective of a natural classification. The benefit of a natural classification is that it is predictive, meaning that soil of other areas would ideally fit into an existing classification without any revision (Williams and Ebach, 2007). However, a natural soil classification would require far greater knowledge of soil genesis and may not necessarily be ideal for use by non-specialists. As such, non-natural classification is widely used as they are generally easier for a non-soil scientist, such as an end-user, to identify soil types in the field (Williams and Ebach, 2007). In addition, a natural soil classification is essential for soil management studies, as a non-natural classification scheme would not necessarily reflect the real world (i.e., classifying soil based on morphological descriptions rather than soil genesis) and could lead to ineffective management decisions for soil use and remediation. Cladistic analysis is a method developed in biological classification (systematics) to test for a natural classification. However, cladistic analysis has been successfully used in various fields other than biology, such as transmission and spread of folktales in Indo-European-speaking societies (da Silva and Tehrani, 2016) and formation and evolution (Fraix-Burnet, 2009) and classification (Fraix-Burnet et al., 2003) of galaxies. It searches for monophyly, namely when two or more taxa (e.g., soil Orders) are more closely related to each other than to any other. The presence of monophyly supports a natural classification (Hennig, 1966; Williams and Ebach, 2007). Properties that support a monophyletic classification are termed homologous and are informative (Williams and Ebach, 2007). Similar to the evolution of plants or animals from common ancestry, spread of folktales and evolution of galaxies, presence of homologous soil properties and the resulting monophyletic classification will confirm the process of soil genesis

and will be objective and robust (Buol et al., 2011). Recently, Miltenyi et al. (2015) used cladistics to test the Australian soil classification (ASC) system for natural soil properties, that is, to test whether it is part of a natural classification. They found it is mostly artificial. While the ASC was an excellent system for identifying soils, it did not indicate the natural relationship between soil taxa. If a classification system is not natural, the addition of new soil types may change the whole taxonomy. For example, Anthrosols were added to the CST system that did not exist in the CT system while the Ferrosols of the CST system were not directly comparable to any soil Orders of the CT system (Gong et al., 1999). In addition, most national soil classification systems are often not applicable to other countries, leading to difficulty in communication. To solve the problem, extensive but not wholly satisfactory studies have been conducted to cross-reference different classifications (e.g., Shi et al., 2006a,b; Krasilnikov et al., 2009; Shi et al., 2010) or to develop universal classifications such as US Soil Taxonomy and World Reference Base for Soil Resources (IUSS Working Group, 2006). By using cladistic analysis, it may be possible to create a universal soil classification. Given the successful application of cladistics analysis in the ASC (Miltenyi et al., 2015), we use a similar cladistic analysis to identify any natural elements within the CST. The aims of this study are threefold; 1) to assess if CST contains natural soil properties or soil Orders (i.e., monophyly) 2) if so, what relationship between different soil Orders can be deducted from the cladistics analysis; 3) if not, what should be done to develop an independent Chinese natural soil classification scheme for the purposes of investigating soil genesis? 2. Materials and methods 2.1. Chinese Soil Taxonomy The Chinese Soil Taxonomy (CST) is a hierarchical system, comprising six categories, namely; Orders, Suborders, Groups, Subgroups, Family and Series. It is a system based on 33 diagnostic horizons and 25 diagnostic properties (Gong et al., 2001). The study includes 40 properties from CST, which are the diagnostic horizons and diagnostic properties identified in 14 soil Orders and 39 Suborders of CST. The 14 soil Orders are listed in Table 1 and in the order in which they appear in the CST, including; Histosols, Anthroposols, Spodosols, Andosols, Ferralosols, Vertosols, Aridisols, Halosols, Gleysols, Isohumosols, Ferrosols, Argosols, Cambosols, Primosols. In addition, the 39 Suborders of the CST are included in Table 1; for example Permagelic and Orthic for the Histosols. Table 1 also shows a summary of the description of the soil Orders (following Gong et al., 2001). The large number of soil properties in classifying soil Groups make it time-consuming to include all categories of the CST in a cladistic analysis. In addition, important properties (e.g., major soil forming factors and controlling factors) are located in the upper categories (Gong et al., 2001; Isbell, 2002). Therefore, we limited the cladistic analysis to the Suborder level. 2.2. Types of soil properties and conversion of composite properties All 40 soil properties were assessed for morphological, numeric and potentially non-homologous states. Morphological properties consist of observable structures or qualities (e.g., Spodic horizon, Gleyic features, Isohumic or Andic properties). Numeric properties are quantitative. Examples of numeric properties include n value which indicates the ratio of water in the soil associated with different soil textures (b0.7 or ≥ 0.7), and subhorizon organic carbon (b60 g/kg or 60 g/kg). Both morphological and numeric values have been determined empirically and reflect practical knowledge about soil use and management. However, they do not necessarily lead to a natural classification and need to be assessed using the cladistic analysis.

J. Huang et al. / Geoderma Regional 10 (2017) 11–20

13

Table 1 Summary of soil Orders and soil Suborders of Chinese Soil Taxonomy (CST) (from Gong et al., 2001). Order

Characteristics

Suborder

Histosols Anthrosols Spodosols

High amounts of organic matter accumulation under conditions of wetness or low temperature. Properties induced in soil subsequent to long-term management of soil for agricultural or other uses. Illuvial accumulation of organic matter with or without associated accumulation of iron and aluminium in humid environments. Weathering and mineral transformation resulting in dominance of short-range order minerals from volcano-clastic materials. Weathering resulting in loss of weatherable minerals and accumulation of colloids comprising 1:1 alumino-silicate minerals and associated iron and aluminium oxihydrates. Development of shear stresses due to swell/shrink of smectitic materials in alternating wet/dry conditions. Development of soils under dry conditions, present or past. Accumulation of salts and alkalis in soils under influence of ground water or dry environments. Development of redoximorphic conditions under a permanent of fluctuating water-table Deep accumulation of humus under cool temperatures. Weathering and soil formation leading to lower (sub-medium) activity colloids or with mixed clay mineralogy. Illuvial accumulation of clays in soils with medium activity clays. Low grade soil development, with formation of horizon of alteration or weak expression of other diagnostic horizons. Recent soils with no diagnostic horizons or only an ochric epipedon,

Permagelic; Orthic Stagnic; Orthic Humic; Orthic

Andosols Ferralosols Vertosols Aridisols Halosols Gleyosols Isohumosols Ferrosols Argosols Cambosols Primosols

Among all the 40 soil properties we identified five properties, which have multiple property-states. These are called composite properties. Table 2 shows these along with their original states and including organic soil materials, soil moisture regimes, soil temperature regimes, lithologic properties and base saturation. For example, organic soil materials have five property-states (i.e., Fibric, Hemic, Sapric, Folic, and Mattic). Table 2 also shows how we have converted these composite properties to reduce the number of property-states. With regard to the organic soil materials we simply converted the composite property-state from 5 to 2 (i.e., absent/present) by simply considering whether or not organic matter was present. With respect to the soil moisture regime we split this property into two (i.e., dry and wet) and then into a few property-states (e.g., absent/Ustic/Udic for the dry regime). With respect to the soil properties of soil temperature regime and base saturation we similarly reduced the number of property-states. For the soil temperature regime, which we now call cold temperature regimes, we converted this to three states: absence (0), Permagelic (1) and Cryic and Frigid (2) temperature regimes. For base saturation, the property-state was binary: b 50% (0) and N50% (1). The last series of composite properties involved splitting the lithologic properties into three properties and including; particle size fraction; lithologic and alluvial properties. We have also added a property of sub-horizon organic carbon because it is used to differentiate Humic and Orthic Spodosols. The converted properties and their original forms are shown in Table 2. It is worth noting that the conversion process will

Cryic; Vitric; Udic Udic Aquic; Ustic; Udic Cryic; Orthic Alkalic; Orthic Permagelic; Stagnic; Orthic Lithomorphic; Ustic; Udic Ustic; Perudic; Udic Boric; Ustic; Perudic; Udic Gelic; Aquic; Ustic; Perudic; Udic Anthric; Sandic; Alluvic; Orthic

not affect the original CST system because we do not add or remove any classification criteria to the system. 2.3. Property description After converting the composite properties, there were a total of 44 properties. To undertake a cladistic analysis, the 44 morphological and non-morphological properties identified need to be coded into binary or multiple property-states. For most properties, coding is binary “absent” (0) or “present” (1), however all properties are ordered and polarised, meaning that the binary coding 0 and 1 should be interpreted as a hypothetical hierarchical relation of (0(1,1)), and 0, 1 and 2 as (0,(1,(2)). All properties and their states are denoted in square brackets (e.g., [32:1]). Single properties are denoted as single numerals (e.g., [35]). The 44 soil properties and their states (based on Gong et al., 2001) are described as follows. [1] Histic epipedon: organic epipedon in mineral soil (States: 0 – absent; 1 – present). [2] Mollic epipedon: dark colored, well structured, humic epipedon with high base saturation (N50%) and high or relatively high organic carbon content (0 – absent; 1 – present). [3] Umbric epipedon: dark colored, humic epipedon with low to intermediate base saturation (b 50%) and high or relatively high organic carbon content (0 – absent; 1 – present).

Table 2 Summary of converted composite properties and their original forms. Original character

Original character state

Converted character

Converted character state

State value

Organic soil materials Soil moisture regimes

Fibric/Hemic/Sapric/Folic/Mattic Ustic/Udic/Perudic/Stagnic/Aquic Ustic/Udic/Perudic/Stagnic/Aquic Permagelic/Gelic/Cryic/Frigid/Mesic/Thermic/Hyperthemic Alluvial deposits/sandy deposits/loess and loess-like deposits/purplish sandstones and shales/red sandstones, shales and conglomerates, and northern red earths/carbonate rocks Alluvial deposits/sandy deposits/loess and loess-like deposits/purplish sandstones and shales/red sandstones, shales and conglomerates, and northern red earths/carbonate rocks Alluvial deposits/sandy deposits/loess and loess-like deposits/purplish sandstones and shales/red sandstones, shales and conglomerates, and northern red earths/carbonate rocks Eutric/dystic or eutrophic/dystrophic N.A.

Organic soil materials Dry soil moisture regimes Wet soil moisture regimes Cold temperature regimes Particle size fraction

Absent/present Absent/Ustic/Udic Absent/Perudic/Stagnic/Aquic Absence/Permagelic/Cryic and Frigid Finer than silt loam/coarser than silt loam

0/1 0/1/2 0/1/2/3 0/1/2 0/1

Lithologic characters

Absent/carbonate rocks

0/1

Alluvial characters

Absent/Alluvial deposits/Sandy deposits

0/1/2

Base saturation Subhorizon organic carbon

b50%/Over 50% b60 g/kg/Over 60 g/kg

0/1 0/1

Soil temperature regimes Lithologic characters (L.C.)

Base saturation N.A.

14

J. Huang et al. / Geoderma Regional 10 (2017) 11–20

[4] Siltigic epipedon (Irragric epipedon): anthropic epipedon consists of irrigation-silting from long-term application of sediment-rich irrigation water (0 – absent; 1 – present). [5] Cumulic epipedon: anthropic epipedon from application of large amount of earthy manure and compost, or pond mud, and mellowing by cultivation (0 – absent; 1 – present). [6] Fimic epipedon: anthropic epipedon with high degree of mellowing from planting vegetables and applying large amount of human and animal excreta, manures, organic garbage, miscellaneous manure, under intensive cultivation and frequent irrigation (0 – absent; 1 – present). [7] Anthrostagnic epipedon (Hydragric epipedon): anthropic epipedon formed under submerged cultivation, including cultivated horizon and plow-pan (0 – absent; 1 – present). [8] Aridic epipedon: one of the crustic epipedons, formed under aridic moisture regime, with special morphological differentiation (0 – absent; 1 – present). [9] Albic horizon: subsurface horizon of albic materials (0 – absent; 1 – present). [10] Cambic horizon: B horizon formed by weathering and soil forming processes, which has no or almost no illuviation with no distinct argillification or clayification, but has a color of brown, red, yellow, or purple, etc., and has the development of soil structure (0 – absent; 1 – present). [11] Ferralic horizon: subsurface horizon from high degree of ferralitization (0 – absent; 1 – present). [12] LAC-ferric horizon: subsurface horizon from medium degree of ferralitization, which has lower activity clays and is rich in free iron oxides. (0 – absent; 1 – present). [13] Spodic horizon: illuvial horizon from cheluviation (0 – absent; 1 – present). [14] Hydragric horizon: subsurface horizon affected by rice-cultivation formed by leaching down the reduced iron and manganese oxides from upper layers (0 – absent; 1 – present). [15] Argic horizon: subsurface horizon in which clay content is distinctly higher than that in the overlying horizons (0 – absent; 1 – present). [16] Clay-pan: heavy, compact layer, which differs from surface horizon or overlying horizon in clay content (0 – absent; 1 – present). [17] Alkalic horizon: clay-illuvial horizon high in exchangeable sodium (0 – absent; 1 – present). [18] Hypersalic horizon: horizon high in soluble salt, not cemented (0 – absent; 1 – present). [19] Salipan: continuous or discontinuous pan formed by cementation or induration of soluble salts mainly composed of NaCl (0 – absent; 1 – present). [20] Gypsic horizon: horizon rich in secondary gypsum, neither cemented nor indurated (0 – absent; 1 – present). [21] Hypergypsic horizon: horizon with large amount of gypsum resulting from pedogenetic accumulation or geological deposition, but not cemented (0 – absent; 1 – present). [22] Calcic horizon: horizon rich in secondary carbonates, neither cemented nor indurated (0 – absent; 1 – present). [23] Hypercalcic horizon: non-cemented nor indurated horizon in which carbonates have accumulated in large amounts (0 – absent; 1 – present). [24] Calcipan: continuous or discontinuous pan formed by cementation or induration of carbonates (0 – absent; 1 – present). [25] Salic horizon: horizon rich in salts that are more soluble than gypsum in cold water (0 – absent; 1 – present). [26] Organic soil materials: soil materials including peat and mud, often saturated with water and have high organic carbon content, or consisting of litter or Mattic matter (0 – absent; 1 – present). [27] Anthro-silting materials: sedimentary material resulting from human activities, including irrigation-silting materials and interception-silting materials (0 – absent; 1 – present).

[28] Vertic features: features include crack, auto-inversion, and pedoturbation of clay soil with high degree of shrinking and swelling, rich in expanded clay minerals, such as smectite, etc. (0 – absent; 1 – present). [29] Anthroturbic layer: a plowing-disturbed layer resulting from leveling land or building terrace (0 – absent; 1 – present). [30] Dry moisture regimes. States: absent (0), Ustic (intermediate between the aridic and the udic regimes) (1) and Udic (soils of humid climate which have well-distributed rainfall or which have enough rain in summer so that the amount of stored moisture plus rainfall is approximately equal to, or exceeds, the amount of evapotranspiration) (2). [31] Wet moisture regimes. States: absent (0), Perudic (an extremely wet moisture regime in the regions where rainfall is well-distributed and the weather is foggy, and where the relief is mostly mountain) (1), Stagnic (the upper layers of the soil have a long moist period or are saturated with the surface water or upper stagnant water in a period in most years) (2), and Aquic (entire or some layers of the soil are saturated with groundwater or with water of the capillary fringe accompanied by reduction at one period in most years, when the soil temperature is higher than 5 °C) (3). [32] Gleyic features: strongly reduced features of soil developed under long-term water-saturated conditions (0 – absent; 1 – present). [33] Redoxic features: characteristics of soil horizons saturated with water seasonally and which redox alteration takes place at one period in most years (0 – absent; 1 – present). [34] Cold temperature regimes. States: absent (0), Permagelic (soil temperature is perennially at or below 0 °C, including moist and dry frost) (1), and Cryic (mean annual soil temperature between 0 and 8 °C) and Frigid (mean annual soil temperature is lower than 8 °C and the summer soil temperature is higher than that of Cryic one) (2). [35] Permafrost layer: layer in which soil temperature is perennially at or below 0 °C (0 – absent; 1 – present). [36] Frost-thawic features: morphological properties resulting from frost-thawic alteration on land-surface or in soil layers (0 – absent; 1 – present). [37] n Value: (A − 0.2R) / (L + 3H). (A is the percentage of water in the soil in the field condition; R is the percentage of silt plus sand; L is the percentage of clay; and H is the percentage of organic matter.) States: ≥0.7 (0) and b 0.7 (1). [38] Isohumic property: properties of soils in steppe or forest-steppe where bio-accumulation of humus has reached to relatively large depth (0 – absent; 1 – present). [39] Andic property: soil material characterized by N60% by weight of volcanic ash, cinders and other pyroclastic materials (0 – absent; 1 – present). [40] Base saturation: percentage of saturation with K, Na, Ca and Mg cations in adsorption complex (by NH4OAc). States: b50% (0) and N50% (1). [41] Subhorizon organic carbon. States: b60 g/kg (0) and N 60 g/kg (1). [42] Particle size fraction. States: finer than silt loam (0) and coarser than silt loam (1). [43] Lithologic properties. States: absence of carbonate rocks (0) and presence of carbonate rocks (1). [44] Alluvial properties. States: absent (0), presence of alluvial deposits (1) and presence of sandy deposits (2).

2.4. Cladistic analysis Cladistic analysis in this study was conducted using a parsimony algorithm TNT 1.1 (Goloboff et al., 2008) and LisBeth 1.3 (Zaragüeta-Bagils et al., 2012). A parenthetical matrix of each character tree was

J. Huang et al. / Geoderma Regional 10 (2017) 11–20

constructed in a hierarchical fashion, in which 0 s are assumed to out groups (e.g., absences) and 1 s, 2 s and 3 s are assumed to be derived states. The parenthetical matrix was converted to the smallest possible units of relationships, namely, three-item statements, and exported to TNT as a binary matrix. The binary matrix was used to conduct a heuristic search (i.e., New Technology Search, Ratchet setting with 1000 iterations). The resulting trees were imported into LisBeth 1.3 in order to find the most compatible tree, that is, the tree with the least amount of conflict. A Retention Index (RI) and Compatibility Index (CompI) were generated for each analysis. Generally, large RI and CompI values indicate robust cladograms.

2.5. Identifying robust soil properties In order to identify the most robust morphological and numeric properties, we constructed three data matrices. This includes: 1) all 44 soil properties identified (base matrix); 2) all homologous soil properties identified in the base matrix after an initial cladistic analysis (matrix 2); and 3) all homologous soil properties after removal of numeric soil properties identified in matrix 2 (matrix 3). Robust properties were identified as homologous (i.e., non-arbitrary and support a monophyletic classification) and morphological (i.e., non-numeric).

15

3. Results and discussion 3.1. Base cladogram The base matrix resulted in a base cladogram (BC) which is shown in Fig. 1. It includes all 14 soil Orders and the 39 Suborders. The 44 properties described in Table 1 and Section 2.3 (Fig. 1) are also shown with the homologous properties (i.e., properties that support a monophyletic classification) shown in bold and non-homologous indicated in italics. It is worth noting that almost all the soil Orders are well resolved using the base matrix comprising 44 morphological and numeric properties. For example, from top to bottom, two Suborders of Histosols (i.e., Permagelic and Orthic), two Suborders of Aridisols (i.e., Cryic and Orthic), five Suborders of Cambosols (i.e., Gelic, Aquic, Perudic, Ustic and Udic), four Suborders of Argosols (i.e., Boric, Ustic, Perudic and Udic), three Suborders of Gleyosols (i.e., Permagelic, Stagnic and Orthic), three Suborders of Isohumosols (i.e., Lithomorphic, Ustic and Udic), and two Suborders of Halosols (i.e., Alkalic and Orthic) form separate clades within a large clade. This is consistent with the relatively large RI value (0.902), which means that a large number of shared property-states are retained in the BC. This result suggests that the CST is an effective identification system based on diagnostic horizons and diagnostic characteristics (Gong et al., 2001).

Fig. 1. Base cladogram. Note: All properties and their states are denoted in square brackets (e.g., [32:1]). The 21 homologous properties are marked in bold and 23 non-homologous properties are marked in italics.

16

J. Huang et al. / Geoderma Regional 10 (2017) 11–20

With regard to the monophyletic Orders or Suborders (i.e., clades formed by homologous properties), the BC shows that the three Suborders of Andosols (i.e., Cryic, Vitric and Udic) and two Suborders of Spodosols (i.e., Humic and Orthic) form separate clades which are shown at the bottom of the BC. These monophyletic groups form as a function of shared property-states which do not appear within the clades of other soil Orders. For example, the Andic [39] property (i.e. soil material characterized by N60% by weight of volcanic ash, cinders and other pyroclastic materials) only resolves the Andosols Suborders (Cryic and Vitric) and the Spodic [13] horizon (i.e. illuvial horizon from cheluviation) only groups the Spodosols Suborders (Humic and Orthic). In addition, Histosols and Gleyosols are also monophyletic and are grouped by homologous properties. In total there are 21 homologous properties. These are useful properties because they clearly identify clades based on single characteristics with no ambiguity in the clades. Conversely, we note that more than half of the soil properties (i.e., 23) are non-homologous. These properties are mostly found in the large clade and we consider the clade to be non-monophyletic. There are three kinds of non-homologous properties. The first type forms clades based on arbitrary similarities and group soil Orders that are not necessarily related to each other in the context of soil genesis. For example, the Udic [30:2] property-state of the dry moisture regime [30] property groups the monotypic (i.e., one of a kind) Udic Ferralosols Suborder with the Udic Ferrosols Suborder. From a natural classification perspective, the use of soil moisture regimes (e.g., Udic) is not optimal and maybe misleading because it may group soil Orders with similar moisture that have developed through different pedogenesis processes. The second type of non-homologous property is one whereby the property is identified in different clades spaced far apart in the cladogram. This is the case for the Mollic epipedon [2] property, which grouped three Isohumosols (i.e., Lithomorphic, Ustic and Udic) in the center of the BC and four Cambosols (i.e., Gelic, Aquic, Perudic, Ustic and Udic) at the top. This result is consistent with Gong et al. (2001), who state that while all Isohumosols Suborders have a Mollic epipedon, only some Cambosols Suborders have a Mollic epipedon. This means that these two soil Orders are not totally mutually exclusive using the current diagnostic horizons and characteristics. From a taxonomic perspective, it is useful to keep this type of properties. However, it needs to be further investigated if these properties can help explain the interactions between soil Orders when constructing a natural classification. The third type of non-homologous property defines only a single Suborder. One example is the Hydragric horizon [14] which characterizes the leaching process of iron and manganese oxides during rice cultivation of irrigated soils (e.g., Chinese paddy soils) (Zhang and Gong, 2003). As is shown in the BC, it explicitly defines Stagnic Anthrosols along with property Anthrostagnic epipedon (or Hydragric epipedon) [7]. At this stage, both of the two properties fail to illustrate the relationship and similarities between Stagnic Anthrosols and other Suborders. However, it is worth studying when new taxon is added into the classification, if they may become homologous. In addition, the effects of human activities should not be overlooked given their slow but increasingly stronger impacts on the development of soils, such as secondary soil salinization (Huang et al., 2016), change in soil carbon stocks (Smith, 2005), soil acidification (Guo et al., 2010), soil contamination (e.g., Wei and Yang, 2010; Li et al., 2014) and soil degradation (Wu and Tiessen, 2002). With the development of human technology, it is anticipated that anthropogenic activities will become more and more powerful. Consequently, studying soil genesis will become extremely difficult as humans have been significantly reshaping the landscapes and altering the soils. At that time, when constructing a natural classification system, Anthrosols may be merged with other soil Orders based on their chemical composition and mineralogy as well as other measurable properties affected by human activities such as Anthrostagnic epipedon and heavy metal concentrations. These properties will be used to account for the human impacts on soil genesis.

All the non-homologous properties identified suggest that the CST system is not based on a genetic soil classification. This result is consistent with Gong et al. (2001). Furthermore, the presence of the non-homologous soil properties indicates that the CST is not a predictive classification. This implies that the CST system is not as robust as those used in botany and zoology (Schenk and McMasters, 1956) and it has to be reconstructed whenever soil Orders or Suborders are added or removed. However, it should be noted that although the CST system itself is not designed to be a natural classification, it is still very helpful when we try to build one, as shown in the BC, for the purposes of guiding real world use and management of soils. 3.2. Cladogram 2 We derived matrix 2 by removing the 23 non-homologous properties identified in the BC. The resulting tree from matrix 2 is shown in Fig. 2. We call this cladogram 2 and it shows slightly less structure than the BC. The most obvious difference between the BC and cladogram 2 is that the former large clade comprising non-monophyletic soil Orders (e.g., Histosols, Aridisols, Cambosols, Argosols and Gleyosols) collapses. This is because there are no informative soil properties to determine their inter-relationships. A few other differences between cladogram 2 and BC are also worth reporting. For example, previous separate or unrelated soil Orders, specifically Spodosols, Andosols, Gleyosols and Isohumosols, are now

Fig. 2. Cladogram 2 with 21 homologous morphological and numeric soil properties. Note: All properties and their states are denoted in square brackets (e.g., [32:1]).

J. Huang et al. / Geoderma Regional 10 (2017) 11–20

grouped into one clade. It should be noted that this node of this clade is different from the root node, which suggests that a super-clade exists. However, the relationship between these clades is unknown because of the insufficient information (properties defining the node), despite the fact that properties [13], [39], [32] and [38] and [40] characterize these soil Orders, respectively. Conversely, several previous closely related soil Orders, that is Aridisols and Cambosols, are still found within one clade (also a super-clade). This is a function of the retention several homologous properties including [10], [20], [21], [22], [23] and [24]. The removal of the non-homologous properties leads to a tree (i.e. cladogram 2) which is highly robust and stable given and as evidenced by the larger RI (1.000) and CompI (95.2%) values compared with that of the BC (0.902 and 39.4%, respectively). It is also worth noting that all the soil properties considered in cladogram 2 are homologous, which indicates cladogram 2 is natural. 3.3. Cladogram 3 To determine the effect of numeric properties on the naturalness of the CST we excluded the two non-morphological (i.e., numeric) properties (i.e., [37] n value and [40] base saturation) from matrix 2 to form matrix 3. The result of the cladistics analysis is shown in Fig. 3 (i.e. cladogram 3) and which shows an identical tree structure to cladogram 2. This result is not surprising as these two numeric properties (i.e., [37] and [40]) were holding the clades of Cambosols and Isohumosols

Fig. 3. Cladogram 3 with 19 homologous morphological soil properties. Note: All properties and their states are denoted in square brackets (e.g., [32:1]).

17

together along with two other properties (i.e., properties [1] and [38], respectively). As such, the removal of [37] and [40] did not collapse these clades. Given the same RI (1.000) and CompI (95.2%) values were achieved for cladogram 3 and 2, this result suggests that these two numeric properties (i.e., n value and base saturation) are redundant when classifying Cambosols and Isohumosols of the CST. However, given the importance of n value in distinguishing between Cambosols and Primosols, it is worth further investigating the role of this property in soil classification and even the inter-relationship between Primosols and other soil Orders. It should be also noted that not all the morphological properties are necessary. As is shown in Figs. 2 and 3, properties [20], [21], [22], [23] and [24] are considered redundant as they group Aridisols and Cambosols along with property [10]. These morphological and numeric properties are important and necessary in classifying soils in the field because it is often difficult to find representative soil profiles with all the diagnostic horizons and features. However, from the perspective of a natural classification, it is possible to reduce the number of the redundant properties. It is also worth noting that cladograms 2 and 3 consist of two types of clades (Figs. 2 and 3, respectively). One type is well-resolved. This includes the Spodosols-Andosols-Gleyosols-Isohumosols or S-A-G-I clade, the Aridisols-Cambosols or A-C clade, and the Argosols and Histosols clades. The remaining clades and the associated soil Orders fall into an unresolved basal node. This result shows that the CST is a partially resolved and robust soil classification given nine soil Orders have been shown to be monophyletic, namely the Spodosols, Andosols, Gleyosols, Isohumosols, Histosols, Aridisols, Cambosols, Argosols and Ferralosols clades. With regard to the unresolved Orders, the Vertosols and Primosols are confirmed to be non-monophyletic, which means the soil Suborders from the same soil Order are not grouped together within the same clade. With respect to the Anthrosols, Ferrosols, and Halosols soil Orders, these are confirmed to be aphyletic, because they are of unknown “—phyly” given they are connected directly to the base node. This result indicates these soil Orders are in need of revision when constructing a natural classification and more soil properties should be included (Ebach and Williams, 2010). 3.3.1. Spodosols-Andosols-Gleyosols-Isohumosols (S-A-G-I) clade The S-A-G-I clade consists of four soil Orders (i.e., Spodosols, Andosols, Gleyosols and Isohumosols). Because no properties are identified at the nodes of this clade, the results suggested that these Orders are grouped based on their similarities instead of known properties. Therefore, we use the properties grouping the corresponding soil Suborders for interpretation. Taking the numeric property into consideration (see Fig. 2), the main properties found in the clade include Spodic horizon [13], Andic property [39], Gleyic features [32], Isohumic property [38] and as well as base saturation [40]. Although these five properties differ from each other, they are most likely to be found in mountainous or humid environments. Interestingly, this is consistent with the distribution of the soil Suborders of the CST. For example, and as shown in Fig. 4 Spodosols (green solid dots) are mainly located in isolated areas including northern part of Da Xinganling Mountains (northeast China), northern slopes of Changbai Mountain (northeast China) and south and southeast margins of Tibetan Plateau (southwest China). In these areas illuvial accumulation of organic matter with or without associated accumulation of iron and aluminium occurs in humid environments (see Table 1). Andosols are also found in high altitudes (red triangles) near volcanoes, which are mainly distributed in the northeast of China as well as Kunlun Mountains near the northern parts of the Tibetan Plateau. In these locations the soil forms from weathered volcano-clastic materials (see Table 1). As for the Gleyosols they are mostly found in northeast China, but in valleys near the mountains of Da Xinganling, Xiao Xinganling and

18

J. Huang et al. / Geoderma Regional 10 (2017) 11–20

Fig. 4. Map of soil Orders and Suborders from Chinese Soil Taxonomy (after CSSD, 2015). Note: Main geographic features of China are also highlighted. (For interpretation of the references to color in this figure, the reader is referred to the web version of this article.)

Changbai and floodplains of Sanjiang and Song-Liao (purple areas). Additionally, they are located in the wet low-lying lands of the Northern Tibetan Plateau and northern and southern slopes of Tianshan Mountains (northwest China). In these areas and landscape positions they are developed under redoximorphic conditions with permanent fluctuating water-table (see Table 1). In terms of Isohumosols, this soil Order is mostly situated in the northeast (e.g., Da Xinganling Mountains) and northwest (e.g., Tianshan Mountains) of China (grey areas), where accumulation of humus deep under the ground surface and under cool temperatures is possible. Given the similar climate conditions of these soil Orders (i.e., mountainous and humid), it is reasonable to construct a Super-Order comprising these four soil Orders. Interestingly, this Super-Order of mountainous and humid soils is similar to the Pedalfers of the zonal soils of the 1938 USDA soil taxonomy (Baldwin et al., 1938). The idea of zonal soils has been long-discredited due to over simplicity. For example, the United States can be represented by Pedalfers in the humid east and Pedocals in the arid west with a division roughly along the Mississippi River (Brevik and Hartemink, 2013). This was incorrect because Pedocals were not characterized by climate but limestone which was also found in the east of the U.S. (Paton and Humphreys, 2007). However, the Super-Order identified here should not be overlooked because it was constructed using an independent cladistic analysis without any a priori knowledge on the zonal soils. Given that the soil

Orders of this clade are all monophyletic and that the Orders are grouped by all homologous soil properties, the Super-Order may reveal some hidden overall similarities between these soil Orders as a function of one or more soil forming factors dominant at large spatial scales (e.g., climate, parent materials). 3.3.2. Aridisols-Cambosols (A-C) clade Another clade identified in cladogram 2 and 3 includes Aridisols and Cambosols. Because a number of properties are identified at the node of this clade, we use these properties for further interpretation. Seeing from Fig. 3, the properties, which were identified at the note of this clade and grouped these two soil Orders include Cambic horizon [10], Gypsic horizon [20], Hypergypsic horizon [21], Calcic horizon [22], Hypercalcic horizon [23] and Calcipan [24]. Based on the arid characteristics of these controlling soil properties, it is envisaged that Aridisols and Cambosols should be found in the arid environment. The former is confirmed in Fig. 4 which shows the distribution of Aridisols. Specifically, the Cryic Aridisols (light grass green) and Orthic Aridisols (pink) Suborders which are located in the western half of the Tibetan Plateau and northwest of China, respectively. In both cases, these areas are within the arid regions of China, where annual precipitation is b400 mm (Xi and Zhang, 1982; Shi et al., 2015). Similarly, this Super-Order of arid soils is similar to the Pedocals of the zonal soils of the 1938 USDA soil taxonomy (Baldwin et al., 1938). Although

J. Huang et al. / Geoderma Regional 10 (2017) 11–20

the idea of the zonal soils has been replaced, clades comprising all monophyletic arid soil Orders may still be valid when people consider soils as an independent natural body with an inherent hierarchical structure instead of a geological formation (Afanasiev, 1927). However, this is not the case for Cambosols (grass green) which are found in the arid (e.g., eastern half of Tibetan Plateau), semi-arid (e.g., northern margin of Inner Mongolian Plateau) and humid (e.g., Sichuan basin and middle and lower reaches of the Yangtze River basin) regions (see Fig. 4). This is not unexpected because the arid properties mentioned above may apply to certain Suborders of Cambosols (e.g., Gelic, Ustic), but they may not apply to other Suborders (e.g., Perudic, Udic, Aquic). Based on the description of Cambosols (see Table 1), they are less developed, with altered horizons or weak expression of other diagnostic horizons. Therefore, when we build a natural classification, the Cambosols Order in the CST cannot be used directly because it contains soils of different parent materials (Shi et al., 2006a). 3.3.3. Non-monophyletic CST soil Orders Vertosols are non-monophyletic, suggesting their Suborders belong to different Orders. This is the case for the Udic Vertosols which is found in the S-A-G-I clade. However, and from the standpoint of soil genesis this is not surprising. This is because the Vertosols are equivalent to lime concretion black soils of the Semi-aqueous soils of GSCC system (Shi et al., 2006a). However, with regard to the non-monophyletic Primosols, the situation is more complicated. This is because Primosols are other soils which cannot be divided into any other soil Orders (Gong et al., 2001). Based on soil genesis (Shi et al., 2006a), Primosols can be divided into Amorphic soils, Alpine soils or Alkali-saline soils. Similar to the Australian Dermosols (Isbell, 2002, p. 34), they are equally ad hoc and resemble wastebasket taxa (Plotnick and Wagner, 2006). Therefore, it is possible to place Suborder Anthric Primosols into the S-A-G-I clade if the characteristic of the Anthric Primosols are akin to the soils developed under mountainous and humid environments. 3.3.4. Aphyletic CST soil Orders What is not clear is the relationship between the Aphyletic soil Suborders of soil Orders including Anthrosols, Ferrosols and Halosols. Cladistic relationship shows that these Suborders do not form Orders based on robust morphological properties. In Fig. 1, for example, it is found that the Orthic Anthrosols Suborder is grouped with the Anthric Primosols based on some unknown relationship. However, after excluding the non-homologous soil properties, these soil Suborders fall apart as separate clades. In term of the GSCC system (Shi et al., 2006a), Anthrosols are equivalent to Anthrosols (i.e., paddy soils, irrigated desert soils and irrigated warped soils); Ferrosols correspond to Ferralosols (i.e., Latosols, Latosolic red soils and Red soils); and Halosols are divided into Alkali-saline soils (i.e., desert solonchaks, acid sulfate soils, solonetzes and coastal solonchaks). If these soil Orders do exist and represent soils with different “genetic materials” (i.e., parent materials) or different soil genesis processes, additional properties that have an impact on soil genesis should be measured for all the soil Orders and included into the CST system, such as pH. 4. Conclusions The CST system, as shown in the base cladogram, has several characteristics that may be part of a natural classification because many of the well-resolved soil Orders (e.g., Aridisols, Isohumosols) are grouped by a number of non-homologous soil properties. After excluding all the non-homologous soil properties (e.g., soil moisture regimes, Mollic epipedon, Hydragric horizon) and numerical soil properties (e.g., n value and base saturation), the resulting cladogram 3 becomes more natural. This suggests the potential to remove these properties to construct a natural soil classification. Many modern soil classifications,

19

such as the CST system, are not designed to be natural classifications (they are simply soil identification keys). Regardless, they may contain soil properties that are part of a natural soil classification. In cladogram 3, Spodosols, Andosols, Gleyosols and Isohumosols Orders and Udic Vertosols and Anthric Primosols Suborders are more closely related to each other, which suggests a potential Superorder of mountainous and humid soils. Similarly, closely related Aridisols and Cambosols indicate a potential Superorder of arid soils. Moreover, several non-monophyletic CST soil Orders (e.g., Vertosols, Primosols) were identified in cladogram 3. These Orders need to be revised from a natural classification perspective based on their parent materials or other homologous soil properties. In addition, several aphyletic soil Orders (e.g., Anthrosols, Ferrosols, and Halosols) were identified due to insufficient information for the cladistic analysis. As such, measurements of additional morphological properties (e.g. pH) or other potentially homologous soil forming factors including climate (Driessen et al., 2000), topography and human activities (e.g. heavy metal concentrations) for all the soil Orders can be done to understand the relationships between the aphyletic soil Orders and to establish a more natural soil classification scheme. In terms of the future work, cladistic analysis can also be applied to extract information from the Russian soil classification, the ST system as well as the World Reference Base for Soil Resources to provide guidance for establishing a world-wide natural soil classification scheme. Acknowledgements The authors acknowledge the Editor-in-Chief (Professor Alfred E. Hartemink), Professor David G. Rossiter (Cornell University) and an anonymous referee for the helpful and constructive comments which assisted us to materially improve the scientific merit of the paper. Appendix A. Supplementary data Supplementary data associated with this article can be found in the online version doi:10.1016/j.geodrs.2016.05.002. These data include the Google maps of the most important areas described in this article. References Afanasiev, J.N., 1927. The classification problem in Russian soil science. Russian Academy of Science, Pedological Investigations 5, p. 51. Baldwin, M., Kellogg, C.E., Thorp, J., 1938. Soil classification. In: Hambridge, G. (Ed.), Soils and Men: U.S. Dept. of Agriculture Yearbook, 1938. U.S. Government Printing Office, pp. 979–1001. Basinski, J.J., 1959. The Russian approach to soil classification and its recent development. J. Soil Sci. 10 (1), 14–26. Bockheim, J.G., Gennadiyev, A.N., Hartemink, A.E., Brevik, E.C., 2014. Soil-forming factors and soil taxonomy. Geoderma 226, 231–237. Brevik, E.C., Hartemink, A.E., 2013. Soil maps of the United States of America. Soil Sci. Soc. Am. J. 77, 1117–1132. Buol, S.W., Southard, R.J., Graham, R.C., McDaniel, P.A., 2011. Soil Genesis and Classification. John Wiley & Sons. Cain, A.J., 1958. Logic and memory in Linnaeus's system of taxonomy. Proc. Linn. Soc. Lond. 169, 144–163. Chan, C.K., Yao, X., 2008. Air pollution in mega cities in China. Atmos. Environ. 42 (1), 1–42. China Soil Scientific Database, 2015. Map of Chinese Soils (1:12 Million), accessed on 29/ 09/2015 from http://www.soil.csdb.cn/page/showEntity.vpage?uri=cn.csdb.soil. taxonomy1.cstTugang. Coffey, G.N., 1912. A study of the soils of the United States. USDA Bureau of Soils Bull. 85. U.S. Gov. Print. Office, Washington, DC, USA. Dokuchaev, V.V., 1879. Short historical description and critical analysis of the more important soil classifications. Trav. Soc. Nat. St. Petersburg 10, 64–67. Dokuchaev, V.V., 1893. The Russian Steppes and the Study of the Soil in Russia, Its Past and Present. J.M. Crawford, Trans. Department of Agriculture, Ministry of Crown Domains for the World's Columbian Exposition, St. Petersuburg (61 pp.). Driessen, P., Deckers, J., Spaargaren, O., Nachtergaele, F., 2000. Lecture Notes on the Major Soils of the World (No. 94). Food and Agriculture Organization (FAO). Ebach, M.C., Williams, D.M., 2010. Aphyly: a systematic designation for a taxonomic problem. Evol. Biol. 37 (2-3), 123–127. Fraix-Burnet, D., 2009. Galaxies and cladistics. Evolutionary Biology. Springer, Berlin Heidelberg, pp. 363–378.

20

J. Huang et al. / Geoderma Regional 10 (2017) 11–20

Fraix-Burnet, D., Choler, P., Douzery, E., 2003. What can biologists say about galaxy evolution? Astrophys. Space Sci. 284, 535–538. Glinka, K.D., 1914. The Great Soil Groups of the World and Their Development, C.F. Marbut, Trans., 1927. Edwards Bros., Ann Arbor, Mich. (235 pp.). Glinka, K.D., 1924. Differents types d'apres lesquels se forment les sols et al classification de ces derniers. Comite Internat. Pedologie IV, Comm. No. 20. Goloboff, P.A., Farris, J.S., Nixon, K.C., 2008. TNT, a free program for phylogenetic analysis. Cladistics 24 (5), 774–786. Gong, Z.T., Cheng, Z.C., Luo, G.B., Zhang, G.L., Zhao, W.J., 1999. Cross-reference of the Chinese Soil Taxonomy. Soil 2, 57–63 (In Chinese). Gong, Z.T., Lei, W.J., Chen, Z.C., Gao, Y.X., Zeng, S.G., Zhang, G.L., Xiao, D.N., Li, S.G., 2001. Chinese Soil Taxonomy. Science Press, Beijing. Gong, Z., Zhang, X., Chen, J., Zhang, G., 2003. Origin and development of soil science in ancient China. Geoderma 115 (1), 3–13. Guo, J.H., Liu, X.J., Zhang, Y., Shen, J.L., Han, W.X., Zhang, W.F., Christie, P., Goulding, K.W.T., Vitousek, P.M., Zhang, F.S., 2010. Significant acidification in major Chinese croplands. Science 327, 1008–1010. Hennig, W., 1966. Phylogenetic Systematics. University of Illinois Press, Urbana. Huang, J., Prochazka, M.J., Triantafilis, J., 2016. Irrigation salinity hazard assessment and risk mapping in the lower Macintyre Valley, Australia. Sci. Total Environ. 551, 460–473. Isbell, R., 2002. The Australian soil classification. vol. 4. CSIRO publishing, Australia. IUSS Working Group, 2006. World reference base for soil resources. World Soil Resources Report, 103. Krasilnikov, P., Martí, J.-J.I., Arnold, R., Shoba, S. (Eds.), 2009. Soil Terminology, Correlation, and Classification. Earthscan, London, UK. Lee, P.H., 1921. The economic history of China with special reference to agriculture. Columbia University Studies in History, Economics, and Public Law 99, pp. 1–461. Li, Z., Ma, Z., van der Kuijp, T.J., Yuan, Z., Huang, L., 2014. A review of soil heavy metal pollution from mines in China: pollution and health risk assessment. Sci. Total Environ. 468, 843–853. Marbut, C.F., 1927. A scheme of soil classification. 1st Inter. Congr. Soil Sci. Trans. 4, pp. 1–31 Marbut, C.F., 1951. Soil classification. Life and Work of Curtis F. Marbut. Artcraft Press, Columbia, Mo., pp. 85–94. Mayr, E., 1968. Theory of biological classification. Nature 220, 545–548. McBratney, A., Field, D.J., Koch, A., 2014. The dimensions of soil security. Geoderma 213, 203–213. Miltenyi, G.P., Ebach, M.C., Triantafilis, J., 2015. Assessing the Australian soil classification using cladistic analysis. Soil Res. 53 (7), 772–785. Minasny, B., McBratney, A.B., 2010. Methodologies for global soil mapping. Digital Soil Mapping. Springer, Netherlands, pp. 429–436. Nelson, G., Platnick, N.I., 1981. Systematics and Biogeography: Cladistics and Vicariance. Columbia University Press, New York. Paton, T.R., Humphreys, G.S., 2007. A critical evaluation of the zonalistic foundations of soil science in the United States. Part I: the beginning of soil classification. Geoderma 139, 257–267. Plotnick, R.E., Wagner, P.J., 2006. Round up the usual suspects: common genera in the fossil record and the nature of wastebasket taxa. Paleobiology 32 (1):126–146. http://dx.doi.org/10.1666/04056.1. Qu, J., Fan, M., 2010. The current state of water quality and technology development for water pollution control in China. Crit. Rev. Environ. Sci. Technol. 40 (6), 519–560. Ramann, E., 1918. The Evolution and Classification of Soils, 1928, C.L. Whittles, Trans., Heffner, Cambridge, England (619 pp.). Riecken, F.F., Smith, G.D., 1949. Lower categories of soil classification: family, series, type, and phase. Soil Sci. 67 (2), 107–116. Robinson, G.W., 1932. Soils — Their Origin, Constitution and Classification. An Introduction to Pedology. Thomas Murby & Co., London.

Schenk, E.T., McMasters, J.H., 1956. Procedures in Taxonomy. Stanford University Press, Standford (199 pp.). Sheng, J., Ma, L., Jiang, P.A., Li, B., Huang, F., Wu, H., 2010. Digital soil mapping to enable classification of the salt-affected soils in desert agro-ecological zones. Agric. Water Manag. 97 (12), 1944–1951. Shi, X.Z., Yu, D.S., Yang, G.X., Wang, H.J., Sun, W.X., Du, G.H., Gong, Z.T., 2006a. Cross-reference benchmarks for translating the genetic soil classification of China into the Chinese soil taxonomy. Pedosphere 16 (2), 147–153. Shi, X.Z., Yu, D.S., Warner, E.D., Sun, W.X., Petersen, G.W., Gong, Z.T., Lin, H., 2006b. Crossreference system for translating between genetic soil classification of China and soil taxonomy. Soil Sci. Soc. Am. J. 70 (1), 78–83. Shi, X.Z., Yu, D.S., Xu, S.X., Warner, E.D., Wang, H.J., Sun, W.X., Zhao, Y.C., Gong, Z.T., 2010. Cross-reference for relating genetic soil classification of China with WRB at different scales. Geoderma 155 (3), 344–350. Shi, Z., Ji, W., Viscarra Rossel, R.A., Chen, S., Zhou, Y., 2015. Prediction of soil organic matter using a spatially constrained local partial least squares regression and the Chinese vis–NIR spectral library. Eur. J. Soil Sci. 66 (4), 679–687. Sibirtzev, N.M., 1895. Genetic classification of soils. Novo-Aleksandr. Agric. Inst. Zap. 9, 1–23. da Silva, S.G., Tehrani, J.J., 2016. Comparative phylogenetic analyses uncover the ancient roots of Indo-European folktales. R. Soc. Open Sci. 3, 150645. Smith, G.D., 1986. The Guy Smith interviews: Rationale for concepts in soil taxonomy. In: Forbes, T.R. (Ed.) vol. 11. Soil Management Support Services, Washington, DC. Smith, P., 2005. An overview of the permanence of soil organic carbon stocks: influence of direct human-induced, indirect and natural effects. Eur. J. Soil Sci. 56, 673–680. Soil Survey Staff, 1975. The categories of the system. Soil Taxonomy: A Basic System for Making and Interpreting Soil Surveys. U.S. Government Printing Office, Washington, D.C., pp. 71–81. Sun, X.L., Zhao, Y.G., Zhang, G.L., Wu, S.C., Man, Y.B., Wong, M.H., 2011. Application of a digital soil mapping method in producing soil orders on mountain areas of Hong Kong based on legacy soil data. Pedosphere 21 (3), 339–350. Thorp, J., Smith, G.D., 1949. Higher categories of soil classification: order, suborder, and great groups. Soil Sci. 67 (2), 117–126. Wei, B., Yang, L., 2010. A review of heavy metal contaminations in urban soils, urban road dusts and agricultural soils from China. Microchem. J. 94 (2), 99–107. Williams, D.M., Ebach, M.C., 2007. Foundations of Systematics and Biogeography. Springer Science & Business Media. Winsor, M.P., 2003. Non-essentialist methods in pre-Darwinian taxonomy. Biol. Philos. 18 (3), 387–400. Winsor, M.P., 2006a. Linnaeus's biology was not essentialist. Ann. Mo. Bot. Gard. 93 (1), 2–7. Winsor, M.P., 2006b. The creation of the essentialism story: an exercise in metahistory. Hist Philos Life Sci 28 (2), 149–174. Wu, R., Tiessen, H., 2002. Effect of land use on soil degradation in alpine grassland soil, China. Soil Sci. Soc. Am. J. 66, 1648–1655. Xi, C., Zhang, J., 1982. The basis and regionalization of China's soil. Acta Pedol. Sin. 19, 97–109. Yu, D., Shi, X., Wang, H., Sun, W., Warner, E.D., Liu, Q., 2007. National scale analysis of soil organic carbon storage in China based on Chinese soil taxonomy. Pedosphere 17 (1), 11–18. Zaragüeta-Bagils, R., Ung, V., Grand, A., Vignes-Lebbe, R., Cao, N., Ducasse, J., 2012. LisBeth: new cladistic for phylogenetics and biogeography. C.R. Palevol 11 (8), 563–566. Zhang, G.L., Gong, Z.T., 2003. Pedogenic evolution of paddy soils in different soil landscapes. Geoderma 115 (1), 15–29. Zhu, A.X., Yang, L., Li, B., Qin, C., Pei, T., Liu, B., 2010. Construction of membership functions for predictive soil mapping under fuzzy logic. Geoderma 155 (3), 164–174.