Catena 92 (2012) 186–195
Contents lists available at SciVerse ScienceDirect
Catena journal homepage: www.elsevier.com/locate/catena
Changes in soil nutrient and enzyme activities under different vegetations in the Loess Plateau area, Northwest China Bing Wang a, b, c, 1, Sha Xue a, b, 1, Guo Bin Liu a, b,⁎, Guang Hui Zhang a, b, c, Gary Li d, Zong Ping Ren c a
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau of Northwest A&F University, Yangling, Shaanxi, 712100, PR China Institute of soil and water conservation, Chinese Academy Sciences & Ministry of Water Resources, Yangling, Shaanxi, 712100, PR China School of Geography, Beijing Normal University, Beijing, 100875, PR China d Department of Geography and Environmental Studies, California State University — East Bay, Hayward, CA 94542, United States b c
a r t i c l e
i n f o
Article history: Received 5 December 2010 Received in revised form 17 October 2011 Accepted 14 December 2011 Keywords: Land use Vegetation restoration Soil nutrients Soil enzymes Loess plateau
a b s t r a c t This study examined the changes in soil properties and soil quality 30 years after cultivated farmland was restored back to forest land in Loess Plateau, China. Specifically, organic matter, total nitrogen (N) and phosphorus (P), available N, P and Potassium (K) contents in soils were tested and analyzed. In addition, enzyme activities of α-amylase, saccharase, polyphenol oxidase, cellulase, urease, catalase and alkaline phosphatase were also investigated. The study area has mostly been restored, in the past 30 years, back to grassland in some parts, and the other parts of forest lands of black locust, korshinsk peashrub, Chinese pine, mixed trees of Chinese pine and amorpha, and mixed trees of black locust and amorpha. Soil properties on a sloped farmland, located in the study area but has not had a chance to be restored, were tested and the result was treated as the soil properties of non-restoration. Soil properties of an 80-year old forest land of Chinese arborvitae were tested and the result was treated as that of a climax community. The study showed that after 30 years of restoration, nutrients content in the soil of mixed forest of black locust and amorpha increased significantly. However, nutrients content in the soil of mixed forest of Chinese pine and amorpha decreased. As to soil enzyme activities, saccharase, cellulase, urease, catalase and alkaline phosphatase increased while polyphenol oxidase activity decreased compared to non-restoration and climax community soils. The study also found that the organic matter content was relatively low in the restored soils, compared with not-restored land. This may be caused by the high enzyme activity per unit of organic carbon in the soils of the study area which tends to help decompose and therefore decrease the organic matter in soil. © 2011 Elsevier B.V. All rights reserved.
1. Introduction Overgrazing, intensive cultivation, and the loss of vegetative cover have resulted in the degradation of millions of hectares of cultivated land in Loess Plateau. Severe soil erosion has resulted in the loss of most topsoil in many locations, thus exposing parent material or soils with low nutrient content (Liu and Zhao, 1993; Wei, et al., 2006; Zhou et al., 2006). The problem has become especially acute during the past fifty years. As we know, Loess is a highly erosion-prone soil that is susceptible to the forces of wind and water. In fact, the soil of this region has been called “the most highly erodible soil on Earth” (Laflen, 2000). In an effort to control soil erosion and establish a healthy ecosystem in the Loess Plateau, several measures have been taken including eco-environment rehabilitation by engineering (e.g. check dam construction) and biological approaches (e.g. the “Conversion of Cropland to Forest and Grassland” project). Among them, re-vegetation has ⁎ Corresponding author: Tel.: + 86 29 87012907; fax: + 86 29 87012907. E-mail addresses:
[email protected] (B. Wang),
[email protected] (S. Xue),
[email protected] (G.B. Liu). 1 These authors contributed equally to this work. 0341-8162/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.catena.2011.12.004
been reported as the most effective and useful way to abate soil erosion and soil degradation and to restore the ecological integrity of disturbed ecosystems (Hou et al., 2002). With the stoppage of farming practices, soil structure gradually recovers as vegetation restoration proceeds and the ability of the soil to resist erosive forces slowly increases. Soil quality changes with different types of land use and management and depends on the physical, chemical, biological and biochemical properties of the soil. The changes in these properties must be taken into account in assessing changes in soil quality (Klein et al., 1985; Yakovchenko et al., 1996). The Cerdà (1996, 1998) showed how soil aggregates are related to the vegetation cover, and confirmed that the vegetated soils have the stronger aggregates, and less breakable than the bare soil. Cerdà (1997, 2002) also showed the effect of vegetation on water erosion, and confirmed that the large infiltration rates induce negligible variability in erosion and runoff on the vegetated surfaces. Although certain soil properties are important in reflecting soil quality (e.g. nutrient, the foundation of plant growth), they may not be suitable for assessing soil quality due to the fact that they change slowly. Some studies have demonstrated that soil biochemical properties, responding to environmental stress rapidly, must be used (Dalal, 1998). For example, soil enzyme activities
B. Wang et al. / Catena 92 (2012) 186–195
are sensitive to the stress on ecosystems and have the potential to serve as an indicator of the health and sustainability of managed ecosystems (Bergstrom et al., 1998; Dick, 1994; Dick and Tabatabai, 1992). Vegetation restoration, a change of land use in a relatively short period of time, is also expected to have a significant impact to soil properties. It is reasonably expected that such an impact would be reflected in sensitive enzyme activities in the soil. However, there is a lack of standardized protocols for determining enzyme activity (Trasar-Cepeda et al., 2008). Enzymes associated with different cycles and that participate in different stages of degradation will not necessarily respond to land use change in the same way (Sinsabaugh et al., 1991; Trasar-Cepeda et al., 2007). Some scholars suggest that the enzymes, together with the decomposed organic compounds and soil nutrients, may represent a holistic view of the acclimatization response of the microbial assemblage to the organic matter types and environmental conditions of the site over an ecologically- significant period of time (Boerner et al., 2005). Nevertheless, despite the profusion of information, a suite of universal indicators of enzyme activity to demonstrate the effects of land use has not been established, and the results obtained by different researchers are often inconsistent. This study focuses on the change of land use through vegetation restoration in a Loess Plateau region of China. It is assumed that the vegetation restoration, although relatively short in time comparing to other long standing land uses, would affect soil properties. If so, such a change in soil properties should be able to be detected by sensitive enzyme activities. The aim of this study is to: 1) detect the changes of soil properties and enzyme activities after 30 years of soil restoration in the study area as well as the soil property difference between the restored soil and the best quality soil. 2) to investigate the relationship between soil organic content and enzyme activities by using enzyme activities per unit of organic carbon. 2. Materials and methods 2.1. Study area The study was conducted at the Ansai Research Station of Soil and Water Conservation, Chinese Academy of Sciences, which is located in the Zhifanggou Watershed, Shaanxi Province, NW China (36°46′28″– 36°46′42″N, 109°13′03″–109°16′46″E, 1010–1431 m altitude, 8.27 km 2; Fig. 1). The landform and vegetation at the station are typical for the western part of the Loess Plateau. Slopes vary between 0° and 65°. The area has a temperate, semi-arid climate. Mean annual temperature in the watershed ranges from 8.8 °C (min. −23.6 °C and max. 36.8 °C) and the average frost-free period is 157 days.
187
Mean annual precipitation is 505 mm, of which about 70% falls between July and September. The loess-derived soils are fertile but extremely susceptible to erosion. The sand, silt, and clay contents are 65%, 24%, and 11% respectively. Soil pH (H2O) is 5.8.
2.2. Experiment design and soil sampling The study was carried out in the Zhifanggou watershed which had been enclosed for 30 years to allow natural re-vegetation. Before enclosure, the land was used as cultivated land. The history of the sites was determined through interviews with local farmers and village elders and by rental contracts between farmers and the local government. Samples were taken from soils of grassland (GL), black locust (Robinia pseudoacacia, BL), korshinsk peashrub (Caragana korshinskii, KP), Chinese pine (Pinus tabulaeformis, CP), mixed forest of Chinese pine–amorpha (Pinus tabulaeformis–Amorpha fruticosa, CPA) and black locust–amorpha (R. pseudoacacia–A. fruticosa, BLA). The sampling sites were all located close to the top of the loess mounds with little difference in terms of aspect, slope gradient, elevation, or previous farming practices. Moreover, a slope farmland with the same previous farming practices and the similar aspect, gradient and elevation of the aforesaid vegetations was selected and treated as the starting point in restoration process. A native forest of Chinese arborvitae, regarded as the climax community in the region (Zou et al., 2002), was selected and treated as a theoretical end point of restoration processes. Physical and morphological characters of each site are listed in Table 1. Soil samples were taken from 20 m × 20 m plots in July 2005. Three of these plots were used for each of eight study sites, totaling 24 plots. These plots were considered to be independent of each other as the distance among them exceeded the spatial dependence (b13.5 m) of most soil nutritional and microbial variables (Mariotte et al., 1997). Literature shows that the depth of the soil sampling in studying soil properties is often from 0 to 20 cm (Benitez et al., 2004; Fenner et al., 2005; Stark et al., 2008; Yüksek and Yüksek, 2011). In this study, soil core samples were thus collected from the top 20 cm of soil profile using soil augers (10 cm inner diameter). Litter horizons were removed before soil sampling. Ten soil core samples were collected along a spatially “S” curve within each plot and then mixed together to make one large sample. At the native forest site, samples were collected at a distance of approximately 80 cm from trees. All samples were sieved through a 2 mm screen to remove vegetation roots and other debris. Half of each sample was kept fieldmoist in a cooler at 4 °C until analyses so that soil biological properties could be conducted. The other half of each sample was air-dried
Fig. 1. Location and 3D render of the study area (Zhifanggou watershed, Wang et al., 2011). The inset shows the experiment area. Note: This figure was supported by the National Key Technologies R&D Program: Assessment of impact on soil erosion and its indicators (2007CB407205).
188
B. Wang et al. / Catena 92 (2012) 186–195
Table 1 Description of the sampling plots. Vegetation types
Code
Landform
Soil Type
Altitude (m)
Primary undergrowth vegetations
Slope farmland Grassland Black locust (Robinia pseudoacacia) Korshinsk peashrub (Caragana Korshinskii) Chinese pine (Pinus tabulaeformis) Chinese pine–Amorpha (Pinus tabulaeformis –Amorpha fruticosa) Black locust–Amorpha (Robinia pseudoacacia–Amorpha fruticosa) Chinese arborvitae (Platycladus orientalis)
SF GL BL KP CP CPA BLA CA
HS HS HS HS HS HS HS HS
LS LS LS LS LS LS LS LS
1175 1206 1129 1029 1166 1142 1185 1283
Grain Artemisia sacrorum Lespedeza davurica–Stipa bungeana Artemisia sacrorum–Stipa bungeana Artemisia sacrorum–Carex lanceolata Artemisia sacrorum–Stipa bungeana Artemisia sacrorum Carex lanceolat
Note: HS represents hillside, LS presents Loessial Soil, SF is sloped farmland, CA is a native forest of 80-years Chinese arborvitae, GL is grassland, KP represents korshinsk peashrub, CP is Chinese pine, CPA is mixed forest of Chinese pine and amorpha, and BLA represents a mixed forest of black locust and amorpha.
and stored at room temperature to be used for the determination of soil physical and chemical properties. 2.3. Laboratory analyses Soil nutrients and chemical analyses were performed on soil samples using standard soil test procedures from the Chinese Ecosystem Research Network (Editorial Committee, 1996) and the Soil Science Society of China (1999). Soil organic carbon (OC) was determined by wet digestion with a mixture of potassium dichromate and concentrated sulfuric acid. Total soil nitrogen (TN) was measured by the semi-micro Kjeldahl method, and soil total phosphorus (TP) was determined colorimetrically samples went through wet digestion with H2SO4 + HClO4. Available nitrogen in soil (AN) was determined with a micro-diffusion technique after samples went through alkaline hydrolysis. Soil available phosphorus (AP) was determined by the Olsen method (ISSCAS, 1978). Soil available potassium (AK) was measured in 1 mol L − 1 NH4OAc extracts by flame photometry. An automatic acid–base titrator (Metrohm 702) was used to determine soil pH value in 1:5 soil/water suspensions. The results are listed in Table 2. Extracellular enzyme activity was measured using assay techniques modified from Guan (1986). Soil α-amylase (EC 3.2.1.1; ALA) activity was measured by 3, 5-dinitro salicylic acid colorimetry using soluble starch as the substrate. The amount of maltose released over 24 h was assayed colorimetically at 508 nm and expressed as μmol maltose g − 1 dry sample. Soil saccharase (EC 3.2.1.26; SAC) activity was measured by 3, 5-dinitro salicylic acid colorimetry with sucrose as the substrate. The amount of 3-amino-5-nitro-salicylic-acid released over 24 h was assayed colorimetically at 508 nm and expressed as μmol glucose g − 1 dry sample. Soil polyphenol oxidase (EC 1.10.3.1; PPO) activity was measured using the iodine titrimetry method and expressed as μmol I2 g − 1 dry sample. Soil cellulase (EC 3.2.1.4; CEL) activity was measured by nitrosalicylic acid colorimetry. The amount of glucose released over 72 h was assayed colorimetically Table 2 Results of ANOVA. Index
F
Sig.
Organic matter Total N Available N Total P Available P Available K pH Urease α-amylase Alkaline phosphatase Catalase Saccharase Polyphenol oxidase Cellulase
3058.1 1.6 552.0 12.5 14.0 17253.2 228.5 74.2 4.2 74.0 37.4 43.5 18.4 59.6
P b 0.001 P b 0.001 P b 0.001 0.001 0.001 P b 0.001 P b 0.001 P b 0.001 0.009 P b 0.001 P b 0.001 P b 0.001 P b 0.001 P b 0.001
at 540 nm and expressed as μmol glucose g − 1 dry sample. Soil urease (EC 3.5.1.5; URE) activity was measured by indophenol colorimetry with urea as the substrate. The amount of ammonium released over 24 h was assayed colorimetically at 578 nm and expressed as μmol ammonium g − 1 dry sample. Soil catalase (EC 1.11.1.6; CAT) activity was titrated over 20 min with a standard solution of 0.1 N KMnO4 and expressed as μmol KMnO4 g − 1 dry sample. Soil alkaline phosphatase (EC 3.1.3.1; ALP) activity was measured by disodium phenyl phosphate colorimetry. The amount of phenol released over 24 h was assayed colorimetically at 660 nm and expressed as μmol phenol g − 1 dry sample. All determinations of enzymatic activities were performed in triplicates. Data shown (Table 3 and Figs. 2 to 8) are the average of the three determinations. All indexes tested in this paper were reported as means ±standard deviations. Data were analyzed by one-way analysis of variance (ANOVA) with vegetation type as the factor. Effects of vegetations on soil properties were analyzed by Multidimensional scaling (ASLCAL, MS). Differences at P b 0.05 were considered statistically significant. 3. Results and discussions There is also a lack of agreement about what kind of soil represents the best quality and can be used as a reference by which to compare soils affected by different land use (Gil-Sotres et al., 2005). However, a strong argument has been developed that the natural soils developed under local vegetation of climax community are the soils of best quality, and therefore are those that should display the greatest degree of equilibrium among all properties (Gil-Sotres et al., 2005; Trasar-Cepeda et al., 1997). Based on this argument, a forest soil under native climax vegetation of Chinese arborvitae (Platycladus orientalis, CA) is selected as the soil of best quality in our study to which soil properties of other land uses are compared. 3.1. Soil pH and nutrient properties As Table 1 describes, the soils under different land uses share similar morphological characteristics. However, the soil properties, represented by soil organic matter (OM), total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), available phosphorus (AP), available potassium (AK), and pH values are quite different (Table 3). In general, the soils were slightly alkaline on farmland and all restored land. The pH values of these land uses are all higher than that of climax community soil: Chinese arborvitae soils (Table 3). The low pH value in climax community soil is due to a greater accumulation of humus than other types of land uses. Compare with slope farmland, vegetation restoration of grassland, black locust, korshinsk peashrub, Chinese pine, mixed forest of Chinese pine–amorpha, and mixed forest of black locust–amorpha generated a noteworthy increase in soil nutrient content. Concentrations of organic matter, total N, available N, available P, and available K were 2.5, 2.1, 2.4, 1.5, and 1.6 times greater on
B. Wang et al. / Catena 92 (2012) 186–195
189
Table 3 Soil nutritional properties under different restoration and vegetation types. Site
Organic C g kg− 1
Total N g kg− 1
Available N mg kg− 1
Total P g kg− 1
Available P mg kg− 1
Available K mg Kg− 1
pH
SF GL BL KP CP CPA BLA CA
2.7 ± 0.004 6.6 ± 0.275 5.9 ± 0.000 5.7 ± 0.158 6.8 ± 0.160 6.4 ± 0.068 9.2 ± 0.027 20.8 ± 0.157
0.4 ± 0.009 0.8 ± 0.022 0.7 ± 0.009 0.7 ± 0.023 0.8 ± 0.021 0.7 ± 0.011 0.9 ± 0.006 1.93 ± 0.002
20.9 ± 0.469 50.8 ± 2.346 58.7 ± 1.408 45.1 ± 0.938 46.1 ± 1.408 41.1 ± 0.000 71.3 ± 2.346 109.5 ± 0.938
0.055 ± 0.001 0.059 ± 0.000 0.057 ± 0.000 0.058 ± 0.001 0.060 ± 0.001 0.057 ± 0.000 0.062 ± 0.001 0.061 ± 0.000
1.6 ± 0.255 2.4 ± 0.028 2.5 ± 0.445 2.3 ± 0.085 2.4 ± 0.594 1.8 ± 0.127 2.8 ± 0.042 3.5 ± 0.071
10.5 ± 0.764 16.3 ± 0.135 20.3 ± 0.735 19.2 ± 0.169 16.8 ± 0.132 12.3 ± 0.146 20.4 ± 0.088 19.5 ± 1.888
8.7 ± 0.000 8.7 ± 0.007 8.8 ± 0.007 8.7 ± 0.000 8.7 ± 0.007 8.7 ± 0.007 8.6 ± 0.021 8.5 ± 0.000
Note: SF is sloped farmland, CA is a native forest of 80-years Chinese arborvitae, GL is grassland, KP represents korshinsk peashrub, CP is Chinese pine, CPA is mixed forest of Chinese pine and amorpha, and BLA represents a mixed forest of black locust and amorpha.
restored lands than that on the farmland. However, compared with the climax community of native forest, the concentrations of these six restored lands of organic matter, total N, available N, available P, and available K were 67.3, 59.9, 54.9, 35.4 and 91.2% less than that in the soil of Chinese arborvitae (Table 3). Values of total P increased under restorated vegetation comparing to the slope farmland. However, due to the total P has a high content in anemogenic sediment (loess soil) throughout the study area, changes among restored lands were relatively small. Mixed forest may increase the contents of soil nutrient in different extents comparing to the single tree species. Results showed that soil nutrients of organic matter, total N, and available N, P and K in the soil of mixed forest of black locust and amorpha were 1.6, 1.2, 1.7, 1.4, and 1.2 times higher than those in the black locust soil. However, these soil nutrients of the mixed forest of Chinese pine and amorpha were 6.0, 17.8, 10.8, 26.3 and 27.1% less than those in the Chinese pine soil. Interestingly, the values of these nutrients were mostly higher in the soil of the mixed forest of black locust and amorpha, but mostly lower in the soil of mixed forest of Chinese pine and amorpha. This phenomenon indicated that the improvement of black locust on soil nutritional properties was enhanced by the mixing with amorpha, while the improvement of Chinese pine on soil nutritional properties was weakened by the mixing with amorpha. Furthermore, the mixing of different species could also influence the soil nutrient contents. For instance, the concentrations of organic matter, total N and P in the Chinese pine and grassland soils were higher than that in the soils of black locust and korshinsk peashrub; the concentrations of
available K were relatively high in the soils of black locust and korshinsk peashrub but were relatively low in the soils of Chinese pine and grassland (Table 3). Soil N availability is also one of the important factors regulating the competitive interaction of soil microorganisms and, thus, modifying the relative production of soil enzymes (Fog, 1988). Interestingly, the content of available N in the soils of black locust and the mixed black locust and amorpha was higher than that in other soils, probably because black locust, as an N fixing legume, could accumulate nitrogen effectively. 3.2. Soil enzymatic activities Considerable evidences suggest that soil enzyme activity can be used as an indicator of soil fertility and microbial activity (Badiane et al., 2001) and to evaluate the influence of land use on soil properties (Saggar et al., 1999). In addition, it can be used as a direct expression of the soil community to metabolic requirements and available nutrients and provides a more comprehensive understanding of those key processes linking microbial populations and nutrient dynamics (Sinsabaugh and Moorhead, 1994; Schimel and Weintraub, 2003). Soil enzyme responds well to the change of soil nutrients and is a good microbial indictor. To investigate the change in soil nutrients from microbial's perspective, enzyme activities on restored and non-restored lands were tested and analyzed. The analysis result showed that the soil enzyme activities varied with the type of vegetation. Except for α-amylase (ALA), there were significant differences in urease (URE), alkaline phosphatase (ALP),
Fig. 2. Vegetation influence on α-amylase activity and α-amylase activity per unit of organic carbon.
190
B. Wang et al. / Catena 92 (2012) 186–195
Fig. 3. Vegetation influence on saccharase activity and saccharase activity per unit of organic carbon.
catalase (CAT), saccharase (SAC), polyphenol oxidase (PPO), and cellulase (CEL) in soils of different vegetation types (P b 0.01, Table 2). Moreover, compared to non-restoration of slope farmland and climax community of Chinese arborvitae soils, saccharase, cellulase, urease, catalase and alkaline phosphatase activities increased while polyphenol oxidase activity decreased. Generally, forest generates more litter than grassland, which in turn creates more microbial biomass hence higher enzyme activities in the soil. The current study showed that the total enzyme activities were always lower in grassland soil than in forest land soils, but higher than that in slope farmland soil. In addition, enzyme activities in the soils of mixed forest were higher than that in other forest soils such as korshinsk peashrub and Chinese pine, but still lower than that in the soils of native forest of Chinese arborvitae (Figs. 2 to 8). For all of the carbon cycle enzymes (Figs. 2 to 5), the activities of polyphenol oxidase and cellulase in forest soils were similar to
those in the grassland soil. Differently, polyphenol oxidase activities in the soils of grassland, black locust, korshinsk peashrub, Chinese pine, the mixed forest of Chinese pine and amorpha, and the mixed black locust and amorpha were 23.2, 24.5, 25.0, 26.2, 28.6 and 29.3% less than that in the soil of slope farmland, and 1.4, 1.5, 1.5, 1.5, 1.5 and, 1.6 times greater than that in the soil of native Chinese arborvitae forest. Soil polyphenol oxidase mainly comes from edaphon, secretion of plant roots and propagation residue. Our results showed that the activity of polyphenol oxidase in the soils of restored lands decreased while available soil N increased, comparing to the slope farmland and native forest. This might be because that the increased available soil N inhibited the activity of oxidative enzymes such as polyphenol oxidase and peroxidase (Sinsabaugh et al., 2005). While cellulase activities in the soils of grassland, black locust, korshinsk peashrub, Chinese pine, the mixed Chinese pine and amorpha, and the mixed black locust and amorpha were 1.5, 1.4, 1.4, 1.2, 1.5 and
Fig. 4. Vegetation influence on polyphenol oxidase activity and polyphenol oxidase activity per unit of organic carbon.
B. Wang et al. / Catena 92 (2012) 186–195
191
Fig. 5. Vegetation influence on cellulase activity and cellulase activity per unit of organic carbon.
1.4 times greater than in that in the soil of slope farmland and 47.7, 51.8, 52.1, 56.3, 48.0 to 52.3% less than that in the soil of Chinese arborvitae. Cellulase activity is affected by the quality of organic matter. Besides, the decomposition of cellulose is controlled by cellulase levels in the soil. The current study showed that the increase in organic matter accumulation improved cellulase activity thus increased the decomposition of cellulose in plant litter. The activities of α-amylase and saccharase in the soil of mixed Chinese pine and amorpha were similar to those in the soil of mixed black locust and amorpha. The α-amylase activity was highest in Chinese pine soil (4.1 μmol maltose g − 1 soil h − 1), and lowest in black locust soil (2.5 μmol maltose g − 1 soil h − 1). The reason for high α-amylase activity in Chinese pine soil was that the leaf of Chinese pine contains resin which creates a low pH environment favorable for α-amylase (Guan, 1986). However, saccharase activity was lowest in Chinese pine soil (9.9 μmol glucose g − 1 soil h − 1), but highest in black locust
soil (18.2 μmol glucose g − 1 soil h − 1). Soluble soil organic matter accumulated with the increase in soil saccharase activity which directly participated in the process of organic matter metabolism. As mentioned above, forest always returned more litter than other species such as grass and shrub. After 30 years' restoration, biomass on the forest soil surface increased and returned more litter to soil, thus multiplying saccharase activity. Because the leaf of Chinese pine was difficult to be decomposed, the saccharase activity in Chinese pine soil was therefore low. For nitrogen cycle enzymes, urease and catalase activities varied significantly under different vegetations. Urease plays an important role in soil nitrogen cycle and utilization because it can hydrolyze urea to ammoniacal nitrogen. In this study, urease activity was found to be high in the soils of restored forest lands and low in grassland soil (Figs. 6 and 7). This is because korshinsk peashrub and black locust were nitrogen fixing legume plant. Their soil urease activities
Fig. 6. Vegetation influence on urease activity and urease activity per unit of organic carbon.
192
B. Wang et al. / Catena 92 (2012) 186–195
Fig. 7. Vegetation influence on catalase activity and catalase activity per unit of organic carbon.
were therefore high under these trees. The fact that the urease activity in korshinsk peashrub soil was higher than that in the soils of black locust and Chinese arborvitae indicates that korshinsk peashrub has higher utilization efficiency in nitrogen. On the other hand, there is more nitrogen content in the black locust soil due to its nitrogen fixation capability. Catalase activity was found to be high in black locust soil but low in the mixed forest of Chinese pine and amorpha or the mixed black locust and amorpha (Fig. 7). The increase in soil catalase activity could affect soil solution chemistry and change soil redox conditions. This change of soil solution has the potential to dissociate bonds between metals and complex organic matter and therefore alter soil carbon storage. Catalase therefore has a great effect on changing soil redox, chemical properties of soil solution, and accelerating transformation of organic matter. The high value of catalase
activity in black locust soil indicated that black locust played a great role in improving soil quality. Mixed forest usually has abundant species and its catalase activity should be higher than that on other restored lands. However, catalase activities in mixed forest of Chinese pine and amorpha soil and black locust and amorpha soil were lowest compared to other restored lands. This may be attributed to the species interaction between Chinese pine and amorpha as well as black locust and amorpha that weakened the catalase activity. Finally, the values of phosphorus cycle enzyme and alkaline phosphatase were high in the mixed forest soils of black locust and amorpha, and Chinese pine and amorpha, but low in the black locust and Chinese pine soils (Fig. 8). Alkaline phosphatase is a kind of hydrolase in soils and mainly extracellular, their activities were still alive despite the lysis of the cells. Additionally, hydrolase is released by
Fig. 8. Vegetation influence on alkaline phosphatase activity and alkaline phosphatase activity per unit of organic carbon. Note: For Figs. 2 to 8, SF is sloped farmland, CA is Chinese arborvitae, GL is grassland, KP represents korshinsk peashrub, CP is Chinese pine, CPA is mixed forest of Chinese pine and amorpha, and BLA represents a mixed forest of black locust and amorpha.
B. Wang et al. / Catena 92 (2012) 186–195
microorganisms in response to their substrates. With the increasing of organic matter and total nitrogen, the activity of hydrolase also increased. Due to the abundant species of mixed forests, more leaf return to the soil. They cause the content of soil nutrient to increase which in turn lead to the increased activity of alkaline phosphatase. 3.3. Expressing soil enzymatic activities on an organic matter basis Soil organic matter is an organic carrier of soil enzymes. Organic amendments added to soils are rapidly decomposed by microbial transformation, releasing essential nutrients of N, P and K. It is always difficult to determine whether the observed modifications in the enzymatic activities are due to the organic matter content in the soils or to real differences in enzymatic activity. Both soil nutrients and enzyme may be used as the indictor of soil quality. However, they may interact with each other and make the usage of both of them misleading in some cases. One approach to solve this issue is to use the values of enzyme activity per unit of organic carbon (Barriuso et al., 1988). Expressing activity on an organic matter basis shows a microbial property, as it expresses the nutritional status of the organic matter present from the perspective of the microorganism. The changes of enzyme activities per unit of organic carbon were different to soil nutrients and enzymes in restored lands. For carbon cycle enzymes (Figs. 2 to 5), activity of α-amylase per unit of organic carbon was significantly higher in Chinese pine soil (almost fourfold than in native forest soil), and lower in the soil of mixed black locust and amorpha comparing with other restored soils. Activity of saccharase per unit of organic carbon was higher in black locust soil and lower in the soils of Chinese pine and the mixed black locust and amorpha comparing with restored soils. Activities of polyphenol oxidase and cellulase per unit of organic carbon were clearly higher in the soils of black locust and korshinsk peashrub, and lower in the soil of mixed black locust and amorpha comparing with other restored soils. Noteworthily, activity of polyphenol oxidase per unit of organic carbon in black locust soil was almost sextuple than that in native forest soils. As to the nitrogen cycle enzymes (Figs. 6 and 7), activity of urease per unit of organic carbon was higher in korshinsk peashrub soil (almost fourfold than in native forest soils), and lower in the soils of grassland and the mixed black locust and amorpha comparing with other restored soils. Activity of catalase per unit of organic carbon was obviously higher in black locust soil and lower in the soils of black locust and amorpha, Chinese pine and grassland than that in the soils of korshinsk peashrub and mixed Chinese pine and amorpha. For the phosphor cycle enzymes (Fig. 8), activity of alkaline phosphatase per unit of organic carbon was higher in the soils of korshinsk peashrub and mixed Chinese pine and amorpha, and lower in the soil of mixed black locust and amorpha than that in the soils of other restored lands. As mentioned above, soil enzyme activities per unit of organic carbon changed differently compared to enzyme activities on different lands. Considered the organic matter discussed in Section 3.1, the maximum value of soil enzyme activities per unit of organic carbon was found in cultivated soil (slope farmland), and the minimum value was found in the native forest soil that had not been affected by human activities in recent history. We also found that soil enzyme activity per unit of organic carbon was high in the soil of low organic matter content. For example, the content of organic matter in the soil of mixed forest of Chinese pine and amorpha was lower than that in the soil of mixed black locust and amorpha. Their enzymes activities were similar to each other. But enzyme activities per unit of organic carbon in the soil of mixed forest of Chinese pine and amorpha were clearly higher than that in the soil of mixed black locust and amorpha. Similarly, the content of organic matter in grassland soil was higher than that in the soil of mixed Chinese pine and amorpha. But enzyme activities per unit of organic carbon were lower than that in the soil of mixed Chinese pine and amorpha. The urease activity per
193
unit of organic carbon was much lower in grassland soil than that in the soil of mixed Chinese pine and amorpha. Moreover, the changes in enzymatic activity per unit of organic carbon were not only affected by the content of organic matter, but also affected by the land use (vegetation restoration model) and enzyme species. For example, the content of organic matter in black locust and korshinsk peashrub soil was similar to each other, but there was a great difference in their enzyme activity per unit organic matter, especially for urease, catalase and saccharase. It is usually thought that a decrease in the soil organic matter content would be accompanied by a similar reduction in enzymatic activity. The results of soil enzyme activities per unit of organic carbon obtained here are significant and unexpected. In general, vegetation restoration increases the content of organic matter, which generates stress in the microbiota, therefore causing enzyme activities enrichment (Doran, 1980). However, the utilization efficiency of soil enzyme to organic matter was enhanced to retain soil metabolic activity in the low content of organic matter soil, and would indirectly increase the proportion of enzymes in the organic matter from soil.
3.4. Multidimensional scaling (MS) analysis Soil nutrients, enzyme activities and soil enzyme activity per unit of organic carbon showed a great difference among different species through above-mentioned analysis. To better understand the relationship between soil nutrient and microorganism, and to visualize the improvement of different vegetations on soil properties, multidimensional scaling (MS) ordination is employed here to compare the effects of vegetations on soil nutrients, enzymes and the enzyme activity per unit of organic carbon. MS ordination results showed that slope farmland and Chinese arborvitae appeared always at the two ends of abscissa, represented the starting point and the end point of the restoration processes (Fig. 9A to E). As for the effects of vegetations on soil nutrients, Black locust, Chinese pine, grassland and korshinsk peashrub were close to each other on the chart, indicating the similarity of these plants in their enrichment to soil (Fig. 9A, Stress = 0, RSQ = 1). Just as mentioned above that soil nutritional properties in black locust soil were enhanced, while in Chinese pine soil were weakened by mixing with amorpha. This large difference between the mixed black locust and amorpha and the mixed Chinese pine and amorpha in soil nutrients was also reflected by the result of MS ordination. For the effect of vegetations on soil enzymes, result of MS ordination showed that black locust and Chinese arborvitae, two mixed forests, Chinese pine, and the grass land were similar to each other (Fig. 9B, Stress = 0.2%, RSQ = 0.999). The difference of MS results on nutrients and enzymes indicated that the change of soil nutrient contents and enzyme activities was not always consistent. For the effect of vegetations on the enzyme activity per unit of organic carbon, MS ordination result showed that grassland and Chinese pine, and korshinsk peashrub, and black locust were similar to each other (Fig. 9C, Stress = 0.6%, RSQ = 0.999). And, their organic matter values were also similar to each other. This result indicated that there is an interaction between soil enzyme activity per unit of organic carbon and organic matter. For the effects of vegetations on both soil nutrients and enzymes, MS ordination showed a great difference compared to the MS result of soil nutrients or enzymes. Only grassland and Chinese pine were similar to each other in this regard (Fig. 9D, Stress = 3.0%, RSQ = 0.996). Soil enzyme activity was not only affected by the content of soil nutrient, but also affected by other factors such as vegetations, enzyme species, etc. This may due to a divergence between soil enzyme activity and soil nutrient in soils. However, grassland and Chinese pine showed a similarity both in soil nutrients and enzymes for their low nutrients content and enzyme activities. Finally, the effects of vegetations on soil nutrients, enzymes and the enzyme activity per unit of organic carbon, the result showed a great similarity to
194
B. Wang et al. / Catena 92 (2012) 186–195
added to soils are rapidly decomposed by microbial transformation, releasing essential nutrients such as N, P and K. Soil enzyme takes part in the process of organic decomposition, and soil enzyme enrichment clearly occurs in response to soil nutrients, and to vegetation types. Our results of MS ordination did not found the interaction of soil nutrients with other factors (such as soil enzyme activities). The interaction was only noticeable when MS analysis was modified to include soil nutrients, enzymes and the enzyme activity per unit of organic carbon. The modified analysis showed the importance of the enzyme activity per unit of organic carbon in understanding the interaction of soil nutrients and enzymes. It was a norm in the past to use soil nutrient and enzyme to assess soil quality. The current study however suggests that the enzyme activity per unit of organic carbon should be used instead in order to better understand the interactions of soil enzyme and nutrients. 4. Conclusions Re-vegetation has been reported as the most effective and useful way to abate soil erosion and soil degradation and to restore the ecological integrity of disturbed ecosystems. Our study found that restoration of the degraded lands in Loess areas in China has a significant effect on soil properties and soil nutrient cycle. Mixed forest increased in some circumstances but decreased in other situations the contents of soil nutrient compared to the single tree species. Soil enzyme was mainly influenced by vegetation species. Organic matter influenced soil enzyme activity per unit of soil organic carbon at different levels. In general, the low content of organic matter in soils was caused by the high enzyme activity per unit of soil organic carbon, but was also caused by the interactions with other factors such as vegetations and enzyme species. Moreover, the enzyme activity per unit of organic carbon may play a great role in understanding the interactions of soil nutrients and enzymes. The order of soil qualities under different land uses is generally the soil of native forest, restored land of forest, grassland, and slope farmland. The study showed that, despite that they were still less than that of Chinese arborvitae (the local climax community), the soil properties of 30-year restored forest lands had improved greatly comparing with non-restored slope farmland, The results confirmed that the vegetation restorations can play an important role in improving soil properties. It also implies that severe vegetation destruction in the semi-arid loess Plateau could be reversed by a management approach of secondary succession of vegetation on a large spatial scale. Acknowledgment This work was funded by the National Sciences Foundation of China Project (No. 40801094), the Strategic Technology Project of CAS (XDA05060300), and the Hundred Talents Project of the Chinese Academy of Sciences. The authors thank the members of the Ansai Research Station of Soil and Water Conservation, Chinese Academy of Sciences for technical assistance. Fig. 9. Ordination of (A) soil nutrients, (B) soil enzymes, (C) soil enzyme activity per unit of organic carbon, (D) soil nutrients and enzymes and (E) soil nutrients, enzymes and enzyme activity per unit of organic carbon under different vegetations using Multidimensional scaling (MS). The first dimension represents the soil quality scale from the starting point of restoration (slope farmland) to maximum quality soils and (Chinese arborvitae), and the second dimension represents the individual difference of vegetations. Interactions in Euclidean distance model stopped when stress is less than 0.005.
the MS ordination that included only soil nutrients (Fig. 9E, Stress = 22.0%, RSQ = 0.768). Soil nutrients play an important role in the process of vegetation growth. The content of organic matter in subsurface soils greatly increased after decomposition of the soil mantle. Organic amendments
References Badiane, N.N.Y., Chotte, J.L., Pate, E., Masse, D., Rouland, C., 2001. Use of soil enzyme activities to monitor soil quality in natural and improved fallows in semi-arid tropical regions. Applied Soil Ecology 18, 229–238. Barriuso, E., Pérez-Mateos, M., González-Carcedo, S., 1988. Actividad Ureasa especifica de suelo. Agrochimica 32, 284–294. Benitez, E., Melgar, R., Nogales, R., 2004. Estimating soil resilience to a toxic organic waste by measuring enzyme activities. Soil Biology and Biochemistry 36, 1615–1623. Bergstrom, D.W., Monreal, C.M., King, D.J., 1998. Sensitivity of soil enzyme activities to conservation practices. Soil Science Society of America Journal 62, 1286–1295. Boerner, R.E.J., Brinkman, J.A., Smith, A., 2005. Seasonal variations in enzyme activity and organic carbon in soil of a burned and unburned hardwood forest. Soil Biology and Biochemistry 37, 1419–1426.
B. Wang et al. / Catena 92 (2012) 186–195 Cerdà, A., 1996. Soil aggregate stability in three Mediterranean environments. Soil Technology 9, 133–140. Cerdà, A., 1997. The effect of patchy distribution of Stipa tenacissima L. on runoff and erosion. Journal of Arid Environments 36, 37–51. Cerdà, A., 1998. Soil aggregate stability under different Mediterranean vegetation types. Catena 32, 73–86. Cerdà, A., 2002. The effect of season and parent material on water erosion on highly eroded soils in eastern Spain. Journal of Arid Environments 52, 319–337. Dalal, R.C., 1998. Soil microbial biomass—what do the numbers really mean? Australian Journal of Experimental Agriculture 38, 649–665. Dick, R.P., 1994. Soil enzyme activities as indicators of soil quality. In: Doran, J.W., Coleman, D.C., Bezdicek, D.F., Stewart, B.A. (Eds.), Soil Enzymes. Soil Science Society of America, Madison, WI, pp. 107–124. Dick, W.A., Tabatabai, W.A., 1992. Significance and potential use of soil enzymes. In: Metting, F.B. (Ed.), Soil Microbial Ecology. Marcel Decker, NY, pp. 95–130. Doran, J.W., 1980. Soil microbial and biochemical changes associated with reduced tillage. Soil Science Society of America Journal 44, 765–771. Editorial Committee, 1996. Soil Physical and Chemical Analysis Description of Soil Profiles. Standards Press of China, Beijing (In Chinese). Fenner, N., Freeman, C., Reynolds, B., 2005. Observations of a seasonally shifting thermal optimum in peatland carbon-cycling processes; implications for the global carbon cycle and soil enzyme methodologies. Soil Biology and Biochemistry 37, 1814–1821. Fog, K., 1988. The effect of added nitrogen on the rate of decomposition of organic matter. Biological Reviews 63, 433–462. Gil-Sotres, F., Trasar-Cepeda, C., Leirós, M.C., Seoane, S., 2005. Different approaches to evaluating soil quality using biochemical properties. Soil Biology and Biochemistry 37, 877–887. Guan, S.Y., 1986. Soil Enzyme and its Research Approaches. China Agriculture Press, Beijing (In Chinese). Hou, F.J., Xiao, J.Y., Nan, Z.B., 2002. Eco-restoration of abandoned farmland in the loess plateau. Chinese Journal of Applied Ecology 13, 923–929 (In Chinese). ISSCAS, Institute of Soil Science, Chinese Academy Science, 1978. Physical and Chemical Analysis Methods of Soils. Shanghai Science Technology Press, Shanghai (In Chinese). Klein, D.A., Sorensen, D.L., Redente, E.F., 1985. Soil enzymes: A predictor of reclamation potential and progress. In: Tate, R.L., Klein, D.A. (Eds.), Soil Reclamation Processes. Microbiological Analyses and Applications, Marcel Dekker, New York, pp. 273–340. Laflen, J.M., 2000. Soil Erosion and Dryland Farming. CRC Press. Liu, X.M., Zhao, H.L., 1993. Comprehensive Strategy for Ecoenvironmental Control in Horqin Sand Land. Gansu Science and Technology Publishing, Lanzhou (In Chinese). Mariotte, C.A., et al., 1997. Spatial variability of soil total C and N and their stable isotopes in an upland Scottish grassland. Plant and Soil 196, 151–162.
195
Saggar, S., McIntosh, P.D., Hedley, C.B., Knicker, H., 1999. Changes in soil microbial biomass, metabolic quotient, and organic matter turnover under Hieracium (H. pilosella L.). Biology and Fertility of Soils 30, 232–238. Schimel, J.P., Weintraub, M.N., 2003. The implications of exoenzyme activity on microbial carbon and nitrogen limitation in soil: a theoretical model. Soil Biology and Biochemistry 35, 549–563. Sinsabaugh, R.L., Moorhead, D., 1994. Resource allocation to extracellular enzyme production: a model for nitrogen and phosphorus control of litter decomposition. Soil Biology and Biochemistry 26, 1305–1311. Sinsabaugh, R.L., Antibus, R.K., Linkins, A.E., 1991. An enzymic approach to the analysis of microbial activity during plant litter decomposition. Agriculture, Ecosystems & Environment 34, 43–54. Sinsabaugh, R.L., Gallo, M.E., Lauber, C., Waldrop, M.P., Zak, D.R., 2005. Extracellular enzyme activities and soil organic matter dynamics for northern hardwood forests receiving simulated nitrogen deposition. Biogeochemistry 75, 201–215. Soil Science Society of China, 1999. Soil Physical and Chemical Analysis. Agricultural Science and Technology, Beijing (In Chinese). Stark, C.H., Condron, L.M., O'Callaghan, M., Stewart, A., Di, H.J., 2008. Differences in soil enzyme activities, microbial community structure and short-term nitrogen mineralisation resulting from farm management history and organic matter amendments. Soil Biology and Biochemistry 40, 1352–1363. Trasar-Cepeda, C., Leirós, C., Gil-Sotres, F., Seoane, S., 1997. Towards a biochemical quality index for soils: an expression relating several biological and biochemical properties. Biology and Fertility of Soils 26, 100–106. Trasar-Cepeda, C., Gil-Sotres, F., Leirós, M.C., 2007. Thermodynamic parameters of enzymes in grassland soils from Galicia, NW Spain. Soil Biology and Biochemistry 39, 311–319. Trasar-Cepeda, C., Leirós, M.C., Gil-Sotres, F., 2008. Hydrolytic enzyme activities in agricultural and forest soils. Some implications for their use as indicators of soil quality. Soil Biology and Biochemistry 40, 2146–2155. Wang, B., Liu, G., Xue, S., Zhu, B., 2011. Changes in soil physico-chemical and microbiological properties during natural succession on abandoned farmland in the Loess Plateau. Environmental Earth Sciences 62, 915–925. Wei, J., Zhou, J., Tian, J., He, X., Tang, K., 2006. Decoupling soil erosion and human activities on the Chinese Loess Plateau in the 20th century. Catena 68, 10–15. Yakovchenko, V., Sikora, L.J., Kaufman, D.D., 1996. A biologically based indicator of soil quality. Biology and Fertility of Soils 21, 245–251. Yüksek, T., Yüksek, F., 2011. The effects of restoration on soil properties in degraded land in the semi-arid region of Turkey. Catena 84, 47–53. Zhou, Z.C., Shangguan, Z.P., Zhao, D., 2006. Modeling vegetation coverage and soil erosion in the Loess Plateau area of China. Ecological Modelling 198, 263–268. Zou, H.Y., Liu, G.B., S.W.H., 2002. The vegetation development in North Ziwulin forest region in last fifty years. Acta Botanica Boreali-Occidentalia Sinica 22, 1–8 (In Chinese).
