Soil Microbial Activity During Secondary Vegetation Succession in Semiarid Abandoned Lands of Loess Plateau

Pedosphere 19(6): 735–747, 2009 ISSN 1002-0160/CN 32-1315/P c 2009 Soil Science Society of China  Published by Elsevier Limited and Science Press

Soil Microbial Activity During Secondary Vegetation Succession in Semiarid Abandoned Lands of Loess Plateau∗1 JIANG Jin-Ping1,4 , XIONG You-Cai1 , JIANG Hong-Mei2 , YE De-You3 , SONG Ya-Jie5 and LI Feng-Min1,∗2 1 Key

Laboratory of Arid and Grassland Ecology of Education Ministry of China, School of Life Sciences, Lanzhou University, Lanzhou 730000 (China) 2 Key Laboratory of Arid and Grassland Ecology of Education Ministry of China, School of Resources and Environment Science, Lanzhou University, Lanzhou 730000 (China) 3 Gansu Academy of Agricultural Science, Lanzhou 730070 (China) 4 Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008 (China) 5 School of Forestry and Environment Studies, Yale University, New Haven CT06511 (USA) (Received November 9, 2008; revised September 22, 2009)

ABSTRACT To show the vegetation succession interaction with soil properties, microbial biomass, basal respiration, and enzyme activities in different soil layers (0–60 cm) were determined in six lands, i.e., 2-, 7-, 11-, 20-, and 43-year-old abandoned lands and one native grassland, in a semiarid hilly area of the Loess Plateau. The results indicated that the successional time and soil depths affected soil microbiological parameters significantly. In 20-cm soil layer, microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), MBC/MBN, MBC to soil organic carbon ratio (MBC/SOC), and soil basal respiration tended to increase with successional stages but decrease with soil depths. In contrast, metabolic quotient (qCO2 ) tended to decrease with successional stages but increase with soil depths. In addition, the activities of urease, catalase, neutral phosphatase, β-fructofuranosidase, and carboxymethyl cellulose (CMC) enzyme increased with successional stages and soil depths. They were significantly positively correlated with microbial biomass and SOC (P < 0.5), whereas no obvious trend was observed for the polyphenoloxidase activity. The results indicated that natural vegetation succession could improve soil quality and promote ecosystem restoration, but it needed a long time under local climate conditions. Key Words:

microbial biomass carbon, microbial biomass nitrogen, SOC, soil enzyme activity

Citation: Jiang, J. P., Xiong, Y. C., Jiang, H. M., Ye, D. Y., Song, Y. J. and Li, F. M. 2009. Soil microbial activity during secondary vegetation succession in semiarid abandoned lands of Loess Plateau. Pedosphere. 19(6): 735–747.

INTRODUCTION In semiarid ecosystems, dominant plants often cause the changes in soil properties which lead to complex local interactions between vegetation and soil (Wilson and Agnew, 1992). In the gully and hilly region of the semiarid Loess Plateau, vegetation destruction, caused by the removal of firewood, overgrazing, and unsuitable agricultural practices together with adverse environmental and extreme climate conditions, led to the permanent land degradation, the fertility loss, and the environmental deterioration (Wang, 2002; Jiang et al., 2007). A key factor causing soil degradation is the reduction in vegetation cover, allowing increased erosion and degradation processes and decreased soil quality (Jia et al., 2004). The restoration of native vegetation cover is a critical practice against erosion by abandonment, especially for those lands with low productivity or over 20◦ slope angle (Wang, 2002). ∗1 Project

supported by the National Key Basic Research Program (973 Program) of China (No. 2007CB106804), the PhD candidate Training Program (No. 20060730027), and the “111” Project from the State Administration of Foreign Experts Affairs (SAFEA) and the Ministry of Education of China. ∗2 Corresponding author. E-mail: [email protected].

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The microbiological and biochemical status of the soil is often proposed as an early and sensitive indicator of soil ecological stress or restoration processes in both native and secondary agroecosystems (Martyniuk and Wagner, 1978; Dick, 1994). In general, it is believed that the changes in microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), basal soil respiration, and metabolic quotient (qCO2 ) can explain most of the soil ecological processes. Short-term change in microbial biomass can reflect the long-term trend of the organic matter (Powlson et al., 1987). These parameters are closely linked to the primary productivity of the ecosystem (Zak and Pregitzer, 1990) and responsible for the nutrient cycling and development and function of the soil system. Several studies have been published on the potential use of microbiological parameters as indices of soil productivity or microbial activity (Sparling, 1997; Klose et al., 2004). Biochemical parameters include the activities of some soil enzymes, which play a key role in regulating soil nutrient cycling. Enzyme activities in soil result from the activities of accumulated enzymes and from enzyme activities of proliferating microorganisms (Kiss et al., 1975), which are also very responsive and provide immediate and precise information on small changes occurring in soil (Dick and Tabatabai, 1993). There are increasing evidences that such parameters are also sensitive indicators of ecology stress suffered by a soil and its recovery, because microbial activity has a direct influence on the stability and fertility of ecosystems (Dick et al., 1996). Vegetation succession might be related to the degraded soil properties (Aweto, 1981), and abandoned land also could recover soil quality by restoring native vegetation (Wang, 2002; Jia et al., 2004). In most areas of Loess Plateau, lots of slope lands and native grasslands were used as farm lands because of population pressure, which led to soil degradation and soil erosion. The Chinese government has launched a series of nation-wide conservation projects focused on the ecological restoration mainly by returning cropland to forest and grassland, and the Loess Plateau is one of the key areas. Therefore, understanding the secondary vegetation development and soil quality changes during the vegetation succession of abandoned croplands in the Loess Plateau is becoming increasingly important. Some studies showed that establishment of forestry or seeded grassland as well as native vegetation regeneration through secondary succession can restore the quality of degraded soil, maintain the fertility of soil, and then improve the stability of ecosystem (Wang, 2002). In this study the vegetation structure and the soil microbial and enzyme activities in the abandoned lands were determined to show the vegetation succession interaction with soil biological and biochemical properties in the semiarid Loess Plateau. MATERIALS AND METHODS Study site This study was conducted at the Semiarid Ecosystem Research Station of the Loess Plateau, Lanzhou University, from April to October 2004. The study area is located at Zhonglianchuan Village, a typical northern mountainous region of Yuzhong County (36◦ 02 N, 104◦ 25 E, 2 400 m above sea level), Gansu Province, China. The area has a medium temperate semiarid climate, with a mean annual air temperature of 6.5 ◦ C, a mean monthly maximum temperature of 19.0 ◦ C in July, and a mean monthly minimum temperature of −8.0 ◦ C in January. The mean annual precipitation is approximately 320 mm, mostly concentrated between July and September, and the average annual free water evaporation is 1 326 mm. The ratio of rainfall to free evaporation for the area is 0.24. Due to a deep water table, underground water is unavailable for plant growth. The soil is Heima soil (Calcic Kastanozems, FAO Taxonomy), with a field water-holding capacity of 19.7% and a permanent wilting coefficient of 4.5% (Jiang et al., 2007). The experimental site was located on a watershed with an elevation from 2 380 to 2 450 m and a relative gentle slope from 0◦ to 25◦ . A successional sere was selected as the experimental fields, including five abandoned lands with the fallow time of 2, 7, 11, 20, and 43 years and one native grassland. These six experimental fields were adjacent to each other and shared a common bedrock, parent material

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(loess), and topography. The ages of the abandoned lands were identified by inquiring local villagers and collecting the documents of the lands. Owing to the actual age of native grassland exceeding over one century, preliminarily survey indicated that its approximate age was from 140 to 160 years. The 43-year abandoned land and the native grassland were graveyards. The other four lands were abandoned farmlands in recent years, but before abandonment, the conventional rotation in this area was spring wheat (Triticum aestivum L.), potato (Solanum tuberosum L.), and pea (Pisum sativum L.). The disturbance was less to these abandoned lands and native grassland. Orientations of each studied field were positioned by the global positioning system (Garmin-12c). Table I describes the studied fields in detail. TABLE I Description of the studied abandoned lands and native grassland in the semiarid Loess Plateau Studied field Abandoned lands

Native grassland

Time since abandonment years 2

Location

36◦ 02 N 104◦ 25 E

Altitude

Slope angle

Plot area

◦

m 2 440

15

m×m 20 × 30

Dominant plant species

Setaria viridis (Linn.) Beauv., Corispermum declinatum Steph. ex Stev., Elsholtzia densa Levl. Leymus secalinus (Georgi) Tzvel., Heteropappus altaicus (Willd.) Novopokr., Thermopsis lanceolata R. Brown

7

36◦ 02 N 104◦ 25 E

2 432

10

20 × 26

11

36◦ 02 N 104◦ 25 E

2 440

5

25 × 50

L. secalinus (Georgi) Tzvel., Artemisia frigida Willd., H. altaicus (Willd.) Novopokr.

20

36◦ 02 N 104◦ 25 E

2 370

17

15 × 80

L. secalinus (Georgi) Tzvel., H. altaicus (Willd.) Novopokr., A. frigida Willd.

43

35◦ 59 N 104◦ 21 E

2 435

22

30 × 35

Stipa breviflora Griseb., Stipa bungeana Trin., L. secalinus (Georgi) Tzvel

> 140

36◦ 02 N 104◦ 25 E

2 444

9

20 × 40

S. bungeana Trin., Artemisiagmelinii Web. et Stechm.

Sampling and analyzing Soils were sampled at three different layers of 0–20, 20–40, and 40–60 cm in late October (autumn) 2004. In each soil layer, five samples with each size of 0.25 m2 were collected from each direction (i.e., northern, eastern, southern, western, and center) of the 300-m2 plot and three random samples were collected again from each of five samples. The soil samples were passed through a 2-mm sieve, with the exclusion of plant roots, and stored at 4 ◦ C before microbial analysis. Microbial and enzyme assays were conducted within four weeks after sampling. Subsamples were air-dried and ground to pass through a 180-μm sieve for soil physicochemical analyses. A total of 10 quadrats (each 1 m × 1 m) were surveyed in each of the six studied fields. The abundance and height for each plant species in the quadrats and the vegetation coverage were recorded every month from April to October 2004. The soil bulk density was determined by the auger-hole method (O’Connell, 1975). Soil pH (soil:water = 1:1) was measured with a glass electrode. Available P was extracted by the Olsen bicarbonate method and determined according to the method outlined by Murphy and Riley (1962). Soil organic C (SOC) was determined by the Walkley-Black method (Nelson and Sommers, 1982) and total N by the Kjeldahl − method (Bremner and Mulvaney, 1982). NH+ 4 -N and NO3 -N were measured by FIAstar 5000 analyzer (Foss Tecator AB Sweden Supply Company, Hoganas, Sweden). The basal respiration was determined by measuring the CO2 emission in a 40-d incubation experiment at 28 ◦ C, in which 20 g of each soil sample at 60% of its water-holding capacity was placed in a hermetically sealed polyethylene flask with a vial containing 10 mL 0.1 mol L−1 NaOH and another containing 10 mL distilled water in the dark. The NaOH was titrated with 0.05 mol L−1 HCl every 5 days. The qCO2 was calculated by dividing the C-CO2 released from the soil sample in 1 h by the MBC

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content. The fumigation-extraction method (Vance et al., 1987) was used to determine the soil MBC. For the biological analyses, 135 g of soil sample was wetted to 65% water-holding capacity and incubated at 28 ◦ C for 48 h. A factor of KEC = 0.45 (Joergensen, 1995) was used to convert the C content to MBC. Nitrogen flush was calculated from the difference between ninhydrin-reactive N in fumigated and non-fumigated samples. MBN was calculated by MBN = EN /kEN , where EN = (total N extracted from fumigated soils) − (total N extracted from non-fumigated soils) and kEN = 0.54 (Joergensen and Mueller, 1996). Enzyme activities were determined for all soil samples according to the methods of the Institute of Soil Science, Chinese Academy of Sciences (1985), including catalase (0.1 mol L−1 KMnO4 g−1 , 37 ◦ C, −1 −1 h , 37 ◦ C), neutral phosphatase (g hydroxybenzene g−1 h−1 , 37 ◦ C), 24 h), urease (μg NH+ 4 -N g carboxymethyl cellulose (CMC) enzyme (μg glucose g−1 h−1 ), polyphenoloxidase (mg purpurogallin g−1 h−1 ), and β-fructofuranosidase (0.1 mol L−1 Na2 S2 O3 , mL g−1 d−1 , 37 ◦ C). The reagents used in the analyses, such as disodium phenyl phosphate, 2,6-dibromoquinone chlorimide, CMC sodium, pyrogallic acid, and glucose oxidase, were purchased from Shanghai Chemical Reagent Co., Shanghai of China, all of which were in analytical grade. Statistical analysis All data were calculated based on oven-dry (105 ◦ C) soil weight and presented as arithmetic means of 15 samples for each site. Different statistical analyses were performed separately on the microbial and enzyme activity data sets using the statistical package for the social sciences (SPSS version 13.0 for Windows), including one-way ANOVA, Duncan’s multiple range comparison (P = 0.05), correlation analyses by Pearson, and principal component analysis (PCA). Multiple linear regression analysis was performed on the first two principal components (PCs) for the microbial and enzyme activities and soil physicochemical properties. RESULTS Vegetation succession The dominant plant species showed noticeable differences with years after the cultivation abandonment (Table I). Annual and biannual plants were the dominant species during primary successional stage (2 years), such as Setaria viridis (Linn.) Beauv., Corispermum declinatum Steph. ex Stev., and Elsholtzia densa Levl. However, in the 7-year abandoned land, these species were replaced gradually by perennials, e.g., Leymus secalinus (Georgi) Tzvel., Heteropappus altaicus (Willd.) Novopokr., and Thermopsis lanceolata R. Brown, and annuals persisted as subdominant species. Comparing with the 7-year abandoned land, Artemisia frigida Willd. replaced T. lanceolata R. Brown to become the dominant species in the 11-year abandoned land. In the 20-year abandoned land, some other new species emerged to be important species, but not dominant species, such as Stipa breviflora Griseb., Poa sphondylodes Trin., and Astragalus tanguticus Bat. The largest plant species can be observed in the 43-year abandoned land. Its species richness was 26, and dominant species were Stipa bungeana Trin., S. breviflora Griseb., and L. secalinus (Georgi) Tzvel. In native grassland, S. bungeana Trin. and Artemisia gmelinii Web. et Stechm. were dominant plant species. Species richness in the studied fields showed a hump-shaped curve along the successional sere (Fig. 1). Soil physicochemical properties The main soil physicochemical characteristics of the abandoned lands are shown in Table II. An increased trend was found in SOC and NH+ 4 -N along the successional sere, old abandoned lands having higher (P < 0.5) SOC and NH+ -N contents than young abandoned lands. Total N and NO− 4 3 -N values significantly (P < 0.5) decreased with time since abandonment in topsoil (0–20 cm) during recent successional stages (from 2 to 20 years), and increased during late successional stages (from 20 years

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Fig. 1 Species richness in the studied fields, five abandoned lands with the fallow time of 2, 7, 11, 20, and 43 years and one native grassland (NG), in the semiarid Loess Plateau. TABLE II Soil physicochemical properties in the studied fields, five abandoned lands with the fallow time of 2, 7, 11, 20, and 43 years and one native grassland (NG) in autumn Depth cm 0–20

20–40

40–60

Fallow land

2-year 7-year 11-year 20-year 43-year NG 2-year 7-year 11-year 20-year 43-year NG 2-year 7-year 11-year 20-year 43-year NG

Bulk density g cm3 1.05Da) 1.15BC 1.13C 1.18A 1.16AB 1.06D 1.20AB 1.21A 1.18ABC 1.17BCD 1.15CD 1.14D -

Moisture content 121ab) D 130aC 132aBC 135aAB 138aA 136aAB 82bC 84bC 91bB 86bC 93bAB 96bA 75cCD 70cE 73cDE 79cBC 82cAB 85cA

Soil organic carbon g kg1 5.5aC 5.6aC 6.2aC 6.5aC 8.7aB 11.4aA 4.2bE 4.5bDE 4.8bD 5.3bC 6.0bB 7.1bA 3.8bD 3.8cD 4.1cCD 4.3cC 5.1cB 6.2bA

Total N

0.62aC 0.60aC 0.57aC 0.58aC 0.84aB 1.15aA 0.41bC 0.44bC 0.46bC 0.48bBC 0.55bB 0.87bA 0.35bDE 0.33cE 0.38cD 0.43bC 0.48cB 0.53cA

NH+ 4 -N

NO− 3 -N

Available P

pH (1:1)

9.1bF 13.8aC 13.2aD 12.7aE 20.9aB 25.3aA 12.1aE 12.5bD 13.2aC 10.7bF 18.3bB 19.6bA 12.2aD 10.6cE 10.7bE 12.7aC 15.2cB 17.6cA

mg kg1 15.4aBC 14.3aCD 12.9aE 13.4aDE 16.6aB 26.6aA 12.1bC 10.8bD 9.6bE 11.3bD 14.0bB 23.6bA 11.5cB 8.9cD 9.5bD 10.5cC 12.1cB 19.9cA

7.4aA 7.1aA 6.9aAB 6.2aB 7.2aA 7.3aA 5.6bABC 5.4bBC 6.0bA 5.2bC 5.8bAB 5.4bBC 4.6cB 4.4cB 4.6cB 4.2cC 4.8cA 4.5cB

8.21bAB 8.22cA 8.20bAB 8.18bB 8.11cC 8.06bD 8.26aA 8.25bAB 8.25aAB 8.23aB 8.16aC 8.12aD 8.28aA 8.29aA 8.26aAB 8.24aB 8.18aC 8.14aD

a) Means followed by the same uppercase letter(s) within a column are not significantly different among successional ages at P < 0.05. b) Means followed by the same lowercase letter(s) within a column are not significantly different among soil depths at P < 0.05.

to native grassland). Soil pH, SOC/TN, and bulk density increased from 2 to 11 years but decreased after 11 years since abandonment. Similar trends were observed in the other depths for the above properties. There were significant differences (P < 0.05) in available P during succession in the same soil layer, and they decreased with the soil depth. Soil moisture in topsoil had no noticeable changing trend with the time since abandonment, but in 20–40 and 40–60 cm layers increased with the time since abandonment. Soil moisture showed significant differences (P < 0.5) among various soil layers. Correlation analyses showed that SOC in topsoil in all successional stages was negatively correlated with soil pH (r = −0.934, P < 0.01) and bulk density (r = −0.309, P < 0.01), but positively correlated with total N (r = 0.927, P < 0.01), available P (r = 0.232, P = 0.028), NH+ 4 -N (r = 0.961, P < 0.01), and NO− -N (r = 0.905, P < 0.01). 3

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Microbial biomass, MBC/MBN, and MBC/SOC MBC, MBN, MBC/SOC, and MBC/MBN of the soils are listed in Table III. MBC showed significant differences (P < 0.5) among the six lands with different abandonment years. The MBC values were 126.34 and 53.61 μg C g−1 for native grassland and 7-year abandoned land in topsoil (0–20 cm), respectively, which were the highest and the lowest among all the successional lands (Table III). It was found that the MBC values in topsoil slightly decreased at early-stage (2–7 years) and gradually increased at late-stage (11 years to native grassland) along the successional sere. The lowest MBN in topsoil was 15.68 μg C g−1 , occurring in 11 years since abandonment, and the highest value was 31.84 μg C g−1 in the native grassland. It means that agricultural production disturbance leads to half reduction of MBC and MBN, which increased again gradually after abandonment. Similar to MBN, a sharp decline of MBC was observed in deeper soil depth, indicating that MBC and MBN were concentrated in topsoil. TABLE III Biological activitiesa) at three depths of the studied fields, five abandoned lands with the fallow time of 2, 7, 11, 20, and 43 years and one native grassland (NG), in the semiarid Loess Plateau Depth cm 0–20

20–40

40–60

Fallow land

MBC

MBN g−1

2-year 7-year 11-year 20-year 43-year NG 2-year 7-year 11-year 20-year 43-year NG 2-year 7-year 11-year 20-year 43-year NG

μg C 56.10aDb) 53.61aD 57.40aD 64.33aC 97.67aB 126.34aA 43.30bE 45.70bDE 48.30bCD 50.52bC 63.07bB 85.30bA 34.62cD 36.80cCD 41.20cC 40.50cC 48.70cB 54.45A

MBC/MBN g−1

μg N 15.60aC 16.30aC 15.82aC 16.85aC 25.10aB 31.84aA 12.85bC 13.30bC 13.81bC 14.10bC 18.52bB 22.65bA 10.74cD 11.58cCD 12.06cC 11.76cCD 14.78cB 16.35cA

% 3.60aBC 3.29bC 3.63aABC 3.82aAB 3.89aAB 3.98aA 3.37abA 3.44aA 3.50aA 3.58abAB 3.56bAB 3.77bA 3.22bA 3.18cA 3.42aA 3.45bA 3.15cA 3.33cA

qCO2

BR μg CO2 -C 0.48aD 0.53aC 0.54aC 0.55aC 0.67aB 0.73aA 0.35bC 0.36bC 0.41bB 0.40bBC 0.44bB 0.56bA 0.30cB 0.30cB 0.32cB 0.33cB 0.38cA 0.42cA

g−1

h−1

μg CO2 -C 8.57aB 9.92aA 9.41aAB 8.57aB 6.81cC 5.78cD 8.09aAB 7.88bB 8.54bA 7.93aB 7.02bC 6.52bD 8.60aA 8.15bA 7.86cA 8.05aA 7.83aA 7.64aA

MBC/SOC mg−1

h−1

% 1.02aB 0.95bCD 0.93bD 1.0aBC 1.11aA 1.12aA 1.04aB 1.02aBC 1.00aBC 0.96aD 1.06aB 1.19aA 0.92AB 0.98aAB 1.02aA 0.94aAB 0.96bAB 0.88bB

a) MBC and MBN are microbial biomass carbon and nitrogen, respectively; BR is basal soil respiration; qCO is metabolic 2 quotient; SOC is soil organic carbon. b) Means followed by the same lowercase and uppercase letter(s) within a column are not significantly different at P < 0.05 among soil depths and successional ages, respectively.

Correlation analyses showed that MBC was closely (P < 0.01) related to SOC and TN in topsoil with r of 0.988 and 0.937, respectively, and negatively correlated with soil pH (r = −0.935, P < 0.01). MBN was also significantly positively correlated with SOC (r = 0.98, P < 0.01) and total N (r = 0.934, P < 0.01) in topsoil and negatively correlated with soil pH (r = −0.924, P < 0.01). MBC/MBN in the topsoil was significantly lower in young abandoned lands (2–20 years) than that in old abandoned fields (43 years and native grassland). MBC/SOC showed higher values in topsoil at successional late-stages compared with those at the early-stages. A similar trend was found in deeper soils, but the values were generally lower. MBC/MBN in topsoil of six lands was significantly positively correlated with SOC (r = 0.707, P < 0.01), TN (r = 0.621, P < 0.01), MBC (r = 0.727, P < 0.01), and MBN (r = 0.631, P < 0.01). MBC/SOC was significantly positively correlated with SOC (r = 0.697, P < 0.01), TN (r = 0.728, P < 0.01), MBC (r = 0.794, P < 0.01), and MBN (r = 0.770, P < 0.01). Based on PCA, the change in soil microbial biomass was obvious with comparison of MBC and

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MBN in six fallow lands (Fig. 2a). The first PC accounted for 65.5% of the variation in the microbial biomass and obviously separated 2-, 7-, 11-, and 20-year abandoned lands. The second PC accounted for 15.3% and obviously separated native grassland, 43-, and ≤ 20-year abandoned lands. The combination of these two factors reflected the variation in soil microbial activities according to abandoned land ages. Although the difference between the 7- and 11-year abandoned lands was not significant, the four abandoned lands with fallow time from 2 to 20 years could be distinguished along the PC1 axis. Along the PC2 axis, native grassland had the largest microbial activities. The two PCs were correlated with soil physicochemical parameters by regression analysis, showing that PC1 can be predicted from a linear 2 equation of PC1 = 0.486SOC − 3.634pH − 0.128SOC/TN − 0.064NO− 3 -N (r = 0.934, P < 0.05). The + PC2 can also be predicted by the equation of PC2 = −0.455NH4 -N + 1.661SOC − 0.302NO− 3 -N − 0.25SOC/TN (r2 = 0.474, P < 0.05).

Fig. 2 Scores of the first two principal components (PCs) of the microbial (a) and enzyme activities (b) in topsoil (0–20 cm) of the studied fields, five abandoned lands with the fallow time of 2, 7, 11, 20, and 43 years and one native grassland (NG), in the semiarid Loess Plateau.

Basal respiration, qCO2 and enzyme activities Soil basal respiration showed significant differences (P < 0.05) among the lands with different abandonment years (Table III). The lowest value of 0.48 μg CO2 -C g−1 h−1 was found in topsoil of 2year abandoned land and the highest value of 0.73 μg CO2 -C g−1 h−1 was in topsoil of native grassland. Soil basal respiration differed significantly (P < 0.5) among the three sampling depths (Table III). They tended to increase at the upper layer. qCO2 ranged between 5.78 and 9.92 μg CO2 -C mg−1 MBC h−1 . Soil basal respiration in topsoil of six lands was significantly correlated with SOC (r = 0.951, P < 0.01), TN (r = 0.868, P < 0.01), MBC (r = 0.949, P < 0.01), and MBN (r = 0.948, P < 0.01). However, qCO2 was significantly negatively correlated with SOC (r = −0.91, P < 0.01), TN (r = −0.869, P < 0.01), MBC (r = −0.943, P < 0.01), and MBN (r = −0.912, P < 0.01). The activities of urease, catalase, β-fructofuranosidase, neutral phosphatase, and CMC enzyme in the soil profile decreased with soil depths, and the significant differences were found among three soil layers (P < 0.5) (Table IV). Moreover, these enzyme activities, except for polyphenoloxidase activity, showed similar trend in each depth, and they increased with the time since abandonment, especially in the topsoil. Correlation analyses showed that six enzyme activities in the topsoil were positively correlated with MBC and MBN (r ≥ 0.235, P ≤ 0.026), SOC (r ≥ 0.216, P ≤ 0.041), and TN (r ≥ 0.304, P ≤ 0.004). The enzyme activities in the topsoil were negatively correlated with pH (r ≤ −0.628, P ≤ 0.01) (with exception of polyphenoloxidase activity) and positively correlated with soil moisture (r ≥ 0.333, P ≤ 0.001) (with exception of neutral phosphatase activity). β-fructofuranosidase and neutral phosphatase activities were positively correlated with available P with r-values of 0.355 (P ≤ 0.001) and 0.471 (P < 0.01), respectively.

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TABLE IV Soil enzyme activities at three soil depths of the studied fields, five abandoned lands with the fallow time of 2, 7, 11, 20, and 43 years and one native grassland (NG), in the semiarid Loess Plateau Depth

Fallow land

cm 0–20

20–40

40–60

2-year 7-year 11-year 20-year 43-year NG 2-year 7-year 11-year 20-year 43-year NG 2-year 7-year 11-year 20-year 43-year NG

Urease

Catalase

β-fructofuranosidase

Phosphatase

Polyphenoloxidase

Carboxymethyl cellulose enzyme

μg NH+ 4 -N g−1 h−1 11.15aDa) 10.68aE 11.24aD 12.06aC 13.59aA 13.28aB 8.68bE 9.15bD 9.26bD 9.71bC 11.32bB 11.78bA 7.33cD 7.86cC 7.76cC 7.93cC 9.17cB 10.24cA

0.1 mol L−1 KMnO4 g−1 8.12aC 8.60aB 8.71aB 8.89aB 10.18aA 10.24aA 6.84bD 6.76bE 7.06bD 7.15bC 8.67bA 8.15bB 6.47bBC 6.14cC 6.63cB 6.79cB 7.88cA 8.06bA

mL (0.1 mol L−1 Na2 S2 O3 ) g−1 0.68aCD 0.69aC 0.64aD 0.67aCD 0.81aB 0.93aA 0.47bC 0.52bB 0.41bD 0.46bC 0.63bA 0.66bA 0.39cC 0.38cC 0.37bC 0.38cC 0.45cB 0.51cA

μg hydroxybenzene g−1 h−1 6.15aAB 5.86aBC 4.97aD 5.56aC 6.63aA 6.48aA 3.35bB 3.45bB 2.71bC 2.85bC 3.68bAB 3.94bA 2.76cA 2.88cA 2.82cA 2.01cB 2.66cA 2.57cA

mg purpurogallin g−1 h−1 0.814bC 0.850bBC 0.895abA 0.834aC 0.847abBC 0.875aAB 0.836abC 0.892aA 0.915aA 0.862aB 0.813bC 0.824bC 0.858aA 0.862abA 0.856bA 0.846aAB 0.857aA 0.818bB

μg glucose g−1 h−1 6.57aE 7.01aD 7.35aCD 7.58aC 8.62aB 9.76aA 5.64bE 5.48bDE 5.96bCD 6.18bC 7.34bB 7.82bA 5.36bCD 5.16cD 5.55bC 5.61cC 6.38cB 7.23cA

a) Means followed by the same lowercase and uppercase letter(s) within a column are not significantly different at P < 0.05 among soil depths and successional ages, respectively.

The PCA for the topsoil was chosen to represent the pattern of enzyme activities in the abandoned lands (Fig. 2b). The PC1 accounted for 59.6% of the variation in the enzyme activities and significantly (P < 0.5) separated 2-, 7-, 11-, and 20-year abandoned land soils. The PC2 accounted for 11.7% and significantly (P < 0.5) separated native grassland, 43-, and ≤ 20-year abandoned land soils (Fig. 2b). The result indicated that the native grassland had the largest enzyme activities and 2-year abandoned land had the smallest value according to the coordinates along the two axes. The two PCs were correlated with soil physicochemical parameters by regression analysis, which showed that PC1 can be predicted − from a linear equation of PC1 = 0.063NH+ 4 -N − 3.469pH + 1.401TN − 0.065NO3 -N + 0.191SOC (r2 = 0.945, P < 0.05). The PC2 can be predicted with the equation of PC2 = 0.262SOC/TN + 0.331 soil moisture (r2 = 0.188, P < 0.05). DISCUSSION Vegetation succession The vegetation survey showed that three typical pioneer plant species (S. viridis (Linn.) Beauv., C. declinatum Steph. ex Stev., and E. densa Levl.) as dominant plants emerged in the bare soil during primary succession of 2 years. In this stage there was basically a newly abandoned farmland. Long-term agricultural activities might have thoroughly destroyed the modules for the proliferation of plants with long life history, while these annuals and biannuals with stable soil seed pool would soon occupy the abandoned soil and develop into dominant species during this period (Wang, 2002). However, these pioneer plant species were replaced with more competitive grasses (L. secalinus (Georgi) Tzvel. and H. altaicus (Willd.) Novopokr.) as succession progressed after 7 years, i.e., the intermediate phase of vegetation succession. Pioneer plant species were less competitive due to their low growth rates compared with perennial herbs, which formed an initial grassland vegetation. These new perennial herbs

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had higher height and cover, increasing the vegetation cover. However, a 7-year period of ecosystem development was too short to enable plant species to colonize the bare soil, and a lot of area still had not been covered by vegetation. Therefore water-soil loss increased and surface soil became poor. New plant species were very few by 11-year succession, but the vegetation cover and species richness increased. During 20-year succession, some plant species (such as A. frigida Willd.) developed and became dominant plant species, which resulted in the increment of vegetation cover, and then affected microbial growth and activity in soils (Paul and Clark, 1996). A big change in vegetation coverage occurred between the 20- and 43-year-old stages. Vegetation covered nearly 60% of the land surface, the number of species increased to 26, and a lot of new plant species emerged. Some annuals and biannuals, such as A. scoparia Waldst. et Kitam and S. viridis (Linn.) Beauv., with large amount of seeds still persisted in this stage as a subdominant but had a lower coverage than that of perennial plants. Some N-fixing legumes (such as Melissitus rutenica (L.) C. W. Chang, T. lanceolata R. Brown, Oxytropis kansuensis Bge., and A. tanguticus Bat.) occurred relatively late in the succession, which were very important plants for enhancing soil nitrogen (Wang and Hu, 2001). After 43 years of succession, the grassland developed into native vegetation with the coverage of nearly 65%, but the number of species declined to 13. This native vegetation was dominated by perennial S. bungeana Trin. and A. gmelinii Web. et Stechm. With the vegetation development, the abundance of annuals decreased and the perennials increased during succession. The increases in vegetation coverage and plant diversity were related to an increase in plant biomass, which most likely resulted in enhanced competition for available nutrient resources in the soil (Heer and K¨orner, 2002). In addition, the increase in vegetation coverage indicates a decreased disturbance with ecosystem development. The latter community represents the balance between soil nutrient/moisture availability and competition and is characterized by high productivity (Tscherko et al., 2005). Succession effect on soil physicochemical properties Soil physicochemical properties varied with the succession years (Tilman, 1986), and vegetation development could affect soil properties (Wang, 2002; Tscherko et al., 2005). Soil bulk density (Ma et al., 2005) and pH (Wang, 2002) decreased during abandoned land succession in the Loess Plateau. This study showed similar trends; SOC, total N, and available N increased, but available P showed no obvious change with the abandonment years. Vegetation development led to the amount of roots increasing underground during succession, which enhanced soil porosity. At the same time fresh litter input with increasing plant cover probably further improved soil organic matter, which decreased soil bulk density and pH. Vegetation cover and a lot of roots could decline soil erosion and water loss, avoiding much available nutrients (such as available N and P) loss, which was an important factor of the increase in − NH+ 4 -N and NO3 -N in the topsoil with the abandonment years. Moreover, some important N-fixing legumes development increased N input, which was useful for soil N accumulation (Wunderlin, 1982). Succession effect on microbial activities and soil basal respiration The microbial biomass, as one of living components of soil organic matter, generally comprises 1%– 5% of total organic matter content. Because of its high turnover rate, microbial biomass content can respond rapidly to the changes in soil ecological environment (Gregorich et al., 1997). With secondary vegetation in abandoned land succession in this study, MBC and MBN were closely related to SOC and TN, which is in agreement with Arunachalam and Pandey (2003). Besides, both MBC and MBN had a close correlation with succession time, indicating the increase in microbial biomass during succession development. The vegetation cover, plant species, and soil organic matter were proved to be the most important drivers of microbial changes during succession (Yao et al., 2000; Tscherko et al., 2003, 2005). Vegetation cover could regulate the temperature regime at the soil surface and provide a favorable environment for microbial growth and activity by declining heat stress, soil dryness, and disturbance at

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the soil surface. Our results showed that soil erosion and water loss increased in primary abandoned land (2–7 years) because dominant plant species was annuals and biannuals with less vegetation coverage and short life history. Plant species richness could affect soil microbial biomass, but the weak correlation between plant species richness and the properties of the underground microbial community suggests that short-term effects on microbial populations caused by specific plant species are less important than long-term soil processes, such as the build-up of soil organic matter (Spehn et al., 2000). The ratio of MBC/MBN is often used to describe the structure and the state of the microbial community. Some studies suggest that a high MBC/MBN ratio means the microbial biomass containing a higher proportion of fungi, whereas a low value indicates bacteria dominated in the microbial population (Campbell et al., 1991). Based on this viewpoint, the ratio in the abandoned lands along succession year gradient in this study could imply that the microbial biomass in the early succession was dominated by bacteria, whereas fungi were predominant in the late succession. Joergensen (1995) reported that the ratio varied from 5.2 in an arable soil to 20.8 in a forest soil. Moore et al. (2000) reported that it was from 4.3 to 11.4 when cropping system studied and found the average ratios increased with the cropping year increasing. Others showed significant temporal changes in the ratio depending on the stage of plant growth (Collins et al., 1992) and plant cover (Drury et al., 1991). In this study, the ratio ranged from 3.29 to 3.98 and changed with successional time, which was relative small. The ratio of MBC/SOC, interpreted as substrate available and the portion of SOC immobilized in microbial cells, is a more sensitive index for measuring SOC or microbial biomass (Garcia et al., 2002), and it is also useful to determine its trend with time (Sparling, 1997). The higher the MBC/SOC in systems with similar properties and conditions, the higher the portion of easily decomposable SOC compared to stable humus compounds (Anderson and Domach, 1989). Some studies showed that MBC/SOC decreased with increasing succession years (Schipper et al., 2001). Our results indicated that the ratio increased with the time since abandonment in topsoil, and there was similar trend in deeper soil. It was reported that MBC/SOC had a wide range from 0.27% to > 4.0% with an average of 2%–3% (Anderson and Domach, 1989), whereas in this study it varied from 0.93% to 1.12% with an average of 1.04% in topsoil. Our data fall into that range, but the values were relatively low, which may result from the higher soil pH (Klose et al., 2004) and severe dry conditions (Wolters et al., 1995). The basal respiration reflected the activity of the soil microflora, which may be related to biodegradation of soil organic compounds in the soil (Brohon et al., 2001). Our results indicated that the basal respiration values increased with the abandonment years. The direct reason may be the higher microbial biomass and microbial activity in the late succession than that in the early succession. However, the percentage of the mineralized SOC is lower in late succession than in early succession, which indicated that SOC would accumulate with the abandonment years. The qCO2 has been used as an ecophysiological index for soil microbes and reflects the bioenergetic status of microbial biomass (Santruckova and Straskraba, 1991). A high value means that soil microbial activity is low in efficiency (Wardle and Ghani, 1995) and that the soil microorganisms are living under environmental stress (Anderson and Domach, 1993). In relation to a stable ecosystem, the qCO2 value increases in a disturbed ecosystem (Haynes, 1999; Tirol-Padre et al., 2007). This is explained by the increased energy need of soil microorganisms to repair damage caused by stress (Odum, 1985). According to these views, the higher qCO2 values may result from long-term agricultural activity with stressed environment in early succession, while its decrease in the late succession indicated that the ecosystem is tending to stability by long-term natural self-restoring. Succession effect on soil enzyme activities Soil enzymes originate from microbial activity, root exudates and the remains of plants and animals (Burns, 1978), so their activities are always correlated with microbial biomass, microbial diversity, and the amount of microorganisms in the soil biota during vegetation succession (Taylor et al., 2002). Our results showed that the enzyme activities, including urease, catalase, neutral phosphatase, β-

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fructofuranosidase, and CMC enzyme, were higher in the latter succession than in the early period and higher in topsoil than in deeper soil. With the improved soil conditions, several microorganisms and plant roots existed in the latter succession and in the topsoil, and the enzymes were involved in their busy metabolism. It was supported by the positively significant correlation between enzyme activities and microbial biomass. Some similar results were obtained by previous researchers. It was found that there were significant positive correlations between MBC and the activities of alkaline phosphatases (r = 0.97, P < 0.01), urease (P < 0.01), and catalase (P < 0.5) (Klose and Tabatabai, 1999; B¨ohme et al., 2005). Thus, soil enzyme activities can be used as important quality index to monitor and evaluate soil quality, although soil enzyme activities often vary with ecological conditions (e.g., seasons, vegetation, soil temperature and moisture). CONCLUSIONS The results provided information on soil quality properties (e.g., physicochemical, biological and biochemical properties) influenced by vegetation succession on fallow land in the hilly region of the semiarid Loess Plateau. The soil quality properties and vegetation cover were improved by natural soil succession over a relatively long time, although local ecosystem had been destroyed by long-term agricultural production patterns and inclement macroscale climate conditions. Furthermore, our results showed that soil microbial activity and enzyme activities were closely related with SOC. Natural vegetation development was very important factor to promote soil quality and local ecosystem restoration, but it needed longer time under local climate conditions. It was obvious that 43 years were not enough to restore the characteristics as found in the native grassland. Hence, establishment of seeded grasslands may be a better measurement to speed vegetation and restore soil quality in this area. REFERENCES Anderson, T. H. and Domsch, K. H. 1989. Ratios of microbial biomass carbon to total organic carbon in arable soils. Soil Biol. Biochem. 21: 471–479. Anderson, T. H. and Domsch, K. H. 1993. The metabolic quotient for CO2 (qCO2 ) as a specific activity parameter to assess the effects of environmental conditions, such as pH, on the microbial biomass of the soil. Soil Biol. Biochem. 25: 393–395. Arunachalam, A. and Pandey, H. 2003. Ecosystem restoration of Jhum fallows in Northeast India: microbial C and N along altitudinal and successional gradients. Restor. Ecol. 11: 168–173. Aweto, A. O. 1981. Secondary succession and soil fertility restoration in southwestern Nigeria. II. Soil fertility restoration. J. Ecol. 69: 609–614. B¨ ohme, L., Langer, U. and B¨ ohme, F. 2005. Microbial biomass, enzyme activities and microbial community structure in two European long-term field experiments. Agr. Ecosyst. Environ. 109: 141–152. Bremner, J. M. and Mulvaney, C. S. 1982. Nitrogen-total. In Page, A. L., Miller, R. H. and Keeney, D. R. (eds.) Methods of Soil Analysis. Part 2. Chemical and Microbiological Properties. ASA, Soil Sci. Soc. Am., Madison, WI. pp. 595–624. Brohon, B., Delolme, C. and Gourdon, R. 2001. Complementarity of bioassays and microbial activity measurements for the evaluation of hydrocarbon-contaminated soils quality. Soil Biol. Biochem. 33: 883–891. Burns, R. G. (ed.). 1978. Soil Enzymes. Academic Press, New York. Campbell, C. A., biederbeck, V. O., Zentner, R. P. and Lafond, G. P. 1991. Effect of crop rotations and cultural practices on soil organic matter, microbial bomass and respiration in a thin Black Chernozem. Can. J. Soil Sci. 71: 363–376. Collins, H. P., Rasmussen, P. E. and Douglas, C. L. J. 1992. Crop rotation and residue management effect on soil carbon and microbial dynamic. Soil Sci. Soc. Am. J. 56: 783–788. Dick, R. P. 1994. Soil enzyme activities as indicators of soil quality. In Doran, J. W., Coleman, D. C., Bezdicek, D. F. and Stewart, B. A. (eds.) Defining Soil Quality for a Sustainable Environment. Soil Sci. Soc. Am., Madison. pp. 107–124. Dick, R. P., Breakwill, D. and Turco, R. 1996. Soil enzyme activities and biodiversity measurements as integrating biological indicators. In Doran, J. W. and Jones, A. J. (eds.) Handbook of Methods for Assessment of Soil Quality. Soil Sci. Soc. Am., Madison. pp. 247–272. Dick, W. A. and Tabatabai, M. A. 1993. Significance and potential uses of soil enzymes. In Metting, F. B. (ed.) Soil Microbial Ecology: Application in Agricultural and Environment Management. Marcel Dekker, New York. pp. 95–125.

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