The succession characteristics of soil erosion during different vegetation succession stages in dry-hot river valley of Jinsha River, upper reaches of Yangtze River

Ecological Engineering 62 (2014) 13–26

Contents lists available at ScienceDirect

Ecological Engineering journal homepage: www.elsevier.com/locate/ecoleng

The succession characteristics of soil erosion during different vegetation succession stages in dry-hot river valley of Jinsha River, upper reaches of Yangtze River Yong-ming Lin a , Peng Cui b,∗ , Yong-gang Ge b , Can Chen a , Dao-jie Wang b , Cheng-zhen Wu a , Jian Li a , Wei Yu a , Guang-shuai Zhang a , Han Lin a a

College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, China Key Laboratory of Mountain Hazards and Earth Surface Process, Chinese Academy of Sciences/Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China b

a r t i c l e

i n f o

Article history: Received 14 May 2013 Received in revised form 4 October 2013 Accepted 15 October 2013 Available online 13 November 2013 Keywords: Dry-hot river valley Vegetation succession Soil erosion 137 Cs technique

a b s t r a c t Declining vegetation coverage caused by serious soil erosion in dry-hot river valley of the Jinsha River has resulted in a vicious cycle of environmental deterioration and aggravated soil erosion. In order to identify the relationship between vegetation succession and transformation of soil erosion, the methods of “space replacing time” and 137 Cs technique have been used to analyze community structure of vegetation and distribution characteristics of 137 Cs contents in the slopes and vegetation units of five succession stages, which included native grassland, shrub, sapling forest, half-mature forest and near mature forest in Jiangjiagou gully, Dongchuan city, Yunnan province. We found, during the course of succession, the number of species in communities increased with vegetation development and succession, but the 137 Cs loss decreased with vegetation succession. Following the succession, near mature forest had the highest 137 Cs inventory and native grassland had the lowest 137 Cs inventory in both slopes and vegetation units. Principal component analysis showed that 137 Cs inventory was significantly positively correlated with average crown diameter of tree (ACDT), species number, tree coverage and average tree height. Average crown diameter of shrub (ACDS) and average shrub height were also positively related to 137 Cs inventory but to a lesser extent. Based on the results of our study, we illustrated the improvement of soil erosion control through soil conservation and water regulation with vegetation succession. Consequently, the results suggest that community features significantly affect soil erosion, through which we can evaluate and predict the soil erosion intensity of different vegetation. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Soils can sustain mature ecosystems in sustainable and stable equilibrium with their environmental conditions (Rodríguez Rodríguez et al., 2005), but their functions degrade due to soil erosion, which rank as main environmental issues in many lands (Morgan, 1995; Pimentel and Kounang, 1998; Burylo et al., 2012). Soil erosion causes the problem of rivers’ sedimentation and increases the possibility of flooding (Bilotta et al., 2007). Furthermore, severe soil erosion results not only in the decline of vegetation productivity, but also in the loss of organic matter of soils, reduction of porosity and aggregate stability that in turn leads to ecological degradation (Rhoton et al., 2002; Dou et al., 2013). Due to this degradation, a decrease in soil quality is caused

∗ Corresponding author. Tel.: +86 13880700168; fax: +86 28 8523 8460. E-mail address: [email protected] (P. Cui). 0925-8574/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ecoleng.2013.10.020

together with reverse ecological succession (Arbelo et al., 2002; Rodríguez Rodríguez et al., 2002a,b; Cui et al., 2012). Therefore, Erosion control and sediment retention has become one of the 17 major ecosystem services contributing to human welfare and development (Costanza et al., 1997). Ecological restoration has been carried out in eroded lands induced by soil erosion (Stokes et al., 2010). As a regular measure to protect soils and prevent water erosion, vegetation protects the soil against erosion by physical binding of soil, and the retention of surface water. The relationship between soil and vegetation has become an important scientific issue in the fields of ecology and erosion. In order to study the relationship between soil and vegetation, in recent years, scientists focused in two main research areas: (1) soil quality change in the process of vegetation succession and (2) the effects of vegetation on erosion control and soil stability. At present, the relationship between soil quality change and vegetation succession has been studied in typical regions. For

14

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

example, Rodríguez Rodríguez et al. (2005) studied vegetation succession and soil degradation in desertified areas (Fuerteventura, Canary Islands, Spain) and found that the vegetation may remain degraded due to the effect of drought, saline–sodic soils and wind. However, plant succession regression only implies changes in soil properties as a consequence of the intensified physical and biological degradation processes, without causing a significant loss of quality in soils that already have poor soil quality. In Changting county of China, after 25 years of monitoring vegetation recovery, the degraded sites with the lowest levels of vegetation cover (a degradation threshold at about 20%) have shifted to a new state that cannot recover naturally to their original conditions even after further human disturbance was prevented (Gao et al., 2011). Hence, successful ecological restoration should require innovative management such as reforestation and artificially adding organic matter to mitigate the constraints imposed by abiotic conditions in the degraded system (McVicar et al., 2010). Indeed, degraded areas can restore vegetation through human intervention (reforestation) and natural regeneration (spontaneous succession) (Wang et al., 2007). With increased vegetation cover, reforestation can control soil erosion and accelerate vegetation succession by providing an understory environment favorable for native plant recruitment (Parrotta et al., 1997; Parrotta and Knowlesb, 2001; Duncan and Chapman, 2003; Fernandez-Abascal et al., 2003). Then soil erosion intensity decreased with the longer time of reforestation (Wang et al., 2007). However, due to incomplete, uncertain, sparse, empirical and non-formalized ecological knowledge, it is difficult to study and have quantitative analyses on vegetation succession processes and the effects on soil erosion (Salles and Bredeweg, 2006). Thus, studies have mostly focused on the changing characteristics of community structure, species composition and vegetation cover (El-Sheikh, 2005; Degn, 2001; Wen et al., 2005), but little is known about the quantitative interaction between vegetation succession and soil erosion. The effects of vegetation on erosion control and soil stability have been of great concern in recent years. Burylo et al. (2012) divided the effects into two main categories: active and passive protection. On the one hand, the components of plant can control hydrological and mechanical processes of soil erosion in active protection as follows: (1) Plant canopy reduces surface runoff and erosion rates by intercepting rainfall, and by increasing water infiltration and surface roughness (Styzcen and Morgan, 1995). (2) Plant roots lower pore water pressure, increase soil aggregate stability and provide additional soil cohesion through root reinforcement (Gyssels et al., 2005; Hubble et al., 2013; Graf and Frei, 2013). (3) Thicker litter layer protect soil surface, thus preventing soil detachment, and provided surface roughness that minimized soil particle movement down the slope (Hartanto et al., 2003). (4) Canopy completeness, leaf morphology and plant shape influence sediment retention by plants (Burylo et al., 2012). On the other hand, plant does not prevent erosion from occurring but reduce soil loss at a larger scale by sediments trapping in exclosures (Descheemaeker et al., 2006), upslope of shrubs and trees and micro topographic mounds, which are interpreted as filtering barriers (Bergkamp, 1998; Sanchez and Puigdefábregas, 1994; Bochet et al., 2000). Despite the well-known relationships between soil and vegetation have been reported, to date, because of the paucity of field studies, changes in soil erosion intensity during vegetation succession are still poorly understood and documented (Walker et al., 2006). The Chinese government has listed Jinsha River as a key area of ecological environmental construction and promoted vegetation restoration (Fu et al., 1997; Luo and Wang, 2006; Li and Zeng, 1999; Yang et al., 2003). However, we still lack a sophisticated understanding of the benefits from soil and water conservation

in different succession stages in qualitative analyses but only in overall trend analyses (Cui et al., 2005; Wang et al., 2004a,c). In this study, our objectives were (1) to quantitatively analyze the dynamics of soil erosion during different succession stages and (2) to identify community features that significantly affect 137 Cs concentration. We have carried out monitoring of soil erosion and vegetation recovery in five succession stages in Jiangjiagou gully, on the right bank of Xiaojiang river (a tributary of the downstream of Jinsha River), Southwest China. The methods of “space replacing time” and 137 Cs technique were used to analyze the control effect of different succession stages on soil erosion with regard to community structure and species composition of succession stages. Analyses were performed to compare the control ability of different succession stages for evaluating the effects of ecological restoration in that area.

2. Study areas Our research area is the Jiangjiagou gully located on the right bank of the Xiaojiang River as shown by Fig. 1 (Land use and plots distribution in Jiangjiagou gully in 2006). The Xiaojiang deep fault zone joins its zone branch downstream of the Jiangjiagou gully. Based on topographical mapping and digital elevation model (DEM) in the study area, the highest elevation is 3629 m, about 2227 m higher than the lowest elevation at the junction of Jiangjiagou gully and Xiaojiang River. The length of Jiangjiagou gully’s main channel is 13.9 km with an average gradient of 18%, and the average slope gradient of hillside is 43◦ . Jiangjiagou gully has vertical climate differences as follows: (1) The part with an elevation of 1042–1600 m belongs to dry-hot river valley, is the deposit area with annual precipitation of 600–700 mm year−1 , mean annual temperature of 20 ◦ C and mean annual potential evapotranspiration of 3700 mm year−1 . (2) The part with an elevation of 1600–2200 m belongs to subtropical and sub-humid warm temperate, is the main source of debris flow materials with annual precipitation of 700–850 mm year−1 , mean annual temperature of 13 ◦ C and average annual potential evapotranspiration of about 1700 mm year−1 . (3) The part with an elevation of >2200 m belongs to humid warm temperate, is the source of water and moving region of debris flow with annual precipitation of about 1200 mm year−1 , mean annual temperature of 7 ◦ C and average annual potential evapotranspiration of about 1350 mm year−1 . Moreover, active neotectonic led to cracked rock and severe soil and water loss, suffered by frequent debris flow, the area of over severe intensity soil erosion reached 17.32 km2 , accounting for 35.7% of the total area, leading to heavy economic loss and claiming the lives of many local people. Due to severe intensity soil erosion, 440 debris flows have occurred from 1965 to 2003, which caused Jiangjiagou gully to be considered as a typical debris flow basin. Due to perennial disasters and deforestation by humans for farmland and firewood, vegetation in most of Jiangjiagou gully was destroyed in the period of 1950–1970, resulting in serious ecological degradation, severe soil erosion, as well as serious destruction of native vegetation. After 1974, reforestation projects including aerial seeding were applied to restore vegetation. At present, the vegetation of Jiangjiagou gully consists of man-made forests and second growth forests, such as Pinus yunnanensis, Pinus armandii and mixed coniferous and broadleaf forest. Vegetation restoration and protection measures have been launched to improve vegetation cover, especially the protection of second meadow and evergreen shrub under natural conditions in the upper stream of Jiangjiagou gully. However, forest coverage occupied only 11.47% of the total area in 2006. Therefore, typical types of erosion and representative types of vegetation restoration make Jiangjiagou

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

15

Fig. 1. Land use and plots distribution in Jiangjiagou gully in 2006.

gully an ideal watershed for the study of the relationship between vegetation succession and soil erosion. 3. Methods 3.1. Vegetation investigations Five vegetation plots with similar natural conditions, as seen in Fig. 1 (Land use and plots distribution in Jiangjiagou gully in 2006), were selected consisting of native grassland, shrub, sapling forest, half-mature forest and near mature forest to study the evolution characteristics of vegetation and soil erosion in Jiangjiagou gully. All five experimental plots have red loam soil and are located in Duozhaogou gully, which is at the upper stream of the Jiangjiagou gully. Plot 1 developed as Cymbopogon distans subalpine meadow under natural conditions with slope gradient of 26◦ and south slopeexposure. Plot 2 developed from C. distans subalpine meadow to Coriaria sinica shrub in 2001. Plots 3 and 4 developed from native grassland and were reforested with aerial seeding P. yunnanensis in the area in 1974 and 1994. Plot 5 was planted without land leveling projects in 1958 with P. yunnanensis. At plot 3 (slope gradient of

35◦ and north slope-exposure), the diameter at breast height (DBH) and height of P. yunnanensis are 8–13 cm and 5–9 m, respectively. These numbers are 13–20 cm and 8–14 m at plot 4, and 15–28 cm and 12–17 m at plot 5. Canopy density increased from about 50% at plot 3 to about 65% at plot 4 and about 70% at plot 5. However, understory plant species and coverage varied as follows: at plot 3, C. sinica and Cyperus diffusus dominated in understory layer with the coverage of about 55%; at plot 4, C. sinica and Juncus effusus dominated with the coverage of about 60%; at plot 5, Vaccinium bracteatum and Arthraxon lancifolius dominated with the coverage of about 55%. At present, the 5 plots exhibit distinct vegetation communities as shown in Fig. 2a (C. distans subalpine meadow), Fig. 2b (Second shrub of C. distans and C. sinica), Fig. 2c (Saplings forest of P. yunnanensis), Fig. 2d (Half-mature forest of P. yunnanensis) and Fig. 2e (Near mature forest of P. yunnanensis). Vegetation communities and succession were studied by field vegetation investigations in August 2007 on all five experimental plots. Eight sampling quads of 1 m × 1 m were selected in the slope of plot 1, 8 of 5 m × 5 m in plot 2, and 16 of 5 m × 5 m in plot 3–5. On the other hand, near the slopes, 15 quads of 1 m × 1 m for native grassland, 15 of 5 m × 5 m for shrub, and 15 of 10 m × 10 m

16

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

Fig. 2. (a) C. distans subalpine meadow, (b) second shrub of C. distans and C. sinica, (c) saplings forest of P. yunnanensis, (d) half-mature forest of P. yunnanensis, (e) near mature forest of P. yunnanensis.

for sapling forest, half-mature forest and near mature forest were selected and located at the same quad centers in a vegetation unit (including several slopes) of 30 m × 50 m for comparison with data from slopes. According to plant functional traits provided by Cornelissen et al. (2003) and the features of community structure, species number, coverage of each plant species (including trees, shrubs and herbs), status of vegetation development, grass height,

the height and average crown diameter (calculated in the direction of north–south and west–east) of shrubs and trees were investigated and measured. In this study, we used point frame method to measure the degree of grass coverage, point intercept method to measure the degree of shrub coverage, and spherical densiometer to measure the degree of tree coverage. For the height and crown diameter, a TruPulse 200 laser range finder is used to measure the

Table 1 Experimental conditions of five plots in different succession stages. Stage

Slope gradient (◦ )

Slope exposure

Bulk density (g/cm3 )

Elevation (m)

Vegetation type

I II III IV V

26 24 35 35 30

South Northwest North North North

1.20 1.36 1.34 1.15 1.26

2350–2380 2270–2290 2280–2300 2310–2330 2390–2420

C. distans + Leontopodium sinense C. nepalensis + C. distans P. yunnanensis + C. nepalensis + Cyperus diffusus P. yunnanensis + C. nepalensis + J. effusus P. yunnanensis + V. bracteatum + A. lancifolius

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26 Table 2 Diversity indexes in five succession stages. Stage

Richness number S

Diversity indexes H

J

D

I II III IV V

14 26 33 31 39

1.925 2.611 2.873 2.816 3.093

0.729 0.801 0.822 0.820 0.844

0.851 0.918 0.923 0.948 0.957

height of tree, and a flexible rule to measure the height of grass and shrub and crown diameter of shrub and tree in the direction of north–south and west–east. Based on the methods of “space replacing time”, 5 plots were taken as 5 succession stages including native grassland (Stage I), shrub (Stage II), sapling forest (Stage III), half-mature forest (Stage IV) and near mature forest (Stage V), as seen in Table 1 (Experimental conditions of five plots in different succession stages). 3.2. Soil sampling and analysis After vegetation investigations, five representative slope units, namely summit, shoulder-slope, back-slope, foot-slope and toeslope in each plot were selected to provide an assessment of the spatial pattern of the soil redistribution rate (Fan et al., 2006). The slope position and gradients are listed in Table 2 along with the soil bulk density. On the other hand, each quad center of 75 vegetation units was selected as a sampled position. Soil samples were collected using a 6 cm diameter core tube, which was drilled into soil layer to a depth about 30 cm in order to measure the 137 Cs inventory of the entire soil profile. Undertaken in August 2007, three soil samples at each sampling point with same contour levels were mixed as a sample. When depth distribution of 137 Cs was required, depth incremental samples were collected using a scraper-plate with a surface area of 200 cm2 (Zhang et al., 2003) (Fig. 3a (The soil profile of depth incremental samples)). Core samples for local 137 Cs references were collected from non-irrigated flat cultivated terraces that were over 100-year old (Fig. 3b (The site of local 137 Cs references)). Soil samples were air-dried, disaggregated, passed through

17

a 2-mm screen and weighed. Samples weighed 280–400 g were used for determining the 137 Cs content by gamma spectrometry using a hyperpure coaxial germanium detector and multi-channel analyzer in the nuclear physics lab at Sichuan University. The 137 Cs radioactivity was detected at the 662 keV line. Counting time was over 25,000 s and the analytical precision of the measurements was approximately ±5% at the 95% level of confidence. According to our survey of local people, there are no significant human disturbances in all 5 plots since 1958. Plots 3 and 4 were protected and undisturbed by enclosures after aerial seeding. Plots 1 and 2 were in undisturbed and natural conditions as they are far away from the villages. Plot 5 was protected without harvesting after planting in 1958. In undisturbed soils, 137 Cs is generally found with a maximum concentration below the soil surface (1 cm), from where concentrations decrease in exponential type to below detection limits at 20–30 cm depth (Li et al., 2007; Jin et al., 2004; Zhang et al., 1990, 1994; Wallbrink et al., 1999, 2002). Our measured results proved that 137 Cs distributed in an exponential type. Hence, in this study, for the undisturbed land, the net erosion at sites of soil loss was calculated by using the equation of Zhang et al. (1990) as: A (x) = Aref (1 − e−x/h0 )

(1)

where x is the mass depth from soil (kg m−2 ); A (x) is 137 Cs inventory above depth x (Bq/m2 ); Aref is the effective 137 Cs reference inventory; h0 is the coefficient for describing the characteristic of soil profile. Walling and He (1997, 1999) assumed that the total 137 Cs fallout generated in 1963 and the depth distribution of 137 Cs in the soil profile is independent of time, and developed the following equation to estimate the erosion rate Y for a point: Y=



10 X h0 ln 1 − t − 1963 100

 (2)

where Y is annual soil loss (t ha−1 year−1 ); t is the year of sample collection (year); X is percentage reduction in the 137 Cs inventory relative to the local 137 Cs reference value (defined as [(Aref − Au )/Aref ] × 100); Au is the total 137 Cs inventory at the sampling point (Bq m−2 ).

Fig. 3. (a) The soil profile of depth incremental samples. (b) The site of local 137 Cs references.

18

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

3.3. Data analysis

evenness degree, and Simpson domination degree (Wang et al., 2007), respectively:

For this study, a one-way ANOVA was used to test for differences in 137 Cs inventory between five succession stages and to examine differences in vegetation ability for 137 Cs concentration with Tukey’s HSD test. Before analysis, we used Shapiro–Wilk test to test all data for normality. To determine how community features and 137 Cs inventory were related across vegetation succession, principal components analysis (PCA) was used in transformed data. Analyses were carried out with STATISTICA 10.

S 

H=−

J=

H ln S

Because the observation of vegetation succession takes a long time, we chose the method of “space replacing time” to simulate the process of vegetation succession in 5 stages. Plant community composition of the 5 plots were measured in 2007 and the results are listed in Table 2, in which, S is the number of species, H, J and D are Shannon–Wiener diversity index, Shannon–Wiener

ni

S

n i=1 i

(3)

(4)

S    ni (ni − 1) i=1

4.1. Community composition and change of diversity in the process of vegetation succession

pi =

i=1

D= 4. Results

pi ln pi ,

S(S − 1)

(5)

where ni is the number of the ith species. The vegetation composition of different stages is classified as trees, herbages, shrubs and liana as shown by Fig. 4 (Present vegetation composition of five succession stages). The process of plant succession is also illustrated in Fig. 4 (Present vegetation composition of five succession stages). In native grassland (Stage I), there is no tree planting and Cymbopogon distans dominated in plant composition. The vegetation in shrub (Stage II) consists of shrubs such as C. sinica and Salix myrtillacea, and shows sporadic emergence of Potentlla anserine (a type of shade tolerant herb) after 6 years natural succession. In sapling forest (Stage III), due

Fig. 4. Present vegetation composition of five succession stages.

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

to the shadow environment for understory species provided by P. yunnanensis, heliophyte herbs, including Eriophorum vaginatum and Leontopodium alpinum disappeared, and those shade tolerant herbs, such as Fragaria orientalis and Geranium wilfordii, emerged with higher diversity 13 years after planting. Plot 4 (Stage IV) has developed into an integrated assemblage of trees (including Alnus cremastogyne and Populus davidiana), shrubs (including Lespedeza Formosa, C. sinica, Rubus pungens and Smilax china) and herbs (including Eulaliopsis binata and F. orientalis) with local species 33 years after planting. In stage V, species of trees showed little change compared to stage IV, but Cyclobalanopsis glaucoides emerged in shrub layer and Pteris vittata and Hicriopteris glauca emerged in grass layer. As seen in Table 2 (Diversity indexes in five succession stages), vegetation composition and species diversity are different in different succession stages. Plot 1 and 2 has relatively lower richness number, lower diversity index, lower evenness degree, and lower domination degree than plots 3–5, indicating that vegetations in early succession stages have lower bio-diversity and simple vegetation composition. Plot 5 (Stage V) has the largest richness number, the highest diversity index, the highest evenness degree, and the highest domination degree and has the most complicated vegetation composition among all stages. 4.2.

137 Cs

reference inventory

The values of 137 Cs inventories ranged from 614.65 to 1261.89 Bq m−2 with a mean value of 1082.9 Bq m−2 , which was similar to that measured by Zhang et al. (1992) with a value of 1105.4 Bq m−2 . Therefore, 1082.9 Bq m−2 , the average of measurements, was used as the 137 Cs reference inventory in this study. Estimates of soil erosion/deposition for each sample site were made using Eqs. (1) and (2) based on a comparison of 137 Cs reference inventory and 137 Cs in the soil at the sample site.

19

4.3. The characteristics of soil erosion in the slope units of different vegetation succession stages 4.3.1. 137 Cs loss of soil in the slopes during different vegetation succession stages By measuring the concentration of 137 Cs of soil samples on different slope positions, there are great variety in different slope lengths and gradients during different vegetation succession stages ranged from 282.7 to 1612.2 Bq m−2 . This range of 137 Cs concentrations indicated the complication and intensity of soil erosion/deposition during different vegetation succession stages in Jiangjiagou gully. Negative values of 137 Cs loss indicate soil deposition and positive values mean soil erosion. As seen in Table 3 (137 Cs point inventory and loss, annual erosion thickness and average erosion rate estimated in sampled sites of slopes in different succession stages), different slope units exist for different soil erosion intensities during different vegetation succession stages. In native grassland, shrub, and half-mature forest, soil erosion occurs in all sites of their slopes, but soil deposition takes place in the middle or at the bottom of the slopes in sapling forest and near mature forest. Variations of 137 Cs loss are observed to be significant in 5 succession stages. The complicated behavior of 137 Cs redistribution can be explained as follows: (1) Samples collected in back-slope of grassland and shrub and foot-slope in sapling forest were located in the transitional zone of steep-gentle slope that induces soil deposition and low erosion. (2) The relatively low coverage in the toe-slope of half-mature forest led to higher runoff erosion. (3) The relatively higher coverage and rainfall interception capacity in the shoulderand back-slope improved the effect of soil erosion control, inducing soil deposition. As a whole, the percentage of 137 Cs loss reveals an overall downturn following vegetation succession, which in turn indicates that community maturity is an important factor affecting the rate of soil erosion. In other words, stronger soil erosion may happen in younger vegetation communities.

Table 3 Cs point inventory and loss, annual erosion thickness and average erosion rate estimated in sampled sites of slopes in different succession stages.

137

Stage

Sample No.

Distance (m)

Slope gradient (◦ )

137 Cs inventory (Bq m−2 )

Loss of Cs (%)

137

Average annual erosion thickness (mm/a)

Average erosion rate (t/km2 a)

Native grassland

8-17-001 8-17-002 8-17-003 8-17-004 8-17-005

1 14 27 40 54

26 24 27 23 23

283.3 351.8 851.3 459.6 811.1

73.84 67.51 21.39 57.56 25.10

2.69 2.26 0.48 1.72 0.58

3228.11 2706.12 579.26 2062.88 695.73

Shrub

8-13-001 8-13-002 8-13-003 8-13-004 8-13-005

1 7 13 18 23

24 23 26 24 22

535.7 687.9 829.6 525.3 558.2

50.53 36.48 23.39 51.49 48.45

1.41 0.91 0.53 1.45 1.33

1920.10 1237.90 726.91 1973.74 1807.64

Sapling forest

8-12-001 8-12-002 8-12-003 8-12-004 8-12-005

1 6 11 15 19

34 36 37 39 34

607.0 590.0 590.9 1147.1 580.8

43.95 45.52 45.44 −5.93 46.37

1.16 1.22 1.22 −0.12 1.25

1556.11 1632.34 1628.53 −154.74 1674.58

Half-mature forest

8-15-001 8-15-002 8-15-003 8-15-004 8-15-005

1 6 11 15 19

35 36 35 34 36

927.0 772.7 871.0 404.5 974.0

14.40 28.65 19.57 62.64 10.06

0.31 0.68 0.44 1.98 0.21

358.62 778.63 502.44 2271.40 224.48

Near mature forest

8-11-001 8-11-002 8-11-003 8-11-004 8-11-005

1 9 17 25 35

30 29 31 28 32

817.6 1117.2 1612.2 620.5 636.0

24.49 −3.17 −48.88 42.70 29.52

0.56 0.06 −0.29 1.37 0.23

710.15 −78.88 −1005.88 1407.41 884.12

20

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

Loss of

137

Cs (%)

2

50

Average erosion rate[t/(km .a)]

60

40 30 20 10 0 I

II

III

IV

V

Stage

2000 1800 1600 1400 1200 1000 800 600 400 200 0 I

II

III

IV

V

Stage

Fig. 5. Loss of 137 Cs in different succession stages.

Fig. 6. Average erosion rate in different succession stages.

To make an assessment of the average 137 Cs loss in slopes, 137 Cs concentrations at five positions in each slope were calculated by weighted average of the length of slope units given by Wang et al. (2004b) as:

n Cs =

i=1

loss, annual erosion thickness and average erosion rate estimated in sampled sites of slopes in different succession stages).

Cs1 × L1 + (Cs1 + Cs2 )/2 × (L2 − L1 ) + · · · + (Csn−1 + Csn−2 )/2 × (Ln−1 − Ln−2 ) + (Csn + Csn−1 ) × (Ln − Ln−1 ) L

where Cs is the average loss of 137 Cs; Ln is the distance of sampled points to the summit of slope; Csn is the loss of 137 Cs in sampled point; L is the length of total slope. Therefore, average erosion rate (ER) could also be calculated by Eq. (6), replacing Cs with ER. The change of average 137 Cs loss in different vegetation succession stages is shown in Fig. 5 (Loss of 137 Cs in different succession stages). As seen in Fig. 5 (Loss of 137 Cs in different succession stages), the values of average 137 Cs loss in native grassland and shrub are higher than in sapling forest, half-mature forest, and near mature forest. Obviously, due to the more complicated structure and layers of vegetation, average 137 Cs loss decreased with the succession of vegetation. When native grassland with one layer developed into shrub with two layers, the average 137 Cs loss decreased by 8.94% due to the superior ability of shrub to intercept rainfall and energy reduction than native grassland. Following the continuation of vegetation succession, sapling forest has more complicated vegetation structure than shrub with an integrated assemblage of trees (P. yunnanensis with the height of 6–11 m), shrubs, and herbs, which enables sapling forest to delay the time of rainfall attacking soil directly with average 137 Cs loss decreased by 5.89%. Moreover, when sapling forest developed into half-mature forest, average 137 Cs loss decreased by 5.40%, due to the more complicated vegetation structure to delay and intercept rainfall and the litter layer to reduce the flow and speed of surface runoff. Compared with other stages, near mature forest has the most complicated vegetation structure with natural germination of P. yunnanensis and shade tolerant pteridophyte, and average 137 Cs loss decreased by 22.27% from half-mature forest, due to the function of the litter layer with the thickness of 1–2 cm and multiple vegetation structure to intercept rainfall and reduce surface runoff. 4.3.2. Influence of vegetation succession on soil erosion in the slopes Although 137 Cs technique can be used to study soil erosion and sediment delivery (Ritchie et al., 1974), the intensity of soil erosion cannot be monitored over long time periods. Therefore, in this study, the average soil erosion intensity was evaluated during different succession stages. Using Eqs. (1) and (2), soil erosion rates of different stages were calculated and presented in Table 2 (137 Cs point inventory,

(6)

Table 2 (137 Cs point inventory, loss, annual erosion thickness and average erosion rate estimated in sampled sites of slopes in different succession stages) shows that soil erosion rates in each sample site ranged from −1005.88 t/km2 a to 3228.11 t/km2 a. However, the average soil erosion rate of each slope (calculated by Eq. (6)) is similar with average 137 Cs loss. According to the measured data (Fig. 6 (Average erosion rate in different succession stages)), native grassland developed with the most serious erosion (erosion modulus about 1845.18 t/km2 a). About 6 years later, native grassland developed into shrub with comparatively lower erosion (erosion modulus about 1456.24 t/km2 a). About 7 years later, shrub developed into sapling forest with decreasing erosion (erosion modulus about 1245.61 t/km2 a). About 20 years later, sapling forest developed into half-mature forest with the second lowest erosion (erosion modulus about 891.78 t/km2 a). About 16 years later, half-mature forest developed into near mature forest with the lowest erosion (erosion modulus about 341.71 t/km2 a). Therefore, the average 137 Cs loss and erosion rate can be given in this order: native grassland > shrub > sapling forest > half-mature forest > near mature forest. Obviously, average soil erosion rate decreased comparatively with the succession of vegetation.

4.4. Community features and ability for 137 Cs concentration during different succession stages 4.4.1. Different succession stages efficiency in 137 Cs concentration The values of 137 Cs inventories were determined in the sampled soils of each quad center, with the contents ranging from 256.8 to 1722.5 Bq/m2 . The 137 Cs loss of soil ranged from −59.06% to 76.29% of 137 Cs reference inventory. When tested in Tukey’s HSD test, results show significant 137 Cs inventory differences between succession stages (Fig. 7 (Differences in 137 Cs inventory among different succession stages)). The more mature vegetation near mature forest and half-mature forest had the highest contents of 137 Cs inventory ahead of the younger vegetation native grassland and shrub (ANOVA: F = 6.309, p < 0.001). Near mature forest and half-mature forest had respectively 56.91% and 22.02% more 137 Cs content than shrub, and 74.98% and 36.08% more 137 Cs content than grassland.

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

21

database respectively. Axis one differentiated stages according to species number, ACDT and average tree height (Fig. 8a (Principal component axis 2 plotted vs. axis 1)). Half-mature forest and near mature forest, which had respectively higher species number, tree crown diameter and tree height, occupied the upper end of axis one, whereas native grassland and shrub had opposite features (Fig. 8b (Projection of different succession stages on the factor-plane (1–2))). Axis two was mostly defined respectively by shrub coverage and average crown diameter of shrub (ACDS), which indicated shrub, as the middle or upper layer of community, was crucial to vegetation integrity. 137 Cs inventories contributed mainly to axis one. Pearson’s correlations (Table 5 (Correlation matrix between community features and 137 Cs inventory)) showed that 137 Cs inventories were significantly positively correlated with ACDT, species number, average tree coverage and average tree height, and significantly negatively with grass coverage. ACDS and average shrub height were also positively correlated with 137 Cs inventories but correlation coefficients were lower. Pairwise correlation coefficient showed that several features were significantly related, especially average tree coverage and ACDT were most positively correlated with the correlation coefficient of 0.992.

Fig. 7. Differences in 137 Cs inventory among different succession stages. Bars mean ± SE. Different letters mean significant differences among stages (Turkey’s HSD test, ˛ = 0.05).

4.4.2. The community features of different succession stages All community features except average shrub height showed large variation among different succession stages (Table 4 (Mean values ± SE of traits for five succession stages, and results of oneway ANOVA)). Native grassland had the largest grass coverage and near mature forest, the smallest one, representing the decrease of grass dominance as vegetation success. Similarly, the differences of average grass height indicated that native grassland had the highest grass dominance with lowest height due to species competition, while on the other hand, sapling forest, half-mature forest and near mature forest, with high average grass height, had lower grass dominance. Shrub coverage differences indicated that shrub had the highest shrub dominance than sapling forest, half-mature forest and near mature forest, whereas sapling forest had the lowest average crown diameter of shrub due to the competition of comparatively low tree to shrub. Finally, tree features including average tree height, tree coverage and average crown diameter of tree, also differed significantly among different succession stages, near mature forest having the highest average tree height, tree coverage, average crown diameter of tree (ACDT), as well as species number, which indicated that more mature community had significantly higher tree features.

4.5. Relationship between vegetation succession and the regulation and control of soil erosion Fig. 9a (The vertical profile of water and soil regulation in vegetation) and Fig. 9b (Cross sectional view of different succession stages in soil erosion control and regulation) illustrate the relationships between vegetation succession and the regulation and control of soil erosion. The vegetation can improve the effect of soil erosion control through soil conservation and water regulation with succession. In soil conservation, vegetation regulates the control function of raindrop, surface runoff, soil structure disintegration, rill erosion, as well as sediment transport capacity of surface runoff with succession. In the early stage of succession, due to few crown layers, rainfall induces heavy rill erosion in surface soil with little interception. Furthermore, with little function of blockage and alleviation for surface runoff supplied by litter layer and plant body, the speed of surface runoff and the amount of delivered sediment are comparatively high, which cause the appearance of overflow and flow concentration. In addition, shallow root system in early succession stage has a little effect on soil consolidation, which may not only result in soil structure disintegration under the intensive runoff scour, but also give rise to rill erosion. When vegetation succession continues, the aboveground part, ground part, and underground part of vegetation become more complicated and have better effects on soil erosion control as follows: (1) In

4.4.3. Relationship between 137 Cs concentration and community features Based on transformed data of 9 community features and 137 Cs inventories, we used principal components analysis (PCA) to analyze the relationship between community features and 137 Cs inventories. PCA results indicated that principal component axes one and two explained 63.1% and 17.5% of the variation in the Table 4 Mean values ± SE of traits for five succession stages, and results of one-way ANOVA. Succession stages ACDT ACDS Species number Tree coverage Shrub coverage Grass coverage Average tree height Average shrub height Average grass height

I – – 7.7 ± 1.4a – – 0.702 ± 0.049a – – 0.284 ± 0.068a

II – 0.680 16.6 – 0.584 0.566 – 1.81 0.339

III ± 0.084b ± 1.7b ± 0.038b ± 0.042b ± 0.20a ± 0.069ab

2.69 0.527 20.7 0.503 0.361 0.551 6.65 1.75 0.351

IV ± ± ± ± ± ± ± ± ±

a

0.09 0.048a 1.6c 0.029a 0.026a 0.069b 0.29a 0.13a 0.059b

3.24 0.657 20.2 0.632 0.376 0.403 10.49 1.80 0.349

V ± ± ± ± ± ± ± ± ±

b

0.25 0.034b 1.7c 0.041b 0.034a 0.031c 0.68b 0.21a 0.056b

3.79 0.648 26.3 0.674 0.352 0.363 14.32 1.91 0.357

ANOVA ± ± ± ± ± ± ± ± ±

c

0.16 0.049b 1.8d 0.030c 0.025a 0.034c 0.24c 0.20a 0.067b

143.59*** 21.769*** 266.792*** 104.16*** 186.25*** 126.169*** 1094.963*** 1.816ns 3.168*

Note: Different letters indicate significant differences (Turkey’s HSD test) among five succession stages. ACDT: average crown diameter of tree; ACDS: average crown diameter of shrub. Levels of significance are: ns, non significant. * p < 0.05. *** p < 0.001.

22

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

Fig. 8. (a) Principal component axis 2 plotted vs. axis 1. (b) Projection of different succession stages on the factor-plane (1–2). ACDS: average crown diameter of shrub; ACDT: average crown diameter of tree.

aboveground part, due to increased crown layers, biodiversity, and species densities, multilayer with higher horizontal coverage and area of canopy is formed to improve rainfall interception. (2) In ground part, following the depth increase of litter layer, the effects

of obstruction on rain splash increase to improve soil aggregate structure and soil anti-scouribility. Moreover, together with litter layer, the stems of plant near ground filter and intercept sediment from surface runoff and reduce the speed, scouring capability and

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

23

Table 5 Correlation matrix between community features and 137 Cs inventory. ACDT

ACDT ACDS Species number Tree coverage Shrub coverage Grass coverage Average tree height Average shrub height Average grass height 137 Cs inventory

ACDS

Species number

1 0.526*** 0.833*** 0.800*** 0.992*** 0.531*** 0.821*** 0.174 0.904*** 0.569*** −0.813*** −0.710*** −0.819*** 0.974*** 0.520*** 0.835*** 0.597*** 0.947*** 0.839*** 0.285* 0.355** 0.350** 0.453*** 0.321** 0.486***

Tree coverage

Shrub coverage

Grass coverage

Average tree height

0.178 −0.804*** 0.961*** 0.600*** 0.299** 0.417***

−0.442*** 0.159 0.855*** 0.287* 0.161

−0.856*** −0.715*** −0.337** −0.431***

0.568*** 0.274* 0.487***

Average shrub height

Average grass height

137

0.440*** 0.326**

0.052

1

Cs inventory

Note: ACDT: average crown diameter of tree; ACDS: average crown diameter of shrub. Levels of significance are: * p < 0.05. ** p < 0.01. *** p < 0.001.

Fig. 9. (a) The vertical profile of water and soil regulation in vegetation. (b) Cross sectional view of different succession stages in soil erosion control and regulation.

24

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

sediment transport capacity of surface runoff. (3) In underground part, the anchorage action of root systems of plants, which are composed of the layer of herbaceous roots, the layer of shrub roots and the layer of tree roots, improves soil integrity and erosion resistance to prevent soil structure disintegration and inhibit the possibility of rill erosion. Furthermore, the characteristics of runoff, overland flow concentration, infiltration of slopes in vegetation succession and the allocation of surface water, soil moisture and groundwater are changed for water regulation. In early stage of succession, rainfall would overload the interception of crown and stem due to low crown layer of herb and incomplete cover on slope during rainstorm, so slope runoff and subsurface flow will occur due to the time shortage of runoff production induced by saturated soil infiltration. As slope runoff move with little blockage, alleviation by litter layer and plant body and saturated soil infiltration, surface runoff will occur due to flow concentration of slope runoff. Moreover, when surface runoff and subsurface flow continue to move, they infiltrate into underground water and transform into groundwater increment. Following vegetation succession, rainfall which directly reaches slope decreased due to increasing interception of crown and stem, and runoff production will be delayed due to water absorption of thickening litter layer. If rainfall overloads the interception of crown, stem and litter layer, it is possible that this will cause water to infiltrate as water storage in soil. In addition, when rain intensity exceeds the infiltration capacity of the soil, subsurface flow occurs and then slope runoff, surface runoff and groundwater increment will occur with continuous rainfall. Therefore, vegetation succession can improve the function of water regulation, prolong the occurrence of runoff and overland flow concentration, raise infiltration intensity, as well as delay the formation of surface water, soil moisture and groundwater.

5. Discussion The effects of vegetation on surface runoff reduction and erosion control were well-known (Styzcen and Morgan, 1995). For example, vegetation types and coverage, litter layer, plant individual density, plant species diversity can regulate and control rainfall, runoff, sediment and soil erosion (Lal and Elliot, 1994; Morgan, 1995; Wang et al., 2006; Asdak et al., 1998; Aboal et al., 1999; Bochet et al., 2000; Zhou et al., 2002; Jackson, 2000; Levia and Frost, 2003). As time goes on and external factors change, the effects of vegetation on erosion control will fluctuate due to the change of species composition and community structure. Ma and Jiao (2005) and Wang and Liu (1999) have proved that functions of soil and water conservation can increase in accordance with progressive succession of vegetation under natural conditions. However, it took long time to carry out field observations by runoff plots and artificial rainfall experiment that little is known about the varied characteristics of soil erosion in different succession stages due to a lack of long-term research data accumulated for quantitative description of the relationship between vegetation succession and soil erosion. In this study, due to few percent of the total 137 Cs concentration absorbed by plants (Nishita et al., 1958), we only investigated 137 Cs contents in soil of the slopes and vegetation units of different succession stages. Although 137 Cs contents in different slope units showed large variation among succession stages, average 137 Cs concentrations in each slope calculated by weighted average of the length of slope units followed the rule as near mature forest > half-mature forest > sapling forest > shrub > native grassland. In addition, to test the results of 137 Cs contents variation in the slopes of different succession stages, we found 137 Cs contents in

vegetation units of near mature forest and half-mature forest were significantly higher than that of native grassland and shrub, following the same rule as in the slopes. This result is consistent with previous investigations which highlighted that old succession stage maintained greater stability of soil conservation than young succession stage (Wang et al., 2006). Differences in 137 Cs inventories between different succession stages suggest that tree layer and species number are important determinants of 137 Cs concentration. Multivariate analysis showed that 137 Cs inventory was significantly related to several community features. The strongest relationships were found with average tree height, tree coverage, ACDT and species number. The more succession stage is mature, the more soil erosion is controlled. This conclusion is consistent with previous investigations which highlighted that mature succession stage improved soil conservation ability (Wang et al., 2006). Shrub layer also played an important role in soil erosion control, reducing throughfall erosivity and increasing re-interception of drops by its canopy. This conclusion is consistent with the results of Nanko et al. (2008) and Geißler et al. (2010). The results provided by this study are new approaches to understand the succession characteristics of soil erosion with vegetation succession according to soil 137 Cs inventory and community features. Community features, which appear as relevant parameters to predict vegetation performance for 137 Cs concentration in undisturbed condition, could be used to evaluate the soil erosion intensity of different vegetation. In addition, the average soil erosion intensity in different succession stages is estimated in this study, but annual variation of soil erosion and irreversible threshold of vegetation degradation induced by soil erosion are not clear. Therefore, long-term research is required to identify the relationship between soil erosion and vegetation degradation. 6. Conclusion Based on field investigations and collected soil samples on five undisturbed succession stages, including native grassland, shrub, sapling forest, half-mature forest and near mature forest in Duozhaogou gully of Jiangjiagou watershed, the characteristics of community structure, species composition, biodiversity, and 137 Cs inventories in slopes and vegetation units are studied. Our research has confirmed the critical role of vegetation succession in soil erosion control due to more complicated structure and increasing plant species diversity. The vegetation can promote the control function and intensity of soil erosion by the improvement of soil conservation and water regulation. The results of 137 Cs inventories showed that 137 Cs loss and soil erosion modulus in slopes decreased with vegetation succession due to the reinforcement of soil erosion control. Similarly, 137 Cs concentration in vegetation units increased with vegetation succession. Moreover, PCA analysis showed that species number, ACDT, average tree height, ACDS and average shrub height appear as relevant features to evaluate and predict the soil erosion intensity of different vegetation. Finally, this study proposed a hypothesis to explain the relationship between vegetation succession and the regulation and control of soil erosion. Acknowledgements This work is supported by the National Natural Science Foundation of China (Grant No. 41201564), the Key Research Program of the Chinese Academy of Sciences (Grant No. KZZD-EW-0501), and the National Key Technologies R&D Program (Grant No. 2006BAC10B04). The authors are very grateful for the suggestions

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

of the Professor of Zhang Xinbao and the helps from the staffs of Dongchuan Debris Flow Observation and Research Station.

References Aboal, J.R., Morales, D., Hernándes, M., Jiménez, M.S., 1999. The measurement and modelling of the variation of stem-flow in a land forest Tenerife, Canary Islands. J. Hydrol. 221, 161–175. Arbelo, C.D., Rodríguez Rodríguez, R.A., Guerra García, J.A., Mora Hernández, 2002. Soil quality and plant succession in forest andosols. In: Lianxiang, W., Deyi, W., Xiaoning, T., Jing, N. (Eds.), Proceedings of 12th ISCO Conference. Sustainable Utilization of Global Soil and Water Resources, vol. III. Tsinghua University Press, Beijing, China, pp. 452–458. Asdak, C., Jarvis, P.G., van Gardingen, P., Fraser, A., 1998. Rainfall interception loss in unlogged and logged forest areas of Central Kalimantran, Indonesia. J. Hydrol. 206, 237–244. Bergkamp, G., 1998. A hierarchical view of the interactions of runoff and infiltration with vegetation and icrotopography in semiarid shrublands. Catena 33, 201–220. Bilotta, G.S., Brazier, R.E., Haygarth, P.M., 2007. The impacts of grazing animals on the quality of soils, vegetation, and surface waters in intensively managed grasslands. Advances in Agronomy, vol. 94. Elsevier Academic Press Inc., San Diego, pp. 237–280. Bochet, E., Poesen, J., Rubio, J.L., 2000. Mound development as an interaction of individual plants with soil, water erosion and sedimentation processes on slopes. Earth Surf. Proc. Land. 25, 847–867. Burylo, M.F., Rey, F.E., Bochet, T., Dutoit, T., 2012. Plant functional traits and species ability for sediment retention during concentrated flow erosion. Plant Soil 353, 135–144. Cornelissen, J.H.C., Lavorel, S., Garnier, E., Diaz, S., Buchmann, N., Gurvich, D.E., Reich, P.B., ter Steege, H., Morgan, H.D., van derHeijden, M.G.A., Pausas, J.G., Poorter, H., 2003. A handbook of protocols for standardised and easy measurement of plant functional traits worldwide. Aust. J. Bot. 51, 335–380. Costanza, R., de Groots, R., Farber, S., Grasso, M., Hannon, B., Limburg, K., Naeem, S., O’Neil, R.V., Paruelo, J., Raskin, R.G., Sutton, P., van den Belt, M., 1997. The value of the world’s ecosystem services and natural capital. Nature 387, 253–260. Cui, P., Lin, Y.M., Chen, C., 2012. Destruction of vegetation due to geo-hazards and its environmental impacts in the Wenchuan earthquake areas. Ecol. Eng. 44, 61–69. Cui, P., Wang, D.J., Wei, F.Q., 2005. Model and effect of ecological restoration of dryhot valley: a case study of the CAS Dongchuan Debris Flow Observation Station. Sci. Soil Water Conserv. 3 (3), 60–64 (in Chinese with English abstract). Degn, H.J., 2001. Succession from farmland to heathland: a case for conservation of nature and historic farming methods. Biol. Conserv. 97, 319–330. Descheemaeker, K., Nyssen, J., Rossi, J., Poesen, J., Haile, M., Raes, D., Muys, B., Moeyersons, J., Deckers, S., 2006. Sediment deposition and pedogenesis in exclosures in the Tigray highlands, Ethiopia. Geoderma 132, 291–314. Dou, X.L., Deng, Q., Li, M., Wang, W.B., Zhang, Q.F., Cheng, X.L., 2013. Reforestation of Pinus massoniana alters soil organic carbon and nitrogen dynamics in eroded soil in south China. Ecol. Eng. 52, 154–160. Duncan, R.S., Chapman, C.A., 2003. Consequences of plantation harvest during tropical forest restoration in Uganda. For. Ecol. Manage. 173, 235–250. El-Sheikh, M.A., 2005. Plant succession on abandoned fields after 25 years of shifting cultivation in Assuit, Egypt. J. Arid Environ. 61, 461–481. Fan, H.J., Yang, X.M., Zhang, X.P., Liang, A.Z., 2006. Using 137 Cs tracer technique to evaluate erosion and deposition of black soil in Northeast China. Pedosphere 16, 201–209. Fernandez-Abascal, I., Tarrega, R., Lius-Calabuig, E., Marcos, E., 2003. Effects of sowing native herbaceous species on the post-fire recovery in a healthland. Acta Oecol. 24, 131–138. Fu, M.F., Gao, J., Zhang, S.Y., 1997. A preliminary study on microclimate effects of different stands structure of Yangtze River of protection forest in Yuanmou County. J. Southwest Forestry College 17 (2), 44–48 (in Chinese with English abstract). Gao, Y., Zhong, B.L., Yue, H., Wu, B., Cao, S.X., 2011. A degradation threshold for irreversible loss of soil productivity: a long-term case study in China. J. Appl. Ecol. 48, 1145–1154. Geißler, C., Kühn, P., Shi, X.Z., Scholten, T., 2010. Estimation of throughfall erosivity in a highly diverse forest ecosystem using sand-filled splash cups. J. Earth Sci. 21 (6), 897–900. Graf, F., Frei, M., 2013. Soil aggregate stability related to soil density, root length, and mycorrhiza using site-specific Alnus incana and Melanogaster variegatus s.l. Ecol. Eng. 57, 314–323. Gyssels, G., Poesen, J., Bochet, E., Li, Y., 2005. Impact of plant roots on the resistance of soils to erosion by water: a review. Progr. Phys. Geogr. 29, 189–217. Hartanto, H., Prabhu, R., Widayat, A.S.E., Asdak, C., 2003. Factors affecting runoff and soil erosion: plot-level soil loss monitoring for assessing sustainability of forest management. For. Ecol. Manage. 180 (1–3), 361–374. Hubble, T.C.T., Airey, D.W., Sealey, H.K., De Carli, E.V., Clarke, S.L., 2013. A little cohesion goes a long way: estimating appropriate values of additional root cohesion for evaluating slope stability in the Eastern Australian highlands. Ecol. Eng., http://dx.doi.org/10.1016/j.ecoleng.2013.07.069. Jackson, I.J., 2000. Measure and modeled rainfall interception loss from an agroforestry system in Kenya. Agric. For. Meteorol. 100, 323–326.

25

Jin, P.H., Pu, L.J., Wang, J.L., Wang, Y.F., Pan, S.M., 2004. Preliminary study on using 137 Cs tracer method to estimate soil erosion of typical area: a case study on Xitiaoxi drainage area at up stream of Taihu Lake basin. J. Nat. Resour. 19 (1), 47–54 (in Chinese with English abstract). Lal, R., Elliot, W., 1994. Erodibility and erosivity. In: Lal, R. (Ed.), Soil Erosion: Research Methods. Soil and Water Conservation Society. St. Lucie Press, Florida, USA, pp. 181–208. Levia, D.F., Frost, E.E., 2003. A review and evaluation of stemflow literature in the hydrologic and biogeochemical cycles of forested and agricultural ecosystem. J. Hydrol. 274, 1–29. Li, K., Zeng, J.M., 1999. A study on transpiration of some tree species planted in hot and arid valley of Jinsha River. For. Res. 12 (3), 244–250 (in Chinese with English abstract). Li, Y.S., Wang, G.X., Wang, J.D., Wang, Y.B., Wu, Q.B., 2007. 137 Cs trace technique to study soil erosion at Alpine meadow of Tibetan Plateau. J. Mountain Sci. 25 (1), 114–117 (in Chinese with English abstract). Luo, H., Wang, K.Q., 2006. Soil seed bank and aboveground vegetation in Jinshajiang hot-dry River valley hillslope vegetation site. Acta Ecol. Sin. 26 (8), 2432–2442 (in Chinese with English abstract). Ma, X.H., Jiao, J.Y., 2005. Characteristics of vegetation with natural restoration in removal lands in loess hilly-gully region and the relationship between the characteristics and soil environment. Sci. Soil Water Conserv. 3 (2), 15–22 (in Chinese with English abstract). McVicar, T.R., Van Niel, T.G., Li, L.T., Wen, Z.M., Yang, Q.K., Li, R., Jiao, F., 2010. Parsimoniously modeling perennial vegetation suitability and indentifying priority areas to support China’s re-vegetation program in the Loess Plateau: matching model complexity to data availability. For. Ecol. Manage. 259, 1277–1290. Morgan, R.P.C., 1995. Soil Erosion and Conservation. Longman Publishing Group, London, UK, pp. 58–90. Nanko, K., Mizugaki, S., Onda, Y., 2008. Estimation of soil splash detachment rates on the forest floor of an unmanaged Japanese cypress plantation based on field measurements of throughfall drop sizes and velocities. Catena 72, 348–361. Nishita, H., Steen, A.J., Larson, K.H., 1958. Release of Sr-90 and Cs-137 from vina loan upon prolonged cropping. Soil Sci. 86, 195–201. Parrotta, J.A., Knowlesb, O.H., 2001. Restoring tropical forests on lands mined for bauxite: examples form the Brazilian Amazon. Ecol. Eng. 17, 219–239. Parrotta, J.A., Trunbll, J.W., Jones, N., 1997. Introduction catalyzing native forest regeneration on degraded tropical lands. For. Ecol. Manage. 99, 1–7. Pimentel, D., Kounang, N., 1998. Ecology of soil erosion in ecosystems. Ecosystems 1, 416–426. Rhoton, F.E., Shipitalo, M.J., Lindbo, D.J., 2002. Runoff and soil loss from Midwestern and southeastern US silt loam soils as affected by tillage practice and soil organic matter content. Soil Till. Res. 66, 1–11. Ritchie, J.C., Spraberry, J.A., McHenry, J.R., 1974. Estimating soil erosion from the redistribution of fallout 137 Cs. Soil Sci. Soc. Am. J. 38, 137–139. Rodríguez Rodríguez, A., Mora Hernández, J.L., Arbelo Rodríguez, C.D., 2002a. Variation of soil quality in plant succession of the coastal scrub of Tenerife (Canary Islands, Spain). In: Rubio, J.L., Morgan, R.P.C., Asins, S., et al. (Eds.), Proceedings of the Third International Congress Man and Soil at the Third Millennium. Geo˜ Spain, pp. 1185–1198. forma Ediciones, Logrono, Rodríguez Rodríguez, A., Mora Hernández, J.L., Guerra García, J.A., Arbelo, C.D., Sánchez, J., 2002b. An ecosystemic approach to soil quality assessment. In: Faz, A., Ortiz, R., Mermut, A.R. (Eds.), Sustainable Use and Management of Soils in Arid and Semiarid Regions, vol. I. Quadernal Editorial, Murcia, Spain, pp. 194–208. Rodríguez Rodríguez, A., Mora, J.L., Arbelo, C., Bordon, J., 2005. Plant succession and soil degradation in desertified areas (Fuerteventura, Cannary Islands, Spain). Catena 59, 117–131. Salles, P., Bredeweg, B., 2006. Modelling population and community dynamics with qualitative reasoning. Ecol. Model. 195, 114–128. Sanchez, G., Puigdefábregas, J., 1994. Interactions of plant growth and sediment movement on slopes in a semi-arid environment. Geomorphology 9, 243–260. Stokes, A., Sotir, R., Chenand, W., Ghestem, M., 2010. Soil bio and ecoengineering in China: past experience and future priorities. Ecol. Eng. 36, 247–257. Styzcen, M.E., Morgan, R.P.C., 1995. Engineering properties of vegetation. In: Morgan, R.P.C., Rickson, R.J. (Eds.), Slope stabilization and erosion control: a bioengineering approach. E and FN SPON, London, pp. 5–58. Walker, L.R., Bellingham, P.J., Peltzer, D.A., 2006. Plant characteristics are poor predictors of microsite colonization during the first two years of primary succession. J. Veg. Sci. 17, 397–406. Wallbrink, P.J., Murray, A.S., Olley, J.M., 1999. Relating suspended sediment to its original soil depth using fallout radionuclides. Soil Sci. Soc. Am. J. 63, 369–378. Wallbrink, P.J., Roddy, B.P., Olley, J.M., 2002. A tracer budget quantifying soil redistribution on hillslopes after forest harvesting. Catena 47, 179–201. Walling, D.E., He, Q., 1997. Models for converting 137 Cs measurements to estimates of soil redistribution rates on cultivated and uncultivated soils (including software for model implementation). University of Exeter, Exeter, UK, pp. 29 (Report to IAEA). Walling, D.E., He, Q., 1999. Improved models for estimating soil erosion rates from cesium-137 measurements. J. Environ. Qual. 28, 611–622. Wang, D.J., Cui, P., Wei, F.Q., Wang, Y.K., 2004a. Vegetation rehabilitation techniques and ecological effects in dry-hot valley of Jinsha River—Case study in Xiaojiang Basin, Yunnan Province. J. Soil Water Conserv. 18 (5), 95–98 (in Chinese with English abstract).

26

Y.-m. Lin et al. / Ecological Engineering 62 (2014) 13–26

Wang, X.Y., Tian, J.L., Liu, P.L., Yang, M.Y., 2004b. Study on relationships between slope gradient and soil loss using 137 Cs tracer. Acta Agric. Nucl. Sin. 18 (5), 390–393. Wang, Z.Y., Huang, G.H., Wang, G.Q., Gao, J., 2004c. Modeling of vegetationerosion dynamics in watershed systems. J. Environ. Eng. ASCE 130 (7), 792–800. Wang, F.X., Wang, Z.Y., Lee, J.H.W., 2007. Acceleration of vegetation succession on eroded land by reforestation in a subtropical zone. Ecol. Eng. 31, 232–241. Wang, H.S., Liu, G.S., 1999. Analyses on vegetation structures and their controlling soil erosion. J. Arid Land Resour. Environ. 13 (2), 62–68 (in Chinese with English abstract). Wang, Z.H., Duan, C.Q., Hou, Y.P., Yang, J.S., 2006. The relationship of plant species diversity to ecosystem function in relation to soil conservation in semi-humid evergreen forests, Yunnan province, China. J. Plant Ecol. 30 (3), 392–403 (in Chinese with English abstract). Wen, Z.M., Jiao, F., Liu, B.Y., Bu, Y.J., Jiao, J.Y., 2005. Natural vegetation restoration and soil nutrient dynamics of abandoned farmlands in forest steppe zone on Loess Plateau. Acta Ecol. Sin. 26 (4), 1165–1175 (in Chinese with English abstract).

Yang, Z., Xiong, D.H., Zhou, H.Y., Zhang, X.B., 2003. Rainfall infiltration on hilly slopes under various lithology and its effect on tree growth in the dry-hot valley. Sci. China Ser. E 46 (S1), 110–119. Zhang, X.B., Higgitt, D.L., Walling, D.E., 1990. A preliminary assessment of the potential for using Caesium-137 to estimate rates of soil erosion in the Loess Plateau of China. Hydrol. Sci. J. 35, 267–276. Zhang, X.B., Quine, T.A., Walling, D.E., Li, X., 1994. Application of the Caesium-137 technique in a study of soil erosion on gully slopes in a Yuan area of the Loess plateau near Xifeng, Gansu Province, China. Geogr. Ann. 76A, 103–120. Zhang, X.B., Wang, Y.C., Li, S.L., Zhang, Y.Y., Zhao, Q.C., Jiang, J.J., Bai, L.L., Yan, M.M., Wu, L.P., 1992. A preliminary study on the sources of fine materials of the sediment and debris flow. Soil Water Conserv. China 2 (32–35), 66 (in Chinese with English abstract). Zhang, X.B., Zhang, Y.Y., Wen, A.B., Feng, M.Y., 2003. Assessment of soil losses on cultivated land by using the 137 Cs technique in the upper Yangtze River basin of China. Soil Till. Res. 69, 99–106. Zhou, G.Y., Wei, X.H., Yan, J.H., 2002. Impacts of eucalyptus (Eucalyptus exserta) plantation of sediment yield in Guangdong Province south China—a kinetic energy approach. Catena 49, 231–251.