Research Article
Print
Research Article
Tree species composition rather than biodiversity impacts forest soil organic carbon of Three Gorges, southwestern China
expand article infoNan Liu‡, Yujie Wang§, Yunqi Wang§, Zhanjun Zhao|, Yangyi Zhao
‡ Taiyuan University of Technology, Taiyuan, China
§ Beijing forestry university, Beijing, China
| Jilin Agricultural University, Changchun, China
¶ Southwest Forestry University, Kunming, China

Corresponding author: Nan Liu ( liunan@tyut.edu.cn )

Academic editor: Yu-Pin Lin
© 2016 Nan Liu, Yujie Wang, Yunqi Wang, Zhanjun Zhao, Yangyi Zhao.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: Liu N, Wang Y, Wang Y, Zhao Z, Zhao Y (2016) Tree species composition rather than biodiversity impacts forest soil organic carbon of Three Gorges, southwestern China. Nature Conservation 14: 7-24. https://doi.org/10.3897/natureconservation.14.6486
ZooBank: urn:lsid:zoobank.org:pub:20CB3FC4-C2B1-45D5-9D35-2814EE7756F7
Open Access

Abstract

Forest soil represents an important resource for mitigating the climate change. Besides, plant composition and diversity and their roles in ecosystem functioning are becoming a central issue in forest soil organic carbon (SOC) research. The primary objective of this research is to investigate the effects of tree species diversity and composition on potential of C sequestration of forest soil in Three Gorges area and provide basic information to future research on climate change. Two dominant forest ecosystems were selected: mixed conifer-broadleaf forest (Fm) and evergreen broadleaf forest (Fb). Then study transects were established and investigated. Soil samples were collected and determined for bulk density, SOC concentration and stock, nitrogen (N) concentration and C:N ratio. The results showed that the statistical differences of SOC concentrations and stocks between Fm and Fb were caused by tree species composition rather than the tree species diversity. And the most significant differences were found in the first two soil horizons (0–15 cm and 15–30 cm). The average C:N values of four different horizons in Fm were decreased with increasing soil depth as well as Fb. Not only SOC concentrations but also stocks of the two studied forests were decreased with increasing soil depth. However, Fm showed a larger capacity to store SOC with an average stock of 183.50 t/ha than that of Fb (100.44 t/ha) in study area. Thus, forest which is composed of conifer and evergreen broadleaf tree species may be the best choice for local afforestation and reforestation aimed at alleviating climate change in Three Gorges region.

Keywords

Soil organic carbon, tree species composition, biodiversity, C:N ratio, Three Gorges

Introduction

Scientists have long been concerned with soil carbon (C), because it is often the master variable determining soil fertility (Malhi et al. 1999; Johnson and Curtis 2001; Johnson et al. 2002). C enters the soil through both litterfall and rhizodeposition and leaves the soil mainly as CO2 via root and microbial respiration (Sulzman et al. 2005; Cleveland et al. 2010; Díaz-Pinés et al. 2011; Sayer et al. 2011). However, as one of the most important green house gases, the tightly relationship between CO2 and soil C is generally accepted in the context of global climate change. Thus, known soil C stock has become very important for assessing changes in atmospheric CO2 concentrations and of global climate (Dixon et al. 1994; Schimel 1995; Søe et al. 2004). As the largest pool of terrestrial organic carbon in the biosphere, more C is stored in soil than is contained in plants and the atmosphere combined (Jobbágy and Jackson 2000). Global surveys of mineral soil organic carbon (SOC) indicate that the soil holds about 1500 Pg C in the upper meter of soil (Post et al. 1982; Eswaran et al. 1993; Jobbágy and Jackson 2000), and most of this SOC (roughly 70% of all SOC) is contained in forest soils (Dixon et al. 1994; Batjes 1996; Jandl et al. 2007).

The potential C sequestration of forest ecosystems is widely accepted (Batjes 1996; Jandl et al. 2007). In fact, by sequestering large amounts of atmospheric C, forest plays an essential role in the global C cycle and is thought to offer a mitigation strategy to reduce global warming (Dixon et al. 1994; Chiti et al. 2012). However, the extent to which the vegetation layer influences SOC stocks in natural mountain forest land of Three Gorges area is still poorly understood. Moreover, many articles about SOC have been focusing on its stock of a large area, for example, global scale, hemispheric scale or national scale (Eswaran et al. 1993; Dixon et al. 1994; Batjes 1996; Fang et al. 2001; Goodale et al. 2002; Li et al. 2004; Chiti et al. 2012). The SOC of smaller scale, such as forest communities and ecosystems, is not considered enough, especially in the aspect of relation between SOC and forest composition and diversity. Composition of tree species has a pivotal effect on soil processes, including the cycling and accumulation of C (García-Oliva et al. 2006; Díaz-Pinés et al. 2011). For example, trees drive litterfall inputs, rhizodeposition, animal manure and rainfall distribution, soil temperature, and consequently they shift soil microbial quantity and activity (Simón et al. 2013). Based on composition, the forest area can be classified into various types. Proportion of different species in the same plant community can be quantified through species composition investigation. Therefore, it is important to consider the influence of tree species composition on SOC stock at given sites, as it may provide a basis for quantifying C pool in forest, which plays a relevant role in the global C cycle (Mathers and Xu 2003; Chen et al. 2004). Our study will be added to the growing body of information on soil C storage in subtropical mountain forest of China. But beyond that, the relationship between plant diversity (i.e.: totality of genes, species, and ecosystems of a region) and biogeochemical process that regulates the ecosystem has been a central issue in both ecological and environmental sciences recently (Bunker et al. 2005; Chen 2006). Many studies have suggested that plant communities with high species diversity may promote more efficient use of resources compared with those of less species diversity and thus lead to greater net primary production, and consequently higher C sequestration (Saha 2008; Saha et al. 2009; Meier and Bowman 2010; Wang et al. 2011). However, Huston and Marland (2003) indicated that ecosystems with multiple species are not necessarily more productive than ecosystems with few species. Many natural ecosystems with low plant diversity, even near monocultures, are highly productive. Nevertheless, ecosystems with multiple species indeed provide some insurance that they may be steadier and continue to perform a particular function even if one of the species is lost. However, quantitative estimates of effects of tree species composition on SOC stocks under natural forest ecosystems remain scarce (Chapin III et al. 2000; Berger et al. 2002; Díaz-Pinés et al. 2011). Therefore, forest composition or biodiversity, which can be confirmed as the dominant effect on ecosystem C sequestration? The issue needs further researches.

In natural ecosystem, nitrogen (N) is a primary nutrient that limits vital activities of plant and microbe (Vitousek and Howarth 1991; Hu et al. 2001; LeBauer and Treseder 2008; Wei and Sun 2009). C cycling is consequently influenced by soil N and C:N ratio (Cleveland and Liptzin 2007; Cleveland et al. 2011), and both factors partly indicate activity of microbe and level of soil C decomposition by respirations of roots and microbes. Thus, both C stock and effects of C:N ratio have been hot spots of scientific interest in global change (Hungate et al. 2003; Chen 2006; Davidson and Janssens 2006).

Because of the alleviation effect on global warming, C sequestration ability of forest is expected for more and more focus (Wu et al. 2003; Lal 2004; Bonan 2008; Tarnocai et al. 2009). Especially in China, the large developing country all through the world, the conflict between environment and develop is becoming sharper and sharper. In order to reduce the green house gas, Chinese government has been struggling since a long time ago. Many measures have been conducted particularly in forestry. In last decades, although millions of hectares were planted (afforestation and reforestation) per year, making a huge C pool, the SOC stocks of forests in China have not restored from the continuously forestry C sequestration reducing since late 1940s (Fang et al. 2001). However, little attention was paid on the composition of tree species during silviculture and afforestation. It may cause inefficient C sequestration and cause unintended disastrous environmental consequences, especially in arid and semiarid regions (Gao et al. 2011). Nevertheless, C sequestration of natural forest should be studied in detail for “close-to-nature” afforestation and reforestation and finding the best forest management plan. Moreover, about 28 to 35% of forest C storage occurs in the southwestern region (including the provinces of Sichuan, Chongqing, Tibet, Yunnan, Guangxi, and Guizhou) which is the largest in China (Fang et al. 2001). Thus, forest C sequestration study in this region is important for afforestation and reforestation aiming at reducing green house gas in China. Since the end of 20th century, the Natural Forest Protection Project has been conducted in Three Gorges of southwestern China (http://english.forestry.gov.cn/index.php/information-services). Vegetation coverage in this area was 35.62% by the end of 2007 and it was far greater than average of China (20.36%) (Zhao 2007). The natural forest ecosystems of the area are great potential for C stock. But study on this is still rarely showed. Therefore, the aims of this study are as follows: (1) Study the effects of forest composition on SOC concentration and stock. (2) Analyze the effects of tree species diversity on SOC concentration and stock. (3) Difference of SOC decomposition in different forests is showed by C:N ratio.

Materials and methods

Description of research area

Our study was carried out at Jinyun Mountain, Three Gorges area, southwestern China. The forest area is totally 1112.7 ha which accounts for 96.6% local land area, and typical subtropical forest species are abundant. The study area is bounded by the two major river systems of the region, i.e., the Yangtze River and the Jialingjiang River. Elevation ranges from 350 to 952 m. This region has a subtropical monsoon climate with long warm to hot humid summers and short cool to cold and cloudy winters with the lowest total number of sunshine days in China (about 1000 hours per year). The mean annual temperature is 13.6 °C and the average annual precipitation is 1611.8 mm. Soil type is Kandihumults of Ultisols (Staff 2010).

Methods for investigating, sampling and determining

In our study, we investigated two natural forest ecosystems in April, 2011: the mixed conifer-broadleaf forest (Fm) and the evergreen broadleaf forest (Fb). These two forests are close to each other (separated from each other by approximately 100 m) and have similar elevation and same aspect. The basic information, including vegetation, soil and topography characteristics, is showed in Table 1. The total area of Fm was 17.3 ha, and the area of Fb is 12 ha. Transect method was performed to survey trees, shrubs and herbs. Soil samples were collected by establishing plots in transects. Parallel transects (100 × 40 m) separated by about 50 m, were established in forest Fm (n = 7) and Fb (n = 5). Then two 20 m × 20 m plots were randomly selected in each single transect. Unfortunately, only thirteen plots were set in Fm because of topographical reason. After this, the total inventory of all tree species was conducted in every plot. Shrub species were surveyed in three randomly selected 2 m × 2 m subplots involved in each 20 m × 20 m plot. And within each 2 m × 2 m subplot, herb species were recorded by setting one 1 m × 1 m quadrate. Plant species were recorded and counted. Biodiversity indices were calculated according to the inventory process mentioned above. Then mineral soil samples were collected by depth (0–15, 15–30, 30–50 and 50–100 cm or bedrock when the profile is not deep down to 100 cm.) in all quadrates. Soils from 1 m × 1 m quadrates in the same 20 m × 20 m plot were mixed and homogenized by depth. Consequently, one composite sample of mineral soil of each single horizon was collected in a plot. The total number of soil composite samples of Fm was 50 and that of Fb was 34. These samples were transported to the lab shortly after sampling (Díaz-Pinés et al. 2011) and air dried in shade. Soil bulk density and volume proportion of gravel at each soil sampling horizon were determined according to Landsberg et al. (2003). The Kjeldahl method was carried out to obtain N concentrations of soil (Gong et al. 2012). The SOC concentrations were tested according to the dichromate acid wet oxidation method (Yeomans and Bremner 1988).

Table 1.
Download as
CSV
XLSX

Basic information of studied forest ecosystems.

Site Dominant tree species Shrub species Herb species Soil type Range of slope (°) Aspect Mean elevation (m) Range of canopy density Total area (ha)
Fm Pinus massoniana Lamb.
Cunninghamia lanceolata (Lamb.) Hook.
Symplocos setchuensis Brand
Lindera kwangtungensis (Liou) Allen		 Maesa japonica (Thunb.) Moritzi.
Eurya nitida Korthals
Sarcandra glabra (Thunb.) Nakai
Smilax china
Rosa multiflora Thunb.
Eurya fangii Rehd.
Elaeagnus bockii Diels
Rubus assamensis Focke
Rubus malifolius Focke
Rubus corchorifolius L. f.
Camellia cuspidata (Kochs) Wright ex Gard.		 Woodwardia japonica (L. f.) Sm.
Lophatherum gracile Brongn.
Oplismenus compositus (Linn.) Beauv.
Hicriopteris glauca (Thunb.) Ching
Commelina communis Linn.
Stenoloma chusanum Ching
Miscanthus sinensis Anderss.
Hemerocallis fulva (L.) L.
Conyza canadensis (L.) Cronq.
Phyla nodiflora (L.) Greene		 Kandihumults of Ultisols 15–24 N 820 0.85–0.97 17.3
Fb Lindera kwangtungensis (Liou) Allen
Symplocos setchuensis Brand
Castanopsis fargesii Franch.
Adinandra bockiana
Gordonia acuminata Chang		 Maesa japonica (Thunb.) Moritzi.
Eurya nitida Korthals
Sarcandra glabra (Thunb.) Nakai
Smilax china
Neolitsea aurata (Hay.) Koidz
Eurya fangii Rehd.
Symplocos lancifolia Sieb. & Zucc.
Rubus malifolius Focke
Camellia cuspidata (Kochs) Wright ex Gard.		 Woodwardia japonica (L. f.) Sm.
Oplismenus compositus (Linn.) Beauv.
Hicriopteris glauca (Thunb.) Ching
Commelina communis Linn.
Stenoloma chusanum Ching
Miscanthus sinensis Anderss.
Hemerocallis fulva (L.) L.
Conyza canadensis (L.) Cronq.
Phyla nodiflora (L.) Greene		 Kandihumults of Ultisols 12–28 N 822 0.88–0.94 12

Calculation

SOC concentrations and stocks and their vertical distributions were studied. The statistical differences of SOC in 0–100 cm between the two studied forests were analyzed by T-test. The statistical differences of SOC in each horizon (i.e.: 0–15cm, 15–30 cm, 30–50 cm and 50–100 cm) between the two studied forests, as well as those among horizons, were analyzed by one-way ANOVA respectively. And this method was performed to test the differences between tree species diversity of the two researched forests. The results were summarized to explain the effects of tree species composition and diversity on SOC accumulation. In order to study the effect of tree diversity on SOC sequestration, the correlations between SOC and tree species diversity indices of Fm, as well as Fb, were then estimated by regression analysis. As an important controller of SOC decomposition, soil C:N ratio was also analyzed. One-way ANOVA was performed to evaluate the differences between C:N ratios of the two studied forests so as to understand the condition of SOC decomposition. Data analysis was implemented by using Microsoft Office Excel 2003 (Microsoft Corporation, US) and SPSS-17 (IBM Corporation, US).

SOC stock was calculated according to following formula:

(1)

Where ST is SOC stock (t/ha), i is soil horizon code, n is the number of soil horizons, Ci is SOC concentration (g/kg), ρi is soil bulk density (g/cm3), hi is soil horizon thickness (cm), θi is volume proportion (%) of gravel with diameter (φ) >2 mm.

Tree species diversity was presented by following indices (Li and Li 2006):

Simpson’s index (biodiversity index):

(2)

Shannon - Wiener index (biodiversity index):

(3)

Margalef index (richness index):

(4)

Where N is total number of trees in plot, i is tree species type, ni is number of individuals of tree species i, S is number of tree species.

Results

SOC under the two studied forests

SOC concentrations of the studied forests remarkably decreased with increasing depth of mineral soil. These correlations could be simulated as follows:

SOC concentrations of Fm and Fb may be calculated by above empirical models. But it indeed needs more samples for accuracy.

Significant differences (p<0.001) were found among the four soil horizons in both Fm and Fb (see Fig. 1A). The statistical difference of total SOC concentrations of 0-100 cm mineral soil between the two studied forests was significant with p=0.0016 (see Fig. 1A and Table 2). It indicated that the average concentration of 0-100 cm SOC in Fm (85.62 g/kg) was remarkably larger than Fb (46.18 g/kg) (see Fig. 1A, Table 2). Compared with Fm, SOC of Fb (46.18 g/kg) only accounted for 53.94% of its SOC concentration. In the first two soil horizons, the SOC concentrations were even more remarkably different: 0–15 cm soil with p=0.0101 and p=0.0338 for 15–30 cm soil (see Fig. 1A, Table 2). In the other two horizons, that the p values were 0.2068 (30–50 cm) and 0.1539 (50–100 cm) respectively indicated insignificant differences between SOC concentrations of Fm and Fb. The most remarkable difference was found in the first mineral soil horizon. 0–15 cm SOC concentration of Fm (52.38 g/kg) was significantly larger than that of Fb (31.02 g/kg). The other horizons of Fm had greater SOC than Fb as well even though the statistical differences were not remarkable (see Fig. 1A, Table 2).

Figure 1.

SOC concentrations (Fig. 1A), SOC stocks (Fig. 1B) and C:N ratios (Fig. 1C) of Fm and Fb. Where solid columns of different colors respectively show average values of each single horizon under the Fm and Fb. The columns with oblique lines are mean values of total SOC concentrations, total SOC stocks and average C:N ratios of 0-100 cm soil in Fm and Fb separately. Letters above each error bar indicate the statistical difference. The different capital letters show significant difference between value series of two forests (p<0.05), for example, capital letters on top of the two white columns (A and B) show difference between average 0–15 cm SOC concentrations of Fm and Fb. The different lowercase letters present remarkably differences of values among different soil horizons within a studied forest (p<0.001), for example, differences among SOC concentrations of 0–15 cm, 15–30 cm, 30–50 cm and 50–100 cm horizon of Fm were significant according to “a, b, c and d”.

Table 2.
Download as
CSV
XLSX

Mean value (`x) ± standard deviation (σ) of SOC concentration, SOC stock and C:N ratio. The p values which are less than 0.05 indicate significant difference between Fm and Fb.

Fm Fb
xˉ ± σ xˉ ± σ p F Critical values of F t Statistical values of t
SOC concentration
0–15 cm 52.38±22.49 31.02±8.88 0.0101 7.9880 4.3248 —— ——
15–30 cm 16.45±7.66 9.51±6.37 0.0338 5.1562 4.3248 —— ——
30–50 cm 10.62±9.77 5.19±6.31 0.2068 1.7229 8.3997 —— ——
50–100 cm 7.57±7.52 2.89±4.41 0.1539 2.2275 8.3997 —— ——
0–100 cm 85.62±30.17 46.18±18.44 0.0016 —— —— 2.0796 3.6342
SOC stock
0–15 cm 75.23±29.09 56.96±14.58 0.0843 3.2841 4.3248 —— ——
15–30 cm 32.03±14.88 18.70±11.55 0.0294 5.4666 4.3248 —— ——
30–50 cm 29.00±24.38 15.09±18.60 0.2114 1.6865 4.4513 —— ——
50–100 cm 53.59±47.01 20.30±28.37 0.1092 2.8583 4.4513 —— ——
0–100 cm 183.50±71.59 100.44±50.38 0.0052 —— —— 2.0796 3.1159
C:N ratio
0–15 cm 9.63±12.47 7.44±6.71 0.5853 0.3071 4.3248 —— ——
15–30 cm 7.30±8.41 4.27±4.45 0.3162 1.0544 4.3248 —— ——
30–50 cm 4.82±5.54 4.51±5.36 0.8910 0.0194 4.4513 —— ——
50–100 cm 4.89±8.53 3.83±4.72 0.7780 0.0821 4.4513 —— ——
0–100 cm 6.66±2.29 5.01±1.64 0.4464 0.8175 3.9574 —— ——

SOC stocks in 0–100 cm of Fm and Fb (Fig. 1B, Table 2) were statistically different (p=0.0052). However, 0–15 cm SOC stocks of the two forests were not significantly different with a p value of 0.0843 in contrast with 0–15 cm SOC concentrations (see Fig. 1A, B and Table 2). But the statistical difference of SOC stocks in 15–30 cm soil was remarkable (p=0.0294) (Fig. 1A). The SOC stocks, at the last two horizons, were both not statistically different between Fm and Fb as the same as those of SOC concentrations (see Fig. 1A, B and Table 2). Both SOC stocks of Fm and Fb along soil horizons were found to be significantly different (p=0.0013 for Fm, p=0.00006 for Fb, Fig. 1B). The change of SOC stocks from topsoil to bottom was performed as follows:

SOC stocks of Fm and Fb were decreased from 0-15 cm to 30-50 cm firstly, then they were increased (Fig. 1B and Table 2).

As shown in Fig. 1B and Table 2, the average total SOC stocks (0-100 cm) ranged from 183.50 t/ha of Fm to 100.44 t/ha of Fb. The quantitative relationship between SOC stocks of Fm and Fb was consistent with that of SOC concentrations (see Fig. 1A, B and Table 2). In Fm, 62.91% of the total SOC down to 1 m was in the top 30 cm (Fig. 1B and Table 2). The proportion was even more in Fb (83.08%). However, the main difference of SOC stock was found in 15-30 cm soil rather than the first horizon (Fig. 1B and Table 2).

C:N ratios of Fm and Fb

Concentrations of SOC and soil N of Fm (r=0.6656, n=50, p<0.001) were linearly and remarkably correlated as well as those of Fb (r=0.5566, n=34, p<0.001). The results showed that soil N may have important effects on SOC. However, as a metric of SOC quality, the soil C:N ratios of the studied forests were not statistically different (Fig. 1C and Table 2). The above results indicated that C:N ratio may not lead to the differences of SOC between the two studied forests. However, the C:N ratio was decreased with increasing soil depth (Fig. 1C and Table 2). From the first to the forth horizon, the average C:N values of Fm were respectively 9.63, 7.30, 4.82 and 4.89 (Fig. 1C and Table 2). And those of Fb were 7.44, 4.27, 4.51 and 3.83 (Fig. 1C and Table 2). Although the average C:N ratio of 30–50 cm soil under Fb was larger than 15–30 cm soil, and the mean C:N ratio of 50–100 cm under Fm was larger than 30–50 cm soil, the C:N ratio was also generally decreased from 0–15 cm with maximum to 50–100 cm with minimum.

Relationship between tree species diversity and C

Average values of tree species diversity indices were shown in Table 3. That the average values of diversity indices of Fm were greater than those of Fb except for D indicated that the biodiversity (H) and richness (R) were the best in Fm, whereas another biodiversity index D of Fb was the greatest. And the one-way ANOVA analysis supplied the estimation: the statistical difference between biodiversity indices of Fm and Fb was not significant. According to the linear correlation analysis between SOC and tree species diversity of Fm and Fb, the SOC concentrations, including SOC in each individual horizon and total soil profile, were not significantly correlated with the three diversity indices as well as SOC stocks (p>0.05).

Table 3.
Download as
CSV
XLSX

Average values of tree species diversity indices.

Forests R (Margalef) H (Shannon-Wiener) D (Simpson’s)
Fm 1.542 1.832 0.693
Fb 1.406 1.663 0.812

Discussions

The main differences of SOC concentrations of Fm and Fb were presented in 0–15 cm and 15–30 cm soil with p value of 0.0101 and 0.0338 respectively. The reason may be that roots are mainly distributed in 0–50 cm soil horizon (Waisel et al. 1991; Upson and Burgess 2013). However, the difference of SOC concentrations was insignificant in 30–50 cm horizon (p=0.2068). The SOC stocks of Fm and Fb were only significantly different in 15–30 cm horizon (p=0.0294). Totally, SOC concentrations of 0–100 cm in the two forests (p=0.0016) were significantly and statistically different as well as SOC stocks (p=0.0052) (Fig. 1A, B and Table 2). Thus, tree species compositions of forest ecosystems could be considered as a reasonable factor for distinguishing SOC from each other especially in surface soil (0–30 cm). Currently, Chinese government has been carried out many protection programs of forest in order to build a healthy natural ecosystem, for example, Land Conversion from Farmland back to Forestland Project, Wildlife Protection and Nature Reserve Development Program and Natural Forest Protection Project, etc (http://english.forestry.gov.cn/index.php/information-services). Simultaneously, afforestation and silviculture are implemented all through the country to decelerate global warming. Ecological conditions of China have a continual improvement and C sink potential keeps increasing. However, problems are also existed: monoculture afforestation, lack of forest management, and contradiction between food shortage and returning crop land to forest. Forest quality is influenced by those problems. These issues should be properly solved. In Three Gorge area, because of our SOC stock estimates, mixed conifer-broadleaf forest (Fm) with the largest soil C pool (183.50 t/ha) may be the best choice for local afforestation and reforestation aimed at alleviating climate change.

Liu (2005) suggested that broadleaf forest was climax communities in succession process of Mt. Jinyun with mixed conifer-broadleaf forest being inferior community. Several works (Malhi et al. 1999; Marín‐Spiotta and Sharma 2013) suggested that both land use change and forest succession gradient were generally thought to have effect on SOC stocks, especially for surface soil. Nevertheless, the successional effects of forest communities in Three Gorges are still not understood well. Thus, the specific studies under local conditions are very necessary. Not only the 0–15 cm SOC concentrations were remarkably different (p=0.0101) between Fm and Fb, but also the 15–30 cm SOC concentrations were significantly different from each other (p=0.0338). Although insignificant, the difference of 0–15 cm SOC stocks between forests was indeed existent with p value of 0.0843. Nevertheless SOC stocks of 15–30 cm soil were remarkable different between Fm and Fb (p=0.0294). And the differences of SOC concentrations and stocks between Fm and Fb became weaker and weaker with increasing soil depth where roots of bottom soil were far less than surface soil. The above analysis showed that succession effects may be another reason which could control SOC stock of forest by influencing tree species composition.

Our total C stock estimates of 0-100 cm mineral soil under the two forest ecosystems (100.44–183.50 t/ha, Fig. 1B and Table 2) were beyond the range of values estimated for the mineral soil under forests of Mt. Dinghu with the similar climate (30.90-127.90 t/ha) (Fang et al. 2003), but included the estimate for the Ultisols soil (144.80 t/ha) in Chongqing city (Huang et al. 2005) (Table 4). In Mt. Dinghu (Fang et al. 2003), the SOC stocks in mixed conifer-broadleaf forests (30.90-107.10 t/ha) were less than those of evergreen broadleaf forests (95.00-127.90 t/ha). Chen (2007) suggested that mixed conifer-broadleaf forest (92.33-127.13 t/ha) sequestrated less C than evergreen broadleaf forest (151.63-290.82 t/ha) in Three Gorges region (Table 4). The results were contrary to our data. However, study in Spain showed that mixed conifer-broadleaf forest caught more SOC than evergreen broadleaf forest as well as in other regions of Mediterranean conditions which belongs to subtropics as the same as our research area (Díaz-Pinés et al. 2011) (Table 4). Li et al. (2004) also suggested that SOC stock of evergreen broadleaf forest (129.2 t/ha) in China was less than that of mixed conifer-broadleaf forest (225.70 t/ha) (Table 4). Ni (2001) estimated the SOC stocks of the two types of forests in China: 124.00-142.00 t/ha for evergreen broadleaf forest and 130.00-150.00 t/ha for mixed conifer-broadleaf forest (Table 4). Mixed forest caught more SOC than evergreen broadleaf forest. The differences of C stock among regions may be also due to climatic (Díaz-Pinés et al. 2011; Chiti et al. 2012) and geologic conditions etc (Schaefer et al. 2009). Besides, sampling time may also affect estimating value of C stock in forest soil. However, in southwestern China, the average forest biomass C stock was 60 t/ha which was the largest all through the country (Fang et al. 2001). And that the SOC is far more than biomass C is widely accepted. It indicated that natural forest in this region is a great container for C. Our results were greater than the average SOC stock of Ultisols soil on the Earth (Eswaran et al. 1993), which also showed the strong C sequestration of forests in the research area (Table 4). However, Woodwell (1984) indicated that Ultisols soil under virgin and secondary forests on Earth stored more SOC (180.00-240.00 t/ha) than the two forests in this study (Table 4).

Table 4.
Download as
CSV
XLSX

Published values of SOC in comparable mixed conifer-broadleaf forest and evergreen broadleaf forest in subtropical region.

Locatoin Vegetation type SOC stocks (t/ha) Soil type Source
Earth Virgin and secondary forests 180.00–240.00 Ultisols Woodwell (1984)
Earth —— 83.00 Ultisols Eswaran et al. (1993)
China Mixed conifer-broadleaf forest 130.00–150.00 —— Ni (2001)
China Evergreen broadleaf forest 124.00–142.00 —— Ni (2001)
Fujian, China Mixed conifer-broadleaf forest 30.90–107.10 Ultisols Fang et al. (2003)
Fujian, China Evergreen broadleaf forest 95.00–127.90 Ultisols Fang et al. (2003)
China Mixed conifer-broadleaf forest 225.70 —— Li et al. (2004)
China Evergreen broadleaf forest 129.20 —— Li et al. (2004)
Chongqing, China —— 144.8 Ultisols Huang et al. (2005)
Three Gorges region, China Mixed conifer-broadleaf forest 92.33–127.13 Ultisols and Alfisols Chen (2007)
Three Gorges region, China Evergreen broadleaf forest 151.63–290.82 Ultisols and Alfisols Chen (2007)
Central Spain Mixed conifer-broadleaf forest 80.00–100.00 Inceptisols and Alfisols Díaz-Pinés et al. (2011)
Central Spain Evergreen broadleaf forest 40.00–70.00 Inceptisols and Alfisols Díaz-Pinés et al. (2011)
Three Gorges region, China (Chongqing section) Mixed conifer-broadleaf forest 183.50 Ultisols This study
Three Gorges region, China (Chongqing section) Evergreen broadleaf forest 100.44 Ultisols This study

Both the average soil C:N ratios of Fm and Fb were decreasing with increasing soil depth. And the average C:N ratios of Fb were less than those of Fm in each soil horizons. The C:N ratio provides some indication about the relative quality and biochemical stability of soil organic materials (Díaz-Pinés et al. 2011; Bui and Henderson 2013). The C:N ratio hinted a weak SOC decomposition in our studied forests. Therefore, SOC stock of study area was larger than the average value of Utisols soil on the earth (Eswaran et al. 1993) as well as forest soil in southwestern China (Fang et al. 2001). However, the C:N values of Fm and Fb were not statistically different (p=0.3879). On the other hand, SOC concentrations (p=0.0474) and stocks (p=0.0116) of Fm and Fb were remarkably different. The results showed that SOC differences between Fm and Fb were influenced by C:N ratio little, which indicated that SOC decompositions of Fm and Fb were similar. The composition of tree species may be a rational factor for distinguishing the differences between C sequestrations of forests in study area as above analysis.

The relationship between tree species diversity and SOC under studied forest ecosystems was not linear in our study. However, Chen (2006) suggested that SOC stocks were linearly increased with growing H indices of forests in Northeastern China. Nevertheless, in Sichuan Province of southwestern China (closely located in the west of our study area), the correlations between SOC and R and H of forests were as the same as our findings (Zhang et al. 2011). Kirby and Potvin (2007) did not find any linear relationship at soil profiles under forests in Eastern Panama either. The environmental factors of different region (Ewel et al. 1991; Berendse 1998; Forrester et al. 2006) and various forest productivities (Vandermeer 1989; Tilman et al. 1997) may cause the different relationships. And more studies are needed to explain the correlation between biodiversity and SOC in order to develop forest management and establish forest with great C sequestration. However, the statistical difference between biodiversity indices of Fm and Fb was not significant (Table 3). Thus, in contrast to plant species composition, biodiversity may not make difference in forest soil C sequestrations.

Conclusions

Tree species composition significantly and statistically influenced SOC concentrations and stocks of Fm and Fb. In first two soil horizons (0-15 cm and 15-30 cm), these differences were even more significant. However, SOC of Fm and Fb were not influenced by tree species diversity due to the very low linear coefficients. And the statistical difference between biodiversity indices of Fm and Fb was not significant. Thus, in contrast to plant species composition, biodiversity may not make difference in forest soil C sequestrations. The average C:N values of Fm in four different horizons were decreased with increasing soil depth as well as Fb. And the values were larger in Fm. But the difference between C:N ratios of Fm and Fb was not remarkable. C:N ratio contributed little to the difference between SOC of the two studied forests. Not only SOC concentrations of Fm and Fb were decreased with increasing soil depth but also SOC stocks reduced from surface soil to bottom. Fm showed a large capacity to store SOC rather than Fb in the area. Thus, mixed conifer-broadleaf forest may be the best choice for local afforestation and reforestation aimed at alleviating climate change in Three Gorges region. However, conflict issues can still be found in the relation between SOC and tree species diversity in studies all over the world. It needs more detail researches in different scale to explain.

Acknowledgement

The work was funded by projects of National Natural Science Foundation of China (31400618, 41201265, 41503074), Qualified Personnel Foundation of Taiyuan University of Technology (Grant No: tyut-rc201277a), and the project supported by Youth Foundation of Taiyuan University of Technology (No. 1205-04020102, No. 2013Z070). We are grateful to the Ecologist Kristen Manies from U.S. Geological Survey and Ecologist Charlotte Reemts from Texas Field Office of Nature Conservancy for their constructive comments that improved this manuscript.

References

  • Berendse F (1998) Effects of dominant plant species on soils during succession in nutrient-poor ecosystems. Biogeochemistry 42: 73–88. doi: 10.1023/A:1005935823525
  • Berger TW, Neubauer C, Glatzel G (2002) Factors controlling soil carbon and nitrogen stores in pure stands of Norway spruce (Picea abies) and mixed species stands in Austria. Forest Ecology and Management 159: 3–14. doi: 10.1016/S0378-1127(01)00705-8
  • Bonan GB (2008) Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320: 1444–1449. doi: 10.1126/science.1155121
  • Bui EN, Henderson BL (2013) C: N: P stoichiometry in Australian soils with respect to vegetation and environmental factors. Plant and soil 373: 553–568. doi: 10.1007/s11104-013-1823-9
  • Bunker DE, DeClerck F, Bradford JC, Colwell RK, Perfecto I, Phillips OL, Sankaran M, Naeem S (2005) Species loss and aboveground carbon storage in a tropical forest. Science 310: 1029–1031. doi: 10.1126/science.1117682
  • Chapin III FS, Zavaleta ES, Eviner VT, Naylor RL, Vitousek PM, Reynolds HL, Hooper DU, Lavorel S, Sala OE, Hobbie SE (2000) Consequences of changing biodiversity. Nature 405: 234–242. doi: 10.1038/35012241
  • Chen C, Xu Z, Mathers N (2004) Soil carbon pools in adjacent natural and plantation forests of subtropical Australia. Soil Science Society of America Journal 68: 282–291. doi: 10.2136/sssaj2004.2820
  • Chen L (2007) Studies on soil organic carbon under main forest vegetation types in the Three Gorges Reservoir area. PHD Thesis. Beijing Forestry University, Beijing.
  • Chen X (2006) Tree Diversity, Carbon Storage, and Soil Nutrient in an Old‐Growth Forest at Changbai Mountain, Northeast China. Communications in soil science and plant analysis 37: 363–375. doi: 10.1080/00103620500440210
  • Chiti T, Díaz-Pinés E, Rubio A (2012) Soil organic carbon stocks of conifers, broadleaf and evergreen broadleaf forests of Spain. Biology and Fertility of Soils 48: 817–826. doi: 10.1007/s00374-012-0676-3
  • Cleveland CC, Liptzin D (2007) C: N: P stoichiometry in soil: is there a “Redfield ratio” for the microbial biomass? Biogeochemistry 85: 235–252. doi: 10.1007/s10533-007-9132-0
  • Cleveland CC, Townsend AR, Taylor P, Alvarez‐Clare S, Bustamante M, Chuyong G, Dobrowski SZ, Grierson P, Harms KE, Houlton BZ (2011) Relationships among net primary productivity, nutrients and climate in tropical rain forest: a pan‐tropical analysis. Ecology Letters 14: 939–947. doi: 10.1111/j.1461-0248.2011.01658.x
  • Cleveland CC, Wieder WR, Reed SC, Townsend AR (2010) Experimental drought in a tropical rain forest increases soil carbon dioxide losses to the atmosphere. Ecology 91: 2313–2323. doi: 10.1890/09-1582.1
  • Díaz-Pinés E, Rubio A, Van Miegroet H, Montes F, Benito M (2011) Does tree species composition control soil organic carbon pools in Mediterranean mountain forests? Forest Ecology and Management 262: 1895–1904. doi: 10.1016/j.foreco.2011.02.004
  • Davidson EA, Janssens IA (2006) Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440: 165–173. doi: 10.1038/nature04514
  • Dixon RK, Solomon A, Brown S, Houghton R, Trexier M, Wisniewski J (1994) Carbon pools and flux of global forest ecosystems. Science 263: 185–190. doi: 10.1126/science.263.5144.185
  • Ewel JJ, Mazzarino MJ, Berish CW (1991) Tropical soil fertility changes under monocultures and successional communities of different structure. Ecological Applications 1: 289–302. doi: 10.2307/1941758
  • Fang J, Chen A, Peng C, Zhao S, Ci L (2001) Changes in forest biomass carbon storage in China between 1949 and 1998. Science 292: 2320–2322. doi: 10.1126/science.1058629
  • Fang Y, Mo J, Sandra B, Zhou G, Zhang Q, Li D (2003) Storage and distribution of soil organic carbon in Dinghushan Biosphere Reserve. Acta Ecologica Sinica 24: 135–142.
  • Forrester DI, Bauhus J, Cowie AL, Vanclay JK (2006) Mixed-species plantations of Eucalyptus with nitrogen-fixing trees: A review. Forest Ecology and Management 233: 211–230.
  • Gao G, Ding G, Wang H, Zang Y, Liang W (2011) China needs forest management rather than reforestation for carbon sequestration. Environmental science & technology 45: 10292–10293. doi: 10.1021/es203897f
  • García-Oliva F, Hernández G, Lancho JFG (2006) Comparison of ecosystem C pools in three forests in Spain and Latin America. Annals of forest science 63: 519–523. doi: 10.1051/forest:2006034
  • Gong J, Ge Z, An R, Duan Q, You X, Huang Y (2012) Soil respiration in poplar plantations in northern China at different forest ages. Plant and soil 360: 109–122. doi: 10.1007/s11104-011-1121-3
  • Goodale CL, Apps MJ, Birdsey RA, Field CB, Heath LS, Houghton RA, Jenkins JC, Kohlmaier GH, Kurz W, Liu S (2002) Forest carbon sinks in the Northern Hemisphere. Ecological Applications 12: 891–899. doi: 10.1890/1051-0761(2002)012[0891:FCSITN]2.0.CO;2
  • Hu S, Chapin FS, Firestone M, Field C, Chiariello N (2001) Nitrogen limitation of microbial decomposition in a grassland under elevated CO2. Nature 409: 188–191. doi: 10.1038/35051576
  • Huang X, Ni J, Gao M, Wei C, Xie D (2005) Estimating soil organic carbon pool of Chongqing area and its spatial distribution. Journal of Soil Water Conservation 1: 014.
  • Hungate BA, Dukes JS, Shaw MR, Luo Y, Field CB (2003) Nitrogen and climate change. Science 302: 1512–1513. doi: 10.1126/science.1091390
  • Huston MA, Marland G (2003) Carbon management and biodiversity. Journal of environmental Management 67: 77–86. doi: 10.1016/S0301-4797(02)00190-1
  • Jandl R, Lindner M, Vesterdal L, Bauwens B, Baritz R, Hagedorn F, Johnson DW, Minkkinen K, Byrne KA (2007) How strongly can forest management influence soil carbon sequestration? Geoderma 137: 253–268. doi: 10.1016/j.geoderma.2006.09.003
  • Johnson D, Knoepp JD, Swank WT, Shan J, Morris L, Van Lear D, Kapeluck P (2002) Effects of forest management on soil carbon: results of some long-term resampling studies. Environmental Pollution 116: S201–S208. doi: 10.1016/s0269-7491(01)00252-4
  • Johnson DW, Curtis PS (2001) Effects of forest management on soil C and N storage: meta analysis. Forest Ecology and Management 140: 227–238. doi: 10.1016/S0378-1127(00)00282-6
  • Kirby KR, Potvin C (2007) Variation in carbon storage among tree species: implications for the management of a small-scale carbon sink project. Forest Ecology and Management 246: 208–221. doi: 10.1016/j.foreco.2007.03.072
  • Landsberg JD, Miller RE, Anderson HW, Tepp JS (2003) Bulk density and soil resistance to penetration as affected by commercial thinning in northeastern Washington.
  • LeBauer DS, Treseder KK (2008) Nitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed. Ecology 89: 371–379. doi: 10.1890/06-2057.1
  • Li J, Li J (2006) Studies on forest species diversity protection. China Forestry Publishing House, Beijing.
  • Li K, Wang S, Cao M (2004) Vegetation and soil carbon storage in China. Science in China series d earth sciences-english edition- 47: 49–57. doi: 10.1360/02yd0029
  • Liu H (2005) Dynamics of Soil Properties and the Effect Factors among Secondary Successive Communities in Mt. Jinyun. PHD Thesis. Southwest Agricultural University, Chongqing.
  • Malhi Y, Baldocchi D, Jarvis P (1999) The carbon balance of tropical, temperate and boreal forests. Plant, Cell & Environment 22: 715–740. doi: 10.1046/j.1365-3040.1999.00453.x
  • Marín-Spiotta E, Sharma S (2013) Carbon storage in successional and plantation forest soils: a tropical analysis. Global Ecology and Biogeography 22: 105–117. doi: 10.1111/j.1466-8238.2012.00788.x
  • Mathers NJ, Xu Z (2003) Solid-state 13C NMR spectroscopy: characterization of soil organic matter under two contrasting residue management regimes in a 2-year-old pine plantation of subtropical Australia. Geoderma 114: 19–31. doi: 10.1016/S0016-7061(02)00339-7
  • Meier CL, Bowman WD (2010) Chemical composition and diversity influence non-additive effects of litter mixtures on soil carbon and nitrogen cycling: Implications for plant species loss. Soil Biology and Biochemistry 42: 1447–1454. doi: 10.1016/j.soilbio.2010.05.005
  • Ni J (2001) Carbon storage in terrestrial ecosystems of China: estimates at different spatial resolutions and their responses to climate change. Climatic Change 49: 339–358. doi: 10.1023/A:1010728609701
  • Post WM, Emanuel WR, Zinke PJ, Stangenberger AG (1982) Soil carbon pools and world life zones.
  • Søe AR, Giesemann A, Anderson T-H, Weigel H-J, Buchmann N (2004) Soil respiration under elevated CO2 and its partitioning into recently assimilated and older carbon sources. Plant and Soil 262: 85–94. doi: 10.1023/B:PLSO.0000037025.78016.9b
  • Saha SK (2008) Carbon sequestration potential of tropical homegardens and related land-use systems in Kerala, India. PHD Thesis. University of Florida, Gainesville.
  • Saha SK, Nair PR, Nair VD, Kumar BM (2009) Soil carbon stock in relation to plant diversity of homegardens in Kerala, India. Agroforestry systems 76: 53–65. doi: 10.1007/s10457-009-9228-8
  • Sayer EJ, Heard MS, Grant HK, Marthews TR, Tanner EV (2011) Soil carbon release enhanced by increased tropical forest litterfall. Nature Climate Change 1: 304–307. doi: 10.1038/nclimate1190
  • Schaefer DA, Feng W, Zou X (2009) Plant carbon inputs and environmental factors strongly affect soil respiration in a subtropical forest of southwestern China. Soil Biology and Biochemistry 41: 1000–1007. doi: 10.1016/j.soilbio.2008.11.015
  • Simón N, Montes F, Díaz-Pinés E, Benavides R, Roig S, Rubio A (2013) Spatial distribution of the soil organic carbon pool in a Holm oak dehesa in Spain. Plant and soil 366: 537–549. doi: 10.1007/s11104-012-1443-9
  • Staff SS (2010) Keys to Soil Taxonomy. United States Department of Agriculture Natural Resources Conservation Service.
  • Sulzman EW, Brant JB, Bowden RD, Lajtha K (2005) Contribution of aboveground litter, belowground litter, and rhizosphere respiration to total soil CO2 efflux in an old growth coniferous forest. Biogeochemistry 73: 231–256. doi: 10.1007/s10533-004-7314-6
  • Tarnocai C, Canadell J, Schuur E, Kuhry P, Mazhitova G, Zimov S (2009) Soil organic carbon pools in the northern circumpolar permafrost region. Global biogeochemical cycles 23. doi: 10.1029/2008gb003327
  • Tilman D, Lehman CL, Thomson KT (1997) Plant diversity and ecosystem productivity: theoretical considerations. Proceedings of the National Academy of Sciences 94: 1857–1861. doi: 10.1073/pnas.94.5.1857
  • Upson M, Burgess P (2013) Soil organic carbon and root distribution in a temperate arable agroforestry system. Plant and soil 373: 43–58. doi: 10.1007/s11104-013-1733-x
  • Vandermeer JH (1989) The ecology of intercropping. Cambridge University Press, Cambridge, 1–249. doi: 10.1017/cbo9780511623523
  • Vitousek PM, Howarth RW (1991) Nitrogen limitation on land and in the sea: how can it occur? Biogeochemistry 13: 87–115. doi: 10.1007/BF00002772
  • Waisel Y, Eschel A, Kafkafi U (1991) Plant roots: the hidden half. Marcel Dekker, Inc., New York.
  • Wang W, Lei X, Ma Z, Kneeshaw DD, Peng C (2011) Positive Relationship between Aboveground Carbon Stocks and Structural Diversity in Spruce-Dominated Forest Stands in New Brunswick, Canada. Forest Science 57.
  • Wei XH, Sun G (2009) Watershed ecosystem processes and management. Higher Education Press, Beijing.
  • Woodwell GM (1984) The role of terrestrial vegetation in the global carbon cycle: measurement by remote sensing. John Wiley & Sons Ltd., Hoboken.
  • Wu H, Guo Z, Peng C (2003) Land use induced changes of organic carbon storage in soils of China. Global Change Biology 9: 305–315. doi: 10.1046/j.1365-2486.2003.00590.x
  • Yeomans JC, Bremner JM (1988) A rapid and precise method for routine determination of organic carbon in soil. Communications in soil science and plant analysis 19: 1467–1476. doi: 10.1080/00103628809368027
  • Zhang Y, Duan B, Xian J, Korpelainen H, Li C (2011) Links between plant diversity, carbon stocks and environmental factors along a successional gradient in a subalpine coniferous forest in Southwest China. Forest Ecology and Management 262: 361–369. doi: 10.1016/j.foreco.2011.03.042
  • Zhao J (2007) Study on dynamic changes of the vegetation cover of the Three Gorges Reservoir Area in 1988–2007. Thesis. Huazhong Agricultural University.
login to comment