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The impacts of geographic, soil and climatic factors on plant diversity, biomass and their relationships of the alpine dry ecosystems: Cases from the Aerjin Mountain Nature Reserve, China
Ecological Engineering 127 (2019) 170–177
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The impacts of geographic, soil and climatic factors on plant diversity, biomass and their relationships of the alpine dry ecosystems: Cases from the Aerjin Mountain Nature Reserve, China
T
⁎
Dong Shi-kuia, , Sha Weia, Su Xu-kunb, Zhang Yongc, LI Shuaia, Gao Xiaoxaia, Liu Shi-lianga, Shi Jian-bina, Liu Quan-rud, Hao Yana a
School of Environment, Beijing Normal University, Beijing 100857, China Research Center for Eco-Environment, Chinese Academy of Sciences, Beijing 100085, China Collge of Wetland, Southwest Forestry University, Kunming 650224, China d School of Life, Beijing Normal University, Beijing 100875, China b c
A R T I C LE I N FO
A B S T R A C T
Keywords: Alpine Desert Nature Reserve Plant species diversity Plant functional diversity Plant biomass Impacting factors
Spatial patterns of plant species diversity, functional diversity, and aboveground plant biomass, and their relationships with environmental factors in the Aerjin Mountain Nature Reserve (AMNR) on the Qinghai-Tibetan Plateau, China were examined in this study. The transect-quadrat sampling method was applied to sample the plant species and functional diversity and the aboveground plant biomass. Statistical package F-diversity v. 2011 was used to calculate the functional diversity index. OriginPro 9.0 drawing software was used to diagram 3dimensional (longitudinal, latitudinal, and altitudinal) distribution patterns of plant diversity, plant biomass and environmental factors. Correlations among plant biomass, species diversity, functional diversity, and environmental factors were analyzed by using SPSS16.0. The results indicated that alpine steppe was the major vegetation type in high-altitude areas of the southwestern region of the AMNR, alpine wet meadow and alpine steppe were the major vegetation types in low altitude areas of the northeastern region of the AMNR. The vegetation types in mid-altitude areas of the northwestern region and low altitude areas of the southeastern region of the AMNR were primarily alpine desert. Plant species diversity and biomass did not vary significantly along latitudinal, longitudinal, and altitudinal gradients. Plant species diversity was positively correlated with soil total nitrogen, total carbon, organic carbon, and moisture. The functional diversity of the plant community was positively correlated with precipitation and soil moisture. Vegetation biomass was positively correlated with soil total nitrogen, organic carbon, and soil moisture, whereas it was negatively correlated with soil bulk density. Plant species diversity was positively correlated with the functional diversity of the plant community. The integrated effects of geographic factors, soil factors, and meteorological conditions contributed to the spatial heterogeneity of species biodiversity and vegetation biomass of the plant communities in the AMNR, whereas the effects of soil and climatic factors were much stronger than those of geographical factors.
1. Introduction Plant composition and diversity are the most important factors that determine plant community structure and type, development level, and habitat differences (Wang et al., 2005). The study of plant-community species composition, diversity, and primary productivity is the basis for understanding plant community features (Wang et al., 2012). Plant community, a unit of association, may change spatially and temporally (Li, 1993). Some researchers reported from global and regional studies that plant species diversity exhibited obvious changes because of
⁎
latitudinal and altitudinal dimensions (Gentry, 1988; Malyshev et al., 1994; Gaston, 2000); more specifically, plant diversity decreased with increasing latitude or altitude (Brown and Lomolino, 1998), or exhibited higher “inflation” at mid-level latitude and altitude (Whittaker, 1960). The changes of plant species diversity along geographical gradients and their causes have become key issues in the fields of biodiversity research (Yang et al., 2004). Spatial changes in plant species diversity may be mainly associated with environmental factors, such as temperature, humidity, soil nutrients, and solar radiation (Yang et al., 2004; Xin et al., 2004). In
Corresponding author. E-mail address: [email protected] (S.-k. Dong).
https://doi.org/10.1016/j.ecoleng.2018.10.027 Received 26 May 2018; Received in revised form 28 October 2018; Accepted 31 October 2018 0925-8574/ © 2018 Elsevier B.V. All rights reserved.
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2014, Palombo, 2016), whereas few scholars have studied the functional diversity of alpine ecosystems. Therefore, the objectives of our study were to: 1) identify the spatial patterns of plant species diversity, functional diversity, and biomass of the undisturbed alpine ecosystems; 2) understand the effects of environmental factors on plant species diversity, functional diversity, and biomass; and 3) clarify the relationships between plant species diversity, functional diversity, and biomass in the alpine ecosystems. The findings of this study could provide a sound basis for scientifically managing the alpine parks and protected areas, such as the AMNR, to maintain their ecosystem functions of biodiversity conservation and primary production.
alpine grassland ecosystems (mostly alpine meadow and alpine steppe), the dominant ecosystems on the Qinghai-Tibetan Plateau (QTP), most scholars have focused on the study of plant species diversity, functional group diversity, and their relationships with plant biomass and environmental factors. They have drawn different conclusions. Plant species diversity of the alpine grasslands increased with the increasing latitude and longitude, decreased with increasing altitude (Yang et al., 2004), or exhibited “inflation” at the mid-level altitude (Wang et al., 2005). The dynamics of alpine plant diversity with altitude and latitude may be mainly related to growing season, precipitation, the warmness index, and plant biomass (Yang et al., 2004). Both species diversity and functional diversity are very important factors for evaluating ecosystem functions (Petchey and Gaston, 2006; Li and Zeng, 2008); in other words, ecosystem functions are dependent not only on the number of species, but also on species composition and functions of traits (Diaz et al., 2001; Cadotteet al., 2009; Mokanyet al., 2008). Functional diversity, defined by Tilman (2001) as the “component of biological diversity that can affect the operation of the ecological system or function“ is also equally important to plant ecology. Growing studies on functional diversity in recent years have shown that functional diversity is a key issue in the field of ecological study (Naeem, 2002). However, it is difficult to quantify and evaluate the functional diversity of various ecosystems, because there are numerous and mixed definitions of functional diversity, such as community functional diversity and ecological system functional diversity (Daz and Cabido, 2001; Tesfaye et al., 2003). Recently, some scholars have unified the definition of functional diversity and developed a formula for quantifying functional diversity. Functional dispersion (FDis) represents the mean space of each species weighted by relative abundance to the centroid of all species in the community (Spasojevic et al., 2014). In particular, higher FDis may reflect the coexistence of different functional strategies and increases in niche-complementation among species (Schleicher et al., 2011; Spasojevic et al., 2014). This has stimulated research to assess the functional diversity and its relationship with species diversity in various ecosystems worldwide. In recent years, some researchers have studied the conservation of plant functional diversity in fens (Kotowski, 2013). Others have studied how succession and human-mediated alterations influenced functional diversity in raised bog vegetation. The relationship between species diversity and functional plant diversity in a heavily affected riverine landscape has also been studied. However, very few studies have been conducted on the functional diversity of alpine ecosystems. Therefore, it is imperative to examine the functional diversity and their relationships with species diversity in alpine regions. The QTP, known as the “Roof of the World,” is a typical alpine region, in which alpine grasslands dominate the landscape. The alpine grasslands of the QTP are key biomes and important pools of alpine flora and fauna in the world. The Aerjin Mountain National Nature Reserve (AMNR) is located in the Northwestern QTP, and is one of the largest nature reserves in China, as well as in the world, for protecting endemic species of alpine ecosystems (Dong et al., 2015). The AMNR is inaccessible year round because of harsh environmental conditions and remains one of China's four substantial “No Man's Land” (the other three are Qiangtang, Kekexili, and Luobupo). The AMNR becomes the “Natural Laboratory” geographical, biological, environmental studies (Dong et al., 2015). In the past, some scholars have reported on the fauna and flora, plant diversity, and populations of wild ungulates in the AMNR (Cui and Akov, 1993; Cui and Li, 1998; Xu et al., 2006; Hai and Zeng, 2010; Cai et al., 2013; Wu et al., 2013; Su et al., 2014). However, few scholars have studied the spatial distributions of plant species diversity, biomass, and their driving forces in the AMNR. Therefore, it is imperative to examine the effects of environmental factors on the plant diversity and biomass in an undisturbed alpine desert ecosystem. In addition, numerous scholars have increasingly studied the functional diversity of plant communities in temperate wetlands, forests, and farmlands (Kotowski, 2013, Ma and Herzon,
2. Methods and materials 2.1. Study site The AMNR was located in the southern Kunlun Mountains of the QTP (87°10′18″–91°E, 36°00′ 49″–37°N). It bordered the Changtang and Hohxil National Nature Reserves, two other “no man’s land” nature reserves on the QTP. The AMNR was one of the largest inland nature reserves in the world. The AMNR was 360 km long from east to west, and 190 km wide from north to south, with a total area of 45,000 km2. The elevation of the AMNR ranged from 3748 m to 6948 m (average altitude was approximately 4600 m). The climate was cold, dry, and windy year round with no frost-free period. The annual average air temperature was below 0° and annual precipitation was approximately 300 mm. The dominant soils were alpine steppe soil and alpine desert soil (according to the Chinese Soil Classification System), which are loam and loam-sandy soils, according to the International Soil Classification System. The key vegetation in the AMNR included alpine steppe, alpine desert, alpine wet meadow, alpine cushion vegetation, and alpine sparse vegetation (Cui and Li, 1998). The plants in the AMNR generally grew from May to August with an effective growth period of approximately 120 d (Cui and Akov, 1993). Surrounded by high mountains, the AMNR remained a relatively closed ecological unit for wild alpine flora and fauna protection (Dong et al., 2015). From June to July 2012 and 2013, 19 sampling sites were selected representing different vegetation types (Fig. 1). In each sampling site, following the methods of Hankins (2004), we randomly selected three 30-m radius circular plots. In each plot, three 30-m transect lines were placed at 120° angles (Fig. 2). Along each transect line, three to six 1 m × 1 m quadrats were placed at equal intervals to record plant species, individuals of each species, ground cover, plant height, and biomass. Furthermore, we sampled soils in each plot using soil gauges (3.5-cm diameter) at 0–15-cm soil depth taking three random replicates for chemical analysis in the laboratory. In addition, site inventories, including longitude and latitude, altitude, and slope, among other variables, were recorded using a portable GPS. Because of the shortage of meteorological station data, we estimated precipitation and temperature of the sampling sites using the meteorological model developed by Liu et al. (2014).
2.2. Plant functional diversity traits and species diversity index measurements We chose the habitat types (meadow, steppe, desert), life history (annual, biennial, perennial), flowering time (first flowering in 4–5, 6–8 months), and pollination type (insect, wind, water) as plant functional traits. We chose the FEve index, FDis index, FDp index, MFAD index as functional diversity indices. S−1
FEve =
171
(
1
)
∑b = 1 min PEWb ∙ S − 1 − 1−
1 S−1
1 S−1
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Fig. 1. Key vegetation types and sampling sites in the Aerjin Mountain Nature Reserve.
c = [ci] =
360°
∑ wj x ik ∑ wj
where, wj represents the relative abundance of species j, c represents the orthocenter of the weight, xik represents the values of trait k of species I, zj represents the weighted distance between species j and the orthocenter of the weight c.
Sample lines
N
240°
N
∑i = 1 ∑ j > 1 dij
MFAD =
N
where, Ni represents the individual of species I, N represents all the individuals in the plant community, dij represents the distance between species I and species j. We chose four species diversity indices, Patrick index (R0), Shannon index (H), Pielou index (J), and Simpson index (D) to calculate species diversity of plant communities using the following formulas, respectively:
120°
R0 = S Fig. 2. Placement of sampling transects.
PEWb =
EWb =
H = − ∑ Pi ln Pi
EWb
J = H /ln S
S−1
∑b = 1 EWb
D=1−
dij
Pi = Ni / N
wi + wj
where, Pi is the number of individuals of species i, S is the number of species, Ni is number of individuals of species i, and N is the number of all individuals in the community.
where, S represents species number, wi represents the relative abundance of species i, wi represents the relative abundance of species j, dij represents the distance between species i and species j.
FDis =
∑ Pi2
2.3. Soil chemical analysis
∑ wj zj The fresh soil samples were air-dried to measure soil moisture and soil bulk density. The air-dried soil was ground through 100-mesh sieve
∑ wj 172
Vegetation types The altitude (m)
3.2. Spatial patterns of plant biomass, species diversity, and functional diversity
173
4 5 3 3 1 3 3 3 10 3 4 5 1 5 5 5 6 7 4 3 3 2 2 1 2 3 3 7 2 3 4 1 3 3 3 4 5 3 North of the reserve Northeast of the reserve Northeast of the reserve Northeast of the reserve Northwest of the reserve Northwest of the reserve Southwest of the reserve Southwest of the reserve Southwest of the reserve Southwest of the reserve Northeast of the reserve Northeast of the reserve Northeast of the reserve Southeast of the reserve Southeast of the reserve Middle of the reserve Southeast of the reserve Northeast of the reserve Northeast of the reserve
Longitude (°)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
In the AMNR, the precipitation varied from 71.74 mm in the west to 122.45 mm in the east (Fig. 4a), temperature ranged from 5.05 °C at lower elevation around 3800 m to approximately 7.88 °C at higher altitudes around 5000 m (Fig. 4b). There were no clear spatial patterns for soil factors related to altitudinal, latitudinal, or longitudinal dimensions, with soil moistures ranging from 1.38% to 13.16% (Fig. 4c),
Sampling sites
3.3. Spatial patterns of environment factors
Sample number
Table 1 Spatial variation of plant composition in the Reserve.
Latitude (°)
The aboveground plant biomass in the AMNR varied greatly according to spatial dimensions (altitude, longitude, and latitude), ranging from 116.8 to 1076.7 kg hm−2 (Fig. 3a). There was substantial spatial variation in plant species diversity, as shown by the 3-D modules, with the Patrick index ranging from 1 to 8.7 (Fig. 3b), Shannon index ranging from 0 to 2.6 (Fig. 3c), Simpson index ranging from 0 to 0.8 (Fig. 3d), and Pielou index ranging from 0 to 1.3 (Fig. 3e). Plant functional diversity varied drastically according to spatial dimensions (altitude, longitude, and latitude), with the FEve index ranging from 0 to 0.99 (Fig. 3f), FDis ranging from 0.07 to 1.8 (Fig. 3g), FDp index ranging from 2 to 4.7 (Fig. 3h), and MFAD index ranging from 0.5 to 2.4 (Fig. 3i). There were no liner distribution patterns for the plant biomass, species diversity index, and functional diversity index based on latitudinal, longitudinal, or altitudinal dimensions. The peak values for plant biomass, species diversity, and functional diversity were observed at an elevation of 4500–5000 m in the southwestern region of the Reserve, 3800–4200 m in the northeastern region of the Reserve, and 4200–4500 m in the northwestern region of the AMNR.
3 2 1 1 1 2 2 2 4 1 2 3 1 2 3 2 3 4 2
Family number
The vegetation type and plant composition in the AMNR were presented in Table 1. Alpine steppe, dominated by Stipa purpurea, Thermopsis lupinoides or Festuca ovina, was the most important vegetation in the southwestern and northeastern parts of the AMNR. Alpine desert, dominated by Salsola abrotanoides, was the most important vegetation in the central and southeastern part of the AMNR. Mountain sparse vegetation, dominated by Androsace tapete, was the most important vegetation in the southern and northern edges of the AMNR. Alpine wet meadow, dominated by Kobresia robusta and Carex moorcroftii, was intrazonal vegetation distributed along the riparian areas of the river and lakes in the AMNR.
desert wet meadow desert desert steppe wet meadow steppe steppe vegetation vegetation desert wet meadow desert steppe steppe vegetation steppe steppe steppe
3.1. Plant composition
Alpine Alpine Alpine Alpine Alpine Alpine Alpine Alpine Sparse Sparse Alpine Alpine Alpine Alpine Alpine Sparse Alpine Alpine Alpine
3. Results
3938 3928 3875 3953 4291 4392 4605 4941 4927 4786 3962 3946 3899 4142 4118 4316 4056 3997 3901
Genera number
Specie number
We used Microsoft Excel 2010 to process the original data to obtain sums, means, and standard errors. Using the statistical package F-diversity v. 2011 (Casanoves et al., 2011), we calculated the functional diversity index. We applied OriginPro 9.0 drawing software to diagram 3-dimensional (longitudinal, latitudinal, and altitudinal) distribution patterns of plant biomass, species diversity, and functional diversity, as well as environmental factors, including temperature, precipitation, and soil properties. We used SPSS16.0 to examine the relationships among plant biomass, species diversity, functional diversity, and environmental factors.
N37.84 N37.20 N37.21 N37.20 N37.13 N37.13 N36.83 N36.61 N36.57 N36.71 N37.31 N37.37 N37.27 N36.88 N36.88 N36.87 N36.98 N37.17 N37.27
Dominant plants
2.4. Statistical analysis
E89.54 E90.49 E90.46 E 90.56 E88.59 E87.74 E87.49 E87.03 E89.24 E89.26 E90.39 E90.03 E90.43 E90.20 E90.04 E89.80 E90.24 E90.24 E90.30
for laboratory analysis. We applied the potentiometer method (soil at 2.5:1) to test soil pH. We used the potassium dichromate oxidation method to estimate soil organic carbon content. We used the Kjeldahl method to estimate soil total nitrogen content. We used an elemental analyzer (Vario EI, Elementar, Germany) to measure soil P, K, and Mg, among others.
Salsola abrotanoides, Oxytrops aciphylla Kobresia robusta, Carex moorcroftii Salsola abrotanoides, Carex moorcroftii Salsola abrotanoides, Leymus secalinus Leymus secalinus Carex moorcroftii, Poa festcucaus Leontopodium pusillum, Carex moorcroftii Artemisia nanschanica, Ceratoides compacta Androsace tapete, Poa alpine Androsace tapete, Saxifraga pulvinaria Saxifraga pulvinaria, Salsola abrotanoides Kobresia robusta, Oxytrops aciphylla Salsola abrotanoides Thermopsis lupinoides, Stipa purpurea Stipa purpurea, Oxytrops aciphylla Saussurea gnaphalodes, Potentilla bifurca Stipa purpurea, Leontopodium pusillum Festuca ovina, Stipa purpurea Triglochin maritimum, Poa alpine
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a
b
c
d
e
f
g
h
i
Fig. 3. Three-dimensional distribution patterns of plant biomass, species diversity, and functional diversity.
soil bulk density ranging from 2.97 to 10.1 mg·g−1 (Fig. 4d), soil pH ranging from 7.74 to 8.58 (Fig. 4k), soil organic carbon ranging from 11.77 to 29.76 mg·g−1(Fig. 4f), soil total carbon ranging from 1.19 to 1.69 g·cm−3 (Fig. 4e), soil total nitrogen ranging from 0.29 to 1.24 mg·g−1 (Fig. 4g), soil total phosphorus ranging from 0.396 to 0.765 mg·g−1(Fig. 4h), soil total magnesium ranging from 9.492 to 13.811 mg·g−1 (Fig. 4l), and soil total potassium ranging from 15.16 to 17.92 mg·g−1 (Fig. 4j).
vegetation. Pielou index and Shannon index for swamp meadow were significantly lower than those for other types of vegetation. 3.5. Relationships among plant biomass, species diversity, and functional diversity As shown in Table 2, Patrick index, Shannon index, and FDp index were significantly positively correlated. Pielou index and Shannon index were significantly positively correlated. Shannon index, Simpson index, and FDp index were significantly positively correlated. Plant biomass and species diversity were not correlated, as well as plant biomass and species diversity. Species diversity and functional diversity were positively correlated.
3.4. Plant biomass, species diversity, and functional diversity in different types of vegetation According to the variance analysis, there was significant variation of plant biomass, species diversity, and functional diversity across different types of the vegetation: alpine desert, swamp meadow, alpine steppe, alpine meadow, and mountain sparse vegetation (Fig. 5). The plant biomass index, MFAD index, FDp index, FEve index, FDis index, Patrick index, and Simpson index were slightly different across types of
3.6. Relationships between plant biomass and species diversity, functional diversity, and environmental factors As shown in Table 3, aboveground biomass was significantly 174
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a
b
c
d
e
f
g
h
j
i
k Fig. 4. Three-dimensional distribution patterns of environmental factors.
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Fig. 5. Differences of species biomass, diversity and function diversity across different types of vegetation.
Conservation of higher plant diversity may maintain higher N-use efficiency in sandy grassland ecosystems (Zuo et al., 2016). Worldwide studies indicated that plant species diversity decreased with increasing latitude and altitude or exhibited “inflation” at midlevel altitudes. However, we did not detect changes in plant species diversity along the latitudinal, longitudinal, or altitudinal gradients in the AMNR on the QTP of China. Our findings supported previous researchers who found that environmental factors and constraints, such as soil salinity, water, nutrient availability, and human disturbance, are more important in the occurrence and distribution of plants (Mahdavi and Bergmeier, 2016). Some studies conducted in neighboring areas of the AMNR on the QTP found that the plant diversity in the alpine plant communities increased with increasing longitude and decreased with increasing altitude (Yang et al., 2004), or exhibited “inflation” at midlevel altitudes (Wang et al., 2004). The difference between these studies and our study may be attributed to two major factors: 1) the area of the AMNR is relatively small, resulting in less heterogeneity in the habitats for the differentiation of plant community structure and composition (Wang et al., 2001); 2) the climatic and soil factors did not show regular changes along the latitudinal, longitudinal, and altitude gradients, which could therefore not contribute to the differentiation of plant biomass, species diversity, and functional diversity in latitudinal, longitudinal, and altitudinal dimensions. However, there were substantial differences in plant biomass, species diversity, and functional diversity among different types of vegetation in the AMNR, and uninformed distribution patterns in plant biomass, species diversity, and functional diversity in 3-D spatial dimensions of latitude, longitude, and altitude. This information may provide a scientific basis for the sustainable management of the AMNR. According to previous research (Whittaker et al., 2001; Willis and Whittaker, 2002; Yang et al., 2004), species distribution patterns are the result of different ecological processes regulated by both biotic
Table 2 Correlation between species diversity, function diversity and plant biomass. f1 Patrick index (f1) Pielou index (f2) Shannon index (f3) Simpson index (f4) FEve index (f5) FDis index (f6) FDp index (f7) MFAD index (f8) Plant biomass (f9)
1
f2 0.56 1
f3
f4 *
0.89 0.87* 1
0.54 0.82 0.89* 1
f5
f6
0.15 0.13 0.22 0.34 1
0.36 0.21 0.18 0.52 0.31 1
f7 *
0.88 0.43 0.89* 0.72 0.54 0.62 1
f8
f9
0.14 0.31 0.26 0.34 0.43 0.21 0.14 1
0.15 0.28 0.16 0.34 0.17 0.29 0.37 0.11 1
influenced by soil moisture and precipitation. Patrick index and Shannon index were significantly affected by precipitation. Pielou index was significantly affected by temperature. Simpson index was significantly influenced by temperature and soil potassium. MFAD was significantly affected by soil total carbon. FDp was significantly affected by soil total nitrogen and precipitation. FEve was significantly affected by soil total carbon. FDis was significantly influenced by soil moisture and temperature.
4. Discussion Plant biomass is a key determinant of ecosystem structure and function (Zhou et al., 2010; Li et al., 2012). Biodiversity, one of the top issues in plant ecology (Troumbis, 2001; Wardle, 2001), is the foundation of stable ecosystem structure and function (Loreau, 2000; Loreau et al., 2001). It has been previously concluded that higher functional diversity of ecosystem was associated with higher productivity (Tilman et al., 1997), and stronger resilience (Nystrom and Folke, 2001) and resistance (Prieur-Richard and Lavorel, 2000; Dukes, 2001). Table 3 Correlations between plant biomass and environmental factors.
Biomass on the groun (f1) Soil potassium (f2) Soil magnesium (f3) Soil phosphorus (f4) Soil total nitrogen (f5) Soil organic carbon (f6) Soil total carbon (f7) Soil bulk density (f8) Soil moisture contents (f9) Precipitation (f10) Temperature (f11) Soil pH (f12)
f1
f2
f3
f4
f5
f6
f7
f8
f9
f10
f11
f12
1.000
0.077 1.000
0.025 0.482 1.000
0.070 0.488 0.230 1.000
−0.055 0.558 −0.042 0.435 1.000
0.078 0.533 −0.034 0.083 0.799 1.000
−0.436 0.180 0.107 −0.088 0.502 0.543 1.000
−0.258 −0.105 0.098 −0.202 −0.121 −0.298 0.196 1.000
0.379 0.387 0.186 0.342 0.387 0.406 −0.077 −0.298 1.000
0.311 −0.152 0.044 0.369 −0.054 −0.072 −0.233 −0.297 0.510 1.000
0.081 0.550 0.514 0.537 0.145 0.127 −0.026 −0.262 0.666 0.430 1.000
−0.117 −0.136 −0.048 −0.166 −0.054 0.002 −0.011 0.152 0.166 0.349 0.096 1.000
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Wang, C.T., Cao, G.M., Wang, Q.L., et al., 2007. Changes of plant species composition and biomass of alpine meadow along the environmental gradient on Qinghai-Tibetan Plateau. Sci. China (C): Life Sci. 37 (5), 585–594. Wang, C.T., Wang, Q.J., Long, R.J., Jing, Z.C., Shi, H.L., 2004. Changes in plant species diversity and productivity along an elevation gradient in an alpine meadow. Acta Phytoecologica Sinica 28 (2), 240–245. Wu, Y., Zhang, X.F., Dong, S.K., Liu, S.L., Zhang, X., Su, X.K., Wang, X.X., Li, Y.Y., 2013. Species composition, diversity, and biomass of representative plant communities in eastern Aerjin Mountain Nature Reserve, Northwest China. Chinese J. Ecol. 32 (9), 2250–2256. Xin, X.P., Wang, Z.L., Yang, G.X., Li, X.L., 2004. Community structure organization and its relation with environmental factors of sown grassland in South China. Chinese J. Appl. Ecol. 15 (6), 963–968. Xu, J., Zhang, B.P., Zhu, Y.H., Sun, R.H., 2006. Distribution and geological analysis of altitudinal belt in the Altun Qilian Mountains. Geographical Res. 25 (6), 977–984. Yang, Y.H., Rao, S., Hu, H.F., Chen, A.P., Ji, C.J., Zhu, B., Zuo, W.Y., Li, X.R., Shen, H.H., Wang, Z.H., Tang, Y.H., Fang, J.Y., 2004. Plant species richness of alpine grasslands in relation to environmental factors and biomass on the Tibetan Plateau. Biodiv Sci. 12 (1), 200–205. Zhou, G.Y., Chen, G.C., Xu, W.H., et al., 2010. Influence of enclosure to Achnatherum splendens steppes biomass in the Qinghai Lake area. Arid Land Geogr. 33 (3), 434–441. Zuo, X.Y., Zhang, J., Lv, P., et al., 2016. Plant functional diversity mediates the effects of vegetation and soil properties on community-level plant nitrogen use in the restoration of semiarid sandy grassland. Ecol. Indic. 64, 272–280.
4.1. Conclusion and suggestion We can state that plant biomass, species diversity, and functional diversity in the wide region of the QTP are commonly affected by climatic and soil factors. Protecting plant diversity and functional diversity is imperative to enhancing primary production of the plant community in alpine ecosystems of the AMNR and the entire QTP. Acknowledgements The authors acknowledge financial support from the National Key R &D Program of China (2016YFC0501906) and the State Key Joint Laboratory of Environmental Simulation and Pollution Control (Beijing Normal University) (17L03ESP). Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.ecoleng.2018.10.027. References Brown, J.H., Lomolino, M.V., 1998. Biogeography, 2nd Ed. Sinauer Associates, Inc. Publishers, Sunderland, Massachusetts. Cadotte, M., Cavender-Bares, J., Tilman, D., Oakley, T., 2009. Using phyla genetic, functional and trait diversity to understand patterns of plant community productivity. PLoS One 4, e5695. Cai, X.B., Qi, C., Liu, L.Y., Jiang, X.B., Buzao, L.M., 2013. Preliminary investigation on wetland resources in Aerjin Mountain National Nature Reserves of Xinjiang. Protection Forest Sci. Technol. 23 (12), 77–80. Casanoves, F., Pla, L., Di Rienzo, J.A., Díaz, S., 2011. FDiversity: a software package for the integrated analysis of functional diversity. Methods Ecol. Evol. 2, 233–237. Cui, D.F., Li, X.S., 1998. The plant species diversity in Aerjin Mountain Nature Reserve. J. Shihezi Univ. (Nat. Sci. Ed.) 2 (4), 281–288. Cui, N.R., Akov, P., 1993. The composition and characteristics of Flora in Aerjin Mountain Nature Reserve. J. Xinjiang Normal Univ. (Nat. Sci. Ed.) 12 (1), 47–53. Daz, S., Cabido, M., 2001. Vive la difference: plant functional diversity matters to ecosystem processes. Trends Ecol. Evol. 16 (11), 646–655. Dukes, J.S., 2001. Biodiversity and invisibility in grassland micro cosmos. Oecologia 126 (4), 563–568. Dong, S.K., Zhang, X., Liu, S.L., Shi, J.B., Li, X.W., 2015. Ecological Monitoring and Integrated Management of Aerjin Mountain National Nature Reserve. China Environmental Press, Beijing. Gaston, K.J., 2000. Global patterns in biodiversity. Nature 405, 220–226. Gentry, A.H., 1988. Changes in plant community diversity and floristic composition on environmental and geographical gradients. Ann. Missouri Botanical Garden 75, 1–34. Hai, Y., Zeng, Y.J., 2010. Study on the flora of seed plants in Aerjin National Nature Reserve. J. Xinjiang Normal Univ. (Nat. Sci. Ed.) 29 (2), 1–6. Kotowski, W., 2013. Conservation management in fens: do large tracked mowers impact functional plant diversity? Biol. Conserv. 167, 292–297. Li, B., 1993. Basic Ecology. Inner Mongolia University Press, Huhhot. Li, L.J., Zeng, D.H., 2008. Research progress on the relationships between species diversity and ecosystem function. Chinese J. Ecol. 27, 2010–2017. Li, Y.Y., Dong, S.K., Li, X.Y., Wen, L., 2012. Effect of enclosure on vegetation photosynthesis and biomass of degraded grasslands in headwater area of Qinghai-Tibetan Plateau. Acta Agrestia Sinica 20 (4), 621–625. Liu, S.L., Zhao, H.D., Dong, S.K., Su, X.K., Liu, Q., Deng, L., Zhang, X., 2014. Dynamic of Vegetation in the Altun Mountain Nature Reserve based on SPOT NDVI. Arid Zone Res. 31 (5), 832–837. Loreau, M., Naeem, S., Inchausti, P., Bengtsson, J., Grime, J.P., Hector, A., Hooper, D.U., Huston, M.A., Raffaelli, D., Schmid, B., Tilman, D., Wardle, D.A., 2001. Biodiversity
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The impacts of geographic, soil and climatic factors on plant diversity, biomass and their relationships of the alpine dry ecosystems: Cases from the Aerjin Mountain Nature Reserve, China
T
⁎
Dong Shi-kuia, , Sha Weia, Su Xu-kunb, Zhang Yongc, LI Shuaia, Gao Xiaoxaia, Liu Shi-lianga, Shi Jian-bina, Liu Quan-rud, Hao Yana a
School of Environment, Beijing Normal University, Beijing 100857, China Research Center for Eco-Environment, Chinese Academy of Sciences, Beijing 100085, China Collge of Wetland, Southwest Forestry University, Kunming 650224, China d School of Life, Beijing Normal University, Beijing 100875, China b c
A R T I C LE I N FO
A B S T R A C T
Keywords: Alpine Desert Nature Reserve Plant species diversity Plant functional diversity Plant biomass Impacting factors
Spatial patterns of plant species diversity, functional diversity, and aboveground plant biomass, and their relationships with environmental factors in the Aerjin Mountain Nature Reserve (AMNR) on the Qinghai-Tibetan Plateau, China were examined in this study. The transect-quadrat sampling method was applied to sample the plant species and functional diversity and the aboveground plant biomass. Statistical package F-diversity v. 2011 was used to calculate the functional diversity index. OriginPro 9.0 drawing software was used to diagram 3dimensional (longitudinal, latitudinal, and altitudinal) distribution patterns of plant diversity, plant biomass and environmental factors. Correlations among plant biomass, species diversity, functional diversity, and environmental factors were analyzed by using SPSS16.0. The results indicated that alpine steppe was the major vegetation type in high-altitude areas of the southwestern region of the AMNR, alpine wet meadow and alpine steppe were the major vegetation types in low altitude areas of the northeastern region of the AMNR. The vegetation types in mid-altitude areas of the northwestern region and low altitude areas of the southeastern region of the AMNR were primarily alpine desert. Plant species diversity and biomass did not vary significantly along latitudinal, longitudinal, and altitudinal gradients. Plant species diversity was positively correlated with soil total nitrogen, total carbon, organic carbon, and moisture. The functional diversity of the plant community was positively correlated with precipitation and soil moisture. Vegetation biomass was positively correlated with soil total nitrogen, organic carbon, and soil moisture, whereas it was negatively correlated with soil bulk density. Plant species diversity was positively correlated with the functional diversity of the plant community. The integrated effects of geographic factors, soil factors, and meteorological conditions contributed to the spatial heterogeneity of species biodiversity and vegetation biomass of the plant communities in the AMNR, whereas the effects of soil and climatic factors were much stronger than those of geographical factors.
1. Introduction Plant composition and diversity are the most important factors that determine plant community structure and type, development level, and habitat differences (Wang et al., 2005). The study of plant-community species composition, diversity, and primary productivity is the basis for understanding plant community features (Wang et al., 2012). Plant community, a unit of association, may change spatially and temporally (Li, 1993). Some researchers reported from global and regional studies that plant species diversity exhibited obvious changes because of
⁎
latitudinal and altitudinal dimensions (Gentry, 1988; Malyshev et al., 1994; Gaston, 2000); more specifically, plant diversity decreased with increasing latitude or altitude (Brown and Lomolino, 1998), or exhibited higher “inflation” at mid-level latitude and altitude (Whittaker, 1960). The changes of plant species diversity along geographical gradients and their causes have become key issues in the fields of biodiversity research (Yang et al., 2004). Spatial changes in plant species diversity may be mainly associated with environmental factors, such as temperature, humidity, soil nutrients, and solar radiation (Yang et al., 2004; Xin et al., 2004). In
Corresponding author. E-mail address: [email protected] (S.-k. Dong).
https://doi.org/10.1016/j.ecoleng.2018.10.027 Received 26 May 2018; Received in revised form 28 October 2018; Accepted 31 October 2018 0925-8574/ © 2018 Elsevier B.V. All rights reserved.
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2014, Palombo, 2016), whereas few scholars have studied the functional diversity of alpine ecosystems. Therefore, the objectives of our study were to: 1) identify the spatial patterns of plant species diversity, functional diversity, and biomass of the undisturbed alpine ecosystems; 2) understand the effects of environmental factors on plant species diversity, functional diversity, and biomass; and 3) clarify the relationships between plant species diversity, functional diversity, and biomass in the alpine ecosystems. The findings of this study could provide a sound basis for scientifically managing the alpine parks and protected areas, such as the AMNR, to maintain their ecosystem functions of biodiversity conservation and primary production.
alpine grassland ecosystems (mostly alpine meadow and alpine steppe), the dominant ecosystems on the Qinghai-Tibetan Plateau (QTP), most scholars have focused on the study of plant species diversity, functional group diversity, and their relationships with plant biomass and environmental factors. They have drawn different conclusions. Plant species diversity of the alpine grasslands increased with the increasing latitude and longitude, decreased with increasing altitude (Yang et al., 2004), or exhibited “inflation” at the mid-level altitude (Wang et al., 2005). The dynamics of alpine plant diversity with altitude and latitude may be mainly related to growing season, precipitation, the warmness index, and plant biomass (Yang et al., 2004). Both species diversity and functional diversity are very important factors for evaluating ecosystem functions (Petchey and Gaston, 2006; Li and Zeng, 2008); in other words, ecosystem functions are dependent not only on the number of species, but also on species composition and functions of traits (Diaz et al., 2001; Cadotteet al., 2009; Mokanyet al., 2008). Functional diversity, defined by Tilman (2001) as the “component of biological diversity that can affect the operation of the ecological system or function“ is also equally important to plant ecology. Growing studies on functional diversity in recent years have shown that functional diversity is a key issue in the field of ecological study (Naeem, 2002). However, it is difficult to quantify and evaluate the functional diversity of various ecosystems, because there are numerous and mixed definitions of functional diversity, such as community functional diversity and ecological system functional diversity (Daz and Cabido, 2001; Tesfaye et al., 2003). Recently, some scholars have unified the definition of functional diversity and developed a formula for quantifying functional diversity. Functional dispersion (FDis) represents the mean space of each species weighted by relative abundance to the centroid of all species in the community (Spasojevic et al., 2014). In particular, higher FDis may reflect the coexistence of different functional strategies and increases in niche-complementation among species (Schleicher et al., 2011; Spasojevic et al., 2014). This has stimulated research to assess the functional diversity and its relationship with species diversity in various ecosystems worldwide. In recent years, some researchers have studied the conservation of plant functional diversity in fens (Kotowski, 2013). Others have studied how succession and human-mediated alterations influenced functional diversity in raised bog vegetation. The relationship between species diversity and functional plant diversity in a heavily affected riverine landscape has also been studied. However, very few studies have been conducted on the functional diversity of alpine ecosystems. Therefore, it is imperative to examine the functional diversity and their relationships with species diversity in alpine regions. The QTP, known as the “Roof of the World,” is a typical alpine region, in which alpine grasslands dominate the landscape. The alpine grasslands of the QTP are key biomes and important pools of alpine flora and fauna in the world. The Aerjin Mountain National Nature Reserve (AMNR) is located in the Northwestern QTP, and is one of the largest nature reserves in China, as well as in the world, for protecting endemic species of alpine ecosystems (Dong et al., 2015). The AMNR is inaccessible year round because of harsh environmental conditions and remains one of China's four substantial “No Man's Land” (the other three are Qiangtang, Kekexili, and Luobupo). The AMNR becomes the “Natural Laboratory” geographical, biological, environmental studies (Dong et al., 2015). In the past, some scholars have reported on the fauna and flora, plant diversity, and populations of wild ungulates in the AMNR (Cui and Akov, 1993; Cui and Li, 1998; Xu et al., 2006; Hai and Zeng, 2010; Cai et al., 2013; Wu et al., 2013; Su et al., 2014). However, few scholars have studied the spatial distributions of plant species diversity, biomass, and their driving forces in the AMNR. Therefore, it is imperative to examine the effects of environmental factors on the plant diversity and biomass in an undisturbed alpine desert ecosystem. In addition, numerous scholars have increasingly studied the functional diversity of plant communities in temperate wetlands, forests, and farmlands (Kotowski, 2013, Ma and Herzon,
2. Methods and materials 2.1. Study site The AMNR was located in the southern Kunlun Mountains of the QTP (87°10′18″–91°E, 36°00′ 49″–37°N). It bordered the Changtang and Hohxil National Nature Reserves, two other “no man’s land” nature reserves on the QTP. The AMNR was one of the largest inland nature reserves in the world. The AMNR was 360 km long from east to west, and 190 km wide from north to south, with a total area of 45,000 km2. The elevation of the AMNR ranged from 3748 m to 6948 m (average altitude was approximately 4600 m). The climate was cold, dry, and windy year round with no frost-free period. The annual average air temperature was below 0° and annual precipitation was approximately 300 mm. The dominant soils were alpine steppe soil and alpine desert soil (according to the Chinese Soil Classification System), which are loam and loam-sandy soils, according to the International Soil Classification System. The key vegetation in the AMNR included alpine steppe, alpine desert, alpine wet meadow, alpine cushion vegetation, and alpine sparse vegetation (Cui and Li, 1998). The plants in the AMNR generally grew from May to August with an effective growth period of approximately 120 d (Cui and Akov, 1993). Surrounded by high mountains, the AMNR remained a relatively closed ecological unit for wild alpine flora and fauna protection (Dong et al., 2015). From June to July 2012 and 2013, 19 sampling sites were selected representing different vegetation types (Fig. 1). In each sampling site, following the methods of Hankins (2004), we randomly selected three 30-m radius circular plots. In each plot, three 30-m transect lines were placed at 120° angles (Fig. 2). Along each transect line, three to six 1 m × 1 m quadrats were placed at equal intervals to record plant species, individuals of each species, ground cover, plant height, and biomass. Furthermore, we sampled soils in each plot using soil gauges (3.5-cm diameter) at 0–15-cm soil depth taking three random replicates for chemical analysis in the laboratory. In addition, site inventories, including longitude and latitude, altitude, and slope, among other variables, were recorded using a portable GPS. Because of the shortage of meteorological station data, we estimated precipitation and temperature of the sampling sites using the meteorological model developed by Liu et al. (2014).
2.2. Plant functional diversity traits and species diversity index measurements We chose the habitat types (meadow, steppe, desert), life history (annual, biennial, perennial), flowering time (first flowering in 4–5, 6–8 months), and pollination type (insect, wind, water) as plant functional traits. We chose the FEve index, FDis index, FDp index, MFAD index as functional diversity indices. S−1
FEve =
171
(
1
)
∑b = 1 min PEWb ∙ S − 1 − 1−
1 S−1
1 S−1
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Fig. 1. Key vegetation types and sampling sites in the Aerjin Mountain Nature Reserve.
c = [ci] =
360°
∑ wj x ik ∑ wj
where, wj represents the relative abundance of species j, c represents the orthocenter of the weight, xik represents the values of trait k of species I, zj represents the weighted distance between species j and the orthocenter of the weight c.
Sample lines
N
240°
N
∑i = 1 ∑ j > 1 dij
MFAD =
N
where, Ni represents the individual of species I, N represents all the individuals in the plant community, dij represents the distance between species I and species j. We chose four species diversity indices, Patrick index (R0), Shannon index (H), Pielou index (J), and Simpson index (D) to calculate species diversity of plant communities using the following formulas, respectively:
120°
R0 = S Fig. 2. Placement of sampling transects.
PEWb =
EWb =
H = − ∑ Pi ln Pi
EWb
J = H /ln S
S−1
∑b = 1 EWb
D=1−
dij
Pi = Ni / N
wi + wj
where, Pi is the number of individuals of species i, S is the number of species, Ni is number of individuals of species i, and N is the number of all individuals in the community.
where, S represents species number, wi represents the relative abundance of species i, wi represents the relative abundance of species j, dij represents the distance between species i and species j.
FDis =
∑ Pi2
2.3. Soil chemical analysis
∑ wj zj The fresh soil samples were air-dried to measure soil moisture and soil bulk density. The air-dried soil was ground through 100-mesh sieve
∑ wj 172
Vegetation types The altitude (m)
3.2. Spatial patterns of plant biomass, species diversity, and functional diversity
173
4 5 3 3 1 3 3 3 10 3 4 5 1 5 5 5 6 7 4 3 3 2 2 1 2 3 3 7 2 3 4 1 3 3 3 4 5 3 North of the reserve Northeast of the reserve Northeast of the reserve Northeast of the reserve Northwest of the reserve Northwest of the reserve Southwest of the reserve Southwest of the reserve Southwest of the reserve Southwest of the reserve Northeast of the reserve Northeast of the reserve Northeast of the reserve Southeast of the reserve Southeast of the reserve Middle of the reserve Southeast of the reserve Northeast of the reserve Northeast of the reserve
Longitude (°)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
In the AMNR, the precipitation varied from 71.74 mm in the west to 122.45 mm in the east (Fig. 4a), temperature ranged from 5.05 °C at lower elevation around 3800 m to approximately 7.88 °C at higher altitudes around 5000 m (Fig. 4b). There were no clear spatial patterns for soil factors related to altitudinal, latitudinal, or longitudinal dimensions, with soil moistures ranging from 1.38% to 13.16% (Fig. 4c),
Sampling sites
3.3. Spatial patterns of environment factors
Sample number
Table 1 Spatial variation of plant composition in the Reserve.
Latitude (°)
The aboveground plant biomass in the AMNR varied greatly according to spatial dimensions (altitude, longitude, and latitude), ranging from 116.8 to 1076.7 kg hm−2 (Fig. 3a). There was substantial spatial variation in plant species diversity, as shown by the 3-D modules, with the Patrick index ranging from 1 to 8.7 (Fig. 3b), Shannon index ranging from 0 to 2.6 (Fig. 3c), Simpson index ranging from 0 to 0.8 (Fig. 3d), and Pielou index ranging from 0 to 1.3 (Fig. 3e). Plant functional diversity varied drastically according to spatial dimensions (altitude, longitude, and latitude), with the FEve index ranging from 0 to 0.99 (Fig. 3f), FDis ranging from 0.07 to 1.8 (Fig. 3g), FDp index ranging from 2 to 4.7 (Fig. 3h), and MFAD index ranging from 0.5 to 2.4 (Fig. 3i). There were no liner distribution patterns for the plant biomass, species diversity index, and functional diversity index based on latitudinal, longitudinal, or altitudinal dimensions. The peak values for plant biomass, species diversity, and functional diversity were observed at an elevation of 4500–5000 m in the southwestern region of the Reserve, 3800–4200 m in the northeastern region of the Reserve, and 4200–4500 m in the northwestern region of the AMNR.
3 2 1 1 1 2 2 2 4 1 2 3 1 2 3 2 3 4 2
Family number
The vegetation type and plant composition in the AMNR were presented in Table 1. Alpine steppe, dominated by Stipa purpurea, Thermopsis lupinoides or Festuca ovina, was the most important vegetation in the southwestern and northeastern parts of the AMNR. Alpine desert, dominated by Salsola abrotanoides, was the most important vegetation in the central and southeastern part of the AMNR. Mountain sparse vegetation, dominated by Androsace tapete, was the most important vegetation in the southern and northern edges of the AMNR. Alpine wet meadow, dominated by Kobresia robusta and Carex moorcroftii, was intrazonal vegetation distributed along the riparian areas of the river and lakes in the AMNR.
desert wet meadow desert desert steppe wet meadow steppe steppe vegetation vegetation desert wet meadow desert steppe steppe vegetation steppe steppe steppe
3.1. Plant composition
Alpine Alpine Alpine Alpine Alpine Alpine Alpine Alpine Sparse Sparse Alpine Alpine Alpine Alpine Alpine Sparse Alpine Alpine Alpine
3. Results
3938 3928 3875 3953 4291 4392 4605 4941 4927 4786 3962 3946 3899 4142 4118 4316 4056 3997 3901
Genera number
Specie number
We used Microsoft Excel 2010 to process the original data to obtain sums, means, and standard errors. Using the statistical package F-diversity v. 2011 (Casanoves et al., 2011), we calculated the functional diversity index. We applied OriginPro 9.0 drawing software to diagram 3-dimensional (longitudinal, latitudinal, and altitudinal) distribution patterns of plant biomass, species diversity, and functional diversity, as well as environmental factors, including temperature, precipitation, and soil properties. We used SPSS16.0 to examine the relationships among plant biomass, species diversity, functional diversity, and environmental factors.
N37.84 N37.20 N37.21 N37.20 N37.13 N37.13 N36.83 N36.61 N36.57 N36.71 N37.31 N37.37 N37.27 N36.88 N36.88 N36.87 N36.98 N37.17 N37.27
Dominant plants
2.4. Statistical analysis
E89.54 E90.49 E90.46 E 90.56 E88.59 E87.74 E87.49 E87.03 E89.24 E89.26 E90.39 E90.03 E90.43 E90.20 E90.04 E89.80 E90.24 E90.24 E90.30
for laboratory analysis. We applied the potentiometer method (soil at 2.5:1) to test soil pH. We used the potassium dichromate oxidation method to estimate soil organic carbon content. We used the Kjeldahl method to estimate soil total nitrogen content. We used an elemental analyzer (Vario EI, Elementar, Germany) to measure soil P, K, and Mg, among others.
Salsola abrotanoides, Oxytrops aciphylla Kobresia robusta, Carex moorcroftii Salsola abrotanoides, Carex moorcroftii Salsola abrotanoides, Leymus secalinus Leymus secalinus Carex moorcroftii, Poa festcucaus Leontopodium pusillum, Carex moorcroftii Artemisia nanschanica, Ceratoides compacta Androsace tapete, Poa alpine Androsace tapete, Saxifraga pulvinaria Saxifraga pulvinaria, Salsola abrotanoides Kobresia robusta, Oxytrops aciphylla Salsola abrotanoides Thermopsis lupinoides, Stipa purpurea Stipa purpurea, Oxytrops aciphylla Saussurea gnaphalodes, Potentilla bifurca Stipa purpurea, Leontopodium pusillum Festuca ovina, Stipa purpurea Triglochin maritimum, Poa alpine
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a
b
c
d
e
f
g
h
i
Fig. 3. Three-dimensional distribution patterns of plant biomass, species diversity, and functional diversity.
soil bulk density ranging from 2.97 to 10.1 mg·g−1 (Fig. 4d), soil pH ranging from 7.74 to 8.58 (Fig. 4k), soil organic carbon ranging from 11.77 to 29.76 mg·g−1(Fig. 4f), soil total carbon ranging from 1.19 to 1.69 g·cm−3 (Fig. 4e), soil total nitrogen ranging from 0.29 to 1.24 mg·g−1 (Fig. 4g), soil total phosphorus ranging from 0.396 to 0.765 mg·g−1(Fig. 4h), soil total magnesium ranging from 9.492 to 13.811 mg·g−1 (Fig. 4l), and soil total potassium ranging from 15.16 to 17.92 mg·g−1 (Fig. 4j).
vegetation. Pielou index and Shannon index for swamp meadow were significantly lower than those for other types of vegetation. 3.5. Relationships among plant biomass, species diversity, and functional diversity As shown in Table 2, Patrick index, Shannon index, and FDp index were significantly positively correlated. Pielou index and Shannon index were significantly positively correlated. Shannon index, Simpson index, and FDp index were significantly positively correlated. Plant biomass and species diversity were not correlated, as well as plant biomass and species diversity. Species diversity and functional diversity were positively correlated.
3.4. Plant biomass, species diversity, and functional diversity in different types of vegetation According to the variance analysis, there was significant variation of plant biomass, species diversity, and functional diversity across different types of the vegetation: alpine desert, swamp meadow, alpine steppe, alpine meadow, and mountain sparse vegetation (Fig. 5). The plant biomass index, MFAD index, FDp index, FEve index, FDis index, Patrick index, and Simpson index were slightly different across types of
3.6. Relationships between plant biomass and species diversity, functional diversity, and environmental factors As shown in Table 3, aboveground biomass was significantly 174
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a
b
c
d
e
f
g
h
j
i
k Fig. 4. Three-dimensional distribution patterns of environmental factors.
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Fig. 5. Differences of species biomass, diversity and function diversity across different types of vegetation.
Conservation of higher plant diversity may maintain higher N-use efficiency in sandy grassland ecosystems (Zuo et al., 2016). Worldwide studies indicated that plant species diversity decreased with increasing latitude and altitude or exhibited “inflation” at midlevel altitudes. However, we did not detect changes in plant species diversity along the latitudinal, longitudinal, or altitudinal gradients in the AMNR on the QTP of China. Our findings supported previous researchers who found that environmental factors and constraints, such as soil salinity, water, nutrient availability, and human disturbance, are more important in the occurrence and distribution of plants (Mahdavi and Bergmeier, 2016). Some studies conducted in neighboring areas of the AMNR on the QTP found that the plant diversity in the alpine plant communities increased with increasing longitude and decreased with increasing altitude (Yang et al., 2004), or exhibited “inflation” at midlevel altitudes (Wang et al., 2004). The difference between these studies and our study may be attributed to two major factors: 1) the area of the AMNR is relatively small, resulting in less heterogeneity in the habitats for the differentiation of plant community structure and composition (Wang et al., 2001); 2) the climatic and soil factors did not show regular changes along the latitudinal, longitudinal, and altitude gradients, which could therefore not contribute to the differentiation of plant biomass, species diversity, and functional diversity in latitudinal, longitudinal, and altitudinal dimensions. However, there were substantial differences in plant biomass, species diversity, and functional diversity among different types of vegetation in the AMNR, and uninformed distribution patterns in plant biomass, species diversity, and functional diversity in 3-D spatial dimensions of latitude, longitude, and altitude. This information may provide a scientific basis for the sustainable management of the AMNR. According to previous research (Whittaker et al., 2001; Willis and Whittaker, 2002; Yang et al., 2004), species distribution patterns are the result of different ecological processes regulated by both biotic
Table 2 Correlation between species diversity, function diversity and plant biomass. f1 Patrick index (f1) Pielou index (f2) Shannon index (f3) Simpson index (f4) FEve index (f5) FDis index (f6) FDp index (f7) MFAD index (f8) Plant biomass (f9)
1
f2 0.56 1
f3
f4 *
0.89 0.87* 1
0.54 0.82 0.89* 1
f5
f6
0.15 0.13 0.22 0.34 1
0.36 0.21 0.18 0.52 0.31 1
f7 *
0.88 0.43 0.89* 0.72 0.54 0.62 1
f8
f9
0.14 0.31 0.26 0.34 0.43 0.21 0.14 1
0.15 0.28 0.16 0.34 0.17 0.29 0.37 0.11 1
influenced by soil moisture and precipitation. Patrick index and Shannon index were significantly affected by precipitation. Pielou index was significantly affected by temperature. Simpson index was significantly influenced by temperature and soil potassium. MFAD was significantly affected by soil total carbon. FDp was significantly affected by soil total nitrogen and precipitation. FEve was significantly affected by soil total carbon. FDis was significantly influenced by soil moisture and temperature.
4. Discussion Plant biomass is a key determinant of ecosystem structure and function (Zhou et al., 2010; Li et al., 2012). Biodiversity, one of the top issues in plant ecology (Troumbis, 2001; Wardle, 2001), is the foundation of stable ecosystem structure and function (Loreau, 2000; Loreau et al., 2001). It has been previously concluded that higher functional diversity of ecosystem was associated with higher productivity (Tilman et al., 1997), and stronger resilience (Nystrom and Folke, 2001) and resistance (Prieur-Richard and Lavorel, 2000; Dukes, 2001). Table 3 Correlations between plant biomass and environmental factors.
Biomass on the groun (f1) Soil potassium (f2) Soil magnesium (f3) Soil phosphorus (f4) Soil total nitrogen (f5) Soil organic carbon (f6) Soil total carbon (f7) Soil bulk density (f8) Soil moisture contents (f9) Precipitation (f10) Temperature (f11) Soil pH (f12)
f1
f2
f3
f4
f5
f6
f7
f8
f9
f10
f11
f12
1.000
0.077 1.000
0.025 0.482 1.000
0.070 0.488 0.230 1.000
−0.055 0.558 −0.042 0.435 1.000
0.078 0.533 −0.034 0.083 0.799 1.000
−0.436 0.180 0.107 −0.088 0.502 0.543 1.000
−0.258 −0.105 0.098 −0.202 −0.121 −0.298 0.196 1.000
0.379 0.387 0.186 0.342 0.387 0.406 −0.077 −0.298 1.000
0.311 −0.152 0.044 0.369 −0.054 −0.072 −0.233 −0.297 0.510 1.000
0.081 0.550 0.514 0.537 0.145 0.127 −0.026 −0.262 0.666 0.430 1.000
−0.117 −0.136 −0.048 −0.166 −0.054 0.002 −0.011 0.152 0.166 0.349 0.096 1.000
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factors (including evolution of plant species, species competition, and grazing, among others) and abiotic factors (such as geography, geology, climate, and soil, among others). This viewpoint can be further supported by the positive relationships between precipitation and plant biomass, species diversity, and functional diversity observed in this study, as well as others (Wu et al., 2013) in the AMNR. The positive relationships between plant biomass and species diversity, and soil organic carbon and soil total nitrogen in this study were consistent with the previous findings in the neighboring areas on the QTP (Yang et al., 2004; Wang et al., 2007).
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