J. Plant Biol. (2016) 59:357-367 DOI 10.1007/s12374-015-0503-0
ORIGINAL ARTICLE
Environmental Factors and Underlying Mechanisms of Tree Community Assemblages of Pine-oak Mixed Forests in the Qinling Mountains, China Zongzheng Chai, Defang Fan and Dexiang Wang College of Forestry, Northwest A & F University, Yangling 712100, China Received: October 24, 2015 / Accepted: April 12, 2016 © Korean Society of Plant Biologists 2016
Abstract Understanding the mechanisms of assembly of tree communities is very important for restoring and managing pine-oak mixed forests in the Qinling Mountains, China, but the essential mechanisms remain largely unexplored. The objective of this research was to uncover the underlying mechanisms of species coexistence and to identify the key environmental factors influencing the tree community assemblages in these forests. We investigated tree species and 15 environmental factors of topography, soil properties, and stand development of pine-oak mixed forests at an elevation of 1000-2000 m a.s.l. in the Qinling Mountains. Six classical models for the distribution of species abundance were used to fit the observed distributions; a clustering analysis was conducted to divide the ecological species groups, and a redundancy analysis examined the relationship between species assemblages and various environmental factors. Zipf-Mandelbrot, neutral-theory, log-normal, and Zipf models performed well in fitting the patterns of species-abundance distribution in the pine-oak mixed forests, which was related to the complexity of the community structure of the forests. A special combination of the Zipf-Mandelbrot and neutral-theory models, however, best explained the mechanism of species coexistence for the forests and indicated that these forests were progressive successional communities able to maintain stable development during succession. In addition, multiple factors controlled the tree community assemblage of pine-oak mixed forests in the mountainous regions, although available potassium, slope aspect, average tree DBH, and slope position were significant environmental variables. Keywords: Community ordination, Ecological species groups, Neutral-theory, Species abundance distribution, Species coexistence *Corresponding author; Dexiang Wang Tel : +86-029-8708-0202 E-mail :
[email protected];
[email protected]
Introduction Assemblages of vegetation are complex units with many interrelated processes at various levels of biological organization (Zavala et al. 2004). The niche and neutral theories propose alternative mechanisms for explaining the long-term coexistence of ecological communities (Pigolotti et al. 2013). The distribution of species abundance is an essential tool that is being increasingly used to analyze the mechanisms of community assemblages, to evaluate models of diversity maintenance and community structure, and to infer community properties (Connolly et al. 2012). Pine-oak mixed forests and mosaic forests of pure stands of pine and oak are widely distributed worldwide and can adapt to a wide variety of site and soil conditions (Broncano et al. 1998; Albert 2007; Bieng et al. 2013). Understanding the forces shaping ecological communities and promoting species coexistence in pine-oak mixed forests during succession and development is important for the management and protection of these forests. Plant community assemblages are closely linked to environmental factors (Hejcman et al. 2010; Lin et al. 2013; Liu et al. 2012). Factors such as climate (Gomez-Mendoza et al. 2007), topography, soil (Jacqmain et al. 1999; Washburn et al. 2003), fire (Gilliam et al. 1999; Park 2001), anthropogenic disturbance (Hong et al. 1995; Parshall et al. 2003; Wolf 2005), and competition (Paluch et al. 2004; Puerta-Pinero et al. 2007) can affect the community assemblage of pine-oak mixed forests to different extents. Evidence for the influence of ecological factors on species diversity and community structure of the forests has accumulated over the years, and habitat heterogeneity has always been considered an important aspect at small spatial scales (Paudel et al. 2014). Historically, the forests in the Qingling Mountains have experienced varying levels of human activity, and much of the area is now covered by secondary growth (Chai and Wang 2016a). Approximately 25% of the Qinling Mountains in China are covered by pine-oak mixed forests (Pinus
358
J. Plant Biol. (2016) 59:357-367
tabuliformis Carr., P. armandii Franch., and Quercus aliena var. acutiserrata Maxim.), which are the prominent forest communities (Liu et al. 2001; Zhang et al. 2012; Yu et al. 2013) that play important roles in establishing and maintaining ecosystems and their functions, such as the conservation of soil and water. The species composition and the structure and function of the forests, though, have remained largely unexplored, and more information is needed for effective conservation and protection. In the present study, we attempt to elucidate the underlying mechanisms of species coexistence and the relationships between species coexistence and various environmental factors of topography, soil properties, and stand development in pine-oak mixed forests at an elevation of 1000-2000 m
a.s.l. in the Qinling Mountains, China. Six classical models of species abundance distribution (SAD) were used to fit the observed distributions. A clustering analysis (CA) was conducted to divide the ecological species groups, and a redundancy analysis (RDA) examined the relationship between species assemblages and various environmental factors. We addressed the following questions: how are tree communities of pine-oak mixed forests assembled, and what environmental factors are responsible for these species assemblages?
Results Species Composition and Species Accumulation Curves (SACs)
Table 1. Environment variables of topography, soil property and stand development analyzed Environmental factor
Variable
Abbreviation
Range
Topography
Elevation (m) Slope position Slope aspect Slope gradient (%)
Soil property
Total nitrogen (g kg−1) Total phosphorus (g kg−1) Total potassium (g kg−1) Organic matter (g kg−1) pH Available nitrogen (mg kg−1) Available phosphorus (mg kg−1) Available potassium (mg kg−1)
Ele SLP Asp SLG TN TP TK OM pH AN AP AK
1020-1999 1-3 1-8 22-98 0.05-0.32 0.02-0.19 1.08-2.65 1.66-8.51 4.90-6.80 12.95-45.17 2.00-7.83 42.52-241.89
Stand development
Base area (m2) Average tree DBH (cm) Average tree height (m)
BA AD AH
0.389-2.390 9.330-20.770 8.290-19.580
Table 2. Six main species abundance distribution models Model
Equation
Reference
S
N 1 aˆ r = ---- ∑ --S k= rk
Broken-stick
(1)
MacArthur (1957)
Niche-preemption
r –1 aˆ r = Nα(1 – a)
(2)
Motomura (1932)
Log-normal
aˆ r = exp[log(u) + log(σ )Φ]
(3)
Preston (1948)
Zipf
γ aˆ r = Npˆ 1r
(4)
Zipf-Mandelbrot
γ aˆ r = Nc(r + β)
(5)
Neutral-theory
J! Γ( γ ) Γ( n + y) Γ( J – n + γ – y ) φ n = θ--------------------- -----------------∫ ----------------- ------------------------------exp(–yθ ⁄ γ )dy n!(J – n)! Γ(J + γ) Γ( 1 + y) Γ(γ – y)
Frontier (1987)
γ
(6)
Hubbell (2001)
0
Note: aˆ r is the expected abundance of species at rank r, S is the number of species, N is the number of individuals, φ is a standard normal function, pˆ 1 is the estimated proportion of the most abundant species, and α, σ, γ, β and c are the estimated parameters in each model. In neutral-the-
m( J – 1) e which is equal to (z-1)!, for integer z and γ = ------------------ , θ is fundamental diversity number, m is migration rate 1–m
∞ z – 1 –t
ory model, where Γ(z) = ∫ t 0
J. Plant Biol. (2016) 59:357-367
359
Table 3. Identification number (ID) and importance value index of the tree species of the pine-oak mixed forests in the Qinling Mountains, China ID
Family
Species
T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 T12 T13 T14 T15 T16 T17 T18 T19 T20 T21 T22 T23 T24
Fagaceae Pinaceae Pinaceae Anacardiaceae Fagaceae Cornaceae Fagaceae Betulaceae Fagaceae Betulaceae Juglandaceae Betulaceae Pinaceae Simaroubaceae Lauraceae Tiliaceae Aceraceae Cornaceae Lauraceae Anacardiaceae Pinaceae Pinaceae Leguminosae Betulaceae
Quercus aliena var. acutiserrata Maxim. 29.45±0.177 25.731±0.1000 Pinus tabulaeformis Carr. 25.457±0.1440 29.486±0.1200 Pinus armandii Franch. 12.134±0.1790 16.631±0.1600 Toxicodendron vernicifluum (Stokes) F. A. Barkl. 4.971±0.048 8.993±0.050 Quercus acutissima Carr. 5.747±0.090 0.854±0.018 Swida macrophylla (Wall.) Sojak 4.668±0.054 0.163±0.005 Quercus variabilis Blume 4.982±0.158 0.161±0.005 Betula albo-sinensis Burk. 2.581±0.057 Quercus serrata var. brevipetiolata (A.DC.) Nakai 0.343±0.011 Carpinus turczaninowii Hance 000.6±0.013 2.702±0.029 Juglans cathayensis Dode 1.557±0.026 1.295±0.032 Carpinus cordata Bl. 2.101±0.037 0.192±0.006 Tsuga chinensis (Franch.) Pritz. Picrasma quassioides (D. Don) Benn. 1.067±0.034 1.789±0.038 Litsea pungens Hemsl. 0.706±0.015 0.625±0.014 00.15±0.005 0.135±0.004 Tilia tuan Szyszyl. Acer davidii Franch. 1.889±0.027 Bothrocaryum controversum (Hemsl.) Pojark. 0.226±0.007 0.222±0.007 Lindera obtusiloba Bl. 0.941±0.030 Rhus potaninii Maxim. 0.504±0.016 0.574±0.012 Larix principis-rupprechtii Mayr. 1.136±0.036 Pinus bungeana Zucc.et Endi 0.992±0.021 Dalbergia hupeana Hance 1.095±0.025 0.292±0.009 Corylus ferox Wall. 0.491±0.011 Dendrobenthamia japonica var. chinensis(Osborn) 00.76±0.016 Fang Platycarya strobilacea Sieb. et Zucc. 00.96±0.016 Sorbus hupehensis Schneid. 0.669±0.015 Albizia julibrissin Durazz. 0.343±0.011 0.148±0.005 Cornus officinalis Sieb. et Zucc. 00.28±0.009 0.176±0.006 Acer mono Maxim. 0.531±0.011 Cerasus clarofolia (Schneid.) Yü et Li 0.402±0.013 Acer palmatum Thunb. 0.512±0.011 Quercus aliena Blume 0.163±0.005 0.136±0.004 Malus kansuensis (Batal.) Schneid. 0.478±0.010 Alangium chinense (Lour.) Harms Salix taiwanalpina Kimura 00.24±0.008 Betula platyphylla Suk. 0.237±0.007 Acer grosseri Pax 0.181±0.006 Quercus spinosa David ex Franchet 0.152±0.005 Populus simonii Carr. -
T25 Cornaceae T26 T27 T28 T29 T30 T31 T32 T33 T34 T35 T36 T37 T38 T39 T40
Juglandaceae Rosaceae Leguminosae Cornaceae Acer Rosaceae Aceraceae Fagaceae Rosaceae Alangiaceae Salicaceae Betulaceae Acer Fagaceae Salicaceae
Lower Ele
Middle Ele
Higher Ele
Total
28.065±0.0580 22.449±0.2060 22.831±0.1920 8.447±0.048 1.216±0.020 1.728±0.044 3.527±0.112 0.396±0.013 0.414±0.013 0.945±0.020 3.004±0.079 1.309±0.022 1.505±0.039 0.267±0.008 1.398±0.024 0.702±0.015 0.204±0.006 0.255±0.008 0.703±0.015
28.489±0.121 026.45±0.161 17.535±0.178 07.798±0.051 01.964±0.052 01.797±0.032 01.689±0.09 01.351±0.04 001.26±0.064 01.081±0.019 01.043±0.024 01.033±0.024 00.927±0.043 00.904±0.028 00.888±0.017 000.59±0.022 00.574±0.014 00.535±0.013 00.506±0.019 00.435±0.012 00.361±0.02 00.36±0.012 00.349±0.012 00.338±0.009
0.183±0.006
0.283±0.009
0.29±0.009 0.161±0.005
0.193±0.006 0.141±0.006 0.138±0.006 0.137±0.005 0.125±0.005 0.121±0.007 0.119±0.005 0.086±0.003 0.082±0.003 0.075±0.004 0.067±0.004 0.066±0.004 0.041±0.002 0.037±0.002 0.034±0.002
Lower Ele, Middle Ele, Higher Ele, and Total represent the low (1000-1400 m), middle (1400-1700 m), high (1700-2000 m), and total (1000-2000 m) elevation zones, respectively.
A total of 1595 individuals (DBH≥5 cm) belonging to 40 tree species (28 genera and 14 families) were recorded from the 30 plots (Table 3). The lower elevation zone contained 25 species (18 genera and 12 families), the middle elevation zone contained 31 species (22 genera and 13 families), and the higher elevation zone contained 22 species (18 genera
and 11 families) tree species. Twelve species (12 genera and 10 families) were common to all three elevation zones. The families with the largest number of species in the study area were Fagaceae (N=6, 15.00%), Pinaceae (N=5, 12.50%), Betulaceae (N=5, 12.50%), Aceraceae (N=4, 10.00%), and Cornaceae (N=4, 10.00%). Q. aliena var. acutiserrata Maxim.,
360
J. Plant Biol. (2016) 59:357-367
Fig. 1. The location of the Qingling Mountains in China, and the red point represent studied forest region (A), and the distribution of the 30 sample plots of pine-oak mixed forests, and the black squares represent multiple sample plots (B).
Fig. 2. Species accumulation curve in pine-oak mixed forests in the Qinling Mountains, China. The dark blue line is the average species accumulation curve, the shaded light blue areas represent the distributional interval of the standard deviations from 100 random permutations of the data, and the box plots represent the distribution of the species accumulation curve from 100 random permutations of the data.
P. tabulaeformis Carr., P. armandii Franch., and T. vernicifluum (Stokes) F. A. Barkl. had the highest importance values and were the predominant species in the pine-oak mixed forests in the Qinling Mountains. In addition, the computed SAC approached an asymptotic value within the 30 plots, which suggests adequate sampling within the study region (Fig. 2).
mixed forests, together with the distributions fitted by the six classical models (broken-stick, niche-preemption, log-normal, Zipf, Zipf-Mandelbrot, and neutral-theory), are shown in Fig. 2. The effects of the simulations were tested by the AIC, BIC, and K-S tests (Table 4). Simulation effects conformed, whether total tree community (elevation range: 1000-2000 m; Fig. 3D) or the three elevation subintervals (1000-1400, 1400-1700, and 1700-2000 m; Fig. 3A-C) of pine-oak mixed forests in the Qinling Mountains, the Zipf-Mandelbrot, neutral-theory, Zipf, and log-normal models simulated SAD well. The Zipf-Mandelbrot and neutraltheory models were much superior to the other models. The observed SAD departed from the outputs of the nichepreemption and broken-stick models (Fig. 3B-D; Table 4). The Zipf-Mandelbrot, neutral-theory, Zipf, and log-normal models may thus be applied for simulating SAD patterns for pine-oak mixed forests in the Qinling Mountains, but the ZipfMandelbrot and neutral-theory models fit the data best. Division of Ecological Species Groups For a more intuitive description of species assemblage in pine-oak mixed forests, we performed a Pearson correlation analysis of the tree species-abundance database with a data matrix of 40 tree species and 30 plots. Fig. 4 shows the matrix of the Pearson correction coefficients. We used the correlation coefficient as a sign of species similarity and then used the complete method to classify four species assemblages or ecological groups (Table 5).
Species Abundance Distribution (SAD) The observed SAD of the tree communities of the pine-oak
Environmental Influences on the Assemblages of Tree Community
J. Plant Biol. (2016) 59:357-367
361
Table 4. Goodness of fit of six models of the pine-oak mixed forests in the Qinling Mountains θ
m
Testing
Neutral
Broken-stick
Lower
5.483
0.875
AIC BIC K-S
157.520 177.962 0.145
368.742 368.740 000.320
175.014 176.232 000.240
Middle
6.961
1.000
AIC BIC K-S
178.320 181.188 0.161
556.020 556.020 000.387*
Higher
4.479
1.000
AIC BIC K-S
171.620 173.808 0.227
Total
8.172
0.432
AIC BIC K-S
346.270 349.645 0.183
Elevation
Niche-preemption Log-normal
Zipf
Zipf-Mandelbrot
108.818 111.256 0.080
116.664 119.102 0.200
102.881 106.538 0.080
271.797 273.231 000.355*
212.481 215.349 0.129
212.997 215.845 0.258
168.196 172.498 0.129
370.070 370.070 000.409*
145.871 146.962 000.227
150.447 152.629 0.136
180.674 182.856 0.318
121.565 124.839 0.091
1709.160 1709.160 0000.375**
829.172 830.861 000.350*
398.618 401.995 0.150
382.752 386.129 0.225
323.299 328.366 0.125
Lower, Middle, Higher and Total represent the low (1000-1400 m), middle (1400-1700 m), high (1700-2000 m), and total (1000-2000 m) altitude zones, respectively. θ and m are parameters of the neutral-theory model; ***, P
