Download stxb201307271960 Diversity and distribution of ground bryophytes

stxb201307271960
Diversity and distribution of ground bryophytes in broadleaved forests in
Mabian Dafengding National Nature Reserve, Sichuan, China
Yanbin Jianga, Xuehua Liub, Shanshan Songa, Zhong Yuc, Xiaoming Shaoa, 
a College
b
of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
School of Environmental Science and Engineering, Tsinghua University, Beijing 100084, China
cMabian
Dafengding National Nature Reserve, Leshan 614600, China
Abstract: Bryophytes, represented by mosses, liverworts, and hornworts, contribute substantially
to forest ecosystems in terms of nutrient cycling, water retention, water availability, plant biomass, and
plant community maintenance. Forests provide numerous types of habitat for bryophytes, especially the
ground floor. To clarify the ground bryophyte diversity and distribution in broadleaved forests, we used
microcoenose sampling to investigate ground bryophytes in 34 sample plots (10 × 10 m) in the Mabian
Dafengding National Nature Reserve (MDNR), Sichuan Province. Species diversity and environmental
factor relationships were analyzed by using α and β diversity indexes, as well as Pearson’s correlation
analysis. Detrended canonical correspondence analysis (DCCA) was applied to analyze the relationships
between species distribution and environmental factors. A total of 230 bryophyte species were identified
in MDNR. These species include 67 liverwort species belonging to 26 genera of 20 families and 163
moss species belonging to 65 genera of 28 families. Diversity of ground bryophytes was negatively
correlated to shrub cover, canopy cover, and tree number, but without significant correlations to altitude,
slope, aspect, vegetation type, and herb cover. The DCCA ordination of relationships between ground
bryophytes and environmental factors showed that altitude, aspect, vegetation type, and shrub cover
were important to the distribution of dominant ground bryophyte species. This study quantitatively
related bryophytes diversity and distribution to environmental factors, which is helpful in understanding
the ecological niche of various bryophytes.
Keywords: ground bryophytes; species diversity; distribution; forest; environment
 Corresponding author.
E-mail address: [email protected] (X. Shao)
1
1. Introduction
Bryophytes, with a variety of ecological communities, are widely distributed globally. Ground
bryophytes are those that grow in the substrate of floor soil. Ground bryophytes form a dominant
ecological group in the forest ecosystems and also serve an important function in forest ecosystems in
such processes as the carbon and nitrogen cycles
[1–3].
For example, in a boreal forest, ground
bryophytes serve as the primary carbon sink over woods and are main contributors to carbon
equilibrium [3, 4].
Broadleaved forest is a typical and widely distributed vegetation type in China that provides
various suitable environments and substrates for bryophytes. Thus, the distribution of ground
bryophytes in the forest is influenced by forest cover (light intensity), stands, composition, and structure
[5–9].
Human activities, such as deforestation and reforestation, have changed the forest, consequently
influencing the diversity, abundance, and distribution of ground bryophytes
[10, 11].
Additional,
macroclimatic factors such as rainfall and temperature, site factors such as topography and understory
vascular, as well as substrate characteristics such as soil moisture and pH, probably induce certain
effects
[7–9, 12–15].
Nature reserve, especially with humid environment, is an important area of
biodiversity conservation and is a vital ecological region that preserves a large amount of ground
bryophytes. The habitat heterogeneity of ground bryophytes is relatively high in broadleaved forests [6, 8].
Thus, ground bryophyte diversity and distribution must be clarified to aid in the conservation of
bryophytes and their habitat. In this study, we illustrate the relationships of the diversity and distribution
of bryophytes with environmental factors by analyzing ground bryophytes of different environment
regimes through correlation and ordination analyses.
2. Methods
2.1. Study area
This study was conducted in the Mabian Dafengding National Nature Reserve (MDNR) (28°26′28°47′N, 103°13′-103°25′E). MDNR is located in the southwest of Mabian Yi Autonomous County,
Sichuan Province and covers an area of 36 000 hm2, with altitude ranging from 800 m to 4042 m a.s.l..
The altitude difference of more than 3000 m causes the temperatures to be significantly distinct in this
region. At 1500 m a.s.l., the annual mean temperature is 14 °C to 15 °C, with 3 °C to 4 °C in the coldest
month of January and 22 °C to 24 °C in the hottest month of July. In areas above 3800 m a.s.l. (close to
the summit of MDNR), the annual mean temperature is -2 °C to 0 °C , and the minimum extreme
temperature is lower than -30 °C. Summer does not occur throughout the year, spring and autumn are
short (approximately 60 d), and winter is long (approximately 300 d), thus resulting in a cold temperate
climate. The annual precipitation in the study area is 1 739.2 mm, reaching the maximum (more than
2000 mm) between 2000 and 2100 m a.s.l.. Similar to climate, soil types and vegetation are vertically
2
Table 1 Summary of sample plots in MDNR
Sample
Number of
Longitude
Latitude
Altitude
Canopy cover
Shrub cover
Herb cover
Slope
Aspect
M1
103.3295
28.4924
1553
0.80
0.05
0.92
30
350
3
M2
103.3300
28.4925
1516
0.80
0.10
0.50
40
250
5
M3
103.3314
28.4954
1518
0.40
0.12
0.60
45
295
3
M4
103.3326
28.4958
1554
0.70
0.15
0.64
30
20
4
M5
103.3372
28.4985
1523
0.50
0.45
0.55
25
295
5
M6
103.3370
28.4990
1524
0.70
0.10
1
17
345
4
M7
103.3419
28.5011
1436
0.85
0.20
0.83
35
20
5
M8
103.3410
28.5020
1462
0.80
0.15
0.20
33
30
4
M9
103.3481
28.5745
1434
0.65
0.13
0.45
30
82
4
M10
103.3475
28.5749
1424
0.35
0.12
0.74
28
18
2
M11
103.3460
28.5751
1495
0.60
0.25
0.25
20
270
5
M12
103.3529
28.5755
1339
0.40
0.06
0.70
35
188
2
M13
103.3506
28.5757
1358
0.60
0.100
0.50
32
192
3
M14
103.3495
28.5782
1549
0.55
0.19
0.61
40
250
4
M15
103.3483
28.5790
1464
0.78
0.1
0.28
20
205
2
M16
103.3473
28.5794
1409
0.75
0.14
0.45
28
280
4
M17
103.3462
28.5820
1375
0.30
0.09
0.72
5
252
2
M18
103.3447
28.5841
1464
0.40
0.07
0.50
40
70
4
M19
103.3431
28.5848
1464
0.64
0.14
0.78
45
30
4
M20
103.3387
28.5877
1489
0.42
0.08
0.81
34
180
4
M21
103.3379
28.5914
1619
0.30
0.03
0.71
5
70
2
M22
103.3364
28.5938
1696
0.45
0.18
0.60
35
210
3
M23
103.3783
28.6827
1794
0.60
0.85
0.02
40
165
3
M24
103.3760
28.6831
1924
0.30
0.65
0.38
25
170
1
M25
103.3640
28.6846
1812
0.70
0.16
0.48
5
168
1
M26
103.3684
28.6852
1921
0.12
0.04
0.65
25
110
1
M27
103.3682
28.6859
1951
0.60
0.55
0.30
27.5
195
3
M28
103.3675
28.6884
1979
0.20
0.38
0.47
27
150
1
M29
103.3584
28.6887
2110
0.30
0.95
0.01
45
200
1
M30
103.3598
28.6904
2203
0.80
0.85
0.27
32
246
1
M31
103.3615
28.6915
2113
0.60
0.12
0.70
32
264
2
M32
103.3595
28.6920
2221
0.80
0.90
0.01
45
80
4
M33
103.363
28.6926
2040
0.30
0.60
0.27
20
210
1
M34
103.365
28.6927
2034
0.40
0.01
0.48
22
187
3
plot
trees
distributed from the bottom to the top. Below 2200 m a.s.l., the soil type is mountainous yellow soil and
dominated by tropical evergreen broadleaved forest. Between 1800 and 2400 m a.s.l., the soil type is
mountainous yellow brown soil and dominated by evergreen and deciduous broadleaved mixed forest.
Between 2400 and 2800 m a.s.l., the soil type is mountainous dark brown soil, and corresponding
vegetation is coniferous and broadleaved mixed forest. Between 2800 and 3500 m a.s.l., the soil type is
mountainous dark brown coniferous forest soil, vegetated by dark coniferous fir forest. Above 3500 m
3
a.s.l., the soil type is mountain meadow soil, vegetated by subalpine shrub and meadow [16].
2.2. Field sampling
For different broadleaved forest types, several sample sites were surveyed along an altitude
gradient from 1300 m to 2300 m in MDNR. Within each site, the community features of trees, shrubs,
and herbs, were measured in a 10 × 10 m sample plot. These features included cover, height, and
abundance. Thirty-four sample plots were investigated. At the four corners of each sample plot, shrubs
and herbs were investigated in quadrates of 3 × 3 m and 1 × 1 m individually. The covers of canopies,
shrubs, and herbs were measured by visual estimation, as well as tree height. Other vascular community
features, including height and abundance, were recorded by measuring and counting. For ground
bryophytes, microcoenose sampling method
[17]
was employed (sampling with the 50 × 50 cm quadrate
at the center of the largest fragment in each of 25 2 × 2m grids) to measure species cover. Unequal
quadrates (two to 25) were sampled in the 34 plots. We also recorded the geographic locations and
topographic factors of the plots. These parameters include longitude, latitude, altitude, slope, and aspect.
Soil pH and moisture were not measured in this study for two reasons. First, previous studies showed
that soil pH does not influence the bryophytes diversity and growth of the same vegetation type in one
certain region
[7].
Second, rainfall is adequate in the study area, and the understory is rather humid.
Table 1 shows the detailed environmental information of each sample plot. We collected all bryophyte
specimens and identified them according to the literature in the laboratory. Some suspected specimens
were identified by native bryologists. All the specimens were stored in BAU.
2.3. Data analysis
Frequency = (quadrates of bryophytes presence / total investigated quadrates) / 100%
Importance value = (relative cover + relative frequency) / 2
We defined dominant family as a family of five or more bryophyte species and dominant species as
species with an importance value higher than 0.5. Dominant species were used to clarify the
relationships between distribution and environmental factors.
Species diversity involving α-diversity and β-diversity was analyzed. Three α-diversity indexes,
namely, Patrick index, Shannon–Wiener index, and Pielous evenness index, as well as two β-diversity
indexes, namely, Sφrenson index and modified Morisita–Horn index, were employed. All these indexes
were calculated using BIO-DAP software.
Patrick index: D = S
Shannon–Wiener index:
S
D = − ∑(Pi lnPi )
i=1
Pielous index:
4
E=
H
ln⁡(S)
Sφrenson index:
β=1−
2𝑐
𝑎+𝑏
Modified Morisita–Horn index:
β = 2∑
ani ∙ bni
(da + db)aN ∙ bN
S is the total species richness recorded in the study area. Pi = Ni/N, where Ni is the relative cover of
species i, and N is the sum of the relative covers of S species. a and b are the species richness values in
the two communities, and c is the common species between the two communities. aN is the species
richness of plot A, whereas bN is the species richness of plot B. ani and bni are the abundance values of i
species in plots A and B, respectively. da = ∑ an2i /aN 2, and db = ∑ bn2i /bN 2.
Pearson’s correlation was used to test the relationships between species diversity and
environmental factors in SPSS 19.0 software. Except for dividing sample plots into groups subjectively
according to altitude and forest types, we used principal components analysis (PCA) to analyze the
inter-correlations of sample plots relating to altitude, slope, aspect, vegetation type, canopy cover, tree
numbers, as well as shrub and herb cover of each sample plot. Species distribution and environmental
relationships were characterized by detrended canonical correspondence analysis (DCCA). Both PCA
and DCCA were executed in software CANOCO for Windows 4.5, and CANODRAW was used to draw
the two-dimensional ordination graphs of species and environmental factors.
In the PCA graph, the sample plots are scattered or clustered along environments. The first and
second axes represent the first and second principal components, respectively, and are strongly related
to environmental factors. The distance between a plot and an ordination axis indicates the correlation
between the plot and axis or one or several environmental factors. The quadrant in which the sample
plot is located can indicate a positive or negative correlation between plot and axis. Sample plots can
possibly be divided into groups according to their clusters. In the DCCA graph, the arrows represent
environmental factors, the length of arrows indicates the correlations of species distribution and
environmental factors, the slope of arrows shows the relationships between environmental factors and
ordination axis, and the quadrant in which a sample is plot located illustrates a positive or negative
correlation between a plot and an axis. In addition, the distance between a species and a plot represents
their relationship; a small distance indicates high relative abundance of the species in the plot. The
distances among different species indicate the degrees of distribution divergence. The optimal
conditions of different species relative to a quantitative environmental factor can also be determined
according to the locations of species projected at the arrow of the environmental factor in the DCCA
graph.
5
3. Results
3.1. Diversity of ground bryophytes under broadleaved forest in MDNR
We identified 230 ground bryophyte species by conducting survey on 34 sample plots in MDNR.
We found 67 liverworts belonging to 20 families and 26 genera, as all as 163 mosses belonging to 28
families and 65 genera.
Table 1 displays the dominant bryophyte families. The dominant liverwort families include
Lophocoleaceae, Plagiochilaceae, Porellaceae, Calypogeiaceae, Radulaceae, and Lepidoziaceae. The
species richness of the six dominant families was 62.7% of the total liverworts, and the coverage was
76.0% of the total population. Among these dominant families, species richness from Lophocoleaceae,
Plagiochilaceae, and Porellaceae were relatively greater than that of other families. Species richness of
genus Heteroscyphus and Chiloscyphus from Lophocoleaceae were high at 4 and 6, respectively, similar
to genus Plagiochila from Plagiochilaceae and genus Porella from Porellaceae, which had species
richness of 8 and 7, respectively.
Fourteen dominant moss families were found in the 34 sample plots in MDNR: Brachytheciaceae,
Mniaceae, Plagiotheciaceae, Hypnaceae, Thuidiaceae, and so on. The species richness of the 14
dominant families of mosses was 86.5% of the total moss species, and coverage was 86.5% of the total.
Species richness of these families was more than 10, and coverage was higher than 10%.
Table 2 Dominant families of ground bryophytes in MDNR
Liverworts
No.
Mosses
Family
Genus
Species
Cover (%)
Family
Genus
Species
Cover (%)
Lophocoleaceae
2
10
16.3
Brachytheciaceae
6
28
56.3
2
Plagiochilaceae
2
9
10.6
Mniaceae
4
18
38.8
3
Porellacea
1
7
1.6
Plagiotheciaceae
1
14
37.2
4
Lepidoziaceae
2
6
15.2
Fissidentaceae
1
10
8.5
5
Radulaceae
1
5
3.8
Thuidiaceae
4
9
26.9
6
Calypogeiaceae
2
5
2.0
Hypnaceae
4
9
11.4
7
Polytrichaceae
3
8
11.5
8
Neckeraceae
3
7
11.2
9
Bryaceae
3
7
10.8
10
Pottiaceae
6
7
5.1
11
Dicranaceae
3
6
8.0
12
Sematophyllaceae
3
6
8.7
13
Meteoriaceae
6
6
4.8
14
Hylocomiaceae
2
6
2.2
Total
10
42
49.5
Total
49
141
241.4
Percentage (%)
38.5
62.7
76.0
Percentage (%)
75.4
86.5
89.4
6
Tables 2 and 3 show that the mosses are more dominant than the liverworts in terms of species
richness and cover. For example, for six of the most dominant families, 88 species were found in the
moss families, but only 42 were found in liverworts, and the coverage of these mosses was 179.1%, four
times that of the liverworts at 49.5%. For 52 species with an importance value higher than 0.5, only four
species were from liverworts, and their total coverage was 19.6%, significantly less than that of mosses
at 183.2%. Table 3 also shows that Thuidium cymbifolium, Plagiothecium euryphyllum, Plagiomnium
rhynchophorum, and Eurhynchium savatieri were the dominant species in the sampled sites. All these
dominant species were creeping growth mosses that occurred in most of the plots with relatively high
average covers. The results illustrated that the understory habitats in the broadleaved forest were
suitable for these creeping bryophytes. Liverworts were present in most sample plots, but the frequency
and cover were relatively lower than those of mosses. The four dominant liverwort species were
Heteroscyphus coalitus, Heteroscyphus argutus, Plagiochila ovalifolia, and Conocephalum conicum.
3.2. α- and β-diversity of ground bryophytes in different broadleaved forest types in MDNR
The vertical distribution of vegetation in MDNR is apparent, but human disturbance has caused the
irregular distribution of some forest types. Thus, to characterize α- and β-diversity of ground bryophytes
in different forest types, we divided the 34 sample plots into groups based on altitude and forest types
and then compared the diversity indexes. Table 4 shows the six forest types based on the subjective
grouping.
Through α-diversity analysis, the corresponding value of species diversity differed when using
different indexes. The Patrick index showed that species richness in six broadleaved forests in MDNR
varied from 46 to 104. The Shannon–Wiener and Pielous indexes consider species coverage, such that
the differences in α-diversity among the six forest types were negligible. Shannon–Wiener index values
ranged from 3.19 to 3.84, whereas Pielous index values were almost the same at 0.82 or 0.83. The
Pielous index revealed that the evenness features of individual ground bryophytes under the six forest
types were similar. Within the six forest types, V6 had the highest α-diversity, with 104 species and a
Shannon–Wiener index of 3.84. This result may indicate that Davidia involucrate forest is suitable for
the growth of various bryophytes. However, the Davidia involucrate forest was the most frequently
investigated type (eight sample plots), which may have affected the result. However, this effect was
uncertain, because seven sample plots were also investigated for V3, the Patrick value of which was
only 71, lower than that for V1 (including five sample plots with Patrick 93). Moreover, V1 and V2
included the same number of sample plots, but the species richness in V2 was 30 less than that in V1
(Figure 1).
7
Table 3 Dominant ground bryophyte species in MDNR
No.
Species
Frequency (%)
S1
Thuidium cymbifolium
61.8
Coverage (%)
22.6
Importance value
5.063
S2
Plagiothecium euryphyllum
41.2
17.0
3.662
S3
Plagiomnium rhynchophorum
35.3
12.3
2.795
S4
Eurhynchium savatieri
14.7
12.8
2.314
S5
Eurhynchium laxirete
32.4
6.8
1.904
S6
Thuidium pristocalyx
32.4
6.5
1.851
S7
Homaliodendron crassinervium
11.8
9.9
1.804
S8
Claopodium aciculum
23.5
7.5
1.762
S9
Plagiothecium formosicum
20.6
7.4
1.673
S10
Heteroscyphus coalitus
29.4
5.6
1.643
S11
Leucobryum juniperoideum
38.2
3.0
1.500
S12
Mnium spinosum
5.9
8.9
1.489
S13
Heteroscyphus argutus
17.6
6.5
1.452
S14
Bryhnia trichomitria
11.8
7.4
1.431
S15
Eurhynchium kirishimense
20.6
5.7
1.410
S16
Plagiochila ovalifolia
23.5
5.0
1.386
S17
Dicranum scoparium
23.5
4.9
1.377
S18
Rhizomnium punctatum
14.7
5.7
1.253
S19
Bryum capillare
17.6
4.7
1.181
S20
Hookeria acutifolia
35.3
1.3
1.166
S21
Atrichum undulatum var. gracilisetum
11.8
5.6
1.155
S22
Plagiothecium cavifolium var. fallax
20.6
3.9
1.144
S23
Rhynchostegium contractum
8.8
6.0
1.131
S24
Bryhnia serricuspis
20.6
3.7
1.117
S25
Conocephalum conicum
26.5
2.5
1.098
S26
Hypopterygium flavolimbatum
23.5
3.0
1.092
S27
Mnium lycopodioides
14.7
4.6
1.091
S28
Taxiphyllum subarcuatum
11.8
4.8
1.037
S29
Plagiomnium succulentum
14.7
4.1
1.021
S30
Fissidens anomalus
17.6
3.1
0.944
S31
Atrichum subserratum
20.6
2.4
0.919
S32
Barbella spiculata
11.8
3.9
0.905
S33
Plagiothecium nemorale
20.6
2.2
0.889
S34
Mnium thomsonii
14.7
3.2
0.876
S35
Mnium laevinerve
17.6
2.6
0.869
S36
Brotherella henonii
14.7
2.9
0.833
S37
Aneura pinguis
8.8
3.7
0.794
S38
Heteroscyphus zollingeri
17.6
2.1
0.791
S39
Bryum salakense
14.7
2.5
0.771
S40
Wijkia deflexifolia
8.8
3.4
0.750
S41
Taxiphyllum cuspidifolium
11.8
2.9
0.748
S42
Plagiochila sciophila
11.8
2.8
0.739
S43
Fauriella tenuis
14.7
2.2
0.732
S44
Fissidens involutus
20.6
0.9
0.700
S45
Plagiothecium succulentum
17.6
1.2
0.664
S46
Eurhynchium eustegium
8.8
2.7
0.641
S47
Neodolichomitra yunnanensis
11.8
2.1
0.638
S48
Plagiothecium cavifolium
5.9
3.2
0.635
S49
Duthiella flaccida
5.9
3.1
0.621
S50
Conocephalum japonicum
8.8
2.5
0.614
S51
Trichostomum tenuirostre
14.7
1.3
0.596
S52
Brotherella falcata
14.7
1.1
0.565
8
Table 4 Vegetation types of sampling plots in MDNR
No.
Vegetation
Altitude (m)
Sample plots
V1
Open evergreen and deciduous broadleaved forest
1300-1450
M9，M10，M12，M13，M17
dominated by Kalopanax septemlobus and Platycarya
strobilacea
V2
Evergreen broadleaved forest dominated by Fagaceae
1460-1500
M8，M11，M15，M19，M20
V3
Dense evergreen and deciduous broadleaved forest
1400-1550
M1，M2，M4，M7，M14，M16，M18
1520-1700
M3，M5，M6，M21，M22
by
1800-1950
M23,M24，M25，M27
Deciduous broadleaved forest dominated by Davidia
1950-2220
M26，M28，M29，M30，M31，M32，M33，
dominated by Aesculus chinensis and Litsea suberosa
V4
Mixed evergreen and deciduous broadleaved forest
V5
Evergreen
broadleaved
forest
dominated
Lithocarpus glabra
involucrata
M34，
4
Shannon-Wiener
Pielous
120
Patrick
Shannon-Wiener index
Pielous index
3.5
100
3
80
2.5
2
60
1.5
40
Patrick index
V6
1
20
0.5
0
0
V1
V2
V3
V4
Vegetation type
V5
V6
Figure 1 α-diversity of ground bryophytes in broadleaved forests in MDNR
In terms of β diversity, the Sφrenson index (βS) and Morisita–Horn index (βM) measure qualitative
and quantitative similarity, respectively. For the qualitative β-diversity index (βS), which only considers
species presence or absence, the highest similarity (0.552) was found for the forest types of evergreen
broadleaved forest dominated by Fagaceae (V2) and mixed dense evergreen and deciduous broadleaved
forest dominated by Aesculus chinensis and Litsea suberosa (V3), whereas the lowest similarity (0.171)
as found in the mixed evergreen and deciduous broadleaved forest (V4) and deciduous broadleaved
forest dominated by Davidia involucrate (V6). According to the quantitative β-diversity index (βM),
which considers both species presence and relative covers, the similarities were somehow different from
the above results. The overall similarities were significantly lower at 0.126 to 0.418 (Table 5). The
generally low similarities of ground bryophyte communities in the involved broadleaved forest types
indicated that species varied significantly with changing forest types, and the species diversity in the
study region was very rich.
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Table 5 β-diversity of ground bryophytes under different broadleaved forests in MDNR
βS / βM
V1
V2
0.436 / 0.229
V3
0.439 / 0.363
0.552 / 0.398
V4
0.429 / 0.418
0.345 / 0.221
0.390 / 0.361
V5
0.278 / 0.126
0.281 / 0.367
0.295 / 0.145
0.224 / 0.152
V6
0.283 / 0.355
0.262 / 0.136
0.250 / 0.162
0.171 / 0.389
V2
V3
V4
V5
0.410 / 0.325
3.3. Relationships between diversity and environmental factors of ground bryophytes in MDNR
In the bryophyte diversity studies, researchers have subjectively divided sample plots into groups
based on some rules to compare the differences between environment gradients or regimes. The rules
included those used in this study, such as vegetation type. However, the factors that determined species
diversity remain unclear. Thus, we conducted a PCA to analyze the relationships among sample plots
objectively. Figure 2 shows the PCA result. Thirty-four sample plots were divided into five groups:
G1: sample plots 1, 2, 3, 5, 6, 11, 14, 16 and 17;
G2: sample plots 12, 13, 15, 20 and 22;
G3: sample plots 27, 29, 30, 31, 33 and 34;
G4: sample plots 23, 24, 25, 26, 28 and 32;
G5: sample plots 4, 7, 8, 9, 10, 18, 19 and 21.
The PCA groups were different from the subjective grouping based on vegetation and altitude, thus
revealing that the subjective grouping was not a scientific grouping method. Calculating bryophyte
diversity per sample plot was efficient in quantifying the relationships between diversity and
environmental factors by taking advantage of every measured factor. Thus, we conducted a correlation
analysis between Patrick index and environmental factors per sample plot. The correlations revealed
that ground bryophyte diversity was significantly negatively correlated to shrub cover (coefficient =
-0.339, P = 0.05) and negatively related to canopy cover and number of trees with coefficients of -0.318
and -0.326, respectively. These two factors were significantly autocorrelated (coefficient = 0.533, P =
0.001). Bryophyte diversity was not strongly related to altitude, slope, aspect, vegetation type, and herb
cover, with all of their coefficients less than 0.2 (Table 6). Therefore, environmental factors that most
affected ground bryophytes in MDNR were vegetation features, including canopy cover and shrub
cover.
10
Figure 2 PCA ordination of 34 sample plots in MDNR
Table 6 Correlation of Patrick index and environmental factors for ground bryophytes in MDNR
Environmental factors
Correlation coefficient
P
Altitude
0.190
0.932
Slope
0.015
0.052
Aspect
0.147
0.406
Vegetation type
-0.066
0.713
Canopy cover
-0.318
0.067
Number of trees
-0.326
0.059
Shrub cover
-0.339
0.050
Herb cover
0.180
0.307
3.4. Relationships between distribution and environmental factors of ground bryophytes in MDNR
DCCA analysis was employed to analyze the relationships between 52 dominant species and
environmental factors. The 52 species were found in the 34 sample plots, and their importance values
were higher than 0.5. Owing to the significant autocorrelations between canopy cover and number of
trees, the latter was excluded in the DCCA analysis. In Figure 3, primary environmental factors that
influenced ground bryophytes, the relationships of bryophytes and environments, and the presence of
bryophytes in sample plots were discerned. Considering geographic location, topography, and
vegetation, the correlation coefficient between ground bryophytes and environmental factors was 0.933
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on axis 1 and 0.895 on axis 2. The effects of topographic factors such as altitude and aspect, as well as
vegetation factors such as vegetation type and shrub cover, were more important than those of slope,
canopy cover, and herb cover to the distribution of ground bryophytes.
Figure 3 also indicates that the relationships between different bryophytes and environmental
factors varied. These relationships possessed the following features:
(1) Altitude, vegetation type, and shrub cover were positive to axis 1 and important to ground
bryophyte distribution pattern. Thus, the species with small projected distance to these factors will
exhibit increasing abundance as the values of these environment factors increase. The species were
Dicranum scoparium (S17), Atrichum undulatum var. gracilisetum (S21), Plagiothecium cavifolium var.
fallax (S22), Eurhynchium savatieri (S24, Fissidens anomalus (S30), Atrichum subserratum (S31),
Plagiothecium nemorale (S33), Brotherella henonii (S36), Plagiothecium cavifolium (S48), and so on.
Canopy cover was negative to axis 1, but its effect on bryophyte distribution was much smaller than that
of the abovementioned factors.
(2) Aspect was positively related to axis 2, which is another important factor in the distribution of
ground bryophytes. The bryophyte species adapted to shady slopes were Plagiomnium rhynchophorum
(S3), Plagiochila ovalifolia (S16), Bryum capillare (S19), Conocephalum conicum (S25),
Plagiothecium succulentum (S45), and Trichostomum tenuirostre (S51).
(3) Eurhynchium laxirete (S5), Claopodium aciculums (S8), Mnium spinosum (S12),
Hypopterygium flavolimbatum (S26), Mnium laevinerve (S35), Aneuraceae pinguis (S37), and
Taxiphyllum cuspidifolium (S41) were positively correlated to herb cover and slope.
(4) The above species were affected by certain factors. However, some species were located in the
middle of DCCA graph and surrounded the environmental factors. For example, Thuidium cymbifolium
(S1), Plagiothecium euryphyllum(S2), Homaliodendron crassinervium (S7), Leucobryum juniperoideum
(S11), Heteroscyphus argutus (S13), Eurhynchium kirishimense (S15), Hookeria acutifolia (S20),
Mnium thomsonii (S34), Bryum salakense (S39), Fauriella tenuis (S43), Fissidens involutus (S44), and
Eurhynchium eustegium (S46) were scattered and minimally affected by all the factors in this study.
These species were present in a few sample plots: M4, M6, M10, M11, M13, M15, M17, M19, and
M21.
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Figure 3 DCCA ordination of 52 dominant ground-bryophytes and environmental factors from MDNR.
- 52 bryophyte species，
- 34 sample plots
4. Conclusion and discussion
The dominant families of ground bryophytes in MDNR included mosses of Brachytheciaceae,
Mniaceae, Plagiotheciaceae, Hypnaceae, and Thuidiaceae, as well as liverworts of Lophocoleaceae,
Plagiochilaceae and Porellaceae. These families included a number of subtropical genera and species,
and their geographic distribution belongs to floras of both Yunnan–Guizhou and Central China [18]. The
ground bryophyte species in MDNR were similar to those in Foping Nature Reserve, which may be
explained by the fact that the bryophyte flora of Foping Nature Reserve belongs to the transitional zone
of North China and Central China [19].
Based on the subjective grouping of bryophyte communities by canopy vegetation types, the
resultant similarities were low, and the values of the diversity index were irregular. This finding
illustrates that vegetation types strongly affected ground bryophytes, the bryophytes species were
significantly changed as the vegetation varied, and the species richness in this study area was high.
Moreover, this observation might indicate that the subjective grouping method was unreasonable. To
clarify further species diversity and its determinants in the broadleaved forest zone, adequate survey
plots and more scientific grouping methods are needed. PCA is one of the effective grouping methods.
TWINSPAN, which is a cluster grouping approach that in the light of bryophytes coverage in each
sample plot, has also been frequently used [7, 20].
Quantitative studies on bryophyte diversity and environments remain limited [21]. In this study, we
13
set diversity indexes of all sample plots as dependent variables, quantified the correlations between
environmental factors and diversity indexes directly, and identified that vegetation, especially upper
vegetation such as trees and shrubs, were key factors that influenced ground bryophytes diversity.
DCCA ordination of species and environments showed different tendencies: canopy cover was not as
important as other factors that affected ground bryophyte distribution, but vegetation type, shrub cover,
and altitude limited the distribution range.
Acknowledgement
This work was supported by the National Natural Science Foundation of China (31300356).
Specimen classification was performed with the assistance of Prof. Pengcheng Wu and Meizhi Wang
from the Institute of Botany, Chinese Academy of Sciences, as well as Prof. Youfang Wang from East
China Normal University. Field works were supported by ShuaRi Luobo and other staff members from
the MDNR Administration Bureau.
14
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