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Article

Population Structure, Distribution, and Spatial Characteristics of Alsophila spinulosa in Chishui, China

by
Dongmei Yuan
1,
Man Yang
1,
Lifei Yu
1,
Mingtai An
2,
Qinqin He
3,
Jun Mu
3 and
Lingbin Yan
1,*
1
Key Laboratory of Plant Resource Conservation and Germplasm Innovation in Mountainous Region (Ministry of Education), College of Life Sciences/Institute of Agro-Bioengineering, Guizhou University, Guiyang 550025, China
2
Research Center for Biodiversiey and Nature Conservation, College of Forestry, Guizhou University, Guiyang 550025, China
3
Guizhou Chishui Alsophila National Nature Reserve Administration Bureau, Chishui 564700, China
*
Author to whom correspondence should be addressed.
Diversity 2023, 15(12), 1200; https://doi.org/10.3390/d15121200
Submission received: 28 September 2023 / Revised: 2 December 2023 / Accepted: 4 December 2023 / Published: 7 December 2023
(This article belongs to the Section Plant Diversity)
Browse Figures
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Abstract

:
Endangered plants are essential components of most forest ecosystems and reflect the ecological integrity of forests. The study of the population structure and spatial pattern of Alsophila spinulosa is of great significance for its conservation. In the subtropical Chishui Tree fern valley in China, we studied the best structure of A. spinulosa to reflect the environmental change, the range of the most intense spatial aggregation change, and the spatial relationship with the community structure, and explored the survival characteristics of A. spinulosa. Our results showed that the variation in tree height structure was the most obvious response to the change in community type. The spatial aggregation degree of A. spinulosa had the most obvious change in the range of 1–5 m. There was an obvious spatial correlation between the dominant plants, the vertical structure of the community, and the distribution of A. spinulosa. These findings provided a reference for exploring the population structure, distribution pattern, and the influence of community types on A. spinulosa populations.

1. Introduction

Population structures and the spatial characteristics of plant populations reflect their growth and distribution across space and time, in addition to the ecological processes influencing forest communities and the coexistence of species within communities and other ecological relationships among populations [1,2]. Patterns of DBH (Diameter at Breast Height) structures, height structures, and canopy structures of plant populations can reflect the long-term competitive ability of populations and predict their future development potential [3]. Spatial distribution patterns and associations, in addition to other spatial characteristics of plant populations, are an important basis for understanding their biological characteristics, development, and co-existence with other species [4]. Specifically, the spatial distributions and relationships of populations are determined by plant biological characteristics, community types, and environmental factors. Thus, spatial characteristics reflect the use of environmental resources, thereby indicating the roles and status of populations within communities, complex relationships between species within communities, and the characteristics of population change and the directions of community development [5,6]. Point pattern analysis can help overcome the shortcomings of traditional spatial pattern analysis and provide more comprehensive spatial information, thereby accurately reflecting the spatial dynamics of populations and their relationships with environments [7].
The study of endangered plants is of great value for biodiversity conservation [8,9]. Alsophila spinulosa is a large tree fern whose population structure can reflect its growth pattern. The spatial distribution and spatial linkage characteristics can reflect the spread range of spores and the characteristics of growth restriction [10]. Therefore, by studying the population structure and spatial characteristics of A. spinulos, the relationship between A. spinulos and the environment can be reflected, which has high practical significance. Habitat destruction, intense anthropogenic disturbance, and the harsh reproductive conditions of A. spinulosa plants have led to dramatic declines in global A. spinulosa populations [11]. Abundant research has consequently been conducted to better protect A. spinulosa populations and save the species from extinction. For example, rapid propagation and breeding techniques for A. spinulosa plants have been explored since the 1990s [12]. Previous studies have shown that the Green Globular Bodies (GGB) pathway of A. spinulosa underpins their fast propagation system, improves propagation rates, and shortens propagation times, subsequently maintaining a factory nursery of A. spinulosa plants [13]. Furthermore, the survival of A. spinulosa plants in the tropical rainforests of the Hangluo Mountains of Hainan Province is affected by environmental conditions; mild disturbance may favor the growth of A. spinulosa [14]. Increasing the number of sapling seedlings is beneficial to the protection of A. spinulosa populations [15]. A previous review of the interspecific relationships of A. spinulosa plants revealed the important influence of biological factors on their growth and development [11]. An investigation of potentially suitable areas for A. spinulosa plant growth at different times also revealed that the geometric center of potentially relevant regions for A. spinulosa growth generally shifted toward the northeast during the last Ice Age through the end of this century, with climatic factors and vegetation types being essential parameters that influence the distribution of potentially suitable growth areas [16]. Studies on A. spinulosa have focused on broad research areas including population and community structure characteristics [17], spatial distributions [18], physiological structures, genetic features [19], pest and disease prevention and control [20], invasiveness [21], and genomic research [22].
In recent years, research on A. spinulosa has been carried out in many fields. However, there is still a relative lack of research on the basic survival characteristics in typical plant communities, the population structure status of A. spinulosa in different plant communities, and the spatial distribution pattern of A. spinulosa plants; the spatial relationships with the community structure are still not clear enough. The present study explored the survival status of A. spinulosa populations in typical plant communities, the range of the most obvious changes in the distribution pattern of the A. spinulosa population, and the spatial relationship between A. spinulosa population and community structure, to elucidate the characteristics of the growth and distribution of A. spinulosa population in typical growing plant communities, and to provide references to solve the problem of the effective management and conservation of A. spinulosa plants.

2. Materials and Methods

2.1. Study Area

The Chishui A. spinulosa National Nature Reserve is located near Jinsha Gou, Huzhi Town, in western Qianbei, Guizhou, China (105°59′54″–106°7′7″ E and 28°20′16″–28°29′44″ N). The reserve was established in 1984 to protect A. spinulosa and its habitat, later becoming a national nature reserve in 1992. In 1993, the reserve was designated as a Chinese Biosphere Reserve, containing a high abundance of A. spinulosa relative to the rest of the world. The area is characterized by high and steep mountains, deep valleys, rivers that are prone to high water during the rainy season, and a high degree of topographic shade. The climate of the area is a typical humid subtropical monsoon climate that is particularly prominent in the valley bottoms at low altitudes, with hydrothermal conditions favorable for A. spinulosa growth. The soils in this reserve are mostly acidic purple soils developed on chalky purple-red sandstones, with deep layers and relatively rich organic matter levels. The vegetation types of the area are diverse and biodiversity is high, with subtropical moist broad-leaved evergreen forests dominating the area, and additional warm coniferous, deciduous broad-leaved, mixed evergreen, deciduous broad-leaved, evergreen broad-leaved, bamboo, and evergreen broad-leaved scrub forests.

2.2. Sample Square Setting and Community Survey

The initial A. spinulosa community survey was conducted from March to June 2021. Based on the survey results, a 1.12 ha (140 m × 80 m) fixed monitoring sample plot was established in July 2021 in a typical A. spinulosa community within the Chishui A. spinulosa National Nature Reserve. Four distinct communities of A. spinulosa grew in the monitoring sample sites, namely, BFB (bamboo forest belt), MF (a mixed forest of bamboo and arbor), ET (ecological transitional zone of community), and EF (evergreen broad-leaved forest) (Table 1). All plant individuals with a DBH > 1 cm in the sample area were marked with projection coordinates using a real-time kinematic (RTK) measurement system (Beidou Haida TS7). Furthermore, the species name, DBH, tree height, height under the branches, and individual characteristics of the crown were recorded for each plant and tagged for long-term analysis.

2.3. Age Class Structure Classification

Populations were classified into eight age classes according to stem height (H), based on a previously described [23] method of classifying the age classes of A. spinulosa and the substantial growth of populations in the monitoring sites. Specifically, classes were established as age class I (0.01 m ≤ H ≤ 0.3 m), age class II (0.03 m ≤ H ≤ 0.6 m), age class III (0.6 m ≤ H ≤ 1.2 m), age class IV (1.2 m ≤ H ≤ 2.1 m), age class V (2.1 m ≤ H ≤ 3.0 m), age class VI (3.0 m ≤ H ≤ 3.9 m), age class VII (3.9 m ≤ H ≤ 4.8 m), and age class VIII (H > 4.8 m). Age classes I and II comprised young individuals; age classes III and IV comprised middle-aged individuals; age classes V, VI, and VII comprised adult individuals; and age class VIII comprised old individuals.

2.4. Point Pattern Analysis

The point pattern analysis method [24,25] is an essential technique for quantifying the spatial distributions of populations. Choosing the correct function and zero models is a critical step for solving problems with this method. The pairwise correlation function g(r), with a scaled non-cumulative effect, represents an improved function of Ripley’s K(r) function with a scaled cumulative impact. The function is more accurate in reflecting the spatial patterns of populations at large scales. In this study, the univariate pair-correlation function, g(r), was used to investigate the spatial distribution of A. spinulosa in Chishui. The Monte-Carlo test method was used to randomly perform 199 simulations to generate 99% confidence intervals to test the significance of deviation from the zero model. The upper envelope represents the upper confidence limit; the lower envelope represents the lower confidence limit. In the graph of the point pattern analysis presented in this paper, the gray area represents the range of confidence intervals, i.e., the area between the upper envelope and the lower envelope. The deviation degree of the actual value in the envelope range (confidence interval) has reliability. If the g(r) values were randomly distributed, they were within the envelope line but significantly deviated from a random distribution; if they were outside the envelope line and clustered above the envelope line, but uniformly distributed, they were below the envelope line. The pair auto-correlation function, g(r), was used to investigate the spatial relationships between intraspecific connections and relevant components of the communities. The community composition includes the dominant plants and the structure of the forest layer. Few older individuals were present in the population, and were thus included in the adult population for intraspecific association analysis. Monte Carlo simulations of the functions were again carried out with 199 loops. The envelope line’s g(r) value was used to indicate the lack of a significant relationship between the two species. If they were above the envelope line, a meaningful positive relationship was inferred between the species, while values below the envelope line reflected important negative relationships.
A complete spatial randomness (CSR) model is essentially a homogeneous Poisson process that does not consider the disturbance of external environmental conditions. Furthermore, a heterogeneous Poisson process (HP) is a null hypothesis model that considers the characteristics of spatial heterogeneity [26]. The two null hypothesis models, CSR and HP, were used here to compare the spatial distributions of populations. The spatial correlations of the populations were investigated using the CSR model; the spatial scale should be half the shortest side length, and thus, at the 0–40 m scale [27]. A model test was also conducted with an actual display effect scale.

2.5. Data Processing and Analysis

The age structure of populations was analyzed using descriptive statistics. Analysis of variance (ANOVA) tests were used to investigate the presence of significant differences in the tree height, DBH, and canopy areas of spinulose plants between various species zones. The spatial distribution of different population age classes and their spatial autocorrelation were analyzed with point pattern analysis. Based on the probability density analysis of all species in the communities, the community canopy was divided into the upper canopy (tree height H > 7.70 m) and the secondary canopy (tree height ≤ 7.70 m) within the monitoring site. Dominant plants in the improved monitoring sample plots were assigned importance values > 1.
The initial collation of data was conducted in Microsoft Excel 2016. Descriptive statistics, one-way ANOVA tests, and Tukey’s HSD analysis were conducted using the SPSS v.25.0 software program. Point pattern analysis and mapping were conducted using the R v.4.1.3 packages “spatstat” and “ggplot2”, in addition to other packages.

3. Results

3.1. Age Structure of A. spinulosa Populations

Alsophila spinulosa populations comprised a large base of young and middle-aged individuals, with the number of individuals gradually decreasing with age class (Figure 1). The number of middle-aged individuals was 46.75% of the total, whereas the number of older individuals was only 0.96% of the total. Considering different community types (Figure 2), A. spinulosa followed an abundance distribution of BFB > MF > ET > EF, while the numbers of A. spinulosa at different ages were significantly different (p < 0.05). Older individuals were only observed in the EF communities.

3.2. Structural Characteristics of A. spinulosa Populations under Different Transects

The crown width structure of A. spinulosa populations significantly differed between different transects(Figure 3), with the degree of variation following the trend of CVBFB (8.15) > CVMF (5.25) > CVET (4.33) > CVEF (2.80). The DBH structure did not significantly differ among transects, with the degree of variation being CVEF (2.09) > CVMF (1.32) > CVBFB (1.21) > CVET (0.97). The height structure significantly differed among transects, with the degree of variation being CVEF (1.69) > CVMF (0.76) > CVET (0.74) > CVBFB (0.61). A. spinulosa populations exhibited the highest density of 0.0825 plants/m2 in BFB and the lowest density of 0.0025 plants/m2 in the EF transect, reflecting a density reduction of 96.97%. Thus, community types influenced the structure of A. spinulosa populations.

3.3. Spatial Patterns of Different Age Classes of A. spinulosa Populations in Chishui and Their Intraspecific Associations

3.3.1. Spatial Distributions Based on the CSR and HP Null Models

In homogeneous environments, the spatial distributions of juvenile, middle-aged, and adult A. spinulosa populations generally exhibited aggregated distributions, with the degree of aggregation decreasing with increasing scale and gradually becoming random distributions (Figure 4). Adult individuals tend to be more randomly distributed at 0–30 m, while the aggregation of juvenile individuals is most obviously affected at the 0–5 m scale. In heterogeneous environments, the spatial patterns of overall populations and age classes of A. spinulosa in Chishui tended to be more randomly distributed (Figure 5). Thus, heterogeneous environments noticeably influence the spatial distribution of A. spinulosa populations.

3.3.2. Spatial Correlation between Different Age Classes of A. spinulosa Populations

The juvenile and middle-aged individuals of A. spinulosa populations all show positive association at 0~30 m scale, and the association degree gradually decreases with increasing scale; juvenile and adult individuals show no association at 0~8 m scale but show positive association at 8~30 m scale, and the association degree is highest at 16 m scale and then stabilizes; middle-aged and adult individuals show no association at 0~3 m scale and show positive association at 4~30 m scale (Figure 6).

3.4. Spatial Association of Different Forest Layer Plants with A. spinulosa Populations

Different forest layer plants exhibited positive relationships with overall A. spinulosa populations and other age groups (Figure 7). Specifically, the canopy substratum exhibited a more positive relationship with young and middle-aged spinifexes at 1–4 m and with adult spinifexes above the 9 m scale. The upper layer of the forest canopy exhibited a more positive relationship with juvenile A. spinulosa individuals at all investigated scales, but most clearly at the 1–8 m scale. Overall, the positive relationships between the upper layer of the forest canopy and A. spinulosa populations were higher than those of the second layer of the forest canopy.

3.5. Association of Dominant Plants with A. spinulosa Populations

A. spinulosa population sizes were positively correlated with most of the dominant plants, wherein the degree of positive correlation decreased with increasing area. In addition, a negative correlation was observed between Mallotus philippensis and Eurya nitida at the 0–25 m scale and the degree of negative correlation decreased with increasing scale, while no correlation was observed across the rest of the scale. The correlation with Lasianthus chinensis was low, exhibiting a negative correlation at the 4.5–8 m scale, a positive correlation at the 24–29 m scale, and no correlation across the rest of the scale (Table 2).

4. Discussion

4.1. Influence of Community Type and Habitat Heterogeneity on A. spinulosa Population Structures

Community types significantly affected A. spinulosa population structures in this study. Population densities were the lowest in the EF transect and the highest in the BFB transect. This may have occurred because A. spinulosa is a pioneer plant of the communities, and simply structured community environments are more suitable for their growth. In contrast, the competitiveness of pioneer plants will gradually decrease as community succession occurs. Similarly, community types affect the stability of plant population structures [28]. The DBH structures of the populations did not significantly differ among transects, while the crown and height structures of the tree significantly varied among transects. A. spinulosa does not exhibit substantial radial growth, perhaps leading to insignificant differences in DBH among populations. The lowest degree of variation was observed in the ET transect, suggesting that a staggered zone community could improve the stability of A. spinulosa thoracic diameter structure. The canopy structures of the populations in the EF transect significantly differed from those in the other transects. The EF transect community type also greatly influenced the canopy structure of A. spinulosa populations. However, variation in the canopy structure of the populations was the lowest in the EF transect, while variation in height structure was the highest for the EF transect. The age class of the EF community strongly fluctuates with different age classes of the individuals. Nevertheless, the number of each age class remained stable, indicating that the conditions in the EF transect promoted stable survival of the populations.
Individuals of all age classes of A. spinulosa populations exhibited similar spatial distributions under both models used in this study. However, the HP model tended to produce more random patterning. The HP null model tests the intrinsic characteristics and formation mechanisms of the spatial pattern formation of populations, thereby compensating for the shortcomings of the CSR null model [29]. This suggested that habitat heterogeneity has an important influence on the spatial distribution of A. spinulosa populations, although the exact mechanism underlying this influence remains unclear. Under both models, the degree of population aggregation varied most significantly at the 0–5 m scale. Thus, this spatial range may critically influence A. spinulosa growth, such that the habitat conditions and species composition at this scale highly Influence A. spinulosa survival.

4.2. Spatial Relationships of A. spinulosa

The results from this study reveal stronger positive correlations between the juvenile and lower age classes of A. spinulosa populations that mostly simultaneously exist at small spatial scales. In contrast, the correlations between age classes significantly differed at larger scales and tended to plateau. This may result from a combination of clustering [30], density constraints [31], dispersal limitation [32], and habitat heterogeneity [33]. Clustering can increase individual survival as a means of defense against external threats. After a change in individual survival strategy, adult individuals expend more energy on maintenance, with population clustering in the environment instead of increasing intraspecific competition and the weakening of clustering enabling the availability of adequate resources. Intraspecific aggregation may lead to asymmetric competition processes between neighboring plant individuals, wherein density effects can trigger the self-thinning of individual plants. Habitat heterogeneity affects population distributions at large scales, while density constraints and dispersal limitations affect population distributions at small scales. In general, larger individuals more strongly influence smaller individuals at smaller scales [34], consistent with the results of this study.
In this study, the positive association of community canopy substrates with A. spinulosa populations was lower than for the upper canopy. The positions of plants within vertical community structures determine the ability of plants to gain adequate access to environmental resources, and also impact colonization by other plant populations [35]. Light levels generally decrease extending from the top to the bottom of the forest layer, such that lower plant species have less light available for their use, and species competition for light is intense [36]. Most individuals in the population belong to the sub-forest layer and species interactions may be responsible for weakening positive interactions between them. The results from this study suggest that the vertical structure of communities influences population spatial relationships.
Population numbers in this study were positively associated with the community type and most of the dominant plants, with differences observed in the degree of positive association at moderate distance scales. The degree of spatial association between species is strongly scale-dependent, with increasing scale weakening the associations between species [37]. The negative correlations observed here between the A. spinulosa populations and the dominant plants in the EF zone, Mallotus philippensis and Eurya nitida, suggest that different plant communities may have an inhibitory effect on the distribution and growth of A. spinulosa. Thus, this study shows that changes in the dominant plants and plant community types impact the spatial relationships of A. spinulosa populations.

5. Conclusions

The results from this study demonstrate that the population structures of A. spinulosa are significantly influenced by different community types, with height structure and canopy structure most clearly responding to differences in community type. The CSR and HP null models showed that the populations are generally aggregated, and the degree of aggregation decreases with scale, while the young- and middle-aged individuals exhibited aggregated distributions across the entire study scale. Mature individuals were randomly distributed on a global scale. However, the aggregation degree of young individuals was most apparent at the 0–5 m scale, suggesting that this is a crucial spatial range that affects their growth. The trends and random distributions of populations under the HP null model indicated that habitat heterogeneity particularly affected the spatial distributions of A. spinulosa. Intra-species correlations between different age classes of the populations were most evident at small scales, with higher positive correlations observed between the upper layer of the community canopy and A. spinulosa populations compared with that of the second layer of the canopy. Furthermore, A. spinulosa populations were positively correlated with the presence of most of the dominant plants in the community. Habitat heterogeneity is one of the principal mechanisms affecting the spatial distribution of plants, while forest types affect spatial relationships. Thus, the effects of the inferred mechanisms structuring A. spinulosa population distributions should be further investigated to improve our understanding of the impacts of forest structure on the population structures of tree-forming ferns.

Author Contributions

Conceptualization, L.Y. (Lingbin Yan) and D.Y.; methodology, D.Y. and M.Y.; software, D.Y. and M.Y.; validation, L.Y. (Lifei Yu); formal analysis, J.M.; investigation, D.Y. and M.Y.; resources, M.A.; data curation, L.Y. (Lingbin Yan); writing—original draft preparation, D.Y.; writing—review and editing, L.Y. (Lingbin Yan); visualization, D.Y.; supervision, Q.H.; project administration, Q.H.; funding acquisition, Q.H. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Special program for key protected plants in national nature reserves (NO-202204); Talent Introduction Scientific Research Project of Guizhou University (Guigengji (2020) No. 27); Construction Program of Biology First-class Discipline in Guizhou, Grant/Award Number: GNYL[2017]009.

Data Availability Statement

Data are contained within the article.

Acknowledgments

We are grateful to the Chishui Alsophila spinulosa National Nature Reserve Administration in Chishui for their help with the field survey.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Age structure of Alsophila spinulosa populations in Chishui.
Figure 1. Age structure of Alsophila spinulosa populations in Chishui.
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Figure 2. Numbers of A. spinulosa individuals. The abbreviations BFB (bamboo forest belt), MF (a mixed forest of bamboo and arbor), ET (ecological transitional zone of community), and EF (evergreen broad-leaved forest) are defined in Table 1. Different lowercase letters indicated significant differences in the number of A. spinulosa among different communities.
Figure 2. Numbers of A. spinulosa individuals. The abbreviations BFB (bamboo forest belt), MF (a mixed forest of bamboo and arbor), ET (ecological transitional zone of community), and EF (evergreen broad-leaved forest) are defined in Table 1. Different lowercase letters indicated significant differences in the number of A. spinulosa among different communities.
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Figure 3. Structural features of A. spinulosa populations. The abbreviations BFB (bamboo forest belt), MF (a mixed forest of bamboo and arbor), ET (ecological transitional zone of community), and EF (evergreen broad-leaved forest) are defined in Table 1. * means p < 0.05, ** means p < 0.01 and *** means p < 0.001.
Figure 3. Structural features of A. spinulosa populations. The abbreviations BFB (bamboo forest belt), MF (a mixed forest of bamboo and arbor), ET (ecological transitional zone of community), and EF (evergreen broad-leaved forest) are defined in Table 1. * means p < 0.05, ** means p < 0.01 and *** means p < 0.001.
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Figure 4. Spatial distribution of A. spinulosa populations based on the CSR (complete spatial randomness) null model. In the figure, g(r) represents the degree of aggregation, and r(m) represents the spatial scale. The gray range is the coverage of the upper and lower limits of the envelope, the red dotted line is the theoretical value, and the black solid line represents the actual value. (a–d) show the spatial distributions of young, middle-aged, adult, and all A. spinulosa, respectively.
Figure 4. Spatial distribution of A. spinulosa populations based on the CSR (complete spatial randomness) null model. In the figure, g(r) represents the degree of aggregation, and r(m) represents the spatial scale. The gray range is the coverage of the upper and lower limits of the envelope, the red dotted line is the theoretical value, and the black solid line represents the actual value. (a–d) show the spatial distributions of young, middle-aged, adult, and all A. spinulosa, respectively.
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Figure 5. Spatial distribution of A. spinulosa populations based on the HP (heterogeneous Poisson process) null model. In the figure, g(r) represents the degree of aggregation, and r(m) represents the spatial scale. The gray range is the coverage of the upper and lower limits of the envelope, the red dotted line is the theoretical value, and the black solid line represents the actual value. (a–d) show the spatial distributions of young, middle-aged, adult, and all A. spinulosa, respectively.
Figure 5. Spatial distribution of A. spinulosa populations based on the HP (heterogeneous Poisson process) null model. In the figure, g(r) represents the degree of aggregation, and r(m) represents the spatial scale. The gray range is the coverage of the upper and lower limits of the envelope, the red dotted line is the theoretical value, and the black solid line represents the actual value. (a–d) show the spatial distributions of young, middle-aged, adult, and all A. spinulosa, respectively.
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Figure 6. Interspecific associations of A. spinulosa populations. In the figure, g(r) represents the degree of aggregation and r(m) represents the spatial scale. The gray range is the coverage of the upper and lower limits of the envelope, the red dotted line is the theoretical value, and the black solid line represents the actual value. (a) Spatial associations of young and middle-aged individuals of A. spinulosa. (b) Spatial associations of middle-aged and adult individuals of A. spinulosa. (c) Spatial associations of young and adult individuals of A. spinulosa.
Figure 6. Interspecific associations of A. spinulosa populations. In the figure, g(r) represents the degree of aggregation and r(m) represents the spatial scale. The gray range is the coverage of the upper and lower limits of the envelope, the red dotted line is the theoretical value, and the black solid line represents the actual value. (a) Spatial associations of young and middle-aged individuals of A. spinulosa. (b) Spatial associations of middle-aged and adult individuals of A. spinulosa. (c) Spatial associations of young and adult individuals of A. spinulosa.
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Figure 7. Spatial correlation between different community canopies and A. spinulosa populations. Point pattern analysis revealed that the community canopies were positively correlated with A. spinulosa populations. a, b, c, and d show the spatial correlations between all, young, middle-aged, and adult A. spinulosa and the secondary layer of the community canopies, respectively. e, f, g, and h show the spatial correlations between all, young, middle-aged, and adult A. spinulosa and the upper layer of the community canopies, respectively.
Figure 7. Spatial correlation between different community canopies and A. spinulosa populations. Point pattern analysis revealed that the community canopies were positively correlated with A. spinulosa populations. a, b, c, and d show the spatial correlations between all, young, middle-aged, and adult A. spinulosa and the secondary layer of the community canopies, respectively. e, f, g, and h show the spatial correlations between all, young, middle-aged, and adult A. spinulosa and the upper layer of the community canopies, respectively.
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Table 1. Sample belt basic information table.
Table 1. Sample belt basic information table.
TransectSlope PositionAltitude/mSlopeStand Density/(Plant/m2)Alsophila spinulosa Density/(Plant/m2)Community Height/mNumber of SpeciesDominant Species
BFBDownhill position52616.320.4328570.0542867.91 ± 5.4534Phyllostachys heterocycla, Brassaiopsis glomerulata, A. spinulosa, Bridelia tomentosa, Ficus virens
MFDownhill position52616.840.5489290.0478576.99 ± 5.2349Phyllostachys heterocycla, Brassaiopsis glomerulata, Bridelia tomentosa, A. spinulosa, Ficus virens
ETMedium position55141.990.5642860.0357147.00 ± 4.8837Phyllostachys heterocycla, Phyllostachys heterocycla, Brassaiopsis glomerulata, Maesa japonica, A. spinulosa
EFMedium position55144.760.43250.0103574.08 ± 3.4137Mallotus philippensis, Maesa japonica, Cinnamomum glanduliferum, Diplospora dubia, Phyllostachys heterocycla
Table 2. Spatial correlation between Alsophila spinulosa populations and dominant plants in the community.
Table 2. Spatial correlation between Alsophila spinulosa populations and dominant plants in the community.
SpeciesSignificant ValuesHighly/mAssociations
Phyllostachys edulis33.0512.09 ± 2.20(+)
Maesa japonica8.283.27 ± 2.04(+)
Bridelia retusa5.593.90 ± 2.56(+)
Brassaiopsis glomerulata5.203.00 ± 1.37(+)
Ficus virens3.534.56 ± 2.19(+)
Diplospora dubia3.013.04 ± 1.710~8 m scale (0), under the rest of the scale (+)
Symplocos cochinchinensis2.944.72 ± 3.93(+)
Mallotus philippensis2.683.08 ± 1.950~21 m scale (−), under the rest of the scale (0)
Mallotus barbatus2.363.89 ± 1.78(+)
Dichroa febrifuga2.282.06 ± 1.09(+)
Eurya kueichowensis2.243.04 ± 2.01(+)
Musa basjoo2.024.29 ± 2.720~26 m scale (+), under the rest of the scale (0)
Toxicodendron sylvestre1.954.88 ± 3.57(+)
Cinnamomum glanduliferum1.863.28 ± 1.62(+)
Eurya nitida1.623.36 ± 1.900~24 m scale (−), under the rest of the scale (0)
Debregeasia orientalis1.461.70 ± 0.46(+)
Lasianthus chinensis1.021.61 ± 0.204.5~8 m scale (−), 24~29 m scale (+), under the rest of the scale (0)
Note: (+) indicates a positive correlation, (−) indicates a negative correlation, and (0) indicates no correlation.
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MDPI and ACS Style

Yuan, D.; Yang, M.; Yu, L.; An, M.; He, Q.; Mu, J.; Yan, L. Population Structure, Distribution, and Spatial Characteristics of Alsophila spinulosa in Chishui, China. Diversity 2023, 15, 1200. https://doi.org/10.3390/d15121200

AMA Style

Yuan D, Yang M, Yu L, An M, He Q, Mu J, Yan L. Population Structure, Distribution, and Spatial Characteristics of Alsophila spinulosa in Chishui, China. Diversity. 2023; 15(12):1200. https://doi.org/10.3390/d15121200

Chicago/Turabian Style

Yuan, Dongmei, Man Yang, Lifei Yu, Mingtai An, Qinqin He, Jun Mu, and Lingbin Yan. 2023. "Population Structure, Distribution, and Spatial Characteristics of Alsophila spinulosa in Chishui, China" Diversity 15, no. 12: 1200. https://doi.org/10.3390/d15121200

APA Style

Yuan, D., Yang, M., Yu, L., An, M., He, Q., Mu, J., & Yan, L. (2023). Population Structure, Distribution, and Spatial Characteristics of Alsophila spinulosa in Chishui, China. Diversity, 15(12), 1200. https://doi.org/10.3390/d15121200

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