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Article

Distinct Community Assembly Mechanisms of Different Growth Stages in a Warm Temperate Forest

by
Xiaolei Jiang
,
Xiao Guo
,
Huicui Lu
,
Jinming Yang
,
Wei Li
and
Qing Hao
*
School of Landscape Architecture and Forestry, Qingdao Agricultural University, Qingdao 266109, China
*
Author to whom correspondence should be addressed.
Diversity 2023, 15(4), 507; https://doi.org/10.3390/d15040507
Submission received: 10 January 2023 / Revised: 26 March 2023 / Accepted: 27 March 2023 / Published: 1 April 2023
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Abstract

:
Community phylogenetic structure and diversity analysis are useful complements to species-centric approaches in biodiversity studies by providing new insights into the processes that drive community assembly. In this study, we aimed to understand the differences in the relative importance of abiotic filtering, biotic interactions, and dispersal limitation on community assembly of trees at different vegetation growth stages. We also examined the influence of geographical distance, elevation, terrain, and soil. Thus, we examined the phylogenetic structures and β-diversities of saplings and adults along different abiotic gradients. The results of the net relatedness index (NRI) showed that, instead of being random, the phylogenetic structure of saplings tended to be convergent, whereas that of adults tended to be divergent. This result implies that the relative forces of abiotic filtering and biotic interactions change throughout vegetation growth. The results of generalized dissimilarity modelling (GDM) showed that dispersal limitation (geographical distance) and abiotic filtering influenced the community assembly of both adults and saplings. This result confirmed our hypothesis that both deterministic and stochastic processes were prevalent. The explanatory rates of geographic distance and environmental factor distance to phylogenetic β-diversity were quite different between adults and saplings, which meant that the relative force of dispersal limitation and abiotic filtering had also changed.

1. Introduction

Understanding the role of different processes that drive community assembly and diversity patterns remains a central topic in ecology. The two main theories that explain community assembly are niche theory, which emphasises the deterministic process, and neutral theory, which emphasises the stochastic process [1].
Based on traditional niche theory, community assembly is a screening process in which species from a large regional species pool are selected into a small region through multilayer abiotic filtering and biotic interactions [2]. Several studies have demonstrated the existence of abiotic filtering which enables species with similar functions to be sorted into the same ecological niche [3,4,5]. The mechanisms of action vary at different scales. On a global scale, climatic factors are often the main drivers of abiotic filtering [6], whereas soil and terrain factors play important roles on a local scale [7]. In addition to abiotic filtering, the niche theory suggests that biotic interactions also play a primary role in the sorting of species into local communities. The process of biotic interactions can be explained by the hypothesis of negative density dependence (NDD), in which natural enemies and competition for resources decrease the growth and survival rates of homogeneous individuals and promote the occurrence of high species diversity [8]. What should be noticed is that with different community types and study scales, the relative importance of abiotic filtering and biotic interactions varies [9,10].
Functional diversity is an important means to understand the mechanism of community assembly [11,12]. However, it is difficult to accurately select and measure functional traits, and there is often intraspecific variation, which will interfere with the research results to some extent [13,14,15]. Therefore, since closely related species tend to retain functional attributes from a common ancestor [16], phylogenetic structure and diversity have been widely used as a proxy for functional diversity [17,18]. However, using phylogenetic information to infer ecological processes requires the proof that phylogenetic distance between taxa approximates their ecological niche difference, which implies niche conservation along evolutionary lineages (niche conservatism) [19]. The link between phylogeny and continuous trait values is commonly referred to in the literature as phylogenetic signal [20], and deciphering the phylogenetic signal may help to detect niche conservatism [21]. On this premise, if community structure is primarily stochastic, then community phylogenetic composition should not differ significantly from expectations based on random community assembly. Furthermore, if abiotic filtering is the most influential process, then coexisting taxa should be more closely related than expected by chance. Contrastingly, if biotic interactions (mainly competition) exert a greater force and lead coexisting taxa to be ecologically differentiated from each other, then coexisting taxa should be more distantly related than expected by chance. Therefore, convergent phylogenetic structures indicate that species have relatively similar niches, suggesting that abiotic filtering governs community assembly; however, divergent structures indicate that species have different niches, suggesting that biotic interactions govern community assembly [13].
In contrast to niche theory, neutral theory states that all individuals of the same trophic level in a community are equivalent in niche, emphasizing the role of stochastic events in community assembly, such as random drift, dispersal limitation, and so on [22]. On a global scale, historical factors, random drift, and other factors may cause the species pool to vary among different regions, leading to differences in species composition [23,24]. However, on a local scale, dispersal limitation caused by species’ different dispersal abilities is the main reason for the different composition of communities [25]. With different community types and study scales, the relative importance of dispersal limitation to ecological processes varies as well [26,27,28]. An increasing number of ecologists believe that niche theory and neutral theory should be integrated, and that both deterministic and stochastic processes play vital roles; however, the relative importance of these factors depends on prevailing environmental conditions [29]. Previous studies on community assembly have concentrated mainly on adults of canopy species [30]; however, dominant factors may change at different vegetation growth stages [13].
Mountains are distinct systems for investigating biogeographical patterns because of their high environmental heterogeneity [31,32]. Several studies have reported that elevation plays an important role in the species composition of plant communities due to its influence on temperature and precipitation, which affect the physiological adaptation of plants [33,34,35]. An increase in elevation results in harsher environmental conditions, such as lower temperatures and stronger winds. Therefore, at high elevations, abiotic filtering tends to govern community assembly, as only adaptable species survive [36]. Nevertheless, dispersal limitations and other environmental gradients, such as slope direction and soil properties, may also influence community composition in mountainous ecosystems [37]. Mount Lao in Shandong Province, China is a natural reserve for the protection of warm temperate forest vegetation and granite peak geomorphology. Owing to its complex microenvironment and strict protection measures, the biodiversity of plant communities is highest in Shandong Province and the communities have a rich vertical hierarchy, including all tree ages [38]. Zhang et al. studied the relationship between alien species richness and environmental factors (human disturbance, slope, aspect, and canopy density) in the mature vegetation of the upper layer on Mount Lao [39]. Additionally, we conducted a similar study on the relationship between species diversity and environmental factors (elevation, slope, aspect, and soil organic matter) in this region [40]. The results of these two studies both showed significant differences in community species composition along environmental gradients, which suggests the existence of environmental filtering during the assembly of temperate secondary forest communities.
Ecological processes acting on the persistence of older trees can differ from those influencing young recruits. Since large trees are established in suitable microhabitats after filtering occurs, their survival is more influenced by the biotic neighbourhood [41]. There was a hypothesis that as ontogeny progresses, biotic interactions should become increasingly important in structuring a community, and should result in an increase in phylogenetic divergent with time [13]. Previous studies have confirmed this hypothesis in tropical and temperate forest [42,43,44]. When the phylogenetic structure of adult trees in a community is divergent, the study of the phylogenetic structure of saplings (if convergent) may provide more direct evidence for the existence of abiotic filtering. The study of Fraaije et al. for riparian plants showed that strong abiotic filtering during seedling growth plays an important role in determining later adult distributions, by forming the spatial template on which all subsequent processes operate [45]. However, the effects of abiotic filtering on sapling composition of mountain communities are rarely studied.
In this study, we expect that both deterministic and stochastic processes play important roles in the assembly process at the local scale. Moreover, for different vegetation growth stages, the dominant driving forces governing species composition may differ and change from abiotic to biotic from saplings to adult trees. We hypothesis that abiotic filtering plays an important role not only in adult trees but also in the composition of saplings. The objectives of this study were to (1) compare the relative effects of abiotic filtering, biotic interactions, and dispersal limitation on community assembly at different vegetation growth stages, and (2) assess the effects of elevation, terrain, and soil factors on phylogenetic structure and phylogenetic dissimilarity at different vegetation growth stages. Figuring out the different mechanisms of plant community assembly at different vegetation growth stages is important for understanding the laws of forest growth and development, and it also has guiding significance for promoting the forward succession of secondary forests artificially.

2. Materials and Methods

2.1. Study Area

This study was conducted from June to August 2019 along six transects from low to high elevations on Mount Lao (36°5′–36°19′ N, 120°24′–120°42′ E) in Shandong Province, northern China. Mount Lao occupies an area of 446 km2 and is bordered by the sea to the east and south. The highest peak of Mount Lao is 1132.7 m, which is also the highest peak along the Chinese coastline. It has a temperate maritime climate owing to its proximity to the ocean. The mean annual precipitation increases with elevation from 726.6 mm to 2103.8 mm. The mean annual temperature is 11.9 °C. The average frost period is over 186 d, and the extreme minimum temperature is −21.2 °C [39]. The bedrock is composed of granite, and the soil is mainly brown [46]. The vegetation on Mount Lao primarily comprises temperate deciduous broad-leaf and temperate coniferous forests. The native vegetation of Mount Lao was largely destroyed prior to the founding of the People’s Republic of China. Most areas of Mount Lao have been closed since the 1950s to allow for the restoration of forests. Our previous research determined that the communities are mainly in the late stage of succession, with complex species composition of different-aged plants and a multilayer stand structure [40].

2.2. Data Collection

We established 69 plots (20 m × 20 m) of representative secondary plant communities along 6 transects (Figure 1, Table 1). To examine the effects of elevation and environmental variables, a minimum of 3 plots were established at every 100 m increase in elevation. The life-stage classifications were based on the diameter at breast height (DBH) (1.3 m). For understory tree species, those with a DBH of 1–2 cm were classified as saplings and those with a DBH greater than 2 cm were classified as adults. For canopy tree species, those with a DBH of 1–5 cm were classified as saplings and those with a DBH greater than 5 cm were classified as adults [47]. Adults were recorded and identified to the species level, and DBH was measured in all plots. Each plot was then divided into 4 equal subplots, and one small sampling site (5 m × 5 m) was randomly selected from each subplot for sapling determination.
To confirm that phylogenetic relatedness reflects how ecologically similar species are, we selected the following functional traits which are critical to the growth, survival and reproduction of vascular plants [48]: specific leaf area (SLA, mm2/g), which can be used to indicate the trade-offs between plant input and output; leaf dry matter content (LDMC, %), which reflects climatic conditions; leaf carbon concentration (LCC, mg/g), which is related to blade construction cost; leaf nitrogen concentration (LNC, mg/g) and leaf phosphorus concentration (LPC, mg/g), which are related to leaf metabolism and energy flow; and wood density (WD, g/cm3), which is related to stress tolerance of species. For each plant type, 15–20 mature, fully developed healthy leaves were collected. The leaves were sourced from at least five different mature individuals with a variety of orientations. The collected leaves were immediately placed in sealed bags with moisturising cotton balls and transferred to the laboratory for subsequent character measurements [49].
The latitude, longitude, elevation, slope, and aspect of each plot were determined using a handheld GPS meter (Zhuolin Technology A10, Hefei, China). Considering the difference in soil thickness, we divided the profile of each hill on which the transects were located in 3 parts from valley to peak: downhill (1), middle-slope (2), and upper-slope (3) positions [50]. The aspect was divided into five levels, as shown in Figure S1. The higher the plot position, the more sunlight it receives [51]. As this is a local-scale study, we chose to focus on soil variables in addition to topographic factors. We collected 5 samples (above 300 g each) of topsoil (0–20 cm) from the 4 corners and centre of each plot. The samples were air-dried, sieved using a 2 mm mesh screen, and stored for the determination of physical and chemical properties. The chemical properties of soil samples were determined according to the method described by Bao et al. [52]. The physical and chemical properties examined were pH, conductivity (CON, mS/m), soil organic matter content (SOM, g/kg), available phosphorus (AP, mg/kg), ammonium nitrogen (AN, mg/kg), nitrate nitrogen (NN, mg/kg), and available potassium (AK, mg/kg).

2.3. Phylogenetic Tree Construction

To estimate the phylogenetic diversity and community structure of the tree species, we constructed a phylogenetic tree for the examined woody plant species using the mega-phylogeny Phyto-Phylo from PhyloMaker [53]. This was based on the updated version of the vascular plant phylogeny published by Zanne et al. [54].

2.4. Statistical Analysis

The use of phylogenetic distance between species as a means to analyse the maintenance mechanism of community diversity is based on the premise of phylogenetic niche conservation [19,55]. We assessed the conservation of a series of functional traits using the phylogenetic signal method and explained the feasibility of using phylogenetic distance to represent species characteristic distances. Phylogenetic signals indicate the tendency of closely related species to display similar trait values because of their phylogenetic proximity [21,56]. In this study, phylogenetic signals were quantified using R (using picante::phylosignal) [57] which computes indices and p-values based on the evolutionary model.
The net relatedness index (NRI) was used to quantify the degree of phylogenetic relatedness among species within each forest plot. NRI measures the standardised effect size of the mean phylogenetic distance (MPD), which estimates the average phylogenetic relatedness between all possible pairs of taxa in an assemblage [58]. NRI was calculated using the following equation:
N R I = − 1 × M P D s a m p l e − M P D n u l l S D M P D n u l l ,
where MPDsample is the mean pairwise phylogenetic distance between all possible pairs of species in a plot and MPDnull is the mean pairwise phylogenetic distance from 1000 randomly generated species assemblages across the tips of the phylogenetic tree. SD (MPDnull) is the standard deviation of the MPDnull. In this study, NRI was calculated using R (picante::ses.mpd) [59].
Pearson’s correlation coefficient was used to examine the relationship between the environmental factors and NRIs. Additionally, considering that the plots were taken from six independent transects, we used linear mixed effect (LME) models to examine changes in NRI along environmental gradients of significant factors screening from Pearson’s correlation (p ≤ 0.05). The NRIs were the response variables, relevant environmental factors were the explanatory variables, and transects were random factors. LME models were conducted using R (lmerTest::lmer) [60].
β-diversity describes the variation in species composition among communities within a region [61]. It is an effective way to study the mechanism of community assembly because we can describe community development by identifying the factors driving the formation of patterns of β-diversity [62]. In this study, we used the Sørensen pairwise dissimilarity index (βsor) to represent β-diversity. It was calculated with R (betapart::phylo.beta.pair) for further analysis in generalized dissimilarity modelling (GDM) [63]. GDM is a statistical technique for quantifying dissimilarity in species composition for a given biological group between a pair of locations in space or time [64]. In order to assess the relative effect of dispersal limitation (stochastic processes) and abiotic filtering (deterministic processes) on community assembly, we performed a GDM analysis. The spatial distance was determined by calculating the geographical distance between pairs of plots using latitude and longitude, and the Euclidean distance of environmental variables between every pair of plots was calculated to represent the environmental distance [65]. We performed GDM using R (gdm::gdm). Statistical significance of full GDM and individual predictors were determined using a permutation test in R (gdm::gdm.varImp).

3. Results

In total, 107 species belonging to 40 families and 76 genera were identified. We recorded 90 sapling species (Table S1) and 62 adult species (Table S2).

3.1. Results of Phylogenetic Signals

We collected leaves and branches only from adult trees. By removing rare species with fewer than 5 occurrences (12 species), we obtained the functional traits of 50 species (Table S4). The results of phylogenetic analysis revealed that, except for leaf dry matter content (LDMC) and wood density (WD), all the functional traits had significant phylogenetic signals (p ≤ 0.05). This result showed that interspecific differentiation of the main functional traits was more conservative than expected by random differentiation, indicating phylogenetic conservation (Table 2).

3.2. Variation in Community Phylogenetic Structure along Environmental Gradients

The mean NRI value of adults across the 69 plots was −0.63 ± 0.14, of which 17 plots recorded positive NRI values, 49 recorded negative NRI values, and 3 recorded NRI values of 0. The mean NRI value of saplings across the 69 plots was 0.66 ± 0.11, of which 53 plots recorded positive values, 15 recorded with negative values, and 1 recorded a value of 0 (S6). Additionally, a one-tailed t-test indicated that the mean NRI value of the adults was significantly less than 0.00 (p ≤ 0.001), whereas the mean NRI value of the saplings was significantly higher than 0.00 (p ≤ 0.001) (Figure 2). This result indicated that compared with complete randomness, the phylogenetic structure of adults tended to diverge, whereas those of saplings tended to converge. Furthermore, Pearson’s correlation analysis showed that the NRI of adults was significantly negatively correlated with ammonium nitrogen (AN) (p ≤ 0.05), whereas the NRI of saplings was significantly positively correlated with elevation (p ≤ 0.05) (Appendix A, Figure A1). The LMEs verified the results of the Pearson’s correlation analysis. For adults, a significant decreasing trend was observed in NRI with the increase in soil AN content (p ≤ 0.05). For saplings, a significant increasing trend was present in NRI with the increase in elevation (p ≤ 0.05) (Figure 3).

3.3. Explanatory Variables of β-Diversity

According to Pearson’s correlation analyses, two factors were excluded from generalized dissimilarity modelling: position and available potassium (Appendix A, Figure A1). The variables were filtered to avoid collinearity, wherein the position was significantly correlated with elevation. We chose elevation because it was an aggregate macro variable. Similarly, available potassium was excluded because of its significant correlation with pH, soil organic matter, and conductivity at the same time.
The full GDMs were significant (p < 0.05) for the dissimilarity of both adults and saplings. The deviances were 12.91% and 24.88%, respectively. Geographic distance and AN were the only two significant predictors for adults, and geographic distance and elevation were the only two significant predictors for saplings. Seen from the importance of each predictor, AN was the most important predictor for adults, and the deviances explained by the remaining predictors were quite low, while geographic distance and elevation were the most important predictors for saplings (Table 3).
We produced partial response graphs for the GDMs (Figure 4 and Figure 5). These plots show the predictor variable on the x-axis and the model-transformed value of the predictor on the y-axis. A greater slope of the spline function at a given point along the predictor variable axis indicates a more rapid increase in dissimilarity when the predictor values for a pair of sites straddle that point [65]. Therefore, the spline showed that AN could only greatly affect the composition of adults in low-gradient regions (when soil AN was less than 50 mg·kg−1). Similarly, for saplings, the effect of AN weakened when its content exceeded 50 mg·kg−1 in the soil. In contrast, the compositional dissimilarity of saplings increased significantly and steadily with increasing geographical and elevational distances between the plots.

4. Discussion

Plant community assembly is a dynamic process with a timeline that may vary at different stages of plant growth [13]. Upon closer examination of the differences between saplings and adults in the warm temperate forest on Mount Lao, we found that saplings exhibited a trend of phylogenetic convergence, whereas adults exhibited a trend of phylogenetic divergence (Figure 2). The divergent phylogenetic structure of adults showed the result of biotic interactions, while the convergent phylogenetic structure of saplings helped to demonstrate the existence of abiotic filtering. The changing of the structures confirmed the hypothesis that biotic interactions may become more intense with plant growth and development, resulting in the elimination of less competitive tree species and more divergence in phylogenetic structure [13,41]. With the same sampling scale (20 m × 20 m), the divergent phylogenetic structure in adult stage on Mount Lao is consistent with findings in the Jianfengling tropical montane rainforest on Hainan Island, China [66], but is contrary to the findings in the temperate forests in Northeast China [44,67]. The reason might be the difference in vegetation diversities among forests. The diversities on Jianfengling and Mount Lao are much greater than that of the temperate forests in Northeast China [38,66,67], and greater diversity leads to increased competition among closely related species [67].
One of the major factors responsible for differences in the species composition of communities is habitat heterogeneity; however, the underlying mechanisms of action differ among communities [30]. Xu examined the assembly mechanism of plant communities on the northern slope of Qinling, China and found that the phylogenetic structure converged as elevation increased [68]. Meanwhile, a contradictory trend was observed in Gutianshan, China [69] because the plant species in Qinling (high elevation) were exposed to low-temperature stress, whereas the plant species in Gutianshan (low elevation) were exposed to drought stress. The abiotic filtering effect is greatly evident under stressful environmental conditions [70]. As the nearby ocean ensures milder weather at Mount Lao compared with that of other locations at the same latitude, the phylogenetic structure of adults in the present study did not display distinct patterns along the elevation gradient (from 0 to 800 m), which is consistent with a previous study by Zhang et al. [39]. However, the phylogenetic structure of saplings was more convergent at higher elevations (Figure 3), indicating that saplings may be highly sensitive to temperature stress. Moreover, the phylogenetic structure of adults was negatively correlated with soil AN content (Figure 3), whereas the phylogenetic structure of saplings was not, suggesting that, as plants grow older, the lack of soil AN will greater affect their community assembly. This phenomenon may be due to the differences in nutrient requirements between adults and saplings [71]. In addition, our study validated the work of Dong et al. and Zhang et al. in demonstrating that conductivity (CON), available phosphorus (AP), and nitrate nitrogen (NN) were not closely associated with community phylogenetic structure [72,73].
The results of GDM in our study showed that all selected variables (screened by GDM) influenced the dispersion pattern of both adults and saplings, although each factor had a different importance. Geographic distance and soil AN were significant predictors for adults, while geographic distance and elevation were significant predictors for saplings (Table 3). These results suggested that community assembly was governed by both dispersal limitation and abiotic filtering [74,75]. Soil AN content was the most important predictor for adults, while geographical distance and elevation were the most important predictors for saplings (Table 3). This may be attributed to the above inference that adults need more AN for physiological functions, while saplings are more sensitive to changes in the microenvironment across geographic and elevational gradients. Since the summed relative importance of all environmental predictors was much larger than the relative importance of spatial predictor (geographic distance) for adults, the effect of abiotic filtering might be greater than that of dispersal limitation. This result further verified the findings of a previous study showing that deterministic processes played a more substantial role in the community composition of temperate forests than they did in that of tropical rainforests [76].
According to previous studies, the typical percent deviance explained values for models of compositional dissimilarity range from 20 to 50% [76]. The interpretation rates of our models were relatively low (only 12.91% for adults and 24.88% for saplings) (Table 3). This result may be due to the lack of consideration of other environmental variables such as soil temperature and moisture in the present study. Mount Lao has a complex topography; thus, elevation, temperature, and precipitation may not sufficiently account for the influence of the microenvironment on community assembly. Additionally, the effect of biotic interactions on community assembly could not be reflected in GDM models, which may be another reason for the low interpretation rates. In addition, we obtained different species of saplings and adults in the survey (saplings had 45 species not represented in adults, and adults had 17 species not present in saplings). The biodiversity of saplings is higher, which might be caused by two reasons: first, some tree species will never grow to the adult stage because of biotic or abiotic reasons; second, based on the 20 × 20 plots, we may have sampled more individual saplings than adults, increasing the chance to find more species in the sapling stage. The higher biodiversity of saplings might cause higher explained values of GDM.

5. Conclusions

In this study, we identified the prevalent forces that drive species distribution within forests at different growth stages on Mount Lao using phylogenetic diversity analyses. Overall, in the community assembly of saplings, the relative force of abiotic filtering was stronger than that of biotic interactions, whereas the opposite was true for the community assembly of adults. Furthermore, our findings showed that deterministic processes played a more significant role than stochastic processes in local-scale temperate forests according to the different interpretation rates of geographic distance and environmental factor distance in GDM. As plants grow, nitrogen limitation may replace dispersal limitation and elevation as the main factor affecting community assembly in Mount Lao.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/d15040507/s1, Figure S1: The numerical representation of the slope direction; Table S1: Sapling list; Table S2: Adult list; Table S3: Environmental and geographic information for each of the 69 plots; Table S4: Functional traits of main adults; Table S5: NRIs of adults and saplings for each of the 69 plots.

Author Contributions

Conceptualization, X.J., Q.H. and X.G.; methodology, X.J. and Q.H.; software, X.J., H.L. and J.Y.; validation, Q.H. and X.G.; formal analysis, X.J. and H.L.; investigation, W.L. and J.Y.; resources, Q.H.; writing—original draft preparation, X.J.; writing—review and editing, X.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Natural Science Foundation of China (31800374), Shandong Provincial Natural Science Foundation (ZR2019BC083), Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration (SHUES2021A11) and the Research Foundation for Advanced Talents of Qingdao Agricultural University (663/1121036).

Data Availability Statement

The data presented in this study are available in Supplementary Material.

Acknowledgments

We would like to thank Shaoying Sun, Zengqiang Liu, Changle Liu and other students from Qingdao Agricultural University for their help in field investigation and sampling. We also greatly thank Yunquan Wang and Jiangshan Lai from Institute of Botany, the Chinese Academy of Sciences for their help during statistical analyses.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Diversity 15 00507 g0a1 550
Figure A1. Results of Pearson’s correlation analyses of environmental factors and net relatedness index (NRI) of forest communities on Mount Lao, northern China. ELE: elevation; SLO: slope; POS: position; ASP: aspect; SOM: soil organic matter; CON: conductivity; AP: available phosphorus; NN: nitrate nitrogen; AN: ammonium nitrogen; AK: available potassium. Asterisks indicate significant effects: “**” p ≤ 0.01, “*” p ≤ 0.05.
Figure A1. Results of Pearson’s correlation analyses of environmental factors and net relatedness index (NRI) of forest communities on Mount Lao, northern China. ELE: elevation; SLO: slope; POS: position; ASP: aspect; SOM: soil organic matter; CON: conductivity; AP: available phosphorus; NN: nitrate nitrogen; AN: ammonium nitrogen; AK: available potassium. Asterisks indicate significant effects: “**” p ≤ 0.01, “*” p ≤ 0.05.
Diversity 15 00507 g0a1

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Figure 1. Locations of the 69 (20 m × 20 m) forest plots sampled along the elevational gradient of Mount Lao, northern China. The plots were established on temperate deciduous broad-leaf and temperate coniferous forests, and adult trees as well as saplings were collected.
Figure 1. Locations of the 69 (20 m × 20 m) forest plots sampled along the elevational gradient of Mount Lao, northern China. The plots were established on temperate deciduous broad-leaf and temperate coniferous forests, and adult trees as well as saplings were collected.
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Figure 2. Net relatedness index (NRI) of tree adults and saplings in 69 plots in secondary forests on Mount Lao, northern China. In box plots, data are shown as median (line) ± the interquartile range (boxes), ±1.5 times the interquartile range (whiskers). Different letters ‘a’ and ‘b’ indicate significant differences at the p ≤ 0.05 level.
Figure 2. Net relatedness index (NRI) of tree adults and saplings in 69 plots in secondary forests on Mount Lao, northern China. In box plots, data are shown as median (line) ± the interquartile range (boxes), ±1.5 times the interquartile range (whiskers). Different letters ‘a’ and ‘b’ indicate significant differences at the p ≤ 0.05 level.
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Figure 3. The results of linear mixed effect model of adult trees and saplings, respectively, taking transects as a random factor, net relatedness index (NRI) as a response variable, and ammonium nitrogen (AN, mg/kg) as an explanatory variables for adult trees; while taking net relatedness index (NRI) as a response variable and elevation (ELE, m) as an explanatory variables for saplings. The different colours represent the plots from different transects.
Figure 3. The results of linear mixed effect model of adult trees and saplings, respectively, taking transects as a random factor, net relatedness index (NRI) as a response variable, and ammonium nitrogen (AN, mg/kg) as an explanatory variables for adult trees; while taking net relatedness index (NRI) as a response variable and elevation (ELE, m) as an explanatory variables for saplings. The different colours represent the plots from different transects.
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Figure 4. GDM for phylogenetic βsor of adults in secondary plant communities on Mount Lao. Each blue dot represents a site-pair. The units of the x-axis variables are original units. The y-axis indicates a transforming function “f” to each environmental variable, which is fitted by I-splines, and the unit is linked to community dissimilarity. The I-splines are partial regression fits and represents the importance of each predictor in determining patterns of β-diversity and total amount of compositional dissimilarity associated with each variable (the greater the ecological distance, the greater the explanatory power of the predictor). The shape of each function indicates how the rate of compositional dissimilarity varies along gradients, and the maximum height reached by each curve indicates the total amount of dissimilarity associated with each variable, maintaining all other variables as constant. If the curve reaches an asymptote, it indicates saturation of dissimilarity, and the variation of predicted ecological distance beyond it will not increase the dissimilarity. ELE: elevation; SLO: slope; POS: position; ASP: aspect; SOM: soil organic matter; CON: conductivity; AP: available phosphorus; NN: nitrate nitrogen; AN: ammonium nitrogen; AK: available potassium.
Figure 4. GDM for phylogenetic βsor of adults in secondary plant communities on Mount Lao. Each blue dot represents a site-pair. The units of the x-axis variables are original units. The y-axis indicates a transforming function “f” to each environmental variable, which is fitted by I-splines, and the unit is linked to community dissimilarity. The I-splines are partial regression fits and represents the importance of each predictor in determining patterns of β-diversity and total amount of compositional dissimilarity associated with each variable (the greater the ecological distance, the greater the explanatory power of the predictor). The shape of each function indicates how the rate of compositional dissimilarity varies along gradients, and the maximum height reached by each curve indicates the total amount of dissimilarity associated with each variable, maintaining all other variables as constant. If the curve reaches an asymptote, it indicates saturation of dissimilarity, and the variation of predicted ecological distance beyond it will not increase the dissimilarity. ELE: elevation; SLO: slope; POS: position; ASP: aspect; SOM: soil organic matter; CON: conductivity; AP: available phosphorus; NN: nitrate nitrogen; AN: ammonium nitrogen; AK: available potassium.
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Figure 5. GDM for phylogenetic βsor of saplings in secondary plant communities on Mount Lao. Each blue dot represents a site-pair. ELE: elevation; SLO: slope; POS: position; ASP: aspect; SOM: soil organic matter; CON: conductivity; AP: available phosphorus; NN: nitrate nitrogen; AN: ammonium nitrogen; AK: available potassium.
Figure 5. GDM for phylogenetic βsor of saplings in secondary plant communities on Mount Lao. Each blue dot represents a site-pair. ELE: elevation; SLO: slope; POS: position; ASP: aspect; SOM: soil organic matter; CON: conductivity; AP: available phosphorus; NN: nitrate nitrogen; AN: ammonium nitrogen; AK: available potassium.
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Table
Table 1. Locations of sample plots on Mount Lao.
Table 1. Locations of sample plots on Mount Lao.
TransectLocationSample Plot NumberElevation Range (m)
1Shangqing1–110–500
2Taiqing12–180–300
3Jufeng19–32300–800
4Yangkou33–410–500
5Beijiushui42–55300–700
6Huayan56–6950–600
Table
Table 2. Phylogenetic signals of functional traits of investigated plants on Mount Lao.
Table 2. Phylogenetic signals of functional traits of investigated plants on Mount Lao.
Functional TraitsBlomberg’s K-Valuep-Value
SLA1.8072 0.0020
LDMC0.3839 0.2168
WD0.1967 0.7755
LPC1.5306 0.0195
LNC1.7398 0.0155
LCC1.4637 0.0156
SLA: specific leaf area; LDMC: leaf dry matter content; WD: wood density; LNC: leaf nitrogen content; LPC: leaf phosphorus content; and LCC: leaf carbon content.
Table
Table 3. Percent deviance in the strength of phylogenetic associations on geographic distance and environmental variables (ELE: elevation; SLO: slope; ASP: aspect; pH; SOM: soil organic matter; CON: conductivity; AP: available phosphorus; NN: nitrate nitrogen; and AN: ammonium nitrogen) explained by generalized dissimilarity models (GDMs), and each predictor’s importance and significance.
Table 3. Percent deviance in the strength of phylogenetic associations on geographic distance and environmental variables (ELE: elevation; SLO: slope; ASP: aspect; pH; SOM: soil organic matter; CON: conductivity; AP: available phosphorus; NN: nitrate nitrogen; and AN: ammonium nitrogen) explained by generalized dissimilarity models (GDMs), and each predictor’s importance and significance.
βsor of Adultsβsor of Saplings
Percent Deviance Explained (%)12.9124.88
Predictor importancePredictorImportance
Geographic distance5.05 **44.18 **
ELE4.5718.18 **
SLO4.053.12
ASP0.862.81
pH1.190.36
SOM1.321.40
CON1.111.00
AP2.520.38
NN6.532.15
AN64.28 **3.73
Asterisks indicate significant effects; “**” p ≤ 0.01.
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Jiang, X.; Guo, X.; Lu, H.; Yang, J.; Li, W.; Hao, Q. Distinct Community Assembly Mechanisms of Different Growth Stages in a Warm Temperate Forest. Diversity 2023, 15, 507. https://doi.org/10.3390/d15040507

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Jiang X, Guo X, Lu H, Yang J, Li W, Hao Q. Distinct Community Assembly Mechanisms of Different Growth Stages in a Warm Temperate Forest. Diversity. 2023; 15(4):507. https://doi.org/10.3390/d15040507

Chicago/Turabian Style

Jiang, Xiaolei, Xiao Guo, Huicui Lu, Jinming Yang, Wei Li, and Qing Hao. 2023. "Distinct Community Assembly Mechanisms of Different Growth Stages in a Warm Temperate Forest" Diversity 15, no. 4: 507. https://doi.org/10.3390/d15040507

APA Style

Jiang, X., Guo, X., Lu, H., Yang, J., Li, W., & Hao, Q. (2023). Distinct Community Assembly Mechanisms of Different Growth Stages in a Warm Temperate Forest. Diversity, 15(4), 507. https://doi.org/10.3390/d15040507

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