Research Article |
Corresponding author: Wen-Yong Guo ( wyguo@des.ecnu.edu.cn ) Academic editor: Elizabeth Wandrag
© 2025 Yan-Yan Wang, Kun Guo, Rui-Ling Liu, Hasigerili, Miao-Miao Zheng, Yuan Gao, Ming-Shui Zhao, Jian Zhang, Wen-Yong Guo.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Wang Y-Y, Guo K, Liu R-L, Hasigerili, Zheng M-M, Gao Y, Zhao M-S, Zhang J, Guo W-Y (2025) Similar alpha yet varied beta functional diversities between invasive and native plant species along an elevational gradient. NeoBiota 99: 1-18. https://doi.org/10.3897/neobiota.99.143495
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Illuminating the invasive strategies of alien species in mountainous regions is critical to preventing the increasing frequency of invasion events and enhancing our understanding of the vulnerability of these ecosystems. Here, we investigated differences in diversity between invasive and native species across an elevational gradient through field experiments conducted along a 1200 m range, combined with measurements of plant functional traits and environmental factors. Our results revealed significant distinctions in diversity patterns between invasive and native species when considering multiple aspects of taxonomic and functional diversity at both α and β levels. Native species showed clear species replacement along elevation, while invasive species at higher elevations tended to be a subset of those found at lower elevations. Although invasive and native species shared relatively similar functional α diversity, they exhibited more significantly different functional β diversity. Elevation-related environmental factors played a major role in shaping functional dissimilarity and species similarity across plots. In contrast, functional redundancy at both α and β levels was more influenced by species status. Our findings highlight that invasive species exhibit a dissimilar strategy compared to native species along the elevational gradient and emphasize the importance of decreasing the introduction of alien species to better manage and prevent plant invasions in mountainous regions.
Environmental changes, functional redundancy, invasive plants, mountainous invasion, multi-dimensional diversities
Biological invasions significantly undermine biodiversity and ecosystem services, posing substantial risks to the economy, food security, and human health (
As invasive species continue to spread upward, researchers are increasingly concerned with whether biodiversity patterns differ between native and invasive species (
Taxonomic diversity provides certain measurements of biodiversity, but it does not consider the differences among species, such as functional aspects (
Recently, a novel framework has been proposed that integrates both taxonomic and functional diversity into mathematical algorithms and ecological theory, providing a comprehensive tool for examining each of the α and β biodiversity from multiple perspectives simultaneously (
Here, we constructed an experiment in the West Tianmu Mountain National Nature Reserve, located in Hangzhou, Zhejiang Province, one of the economic centers in East China, where invasive species have been found across all elevations, posing a significant threat to the local environment and economy (
The experiment was carried out at the West Tianmu National Natural Reserve. Located in a subtropical climate region (30°18'-30°21'N, 119°24'-119°27'E), the mountain’s elevational gradient ranges from 300 m to 1,506 m a.s.l., with an average annual temperature of 8.8 °C at the summit and 14.8 °C at the foot of the hill (
We established 1 m2 plots being 1–3 m from the roadside at low (< 500 m) and high (> 1000 m) elevations, given the presence of either cliff or rocks alongside roads between 500 and 1000 m, rendering it unsuitable for setting up surveying plots. In total, we established 15 low-elevation plots and 22 high-elevation plots, with a minimum horizontal distance of 50 m between sample plots to reduce spatial autocorrelation.
We identified the species in the plots based on the “Flora of Tianmu Mountain” (
To capture the plant’s functional information, we measured nine functional traits for every species. Ten mature and healthy individuals of each species were selected to measure their height (cm), ground diameter (mm), and leaf thickness (mm) in situ. Three mature leaves were collected from the measured individuals and brought back to the laboratory in a cooling box to measure leaf area (mm2), fresh weight (mg), dry weight (mg) after drying, and leaf nitrogen content (%). For species with fewer than 10 individuals, trait information was measured for all mature and healthy individuals. In addition, we calculated specific leaf area (the ratio of leaf area and leaf dry weight, mm2/mg) and leaf dry matter content (the ratio of leaf dry weight and leaf fresh weight, mg/mg). We further calculated the mean value of each trait for each species.
For each plot, the temperature (°C) of soil (6 cm below ground, T.soil), ground (T. ground), air (15 cm above ground, T.air), and soil humidity (%) were obtained using a TMS-4 recorder (
Species richness was calculated for native and invasive species separately in each plot. To demonstrate the differences in species composition among species status along the elevation, we performed the Nonmetric Multidimensional Scaling (NMDS) based on Bray-Curtis distances with the R package Vegan (
To compute native and invasive species’ functional diversity per plot, we scaled the trait matrices and calculated the relative functional Euclidean distance (the ratio of the original functional distance to the maximum functional distance) between species within plots. Simpson’s dominance (D) is the probability that two individuals randomly selected from a plot will belong to the same species and is a complementary index of Simpson’s diversity. Functional diversity (Q), Rao’s quadratic diversity, is the mean of the dissimilarities between each pair of species i and j (dij) within plots, weighted by the species abundance (
D = ∑Ni=1 p2i (1)
Q = ∑Ni,j=1 pi pj dij (2)
R = 1 – D – Q (3)
where N is the number of species in each plot, p is the species’ relative abundance in each plot, and dij is the distance function between the i-th and j-th species.
Species similarity SBC is the complementary index of classical Bray-Curtis dissimilarity, which depicts the taxonomic similarity based on the species relative abundance between plots (dij=1, i and j denote two different species) (
SBC = ∑Ni=1 min{pjh, pjk} (4)
DKG = minπ ∑Ni=1 ∑Nj=1π(i,j) × dij (5)
Rβ = 1– SBC – DKG (6)
where N is the number of species in each plot, pjh and pjk are the j-th species’ relative abundance in the h-th and k-th plot respectively π(i,j) is the i-th species’ relative abundance in the h-th plot matched with j-th species in the k-th plot, and dij is the functional distance between the i-th and j-th species.
The results of functional α and β diversity were illustrated on the ternary diagram by the R package “ggplot2” (
To explore how species status and environmental factors affect the different aspects of functional α and β diversity, we first applied a principal component analysis (PCA) for all environmental factors with the R package “FactoMineR”, and the first two PC axes that explained 61.6% variance of the environmental factors were used as the environmental variables (Appendix
All data analyses were carried out in R version 4.3.1 (
Noticeably, all of the surveyed plots observed the presence of invasive species. Native plant species exhibited significantly higher species richness compared to invasive species, irrespective of elevation (p < 0.05). Additionally, there was no significant difference in species richness between low and high elevations for either native or invasive species (Fig.
(A) Differences in species richness of native species (Native) and invasive species (Invasive) between the low and high elevations. Different letters indicate a significant difference (p < 0.05) from multiple post hoc comparisons with holm-adjustment of one-way ANOVA. Two-dimensional NMDS ordination of all plots showed differences in species composition of (B) Native and (C) Invasive species at different elevations (the stress values equal to 0.12 and 0.04, respectively). Shadow ellipses represent 95% confidence intervals around the centroids for the point types.
Overall, functional α and β diversity differed between invasive and native species, with especially pronounced distinctions in functional β diversity (Fig.
Ternary diagrams of functional (A) α diversity and (C) β diversity for native and invasive species at low and high elevations. One-way ANOVA with holm-adjusted multiple comparisons for each of the functional (B) α diversity and (D) β diversity components were shown in boxplots, with different letters indicating significant differences (p < 0.05). D, species dominance within plots; Q, functional diversity within plots; R, functional redundancy within plots; SBC, species similarity among plots; DKG, functional dissimilarity among plots; and Rβ, functional redundancy among plots.
Species status and the first two environmental PCs (PC1 and PC2) collectively explained a substantial portion of the variation in functional α and β diversity (Fig.
Stacked bar plots demonstrate the explained variation in functional α (A) and (B) β diversity. Each bar represents the contribution of species status (invasive/native), the first two PC axes derived from environmental factors, and residuals. D, species dominance within plots; Q, functional diversity within plots; R, functional redundancy within plots; SBC, species similarity among plots; DKG, functional dissimilarity among plots; and Rβ, functional redundancy among plots.
With the increasing frequency of invasion events in mountainous regions, the differences in multiple diversity patterns between invasive and native species deserve deeper exploration to reduce the consequential damage that would follow. Considering the complexity and lack of harmonization of multiple diversity, we integrated taxonomic and functional information via decomposed α and β diversity methods to reveal the differences in diversity patterns between invasive and native species along an elevational gradient. We found that species of distinct statuses at separate elevations held marked differences in patterns of multiple diversity, especially in β diversity, and the explanatory power of drivers was divergent among indices.
Consistent with our hypotheses, invasive species displayed higher species dominance (D) and species similarity (SBC) compared to native species. Our observation revealed that invasive species found at higher elevations were a subset of the invasive species at lower elevations. Notably, invasive species at high elevations, Erigeron annuus (L.) Pers., Conyza canadensis (L.) Cronquist, Bidens frondosa L., Solidago canadensis L., Crassocephalum crepidioides (Benth.) S. Moore, all belonging to the Asteraceae family, predominantly adopted the ruderal strategy, characterized by traits like rapid dispersal and reproduction (
The functional diversity differences between invasive and native species further clarified the competitive strategies of invasive species. At lower elevations, invasive species occupied functional niche widths comparable to those of native species, suggesting they had an equivalent advantage in colonization despite lower species richness and shorter residence time. Remarkably, at higher elevations, invasive species exhibited lower functional α diversity but higher functional β diversity compared to native species. The reduced functional diversity Q of invasive species at higher elevations was related to their lower species richness, though a substantial proportion remained unexplained. In our study, many invasive species from the same family exhibited significant trait dissimilarity across different plots. The greater trait dissimilarity of invasive species compared to native species across elevations indicates a stronger resistance of these ruderal-strategy invasive species to environmental filtering (
The observed pattern of functional redundancy in our study was counterintuitive, as invasive species, despite having greater species dominance (D) and species similarity (SBC), showed lower functional α and β redundancy compared to native species. This can probably be explained by the limiting similarity hypothesis (
According to our results, the strong biological interactions generated by invasive species outweigh the environmental filtering effect and ultimately lead to invasive species’ upward spread trend along elevation. In the context of dramatic global change, alien species are dispersing intentionally or accidentally at a rapid speed. Once they overcome geographical barriers and become invasive, biotic interactions would dominate the process of colonization even in mountainous areas with harsh environments (
By thoroughly examining various aspects of taxonomic or functional α and β diversity, our study provides a more comprehensive exploration of both invasive and native plant diversity patterns in mountain regions, offering new insights into the mechanisms behind invasion events. We found distinct differences between invasive and native species in terms of distribution and diversity variation. Native species demonstrated a stronger elevational preference, with notable species replacement, whereas invasive species at higher elevations were largely subsets of those at lower elevations. While invasive and native species occupied relatively similar α diversity spaces, their β diversity spaces were more significantly differentiated, likely due to the strong adaptive capacity and more favorable competitive strategies of invasive species. Our study further confirms the utility of the novel diversity decomposition framework to provide a deeper understanding of the factors driving the distinct patterns between invasive and native species across environmental gradients.
The authors have declared that no competing interests exist.
No ethical statement was reported.
The project was supported by the Natural Science Foundation of China (grant no. 32171588 and 32471676 awarded to WYG; grant no. 32301386 awarded to KG), and Shanghai Sailing Program (grant no. 22YF1411700 awarded to KG). This is a part of work based on the BEST (Biodiversity along Elevational gradients: Shifts and Transitions) cooperation network.
Yan-Yan Wang: Conceptualization, Data Curation, Formal analysis, Methodology, Visualization, Writing - original draft, Writing - review & editing. Kun Guo: Data curation, Formal analysis, Methodology, Visualization, Funding Acquisition, Writing - Review & Editing. Rui-Ling Liu: Data Curation, Writing - Review & Editing. Hasigerili: Data Curation, Writing - Review & Editing. Miao-Miao Zheng: Data Curation, Writing - Review & Editing. Yuan Gao: Data Curation, Writing - Review & Editing. Ming-Shui Zhao: Data Curation. Jian Zhang: Data Curation, Writing - Review & Editing. Wen-Yong Guo: Conceptualization, Project administration, Funding Acquisition, Supervision, Methodology, Writing - Original draft, Writing - Review & Editing.
Yan-Yan Wang https://orcid.org/0009-0007-2496-0179
Kun Guo https://orcid.org/0000-0001-9597-2977
Rui-Ling Liu https://orcid.org/0000-0002-0950-5561
Hasigerili https://orcid.org/0009-0004-0084-186X
Miao-Miao Zheng https://orcid.org/0009-0006-2699-1617
Yuan Gao https://orcid.org/0009-0004-8150-1292
Jian Zhang https://orcid.org/0000-0003-0589-6267
Wen-Yong Guo https://orcid.org/0009-0005-6980-1302
All of the data that support the findings of this study are available in the main text or Supplementary Information.
Data utilized for the analysis
Data type: xlsx