Functional Segregation of Resource Utilization Strategies between Invasive and Native Plants and Invasion Mechanisms in the Water Level Fluctuation Zone: A Case Study of Pengxi River in Three Gorges Reservoir, China

: The ecosystem of the water level fluctuation (WLF) zone of the Three Gorges Reservoir (TGR) is highly vulnerable and sensitive due to its unique cyclical flooding and drought conditions. The ecological impact of biological invasion in this area is particularly severe, making it crucial to study the differences in resource utilization strategies between invasive plants (IPs) and native plants (NPs) using functional traits to explore the mechanisms of invasion. We selected the WLF zone of Pengxi River in the TGR area and conducted a multi-scale study along the elevation gradient. The results reveal that at the regional scale, IPs have a larger height and specific leaf area, smaller leaf tissue density, and specific root length compared to NPs, showing a preference for enhancing aboveground resource acquisition over leaf defense capabilities. They allocate more tissue construction resources to their roots to withstand environmental pressures, which may be the key to their successful intrusion, highlighting the role of niche differentiation. On the community scale, the H and SLA of IPs and NPs are positively correlated with elevation, while the LTD of IPs shows a negative correlation. At elevations of 175 m and below, IP and NP exhibit functional convergence, while above 175 m, functional divergence was observed. This indicates that although the different resource utilization strategies are crucial for successful IP invasion, the environmental filtering from periodic floods and drought pressures play a significant role in community assembly in the WLF zone, allowing IP to integrate into habitats with similar functional characteristics already inhabited by NP and establish their own communities.


Introduction
The global concern surrounding invasive species has been growing due to its profound [1][2][3].Not only do invasive species threaten global biodiversity, but they also lead to substantial economic losses [4].Unfortunately, there is no indication that the number of invasive species will decline in the near future [5].As a result, both scholars and society have come to recognize the importance of addressing the issue of biological invasions.Plant functional traits are observable characteristics that have evolved in individual plants over time to adapt to their specific habitats.
Plant functional traits refer to a set of observable characteristics that have developed within individual plants over time to suit their specific habitats [6].These traits are crucial for enhancing plants' survival and functioning in a dynamic environment.Furthermore, they serve as indicators for studying how plants respond and adapt to changes in their surroundings [7], which are usually closely related to resource utilization strategies and functional niches [8].Comparing and analyzing functional trait variations between native and invasive species has become crucial in the field of plant invasion ecology [9].It is crucial to identify specific traits linked to invasiveness to predict potential invasive species and effectively manage established invaders [10].
In the field of invasion ecology, a central focus is understanding the mechanisms through which invasive plants (IPs) spread.This comprehension aids in predicting their potential to establish populations in specific ecosystems [3,11,12].Various perspectives have been proposed to elucidate species coexistence mechanisms.Niche differentiation emphasizes interspecies competition, suggesting that functional similarity heightens competition and exclusion, hindering species coexistence [13].Conversely, environmental filtering underscores the significance of abiotic factors, indicating that similar habitat conditions promote functional similarity among coexisting species in the same habitat [14].Moreover, the Darwin naturalization hypothesis (DNH) and Darwin pre-adaptation hypothesis (DPH) highlight the role of phylogenetic relationships in the successful invasion of plants [15][16][17].The DNH suggests that establishing sustainable populations of alien plants in ecosystems with a high number of native species is challenging [18].The DPH argues that close phylogenetic relationships imply similar ecological requirements, enhancing the adaptability of alien plants to the local environment.These two hypotheses that seemed contradictory at the time were collectively referred to as the "Darwin's naturalization conundrum" [19,20].Recent studies have shown that these seemingly contradictory hypotheses may not be entirely incompatible [19,21].Depending on the specific environment or scale of the study, both hypotheses can effectively predict the outcomes of biological invasions.Research conducted on plants in the United States revealed that at larger spatial scales, environmental filtering traits tend to have a greater impact than competitive traits.This finding has provided a plausible explanation for reconciling Darwin's conflicting hypotheses across different spatial scales [19], highlighting the significance of the scale of research.Differences in traits between invasive and native species are often seen as a key mechanism for successful invasions [22,23].Understanding these trait-based approaches to invasion success involves comparing the traits of invasive species with those of native species, either within a community or between invasive and native species [24].Therefore, conducting a multi-scale study based on functional traits is essential for comprehending the mechanism of invasive plants in the WLF zone.Focusing research on understudied and threatened ecosystems also allows us to develop a more holistic understanding of the ecological dynamics of IP [25].
The Three Gorges Reservoir (TGR) in China is widely recognized as the largest hydraulic and hydroelectric project in the world.Its operational strategy, known as "storing clear water and discharging turbid water", leads to fluctuations in the water level within the reservoir area.Specifically, the water level rises to 175 m during winter and decreases to 145 m during summer, creating a significant water level fluctuation (WLF) zone with a vertical difference of 30 m [26].The TGR underwent experimental impounding from 2006 to 2007, reaching 175 m in 2009.The WLF area of the TGR was officially established in 2010.These annual flooding and drought events have a profound impact on plant communities, requiring the development of unique ecological strategies to thrive in this specific habitat [27].Consequently, these strategies influence the morphological and physiological adaptive characteristics of these plants [28].The cyclic changes between land and water levels within the zone have destabilized the plant community structure [29].Human activities and alterations in the natural water level fluctuations of the Yangtze River's ecosystem have created favorable conditions for the spread of non-native plant species, leading to challenges from invasive species in the TGR area [30,31].Studies showed a significant increase in alien species in the TGR area between 2003 and 2015 [32].Failure to address this trend could result in severe damage to local plant resources, reduced genetic diversity, habitat disruption, decreased plant community diversity [33], and pose a substantial threat to the fragile ecosystem.After 14 years of the WLF zone's establishment, the presence of widespread IPs in various parts of the area indicates a challenging invasion scenario.To protect the ecological integrity of this zone and enhance biodiversity, a comprehensive investigation and research on IPs within the WLF zone, along with the implementation of appropriate control measures, are crucial [34].Recent studies have focused on the impact of habitat characteristics on IPs within the WLF area, such as their proximity to the dam [35], land use composition, surrounding landscape [36], and the distribution patterns of invasive plant species [31].However, there is a lack of systematic exploration concerning the resource utilization patterns of IPs in this zone and their invasion mechanisms from a functional trait perspective.There is evidence that freshwater wetlands are particularly vulnerable to invasive impacts [37].It is crucial to analyze the resource acquisition and allocation patterns of IPs in the WLF zone based on functional traits and compare them with native plants (NPs) to enhance our understanding of the adaptation and invasion mechanisms of wetland plant communities in this zone.Current research on the characteristics of invasive plants in China through multi-species comparison is still in its preliminary stage [38], so the results can offer a theoretical foundation for future scientific predictions and the prevention of plant invasions in the zone.
We conducted a multi-scale study on the functional traits of IP and NP in the Pengxi River of the TGR area to investigate the following: (1) the differences in functional traits between IP and NP at regional and community scales under various inundation gradients; (2) the mechanisms of IP invasion in the WLF zone.Our results highlight distinct resource utilization strategies between IPs and NPs, offering new insights into the mechanisms of plant invasion in the WLF zone.

Study Area
The study area is located in Pengxi River, Kaizhou District, Chongqing, which lies in the hinterland of TGR (Figure 1).This area is a major tributary on the left bank of the Yangtze River, significantly impacted by the impoundment of the TGR.The terrain is predominantly flat, with extensive alluvial plains on both sides.Consequently, the WLF zone in the Kaizhou District is the largest among all the districts and counties in the TGR area, covering 42.78 km 2 , which represents 12.3% of the total area of the WLF zone in the TGR.The study area experiences a subtropical humid monsoon climate, with an average annual temperature of approximately 18.5 • C and annual precipitation of around 1385 mm.To mitigate the effects of the TGR impoundment, the Kaizhou district government built a water level regulation dam downstream of the urban area, reducing the water level drop from 30 m to 4.72 m.This led to the creation of Hanfeng Lake, an urban lake, causing fluctuations in the water levels of Hanfeng Lake and Pengxi River in the research area in line with the TGR water levels.The Three Gorges project and subsequent resettlement efforts have also triggered significant changes in land use around the WLF zone, heightening the risk of invasion by non-native species.The study area is mainly composed of herbaceous plants and sparse shrubs and trees (natural growth and artificial planting).

Community Surveys and Identification of IP
The survey was conducted in July and August when the water level fluctuation (WLF) zone was fully exposed, and plant growth was at its peak.Eight sampling sites were selected in the Pengxi River Basin, including Wuyangba, Furongba, Shilongchuan Bridge, Toudao River Estuary, Dishuiba, Qukouba, Dalangba, and Baijia Stream (Table S3).These sampling points were evenly distributed in the Pengxi River basin, with similar substrate characteristics and minimal human interference.The elevation of these sites covers most of the elevation range of the WLF zone of the TGR, and water level fluctuations align with this pattern.Parallel sample lines were established at each sample point, ranging from the lowest to the highest elevation.These lines were strategically located at different sites: 6 lines at Wuyangba, 3 lines at Furongba, the Shilongchuan Bridge, Toudao River estuary, and Dishuiba, Dalangba, 4 lines at Qukouba, and 7 lines at the Baijia Stream.Along each sample line, sample plots were placed at different elevations.At each elevation, a single sample plot measuring 10 m × 10 m was established.Within each sample plot, at least five herbaceous sample squares measuring 1 m × 1 m were randomly positioned using the random sampling method.Plant data, including species identification, count, height, coverage, and relevant environmental factors, were meticulously recorded.The identification of IP was based on the "Invasive Alien Species of China" (IASC) database (https://www.iplant.cn/frps,accessed on 9 April 2024), while NP identification followed the website of Flora Reipublicae Populis Sinicae (FRPS) (https://www.iplant.cn/frps;accessed on 21 May 2024) according to the description of each plant's distribution area.In this study, a total of 21 species of IPs belonging to 11 families, 19 genera (Table S1), and 55 species of NPs belonging to 25 families, 43 genera (Table S2), were recorded.The intensity of flooding was inversely related to elevation.Hydrological data obtained from the Yangtze River Hydrological Network

Community Surveys and Identification of IP
The survey was conducted in July and August when the water level fluctuation (WLF) zone was fully exposed, and plant growth was at its peak.Eight sampling sites were selected in the Pengxi River Basin, including Wuyangba, Furongba, Shilongchuan Bridge, Toudao River Estuary, Dishuiba, Qukouba, Dalangba, and Baijia Stream (Table S3).These sampling points were evenly distributed in the Pengxi River basin, with similar substrate characteristics and minimal human interference.The elevation of these sites covers most of the elevation range of the WLF zone of the TGR, and water level fluctuations align with this pattern.Parallel sample lines were established at each sample point, ranging from the lowest to the highest elevation.These lines were strategically located at different sites: 6 lines at Wuyangba, 3 lines at Furongba, the Shilongchuan Bridge, Toudao River estuary, and Dishuiba, Dalangba, 4 lines at Qukouba, and 7 lines at the Baijia Stream.Along each sample line, sample plots were placed at different elevations.At each elevation, a single sample plot measuring 10 m × 10 m was established.Within each sample plot, at least five herbaceous sample squares measuring 1 m × 1 m were randomly positioned using the random sampling method.Plant data, including species identification, count, height, coverage, and relevant environmental factors, were meticulously recorded.The identification of IP was based on the "Invasive Alien Species of China" (IASC) database (https://www.iplant.cn/frps,accessed on 9 April 2024), while NP identification followed

Sampling and Measurement of Plant Functional Traits
In each sample area, plants with coverage exceeding 40% were classified as dominant species.In each sample area where dominant IP species were present, 5 intact target individuals that were well-exposed to light, fully developed, and of similar size were selected.Furthermore, 5 companion NPs with a coverage rate exceeding 40% were also included in the selection process.On-site measurements were conducted to assess the characteristics of the sampled plants, including their roots, stems, leaves, and other relevant indicators.Each plant yielded 3-5 undamaged leaves, free from shade and pests.Moreover, primary stems and roots were collected and transported to the laboratory for the determination and calculation of functional traits (Table 1).These selected traits represent plant strategies for acquiring, utilizing, and conserving resources, as well as for exploiting different temporal niches [39,40].The determination of plant functional trait indicators was referred to as the standard protocol [41].Leaf area measurements were conducted using ImageJ 1.53c.The accumulation status of leaf biomass, related to the stretching and defense forces of tissues.

Statistical Analysis
At the regional scale, principal component analysis (PCA) was employed to examine the mean functional trait values of native and invasive plants within the study area.A one-way ANOVA was conducted to determine if significant differences existed between these groups along various axes.The two traits exhibiting the strongest correlation with each primary axis were chosen for further investigation.On the community scale, a comparison was conducted between the character distribution observed in the survey and a null model to detect differences in character composition between actual and random communities.This comparison aided in evaluating the dominant role of ecological processes in community assembly.According to the null hypothesis, the local community reflects the random distribution of individuals and traits derived from the regional species pool across the entire landscape, with weighting based on species abundance at the regional level.This model maintains constant species abundance at the regional scale while allowing for fluctuations at the quadrat level without imposing a fixed number of species in each quadrat.The analysis was carried out using the Picante toolkit in the R software 4.3.2(999 iterations).The Community Weighted Mean (CWT) was used to quantify the average character value at the community level, weighted by the relative abundance of each species as follows: where p i is the abundance of species i at point j and T i is the average eigenvalue of species i at point j.
Our study employed the functional differences index (FD j ) to assess the functional similarity between IPs and NPs.This index quantifies the functional difference between IPs and co-existing NPs by comparing the absolute disparity in weighted trait values within a given plot to the average disparity observed across all plots at the same elevation.The computation of weighted trait values for plant species is derived from the mean trait values Forests 2024, 15, 959 6 of 18 of the plant community, which are subsequently weighted based on the relative abundance of each species [6,42].The FD j was calculated using the following equation: The FD j represents the disparity between the weighted invasive plant traits (CWTalien j ) and the weighted native plant traits (CWTnative j ) in sample j.CWTalien j refers to the weighted invasive plant traits observed in sample j, while CWTnative j represents the weighted native plant traits observed in sample j.CWTalien and CWTnative denote the weighted invasive plant traits and weighted native plant traits, respectively, across all samples.The weighted character value of the community is calculated based on the average character value of the community and weighted by the relative abundance of each species [6,42].Based on 999 randomizations, we calculated the 95% confidence interval and compared the zero prediction with the observed data by calculating the deviation from the zero prediction.When the observed FD j value exceeded the 95% confidence interval of the null model, it suggested functional divergence between invasive plants and native plants in terms of physiological and ecological characteristics, indicating niche differentiation (IPs and NPs were more different from each other than expected by chance).When FD j was observed to occur below the 95% confidence interval, it indicated functional convergence between the IPs and NPs in terms of physiological and ecological characteristics, suggesting the presence of environmental filtering (IPs and NPs were more similar to each other than expected by chance).
The data were tested for normality using the Shapiro-Wilk test and all plant functional traits were log-transformed with a base of 10 to ensure normal distribution before analysis.One-way analysis of variance (ANOVA) was used to analyze the significant differences in plant functional traits at different altitudes at the regional scale.Tukey's method was used for multiple comparisons.All data processing and mapping in this study were performed using Origin 2021 and R 4.3.2.

Differences in Plant Functional Strategies at the Regional Scale
Principal component analysis (PCA) was performed to compare the functional traits of plants between IPs and NPs at various altitudes within the WLF region at the regional scale (Figure 2).The first two principal components out of six accounted for 36.2% and 26.7% of the explained variance, respectively.Axis 1, moving from left to right, showed a gradual increase in LDMC and LTD, along with a gradual decrease in SLA, predominantly representing leaf functional traits.Axis 2, moving from top to bottom, displayed a gradual decrease in SRL and a gradual increase in H and SDMC, which mainly reflected the stem and root traits of the plants.The results highlighted differences between IPs and NPs in terms of their combinations of functional traits.Specifically, IPs showed higher SLA, H, SDMC, and lower LDMC, LTD, and SRL compared to NPs.The notable disparities observed between IPs and NPs along the PCA axis 1 and axis 2 in the WLF area indicate a functional differentiation in their strategies for resource utilization (Figure 3).

Differences in Plant Functional Traits at the Regional Scale
Based on the results of PCA, SLA and LTD were selected from axis 1, while H and SRL were selected from axis 2 for analysis.The results indicate that IPs exhibit a larger H and SLA compared to NPs, whereas SRL and LTD were lower.Specifically, IPs at elevations ranging from 165 m to 172 m significantly exceeded NP, with SLA at altitudes of 160 m, 168 m, and 175 m also surpassing NP.In contrast, SRL was observed to be lower at 170 m, 172 m, and 178 m, while LTD exhibited lower values at 160 m, 168 m, 170 m, and 175 m (p < 0.05; Figure 4).

Differences in Plant Functional Traits at the Regional Scale
Based on the results of PCA, SLA and LTD were selected from axis 1, while H and SRL were selected from axis 2 for analysis.The results indicate that IPs exhibit a larger H and SLA compared to NPs, whereas SRL and LTD were lower.Specifically, IPs at elevations ranging from 165 m to 172 m significantly exceeded NP, with SLA at altitudes of 160 observed between IPs and NPs along the PCA axis 1 and axis 2 in the WLF area indica a functional differentiation in their strategies for resource utilization (Figure 3).

Differences in Plant Functional Traits at the Regional Scale
Based on the results of PCA, SLA and LTD were selected from axis 1, while H an SRL were selected from axis 2 for analysis.The results indicate that IPs exhibit a larger and SLA compared to NPs, whereas SRL and LTD were lower.Specifically, IPs at elev tions ranging from 165 m to 172 m significantly exceeded NP, with SLA at altitudes of 1

Response of Functional Traits at the Community Scale to Elevation
Based on the PCA analysis outcomes, four traits were chosen for examination at th community scale as follows: SLA and LTD of axis 1; H and SRL of axis 2. The results indi cate that the IP communities exhibited higher H and SLA and lower SRL and LTD.Both the H and SLA of IPs and NPs have a significant positive correlation with elevation at th community scale.The LTD of IPs was significantly negatively correlated with elevation The slope absolute values of the H, SLA, and LTD of IPs were higher than those of NPs while the slope absolute value of the SRL of NPs was higher than that of IPs (Figure 5 Table 2).

Response of Functional Traits at the Community Scale to Elevation
Based on the PCA analysis outcomes, four traits were chosen for examination at the community scale as follows: SLA and LTD of axis 1; H and SRL of axis 2. The results indicate that the IP communities exhibited higher H and SLA and lower SRL and LTD.Both the H and SLA of IPs and NPs have a significant positive correlation with elevation at the community scale.The LTD of IPs was significantly negatively correlated with elevation.The slope absolute values of the H, SLA, and LTD of IPs were higher than those of NPs, while the slope absolute value of the SRL of NPs was higher than that of IPs (Figure 5, Table 2).

Functional Differences at the Community Scale
A comparison was made between the functional differences of CW values in the IP and NP communities at various elevations within the WLF area in relation to a null model.The results showed a significant deviation from the null model, indicating a non-random community structure.The functional differences were generally below zero expectations.The functional differences of H, SRL, and SLA on the community scale were significantly positively correlated with elevation.The mean value of FD j was lower than the 95% confidence interval of the null prediction in the elevation range of 160-175 m and higher than the 95% confidence interval of the null prediction at 178 m elevation.The functional differences of LTD were lower than the 95% confidence interval of the null prediction.The SRL was lower than the 95% confidence interval of spatial prediction in the low-elevation area, except for the lack of a significant difference between the SRL and spatial prediction at 178 m (Figure 6).

Functional Differences at the Community Scale
A comparison was made between the functional differences of CW values in the IP and NP communities at various elevations within the WLF area in relation to a null model.The results showed a significant deviation from the null model, indicating a non-random community structure.The functional differences were generally below zero expectations.The functional differences of H, SRL, and SLA on the community scale were significantly positively correlated with elevation.The mean value of FDj was lower than the 95% confidence interval of the null prediction in the elevation range of 160-175 m and higher than the 95% confidence interval of the null prediction at 178 m elevation.The functional differences of LTD were lower than the 95% confidence interval of the null prediction.The SRL was lower than the 95% confidence interval of spatial prediction in the low-elevation area, except for the lack of a significant difference between the SRL and spatial prediction at 178 m. (Figure 6).

Spatial Differentiation of IP Species in the WLF Zone
Plants have the ability to respond to changes in their habitat and adjust their behavior accordingly.Through evolution, organisms have developed a self-regulating mechanism to adapt to dynamic environments [43].Our research findings reveal significant differences in the key traits between invasive and native species in the WLF zone of the Pengxi River, providing strong evidence for phenotypic differentiation [10].These trait variations observed in specific ecosystems between native and invasive species align with previous studies [24,44], suggesting that these distinct attributes may contribute to the spread of invasive species within the WLF zone.
The PCA results indicated that the trait space in the WLF zone is primarily influenced by the following three main trait axes: the leaf economics spectrum, root economics spectrum, and plant main stem (including height).These findings suggest a correlation among different plant characteristics in the WLF zone [45].Moreover, it has been noted that plant functions are constrained within specific trait combinations [46,47].Our study identified significant functional differentiation in resource utilization strategies between IPs and NPs across various elevations in the WLF zone, which is consistent with prior research [48,49].These results suggest that the successful invasion of non-native plants is closely linked to the adoption of distinct resource utilization strategies [50,51].Specifically, our study highlights the crucial role of the leaf economics spectrum in distinguishing between them.IPs in the WLF zone also exhibit trait values aligned with a 'fast return on investment' strategy, similar to those in other regions [52], which remains consistent across different elevations [53].These findings imply that IPs may have a competitive edge in resource extraction, especially in the WLF zone, with significant abiotic constraints, while NPs tend to display a more conservative approach to resource absorption [45,54].In response to varying environmental stresses, IPs allocate resources differently by prioritizing aboveground resources and expanding their ecological niche through significant investments in H and SLA.This shift in resource allocation often leads to a reduction in leaf defense capabilities [10,44].In the face of periodic flooding and drought-induced challenges in the WLF zone, IPs tend to invest more resources in fortifying their root systems.This resource allocation pattern could be considered a distinguishing feature of their resource utilization strategy in such habitats.
The height of IPs is significantly higher at most elevations.Plant height is indicative of a plant's capacity to obtain light resources and is closely linked to its competitive advantage [55][56][57].There is a high level of competition among plants for light and space in the WLF zone.Taller plants have an advantage in accessing light and shading out shorter plants, limiting their growth [58].This competitive advantage enables them to achieve a higher level of success over invasive species by outcompeting other species by overshadowing them and securing a greater share of light resources [59,60].The result is consistent with other conclusions in ecosystems experiencing cycles of drought and rewetting [61].SLA plays a key role in regulating plant functions and resource acquisition [36].SLA has been found to have a positive impact on plant growth rates, biomass production, and nutrient accumulation efficiency [62].In the WLF zone, IPs generally exhibit a higher SLA, allowing them to efficiently acquire resources, leading to enhanced growth and faster leaf turnover rates [63][64][65].Therefore, traits associated with rapid growth and efficient resource acquisition contribute to the invasiveness of plant species [66].
The growth and acquisition of resources in plants are often balanced by their ability to tolerate abiotic stress [67].This phenomenon has been observed in the WLF zone, where IPs have been found to have a smaller LDMC and LTD compared to NPs.LDMC and LTD are indicators of how plants allocate dry matter for leaf construction.An increase in LTD, affecting water diffusion from the leaf interior to the surface [68], can reduce water loss and enhance drought stress resistance.IPs invest less in structural compounds and resource allocation for leaf defense, resulting in lower leaf toughness and drought tolerance compared to NPs [44].This trade-off allows invasive plants to prioritize resource access over tolerance to abiotic stress conditions.Interestingly, this study also found that invasive plants in the floodplain, especially in the upper section, tend to have a smaller SRL.The SRL is a trait sensitive to environmental changes.A larger SRL indicates reduced carbohydrate requirements for root system development and maintenance per unit length, leading to increased energy expenditure for nutrient and water uptake, as well as faster root turnover rates [69,70].IPs in the WLF zone exhibit an opposite SRL compared to those in other areas [10].IPs opt to allocate more defensive resources toward the development of root systems, resulting in increased thickness.This investment comes at the cost of higher construction and maintenance expenses in exchange for enhanced soil penetration capabilities and extended longevity [71].Consequently, IPs in the WLF zone prioritize acquiring more aboveground resources to expand their presence and occupy larger habitat areas.They allocate more resources to their root systems rather than leaves to better withstand harsh environmental conditions (Figure 7).
Forests 2024, 15, 959 12 of 18 compared to NPs [44].This trade-off allows invasive plants to prioritize resource access over tolerance to abiotic stress conditions.Interestingly, this study also found that invasive plants in the floodplain, especially in the upper section, tend to have a smaller SRL.
The SRL is a trait sensitive to environmental changes.A larger SRL indicates reduced carbohydrate requirements for root system development and maintenance per unit length, leading to increased energy expenditure for nutrient and water uptake, as well as faster root turnover rates [69,70].IPs in the WLF zone exhibit an opposite SRL compared to those in other areas [10].IPs opt to allocate more defensive resources toward the development of root systems, resulting in increased thickness.This investment comes at the cost of higher construction and maintenance expenses in exchange for enhanced soil penetration capabilities and extended longevity [71].Consequently, IPs in the WLF zone prioritize acquiring more aboveground resources to expand their presence and occupy larger habitat areas.They allocate more resources to their root systems rather than leaves to better withstand harsh environmental conditions (Figure 7).

The Invasion Mechanism of IP in the WLF Zone
Biological invasion provides a valuable opportunity to study the colonization of new species populations [11,72].Given the unique ecological conditions of intermittent floods and droughts in the WLF region, it is imperative to assess the invasion mechanism of the IP community in this area.This mechanism plays a key role in determining the success or failure of the invasion.
Our findings suggest that at a regional scale, significant differences in features indicate that niche differentiation has a substantial impact.For an alien species to become invasive, it must possess adequate functional similarity to be embraced by the local community while also having enough differences to occupy the edge of the plant functional feature space (unused niche) within the local ecosystem [59].In most altitude areas of WLF, the unique growth strategy of IP allows it to occupy a vacant niche in the ecosystem of

The Invasion Mechanism of IP in the WLF Zone
Biological invasion provides a valuable opportunity to study the colonization of new species populations [11,72].Given the unique ecological conditions of intermittent floods and droughts in the WLF region, it is imperative to assess the invasion mechanism of the IP community in this area.This mechanism plays a key role in determining the success or failure of the invasion.
Our findings suggest that at a regional scale, significant differences in features indicate that niche differentiation has a substantial impact.For an alien species to become invasive, it must possess adequate functional similarity to be embraced by the local community while also having enough differences to occupy the edge of the plant functional feature space (unused niche) within the local ecosystem [59].In most altitude areas of WLF, the unique growth strategy of IP allows it to occupy a vacant niche in the ecosystem of WLF, which may explain its invasive potential.Hence, on a regional scale, the likelihood of invasive success can be predicted by pre-existing characteristics and habitat preferences.Alien species often show significant distinctions from native species at the species level, which may indicate the operation of neutral dynamic and/or density-dependent mechanisms related to limiting similarity, such as competition and evasion/resistance to predators [73,74].Plants like Bidens frondosa and Bidens pilosa exhibit flood resistance, possess achene fruits, and bear barb-shaped prickles, making them easily dispersed by animals, including humans, as well as through water and wind due to their lightweight seeds.Their long dispersal distance is also widely used to indicate high invasiveness [75].Research indicates that IPs of the Asteraceae family can further enhance their community stability by altering the local pollination network [76,77].This adaptive trait to various habitats, along with advantageous propagules and stress tolerance [78], creates favorable conditions for these plants to invade and inhabit, leading to their widespread presence throughout the WLF zone.Another invasive species, Alternanthera philoxeroides, originally from South America and introduced in China nearly a century ago, demonstrates strong habitat adaptability and phenotypic plasticity [79], expanding its ecological niche [80,81] and enabling it to thrive in this zone.Furthermore, the formation of patch-like mosaics post-invasion in specific areas is often attributed to continuous clonal growth by a genealogical strain [82], contributing to the extensive distribution of this species across the entire zone.Our investigation also revealed that native species within the same genus as invasive plants, such as Bidens tripartita related to Bidens frondosa and Bidens pilosa and Alternanthera sessilis related to Alternanthera philoxeroides, are typically absent in this research area.Consequently, from a phylogenetic standpoint, there exists a considerable genetic distance, which may support the DNH.To gain a deeper understanding of the ecological processes that drive species invasion in the WLF zone, additional comprehensive research is required.This research should encompass intra-species variation, inter-species interactions, and phylogenetic distance within the context of global change in the future.
Significant differences in functional traits were observed between IPs and NPs at the community scale.As elevation increased, these differences gradually increased.Moreover, certain traits showed a notable positive correlation with elevation.In particular, the FD j between IP and NP communities, which was below 175 m in the WLF area, fell below the 95% confidence interval of the null model, indicating a minimal divergence in physiological and ecological attributes, suggestive of functional convergence.This study highlights the significant role of environmental filtering in community assembly, indicating that foreign species in degraded areas must endure harsh abiotic conditions to establish and sustain the community, resulting in functional convergence with local plant communities [83,84].As elevation rises, the effects of environmental filtering are mitigated by niche differentiation.The functional differences between communities in the 178 m zone, largely unaffected by flooding, surpass the 95% confidence interval of the null model.These findings highlight the significant impact of environmental filtering, particularly through regular flooding and drought stress, to explain the variations in IP and NP functions within the WLF zone.Although there are challenges between the theory of reconciled coexistence and the concept of environmental filtering because the strength and direction of biotic interactions can be strongly influenced by the abiotic environment, both factors may dynamically interact to drive community patterns [85].Dominant species in a community typically do not coexist with companion plants of the same genus.This absence of potential competitors or natural enemies for invasive species in the WLF zone may accentuate the importance of habitat filtering.As a result, IPs may successfully integrate into habitats with comparable functional characteristics already occupied by NPs and establish their own communities.
The importance of the research scale when elucidating intrusion mechanisms is highlighted in our study, as research findings can differ depending on the scale considered [86].Specifically, at the regional scale of the WLF zone, there are notable differences in the functional characteristics of IPs and NPs in response to changes in altitude.IPs typically display Forests 2024, 15, 959 14 of 18 more invasive traits due to the homogeneity of the habitat environment at the regional scale, leading to direct interactions and competition among individuals for limited resources.Competitive exclusion among coexisting species can lead to significant variations in functional traits, favoring certain branches and species with competitive advantages [87,88].On the community scale, in resource-limited environments, environmental factors constrain the variation in physiological and morphological characteristics within the plant community.Environmental filtering emerges as a key factor influencing community assembly, potentially outweighing interspecific interactions at the species level [20,86].Evidence suggests that strong local competitors may share similarities with strong foreign competitors [89], resulting in convergent character values at the community scale after adjusting for relative abundance.In harsh environmental conditions, the effects of intraspecific competition may be less apparent [19].Additionally, species loss due to abiotic tolerance or differences in competitive fitness with other residents [88] often leads to the functional traits of coexisting species being more similar than expected [90].The variations in the results at the two scales may emphasize the distinct roles of abiotic and biotic effects on community assembly and species distribution at different scales.

Conclusions
Our multi-scale research method is valuable for comprehending the functional differentiation and invasion mechanisms of local plants and invasive plants in the water level fluctuation zone.At the regional scale, IPs exhibit larger H and SLA and smaller LTD and SRL compared to NP. IPs tend to prioritize enhancing their ability to acquire above-ground resources at the expense of leaf defense capabilities, allocating more tissue construction resources to their roots to withstand the strong environmental pressure in the WLF zone.This resource allocation strategy may be the key to their successful intrusion, highlighting the significant role of niche differentiation.On the community scale, the H and SLA of IP and NP communities show a significant positive correlation with elevation, while the LTD of IP communities shows a significant negative correlation with elevation.The functional differences in H, SRL, and SLA in the IP and NP communities are significantly positively correlated with elevation.Functional convergence is observed at elevations of 175 m and below, with functional divergence at elevations of 175 m and above.This suggests that although different resource utilization strategies drive successful IP invasion, the environmental filtering caused by periodic floods and drought stress leads to similar ecological needs for both IP and NP communities, playing a major role in the community assembly in the WLF zone.IPs may successfully integrate into habitats with similar functional characteristics already occupied by NPs and establish their own communities.This environmental filtering effect decreases notably with increasing elevation.Our results can reflect differences in resource utilization strategies between IPs and NPs, offering new insights into the mechanism of plant invasion in the WLF zone.

Supplementary Materials:
The following supporting information can be downloaded at https: //www.mdpi.com/article/10.3390/f15060959/s1,Table S1: List of invasive plants in the water level fluctuation zone; Table S2: List of native plants in the water level fluctuation zone; Table S3: Summary table of sampling sites.Data Availability Statement: Data will be available upon request to the corresponding author.

Forests
(http://www.cjh.com.cn;accessed on 21 May 2024) revealed that the lower section of the Pengxi River WLF zone (elevation 160 m-168 m) experienced flooding depths exceeding 10 m for about 160 days annually, whereas the upper WLF zone (elevation 170 m-175 m) experienced 5 m flood depths for around 70 days per year.

Figure 1 .
Figure 1.Location of the study area in Pengxi River, Kaizhou District, Chongqing, China.

Forests 2024 ,
15, 959  7 of 18    observed between IPs and NPs along the PCA axis 1 and axis 2 in the WLF area indicate a functional differentiation in their strategies for resource utilization (Figure3).

Figure 2 .
Figure 2. Results of PCA analysis for invasive and native plants at different elevations in the water level fluctuation zone.Black color represents invasive plants and red color represents native plants.

Figure 3 .
Figure 3. Results of two-tailed t-tests describing overall trait differences between invasive plants and native plants across the water level fluctuation zone on PCA axes 1 and axes 2. (a) Axis 1; (b) axis 2. Different lowercase letters on the boxplot indicate a significant difference.

Figure 2 .
Figure 2. Results of PCA analysis for invasive and native plants at different elevations in the water level fluctuation zone.Black color represents invasive plants and red color represents native plants.

Figure 2 .
Figure 2. Results of PCA analysis for invasive and native plants at different elevations in the wat level fluctuation zone.Black color represents invasive plants and red color represents native plan

Figure 3 .
Figure 3. Results of two-tailed t-tests describing overall trait differences between invasive plan and native plants across the water level fluctuation zone on PCA axes 1 and axes 2. (a) Axis 1; ( axis 2. Different lowercase letters on the boxplot indicate a significant difference.

Figure 3 .
Figure 3. Results of two-tailed t-tests describing overall trait differences between invasive plants and native plants across the water level fluctuation zone on PCA axes 1 and axes 2. (a) Axis 1; (b) axis 2. Different lowercase letters on the boxplot indicate a significant difference.

Figure 4 .
Figure 4. Differences in functional traits of invasive plants and native plants at different elevation of the water level fluctuation zone.Trait values of native plants and invasive plants calculated as th mean value of measured functional traits.(a) H, (b) SRL, (c) SLA, and (d) LTD.* indicates significan differences between invasive plants and native plants at different elevations (p < 0.05).NS indicate no significant difference between invasive plants and native plants.

Figure 4 .
Figure 4. Differences in functional traits of invasive plants and native plants at different elevations of the water level fluctuation zone.Trait values of native plants and invasive plants calculated as the mean value of measured functional traits.(a) H, (b) SRL, (c) SLA, and (d) LTD.* indicates significant differences between invasive plants and native plants at different elevations (p < 0.05).NS indicates no significant difference between invasive plants and native plants.

ForestsFigure 5 .
Figure 5.The response of weighted functional traits of invasive communities and native communities in the water level fluctuation to elevation.(a) CW−H, (b) CW−SRL, (c) CW−SLA, and (d) CW−LTD.Black color represents invasive plants, and red color represents native plants.The line represents the linear fit curve and the red/black area represents the 95% confidence band.

Figure 5 .
Figure 5.The response of weighted functional traits of invasive communities and native communities in the water level fluctuation to elevation.(a) CW−H, (b) CW−SRL, (c) CW−SLA, and (d) CW−LTD.Black color represents invasive plants, and red color represents native plants.The line represents the linear fit curve and the red/black area represents the 95% confidence band.

Figure 6 .
Figure 6.The functional differences index (FDj) and elevation responses between the invasive community and the native community in the water level fluctuation zone.(a) FDj−H, (b) FDj−SRL, (c) FDj−SLA, and (d) FDj−LTD.When the point is greater than zero, alien species and native species tend to diverge in function.When the point is below zero, the function tends to converge.The solid point is beyond the 95% confidence interval, indicating a significant difference from the null prediction, while the hollow point does not differ from the null prediction.The red line represents the linear fit curve and the red area represents the 95% confidence band.

Figure 6 .
Figure 6.The functional differences index (FD j ) and elevation responses between the invasive community and the native community in the water level fluctuation zone.(a) FD j −H, (b) FD j −SRL, (c) FD j −SLA, and (d) FD j −LTD.When the point is greater than zero, alien species and native species tend to diverge in function.When the point is below zero, the function tends to converge.The solid point is beyond the 95% confidence interval, indicating a significant difference from the null prediction, while the hollow point does not differ from the null prediction.The red line represents the linear fit curve and the red area represents the 95% confidence band.

Figure 7 .
Figure 7. Diagram of functional segregation between invasive plants and native plants in the water level fluctuation zone.The black color represents invasive plants, and the red color represents native plants.

Figure 7 .
Figure 7. Diagram of functional segregation between invasive plants and native plants in the water level fluctuation zone.The black color represents invasive plants, and the red color represents native plants.

Author
Contributions: L.C.: Investigation, Software, Visualization, Data curation, Writing-Original draft.X.Y.: Supervision, Writing-Review and Editing.K.S.: Investigation, Data curation.P.L.: Visualization.All authors have read and agreed to the published version of the manuscript.Funding: This research was funded by the National Natural Science Fund of China (No. 52178031) and the Fundamental Research Funds for the Central Universities (No. 2021CDJQYJC005).

Table 1 .
Method table for calculating functional characteristics.

Table 2 .
Differences in the weighted functional properties of invasive and native communities in the water level fluctuation zone in relation to elevation.

Table 2 .
Differences in the weighted functional properties of invasive and native communities in the water level fluctuation zone in relation to elevation.