Multidimensional Environmental Drivers of Bamboo Species Richness on Subtropical Islands

Abstract

Understanding the distribution patterns and driving mechanisms of bamboo species diversity on islands is essential for advancing knowledge of island ecosystem processes and informing strategies for bamboo resource conservation and management. This study utilized standardized major axis regression (SMA) to assess the effects of island area and isolation on bamboo species across 30 islands in Fujian, China. Furthermore, a partial least squares structural equation model (PLS-SEM) was constructed to explore the driving mechanisms underlying bamboo species richness. This analysis incorporated six key environmental factors—island size, isolation, shape, climate, development intensity, and habitat heterogeneity—spanning a total of 12 variables. The primary findings were as follows: (1) Eight genera and twenty-nine bamboo species were identified on Fujian islands. Species richness increased significantly with island area, consistent with the theory of area effects, while isolation had no significant impact on richness. (2) Different reproductive types exhibited distinct responses to environmental conditions. This was evident in the species–area relationship slopes (z-values): SR = 2.07; monopodial = 0.94; sympodial = 0.82; and polycyclic = 0.44. These variations highlight the ecological adaptability and functional traits of different reproductive strategies within island ecosystems. (3) Among the six environmental factors, island area exerted the greatest influence on species richness, underscoring its role as the primary driver of bamboo diversity and reproductive strategies. (4) Island area and isolation also impacted species richness indirectly through their effects on development intensity. In conclusion, the bamboo species richness and reproductive types on Fujian islands are primarily shaped by island area, followed by development intensity and habitat heterogeneity. In contrast, climate, island shape, and isolation play relatively minor roles. This study provides critical insights into the interplay of island area, isolation, shape, climate, development intensity, and habitat heterogeneity in shaping bamboo diversity. The findings offer a valuable foundation for bamboo resource conservation, island ecosystem management, and sustainable development.

1. Introduction

Although islands comprise only 3–5% of the Earth’s land area, they support 15–20% of the planet’s terrestrial species [1]. Due to their isolation, islands are hotspots for species with restricted ranges [2]. This makes islands ideal regions for studying biodiversity and ecological conservation, providing a model system for addressing key questions in biodiversity conservation [3]. The unique characteristics of island ecosystems—geographic isolation, environmental heterogeneity, and limited resources—result in distinctive patterns of plant distribution and adaptation. With their small size and relative geographic isolation, island plants are highly vulnerable to environmental changes. Consequently, studying the distribution patterns of island plants is critical for understanding their mechanisms of response to environmental factors.

The exploration of factors driving island species richness has its roots in the traditional island biogeography theory [4]. The equilibrium theory, introduced by MacArthur and Wilson, suggests that island species richness results from a dynamic balance between immigration and extinction rates [4,5,6]. This theory highlights island area and isolation from the mainland as the primary determinants of species richness, commonly referred to as the “area effect” and “isolation effect” [7,8,9,10,11].

In addition to the area and isolation effects, environmental factors such as elevation [12,13], temperature [10,14,15], rainfall [16,17,18], and wind speed [19] play critical roles in shaping island species richness and distribution patterns. Habitat heterogeneity [20,21] is also a key driver of species richness on islands [14,22,23,24]. However, intensive human activities, including urbanization, unsustainable tourism, and overgrazing, directly threaten the limited habitats of island species [25] Anthropogenic disturbances can significantly alter the species distribution patterns predicted by traditional island biogeography theory [26]. In general, island species richness distribution patterns are determined by the interplay of multiple environmental gradients, and the predictive power of these factors for plant species richness varies depending on spatial scale and geographic location [27]. Consequently, in-depth exploration of the distribution patterns and mechanisms of species richness in specific island ecosystems is of considerable importance.

Species on islands are influenced by environmental factors, and their functional strategies evolve continuously over long periods [28]. Functional traits provide a clear indication of how plants adapt to environmental heterogeneity during their evolutionary history, reflecting strategies for growth, reproduction, and resource utilization [29]. Moreover, these traits reveal the relationships between plants and environmental factors at various spatial scales [30].

Bamboo, as a key component of global terrestrial forest ecosystems, provides significant economic, ecological, and social benefits due to its extensive distribution, rapid growth, high productivity, strong regeneration capacity, and diverse applications with considerable economic value [31,32,33]. China is the world’s leading country in bamboo resources, ranking first globally in species diversity, distribution range, and biomass. According to The Flora of China [34], China is home to 34 genera and 534 species of bamboo. Bamboo plays a crucial role in maintaining ecological balance, driving economic development, conserving soil and water, preventing soil erosion, and serving as a carbon sink. Bamboo exhibits distinctive reproductive traits, which can be divided into three main types: sympodial, monopodial, and polyclinic. Bamboo exhibit unique reproductive characteristics and can be divided into three main types based on their reproductive strategies: sympodial, monopodial, and polycyclic. Sympodial bamboo rhizomes cannot spread long distances underground, and new shoots are connected to the parent bamboo by short stalks, resulting in a clustered distribution. Monopodial bamboo rhizomes can extend long distances underground, facilitating a more dispersed growth pattern. Polycyclic bamboo combines the rhizome characteristics of both sympodial and monopodial types, exhibiting traits from both growth strategies [35]. The evolutionary progression of bamboo, from sympodial clumping to polycyclic and finally to monopodial types, reflects its adaptation to complex and changing environments through structural evolution to optimize resource acquisition [36]. On islands, with their geographical isolation, limited area, and habitat heterogeneity, bamboo reproductive types exhibit distinct adaptive strategies. Thus, investigating how environmental factors affect the species richness of bamboo with different reproductive types on islands is essential for understanding the influence of island scale, isolation, shape, climate, development intensity, and habitat heterogeneity on bamboo diversity and spatial heterogeneity.

Fujian Province is home to numerous islands with wide variations in area and isolation distances. The islands exhibit diverse landscape features, including topography, coastline length, and elevation, making them ideal for studying plant distribution and the environmental factors driving it. Fujian’s subtropical maritime monsoon climate reflects the characteristics of subtropical island plant diversity in China. However, in recent years, increasing development and human activities in island areas have exerted growing pressure on the ecosystems of Fujian’s islands. The expansion of coastal development and tourism has led to habitat fragmentation and degradation of bamboo species, posing potential threats to the biodiversity and ecosystems of Fujian’s islands. Understanding the relationship between bamboo species richness and environmental factors can provide a scientific basis for relevant authorities in conserving and rationally utilizing bamboo resources on islands. Therefore, this study selected 30 islands in Fujian as research objects to investigate the species richness of bamboo on these islands. Our research aimed to reveal the species–area relationship, area effect, and isolation effect on the species richness of bamboo and its different reproductive types. Furthermore, this study analyzed the roles of environmental factors such as island scale, isolation, shape, climate, development intensity, and habitat heterogeneity in driving the species richness of bamboo and its reproductive types. This investigation seeks to uncover the spatial heterogeneity and distribution patterns of bamboo and its reproductive types on islands. The findings not only enhance understanding of bamboo diversity in island ecosystems but also provide theoretical guidance for the conservation and sustainable development of bamboo resources in the future.

2. Materials and Methods

2.1. Study Area

Fujian Province is situated on the southeastern coast of China, bordering the Taiwan Strait. The region experiences a subtropical maritime monsoon climate, with an annual average temperature ranging from 15.2 to 21.0 °C and average annual precipitation between 1000 and 1600 mm. The dominant vegetation types on the islands include evergreen coniferous forests, evergreen broad-leaved forests, and shrub-grass communities. This study focused on islands that were accessible and covered with vegetation. The selected study area encompasses the entire maritime region of Fujian Province, representing variations in island attributes such as area, isolation, climate, and human disturbances. Island selection was based on differences in area, elevation, isolation, human activity impacts, and climatic conditions, ensuring coverage of islands with distinct environmental gradients. This study examined 30 islands located in the maritime region of Fujian Province (117°31′61″–120°68′66″ E, 23°60′90″–26°93′08″ N) (Figure 1).

2.2. Species Data Collection

During the growing seasons of 2018 and 2022 (May to July and September to November), comprehensive surveys were conducted on 30 islands in Fujian to systematically document all plant species. Transect surveys served as the primary method, supplemented by quadrat surveys. Drone aerial photography was employed to investigate inaccessible areas such as island edges and cliffs. For small islands with an area of less than 1 km², the entire island was surveyed. Each island featured 3 to 10 transects, with each transect surveyed at least twice [37]. For islands ranging from 1 to 10 km², 6 to 20 transects were established, with a combined total length exceeding 12 km. On islands larger than 10 km², in addition to the aforementioned methods, transects were concentrated around prominent mountain features [38], and detailed species information within these transects was recorded.

To ensure comprehensive species documentation, typical bamboo plant community types were identified following the transect surveys, and standard quadrats measuring 20 m × 20 m were established. All plant species within the quadrats were meticulously documented. Geographic information for each quadrat, including latitude, longitude, elevation, slope, and terrain, was carefully recorded [39]. Fieldwork also included photographic documentation and specimen collection, with all voucher specimens deposited in the herbarium of the College of Landscape Architecture and Art, Fujian Agriculture and Forestry University. Bamboo species were identified according to The Flora of China [40] and classified into three reproductive types: monopodial, sympodial, and polycyclic. Ultimately, data on the distribution of bamboo species across the 30 islands in Fujian were compiled.

2.3. Environmental Variables of Islands

To investigate how environmental factors influence bamboo species richness and the richness of different reproductive types on islands, this study initially identified 30 variables spanning 6 categories: climate, island scale, shape, isolation, development intensity, and habitat heterogeneity.

2.3.1. Climate

The climate factors encompass 20 variables, including Bio 1–Bio 19 bioclimatic variables and annual mean wind (AMW). The 19 bioclimatic variables consist of annual mean temperature (Bio 1), mean diurnal range (Bio 2), isothermality (Bio 3), temperature seasonality (Bio 4), max temperature of warmest month (Bio 5), min temperature of coldest month (Bio 6), temperature annual range (Bio 7), mean temperature of wettest quarter (Bio 8), mean temperature of driest quarter (Bio 9), mean temperature of warmest quarter (Bio 10), mean temperature of coldest quarter (Bio11), annual precipitation (Bio 12), precipitation of wettest month (Bio 13), precipitation of driest month (Bio 14), precipitation seasonality (Bio 15), precipitation of wettest quarter (Bio 16), precipitation of driest quarter (Bio 17), precipitation of warmest quarter (Bio 18), and precipitation of coldest quarter (Bio 19).

The Bio 1–Bio 19 bioclimatic data were sourced from the WorldClim database, which provides global bioclimatic variables (http://www.worldclim.org, accessed on 1 March 2024). Annual mean wind data were obtained from NOAA’s 10 m resolution wind vector map (https://www.noaa.gov, accessed on 5 February 2024). Climate data for the 30 islands in Fujian were derived using the Kriging interpolation method, based on the geographic coordinates of each island. All datasets were extracted and analyzed using ArcGIS 10.8 software.

2.3.2. Island Scale

Island scale factors consist of two variables: area (A) and maximum elevation (ELE).

2.3.3. Shape

Island shape is characterized by two variables: the perimeter area ratio (PAR) and the fractal dimension (FD).

PAR is defined as the ratio of perimeter to area (PAR = perimeter/area) and is used to measure the proportion of edge habitats (e.g., coastlines) relative to interior habitats. A higher PAR value indicates a longer perimeter relative to the area, suggesting a higher proportion of edge habitats [41].

The fractal dimension (FD) is used to quantify the complexity of island shapes and is computed using the following formula. In this formula, H^d(S) represents the Hausdorff measure of a set S in dimension d; lim_δ→0 denotes the limit as the diameter of the covering subsets (δ) approaches zero; inf signifies the infimum, or the smallest value, over all possible coverings; and diam S_i < δ specifies that the diameter of each subset S_i must be smaller than δ. A higher FD value indicates a more irregular island shape.

$${\mathrm{H}}^{\mathrm{d}}\left(S\right)={\displaystyle \frac{\mathrm{l}\mathrm{i}\mathrm{m}}{\delta \to 0}}\mathrm{i}\mathrm{n}\mathrm{f}\left\{\sum _{\mathrm{i}=1}^{\mathrm{\infty }}{\left(\mathrm{d}\mathrm{i}\mathrm{a}\mathrm{m}{S}_i\right)}^{\mathrm{d}}:S\subseteq \bigcup _{\mathrm{i}=1}^{\mathrm{\infty }}{S}_{\mathrm{i},}\mathrm{d}\mathrm{i}\mathrm{a}\mathrm{m}{S}_i<\delta \right\}$$

2.3.4. Isolation

We measured the accessibility of islands using the distance from the nearest continent (DNC). DNC is a common factor affecting the frequency of visits by residents and tourists and is a quantitative indicator of island isolation used to measure the degree of isolation of islands [37]. It represents the isolation effect in the theory of island biogeography.

Additionally, to more accurately reflect the remoteness of islands, we referred to the method proposed by Weigelt and Kreft [42] to calculate the stepping stone distance (SSD), which describes the connection points or “stepping stones” for species during migration, dispersion, or between populations. “Stepping stones” enable species to move between their habitats. This distance considers the proximity to both the nearest continent and the nearest large island.

2.3.5. Development Intensity and Anthropogenic Disturbance

The proportion of buildings and farmland area (BFA) was used to represent human activities on the islands. To better capture the development intensity and anthropogenic disturbance of the islands, the number of docks (ND) and the number of land bridges (NLB) were included as additional environmental factors for analysis.

Data on island area, perimeter, DNC, DNI, SSD, NLB, and BFA were obtained from the 2020 global 30 m resolution land cover vector map released by the Aerospace Information Research Institute, Chinese Academy of Sciences (https://data.casearth.cn, accessed on 7 March 2024). These data were extracted using the “mask extraction” technique. Elevation data were derived from the 30-m resolution DEM dataset provided by the Geospatial Data Cloud (http://www.gscloud.cn, accessed on 20 March 2024), from which the highest elevation point was extracted. All data were processed and analyzed using ArcGIS 10.8 software.

2.3.6. Habitat Heterogeneity

The Area-Based Rao’s Index (Q) was utilized to assess the habitat heterogeneity and spatial distribution characteristics of 30 islands in Fujian. This index is a diversity metric that incorporates species relative abundance, interspecies similarity, and spatial distribution features [43]. Compared to conventional diversity indices, such as the Shannon–Wiener Index and the Simpson Index, the Area-Based Rao’s Index integrates spatial structural information, offering a more comprehensive and accurate assessment of habitat heterogeneity across islands.

In this study, the Area-Based Rao’s Index was implemented using the rasterdiv [44] R package and calculated following specific steps. The primary data source was the S2A data product from Copernicus Sentinel-2 (https://www.copernicus.eu/en, accessed on 9 November 2024). Normalized Difference Vegetation Index (NDVI) data were acquired from satellite images taken within 15 days before and after the survey dates. NDVI was processed to capture the spatial heterogeneity and vegetation coverage of island ecosystems, serving as the baseline input for diversity calculations.

Subsequently, the Area-Based Rao’s Index (Q) for each island was computed using NDVI raster data. The formula for the Rao’s index is presented as follows:

$$\mathrm{Q}=\sum _{\mathrm{i}=1}^{\mathrm{S}}\sum _{\mathrm{j}=1}^{\mathrm{S}}{P}_i{P}_j{d}_{ij}{\mathrm{A}}_{\mathrm{i}}{\mathrm{A}}_{\mathrm{j}}$$

Q, the Area-Based Rao’s Index, quantifies community diversity and heterogeneity; $P_i$ and $P_j$ denote the relative abundances of species i and j, respectively, indicating their frequencies of occurrence in the sample; $d_{ij}$ signifies the similarity or dissimilarity between species ii and j, which can be measured as functional distance, genetic distance, or other related metrics; and A_i and A_j are the area weights of the regions inhabited by species i and j, respectively, incorporated to account for the effects of spatial distribution differences.

2.4. Data Analysis

Before constructing the model, collinearity among environmental factors was assessed using the variance inflation factor (VIF) [45]. The results indicated that all 12 environmental factors (

Table A1. Environmental factors and species distribution data of 30 islands.

	Climate		Island Characteristic				Anthropogenic Disturbance					Q index
Island	Bio 6 (°C)	Bio 14 (mm)	A (km2)	ELE (m)	PAR	FD	DNC (km)	SSD (km)	ND	NLB	BFA (%)	Alpha 1	Alpha 2	SR	Sympodial	Monopodial	Polycyclic
Caoyudao	9.06	30	7.05	212.30	2.29	1.25	4.29	3.63	10	0	0.37	0.09	0.17	13	7	4	2
Culudao	7.42	37	14.40	232.60	1.42	1.19	0.26	0.26	9	1	0.49	0.17	0.23	13	6	4	3
Dadengdao	8.89	23	12.99	41.80	1.45	1.18	0.62	5.74	8	2	0.70	0.21	0.27	8	5	2	1
Daisongdao	9.09	25	0.36	27.30	7.71	1.28	0.40	0.40	6	1	0.79	0.16	0.22	6	3	1	2
Daliandao	8.77	32	9.96	238.50	2.03	1.24	7.88	1.18	6	1	0.17	0.09	0.17	10	5	3	2
Dashengdao	9.28	23	0.07	44.20	17.78	1.26	2.54	1.28	0	0	0.00	0.15	0.21	5	3	1	1
Dayudao	8.88	26	0.22	45.10	12.38	1.25	2.47	1.04	1	0	0.13	0.15	0.21	7	4	2	1
Dayushandao	5.13	40	21.22	541.40	1.41	1.18	6.62	5.27	6	0	0.22	0.13	0.18	7	8	7	2
Dazuidao	9.48	24	0.61	103.10	8.39	1.27	2.33	2.33	2	0	0.04	0.15	0.21	9	5	2	2
Dongshandao	10.35	26	220.18	274.30	0.51	1.20	0.31	0.31	35	5	0.24	0.19	0.26	1	10	7	4
Dogxiangdao	8.96	36	4.80	134.60	4.10	1.28	26.50	2.30	8	0	0.46	0.20	0.26	7	3	2	2
Duimianyu	10.74	27	0.10	25.80	20.71	1.30	5.78	0.49	2	0	0.01	0.10	0.16	6	2	3	1
Haitandao	8.77	32	267.13	438.20	0.48	1.24	3.59	1.20	51	2	0.62	0.24	0.31	4	11	8	5
Huanggandao	9.28	23	0.55	72.40	8.27	1.26	0.72	0.72	0	0	0.00	0.15	0.23	5	3	1	1
Huchudao	7.42	37	0.07	33.72	22.56	1.32	5.20	0.38	0	0	0.00	0.15	0.20	4	2	1	1
Huiyu	8.37	24	0.41	59.90	13.14	1.31	1.11	1.11	2	0	0.55	0.16	0.22	10	6	1	3
Jiangyindao	8.67	25	69.75	429.10	0.72	1.19	0.21	0.21	14	7	0.41	0.15	0.21	2	6	4	2
Langqidao	7.42	37	55.50	275.00	0.59	1.16	0.56	0.56	21	5	0.60	0.17	0.23	16	8	4	4
Meizhoudao	9.28	23	14.35	95.20	2.32	1.27	2.19	2.19	3	0	0.67	0.15	0.22	9	9	7	3
Nanridao	9.10	27	47.24	116.30	2.24	1.21	7.34	3.37	10	0	0.85	0.15	0.21	4	7	3	4
Sandudao	5.84	42	29.17	460.60	1.05	1.18	2.08	1.93	3	0	0.22	0.18	0.24	8	7	7	4
Tayu	10.74	27	1.01	91.30	6.82	1.24	2.44	1.16	3	0	0.26	0.19	0.26	8	5	2	1
Xiamendao	9.24	25	134.84	339.60	0.49	1.14	0.71	0.71	90	7	0.80	0.21	0.27	17	8	6	3
Xiaosongdao	9.09	25	0.02	26.00	30.37	1.29	0.35	0.35	0	1	0.00	0.20	0.27	4	2	2	0
Xiaweidao	6.23	46	0.08	35.51	22.42	1.29	0.27	0.27	0	0	0.00	0.16	0.22	4	2	1	1
Xiyangdao	6.23	46	29.80	221.00	0.72	1.21	10.23	6.99	5	0	0.25	0.07	0.11	13	6	5	2
Yuanyangyu	5.13	40	0.64	149.81	9.01	1.28	12.85	0.25	0	0	0.00	0.12	0.18	4	2	1	1
Yutoudao	8.76	28	8.56	77.90	2.57	1.26	2.40	0.25	17	0	0.86	0.09	0.15	6	4	1	1
Zhujiangdao	5.68	45	0.15	47.30	12.82	1.23	0.81	0.81	2	0	0.66	0.13	0.19	7	4	1	2
Zinidao	9.23	26	28.56	5.00	1.26	1.20	0.28	0.28	65	9	0.91	0.15	0.21	17	9	5	3

)—Bio 6 (min temperature of coldest month) and Bio 14 (precipitation of driest month) from the climate factors; area, elevation, PAR, FD from the island attribute factors; and DNC, SSD, ND, NLB, BFA, and Area-Based Rao’s Index from the anthropogenic disturbance factors—had VIF values below 6, well below the maximum threshold of 10, suggesting weak collinearity effects.

To mitigate potential bias caused by collinearity among variables, we employed the variance inflation factor (VIF) [45] to assess collinearity among environmental factors and identified variables with minimal collinearity. Ultimately, 12 environmental factors with low collinearity were selected (Table A1). These included Bio 6 (minimum temperature of the coldest month) and Bio 14 (precipitation of the driest month) from climate factors; area, elevation, PAR, and FD from island attributes; and DNC, SSD, ND, NLB, BFA, and the Area-Based Rao’s Index from anthropogenic disturbance factors. All these variables had VIF values below 6, well below the maximum threshold of 10 [46], indicating weak collinearity and their appropriateness as core variables for subsequent analysis. To further confirm that the spatial distribution of the selected environmental factors was dominated by random processes and that spatial location had no significant effect on data distribution, spatial autocorrelation was assessed using Global Moran’s I [47]. The results revealed no significant spatial autocorrelation among the 12 environmental factors (p > 0.05), indicating that the distribution of environmental factors was random and that spatial factors could be disregarded.

Species accumulation curves were employed to assess the adequacy of bamboo species surveys conducted on Fujian islands [48]. To investigate the relationship between species richness, island area, and isolation, the Standardized Major Axis Tests and Routines (SMATR) [49] package in R was utilized, applying the standardised major axis (SMA) regression method for analysis.

The Pearson correlation coefficient was applied to examine the relationships among island environmental factors, with Bonferroni correction used to adjust significance levels. Subsequently, the Mantel test [49], calculated using Euclidean distance, was conducted to assess the correlations between the matrix of island environmental factors and the matrices of bamboo species and species with different reproductive strategies on the islands.

To explore the combined effects of multiple environmental factors on bamboo species richness and different reproductive types, this study employed partial least squares structural equation modeling (PLS-SEM) for analysis. PLS-SEM is well-suited for analyzing complex causal pathways by maximizing the explained variance (R²) of dependent variables without requiring a normal distribution assumption [50]. First, all independent and dependent variables were standardized to eliminate the influence of variable scale differences. Subsequently, a structural equation model was constructed using the SEMinR package in R, incorporating bamboo species richness, different reproductive types, and 12 environmental factors. Latent variables were defined by their observed indicators, and path coefficients were used to represent the direct effects between variables. To ensure the predictive power of the model, it was optimized based on R² values and the significance of path coefficients (p-values). Additionally, to assess the relative contributions of different environmental factors, the direct and indirect effects in the model were decomposed to quantify each factor’s total impact on species richness. The reliability and validity of the model were evaluated using composite reliability (CR) and average variance extracted (AVE) to ensure the measurement model’s robustness [51]. All analyses were performed in the R 4.2.2 software environment.

3. Results and Analysis

3.1. Composition of Bamboo Species on Islands

A total of 8 genera and 29 bamboo species were identified across 30 islands in Fujian Province (

Table A2. List of bamboo species found on 30 islands in Fujian, China.

Number	Number	Genus	Species
1	Poaceae	Dendrocalamus	Dendrocalamus latiflorus Munro
2	Poaceae	Bambusa	Bambusa vulgaris Schrad. ex J. C. Wendland
3	Poaceae	Bambusa	Bambusa oldhamii Munro
4	Poaceae	Bambusa	Bambusa ventricosa McClure
5	Poaceae	Bambusa	Bambusa blumeana Schult. and Schult. f.
6	Poaceae	Bambusa	Bambusa multiplex (Lour.) Raeusch. ex Schult. and Schult. f.
7	Poaceae	Bambusa	Bambusa albolineata (McClure) L. C. Chia
8	Poaceae	Bambusa	Bambusa emeiensis L. C. Chia and H. L. Fung
9	Poaceae	Schizostachyum	Schizostachyum funghomii McClure
10	Poaceae	Dendrocalamus	Dendrocalamus pulverulentus L. C. Chia and But
11	Poaceae	Bambusa	Bambusa textilis McClure
12	Poaceae	Bambusa	Bambusa multiplex (Lour.) Raeusch. ex Schult. and Schult. f.
13	Poaceae	Phyllostachys	Phyllostachys edulis (Carrière) J. Houz.
14	Poaceae	Phyllostachys	Phyllostachys sulphurea var. viridis R. A. Young
15	Poaceae	Phyllostachys	Phyllostachys rivalis H. R. Zhao and A. T. Liu
16	Poaceae	Phyllostachys	Phyllostachys iridescens C. Y. Yao and S. Y. Chen
17	Poaceae	Phyllostachys	Phyllostachys vivax McClure
18	Poaceae	Phyllostachys	Phyllostachys rubicunda T. W. Wen
19	Poaceae	Phyllostachys	Phyllostachys makinoi Hayata
20	Poaceae	Phyllostachys	Phyllostachys nigra (Lodd. ex Lindl.) Munro
21	Poaceae	Bambusa	Bambusa cerosissima McClure
22	Poaceae	Phyllostachys	Phyllostachys heteroclada Oliv.
23	Poaceae	Indocalamus	Indocalamus tessellatus (Munro) P. C. Keng
24	Poaceae	Indocalamus	Indocalamus latifolius (Keng) McClure
25	Poaceae	Indocalamus	Indocalamus longiauritus Hand.-Mazz.
26	Poaceae	Pseudosasa	Pseudosasa amabilis (McClure) P. C. Keng ex S. L. Chen and al.
27	Poaceae	Pleioblastus	Pleioblastus maculatus (McClure) C. D. Chu and C. S. Chao
28	Poaceae	Pleioblastus	Pleioblastus chino var. hisauchii Makino
29	Poaceae	Shibataea	Shibataea nanpingensis var. fujianica (Z. D. Zhu and H. Y. Zhou) C. H. Hu

). Of these, 12 species were Sympodial, representing 41.38% of the total; 10 species were monopodial, accounting for 34.48%; and 7 species were polycyclic, comprising 24.14%. Phyllostachys edulis exhibited the highest distribution frequency, occurring on 25 islands (86.21%), followed by Dendrocalamus latiflorus, recorded on 24 islands (82.75%). Species with the lowest distribution frequency included Phyllostachys nigra, found on only two islands. Furthermore, the islands also hosted bamboo species endemic to China, such as Phyllostachys sulphurea, Indocalamus tessellatus, and Phyllostachys heteroclada.

The species accumulation curve (Figure 2) illustrates that as the number of sampled islands increases, SR and the species counts of bamboo plants with different reproductive types initially rise rapidly, followed by a gradual slowdown in growth. The cumulative curve for polycyclic is relatively flat due to their lower abundance on Fujian islands. Nevertheless, the overall bamboo species data appear consistent, indicating that the survey of bamboo species across the 30 islands was comprehensive and sufficient.

3.2. Relationship Between Species Richness, Island Area, and Isolation

The species richness (SR) of bamboo plants, as well as different reproductive types, demonstrated a positive correlation with increasing island area. The proportion of variance explained by area (R²) for each richness category was as follows: SR (R² = 73%), sympodial (R² = 72%); monopodial (R² = 59%); and polycyclic (R² = 57%) (Figure 3). The slopes (z-values) of the species–area relationship were as follows: SR = 2.07; sympodial = 0.94; monopodial = 0.82; and polycyclic = 0.44. Furthermore, as illustrated in Figure 3, the distance to the nearest continent, an indicator of isolation effects, exhibited no significant relationship with SR or any reproductive types (p > 0.05). This suggests that the SR and reproductive types of bamboo species on islands are only marginally affected by isolation effects.

3.3. Bamboo Species and Island Environmental Factors

The Pearson correlation analysis and Mantel test results (Figure 4) revealed that island area was significantly positively correlated with elevation (r = 0.55, p < 0.01), ND (r = 0.65, p < 0.001), NLB (r = 0.49, p < 0.01), and the Area-Based Rao’s Index (r = 0.49, p < 0.01). Conversely, island area exhibited significant negative correlations with PAR (r = −0.41, p < 0.05) and FD (r = −0.41, p < 0.05). These findings indicate that elevation, ND, NLB, and the Area-Based Rao’s Index increase with larger island areas, while PAR and FD decrease as island area expands.

Moreover, PAR and FD, which reflect island shape, showed a significant positive correlation (r = 0.70, p < 0.001), implying that an increase in PAR is accompanied by a rise in FD. Bio 14 demonstrated the weakest correlations with other environmental factors, exhibiting a significant negative correlation only with Bio 6 (r = −0.84, p < 0.001), another climatic variable.

Furthermore, as shown in Figure 4, area (A), elevation (ELE), FD, ND, NLB, BFA, and PAR are key environmental factors influencing bamboo species with different reproductive types. Area (r = 0.459, p < 0.001), elevation (r = 0.428, p < 0.001), FD, NLB, and ND (r = 0.414, p < 0.001) are significant contributors to SR on islands. Islands with larger areas, higher elevations, more complex shapes, and greater numbers of land bridges and docks tend to exhibit higher species richness.

The effect of environmental factors varies across different reproductive types. Specifically, sympodial species richness is primarily influenced by A, ELE, PAR, FD, ND, NLB, and BFA. Monopodial species richness is mainly affected by A, ELE, FD, ND, and NLB. Similarly, polycyclic species richness is primarily influenced by A, ELE, FD, ND, and NLB.

3.4. Multidimensional Driving Factors of Island Bamboo Species

The structural equation model was evaluated for reliability and convergent validity. As shown in

Table 1. Measurement model results.

Construct	Type	Items	Loadings	CR	AVE
Isolation	Reflective	DNC	0.876	0.817	0.691
		SSD	0.784
Scale	Reflective	A	0.919	0.872	0.773
		ELE	0.837
Shape	Reflective	PAR	0.932	0.924	0.858
		FD	0.921
Climate	Reflective	Bio6	0.961	0.916	0.922
		Bio14	−0.959
Development intensity	Reflective	ND	0.93	0.871	0.696
		NLB	0.879
		BFA	0.671
Habitat diversity	Reflective	Area-Based Rao’s Index	1.000	1.000	1.000
Species richness	Reflective	SR	0.999	0.973	0.9
		Sympodial	0.97
		Monopodial	0.925
		Polycyclic	0.898

, all factor loadings exceeded 0.5, the average variance extracted (AVE) values were greater than 0.5, and the composite reliability (CR) values surpassed 0.7. These results satisfy or exceed the minimum thresholds of 0.5 for factor loadings, 0.7 for composite reliability (CR), and 0.5 for average variance extracted (AVE) [46], confirming that the reliability and convergent validity of the 12 environmental factors were adequate.

The total effects of each environmental factor, calculated as the sum of direct and indirect effects (Figure 5), revealed that island scale, development intensity, and climate exert positive overall effects on SR. In contrast, isolation, habitat heterogeneity, and shape demonstrated negative overall effects.

Specifically, island scale and development intensity were identified as the primary drivers of species richness, with total effects of 0.55 and 0.178, respectively. Development intensity and habitat heterogeneity acted as mediators across multiple pathways. Climate, scale, and island shape influenced species richness indirectly by affecting habitat heterogeneity, with total effects of 0.19, 0.398, and 0.284, respectively. Furthermore, scale and isolation indirectly impacted species richness through development intensity, with total effects of 0.731 and −0.102, respectively.

Additionally, as illustrated in Figure 5, island scale exerts a significant positive effect on species richness (β = 0.550), primarily through area, which accounts for 91.9% of the variance in scale. This finding suggests that larger islands provide more extensive habitats for bamboo species, thereby supporting higher species richness.

Furthermore, island scale significantly positively influences both development intensity and habitat heterogeneity, indicating that larger islands with higher elevations are generally more developed and exhibit greater habitat heterogeneity. While isolation does not have a direct significant effect on species richness, it indirectly impacts species richness through its effect on development intensity (β = −0.280). This implies that regions farther from the mainland or other islands tend to have lower development intensity, which may further restrict resource availability, ultimately suppressing species richness.

4. Discussion

4.1. Area Effect

The species richness (SR) of island bamboo species, as well as different reproductive types, increased with the expanding area (Figure 3), aligning with the species–area relationship theory [4]. The species–area relationship is a well-established ecological principle that describes the positive correlation between species richness and habitat area, whereby species richness increases as habitat area expands [52]. The z-value, commonly used to represent the growth rate of species richness in relation to area, ranged from 0.44 to 2.07 in this study, deviating significantly from the typical z-value range [53,54].

Notably, the z-values for bamboo species richness (SR) and sympodial types were significantly higher than typical ranges, while those for monopodial and polycyclic types were comparatively lower. This variation is closely linked to the ecological adaptability and functional traits of different reproductive types in island environments [55]. Sympodial bamboo species exhibit strong ecological advantages, including greater culm height, diameter, internode length, and culm wall thickness, which enable efficient utilization of vertical space resources [35]. In the context of limited island area, these traits allow sympodial bamboo to rapidly increase biomass per unit area without relying on extensive horizontal expansion. Additionally, the short rhizomes of sympodial species result in dense culm distribution [56], forming bamboo forests that actively enhance soil structure, conserve water and soil, and create favorable microhabitats for their growth. These ecological characteristics further reinforce their growth and reproductive advantages in space-constrained environments.

In contrast, monopodial bamboo species rely primarily on long rhizomes for horizontal expansion, which can extend 2–5 m annually [57]. However, this horizontal growth strategy is restricted by the limited space available on islands. Furthermore, monopodial bamboo species generally have smaller culm height and diameter compared to sympodial species [35], reducing their competitive advantage in vertical resource utilization. As a result, monopodial bamboo species exhibit less significant responses to area expansion, and their dispersed growth pattern makes it challenging to form high-density communities in resource-limited island environments. Polycyclic bamboo species, which possess characteristics of both sympodial and monopodial types, are sparsely represented on Fujian islands and exhibit limited responses to area expansion. This could be attributed to their lower competitive ability or ecological traits adapted to specific environments, which warrants further investigation.

The structural equation model (PLS-SEM) was used to analyze the effects of environmental factors on SR and different reproductive types, revealing that island scale had the most significant contribution to SR and reproductive types. Among the components of island scale, area was identified as the key driver influencing SR and reproductive types. This result aligns with island biogeography theory [10], highlighting the sensitivity and dependence of bamboo species on habitat area.

The area effect suggests that larger islands provide a greater diversity of habitat types and resources [58], including varied soil conditions, humidity levels, and light availability, creating suitable environments for bamboo species with different adaptive traits. Moreover, larger islands typically support larger population sizes, promoting long-term population stability and reducing the risk of species extinction [59].

Furthermore, different reproductive types exhibit varying environmental requirements. Increased space and resource availability on larger islands reduce interspecific competition, facilitating greater niche differentiation [60,61]. This promotes coexistence among species, particularly those with unique ecological needs that might otherwise be competitively excluded on smaller islands [62].

4.2. Isolation Effect

In island biogeography, isolation is widely regarded as one of the critical factors influencing species richness [23,63]. According to MacArthur and Wilson’s island biogeography theory, greater distances between islands and the mainland (or other species sources) result in lower immigration rates, leading to decreased species richness [59,64,65,66]. However, this study revealed no significant relationship between bamboo species richness and isolation (Figure 3 and Figure 5).

This lack of significance may be attributed to the reproductive strategies of bamboo. Bamboo primarily propagates asexually through rhizomes [61], while its sexual reproduction cycle is prolonged, and seed dispersal depends largely on gravity, short-distance water flow, or animals, with limited capacity for long-distance dispersal across barriers such as oceans. Additionally, bamboo’s considerable economic and cultural value has led to frequent human-mediated introductions to various islands or regions for uses such as construction, handicrafts, and food [67], further mitigating the effects of isolation on species richness.

Furthermore, the Fujian islands were historically connected to the mainland [68]. Over extended geological timescales, bamboo species may have gradually dispersed and established populations on these islands, rendering the current degree of isolation less impactful on species richness.

4.3. Development Intensity and Habitat Heterogeneity on Islands

In addition to island scale, development intensity is one of the most significant drivers of species richness. While development intensity has a relatively small direct effect on the species richness of island bamboo plants (Figure 5), it plays a mediating role in multiple pathways, bridging the complex relationships among island scale, isolation, and species richness.

Larger islands (with greater area and higher elevation) possess higher resource-carrying capacities and more diverse habitat features, making them more attractive for human activities such as agricultural development, tourism, and infrastructure expansion [69]. These activities often involve the introduction of artificial structures and the redistribution of vegetation, providing additional space for bamboo growth and expansion. Moreover, the boundary effects created by artificial structures may further facilitate species dispersal and reproduction [70,71].

Islands with low isolation, being closer to the mainland or other islands, benefit from convenient transportation and lower resource input costs, making them more prone to human disturbances [72,73]. These disturbances often manifest as higher development intensity, such as increased building density and expanded non-forest areas. While such development alters original natural habitats, it may also enhance resource availability, creating opportunities for certain highly adaptable bamboo species to expand their populations. However, intensive development activities could have negative impacts on certain bamboo species, especially those with limited adaptability or restricted distribution ranges. Such species may be at risk of local extinction due to habitat fragmentation or reduced habitat quality. While no bamboo extinctions have been recorded in the study area, similar island ecosystems worldwide have frequently experienced local extinctions caused by human activities. This pattern may also be present in island bamboo communities.

The Area-Based Rao’s Index serves as a critical indicator of island habitat heterogeneity. Correlation analysis of island environmental factors (Figure 4) revealed a positive relationship between island area and the Area-Based Rao’s Index, suggesting that larger islands tend to exhibit greater habitat heterogeneity.

However, as illustrated in Figure 5, although development intensity positively influences habitat heterogeneity, increased habitat heterogeneity is associated with reduced bamboo species richness and richness across reproductive types. This paradox can be explained through the following mechanisms: High-intensity human activities fragment continuous habitats into isolated patches, causing habitat fragmentation and disrupting ecosystem continuity [74]. Such development divides island habitats into smaller, disconnected fragments [75,76], which can hinder the dispersal and population persistence of bamboo species, particularly those reliant on contiguous habitats.

Moreover, habitat fragmentation often limits population sizes and reduces genetic flow between populations [77], ultimately contributing to a decline in species richness. While high-intensity development enhances habitat heterogeneity, it frequently diminishes habitat quality. For instance, the expansion of farmland and landscaping vegetation may lead to soil compaction and pollution, degrading habitat quality and adversely affecting bamboo species growth and reproduction. Additionally, invasive plant species introduced through human activities may compete with and even suppress native plants [78].

Therefore, although moderate development intensity may indirectly enhance bamboo species richness by modifying existing habitats, excessive development disrupts habitat connectivity and quality, resulting in negative impacts on species richness [79].

4.4. Climatic Factors

Climate is typically a key determinant of plant distribution and species richness [80,81]. However, in this study, the influence of climate on bamboo species richness and the richness of different rhizome types was limited, affecting island bamboo species richness only indirectly through habitat heterogeneity. This could be attributed to the broad climatic adaptability of bamboo, which allows it to thrive under diverse climatic conditions and reduces its sensitivity to climatic changes. Additionally, the islands in the study area exhibit relatively uniform climatic conditions (e.g., temperature, precipitation, humidity).

Future research should consider integrating additional environmental factors, such as soil, into models to assess their relative importance alongside climatic variables. Long-term ecological monitoring and more granular climatic data could also be employed to evaluate the dynamic impacts of climatic changes on bamboo species richness. Such efforts would provide a deeper and more comprehensive understanding of the distribution patterns of bamboo species richness across the Fujian islands and other subtropical islands.

4.5. Implications for the Conservation and Management of Island Bamboo Species

Based on the species richness of bamboo and its reproductive types on Fujian islands and the driving mechanisms of their environmental factors, this study recommends the following strategies for future island management and bamboo conservation: 1. Regulate development intensity: Ensure that development activities remain moderate to avoid excessive destruction of contiguous habitats. 2. Establish ecological corridors: Connect developed areas to maintain habitat connectivity and reduce fragmentation effects. Enhanced habitat connectivity can mitigate the isolation of bamboo populations, facilitate gene flow among species, and improve species adaptability. 3. Protect key resources and habitats: Prioritize the conservation of critical resources and specific habitats based on the ecological requirements of bamboo species with different reproductive types. 4. Monitor invasive species: Pay special attention to areas with intensive development to prevent invasive species from entering islands via development activities, thereby reducing competitive pressure on native bamboo species.

By scientifically managing the relationships between island attributes, development intensity, habitat heterogeneity, and species richness, it is possible to conserve bamboo species diversity while supporting the sustainable development of ecosystem functions.

5. Conclusions

This study explored the driving effects of six major categories of environmental factors—island scale, isolation, shape, climate, development intensity, and habitat heterogeneity—on the species richness of bamboo plants and their different reproductive types on islands. It provided a deeper understanding of the spatial distribution patterns of bamboo species richness and their reproductive types across island ecosystems. The findings indicated that bamboo species richness and reproductive types on Fujian islands align with the species–area relationship, supporting the assumptions of island biogeography theory. However, while species richness was significantly influenced by the area effect, it did not support the isolation effect. Among the 12 environmental factors examined across six categories, island scale emerged as the dominant factor influencing bamboo species richness and the richness of different reproductive types. Specifically, area was identified as the key driver. As well as area, development intensity and habitat heterogeneity also had significant impacts, while isolation and climate had relatively minor effects. Development intensity enhanced bamboo diversity but could simultaneously decrease species richness by altering habitat heterogeneity, with the intensity of development being a critical determinant. This study advances theoretical insights into island biogeography and bamboo ecology by uncovering the mechanisms through which factors such as island scale, isolation, shape, climate, development intensity, and habitat heterogeneity affect bamboo species richness. Practically, it offers vital scientific support for the conservation of bamboo plants, the management of island ecosystems, and the design of sustainable development strategies. By understanding these influencing factors, we can better protect bamboo diversity, maintain the ecological health of island systems, and contribute to the sustainable development of regional ecosystems.