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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. [ABSTRACT FROM AUTHOR]

China's rare and endangered bamboo species belonging to the Indocalamus genus, specifically Indocalamus decorus Q. H. Dai, Indocalamus hirsutissimus Z. P. Wang & P. X. Zhang, and Indocalamus pedalis (Keng) P. C. Keng, possess notable value in biodiversity conservation and have significant potential for use in landscape design. Using an enhanced MaxEnt model, this study forecasted shifts in the species' potential range under four separate climate scenarios (SSP1-RCP2.6, SSP2-RCP4.5, SSP3-RCP7.0, and SSP5-RCP8.5), considering both the historical period (1970–2000, referred to as "the current period") and upcoming timeframes (2021–2040, 2041–2060, 2061–2080, and 2081–2100). The analysis disclosed that the present total potential habitat area for these species is approximately 251.79 × 104 km2, with high, medium, and low suitability areas occupying 0.15 × 104 km2, 125.39 × 104 km2, and 126.26 × 104 km2, respectively. The minimum temperature of the coldest month emerged as the critical determinant of their potential habitat distribution. Expected climate changes are likely to increase the suitable habitat for these species, although areas with low suitability might slightly diminish, with Guizhou and Chongqing showing the least impact. The distribution centers of suitable habitats for the three plant species consistently exhibit a westward shift under various climate scenarios. These results contribute valuable insights for the spatial distribution, continuous monitoring, sustainable management, and ex situ conservation in response to climate change. [ABSTRACT FROM AUTHOR]

Invasive alien plants (IAPs) pose a significant threat to island biodiversity and severely impact ecosystems. Understanding the species–area relationship and environmental determinants of growth forms for IAP species on subtropical islands is crucial for establishing an IAP's early warning mechanism, enhancing island ecological management, and protecting the ecosystems of Fujian and other subtropical islands. The study identified significant species–area relationships for IAPs and different life-form plants (trees, shrubs, and herbs), with slopes of 0.27, 0.16, 0.15, and 0.24, respectively. The small island effect does not apply to all species. Isolation has little effect on species richness, and the IAPs on Fujian islands do not conform to the isolation effect in island biogeography. Landscape factors are the main determinants of IAPs and different life-form species richness, with area, shape index, and perimeter–area ratio being the three primary landscape factors. These environmental factors are closely related to habitat heterogeneity. Besides landscape factors, different life forms respond differently to environmental factors. Climate drives the species richness distribution of shrubs and herbs, while trees are mainly influenced by human activities. Overall, landscape, human disturbance, and climate jointly drive the distribution of IAPs, with landscape factors being the most significant. [ABSTRACT FROM AUTHOR]

Plant invasions threaten the biodiversity of islands, causing serious impacts on their ecosystems. To investigate the distribution patterns of invasive alien plants on subtropical islands, the environmental determinants of species richness, and the growth forms of invasive alien plants, this study analyzed the composition and origin of invasive alien plants on 77 islands in Fujian. The similarity in the distribution of invasive alien plants between islands was assessed using the UPGMA. Moreover, feature selection, best-subset regression, and variance decomposition were performed using 19 environmental variables characterizing climate, anthropogenic disturbance, and landscape/geography, as well as the species richness and growth forms of invasive alien plants. Through the analysis, the main environmental factors affecting the species richness and growth forms of invasive alien plants on the Fujian islands were identified. The results showed 142 species of invasive alien plants in 38 families and 102 genera on 77 islands in Fujian. Annual herbs constituted the most representative growth form of invasive alien plants and tropical America was the main origin of invasive alien plants. The distribution of invasive alien plants across the 77 islands in Fujian showed a high degree of similarity, suggesting a nested pattern in their distribution. The proportions of building and farmland area (BFA), island area (A), and maximum elevation (ME) were the main driving factors of species richness and growth forms for invasive alien plants. In particular, BFA played a key role in driving plant invasion. The results of this study can help establish an early warning mechanism for invasive alien plants and better implement island ecological management, which are important for the protection of subtropical island ecosystems. [ABSTRACT FROM AUTHOR]

National Forest Villages in China are village types with significant environmental resources and cultural landscapes that play a vital role in ecological conservation, tourism development, territorial planning, and other elements. Understanding tourists' landscape perception preferences is important to the long-term development of their landscape systems. Using Xidi village from the second batch of National Forest Villages as a research case, we gathered the evaluation digital footprints of visitors to the village with Python (version 3.12.0) and then used the ROST CM6 software and the semantic network analysis method to sort out the general characteristics of visitors' perceptions of the village's landscape. Finally, we constructed a multidimensional landscape perception model by studying precise details of passengers' views of Xidi village on four dimensions: natural landscape, humanistic landscape, landscape environmental atmosphere, and emotional state. The findings show that travelers' perceptions of Xidi village's landscape primarily focus on scenery, architecture, and culture, with the humanistic landscape having the strongest degree of perception, the landscape environment atmosphere having the middle degree of perception, and the natural landscape having a weaker degree of perception. Most travelers have positive emotions, and commercialization and homogenization are negative factors that trigger negative emotions. The optimization recommendations for Xidi village's landscape system are then offered in light of the study's findings. [ABSTRACT FROM AUTHOR]

High-resolution image segmentation for landscape applications has garnered significant attention, particularly in the context of ultra-high-resolution (UHR) imagery. Current segmentation methodologies partition UHR images into standard patches for multiscale local segmentation and hierarchical reasoning. This creates a pressing dilemma, where the trade-off between memory efficiency and segmentation quality becomes increasingly evident. This paper introduces the Multilevel Contexts Weighted Coupling Transformer (WCTNet) for UHR segmentation. This framework comprises the Mult-level Feature Weighting (MFW) module and Token-based Transformer (TT) designed to weigh and couple multilevel semantic contexts. First, we analyze the multilevel semantics within a local patch without image-level contextual reasoning. It avoids complex image-level contextual associations and eliminates the misleading information carried. Second, MFW is developed to weigh shallow and deep features for enhancing object-related attention at different grain sizes from multilevel semantics. Third, the TT module is introduced to couple multilevel semantic contexts and transform them into semantic tokens using spatial attention. Then, we can capture token interactions and obtain clearer local representations. The suggested contextual weighting and coupling of single-scale patches empower WCTNet to maintain a well-balanced relationship between accuracy and computational overhead. Experimental results show that WCTNet achieves state-of-the-art performance on two UHR datasets of DeepGlobe and Inria Aerial. [ABSTRACT FROM AUTHOR]