Urban green spaces (UGSs) are significant features of urban landscapes and integral to urban planning, yet factors shaping tree species composition remain insufficiently understood. This study quantified soil sealing across twenty-five UGSs in the Tokyo Metropolitan Area and investigated patterns in tree species composition as influenced by soil sealing using the proportion of sealed surface area (PSSA), natural soil area (SA), urban proximity (UP), and green space age as relevant metrics. Tree species presence-absence data from selected UGSs were analysed using the pairwise and multisite Jaccard similarity index, hierarchical cluster analysis, and generalised linear models. Results showed varying PSSA (0–58.8
Climate change is one of the major drivers of changes in the natural habitats of many insect pests worldwide. The white-striped longhorn beetle Batocera lineolata Chevrolat, 1852 (Coleoptera: Cerambycidae) is a serious pest species currently causing severe damage to Eucalyptus L’Hér., 1789 (Myrtales: Myrtaceae) plantation forests in Northern Vietnam. Understanding the geographical distribution characteristics of this pest is important for forest management strategies, especially under a changing climate. Therefore, this study sought to clarify environmental factors associated with the presence of B. lineolata and to predict its current and future habitat suitability areas. Distribution data of the pest were collected from field surveys in seven provinces in Northern Vietnam, and the species distribution model was developed using Maxent and 11 bioclimatic and topographical variables. Our study showed that the selected model had a good performance (test AUC = 0.878) compared with the null model (test AUC = 0.539). Mean diurnal temperature range (Bio 2, 21.5
While practicing qigong in natural settings reportedly enhances its benefits, the influence of specific landscape attributes has not been studied extensively. According to the Landscape Preference Matrix, coherence and complexity are key factors in determining environmental preference. Unlike research on meditation, which considers complexity (such as plant diversity), studies on qigong tend to focus more on coherence, leaving the role of complexity and its potential impact on practice efficacy in urban settings unexplored. Because urban qigong takes place in designed greenspace, the answer bears directly on how planting in small urban sites is specified. To address this gap, this study asked 25 experienced participants to practice qigong in three different environments in a within-subjects design: one with complex vegetation, one with coherent vegetation, and a non-vegetated control environment. The physiological indices did not differ significantly between environments, although an exploratory pairwise comparison showed a lower heart rate in the complex-planting condition than in the control. Both vegetated environments yielded significantly higher qi intensity, qi experience, and environmental preference than the control, with no difference between the two planting configurations. For practice, the findings tentatively suggest that a species-rich planting can be introduced in a small urban space without loss of perceived coherence, so that biodiversity-oriented planting and health-supportive design need not be traded off against each other.
Residential outdoor landscapes constitute the most frequently encountered visual environment for urban residents, yet systematic evaluation of their aesthetic quality and ecological service value remains lacking. This study developed an integrated three-stage framework combining deep learning semantic segmentation, the Scenic Beauty Estimation method, and machine learning regression modeling to assess public visual aesthetic preference for residential outdoor landscapes, understood as one measurable component of the cultural ecosystem services provided by urban residential green spaces. A PSPNet model performed pixel-level semantic segmentation on 2816 field-collected landscape images from 32 residential communities in central Chengdu (mIoU = 0.763), extracting 13 element categories to construct a residential landscape feature indicator system. Public aesthetic preference scores were obtained through 276 valid questionnaires. Pearson correlation analysis identified the Green Visual Index (GVI) as the strongest positive predictor (r = 0.57), while the Interference Factor Index (IFI) showed the most pronounced negative correlation (r = − 0.46). The random forest model achieved R2 = 0.796, substantially outperforming the stepwise OLS regression (adjusted R2 = 0.517). SHAP interpretability analysis revealed a marginal contribution saturation effect for GVI at approximately 35–40
As urban ecological conservation receives increasing attention, coordinating green infrastructure (GI) spatial structure with biodiversity conservation has become an important issue in urban ecological planning. However, a highly structured GI does not necessarily correspond to high bird habitat (BH) suitability, and existing research has paid relatively little attention to the spatial congruence and mismatch relationships between the two, and how these can be further translated into ecological network planning strategies. To address this issue, this study employs Hangzhou as a case study. Green infrastructure assessment (GIA) was applied to evaluate GI spatial structure across three dimensions: scale, morphology, and pattern. The Maximum Entropy (MAXENT) model is utilized to assess BH suitability. The four-quadrant model is applied to identify spatial congruence and mismatch zones between GI and BH, based on which three optimization objectives are proposed. Using source patch extraction- resistance surface construction-circuit theory, multi-objective ecological networks (ENs) are developed. Finally, structural resilience assessments of connectivity and robustness are conducted for three ENs using connectivity indices and network attack simulations. The principal findings of this study include: (1) The spatial structure of GI and BH suitability generally exhibit a positive spatial correlation; with some regions displaying high or low values align, while other regions demonstrate mismatched relationships. (2) The three ENs exhibit distinct differences in source area size and composition, corridor number and length, and network topology, reflecting the spatial organizational characteristics associated with different objectives. (3) EN structures that achieve dual-objective coordination exhibit optimal resilience. This study clarified the spatial relationship between GI structure and BH suitability and provided methodological insights for integrating biodiversity conservation with the allocation of blue-green spaces to support sustainable urban development.
