As important linear public spaces, urban greenways are highly important for improving public health. Many studies have proven the benefits of urban greenways for human well-being, but fewer studies have focused on the impact of their specific environmental types and characteristics on physical and mental health. In this study, 100 subjects participated in a comparative experiment on three types of urban greenways (urban roads, urban parks, and urban rivers), and corresponding physiological indicator (systolic blood pressure [SBP], diastolic blood pressure [DBP], and pulse) and psychological indicator (perceived restorativeness scale [PRS] and positive and negative affect schedule [PANAS]) data were collected. The results indicated that (1) different greenway environment types lead to different physiological and psychological states; (2) urban park-type greenways (SBP [t = 2.37, p = 0.020], DBP [t = 2.06, p = 0.042], PANAS = 2.80, PRS = 5.39) have the greatest physical and mental recovery benefits, followed by urban river-type greenways (SBP [t = 2.84, p = 0.006], DBP [t = 1.29, p = 0.200], PANAS = 2.30, PRS= 5.02) and urban road-type greenways (SBP [t = 0.78, p = 0.440], DBP [t = 0.37, p = 0.716], PANAS = 2.00, PRS = 4.15); (3) plant color and layer diversity have a significant positive impact on the mental health benefits of the three greenway types; (4) the aesthetics of waterscapes and ornaments can significantly improve the perceived restoration ability of urban river-type greenways; and (5) the comfort of pathways and facilities can effectively promote the psychological recovery potential of urban road-type greenways. These findings systematically demonstrate for the first time the differences in restoration potential among urban greenways of different environmental types and summarize the key landscape characteristic predictors influencing the restoration potential of various types of urban greenways. Our research provides new ideas for proactive greenway interventions for physical and mental health and for enriching the restorative environmental science system.

Traditional visual quality assessments of rural landscapes rely on subjective methods. This study integrates eye-tracking technology with subjective perception evaluation to construct a visual quality assessment model for rural landscapes, aiming to reveal the intrinsic relationship between objective visual behavior and subjective perception, with the aim of providing scientific guidance for rural landscape planning to promote sustainable rural development. Using landscape photographs from nine rural sampling sites in Guangzhou, eye-tracking experiments were conducted to collect participants’ eye movement data, combined with online questionnaires to obtain scenic beauty ratings and landscape characteristic factor evaluations. The findings reveal the following: (1) Eye-tracking experiments and subjective evaluation results showed high consistency, with samples having higher scenic beauty ratings demonstrating more prominent performance in core eye movement indicators such as total fixation duration and count, and total saccade duration, and typically possessing higher landscape characteristic factor values. (2) Urban–suburban-integrated rural landscapes exhibited poorer visual quality, characteristic-preservation rural landscapes elicited more in-depth and sustained visual exploration, and clustered-improvement rural landscapes possessed higher scenic beauty ratings and landscape characteristic factor values. (3) Total saccade duration was the key eye movement indicator for predicting scenic beauty ratings. (4) Multiple landscape characteristic factors significantly influence eye movement behavior.

Assessing the landscape health of suburban forest parks is a prerequisite for achieving the dual objectives of forest resource conservation and recreational services. However, studies that analyze landscape health in suburban forest parks at a landscape scale by subdividing the landscape into multiple sampling units and adopting a multi-functional perspective have been limited. This study focuses on Xiqiao Mountain National Forest Park and establishes a landscape classification system and indices, taking into account its multifunctionalities. The study employs the entropy weight method to determine indicator weights and utilizes grid analysis and spatial interpolation to analyze the spatial distribution of landscape health under multiple sampling units and functionalities, along with the differences in its impact and influencing factors. The results indicate that: (1) regions with “very poor” and “poor” landscape health grades under multiple sampling units and functionalities exhibited a sheet-like distribution pattern, covering approximately 69.46% to 98.86% of the total area. In contrast, regions with “very good” and “good” grades are primarily located in block-like or linear patterns in the northern, central, and southern regions of the park, accounting for approximately 1.07% to 17.20% of the total area. (2) The area ratios of “very good” and “good” landscape health grades for recreational landscapes under varying sampling units were consistently higher than those of the same grades for eco-conservational landscapes, with a 5.03%–15.43% difference. This suggests a greater emphasis on recreational functionality. (3) The impact of three different sampling unit sizes on the landscape health of Xiqiao Mountain National Forest Park under multifunctionalities is not significantly different; however, the forest/non-forest area ratio and quantity ratio are vital factors influencing its landscape health. The landscape health assessment results, considering multiple sampling units and functionalities in this study, serve to provide technical method support and practical case references for the planning, construction, and management decision-making of suburban forest parks.

Natural environments contribute to people's perception, preference and health restoration. Many researchers have focused either on the positive effects of overall rural environments on stress recovery or concentrated on the perception and preference aspects of the rural landscape, but few have integrated perception, preference and stress recovery simultaneously. This paper developed a framework which includes 11 elements and 38 element components related to Linpan, China, and distributed it online as part of a survey. As a result, a total of 324 valid questionnaires were collected. The questionnaire included demographic details, perception and preference degree for Linpan, as well as self-estimations of stress recovery. Stepwise multiple linear regression was employed, and revealed 16 significant predictors for the perception, preference and stress recovery in rural environments. In terms of elements, atmosphere and imagery were the two elements that could be best perceived, while woodland, farmland, water, residence and road were the five most important elements for the preference. Moreover, seven elements were also identified as significant predictors for stress recovery. Among the element components, tranquility as well as road and water proximity were the two significant predictors for perception, while wide visibility as well as woodland and residence blending contributed significantly to stress recovery. The five element components of woodland interior, vegetable field, stream, courtyard space and branch road each had a significantly predictive ability for preference and stress recovery. These findings extend the understanding of the perception, preference and restorative properties of rural environments through the combination of elements and element components in Linpan of Western Sichuan, helping to improve the quality and characteristics of rural external and internal environments and create health-promoting environments.

Landscape health assessments are crucial for balancing conservation and use practices. However, studies considering different land use intensities and grid scales from a functional perspective are limited. This study aimed to develop a landscape classification and indicator system based on functional characteristics using Xiqiao Mountain National Forest Park and Yunyong National Forest Park as research objects. The entropy weight method was used to determine indicator weights, and grid analysis and spatial interpolation were used to analyze the spatial distribution, impact differences, and factors influencing landscape health. The effect of different grid scales on landscape health under varying land use intensities first weakened and then strengthened with increasing grid scales; the optimal grid scales for the two parks were 54 × 54 m and 66 × 66 m, respectively. The forest/non-forest area ratio decreased as the health level of the landscape increased. At the optimal grid scale, the threshold range of the forest/non-forest area ratio for achieving optimal landscape health was 4.46–5.81 and 0.79–0.87 in the two parks, respectively. The results indicate that improved landscape health in suburban forest parks requires the intensive development of construction land, enhanced forest management, and functional synergistic designs to promote coordinated functional development.

Background: Mycetia, a subshrub genus within the subfamily Rubioideae (Rubiaceae), is predominantly distributed in tropical Asia, lacking comprehensive plastid genomic resources. This study aimed to characterize the complete plastid genomes of two Mycetia species and explore their structural features and evolutionary relationships. Methods: The plastid genomes of Mycetia hirta and Mycetia sinensis were sequenced and assembled. We analyzed genome structure, simple sequence repeats (SSRs), long repeats, codon usage, nucleotide diversity (π), and Ka/Ks and conducted phylogenetic analysis. Results: Both genomes exhibited a typical quadripartite structure (153,989–154,588 bp; GC content 37.7–37.8%), encoding 126 genes (86 protein-coding, 8 rRNA, and 32 tRNA). Both chloroplast genomes contained 52–60 SSRs and three repeat types with minor interspecific differences. Junction regions and codon usage were highly conserved, with slight variations in RSCU values. The average π was 0.0096, and the non-coding trnE-trnT (π = 0.0817) emerged as a potential DNA barcode. The average Ka/Ks was 0.2900, indicating purifying selection. Phylogenetic analysis confirmed the monophyly of Mycetia within Argostemmateae. Conclusions: This study provides the first comparative plastid genomic analysis for Mycetia, enhancing our understanding of its genetic diversity and supporting future phylogenetic and taxonomic research on the genus.