Restorative effects of plant landscapes under different weather and phenology conditions: evidence from EEG and psychological responses

Abstract

Studies on plant landscapes reveal a high degree of complexity in how environmental factors interact with individuals’ psychophysiological recovery processes, particularly the moderating role of individual differences in recovery effects remains to be systematically and thoroughly explored through empirical research. Therefore, we established a three-dimensional experimental framework of “weather-plant phenology-plant type,” integrating EEG and psychological assessment methods to evaluate psychophysiological recovery effects of different plant landscape conditions on individuals. We also incorporated individual different variables such as personality traits and weather preferences to explore their moderating mechanisms on recovery effects. Results indicate: (1) Regardless of weather conditions, blooming plant landscapes significantly enhance physiological (Pa, Pm) and psychological recovery levels, while recovery effects in senescent landscapes vary depending on plant type; (2) Both neuroticism and extraversion significantly modulated the restorative effects of plant landscapes. Neuroticism exhibited a nonlinear dynamic pattern of “promotion-optimal-inhibition”; (3) Personality traits were the key factor influencing restorative differences (highest Mantel’s r), with explanatory power significantly exceeding that of weather preference and gender. We deepen our understanding of plant landscape recovery mechanisms through multifactor interaction and individual variation lens, providing theoretical foundations and practical references for urban green space planning and the scientific construction of healing urban environments.

Introduction

As urbanization advances, declining environmental quality and accelerated lifestyles have directly impacted residents’ psychological well-being, leading to a gradual rise in mental health issues such as anxiety and depression^1,2. According to estimates by the World Health Organization (WHO), approximately one billion people worldwide suffer from mental disorders, with psychological conditions such as depression and anxiety emerging as one of the primary threats to human health^3,4. The restorative effects of natural landscapes on human psychological well-being have become a central topic in environmental psychology and ecological design, and horticultural plants and activities have been proven to effectively improve physical, psychological, and cognitive states^5,6.

Attention Restoration Theory (ART) shows that natural elements possessing “Soft Fascination” can effectively alleviate cognitive fatigue and promote emotional recovery by capturing involuntary attention, with a primary emphasis on their restorative effects on cognition^7,8. The Stress Recovery Theory (SRT) posits that natural environments can alleviate stress responses and promote emotional well-being by reducing an individual’s physiological arousal levels; it primarily emphasizes the regulatory role of natural environments on emotional and physiological states⁹. For example, in such related studies, ornamental plants stand out particularly due to their distinct seasonality and visual aesthetics¹⁰. The process of plant landscapes blooming and withering not only reflects the rhythms of life but also evokes emotional resonance in viewers^11,12.At the same time, weather conditions, as a key contextual moderator, influence the perceived restorative value of the same plant landscape^13,14; Floral scents can boost positive emotions and promote relaxation, and typical floral colors and shapes have been shown to have the same effect^15,16. The blooming and withering of plants induce distinct psychological responses in observers, with their emotional valences exhibiting significant divergence¹⁷. In summary, ART and SRT explain the restorative effects of natural environments from the perspectives of cognitive recovery and emotional-physiological regulation, respectively. Therefore, we have incorporated a dual-pathway mechanism into our analytical framework to provide a more comprehensive explanation of the impact of plant landscapes on individuals’ physiological and psychological recovery. However, existing research on plant restorative effects predominantly focuses on single-dimensional factors (such as analyzing plant species alone or considering weather conditions exclusively), rarely systematically exploring how the interaction of multiple factors influences human restoration.

Previous studies have shown that different phenological states of plants can lead to significant changes in visual and olfactory perceptions, thereby influencing recovery outcomes. During the flowering period, higher color saturation and rich aromas can significantly enhance positive human emotions, creating an aesthetic reward effect^14,18. Research indicates that viewing cherry blossoms during their blooming period can significantly enhance parasympathetic nervous system responses, effectively alleviating physiological stress and boosting viewers’ sense of well-being¹⁹. Conversely, observing fallen peonies increases viewers’ fatigue levels and anxiety scores¹⁴. Therefore, we believe that plant species and phenological states may elicit distinct emotional responses in individuals, serving as key factors influencing individual recovery.

Currently, individual differences—such as personality traits, preferences, and gender—have been demonstrated to exist in the perception and restorative effects of natural landscapes. However, how these differences specifically moderate the relationship between natural landscapes and physiological and psychological recovery has yet to be addressed within a systematic and in-depth theoretical framework^20–22. In terms of research methodology, electroencephalographic signals have been widely employed in studies of natural landscape restoration due to their ability to objectively capture individuals’ immediate neural responses to environmental stimuli and changes in emotional arousal^23–26. On the other hand, psychological questionnaires effectively reveal individuals’ subjective emotional experiences and restorative perceptions of natural landscapes, serving as a primary tool in research on the restorative effects of natural landscapes^27–29. However, survey results are susceptible to the influence of social desirability, individual expression, and recall bias. For the reasons outlined above, integrating physiological and psychological data enables dual verification of the recovery process. Numerous studies have already employed this approach^30,31. Based on this, introducing individual differences as a moderating variable in restorative research and conducting quantitative analysis through multimodal data represent significant challenges and innovative directions for understanding the mechanisms of plant landscape restoration and constructing healing urban landscapes.

This study incorporates individual differences (personality traits, weather preferences, and gender) as moderating variables, integrating weather × plant phenological state × plant type to construct an experimental framework. It examines the effects of different ornamental plant landscapes on individuals’ restorative experiences of psychological and physiological well-being. Therefore, the research focuses on exploring the following three core scientific questions: (1) Which landscape settings demonstrate significant differences in promoting individual psychological and physiological recovery? (2) Do individuals with different personality traits exhibit differentiated restorative responses when exposed to plant landscape stimuli? That is, which personality dimensions are more sensitive to restorative experiences? (3) What moderating role do individual factors such as personality traits, weather preferences, and gender play in the process by which multidimensional environmental factors influence recovery effects?

Methods

Research framework

As research into the impact of plant landscapes on human physical and mental health deepens, researchers have increasingly recognized that personality traits play a crucial role in the perception and restorative processes of natural landscapes. Personality, as an individual’s relatively stable psychological characteristic, shapes unique patterns of cognition, emotion, and behavior, consequently, individuals with different personality traits experience varying degrees of restorative effects when exposed to the same natural landscapes³². Some studies indicate that individuals with extroverted personalities often seek stimulation and social interaction, enabling them to feel a stronger connection with their external environment and enhance hormone secretion to alleviate stress responses^33,34. Individuals with higher levels of neuroticism are more sensitive to environmental changes, when confronted with natural landscapes, they may experience more intense emotional fluctuations, and their physiological and psychological recovery processes tend to be more complex³⁵.

While examining the influence of personality traits on the restorative effects of natural landscapes, gender differences also represent a significant factor that cannot be overlooked. Some studies indicate that women tend to rely more on environments with low sensory load (such as gardens and still water features) to achieve introspective attention restoration³⁶. Men, however, prefer high-stimulus landscapes (such as expansive lakes and dynamic water features), relying on external stimuli to divert their attention, complex terrain better stimulates the reward system, promoting dopamine release^37,38. Based on this, we believe that personality traits and gender play a crucial role in shaping individuals’ environmental preferences, behavioral patterns, and their interaction with plant landscapes. Delving into these interactive mechanisms not only facilitates more precise fulfillment of diverse groups’ restorative needs but also offers new theoretical perspectives and practical strategies for mental health interventions.

Weather preference is an individual’s subjective emotional attitude toward specific meteorological conditions, shaped by life experiences, emotional inclinations, and cognitive patterns. At its core, it represents an integrated expression of environmental adaptability and psychological needs³⁶. For instance, individuals who prefer sunny days tend to exhibit positive and optimistic emotional patterns, and their daily psychological state is more readily influenced by the positive effects of bright light and warm temperatures²⁰. When individuals observe plant landscapes on sunny days, they may experience a synergistic effect of preference and landscape matching due to the dual positive stimuli of the landscape and their preferred weather conditions^39,40. At the same time, plant landscapes offer distinctly different visual, auditory, and sensory experiences under varying weather conditions, and individual weather preferences may either enhance or diminish the restorative effects of these experiences on both mind and body⁴¹. However, most studies have examined the relationship between weather preferences and mental health as independent variables. There remains a lack of systematic research on the mechanisms through which weather preferences interact with natural landscapes to jointly influence physiological and psychological recovery, which continues to be a major challenge in this field.

This study employed a 2 (weather: sunny/rainy) × 2 (plant phenological stages: peak blooming/ senescence) × 2 (plant type: herbaceous plants/ woody plants) to construct a three-dimensional experimental framework of “weather-plant phenological state-plant type.” By integrating physiological neural indicators (EEG data) with psychological scale data (POMS questionnaire), it systematically explores the influence of dynamic characteristics in ornamental plant landscapes on individuals’ psychological and physiological restorative experiences. Additionally, we further examine the moderating effects of individual factors such as personality traits and personal preferences on restorative effects, aiming to deepen our understanding of natural restorative mechanisms influenced by individual differences and to facilitate the development of urban landscape designs tailored to individual variations (The research framework is shown in Fig. 1).

Fig. 1.

Research framework.

Experiment materials

We selected two common ornamental plant types—herbaceous plants (tulips) and woody plants (cherry blossoms)—as subjects. Using a Sony camera (A6400), photographs were taken from a visitor’s perspective at Hunan Botanical Garden (4 A-rated scenic area) and Changsha Landscape Ecological Park (4 A-rated scenic area) in Hunan Province, China. These captured tulip and cherry blossom landscapes under two phenological states (blooming and post-bloom) during both sunny and rainy weather conditions. According to color psychology theory, the diverse colors of floral plants serve both aesthetic and psychological functions. Different hues can trigger distinct psychological responses and emotional experiences, with orange, yellow, red, and white being most effective at enhancing positive emotions³¹. Therefore, we filmed tulips in orange, yellow, red, and white, along with the most common pink and white cherry blossoms, as experimental footage. Subsequently, using professional video editing software, the background audio was removed from the footage and the video was edited into eight one-minute segments, each representing a distinct ornamental plant landscape. To help understand the differences among the 8 types of landscapes, the individual pictures in Figure 2 were obtained from the internet, but they are not the experimental materials.The eight landscape videos are named as follows (Fig. 2):

Fig. 2.

Different types of plant landscapes.

Participants

Extensive research indicates that young people are facing immense psychological pressure, while plant landscapes exert a significant influence on people’s emotional responses, social behaviors, and even memory^30,42. We recruited undergraduate and graduate students from a university in China through both online and offline channels, comprising 30 males and 30 females (average age 19.97 years, SD = 2.19). Participants ranged in age from 18 to 28 years. To ensure the accuracy of the experiment, we excluded individuals with visual impairments, chronic illnesses (including mental disorders or cardiovascular diseases), smokers or heavy drinkers, as well as those who had consumed alcohol or caffeinated beverages within 24 h prior to the experiment. We conducted a pre-analysis of statistical power using the G*Power software. Under a significance level of α = 0.05, statistical power (1 − β) = 0.80, and assuming a medium effect size (f = 0.25), the minimum sample size required for a repeated-measures design was approximately 40 participants. Based on this, and considering that this study involves multi-factor interaction analysis and individual difference variables, the final sample size was determined to be 60 participants to enhance the stability of the results. This sample size meets the requirements for statistical analysis and ensures the reliability of the research findings.

All participants signed written informed consent forms prior to the experiment. We declare that all procedures were carried out in accordance with relevant guidelines and regulations, and that all experimental protocols were approved by the Ethics Committee of Central South University of Forestry and Technology, China.

Experiment design

To ensure the standardization of the experimental process and the accuracy of data collection, the purpose, procedures, and precautions of the experiment were explained to participants in both written and verbal formats prior to the experiment. Participants were also required to arrive at the laboratory 10 min early to familiarize themselves with the environment. During this period, participants are prohibited from using mobile phones and other electronic devices to prevent external stimuli from interfering with their psychological state.

After signing the informed consent form, participants were required to complete a personal information form, a weather preference questionnaire, and the Big Five personality inventory. Subsequently, participants were asked to view a one-minute neutral background image to obtain baseline EEG data and complete the POMS questionnaire based on their current psychological state, thereby establishing baseline psychological levels. The main experimental phase comprised eight video scenes. Participants randomly viewed one video before completing the POMS questionnaire, repeating this process until all landscapes were assessed. EEG signals were continuously recorded throughout the experiment, with event markers placed at the start and end of each video for subsequent data analysis (Fig. 3.).

Fig. 3.

Experimental procedure.

Physiological indicators

Electroencephalography (EEG), with its high temporal resolution and compatibility across multiple states of consciousness, has become the gold standard for quantifying the psychophysiological effects of natural landscapes. Most researchers agree that EEG technology can serve as a more objective tool for evaluating landscape and visual impacts^43,44.

We used Mind Wave, an EEG acquisition device with Think Gear ASIC Module (TGAM) as the core from Neurosky.This device is a single-channel data acquisition instrument. The sensors are placed on the forehead and earlobes, and the frequency range covers 0–100 Hz, encompassing α, β, δ and θ brainwaves. We use the eSense index to calculate attention and relaxation indices.

The formula for calculating the attention index (Pa) is as follows:

In this formula, Pa represents the attentional index, while Y, α, and β denote the score values in the EEG signal corresponding to emotional regulation, tension level, and relaxation level, respectively. Letters m, n, and t denote the weighting coefficients for the Y, α, and β wave, respectively. The exponent in this formula represents the intensity of the subject’s attentional level or psychological activity.

The formula for calculating the relaxation index (Pm) is as follows:

In this formula, Pm represents the relaxation index, while θ, δ, and α denote their respective scores in the EEG signal. The letters x, y, and z denote the weighting coefficients for each frequency band. The index in this formula indicates the subject’s current state of relaxation or calmness.

Psychological indicators

To better capture changes in participants’ emotional states, we utilized the internationally recognized and well-established mood measurement tool—the Profile of Mood States (POMS). The POMS originally comprised six subscales: Tension (T-A), Depression (D), Anger (A-H), Vitality (V), Fatigue (F), and Confusion (C), designed to quantify transient emotional states⁴⁵. The Total Mood Disturbance (TMD) score is a composite indicator of the aforementioned subscales. A higher TMD score indicates stronger emotional disturbance caused by the landscape to the subject, while a lower score suggests the landscape reflects a more positive emotional state and greater well-being. When subjects interact with natural environments and their TMD scores decrease, this indicates that these natural environments exert a positive and beneficial effect on the restoration of emotional well-being^46–48. To reduce the burden on participants, we employed a shortened 24-item version of the POMS scale, with the following calculation formula:

Personality analysis

To better analyze how different personality types influence preferences for eight landscape types and their effects on physiological and psychological recovery, we used the Big Five Personality Questionnaire to distinguish individual personality differences, and this questionnaire has been demonstrated to possess stability across languages and cultures^49,50. Psychologist Costa was the first to establish the reliability and validity of the Big Five personality questionnaire⁵¹. The questionnaire comprises five dimensions: Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness. We used the Big Five personality traits questionnaire to categorize the personality characteristics of 60 participants. The questionnaire is as follows (Table 1):

• ①Openness to experience: This dimension primarily assesses cognitive complexity and openness to experience. Positive scores indicate imaginative thinking, aesthetic sensitivity, and intellectual curiosity, while negative scores reflect rigid thinking, avoidance of novel experiences, and lower creativity.
• ②Conscientiousness: This dimension primarily assesses the capacity for goal management and self-regulation. Positive scores indicate a sense of order, achievement-driven motivation, and the ability to delay gratification, while negative scores suggest a lack of discipline, impulsivity, and lower reliability.
• ③Extraversion: This dimension primarily assesses the direction of social energy and social motivation. Positive values indicate social activity and optimism, while negative values indicate social avoidance and introversion, with low reward responsiveness⁵².
• ④Agreeableness: This dimension primarily assesses interpersonal orientation and conflict strategies. Positive values indicate a higher willingness to cooperate, greater empathy, and stronger trust, while negative values suggest indifference and a tendency toward confrontation⁵³.
• ⑤Neuroticism: This dimension primarily assesses emotional stability and psychological vulnerability. Positive scores indicate calmness, confidence, and resilience, while negative scores reflect anxiety, depression, and emotional volatility⁵⁴.

Table 1.

Personality assessment questionnaire.

Dimension	Numbers	Items
Openness to experience	1	I’m the person who dares to take risks and break the mold
	2	I am willing to try new things
	3	Compared to following tradition, I prefer creative endeavors
Conscientiousness	4	I like to plan things out from the very beginning
	5	I am usually able to complete tasks on time
	6	One of my defining characteristics is that I approach tasks with logic and organization
Extraversion	7	I tend to initiate conversations with others
	8	I try to avoid crowded gatherings and noisy environments
	9	I enjoy attending social and recreational gatherings
Agreeableness	10	I believe most people are fundamentally well-intentioned
	11	Although there are some scammers in society, I believe most people are trustworthy
	12	Despite the darker aspects of human society, I still believe that human nature is fundamentally good
Neuroticism	13	I often worry about trivial matters
	14	I often feel a sense of unease within me
	15	I often worry that something bad is going to happen

This study combined the original English questionnaire with the Chinese Big Five Personality Questionnaire Minimal Version (CBF-PI-15), which possesses good reliability and validity, to meet the requirements of our research⁵⁵.

Weather preference

Numerous studies indicate that weather significantly influences mood fluctuations^36,56. Existing research has largely focused on the negative impacts of extreme weather on psychological recovery, while studies examining the moderating role of common weather conditions in the landscape restoration process and their effects on psychological recovery remain relatively limited^57–59. Based on this, we selected two typical and representative daily weather conditions—sunny days and rainy days—and designed corresponding weather preference questionnaires to quantify participants’ preferences for each type of weather. This approach aims to explore the moderating role of environmental factors in the psychological recovery process (Table 2).

Table 2.

Weather preference questionnaire.

Dimension	Item
Preference for sunny weather	My fondness for sunny days
Preference for rainy weather	My fondness for rainy days

Result

Description of the physiological outcomes of each landscape

We conducted normality tests on the collected EEG data. The results indicate that the Pa data for subjects viewing sunny-day blooming tulips (stlb) and rainy-day senescent tulips (rtlf) did not conform to normal distribution. Similarly, the Pm data for rainy-day blooming tulips (rtlb) and rainy-day senescent tulips (rtlf) deviated from normal distribution. The Pa and Pm data for all other landscapes exhibited normal distribution. Subsequently, we employed nonparametric tests and paired-sample t-tests to determine whether there were differences in Pa and Pm data before and after subjects viewed the eight landscape videos (The results are shown in Tables 3 and 4).

Table 3.

Results of independent samples t-tests and nonparametric tests for various landscape physiological recovery indices (Pa).

Landscape types	Average	SD	Value of T/Z	Sig.
Baseline	44.85	11.95	–	–
stlb	58.21	10.19	− 6.571	＜0.000***
schb	56.44	12.94	− 5.648	＜0.000***
rchb	55.21	11.23	− 5.476	＜0.000***
rtlb	53.89	12.08	− 4.182	＜0.000***
schf	46.50	11.45	− 0.935	0.354
rchf	42.58	10.72	1.169	0.247
rtlf	39.75	9.60	2.733	0.008**
stlf	39.02	8.88	3.192	0.002**

Table 4.

Results of independent samples t-tests and nonparametric tests for various landscape physiological recovery indices (Pm).

Landscape types	Average	SD	Value of T/Z	Sig.
Baseline	52.09	10.22	–	–
stlb	63.06	9.34	− 5.806	＜0.000***
schb	60.79	9.63	− 5.225	＜0.000***
rchb	59.64	10.21	− 4.177	＜0.000***
rtlb	57.58	9.00	− 3.433	0.001***
schf	53.04	9.08	− 0.612	0.543
rchf	52.49	7.80	− 0.243	0.809
rtlf	48.71	8.01	2.119	0.038*
stlf	46.19	8.36	5.006	＜0.000***

The results are as follows: (1) Viewing four types of blooming plant landscapes resulted in a statistically significant increase in subjects’ Pa and Pm values compared to baseline levels (p < 0.001). Similarly, viewing two senescent tulip landscapes also produced significant changes in Pa and Pm values (p < 0.001). However, viewing two senescent cherry blossom landscapes did not yield significant changes in Pa and Pm values.

Further analysis revealed that after viewing the senescent tulip landscape, participants’ Pa and Pm values were significantly lower than baseline levels, indicating that these two landscapes may induce reduced physiological relaxation or increased cognitive load. Conversely, after viewing the four blooming plant landscapes, Pa and Pm values were significantly higher than baseline levels, indicating that participants experienced significant physiological relaxation.

(2) Calculate the average of Pa and Pm values and compare them to baseline levels (Fig. 4). The results are as follows: ① Prior to the main experiment, the average of baseline values for Pa and Pm were 44.85 (SD = 11.95) and 52.09 (SD = 10.22), respectively. After viewing the four blooming landscapes, the mean values for both Pa and Pm showed a significant increase. Concurrently, the senescent tulip landscape caused a significant decrease in the mean values of Pa and Pm compared to baseline; the senescent cherry blossom landscape, however, had no significant effect on the mean values of Pa and Pm.

Fig. 4.

Significance test analysis of physiological indicators for different landscapes compared with baseline.

② Further analysis revealed that all four blooming plant landscapes significantly enhanced participants’ physiological recovery indicators. And under identical conditions, the landscapes of plants in full bloom on sunny days yield superior physiological recovery effects compared to those in full bloom on rainy days. Notably, senescent tulips exhibited significantly reduced physiological recovery indicators, whereas senescent cherry blossoms showed no significant changes. This suggests that different plant types may possess distinct mechanisms influencing physiological recovery during senescence.

Description of the psychological outcomes of each landscape

In terms of psychological recovery, nonparametric tests were employed to analyze the scale data. The results indicated that significant changes were observed across multiple scales, including (T-A), (A-H), (F), (C), (V), (D), and (TMD) (Fig. 5)

Fig. 5.

Significance test analysis of psychological indicators for different landscapes compared with the baseline.

In the Confusion, the senescent tulip landscapes significantly increased participants’ confusion levels. In contrast, senescent cherry blossom landscapes showed no significant change, indicating that different plant types may induce varying degrees of confusion during senescence. Conversely, all four blooming plant landscapes significantly reduced participants’ confusion levels, with both the Tension-Anxiety subscale and the Anger subscale exhibiting identical restorative effects.

Significant differences in recovery effects were also observed in the Depression subscale. Compared to senescent tulip landscapes, subjects exhibited lower depression levels after viewing the four blooming plant landscapes. Notably, the sunny senescent cherry blossom landscape (schf) also significantly reduced subjects’ depression levels, with an effect stronger than that of the rainy blooming plant landscapes.

On the Fatigue subscale, all blooming plant landscapes except the rain-blooming tulip landscape (rtlb) significantly reduced participants’ fatigue levels. Conversely, senescent tulips exhibited a significant negative effect on reducing fatigue. In contrast, senescent cherry blossom landscapes showed no significant impact on the fatigue dimension, indicating that different plant species may exhibit varying emotional regulation effects during their senescent stages.

Compared to the negative emotion scale, the subscale-Vigor exhibited an opposite trend. Results indicate that all four types of blooming plant landscapes significantly elevated participants’ vigor levels, with sunny-day blooming plants demonstrating the most pronounced vigor-enhancing effect. In contrast, sunny-day senescent tulips (stlf) significantly reduced participants’ vigor scores, while the other three senescent landscapes showed no significant impact on vigor levels.

On the TMD (Total Mood Disturbance) scale, participants’ levels of emotional disturbance significantly decreased after viewing all four types of blooming plant landscapes. This finding indicates that plants in full bloom can significantly improve individuals’ emotional states, thereby producing a clear psychological recovery effect. However, compared to the two rainy-day blooming plant landscapes, the two sunny-day blooming plant landscapes resulted in a greater reduction in total TMD scores, suggesting that sunny-day blooming plant landscapes offer superior psychological recovery effects. In contrast, senescent tulip landscapes significantly increased TMD scores, indicating that such landscapes induce stronger negative emotional responses, presenting an opposite effect to blooming landscapes. Notably, senescent cherry blossom landscapes did not result in significant changes in TMD.

In addition, to ensure the accuracy of the results, we used repeated-measures analysis of variance to evaluate the landscapes under each subscale. As shown in Table 5, significant differences were found in all POMS scores. A main effect of the TMD total score was significant (F = 40.576, p < 0.001, η² = 0.407). Further analysis revealed that all four plant landscapes during the flowering period significantly reduced participants’ POMS total scores, with the landscape during the sunny flowering period showing the most significant reduction. In contrast, the two types of tulip landscapes during the senescence period had significantly higher overall scores, indicating that they exhibited the poorest psychological recovery effects among all landscapes.

Table 5.

Results of repeated measures analysis of variance for each subscale.

Subscale	Landscape types	M ± SD	F	p	ηp 2
Confusion	stlb	5.33 ± 1.97	17.231	< 0.001***	0.226
	schb	5.63 ± 2.12
	rchb	5.85 ± 2.60
	rtlb	6.02 ± 2.84
	schf	6.47 ± 2.78
	rchf	6.82 ± 2.45
	rtlf	8.33 ± 4.13
	stlf	9.00 ± 4.17
Depression	stlb	4.88 ± 1.89	20.208	<0.001***	0.255
	schb	4.98 ± 1.83
	rchb	5.30 ± 2.00
	rtlb	5.63 ± 2.56
	schf	5.17 ± 2.65
	rchf	6.05 ± 3.43
	rtlf	8.38 ± 4.82
	stlf	8.80 ± 4.57
Anger	stlb	4.67 ± 1.48	15.081	<0.001***	0.204
	schb	4.72 ± 1.86
	rchb	4.82 ± 2.09
	rtlb	4.90 ± 2.40
	schf	4.80 ± 1.72
	rchf	5.58 ± 2.90
	rtlf	7.45 ± 4.41
	stlf	7.48 ± 4.31
Fatigue	stlb	5.73 ± 2.89	16.248	<0.001***	0.216
	schb	5.77 ± 2.18
	rchb	6.13 ± 2.97
	rtlb	6.42 ± 3.22
	schf	6.57 ± 2.96
	rchf	6.88 ± 3.33
	Rtlf	9.52 ± 5.01
	stlf	9.40 ± 4.89
Tension	stlb	4.80 ± 1.39	21.879	<0.001***	0.271
	schb	4.90 ± 2.00
	rchb	5.00 ± 1.78
	rtlb	5.13 ± 2.13
	schf	6.30 ± 3.26
	rchf	5.72 ± 1.90
	rtlf	8.30 ± 4.33
	stlf	8.43 ± 4.61
Vigor	stlb	14.90 ± 3.00	21.899	<0.001***	0.271
	schb	14.88 ± 3.69
	rchb	14.80 ± 3.55
	rtlb	13.70 ± 3.32
	schf	12.62 ± 4.08
	rchf	12.52 ± 3.59
	rtlf	12.42 ± 3.49
	stlf	9.63 ± 3.65
Total Mood Disturbance	stlb	10.52 ± 8.32	40.576	<0.001***	0.407
	schb	11.12 ± 8.43
	rchb	12.30 ± 9.99
	rtlb	14.40 ± 10.85
	schf	16.68 ± 10.20
	rchf	18.53 ± 11.27
	rtlf	29.57 ± 19.86
	stlf	33.48 ± 22.26

Personality and psychophysiological recovery

To analyze whether different personality traits lead to varying recovery outcomes, we employed two-way ANOVA for validation. Participants were categorized into four levels based on their Big Five Personality Questionnaire scores (Low: 3–6 points; Medium: 7–10 points; High: 11–14 points; Very High: 15–18 points). Using IBM SPSS Statistics 21, the analysis treated personality levels (low, medium, high, ultra-high) and different landscape types as independent variables, while psychological and physiological recovery indicators (Pa, Pm, psychological recovery) served as the dependent variable.

Analysis results indicate that personality traits exert differential effects on physiological and psychological recovery. Among these, subjects exhibiting neuroticism(Fig. 6) and extraversion (Fig. 7) demonstrated significantly varying recovery outcomes across different landscape types. Further analysis of subjects exhibiting neuroticism and extraversion personality traits revealed that: (1) Neuroticism: As neuroticism levels increase, both physiological indicators Pa and Pm exhibit an overall upward trend, peaking at the High level and slightly declining at the Ultra-high level. At the same level of neuroticism, recovery effects also showed significant differences across different landscape types: The Pa and Pm values were highest for plant landscapes blooming on sunny days, followed by those blooming on rainy days, while senescent tulip landscapes had the lowest values. Psychologically, as neuroticism levels increase, individuals’ POMS scores show an overall downward trend, reaching their lowest point at the High level before rebounding at the Ultra-high level. At the same level of neuroticism, psychological recovery patterns across different plant landscapes corresponded with trends in physiological indicators: landscapes dominated by plants blooming on sunny days yielded the lowest POMS scores, those blooming on rainy days scored slightly higher, while landscapes featuring tulips in senescence scored the highest (Fig. 6, Sample size N = 60)

Fig. 6.

Restorative effects of different landscapes at various levels of neuroticism.

(2) Extroversion: As extraversion levels increase, both physiological indicators Pa and Pm exhibit a sustained upward trend, peaking at the Ultra-high level. This indicates that individuals with ultra-high extraversion demonstrate more pronounced physiological recovery responses during exposure to natural landscapes. At the same level of extroversion, recovery effects vary significantly across different landscape types: The plant landscape in full bloom on sunny days exhibits the highest Pa and Pm values, followed by the plant landscape in full bloom on rainy days, while the senescent tulip landscape shows the lowest values. Psychologically, as extraversion levels increase, individuals’ POMS scores show a gradual downward trend, reaching their lowest point at the Ultra-high level. This indicates that individuals with higher extraversion exhibit more pronounced emotional recovery effects. At the same extraversion level, the POMS score for sunny-day blooming plant landscapes was the lowest, followed by rainy-day blooming landscapes, while the senescent tulip landscape scored the highest (Fig. 7, Sample size N = 60).

Fig. 7.

Restoration effects of different landscapes at various levels of extroversion.

Correlation analysis between psychophysiological recovery and personality traits, weather preference, and gender

To explore the associations between weather preferences, personality traits, and gender with individual psychophysiological recovery responses, this study adopted a multilevel correlation analysis strategy. First, Spearman correlation analysis was conducted to evaluate the fundamental correlation structure among physiological and psychological recovery indicators under different landscape conditions. Subsequently, Mantel correlation analysis was employed to examine the overall association pattern between individual differences and restorative responses, with ChiPlot visualization (https://www.chiplot.online/). The results indicate that (Fig. 8):

1. Correlation between psychophysiological recovery Indices (Heatmap Areas): A highly significant positive correlation was observed among the four types of flowering plant landscapes, indicating that regardless of weather conditions—whether sunny or rainy—physiological recovery indicators (Pa, Pm) exhibit relatively consistent patterns of change during plant flowering. Under senescent conditions, the recovery indices of sun-exposed senescent tulip landscapes (stlf) and rain-exposed senescent tulip landscapes (rtlf) showed a significant positive correlation. Similarly, the recovery indices of the senescent cherry blossom landscape on sunny days (schf) and the senescent cherry blossom landscape on rainy days (rchf) also showed a significant positive correlation. This indicates that weather conditions did not significantly alter the psychophysiological recovery effects of tulips or cherry blossoms in their senescent state. Moreover, no significant correlation was observed between tulip and cherry blossom senescence, indicating that different plant species exhibit distinct physiological and psychological regulatory effects during the senescence process. It is noteworthy that the correlation between senescent plant landscapes and flowering plant landscapes is relatively low, suggesting that the phenological states of plants during flowering and senescence elicit two distinct patterns of physiological recovery responses.

2. Mantel correlation analysis of personality traits, weather preferences, and gender with physiological recovery: ① For personality traits, significant correlations exist between these traits and psychophysiological recovery differences across multiple landscape types. Among these, the four types of blooming plants exhibited higher correlations compared to the two senescent tulip landscapes, indicating that personality traits demonstrate greater sensitivity to psychophysiological responses toward blooming landscapes. Notably, no significant correlations were observed between recovery effects from the two types of senescent cherry blossom landscapes and personality traits. ② For weather preferences, weather preferences showed significant correlation with four types of flowering plant landscapes, exhibiting stronger correlation intensity than with senescent cherry blossom landscapes. In contrast, no significant correlation was observed between the restorative effects of senescent tulip landscapes and weather preferences, indicating that weather preferences primarily influence the restorative effects triggered by flowering plants, while exerting a weaker influence on the restorative role of senescent tulip plants.③For gender, significant correlations were observed between gender and recovery metrics for four types of flowering plant landscapes, whereas no significant correlations were detected for senescent plant landscapes. This indicates that gender differences primarily manifest in recovery effects for flowering landscapes, while recovery in senescent landscapes exhibits gender consistency.

3. Comparative analysis of correlation strength between personality traits, weather preferences, gender, and recovery outcomes: A comprehensive comparison of the correlation strengths among the three factors reveals that personality traits are the most critical factor influencing various landscape effects, exhibiting a higher correlation strength than weather preferences and gender. Meanwhile, weather preferences explain restorative effects to a greater extent than gender, indicating that among individual variation factors, personality traits exert the most prominent influence on shaping psychophysiological response patterns, followed by weather preferences, while the impact of gender is relatively weaker.

Fig. 8.

Heatmap of correlations between psychophysiological recovery and personality, weather preference, gender.

Discussion

Flowering plant landscapes significantly promote physiological recovery under various weather conditions, whereas the restorative effects of fallen plant landscapes are limited by plant species

Blooming plant landscapes significantly enhance physiological recovery levels compared to senescent landscapes, reflecting stronger restorative effects. Previous research suggests that ornamental flowering plants effectively promote physiological recovery through multiple sensory cues, including visual structure and color saturation^24,60,61. This further demonstrates the restorative role of flowering plant landscapes across multiple research scales.

Meanwhile, plants that bloom during sunny weather exhibit stronger physiological recovery than those that bloom during rainy weather, indicating that weather preferences play a significant regulatory role during the flowering stage. Numerous studies indicate that light exposure serves as a key regulator of physiological recovery. On sunny days, enhanced visual stimulation leads to decreased blood pressure and increased brainwave activity. While this effect persists on rainy days, its magnitude is significantly reduced. This demonstrates that weather exerts a universal and pronounced regulatory influence on different landscapes^20,36. And individual weather preferences may also amplify positive emotions by intensifying subjective experiences, creating a positive feedback loop between subjective perceptions and physiological indicators that further enhances recovery effects⁶².

Remarkably, senescent tulip landscapes and senescent cherry blossom landscapes exhibited entirely different recovery effects, suggesting that plant species may influence the mechanisms by which senescent landscapes affect physiological recovery. This may be because different plant types induce varying physiological responses through their chemical composition and sensory characteristics⁶³. Based on the EEG data from this study, the physiological indicators of senescent cherry blossom landscapes were higher than those of senescent tulips. This may be because senescent cherry blossoms retain a certain proportion of green foliage, which buffers the decline in physiological indicators¹⁹. Following senescence, herbaceous plants (such as tulips) retain only their flower stalks, lacking green foliage and color stimulation, which makes them more susceptible to reduced physiological recovery¹⁴. Our findings provide practical support for urban landscape design under varying weather conditions across northern and southern China.

Flowering plants significantly enhance psychological recovery, while senescent plants exhibit type-dependent negative or neutral psychological effects

We found that blooming plant landscapes significantly reduce the negative emotion index (TMD), consistent with previous mainstream research^64,65. This may be attributed to the advantages possessed by blooming plants in terms of color saturation, visual orderliness, and symbolic biophilic appeal, which help trigger stronger positive emotional arousal, thereby manifesting a significant restorative effect on subjective psychological states⁶³.Meanwhile, plants provide greater restorative effects on sunny days than rainy days when viewed under optimal blooming conditions. This aligns with the environmental psychology perspective that “light enhances emotional recovery,” suggesting that the high-intensity visual cues associated with sunny weather can amplify positive emotional evaluations and reduce emotional burden. Consequently, individuals experience superior psychological restorative benefits when viewing plant landscapes under sunny conditions^46,66,67.

We find that senescent plant landscapes elicit varying psychological recovery effects depending on plant type. While few studies have directly compared the psychological recovery effects of different plant types in senescent states, existing research has contrasted the effects of grasslands and mixed plant landscapes, indirectly suggesting differences in psychological recovery influenced by plant type^68,69.

Overall, the findings on psychological recovery further validate the multidimensional influence mechanism of the three-way interaction between weather conditions, plant phenology, and plant type on psychological recovery. This provides empirical evidence for creating urban green therapeutic landscapes and enhancing the role of natural landscapes in promoting mental health.

Neuroticism and extraversion significantly moderate the restorative effects of plant landscapes, with extreme levels of neuroticism diminishing restorative capacity

We found significant main effects of neuroticism and extraversion on psychophysiological recovery indicators. Higher extraversion levels correlated with greater recovery effects in blooming plant landscapes. This may stem from extraverts’ typically higher positive affect arousal capacity and stronger positive emotional responses, making them more likely to activate the parasympathetic nervous system when exposed to natural landscapes. This facilitates physiological relaxation and emotional uplift³².

The nonlinear influence pattern of neuroticism we studied shares similarities with previous findings indicating a reverse U-shaped nonlinear relationship between neuroticism and recovery: At moderate levels of neuroticism, heightened vigilance toward natural stimuli moderately increases emotional arousal, manifesting as improved recovery levels. However, when neuroticism reaches extremely high levels, persistent negative emotional tendencies may inhibit parasympathetic regulation. Consequently, individuals struggle to achieve significant improvement even when exposed to highly restorative natural stimuli, resulting in increased negative emotions and declining recovery indices⁷⁰.

Emotion Regulation Theory posits that personality influences which emotion regulation strategies individuals employ, thereby affecting the recovery process⁷¹,⁸². Extroverts tend to employ positive reappraisal and emotional expression strategies, making them more likely to transform natural landscapes into positive experiences^72,73. In contrast, the nonlinear model of neuroticism extends existing theories to some extent, suggesting that natural stimuli may elicit emotional arousal at moderate levels of neuroticism, thereby promoting stronger physiological and psychological recovery. This also demonstrates that the personality-nature interaction is not unidirectionally inhibitory but involves a dynamic “facilitation-optimal-inhibition” process. Our research not only validates the applicability of emotion regulation theory in the context of nature-based recovery but also provides empirical support for understanding the differentiated recovery mechanisms of natural stimuli across different personality types.

Personality traits are a key factor influencing recovery differences

Regarding the Mantel test results, the correlation strength (Mantel’s r) for personality traits was significantly higher than that for weather preferences and gender. It should be noted that personality traits show a significant correlation with senescent tulip landscapes (rtlf, stlf), but no significant correlation with senescent cherry blossom landscapes (rchf, schf). This difference may indicate that when the plant landscape itself carries strong negative visual cues (such as the bare structure of tulips after wilting), individual personality differences are amplified. In contrast, senescent cherry blossoms retain some green foliage elements, which may mitigate psychological response variations among individuals. This further demonstrates that internal regulatory mechanisms within individuals can either amplify or attenuate the restorative effects of external natural stimuli^74,75.

Additionally, while weather preferences also exhibit robust correlations with the four categories of blooming plants, their strength is weaker than that of personality variables. Notably, weather preferences show a significant correlation with the senescent cherry blossom landscape, whereas no correlation is observed with the senescent tulip landscape. This may be because weather preference more significantly influences individuals’ emotional evaluations of “visually soft” landscapes (cherry blossoms retaining green leaves after petal fall) while having limited moderating effects on “visually fragmented” landscapes (tulip stems exposed after wilting). This aligns with previous research findings: light intensity and soft visual features jointly enhance soft attention, thereby boosting recovery, while high-contrast, fragmented structures diminish restorative effects under cloudy or low-light conditions^76,77.

Gender had the weakest influence on recovery and exhibited a stable correlation only in landscapes with flowering plants. This suggests that gender differences may be more pronounced in the enhancement effect of positive stimuli, consistent with some studies indicating that women experience slightly greater emotional improvement in positive natural settings, though no consistent trend emerged in negative stimuli^21,68.

Although existing research has rarely compared the relative strengths of personality traits, weather preferences, and gender in influencing the intensity of psychophysiological recovery, some studies examining landscape restorative have reported the significance and explanatory power of certain factors on restorative effects. This indirectly suggests that personality traits hold greater explanatory power for restorative outcomes. Regarding gender differences, most existing theories fail to distinguish the impact of gender exposure to natural environments^36,38. Furthermore, previous studies rarely report on the effects of gender differences on recovery, and even fewer investigate the strength of their correlation^78,79. Our research indicates that psychophysiological recovery is not driven by a single factor but rather aligns with an interactive model. Specifically, personality traits play a pivotal role as part of the internal mechanism in responding to plant landscape stimuli. This aligns with both the Nature-Based Recovery Theory (SRT) and Emotion Regulation Theory: the effectiveness of nature-based recovery depends on the interaction between external stimuli and individual internal mechanisms^36,80,81.

Limitation

Our study has several limitations: First, the sample consisted solely of college students aged 18–28, and a video scenario was used in place of a real natural environment; therefore, the applicability of the results to other age groups and clinical populations remains to be verified, which may also limit the ecological validity of the study to some extent. Second, the study focused solely on tulip and cherry blossom landscapes, which may not fully reflect the restorative characteristics of diverse ornamental plants. Future research could expand the range of plant types to enhance the generalizability of the findings. Third, EEG analysis was primarily based on overall frequency bands, lacking precise localization to specific brain regions; future studies could incorporate higher-resolution analytical methods to deepen the explanation of underlying mechanisms. Although this study explored the association between personality traits and the restorative effects of plant landscapes, the specific mechanisms underlying this association remain unclear. Future research could employ mediation analysis to further investigate the roles of variables such as emotional regulation strategies and aesthetic ability in this process, thereby revealing more detailed restorative mechanisms.Finally, to enhance the realism of multisensory input, future research could incorporate more samples from real-world environments.

Conclusions

We established a three-dimensional experimental framework integrating weather, plant condition, and plant type. By combining physiological measurements (EEG devices) with psychological assessments (POMS scales), we systematically examined the physiological and psychological restorative effects of tulips and cherry blossoms across eight environmental conditions. Furthermore, we conducted an in-depth analysis of the moderating roles played by personality traits, weather preferences, and gender in these restorative effects. Results clearly indicate that the restorative effects of plant landscapes are significantly influenced by multiple interacting factors. Flowering plant landscapes demonstrate optimal restorative effects, while the restorative effects of senescent plant landscapes vary depending on plant type. Concurrently, personality traits, weather preferences, and gender show certain correlations with restorative differences, with personality traits exhibiting the strongest correlation in moderation effects. In summary, this study not only empirically demonstrates the restorative advantage of flowering plants under varying weather conditions but also reveals the pivotal role of personality traits in landscape restorative experiences. These findings provide valuable theoretical support for scientifically optimizing urban green landscape design and precisely implementing mental health interventions.

Author contributions

Y.Z.: Writing-original draft, conceptualization, data curation, formal analysis, methodology, resources, visualization, validation. J.W.: Data curation, visualization, writing-review and editing. Y.Z.: Conceptualization, funding acquisition, project administration, supervision, writing-review and editing. M.L.: Conceptualization, supervision, validation, writing-review and editing. J.W.: Supervision, validation, writing-review and editing.

Funding

This research was supported by the Scientific Research Project of the Hunan Provincial Education Department, China. (Grant No. 25A0238).

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.