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Sun, Q., Y. Zeng, Y. Zhang, T. Yue, and Y. Zhang. 2025. Assessing the distance effects on motivations of emergency volunteers responding to wildfire events in protected areas. Ecology and Society 30(4):42.ABSTRACT
Emergency volunteers play a critical role in responding to extreme climatic events. Overlooking their motivations may undermine the effectiveness of emergency response efforts. However, there remains a significant research gap in understanding emergency volunteers’ motivations and the influence of distance factors. To address this gap, this study employed the revised Volunteer Functions Inventory (VFI) to analyze the motivations of 345 emergency volunteers who participated in the wildfire rescue at the Jinyun Mountain Nature Reserve in China. The findings revealed that emergency volunteers’ motivations were primarily driven by Values, followed by Social, Understanding, Enhancement, and Protective motivations, with Career motivations being the least influential. Notably, emergency volunteers residing farther from the wildfire-affected areas prioritized ecological conservation over social connections or career interests. Additionally, our study found that age, income, educational level, and experience have a significant impact on emergency volunteers’ motivations. This study represents the first attempt to quantitatively assess emergency volunteers’ motivations in wildfire rescue, revealing spatial disparities in motivations and integrating the social resilience perspective into extreme event management.
INTRODUCTION
Amid global warming, the frequency, duration, and intensity of extreme climate events have significantly increased (Jing et al. 2024). According to the United Nations Office for Disaster Risk Reduction (UNDRR), over 200 wildfires were triggered by climate change between 2000 and 2022 (UNDRR 2000-2022). As sudden and destructive natural disasters, wildfires inflict severe damage on communities and ecosystems (Qiyang et al. 2021, Salcedo-Sanz et al. 2024) and present substantial challenges for emergency management systems (Vaidyanathan et al. 2018, Sun et al. 2023). The wildfire risk management cycle typically consists of four phases: prevention, preparedness, response, and recovery (Molina et al. 2019, Schinko et al. 2023). Studies highlight that social rescue forces, especially emergency volunteers characterized by rapid response (Sarkisian et al. 2020, Sperling and Schryen 2022) play a critical role in complementing professional rescue efforts during response and recovery phases (Schinko et al. 2023, Zhao et al. 2023). Volunteer motivation positively predicts service effectiveness (Zheng et al. 2020); thus, understanding emergency volunteers’ motivations is essential for wildfire risk management.
Research on volunteer motivation began in the 1970s (Esmond 2004, as cited in Erasmus and Morey 2016). Clary et al. (1998) developed the Volunteer Function Inventory (VFI), a widely used framework that examines volunteer motivations across six factors and 30 sub-items (Kim et al. 2010, Esmond 2004, as cited in Erasmus and Morey 2016). Chacón et al. (2017) systematically reviewed 26 studies applying the VFI and found that more than half supported its six-factor model (Wu et al. 2009, Chacón et al. 2017, Niebuur et al. 2019). Overall, the VFI’s structure and application is now well-established. However, its use in research on emergency volunteers still presents notable limitations (Martins et al. 2024).
First, most existing studies focus on long-term volunteers, who typically have time and capacity to plan their participation in advance, often engaging in well-organized, deliberate activities (Max et al. 2024). In contrast, emergency volunteers tend to act impulsively and spontaneously in response to crises, without prior planning (Stallings and Quarantelli 1985, Tierney 2014). To date, only a few studies have employed the VFI to qualitatively analyze emergency volunteers’ motivations. For example, Byrne et al. (2023) found that factors such as “logistics” and “safety” significantly influenced individuals’ decision to engage in volunteer activities during the COVID-19 pandemic. Jaime et al. (2023) demonstrated a correlation between volunteers’ capabilities and their higher self-reported satisfaction as well as perceived performance in socio-natural disaster response. Despite these studies, further research is needed to explore the distinct motivational characteristics of emergency volunteers and to conduct quantitative analyses of their responses to extreme weather events such as wildfires.
Second, existing research on volunteer motivation often overlooks spatial dimensions. Early motivational theories, such as the economic man model (Frey 2001), which assumes that decisions are based on anticipated rewards, highlight both self-serving and altruistic reasons for volunteering, including personal or familial benefits, skill enhancement, organizational rewards, and altruism (Frey 2001, Bernard et al. 2005). However, such early studies, which primarily focused on long-term volunteers, relied heavily on theoretical qualitative analyses. This approach inherently constrained systematic inquiry into spatial variables such as how distance factors may shape volunteers’ motivations. Wildfires possess unique spatiotemporal features, characterized by sudden onset, rapid spread, and broad spatial coverage (Masson et al. 2021, Qiyang et al. 2021). The impacts of wildfire vary spatially, with intensity typically decreasing as distance from the fire source increases (Schmidt et al. 2024). Thus, volunteers living closer to or farther from wildfires may experience different levels of perceived risk, potentially leading to different motivation drivers. This provides a compelling rationale for investigating EV motivation from a spatial perspective (McLennan and Birch 2005).
Moreover, existing wildfire research has primarily focused on ecological dynamics and spatiotemporal patterns (Li and Banerjee 2021), ecological impacts (Pereira et al. 2016, Tang et al. 2022), and social dimensions such as risk prediction (Ban et al. 2020), social equity (Schinko et al. 2023), and vulnerability (Paveglio et al. 2018). Social-ecological approaches emphasizing ecological protection, wildfire prevention, and community cohesion have highlighted the essential role of volunteer engagement in bridging wildfire ecology and emergency management (Prior and Eriksen 2013, Grant and Langer 2021). However, the role of spatial distance in shaping EV motivation remains underexplored. The absence of spatial perspective constrains a comprehensive understanding of EV behavior and limits the capacity of emergency management agencies to make evidence-based decisions.
This study aims to use the VFI scale proposed by Clary et al. (1998) to explore the following: (1) What are the key motivations for emergency voluntary service such as wildfires? (2) What is the relationship between accessibility of wildfires and the motivation of emergency service? (3) What are the motivations of wildfire emergency volunteers affected by demographic factors? We hope that these analyses will promote the understanding of the motivation of volunteerism for extreme climate events and provide a scientific basis for the establishment of a social support system to deal with climate change.
MATERIALS AND METHODS
“821 wildfire” event in Jinyun Mountain
On 21 August 2022, a serious wildfire, referred to as “821 Wildfire,” occurred around Jinyun Mountain Nature Reserve in China. The wildfire occurred at the Hutou Mountain, a branch of Jinyun Mountain, climbed northeast over Puba Mountain and approached the core area of Jinyun Mountain National Reserve, and went south to the junction of Beibei District and Bishan District. The burning range of mountain fires in Jinyun Mountain was 14.31 km² (Fig. 1). The wildfire lasted for six days, until 26 August.
During the 821 Wildfire, the local community demonstrated a robust response by organizing 286 volunteer service teams (Fig. 2). According to statistics, there were 24,019 volunteer participations in the rescue efforts (Zhou and Li 2023), including citizens, local villagers, veterans, medical personnel, and so on (Cai et al. 2022). In the footage taken by reporters at the scene, thousands of volunteers lined up to transport supplies to the mountain, holding high-pressure water pipes to ensure a smooth water supply, and using motorcycles to transport supplies and escort rescue volunteers (Xia 2022, unpublished manuscript).
Theoretical framework
The Volunteer Function Inventory (VFI) is a tool for measuring volunteer motivations invented by psychologist E. Gil Clary and others (Clary et al. 1998). The application of VFI covers sociology, psychology, organizational behavior, and other fields. It is used internationally to study the impact of volunteer participation on individuals and communities, and to evaluate the motivation and influencing factors of volunteer participation (Chacón et al. 2017). For example, Allison et al. (2002) utilized VFI to assess the motivations of 129 volunteers who focused on providing services to community-based sporadic volunteer organizations; Kim et al. (2010) adapted the foundational framework of VFI, modifying its components to tailor it for evaluating the motivation of volunteers in youth sports activities. Zhou and Muscente (2023) used VFI to analyze volunteers’ motivations and predict the impact of motivations on volunteers’ satisfaction, commitment, and behavior. Therefore, through literature review, VFI has experienced the preliminary design of Clary and modification and expansion of future research and application, mainly including the following six aspects of application: (1) measuring the frequency and duration of volunteer participation; (2) assessing the breadth and diversity of volunteer participation; (3) examining the types of organizations volunteers participate in; (4) understanding the role of volunteer participation; (5) exploring the motivation of volunteer participation; (6) evaluating the impact of volunteer participation.
The previous VFI scale mainly studied the motivation of long-term volunteers. Taking the 821 Wildfire as an empirical case, we refined and revised the specific items of the VFI scale for emergency volunteers: (1) Some survey items on Social and Protective motivations were deleted, and the items on Understanding and Values were added and refined. Because emergency volunteers’ actions are often spontaneous, overloading the survey with too many questions about Social and Protective motivations could confuse or overwhelm volunteers, leading to inaccurate or irrelevant responses. By focusing on key factors like Values and Understanding motivations in wildfire rescue efforts, we streamlined the survey and improved its effectiveness to ensure more accurate and reliable data collection. (2) Because most of the volunteers were local villagers with strong regional attributes, the regional attributes were further refined at the cognitive level. (3) The repetitive or jumbled contents of the original VFI scale were deleted and revised. (4) After a structured interview with local residents, the survey was further refined. (5) A preliminary survey was conducted on a subset of volunteers using the revised scale. After calculating the reliability coefficients, the final version of the questionnaire was finalized (Table 1).
The six motivations included in our study for assessment were the following:
- Values: refers to the expression of values related to altruistic, humanitarian, and environmentalism concerns.
- Understanding: motivations oriented to acquiring and/or improving knowledge, skills, experiences, etc.
- Social: motivations related to what are called social relations.
- Career: motivation to enhance knowledge in a specific area related to professional and academic development.
- Protective: motivations oriented to protecting the ego or solving psychological problems.
- Enhancement: motivations centered on self-knowledge, self-development, and, in general, feeling better about oneself.
Data collection
Data collection for this study utilized a combination of semi-structured interviews and questionnaires, which were integrated with the VFI scale. Participants rated six types of functional motivation in response to the question: “How important or applicable was this motivation for your participation in this volunteer activity?” The VFI was adapted as a 25-item questionnaire (Table 1), scored using a 7-point Likert-type scale, where “1” is “totally disagree” and “7” is “totally agree” (Chacón et al. 2017). Demographic data were also collected, including volunteers’ gender, age, identity, income, educational level, participation mode, content, and duration of volunteer service (Appendix 1). We collected volunteers’ spatial coordinates through SoJump online surveys and GPS-assisted field interviews. For the online surveys, we utilized SoJump’s auto-geolocation feature to derive coordinates based on volunteers’ IP addresses or other location data provided by the platform. In field interviews, we recorded volunteers’ home or starting addresses before using GPS devices to capture their precise spatial coordinates. The SoJump system records the IP addresses of volunteers during interviews, primarily reflecting their workplace locations. However, because most volunteers’ workplaces were in close proximity to their residences, potential location-related errors in the survey data were minimized.
The research process began with semi-structured interviews to establish a comprehensive understanding of the overall context and participation motivations behind volunteer activities. These interviews provided essential background information and guided the refinement of the questionnaire design, particularly in relation to questions about motivation and distance. The final questionnaire was further enhanced by incorporating key factors such as community organization and information dissemination.
A preliminary survey was conducted on 12 January 2023, at Jinyun Village within Jinyun Mountain Nature Reserve. Interviews were held with staff from the Jinyun Mountain Fire Protection Office, the village director of Jinyun Village, and community volunteer leaders to explore topics such as fire and rescue processes, multi-stakeholder responses, and psychological motivations. Additionally, two other volunteer leaders were interviewed online for one hour on 13 January 2023. Insights from these interviews informed further optimizations to the preliminary questionnaire design.
The formal survey was conducted on 13 June 2023, employing both online and offline methods. Researchers visited Jinyun Village, Beiquan Village, Houtou Village, and Satellite Village on 6, 11, and 12 of that month to conduct four semi-structured interviews with village cadres and volunteer representatives. Concurrently, household surveys were administered to villagers who had participated in voluntary fire rescue efforts, yielding 120 questionnaires. With the support of the Beibei District Forestry Bureau and the Chongqing Civil Affairs Bureau, questionnaires were disseminated through WeChat groups of volunteers in Jinyun Mountain, resulting in 225 online responses.
In total, 345 questionnaires were collected. After excluding 14 questionnaires lacking spatial data and 1 with outliers in spatial data, 330 valid questionnaires remained, achieving a recovery rate of 95.7%.
Among the 330 valid questionnaires, the proportions of men and women were 70% and 29%, respectively. Young and middle-aged (18 to 65 years old) accounted for the largest proportion, approximately 90%. About 46% of the respondents completed only secondary education, and about 57% of the people had higher education (bachelor’s degree and above). More than 50% of the respondents had a monthly income of less than 5000 RMB. The respondents came from various industries, accounting for a relatively balanced proportion. About 55% of the respondents participated in offline fire rescue. A small number of interviewees participated in the form of individuals, and about 80% of them participated in collective form. Those who were directly involved in fire rescue or material delivery accounted for about 45%. Those who participated for 1 to 3 days accounted for about 63%, for 4 days or more, about 37% (Table S1).
Data analysis
The validity and reliability of the questionnaire data were analyzed. The overall reliability of the questionnaire Cronbach α is 0.764 (> 0.7), indicating that the reliability quality of the research data is good. Subsequently, the Bartlett spherical test of the questionnaire, the KMO value is 0.937 (> 0.9), indicating a high level of validity for the questionnaire (Table S2). On this basis, the principal component analysis of the questionnaire was carried out. The explanation rate of the six common factors is 81.990%, which can reflect the six types of motivations of volunteers (Values, Understanding, Social, Career, Protective, and Enhancement; Table S3).
The spatial geographic coordinates of the 330 questionnaires were imported into ArcGIS 10.2 (ESRI Inc., Redlands, CA, USA) to obtain the spatial distribution of the questionnaire’s points (Fig. 3). The Point Distance tool (ArcGIS 10.2) was used to calculate the shortest distance from the location of the volunteer’s home address to the fire impact boundary, and the calculated distances were grouped into 10 categories by the Natural Breaks. In semi-structured interviews to understand volunteers’ perceptions of safe distances from wildfires, the 10 categories of minimum distances were reclassified according to the risk levels (high danger, moderate danger, low danger, no danger) they proposed. The volunteers’ home locations in relation to the fire’s impact boundary were categorized into four distinct classes, corresponding to distances of 1 km, 5 km, 10 km, and greater than 10 km from the wildfire, respectively. ANOVA (Analysis of Variance) was then used to compare the differences in the six motivation dimensions across the four distance categories. Finally, the kernel density analysis tool (ArcGIS 10.2) was used to display the spatial differences of volunteers’ motivations.
After the spatial analysis, we grouped volunteers with four demographic traits (age, income, educational level, and volunteering experience). We used ANOVA to compare motivation differences within each group and investigated the interaction effects between volunteers’ motivations and these demographic characteristics (Table S4).
RESULTS
Key motivations of emergency volunteers in wildfire rescue
Based on the importance ratings provided by 330 volunteers for each of the six motivations, the mean score for each motivation was calculated to determine the rank order of importance of thee six motivations in this survey. Values were identified as the primary motivation (M = 6.18), followed by Social (M = 6.01), Understanding (M = 5.43), Enhancement (M = 5.23), Protective (M = 4.14), and Career (M = 4.05). Within the realm of value motivation, the majority of emergency volunteers expressed agreement with the value of regional belonging (V2 = 6.633) and natural ecological value (V3 = 6.576). When it comes to volunteers’ Career, a considerable number of emergency volunteers agreed that the participation in wildfire rescue will look good on their resumes (C1 = 4.170) but denied its effects in developing business or career (C2 = 3.894; Fig. 4).
Spatial variation in emergency volunteers’ motivation
ANOVA results showed that motivations, except for Social, significantly increased with distance from the wildfire. The most notable spatial variation was in Values (F = 28.354, p < 0.001), while Enhancement varied the least (F = 5.656, p = 0.001). Social motivation showed no significant spatial differences (F = 1.239, p > 0.05; Table S6). Kernel density analysis further highlighted that all motivation categories shared similar spatial patterns. Emergency volunteers with strong motivations were mainly concentrated to the northeast of Jinyun Mountain National Nature Reserve, with a secondary concentration in the south of the reserve (Fig. 5, Table S6).
Demographic differences in emergency volunteers’ motivations
The motivation of emergency volunteers varied across demographic lines (Table S5). Middle-aged and older individuals (age ≥ 40) were more socially driven, while younger individuals (age < 40) were motivated by personal values and cognition. Volunteers with lower income (income ≤ 5000 RMB) were more likely to be motivated by social and career intentions, while volunteers with higher income (income > 5000 RMB) tended to be motivated by enhancement initiatives. Education level also influenced preferences: those with higher education (bachelor’s and above) favored Values, while those with less education were driven more by Career, Understanding, and Enhancement. Experienced volunteers responded positively to all six motivations, particularly Values and Understanding (Fig. 6).
DISCUSSION
Key motivations of wildfire volunteers
Our research reveals Values as the primary motivation driving emergency volunteers in Jinyun Mountain, with Career emerging as the least influential. The two key factors explain the prominence of value-based motivation. First, wildfires pose a serious threat to the lives and property of residents, prompting them to seek safety and protection for themselves and their families. Second, wildfires destroy the local natural ecological environment and the material basis of residents’ life, so they have the Value motivation to maintain the ecological integrity of the region. In similar studies, non-emergency volunteers engaged in natural services also believe that Values are the main motivation for them to participate in volunteer work. Different types of voluntary service have different value pursuits (Campbell and Smith 2006). For example, animal protection volunteers pursue experience and aesthetic values (Campbell and Smith 2006), while volunteers engaged in natural science research are driven by personal interests and the value pursuit of educational research organizations (Domroese and Johnson 2017). Especially for environmental protection volunteers, Values are the main driving force for them to participate in conservation activities, reflecting their strong concern for nature and their desire to assist in environmental protection (Bruyere and Rappe 2007, Cho et al. 2018).
Conversely, Career motivation exerts limited influence in emergency volunteerism. This contrasts with long-term volunteer programs, where motivations such as skill development, self-improvement, and career advancement play a more significant role (Rotman et al. 2014, Cho et al. 2018, Rozmiarek et al. 2023). Emergency volunteers lack the cultural, social training and interaction that need to be accumulated over a long period of time (Liu and Leung 2019), so Career is not their primary consideration.
Impact of distance on volunteer motivation
Spatial analysis revealed that distance from wildfire zones (within a range of 10 km) significantly influences motivation profiles. As distance from the fire increases, motivations related to Values, Understanding, Protective, Enhancement, and Career all increase, with Values exhibiting the most pronounced shift (the score refers to the ANOVA-F; Table S5).
This pattern suggests that proximity volunteers, driven by urgent conservation needs and the pressing pressure to safeguard lives and property, exhibit more efficient rapid response and initial containment capabilities. Volunteers farther from the immediate threat are less motivated by urgent personal safety and more driven by deeper convictions, such as environmental stewardship and self-development (Foster-Smith and Evans 2003, Heimann and Medvecky 2022). These distant volunteers often perceive their contributions as a meaningful way to protect shared ecosystems and demonstrate ecological responsibility, even in the absence of direct threat. They excel at engaging in long-term recovery and prevention efforts, and their macro perspective enhances the efficiency of post-disaster collaboration in areas such as ecological restoration and community education. Notably, the relationship between distance and motivation is not linear. Although distant emergency volunteers are less affected by immediate danger, their motivations are often more complex and diversified. Many actively engage in wildfire rescue out of a sense of responsibility for biodiversity and a desire for personal growth. Participation enables them to acquire new knowledge (Brightsmith et al. 2008), enhance personal competencies, and fulfill a sense of purpose, factors that are often overlooked in proximity-based models of volunteerism. Considering the aforementioned factors, it is evident that the spatial distribution of motivations significantly impacts the efficiency and collaborative effectiveness of rescue operations. These differentiated motivational characteristics necessitate the implementation of tailored recruitment management strategies.
In contrast, social motivation remains stable across distances. This may be due to the communal nature of volunteer engagement in Jinyun Mountain, where many emergency volunteers are mobilized through familial or friendship ties, forming close-knit rescue teams with a shared sense of purpose (Tang and Wang 2020). This common goal transcends the blockage of space and distance, making emergency volunteers from different regions show similar social motivation.
Moreover, high motivation scores were mainly concentrated to the northeast of Jinyun Mountain National Nature Reserve, with a secondary concentration in the south. Residents in these regions rely heavily on natural resources and display a deep emotional attachment to their environment. Their participation is further supported by established social networks and well-organized community-based response systems. These factors collectively enhance their motivation to protect their homeland and respond proactively to environmental threats.
Demographic characteristics affect volunteer motivation
Our findings also indicate that age, income, education level, and volunteer experience significantly affect motivation profiles. Young people (age < 40) tend to exhibit a wider range of motivations, especially those aligned with values and cognition. In contrast, older individuals (age ≥ 40) are more inclined toward social motives, perhaps because of stronger community ties and established social networks. This diverges slightly from past research suggesting that Values typically increases with age (Dávila and Díaz-Morales 2009, Widjaja 2010, Omoto et al. 2018). In our context, young volunteers may be expressing their values through environmental engagement, reflecting their stronger exposure to global environmental issues (Martin and Greig 2019).
Income levels also shape motivation. Low-income people are more inclined to Social and Career. In previous studies, income is the most significant factor affecting motivation change, especially corporate volunteers and non-profit volunteers (Do Paço et al. 2013). Income mainly affects their Values. However, in our study, income mainly affects their Enhancement. This motivational preference may stem from low-income people’s emphasis on social relations and future career prospects (Brown 2005, Brightsmith et al. 2008, Campbell and Smith 2006, Larson et al. 2020).
Education plays a similarly influential role. Those with higher educational level (bachelor’s degree or above) are more likely to express intrinsic motivations such as Values, Protection, and Enhancement. Previous studies have demonstrated that volunteerism, analogous to higher education, enables volunteers to acquire knowledge and other life skills, while also enhancing their civic awareness and sense of responsibility (Hesser, 1995, Eyler et al. 1997, Astin and Sax 1998). Therefore, individuals with prolonged higher education tend to exhibit stronger social responsibility and enthusiasm for creating social value (Wong and Foo 2011, Dayer et al. 2017, Martins et al. 2024). Our study findings further corroborate this phenomenon.
Finally, compared with inexperienced volunteers, experienced volunteers usually have more comprehensive motivation (Values, Social, Understanding, Protective, Enhancement, Career), especially Values and Understanding. This is consistent with previous studies. Because experienced volunteers have a clear purpose when participating in voluntary work and make their choices after careful consideration of the work content, they are more aware of what they hope to gain from volunteering (Foster-Smith and Evans 2003, Asah et al. 2014, Rozmiarek et al. 2021).
Implications for wildfire management
These findings hold significant implications for the practical management of wildfire emergencies. First, recruitment strategies should develop differentiated strategies based on the core motivational appeals of volunteers residing in different proximity zones. For communities near the wildfire front, outreach should emphasize the urgency of protecting lives and property, alongside a sense of community stewardship, leveraging value-based and protective motivations (Górriz-Mifsud et al. 2019). Emotional appeals and assurances about safety can further enhance participation. In contrast, recruitment in distant areas can focus on cognitive and developmental incentives, such as training opportunities, personal growth, and contributions to ecological well-being (Hao et al. 2018, Souza-Alonso et al. 2024).
Training and management strategies should also take distances into account. Nearby emergency volunteers require practical skills in fire suppression, safety protocols, and first aid to operate effectively in hazardous environments (Orloff 2011). Meanwhile, distant volunteers may benefit more from training in ecological education, wildfire science, and psychological readiness to reinforce their role in long-term conservation efforts.
Additionally, emotional and institutional support is essential. Volunteers close to fire zones often face intense physical and psychological stress. Providing timely psychological assistance, logistical support, and public recognition can help sustain motivation and resilience (Boezeman and Ellemers 2007, Thormar et al. 2013). For distant volunteers, digital platforms can enhance engagement through updates on rescue efforts and public recognition of achievements, maintaining morale and reinforcing long-term involvement (Frey and Gallus 2017). Understanding these motivational differences can enhance rescue operations, improving both immediate response and long-term recovery efforts.
Research significance and limitations
Our study offers a brand-new perspective by introducing spatial distance as a key factor influencing the motivations of emergency wildfire volunteers. Although past research has primarily focused on individual traits, psychological drivers, and organizational factors, the spatial dimension, particularly how distance from a wildfire affects motivation, has been largely overlooked. By examining this gap, our findings enrich the theoretical framework of volunteer motivation and provide practical implications for wildfire management. Specifically, we show that volunteers closer to fire zones are often driven by immediate protective concerns, whereas those farther away tend to be motivated by values such as ecological responsibility and personal growth. These insights suggest that spatial distance not only shapes perceived threat but also influences the types of motivations that drive engagement. Integrating this understanding into recruitment, training, and support strategies can enhance volunteer mobilization, increase rescue effectiveness, and better align management approaches with the diverse motivations across affected regions.
Admittedly, our study has some limitations. Data collection began months after the wildfire event, raising concerns about memory decay and potential discrepancies between reported and actual experiences. The survey focused primarily on residents, overlooking the role of digital platforms in disseminating rescue information and attracting online volunteers. Additionally, the adapted Volunteer Functions Inventory (VFI) was not fully customized for emergency contexts, particularly the Protective dimension, which may have led to underreporting of some motivations. Furthermore, the study is geographically confined to communities near the Jinyun Mountain Nature Reserve, limiting the generalizability of findings to other types of disasters or regions. Future study should expand the scope to include a broader range of emergency events and populations, enabling more comprehensive and transferable insights into volunteer behavior in disaster contexts.
CONCLUSION
Our study explored how spatial distance and demographic variables influence the motivations of emergency wildfire volunteers in the Jinyun Mountain region, using the VFI scale. Results indicate that Values and Social are primary drivers, with Career being the least influential. Although motivations shared similar spatial patterns, Values showed the greatest variation by distance. Demographics such as age, income, education, and experience also played key roles.
Volunteers serve as crucial intermediaries between crisis response and social-ecological systems. Their motivations, shaped by geographical proximity and demographics, reveal adaptive strategies for coping with wildfire risks. Close-range motivations often reflect personal and community protection, whereas volunteers from distant areas express broader environmental values. This diversity underscores the complexity of human-environmental interactions during emergencies. By integrating spatial dimensions into volunteer motivation research, this study enhances both theoretical frameworks and practical applications in disaster management, providing actionable insights to foster resilient, community-based responses to climate-induced risks.
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AUTHOR CONTRIBUTIONS
Conceptualization, Qiaoyun Sun and Ying Zhang. Funding acquisition, Qiaoyun Sun and Ying Zhang. Investigation, Ying Zhang, Teng Yue, and Yizhang Zhang. Methodology, Qiaoyun Sun and Ying Zhang. Supervision, Ying Zhang. Validation, Qiaoyun Sun and Yingran Zeng. Visualization, Yingran Zeng and Teng Yue. Writing – original draft, Qiaoyun Sun, Yingran Zeng, Ying Zhang, and Teng Yue. Writing – review & editing, Qiaoyun Sun, Yingran Zeng, and Ying Zhang. All authors have read and agreed to the published version of the manuscript.
ACKNOWLEDGMENTS
The authors would like to thank all the reviewers and editors who contributed their time and knowledge to this study. We also own special thanks to the undergraduates in Chongqing University, Ruining Du, Haonan Wu, Ruoyi Zhang, Xinxin Zhu, Junyang Chen, Xintong Wang, and Yuting Li, who participated in the fieldwork. We are grateful to the staff of Jingyuan Mountain Nature Reserve and Beibei District Forestry Bureau of Chongqing municipality, who provided us with strong support for the survey. We would like to extend our sincere respect and gratitude to all volunteers and local community members for their dedicated involvement in wildfire response efforts.This study was funded by the [National Natural Science Foundation of China] grant number [52578060], and the [GuangDong Basic and Applied Basic Research Foundation] grant number [2023A1515110856], and the [Guangdong Provincial Philosophy and Social Science Planning Project] grant number [GD22YYS09], and the [Chongqing Postdoctoral Fellowship for Outstanding Candidates] grant number [2024CDJXY014cstc2021jcyj-bshX0027], and the [China Postdoctoral Science Foundation] grant number [2024M753839].
Use of Artificial Intelligence (AI) and AI-assisted Tools
No artificial intelligence (AI) or AI-assisted tools were used in this study.
DATA AVAILABILITY
The data and code that support the findings of this study are available on request from the corresponding author, Ying Zhang. None of the data and code are publicly available because they contain information that could compromise the privacy of research participants.
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Fig. 1
Fig. 1. The geographic location of Jinyun Mountain and the burn area of the wildfire. Notes: (a) relative location of the study area within mainland China; (b) relative location of the study area within Chongqing Municipality; (c) overview of the study area.
Fig. 2
Fig. 2. Rescue at the scene of the wildfire in Jinyun Mountain. (Photo from: https://baijiahao.baidu.com/s?id=1742142378283767592&wfr=spider&for=pc)
Fig. 3
Fig. 3. The relative spatial position of volunteers and the wildfire. Notes: (a) spatial distribution of volunteers; (b) structured interview locations; (c) location of volunteers relative to wildfire range; (d) clustered distribution of volunteer space locations.
Fig. 4
Fig. 4. Different categories of motivations triggering emergency volunteers’ participation in Jinyun Mountain wildfire rescue. Note: See the details of survey indicators of motivation (for example, V1 indicates “I am concerned about those less fortunate than myself”) in Table 1.
Fig. 5
Fig. 5. Spatial distribution patterns of (a) Social motivation, (b) Value motivation, (c) Understanding motivation, (d) Protective motivation, (e) Enhancement motivation, (f) Career motivation.
Fig. 6
Fig. 6. Radar chart of motivation scores across different demographic groups (Age, Income, Education Level, Experience). Notes: (a) different age groups, (b) different income groups, (c) different education level groups, (d) different volunteer experience groups; S = Social, V = Values, C = Career, U = Understanding, P = Protective, E = Enhancement.
Table 1
Table 1. The Volunteer Functioning Inventory (VFI) survey items of this article.
| Type | VFI content of this article | VFI content of this article | |||||||
| Understanding | U1 | I can learn more about the cause for which I am working | Modify: Volunteering helps me understand why and how wildfires occur | ||||||
| U2 | Volunteering allows me to gain a new perspective on things | Reserve: Volunteering allows me to gain a new perspective on things | |||||||
| U3 | Volunteering lets me learn things through direct, hands-on experience | Reserve: Volunteering lets me learn things through direct, hands-on experience | |||||||
| U4 | I can learn how to deal with a variety of people | Reserve: I can learn how to deal with a variety of people | |||||||
| U5 | I can explore my own strengths | Reserve: I can explore my own strengths | |||||||
| Values | V1 | I am concerned about those less fortunate than myself | Reserve: I am concerned about those less fortunate than myself | ||||||
| V2 | I feel compassion toward people in need | Modify: I think that Jinyun Mountain is our home and should be protected | |||||||
| V3 | I am genuinely concerned about the particular group I am serving | Modify: I think it’s important to protect the natural ecosystem | |||||||
| V4 | I feel it is important to help others | Modify: I think it’s important to save the wildlife victims of the Jinyun Mountain wildfire | |||||||
| / | I can do something for a cause that is important to me | Delete | |||||||
| Social | S1 | My friends volunteer | Reserve: My close friends and relatives participated in wildfire rescue in Jinyun Mountain | ||||||
| S2 | Others with whom I am close place a high value on community service | Modify: My close friends and relatives think that volunteering to wildfire rescue on Jinyun Mountain is very valuable | |||||||
| S3 | People I’m close to want me to volunteer | Reserve: People I’m close to want me to volunteer for Jinyun Mountain emergency volunteers | |||||||
| / | People I know share an interest in community service | Delete | |||||||
| / | Volunteering is an important activity to the people I know best | Delete | |||||||
| Career | C1 | Volunteering experience will look good on my resume | Reserve: Volunteering experience will look good on my resume | ||||||
| C2 | I can make new contacts that might help my business or career | Reserve: I can make new contacts that might help my business or career | |||||||
| C3 | Volunteering will help me to succeed in my chosen profession | Modify: Volunteering allows me to develop the competencies I need for my career | |||||||
| C4 | Volunteering can help me to get my foot in the door at a place where I would like to work. | Modify: Volunteering can optimize my career trajectory | |||||||
| C5 | Volunteering allows me to explore different career options | Reserve: Volunteering allows me to explore different career options | |||||||
| Protective | P1 | Volunteering is a good escape from my own troubles | Modify: Participating in Jinyun Mountain wildfire rescue service makes me get rid of worries | ||||||
| P2 | By volunteering I feel less lonely | Modify: Participating in Jinyun Mountain wildfire rescue makes me feel less lonely | |||||||
| P3 | Volunteering helps me work through my own personal problems | Modify: Participating in Jinyun Mountain wildfire rescue can help me solve my own personal problems | |||||||
| / | Doing volunteer work relieves me of some of the guilt over being more fortunate than others | Delete | |||||||
| / | No matter how bad I’ve been feeling, volunteering helps me to forget about it | Delete | |||||||
| Enhancement | E1 | Volunteering makes me feel important | Reserve: Volunteering makes me feel important | ||||||
| E2 | Volunteering increases my self-esteem | Reserve: Volunteering at Jinyun Mountain increases my self-esteem | |||||||
| E3 | Volunteering makes me feel better about myself | Reserve: Volunteering in Jinyun Mountain makes me feel better about myself | |||||||
| E4 | Volunteering is a way to make new friends | Reserve: Volunteering in Jinyun Mountain is a way to make new friends | |||||||
| E5 | Volunteering makes me feel needed | Reserve: Volunteering at Jinyun Mountain makes me feel needed | |||||||