The Willingness and Affecting Factors Underlying Forest Farmers’ Socialization Method to Control Forest Biological Disasters

Abstract

Amid urbanization, many forest farmers have migrated for work, leading to a shortage of young labor in forestry. Socialized prevention and control (SPC) measures have emerged as a new forestry model. By integrating forestland property rights theory, SPC economic principles, and collaborative disaster governance, this study compares the econometrics methods of seemingly unrelated regression (SUR) and structural equation models (SEMs) to address correlation and endogeneity issues. It aims to understand forest farmers’ willingness to pay for SPC services, purchase forest insurance, and join as forest rangers. The findings offer theoretical and practical insights that address current challenges and rationalize SPC promotion costs, filling gaps in the existing literature. The results indicate that high-quality foresters with more home-planted forests are more inclined to hire SPC companies, while better-educated farmers are less likely to purchase forest insurance. Western forest farmers, highly reliant on forests, show greater willingness to become rangers under village committee organization. Farmers organized by committees or with prevention experience suggest SPC costs around USD $65/ha and forest premiums at USD $5/ha, with high-quality farmers proposing a ranger salary of USD $190/month. Recommendations include collecting SPC funds from farmers and supplementing through local finances; enhancing the forest insurance system; monitoring SPC companies; and recruiting young, skilled rangers.

1. Introduction

With the proliferation of both local and foreign invasive species surpassing the natural resilience of ecosystems, forest biological disasters (FBD) have ensued, leading to substantial economic and ecological setbacks, affecting almost 35 million ha annually and globally, mainly in boreal and temperate biomes [1,2]. The annual ecological and economic toll in China exceeds USD $16.92 billion, directly imperiling the livelihoods of forestry farmers, rural revitalization, and ecological rehabilitation achievements [3,4]. To mitigate FBD-related losses in forest resources, China has implemented a management approach based on the principle of “whoever manages bears responsibility”: public welfare forests are overseen by the government, forest land operators manage commercial forests, and those facing significant threats and losses are jointly addressed by both operators and local authorities [5]. Collective forests, which constitute 61.34% of China’s total forest cover, are owned by village collectives, with forest farming rights contracted to individual farmers and management rights held by operators. This setup grants over 87 million farmers control and ownership of more than 173.33 million hectares of forest land, enabling their participation in Forest Biological Disaster Control (FBDC) efforts [6,7].

The control management framework has evolved from sole government oversight in the initial stage to separate management by both government and forest land operators in the second stage, and currently, to collaborative prevention and control efforts led by the forestry department in partnership with land operators, gradually integrating social forces [2]. The socialized prevention and control (SPC) model encompasses various measures, including government-led forest ranger initiatives, voluntary actions by forest farmers, involvement of third-party companies specializing in forest protection, purchase of forest insurance to mitigate economic losses, and engagement of forest farmers in prevention and control efforts facilitated by these companies or rangers [8,9]. As of 2021, China’s control measures have covered an area of 10.088 million hectares, with a capital investment of USD $1.16 billion. Social investment constitutes 15.68% of this total, playing a significant role in curbing the outbreak and propagation of FBD [10].

SPC measures offer relief from control pressures forestry authorities and farmers face [11]. Forest farmers prioritize prevention and control measures that yield economic benefits from forest land, particularly focusing on commercially viable areas within collective forests. Farmers must purchase pesticides and equipment in commercial forests with artificially planted trees, amplifying cost burdens and challenges for FBDC. Limited knowledge of control technology among some farmers hampers control effectiveness [12]. Neglecting timely control of forest land or employing improper prevention methods, like cheap chemical pesticides, can escalate disaster risks and rural non-point source pollution [13,14]. Community-organized cooperative management of invasive plants proves more effective than individual, site-by-site farmer management [7]. Amid urbanization, the SPC model addresses these deficiencies, offering pre-disaster prevention, mid-disaster management, and post-disaster reconstruction services while alleviating labor, fund, and technology shortages [15,16,17]. Through this model, forest farmers engage by hiring SPC companies, purchasing forest insurance, or joining professional teams [18,19], enhancing their economic benefits and participation, which is critical for refining the SPC model [20].

In the realm of literature, farmers expressed willingness to collaborate on pest control services, leveraging economies of scale to alleviate forestry farmers’ land management expenses [7,21,22]. Forestry socialization services, particularly forest pest control and fire prevention, witness high demand [23,24]. Research by Sheremet (2017) revealed British forest visitors’ willingness to pay USD $19.27 annually per household for hedgerows and USD $27.03 for small woods (under 2 ha.), employing chemical/biocide control or thinning methods [25]. Public support leans toward publicly owned and charitable trust forests over private and commercial ones. Forest insurance mitigates economic loss risks, aiding forest farmers in vegetation repair post-disasters [26], albeit with low demand in many nations [27]. To bolster this, scholars devised indicator systems to analyze forest farmers’ insurance demand, aiming to boost market uptake and enhance forest insurance efficacy [28], alongside crafting insurance game models involving government, insurers, and foresters [29]. National-level forest insurance schemes, tailored to owners’ characteristics, forest types, and localization, were established [30]. Zhao and Wang (2015) calculated forest pest and disease insurance compensation at USD $61.54 per 1/15 ha., factoring in the affected area and disaster severity [31]. Forest rangers play a pivotal role in forest area management, with their performance influenced by attitude and motivation [32]. The introduction of ecological forest rangers significantly bolstered forest resource protection [33]. Zhu et al. (2022) assessed the impact of ecological forest rangers’ livelihood capital on livelihood risks using an ordered logistic regression model [34]. Additionally, several studies utilized Logit models and choice experiments to analyze factors influencing farmers’ willingness to engage in pest control services, forest insurance, and forest ranger programs [35,36].

The literature predominantly focuses on forest farmers’ engagement and payment attitudes toward pest control or social services related to forestry. Logit and Tobit models are commonly utilized as dummy variables to assess participation willingness, while choice experiments are employed to gauge payment willingness. These methods offer a theoretical foundation for shaping research ideas and models. However, there is limited analysis of the SPC model from the forest farmers’ perspective, and a dearth of examination regarding costs associated with hiring an SPC company, willingness to serve as forest rangers, expected income, etc. Additionally, governmental support factors are rarely considered in the existing literature. Dummy variables cannot comprehensively measure the willingness to participate and ignore the interrelationship among multiple equations, leading to estimation bias in regression results.

Therefore, approach. Firstly, it examines the current status and influential factors concerning forest farmers’ participation and willingness to pay across three SPC modes: hiring SPC companies, involvement in forest insurance, and transitioning into forest rangers. Additionally, it integrates the organizational capacity of village committees as a governmental support factor into the model, aiming to inform policy decisions regarding SPC expenditure under governmental guidance. Secondly, from a theoretical standpoint grounded in property rights theory, this study posits that forest farmers’ SPC engagement can be incentivized through the acquisition of management or contracting property rights over forest land. Given the economic dynamics of SPC, government intervention is deemed necessary to optimize control costs. Drawing on disaster emergency collaborative governance theories, this study incorporates variables related to forest farmers and government characteristics to enhance the theoretical understanding of forest farmers’ involvement in SPC activities. Thirdly, employing a perception rating Likert scale ranging from 1 to 5, this study analyzes varying degrees of perception differences. Comparative analysis mitigates disturbance relationships and endogeneity between participation and payment willingness models by comparing the structures of seemingly unrelated regression and structural equation models, thereby enhancing regression efficiency. This study addresses three core issues: (1) forest farmers’ inclination toward SPC participation; (2) forest farmers’ willingness to pay or anticipated income regarding SPC; (3) the impact of government, forest farmers, and household forestry management characteristics on forest farmers’ engagement in SPC initiatives.

2. Materials and Methods

2.1. Study Area

Our study introduced the concept of the Hu Line. The Hu Line, a well-known demographic–geographic line in China, was found to comprise only 36% of the country’s territory in South-eastern China, yet it was home to 96% of the population, while the North-west comprised the rest. This line was demonstrated to be superpositioned on the ecological environment, running very close to the 400 mm rainfall line that divides China into semi-humid and semi-arid regions [37]. The differences in population, environment, and economy between the Western and Eastern regions of China, including the differences in forest farmers’ cognition, natural conditions, government support, etc., may result in regional differences in the perception of FBD outbreaks and the resulting losses, the behaviors of measures taken, the investment, etc. Therefore, the representative provinces were selected from both the Western and Eastern regions, and a comparative analysis was conducted to determine the spatial heterogeneity of SPC [3,38]. The questionnaire survey was conducted in the provinces of Shandong, Guangdong, Inner Mongolia, and Xinjiang, selected on both the eastern and western sides of the Hu Line based on different climate zones. The four provinces mentioned above are located in China’s Eeastern, Wwestern, Southern, and Northern regions. Among them, Xinjiang is in the West and Inner Mongolia is in the North, both of which belong to the western side of the Hu Line; Shandong is in the East, and Guangdong is in the South, both of which belong to the eastern side.

As shown in Figure 1, the colors from dark to light represent the outbreak areas of FBDs by province, following the distribution principle of the Hu Line. As shown in Figure 1, the colors from dark to light represent the outbreak areas of FBDs by province. In China, the western side of the Hu Line is primarily affected by rodent (and hare) infestations in forestry. In contrast, the eastern side focuses on preventing key invasive species such as Mikania micrantha, Bursaphelenchus xylophilus, and Hyphantria cunea. These four harmful organisms pose severe and potentially massive threats to China’s forest ecosystems [3,10]. In the Western region, the provinces of Xinjiang and Inner Mongolia were selected for the highest area of FBDs. These places are also in the boreal. By 2023, the forest area in Xinjiang and Inner Mongolia reached 8.02 million and 26.15 million hectares, accounting for 3.64% and 11.86% of the national total, respectively. Their forest coverage rates were only 4.87% and 22.1%, below the national average (22.96%). The area affected by forest pests and diseases was 1.47 million and 1.02 million hectares, making up 13.44% and 9.37% of the national total, respectively. The control rates were 96.16% and 63.77%, respectively. Both regions are also major epidemic areas for forest rodents (hares), with affected areas accounting for 33.86% and 9.69% of the national total, respectively [39]. With their vast territories, this demonstrates that Xinjiang and Inner Mongolia are key regions for the Three-North Shelter Forest Program (TSFP). Increasing forest coverage has been identified as a priority for future efforts, yet both provinces face significant pest and disease control pressures [40]. Among them, Xinjiang has a temperate continental arid climate as its core, combined with mountain vertical climate zones and localized extreme climates. Despite its low forest coverage, it experiences many FBD outbreaks, but has implemented robust prevention and control measures. In contrast, Inner Mongolia is dominated by a temperate continental climate with additional diversity, including cold-temperate, semi-humid, semi-arid, and arid zones. Although its pest and disease pressure is lower than Xinjiang’s, its control rate still needs improvement [10,41]. Therefore, Xinjiang (with severe pest and disease threats) and Inner Mongolia (with insufficient control measures)—two representative regions—were selected as the study areas on the western side of the Hu Line.

In the East, the forest areas of Shandong and Guangdong comprise 2.67 million and 9.46 million hectares, respectively, accounting for 1.21% and 4.29% of the national total. Their forest coverage rates stand at 17.5% and 53.5%, with forest pest and disease occurrence areas of 0.45 and 0.37 million hectares, representing 4.14% and 3.37% of the national total, respectively. The control rates reach 93% and 91.27%, respectively [39]. Among them, Shandong Province falls within the warm temperate monsoon climate zone, making it prone to forestry biohazards and facing significant prevention and control pressures. Shandong is the main epidemic area for Hyhantria cunea, while Bursaphelenchus xylophilus (pine wilt nematode) has also occurred frequently in recent years [10,41]. Guangdong province, characterized by subtropical and tropical monsoon climates, boasts extremely high forest coverage. However, its hot and humid environment is highly conducive to pest and disease outbreaks, particularly Bursaphelenchus xylophilus, it was selected as a study area. The province is also a major epidemic zone for Mikania micrantha [41]. Through proactive prevention and control measures, Guangdong has effectively curbed the spread of these pests and diseases [10,41]. Therefore, regions with higher FBD risks in Shandong and effective control measures in Guangdong were selected as the study areas on the eastern side of the Hu Line.

The survey was conducted from May to November 2019: 20 villages from 10 counties of five cities in Shandong, 20 villages from 10 counties of five cities in Guangdong, 20 villages from 10 counties of five cities in Inner Mongolia, and 18 villages from six counties of two cities in Xinjiang were used. Although parts of Inner Mongolia lie east of the Hu Line, administratively, it belongs to the Northwest region [40]. Notably, all our survey sites were intentionally selected west of the Hu Line. Overall, 818 of 890 questionnaires were effective, with a validity rate of 91.91%. Among them, a total of 437 sets of data were obtained from the Eastern region, where Guangdong and Shandong are located, and 381 sets of data were obtained from the Western region, where Xinjiang and Inner Mongolia are located. In the survey, the decision makers whose families mainly engage in forestry production were selected as the survey subjects. Interviews were used, and the investigators filled out questionnaires to ensure the accuracy of the data.

2.2. Theoretical Base

In terms of theoretical and model selection, based on the property rights theory, the collective forest tenure reform under the system is as follows: forest land ownership remains with the community, contracting rights are allocated to individual forest farmers, and management rights are transferred to specialized households or forest enterprises. This separation of rights gives forest farmers broader usage and management authority while maintaining collective ownership [42]. The higher the degree of freedom that forest farmers have in decision making or disposal of forest land, the stronger their willingness to participate in forest land management [43]. Forest farmers adopt SPC measures to reduce economic losses caused by FBD [44]. The degree of willingness differed based on the ownership motivation [7]. Therefore, this study focused on the farmers who obtained sufficient operating or contracting rights to collective forest land. We selected household forestland management characteristics to represent forestry property rights.

As for the economic theory of SPC measure, Wang (2013) discussed from the perspective of neoclassical welfare economics that forest pest control work has externalities, non-competitiveness, and public goods attributes, which can cause market failures and information asymmetries, causing the government’s control behavior to have the attribute of quasi-public goods [45]. The government and forest land operators sign contracts, hire SPC companies, purchase forest insurance, or recruit forest rangers, etc., resulting in market transactionsand making SPC measures have consumer product attributes [46]. Solely relying on market regulation between farmers and SPC models would cause many problems, such as information asymmetry and imbalance between supply and demand. Government agencies must be added to mediate these problems [47]. Therefore, this study selected the village committee SPC organizing abilities variables to represent the government’s support.

Theory of Collaborative Governance of Disaster Emergency Response: The government should establish an environmental collaborative governance system, starting from the theoretical logic of “public goods-market failure—government intervention-government guidance”and construct a cross-domain ecological environment multi-governance system with “government-led, enterprise-based, social organizations, and public participation” [48,49]. As for the FBDC, it also requires collaboration and cooperation from all of society and relies on an emergency response and collaborative governance system of joint control among governments, forest land managers, and SPC companies [50]. Therefore, this study analyzes the influence of government and forest farmers’ characteristic variables on SPC. Moreover, it selected farmers’ characteristics and their participation, payment, and reimbursement willingness of SPC.

2.3. Indicator Selection

Based on the literature analysis, the constructed models started from three SPC models: participation and willingness to pay for SPC companies, forest ranger participation and expected income, participation in forest insurance, and willingness to pay premiums, which are dependent variables. According to the theoretical research conclusions, the characteristics of forest land plantation decision makers, household forestry, and village committees were used as independent indicators to analyze the degree of impact on SPC.

In terms of the characteristics of production decision makers, the personal characteristics of forest farmers will have a direct impact on household forestry production and management activities [51]. If there is a lack of young laborers in the family and the forest farmers’ cognitive level is high, the forest farmers would increase recognition of SPC [52]. Zhu et al. (2022) found that longer education years for ecological forest rangers can reduce their employment risks [34]. Age and education level strongly impact forest farmers’ cognitive ability, technical level, and attitude [32]. Thus, the factors of age, education level, health status, and whether they are village cadres of farmers were chosen to represent the farmers’ personal cognitive ability.

In terms of household forest management characteristics, the larger the area of the forest land planted by forest farmers (artificial forests) in collective forests, the broader the scope of forest farmers’ dispositional rights over forest land [12]. Han et al. (2019) found that the larger the economic forest scale, the higher the demand for disease and pest control by farmers [35]. If forest farmers have consciously taken control measures, their awareness of SPC may be affected [53]. If the FBD outbreak area is larger, forest farmers’ demand for hiring SPC companies will be more urgent [54]. Qin et al. (2016) hold the opinion that “the frequency of farmers suffering from disasters significantly affects the farmers’ demand for forest insurance” [28]. Therefore, the factors of the proportion of artificial forests to the forest land, the FBD outbreak area, and whether control measures were taken were selected to represent the household forestry production situation.

According to theoretical research, the government plays a positive regulatory role in forest farmers’ participation in the SPC model. Village committees are the most direct government decision making and implementing organizations for forest farmers [54]. Graham and Rogers (2017) highlight that community leaders and supportive government staff who liaise between local groups and government agencies are pivotal to effective collective action [13]. Therefore, the village committee’s function degree variables include their role in organizing SPC, selecting forest rangers, and organizing forest insurance.

2.4. Research Methods

Based on theoretical analysis, forest farmers’ participation and payment willingness in SPC behavior is influenced by their characteristics, forestry features, and the role of village committees. At the same time, there may be a disturbance effect and endogeneity between forest farmers’ willingness to participate and willingness to pay. When forest farmers are willing to participate in the SPC, it may impact their willingness to pay. If the effect is significant, endogeneity exists; even if the impact is not significant, there may still be a correlation issue between participation and willingness to pay disturbances [55]. Therefore, this study establishes a seemingly unrelated regression (SUR) model. SUR is built on the premise that there is no inherent relationship between each equation, but there is a correlation between the disturbance terms of each equation [56]. By integrating two-stage least squares into the SUR model, a simultaneous equation model (SEM) was established to overcome potential endogeneity issues between models. By comparing the regression coefficients of SUR and SEM, the stability and accuracy of the results were improved [57]. SUR and SEM are constructed as follows:

S_ij = α_0j + α_1jX_ij + α_2jY_ij + α_3jZ_ij + μ_1ij

(1)

W_ij = β_0j + β_1jX_ij + β_2jY_ij + β_3jZ_ij + μ_2ij

(2)

W_ij = λ₀ + λ_1jW_ij + μ_3ij

(3)

where i represents the i-th farmer, j represents the j-th indicator value, S_ij represents the SPC participation willingness characteristic variable, including willingness indicators such as hiring SPC companies, becoming forest rangers, and participating in forest insurance; W_ij represents the social payment and compensation characteristic variable, including the willingness to pay for hiring SPC companies, expected income from becoming forest rangers, and forest insurance premium payment; X_i represents the producer decision maker characteristic variable; Y_i is the household forestry feature variable; and Z_i is the village committee role feature variable. α, β, and λ represent the corresponding coefficients, and u is the corresponding error term.

3. Results

3.1. Sample Characteristics

The survey results are shown in

Table 1. The basic characteristics of respondents.

Characteristics	Index	Description	Mean			Std. Err.
			Total	East	West
Production decision makers	Age	Year	51.933	53.044	50.654	12.299
	Education	Year	5.089	5.800	4.260	4.213
	Health Condition	very healthy = 5, healthy = 4, normal = 3, ill = 2, seriously ill = 1	3.882	4.100	3.632	1.179
	Village cadres	Yes = 1, No = 0	0.173	0.203	0.137	0.378
Household forest management	Artificial forest proportion	Plantation area/total forest area	0.491	0.385	0.613	0.812
	FBD outbreak area	Hectare (ha.)	0.682	0.996	0.323	3.232
	Control or not	Yes = 1, No = 0	0.440	0.478	0.396	0.497
Organizing ability of village committee	SPC	very strong = 5, relatively strong = 4, general = 3, relatively weak = 2 and very weak = 1	4.031	4.142	3.914	0.988
	Selecting forest rangers		4.071	4.215	3.916	0.958
	Forest insurance		3.866	4.002	3.712	1.061
Willingness to participate	Hire a SPC company	very willing = 5, willing = 4, general = 3, reluctant = 2, very reluctant = 1	3.079	3.344	2.655	1.358
	Purchase forest insurance		2.545	2.722	2.319	1.170
	Become a forest ranger		3.485	2.972	4.084	1.512
Payment, compensation, and expected income	Pay for SPC company	USD/ha.	108.730	119.393	27.692	747.841
	Forest insurance premium	USD/year/ha.	5.809	9.231	5.654	44.858
	Expected income of forest rangers	USD/month	203.358	241.516	158.621	451.686

Note: USD $1 = CNY 6.5.

. Regarding the basic characteristics of respondents, the average age was 52 years, with an average of 5 years of education, good health, and 17.3% of respondents having served as village cadres. The proportion of artificial forests was 49.10%, the average FBD outbreak area was 0.682 ha, and 44% of forest farmers had taken preventive and control measures on their own forest land. The organizational capacity of village committees and the willingness of forest farmers in SPC to participate are represented using a Likert scale of 1–5 to indicate the degree of agreement [58]. The results showed that the forest farmers generally recognized the organization and prevention ability of the village committee, considered that the committee played the most significant role in selecting forest rangers, and expressed a strong willingness to become forest rangers. However, the awareness of forest insurance participation was relatively weak. Except for the artificial forest proportion and the willingness to become a forest ranger, all other indicators are higher on the east side than on the west side.

This study analyzed six prevention and control modes: self-prevention and control, joint prevention and control, and obtaining ecological medicinal prevention and control. This study also analyzed three SPC participation modes, including becoming forest rangers, paying for forest insurance, and hiring SPC companies. And over half of the forest farmers prefer to adopt SPC measures. Among them, 32.8% of farmers preferred to become forest rangers, while 18% preferred to hire SPC companies, and 6.2% preferred to pay for forest insurance.

3.2. Model Testing

Collinearity tests were implemented on the models, and the inflation factors were all less than 10, indicating that there was no serious collinearity problem. The Breush–Pagan test was used to test the hypothesis that there was no correlation between disturbance terms, and the significance levels were all below 1%, rejecting the null hypothesis of “no contemporaneous correlation”. This indicates that SUR can effectively overcome the estimation bias caused by correlated disturbance terms and improve the efficiency of the model regression. The Hausman test was used to test the endogeneity of the model, and the chi-square values of the three models were small, indicating that the hypothesis that all variables are exogenous was accepted, and the variables are exogenous except for the willingness to participate and pay. The simultaneous equation model is further employed to address potential endogeneity issues that may arise between participation and willingness to pay. Therefore, all three equations can use SUR and SEM for further empirical analysis.

3.3. Willingness to Hire SPC Companies

According to Table 1, forest farmers’ willingness to hire SPC companies is 3.079, indicating a neutral attitude, and they could accept USD $108.73/ha of SPC costs. The willingness to hire SPC companies is higher in the Eastern region than the Western region, and the payment capability is much higher in the East than in the West. The results of the empirical analysis of willingness to hire and pay for SPC are shown in

Table 2. The factors affecting farmers’ hiring willingness (HW) and payment willingness (PW) for SPC companies.

	SUR			SEM
	HW	PW		HW	PW
	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.
HW			−12.753 (8.864)			−25.319 (20.462)
Age	0.006 (0.021)	−0.853 (0.781)		0.008 (0.020)	−0.904 (0.802)
Education	0.172 ** (0.077)	−10.540 *** (2.959)		0.196 *** (0.075)	−11.542 *** (3.174)
Health condition	−0.220 (0.228)	5.934 (8.672)		−0.222 (0.221)	6.941 (8.988)
Village cadres	−0.487 (0.551)	−34.683 * (20.961)		−0.312 (0.534)	−34.192 (21.751)
Artificial forest proportion	1.263 * (0.693)	18.734 (26.568)		1.077 (0.675)	14.874 (28.318)
FBD outbreak area	0.081 (0.176)	−3.198 (6.659)		0.086 (0.170)	−3.607 (6.850)
Self-control	−0.429 (0.615)	−50.262 ** (23.368)		0.200 (0.595)	−50.547 ** (24.172)
Village committee organizing ability (VCOA)	−0.195 (0.303)	−11.396 (11.505)		−0.134 (0.293)	−11.108 (11.876)
Constants	3.227 (2.343)	260.700 *** (88.973)	141.982 *** (33.567)	2.625 (2.263)	266.913 (91.304)	183.761 *** (69.996)
Chi2	16.04	49.49	2.07	17.30	51.11	1.53
R2	0.276 **	0.575 ***	0.019	0.247 **	0.587 ***	−0.034

Note: ***, **, and * represent that the results are significant at p < 0.01, p < 0.05, and p < 0.1 (the values within parentheses are standard errors).

. The results of SUR and SEM do not differ significantly in terms of significance, but the regression results between the hiring and payment willingness toward SPC companies are insignificant, which indicates that the model does not have endogeneity issues, with SUR performing slightly better than SEM in this case. Forest farmers’ education level passed the significance test at the level of willingness to hire, with every one-year increase leading to a 0.172 increase in willingness to participate according to SUR and 0.196 according to SEM. The proportion of artificial forests has passed the significance test in SUR, with a 1% increase leading to a willingness increase of 1.263.

The level of willingness to pay, education level, whether or not they are village cadres, and whether or not they have taken preventive and control measures have all passed the significance test and have a negative impact. Specifically, for every one-year increase in education level, the expected cost of SPC decreases by USD $10.54 for SUR and USD $11.54 for SEM, which means that they can accept a cost of around USD $98/ha for SPC. For those who have served as village cadres before, the expected cost will decrease to USD $34.68. For those who have taken preventive and control measures, the forest farmers hope to reduce the cost by USD $50.26 for SUR and USD $50.54 for SEM, which means that they can accept costs around USD $60/ha, respectively.

3.4. Willingness to Participate in Forest Insurance

A total of 756 households responded to forest insurance, and as shown in Table 1, the willingness of forest farmers to participate in forest insurance is 2.545, indicating a relatively low level of willingness. According to the results of the survey, only 6.4% of forest farmers currently participate in forest insurance. Among the participating households, the average premium paid is USD $5.81/ha, and the average insured area is 1.62 ha. The average compensation received is USD $1266.14/ha. The purchasing and payment willingness is higher on the east side than on the west side. Taking the national forest insurance status in 2021 as an example, the premium for commercial forests is set at USD $5.08/ha, which can provide insurance compensation of up to USD $2307.69/ha. The government provides an 80% fiscal subsidy, requiring forestry operators to pay only USD $1.02/ha. However, this indicates that: actual premiums paid by forest farmers exceed policy-mandated costs, suggesting incomplete delivery of fiscal subsidies; the current premium remains higher than farmers’ psychological expectations; and compensation benefits fall below the national average, with China’s average payout rate being just 20.99% [59]. If the government provides certain funding subsidies, the participation rate of forest insurance among farmers can increase to 91.9%.

Empirical analysis was conducted on forest farmers’ willingness to participate in forest insurance and insurance premiums, and the results are shown in

Table 3. The factors affecting farmers’ willingness to purchase forest insurance (WPI) and pay premiums (PP).

	SUR			SEM
	WPI	PP		WP	PP
	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.
Willingness to Purchase			0.371 ** (0.164)			0.744 ** (0.374)
Age	−0.028 *** (0.006)	−0.013 * (0.008)		−0.028 *** (0.006)	−0.021 ** (0.011)
Education	−0.089 *** (0.021)	−0.028 (0.027)		−0.083 *** (0.020)	−0.055 (0.036)
Health condition	0.035 (0.061)	0.013 (0.070)		0.033 (0.058)	0.023 (0.071)
Village cadres	−0.664 ** (0.327)	−0.292 (0.386)		−0.648 ** (0.312)	−0.490 (0.422)
Artificial forest proportion	0.464 (0.464)	0.284 (0.536)		0.478 (0.441)	0.422 (0.546)
FBD outbreak area	−0.053 (0.071)	0.005 (0.082)		−0.043 (0.068)	−0.011 (0.084)
Self-control	−0.076 (0.158)	−0.145 (0.181)		−0.109 (0.150)	−0.168 (0.181)
VCOA	−0.422 *** (0.079)	−0.198 * (0.105)		−0.416 *** (0.077)	−0.324 ** (0.150)
Constant	5.735 *** (0.785)	5.838 *** (1.027)	3.498 *** (0.385)	5.635 *** (0.762)	6.920 *** (1.390)	2.709 *** (0.811)
Chi2	81.73	6.50	5.11	73.47	6.64	3.94
R2	0.625 ***	0.114	0.018 **	0.622 ***	0.135	−0.039 **

Note: ***, **, and * represent that the results are significant at p < 0.01, p < 0.05, and p < 0.1 (the values within parentheses are standard errors).

. The regression of willingness to purchase on payment of premiums passed the 5% significance test, indicating some endogeneity between the two indicators. The regression results of SEM are slightly better than those of SUR, but the significance difference is not significant.

The willingness to participate, age, education level, whether or not they are village cadres, and the role of the village committee in organizing forest insurance have all passed the significance test and have a negative impact. Specifically, these factors reduce willingness by 0.028, 0.089 of SUR (0.083 of SEM), 0.664 (0.648), and 0.422 (0.416), respectively. This indicates that older farmers, those with higher education levels, and those who have served as village cadres are less willing to participate in forest insurance.

At the level of premium payment, age and the role of the village committee in organizing forest insurance both have a significant negative impact on premium payment willingness, reducing the payment by USD $0.013 (USD $0.021) and USD $0.198 (USD $0.324), respectively. Forest farmers willing to purchase insurance are willing to pay an additional USD $0.371 (USD $0.744) in premiums. This means that after the village committee unified organization, older forest farmers and those willing to purchase insurance could accept a premium of around USD $5.5–6.5/ha.

3.5. Willingness to Become Forest Rangers

As shown in Table 1, the willingness of forest farmers to become forest rangers is 3.485, indicating a relatively high level of enthusiasm. The willingness of forest farmers on the west side to become forest rangers is much higher than that on the east side, but the expected income of forest farmers in the East is higher than that in the West. The selection process for forest rangers is mainly based on village elections and assessments, with priority given to poor households. Through ecological forest ranger registration and certification, a combination of improving prevention and control efficiency and consolidating poverty alleviation results can be achieved [60].

Among the surveyed forest farmers, there were 111 forest rangers, and an analysis was conducted on the current situation of forest ranger management. The results showed that the forest rangers were generally satisfied with their work status and wages, with a satisfaction rate of 80.4%. They expected to receive an average income of USD $203.36 per month, while the actual average income was USD $96.67 per month. The current salary cannot meet the psychological expectations and cannot attract young people with knowledge. This situation could reduce the enthusiasm of farmers to become forest rangers and affect the effectiveness of forest rangers’ protection and their level of integration into society. Empirical analysis was conducted on forest farmers’ willingness to become forest rangers and expected income. Becoming a forest ranger is a nationwide phenomenon, and the economic development strength in the East has historically been superior to that of the West [61], resulting in differences in the intensity of willingness and expected income to become forest rangers between the East and West. Therefore, the empirical analysis was also conducted from three dimensions: overall, West, and East.

Comparing the SUR and SEM results of the overall analysis, a significant relationship was found between willingness to participate and expected income. Thus, SEM was used to eliminate the endogeneity effect on the regression results of the model. The regression results are shown in

Table 4. The factors affecting farmers’ willingness to become forest rangers (WB) and expected income (EI).

	Total			Eastern			Western
	WB	EI		WB	EI		WB	EI
	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.	Coef.
WB			−23.966 *** (6.883)			3.439 (10.721)			−0.047 (4.855)
Age	−0.003 (0.011)	−0.058 (0.311)		−0.013 (0.014)	−0.059 (0.300)		−0.002 (0.008)	−0.097 (0.151)
Education	0.046 (0.037)	−2.349 ** (1.052)		−0.087 (0.057)	−1.685 (1.257)		−0.003 (0.023)	0.538 (0.422)
Health condition	−0.098 (0.121)	3.223 (3.416)		0.156 (0.225)	0.183 (4.632)		−0.043 (0.066)	−0.686 (1.222)
Village cadres	−0.755 ** (0.332)	13.095 (10.053)		−0.938 ** (0.455)	−5.941 (11.382)		−0.029 (0.211)	8.011 ** (3.884)
Artificial forest proportion	1.025 *** (0.314)	−27.802 *** (9.677)		−0.256 (0.482)	5.070 (9.872)		0.385 (0.768)	6.042 (14.146)
FBD outbreak area	0.081 (0.120)	−2.891 ( 3.383)		0.253 (0.159)	−1.237 (3.790)		−0.473 *** (0.081)	−4.665 *** (1.759)
Self-control	−0.358 (0.325)	12.110 (9.202)		−0.472 (0.514)	2.491 (10.931)		0.540 *** (0.181)	1.951 (3.489)
OAVC	0.497 *** (0.147)	−12.259 *** (4.612)		0.347 (0.225)	1.453 (5.177)		0.303 *** (0.082)	−6.809 *** (1.590)
Constant	1.558 (1.126)	266.316 *** (32.831)	289.130 *** (27.349)	2.621 (1.611)	235.558 *** (32.672)	219.992 *** (34.017)	3.435 *** (1.086)	187.562 *** (20.123)	157.213 *** (23.387)
Chi2	40.90	22.46	12.12	17.04	6.25	0.10	40.90	22.46	0
R2	0.266 ***	0.216 ***	0.121 ***	0.234 **	0.139	−0.012	0.266 ***	0.216 ***	0

Note: ***, ** represent that the results are significant at p < 0.01, p < 0.05 (the values within parentheses are standard errors).

. The level of willingness to participate, whether or not they are village cadres, the proportion of artificial forests, and the role of the village committee in selecting forest rangers have all passed the significance test. Specifically, for every 1% increase in the proportion of artificial forests, the willingness to participate increases by 1.025, and for every 1 unit increase in the organizing ability of the village committee, the willingness to become a forest ranger increases by 0.497. In the West, there is a significant increase of 0.303, and the willingness of forest farmers who have experience in forest pest and disease control in the West to become forest rangers increases by 0.540.

The attributes of village cadres have a certain substitutive effect on forest rangers. When forest farmers have served as village cadres before, their willingness to become forest rangers will decrease by 0.755. Additionally, in the Western region, if the area of FBD increases by 1 hectare in a forest farmer’s household, the willingness to become a forest ranger will decrease by 0.473.

Regarding the expected income for forest rangers, factors such as education level, the proportion of artificial forest area, and the organizational ability of the village committee in selecting forest rangers have all passed the significance test and have a negative impact. Specifically, every unit increase in these factors will lead to a reduction in expected income by USD $2.35, USD $27.80, USD $12.26, and USD $23.97, respectively, resulting in an expected income of around USD $176–200 per month. Additionally, forest farmers who are willing to become forest rangers will reduce their income requirements.

Furthermore, in the Western region, forest farmers who have served as village cadres significantly expect an increase of USD $8.011 in income as forest rangers. However, if a forest farmer’s household occurs FBD, the expected income as a forest ranger will decrease by USD $4.67, and after the organization of the village committee, the expected income as a forest ranger will decrease by USD $6.81.

4. Discussion

Using SUR and SEM, this study bridges the empirical research gap in the SPC activities of FBD among forest farmers by examining their engagement, financial contributions, and anticipated earnings across three SPC modes: employing SPC companies, acquiring forest insurance, and taking on roles as forest rangers. This research offers valuable insights for governments at various levels and forestry management bodies to develop informed SPC policies. The discussion is based on the underlying research theory and the key findings presented. The following analysis categorizes and discusses the internal/external factors influencing forest farmers’ participation in and payment for SPC, with consideration of regional variations:

(1) Regarding forest farmers’ willingness to participate in and pay for SPC, forest farmers in the research exhibit varying levels of willingness to engage in different forest protection measures. The highest willingness is seen for assuming the role of a forest ranger, followed by contracting an SPC company, while the least willingness is observed for purchasing forest insurance. This pattern corresponds with prior research indicating that forest farmers are more inclined toward community prevention and control measures rather than purchasing forest insurance [29,52]. This study highlights that forest farmers are prepared to bear SPC costs amounting to USD $108.73 per hectare, significantly surpassing the willingness to pay for forest visitors in the UK for commercial forests, estimated at USD $19.27 by the authors of [25]. Previous studies suggest a willingness to pay around USD $200 per hectare for prevention and control costs to mitigate economic losses on forest land. The adoption of SPC measures can potentially lead to economies of scale and reduced prevention and control expenses.

Forest insurance premiums for SPC are estimated at USD $5.81 per hectare, aligning closely with the annual premium of comprehensive insurance for forests in China, as reported in [62]. This study focuses on FBD and the willingness to pay for forest protection, specifically for this type of event. The results are akin to Tanner’s (2021) findings regarding the US public’s willingness to pay USD $5.14 per month to reduce forest damage from high risk to lower risk [63]. The distinction lies in forest farmers’ willingness to purchase insurance to mitigate their losses compared to the public’s willingness to pay for the ecosystem services provided by forests.

The anticipated earnings for forest rangers, as estimated in the study, amount to USD $203.36 per month. This income benchmark, drawn from data on village-level forest ranger earnings, serves as a pricing reference for forest ranger salaries. When compared to similar situations in Nepal, where youths working in paper production earn between USD $80 and 120 per month and migrant worker rangers earn USD $190–900, it becomes evident that the income levels for forest rangers in China are notably lower [64]. This issue of low income is not confined to grassroots forest rangers; even managerial staff within China’s forestry sector earn lower average annual incomes compared to other government employees and forestry enterprise staff [65]. The combination of low incomes and the ongoing urbanization process has led to a scarcity of grassroots-level employees, particularly in economically prosperous regions like Eastern China, where alternative job opportunities often offer higher pay, dissuading individuals from pursuing forest ranger positions.

(2) Regarding the impact of government support measures on SPC, the supportive role of governmental bodies is exemplified by village committees. However, while village committees have a positive impact on the selection of forest rangers, they exert a significant negative influence on forest ranger income expectations, participation in forest insurance, and willingness to make payments. Additionally, they do not notably affect forest farmers’ hiring of SPC companies. The method employed by village committees in organizing bids for SPC companies is still nascent, contributing to inadequacies in forestry and grassland protection institutions below the county level. These inadequacies manifest in issues such as small-scale, non-standard organizational structures; low marketization levels; weak prevention and control technical capacities; outdated infrastructure; and aging machinery, which collectively diminish the organizational guidance capacity of village committees for SPC [66]. Furthermore, village committees themselves lack capacity and professional expertise [67]. Excessive government involvement impedes market and civil force participation in SPC, thereby limiting the efficacy and oversight mechanisms of socialization. Despite this, village committees serve as the primary implementing agency for selecting, promoting, and training forest rangers [68]. They have demonstrated some effectiveness in implementing national ecological forest ranger policies. Through mobilization and propaganda efforts, village committees can reduce forest farmers’ salary expectations to become forest rangers. However, the heavy workload of village cadres in organizing village affairs diminishes their inclination to become forest rangers themselves, often resulting in the delegation of ecological forest ranger positions to impoverished households or young technical forest farmers. Additionally, village cadres in Western regions advocate for a USD $8 increase in forest ranger incomes, yet they are hesitant to purchase existing forest insurance policies. Village cadres possess insights into the local SPC landscape and the payment capabilities of forest farmers, believing that a reasonable prevention and control cost should hover around USD $98 per hectare.

As for policy-based forest insurance, relevant government departments and institutions play crucial roles in addition to village committees. The state has provided substantial fiscal support policies, with an overall national subsidy rate of 88.16% in 2021 and an insured amount of USD $2067.25/ha. Under normal circumstances, the average afforestation and tending costs reach at least USD $2307.69/ha. However, our survey found that farmers’ actual compensation amounts averaged only USD $1266.14/ha, far below the actual value of forest stands and insufficient to cover post-disaster recovery costs, failing to meet forest operators’ needs for risk mitigation [69]. For insurance providers, operational costs remain high due to China’s decentralized forestry management system. The widespread distribution of insured subjects makes premium collection difficult, resulting in mismatched revenues and costs. Additionally, insurers must employ numerous technical specialists to assess different tree species, ages, and FBD damage conditions, as well as evaluate post-disaster losses—all of which increase claims adjustment and settlement expenses. These combined factors have dampened enthusiasm among both demand-side forest operators and supply-side insurance institutions, making it difficult to further improve the insurance participation rate [70].

(3) The impact of forest land ownership on SPC. Forest ownership rights significantly influence forest farmers’ engagement with SPC companies. While a higher proportion of artificial forests in households increases forest farmers’ willingness to hire SPC companies and assume roles as forest rangers, it reduces their expected income from this endeavor. This aligns with Han’s (2019) finding that a larger economic forest scale drives farmers to seek FBDC services to enhance forest quality [35]. With substantial artificial forest areas, farmers prefer SPC company management to address labor shortages and technical limitations at home [12]. As forest rangers, they not only oversee forest management but also earn additional income, with farmers overseeing larger artificial forest areas accepting around USD $180 monthly for ranger duties [59].

(4) The influence of forest farmers’ household and forest management characteristics on SPC participation. The influence of household silviculture characteristics on forest farmers’ engagement with SPC is noteworthy. Those who have implemented prevention and control measures are less inclined to invest in SPC services but show a higher propensity to become forest rangers. Conversely, households that have encountered pests and diseases experience reduced willingness among forest farmers, particularly on the west side, to assume ranger roles and anticipate lower income. Forest farmers with FBDC capabilities prioritize FBDC’s importance, mitigating economic losses from FBD through proactive measures [71,72]. Farmers on the west side with prevention and control experience are more willing to become forest rangers. Additionally, those facing FBD in their forests may view ranger duties as a convenient way to manage their land while offsetting salary demands. Consistent with Liao’s (2022) findings, farmers must enhance investment in resources such as funds and labor to meet SPC service demands [73]. Those who have implemented prevention and control measures tend to have already invested in pesticides as part of their livelihood strategy, hesitating to allocate additional resources to hire SPC companies. Furthermore, farmers dealing with pests and diseases in their forests may feel overwhelmed, reducing their willingness to become forest rangers as the affected area expands.

(5) The individual attributes of forest farmers influence their involvement in SPC. Elderly forest farmers are less willing to invest in forest insurance and SPC services. Likewise, those with higher educational attainment are less inclined to pay SPC fees and purchase forest insurance. However, they are more likely to enlist SPC companies, potentially sacrificing expected ranger income. This aligns with Sheremet et al.’s (2017) finding that individuals with higher income, greater FBDC knowledge, and frequent nature exposure are more receptive to SPC [25]. Higher-educated forest farmers perceive SPC as imposing opportunity costs on their families, thus opting for SPC companies to save time for other pursuits like outdoor work. However, Sheremet (2017) observed greater public willingness to pay for pest control fees, contrasting slightly with forest farmers’ participation in SPC in China [25].

The socialized mechanisms in China require enhancement, as forest farmers have a limited capacity to afford SPC. Consequently, the more forest farmers comprehend SPC, the more inclined they are to engage SPC companies at reduced rates [74]. According to Zhu’s (2022) study, “the longer the educational tenure of ecological rangers, the lower their employment risk” [34]. Despite considering alternative career paths, forest farmers acknowledge the societal significance of being forest rangers, thus not overly prioritizing ranger income [19,75]. Nevertheless, forest insurance remains nascent, with Chinese farmers often lacking awareness regarding natural disaster risks and forest insurance concepts, leading to limited willingness to participate [28,29]. Additionally, systemic deficiencies, inadequate government subsidies, insufficient policy backing, and a dearth of diverse forest insurance products impede forest insurance progress. Historical negative encounters with poorly regarded insurance entities have fostered skepticism [76,77]. Elevated premiums frequently surpass forest farmers’ economic means, and the coverage may not align with their risk management needs, resulting in older forest farmers possessing greater knowledge about forest insurance but exhibiting lesser inclination to purchase it [62,73].

Regarding regional variation characteristics in forest farmers’ participation in SPC, artificial forests predominate in the Western region, fostering a greater aspiration for forest ranger roles, whereas other metrics favor the Eastern region. The Hu line, a demographic demarcation dividing China into Southeast and Northwest zones, historically boasts economic prosperity, dense populations, ample resources, and favorable climates in the Southeast [40]. Consequently, the Eastern region exhibits higher levels of education, health standards, self-preventive measures, engagement with socialized enterprises, adoption of forest insurance, organizational efficacy of village committees in SPC, and anticipation for forest ranger incomes compared to the Western region. Factors like population migration and trade infrastructure contribute to increased occurrences and risks of pests and diseases in the Eastern region [61]. Conversely, the Western region is characterized by vast expanses of sparsely populated land, arid climates, and relatively lower economic development than the East. The disparity in annual incomes of forest farmers between the East and West is depicted in Figure 2, with Eastern farmers earning notably higher incomes. Eastern forest farmers augment their earnings through off-farm employment, such as factory work, while their Western counterparts rely more on operational revenue, with forestry constituting up to 45%. Limited alternative income avenues, such as migrant labor, prompt Western forest farmers, particularly those experienced in self-preventive practices and encouraged by village committee initiatives, to pursue forest ranger roles to bolster household incomes.

Regarding research limitations, this study fills a gap in China’s research on regional differences in farmers’ willingness to participate in SPC. However, it mainly reflects the average level of farmers’ participation in SPC and the East–West differences along the Hu Line while providing weaker insights into individual participation willingness. While the actual cost of SPC per hectare may surpass farmers’ payment capacity, it is essential to calculate varied SPC and management costs based on regional disparities, tree species in collective forest lands, and forest product values. Moreover, given that China is comprised of 31 provinces, it is challenging to investigate and reflect on each province’s farmers’ willingness to participate in SPC from their perspective. Therefore, in future research, we will expand the study areas and supplement survey data from the same farmers to compare the spatiotemporal differences in livelihoods between farmers on both sides of the Hu Line. We will also deepen the research by examining national policies, forest insurance institutions, and farmers’ participation capacity to address the limitations of this study.

Note: forestry income includes income from forestry operations and subsidies related to forestry; household income includes wage income, operating income (planting, forestry, sideline, breeding, and self-employment), subsidies, and other income (capital income, maintenance income, social relationship income, and other).

5. Conclusions

This research focused on Shandong, Guangdong, Xinjiang, and Inner Mongolia, areas heavily affected by Bursaphelenchus xylophilus, Hyphantria cunea, Mikania micrantha, and forest rodent (rabbit) damage. By examining the engagement and payment willingness of forest farmers in SPC, the following three findings emerged:

• Regarding the willingness to engage SPC companies: An analysis, as presented in Table 2 and discussions, indicates that forest farmers with higher levels of education and a greater proportion of artificial forests are more inclined to hire SPC companies. This aligns with [52]’s findings. Forest farmers are generally willing to accept an average pest control cost of USD $108.73/ha, with those possessing higher education levels, previous village leadership experience, and personal preventive measures opting for approximately USD $65/ha as a more acceptable SPC cost.
• Concerning participation and willingness to pay premiums for forest insurance: Forest farmers exhibit diminished interest in purchasing forest insurance, consistent with prior research [27]. When organized by the village committee, forest farmers with higher education levels, advanced age, and previous village leadership roles tend to decrease their inclination to buy forest insurance. Conversely, those who have undertaken personal preventive measures advocate for reducing forest insurance premiums to approximately USD 5.5/ha, in line with the findings in [62]. However, among those willing to purchase forest insurance, premiums of up to around USD $6.5/ha may be acceptable.
• Regarding participation and expected income of forest farmers transitioning to forest rangers: Forest farmers express the highest willingness to assume roles as forest rangers, particularly in regions heavily reliant on forested land on the western side, a notable discovery. The village committee significantly influences the organization of forest rangers, with forest farmers having a greater share of artificial forests at home, showing a propensity to become rangers, consistent with the findings in [43]. An innovative observation is the substitution relationship detected between assuming village cadres and becoming forest rangers, particularly in areas with significant forest pest prevalence on the western side, which diminishes farmers’ inclination to become rangers. Moreover, village cadres on the western side advocate for higher incomes for forest rangers. Under the village committee’s organization, forest farmers with higher education levels, a greater proportion of artificial forests at home, and larger forest pest areas at home tend to lower their salary expectations and may accept an income of approximately USD $190/month.

6. Recommendations

Previous research indicates that the average cost of forest pest control in China is approximately USD $115/ha [78]. In 2021, the premium for commercial forests was set at USD $5.08/ha, with forestry operators required to pay only USD $1.02/ha (20% of the total). However, surveyed farmers paid an average of USD $5.81/ha of the policy-stipulated amount. Forest rangers’ income can be either quarterly or annually, with a standardized system offering about USD $185 per month annually, supplemented by additional funds based on performance at the end of the year. While SPC costs may vary depending on tree species and regions, they generally align with what forest farmers can afford. However, due to regional differences, control measures’ difficulty, workload intensity, and forest attributes, the actual costs may surpass farmers’ capabilities, necessitating coordinated efforts by village committees and other government departments to supplement funds. The village committee can oversee the coordination of hiring SPC companies, selecting forest insurance, and appointing forest rangers. It is suggested that pest control companies be hired for households with extensive artificial forests, higher education levels, labor shortages, and weaker prevention capabilities, charging around USD $65 per hectare for their services.

Improvements to the forest insurance system should be made at the national and industry levels to raise awareness among forest farmers and village committees, with villagers paying USD $1.5 per hectare for insurance premiums. The remaining SPC and forest insurance costs will be covered by China’s central, provincial, and county-level finances and allocated to village committees. The government should ensure the full implementation of fiscal subsidies to reduce farmers’ insurance burdens, transparent compensation standards to enhance farmers’ understanding and trust in forest insurance, and the promotion of intensive management practices, encouraging optimized planting strategies and scale planning to lower insurers’ operational costs. To strengthen system efficiency, dedicated assessment officers will be appointed to standardize loss evaluations, and the claims processing workflows will be streamlined to improve timeliness. These integrated measures aim to boost participation incentives for both supply (insurers) and demand (farmers) sides [69].

Forest rangers should receive a minimum wage of USD $150 per month, funded by local finances. Rangers could be categorized into three levels: the first would target impoverished forest farmers with minimal educational requirements, ensuring basic wages for daily patrols. The second level would consist of young rangers from forestry households willing to take on supervision, management, and simple control operations, with a monthly performance subsidy of around USD $75 provided by the village committee. The third level would recruit professional pest control personnel from forestry colleges, ensuring a basic wage of USD $300 per month plus performance bonuses based on workload, while working alongside SPC companies. Second-level village forest rangers would oversee and manage SPC operations, ensuring a young and professional team to enhance efficiency and increase farmer participation.