Introduction

The imposition of a decade-long fishing prohibition on the Yangtze River constitutes a pivotal decision by the Central Committee of the Communist Party of China and the State Council.1 This decision is predicated on considering long-term strategic interests and the aspiration to secure a more prosperous future for posterity.2 It signifies a notable advancement in the conservation and administration of significant river systems.3,4 The “No. 1 Central Document” released in 2021 underscored the necessity of ensuring the effective enforcement of this extended fishing prohibition by providing requisite support to retired fishermen.5 Since the comprehensive rollout of the “ten-year fishing prohibition policy,” approximately 164,500 riverine fishermen requiring re-employment have been afforded necessary assistance, and around 221,800 eligible retired fishermen have been guaranteed access to insurance coverage.4 The policies facilitating the occupational transition for these fishermen integrate the principles of “supporting industries—supporting jobs—supporting entrepreneurship—providing safety nets.” This strategy augments their competitiveness in the job market and assists them in securing alternative means of livelihood.

As indigenous people in the Yangtze River basin, after fishermen come ashore, their livelihoods and environment undergo significant changes, and their adaptation to the new identity remains a work in progress. The fishing ban in the Yangtze River has resulted in fishermen losing their primary means of subsistence. During the transitional period between implementing the ban and shifting to alternative occupations, fishermen are particularly vulnerable to disruptions in their livelihood chain. Although various policy-driven economic compensations may provide short-term relief by partially substituting for former fishing incomes, this approach is unlikely to ensure long-term sustainability due to a lack of viable livelihood options. An indigenous problem is that relying solely on post-ban economic subsidies may not be sufficient for retired fishermen to maintain a sustainable living, potentially exacerbating conflicts with the ecological environment. Therefore, there is an urgent need to identify a livelihood transformation approach that facilitates simple operations to help fishermen quickly restore their livelihoods and minimize environmental energy consumption. The merits of engaging in ecological farming livelihoods are evident in their minimal capital investment prerequisites, high potential for sustainability, and suitability for fishermen characterized by advanced age and lower educational attainment.1,6 Such initiatives expedite the improvement of fishermen’s adaptability and foster rural revitalization and wealth creation within fishing communities.

Additionally, they can convert adverse environmental impacts into positive ecological outcomes, thereby propelling eco-friendly development. According to ongoing research tracking the effects on Yangtze River fishermen, government initiatives are concentrated on uncovering inherent potentials within the agricultural and fisheries sectors.7 Specific policy incentives are provided for those inclined to transition into ecological farming practices, including provisions regarding land contracting or transfer arrangements. Furthermore, financial incentives such as adjusted guarantee conditions and interest subsidies are extended.8,9 Through the promotion of agricultural entities, the reinforcement of production enterprises, the creation of distinctive brands, and other strategies,10,11 the advancement of ecological farming practices is being comprehensively pursued while exploring applications for these models within programs aimed at transitioning retired fishermen into new employment opportunities.

Acceptance challenges are particularly pronounced among individuals with limited risk tolerance, whose objective resource allocations, policy awareness, and information acquisition capabilities constrain their future livelihood decisions. The technical threshold inherent in ecological farming further complicates matters, as it necessitates a comprehensive application of fertilization and pest control techniques. The stress induced by fishery bans, coupled with unfamiliarity with policies and skill deficits, can result in extended psychological adjustment periods for fishermen. A deficiency in confidence regarding career transitions often impedes effective engagement with ecological farming models and reduces their inclination for sustained participation. The livelihood status of fishermen is contingent upon the extent of external disturbance pressures and their personal resilience and capacity for recovery from resultant adversities. Livelihood resilience pertains to the aptitude of individuals to sustain and enhance their livelihood well-being amidst external interventions.12 As an integral component of sustainable livelihood theory,13 it concentrates on the dynamic evolution process and mechanisms of livelihoods, emphasizing farmers’ strategic utilization of limited resources to adjust and adapt to external disturbances. This theoretical framework provides a foundation for the sustainable development of farmers’ livelihoods and is extensively utilized in investigating rural poverty.14 The theoretical framework of livelihood resilience can be categorized into three primary groups: a singular framework centered on the relationship between livelihood capital formation and community disaster recovery,15 a multidimensional analysis framework emphasizing resilience and adaptability,16 and a comprehensive analysis framework encompassing buffering, self-organization, and learning capabilities.17 The application of the livelihood resilience theory is predominantly in the domains of environmental protection and rural poverty alleviation, including assessments of livelihoods in the context of poverty alleviation relocations,8 measurements of farmers’ livelihoods in impoverished areas,18 and examinations of the factors influencing multidimensional poverty.19 In this study, livelihood capital is utilized as the primary indicator of buffering ability, and the framework is constructed from the perspectives of the actors themselves and their interactions with social organizations, thereby establishing a livelihood resilience assessment system that emphasizes buffering ability, self-organization ability, and learning ability.20 Given that fishermen’s willingness to engage in farming is influenced by various factors such as capital, policy, and society, livelihood resilience can more profoundly elucidate the multifaceted determinants of their choices and reflect the dynamic impact of structural disparities on their willingness to adopt. The perception of high-value ecological farming can potentially alter individuals’ behavioral states. Fishermen are pivotal participants in the selection of livelihood strategies and engagement in farming practices. Consequently, it is imperative to enhance individuals’ perceptions of ecological farming. The internal transformation of fishermen’s perceptions regarding ecological farming can externalize their participation in standardized cultivation and large-scale aquaculture endeavors. Through this approach, they can diversify their livelihoods, augment their adaptability and transformative capacities, and bolster their resilience against risks. Therefore, adopting fishermen’s livelihood resilience as a focal point holds practical significance in determining whether resilience (buffering-self-organization-learning) influences fishermen’s intentions to adopt farming practices, and in promoting the further application and dissemination of this model.

Using existing resources, as elucidated by Zheng et al.21 and Wu et al.,22 encompasses four principal dimensions: technological investment, information exchange, social relations, governmental support, and transformation opportunities. Scholarly inquiries have delved into the determinants of the adoption intention for ecological farming, focusing on the facets of livelihood capital, neighborhood communication, information exchange, and skill acquisition. Liu et al.23 discerned that the extent of capital owned by farmers exerts a significant influence on their ecological intentions and behaviors. Wang et al.,24 through an analysis centered on the triad of “information capability-perceived ease-farming willingness,” ascertained that farmers’ information capability bears a significant positive correlation with their inclination towards farming. Furthermore, Liu et al.23 identified that observational learning within the community and the sentiments engendered by communication can markedly and positively augment farmers’ readiness to embrace integrated planting and breeding technologies.

Additionally, Zheng and Liu25 highlighted that the subjective psychological element of policy cognition can substantially heighten rural residents’ inclination towards agricultural production. The construct of livelihood resilience pertains to individuals’ capacity to leverage inherent resource endowments to mitigate the effects of external disturbances. This entails the utilization of self-organization and learning competencies to devise adaptive strategies that sustain or elevate prevailing livelihood standards.4 While safeguarding livelihood capital, this approach also acknowledges the subjective agency of fishermen, thereby remedying deficiencies in extant research. Consequently, integrating livelihood resilience into examining fishermen’s willingness to adapt to fishing restrictions along the Yangtze River offers a more comprehensive elucidation of the formation logic behind this willingness to adapt. Prevailing studies have predominantly concentrated on the isolated influence of various conditions on the adoption intention of ecological farming, with scant consideration given to the amalgamation of subjective and objective conditions. Given its complexity, the ecological cultivation inclination of retired fishermen necessitates contemplating the synergistic effect of multiple variables across diverse competencies and levels. Traditional regression analysis, which scrutinizes the isolated effects of individual variables or, at best, the mediating effects of three variables, proves inadequate for explicating the intricacies of ecological farming inclination. The fuzzy set qualitative comparative analysis (fsQCA) methodology, grounded in a holistic analysis of multifactorial configurations, emerges as an efficacious tool for investigating complex, asymmetric, and multifactorial causal relationships. Necessary Condition Analysis (NCA) is specifically tailored to scrutinize necessary relationships and endeavors to rectify the limitations of the Fuzzy Set Qualitative Comparative Analysis (fsQCA) method in discerning essential conditions. Hence, NCA substantiates findings derived from conventional fsQCA necessity analyses. This study employs Necessary Condition Analysis (NCA) and Fuzzy Set Qualitative Comparative Analysis (fsQCA), predicated upon the analytical framework of livelihood resilience theory—encompassing “buffering, self-organization, and learning”—to investigate the configurations and mechanisms that engender regional disparities in fishermen’s inclination to adopt ecological farming. The research objectives are threefold: (1) To delineate the configurations of conditions that either foster or impede fishermen’s inclination to adopt ecological farming, achieving a common objective; (2) To ascertain whether there exist differentiated propelling pathways for fishermen’s inclination to adopt ecological farming across disparate regions; (3) Under specific conditions, to determine if there are equivalent combinations of conditions that can amplify fishermen’s adoption inclination.

Materials and Methods

Research methods: The combination of necessary condition analysis and qualitative comparative analysis of fuzzy sets

The Fuzzy Set Qualitative Comparative Analysis (fsQCA), is a research methodology that utilizes Boolean algebra and set theory to conduct comparative case analyses and ascertain the “synergistic effects” of interactions among multiple conditional variables on specific outcomes.26 The amalgamation of fuzzy sets with qualitative comparative analysis enables a more refined examination of variations in degrees or partial membership.27 Fuzzy Set Qualitative Comparative Analysis (fsQCA) permits a comprehensive examination of the driving pathways influencing fishermen’s inclination to embrace ecological farming practices. This methodology recognizes the complete equivalence of different antecedent configurations without requiring standardized treatment across varying levels of antecedent variables, rendering it appropriate for cross-level analyses as demonstrated in this paper.28 The Necessary Condition Analysis (NCA) is a novel research methodology founded on complex causal premises. It identifies the necessary conditions for outcomes and quantitatively assesses the effect size of these essential conditions and evaluates the magnitude of bottlenecks that constitute necessary conditions.29

Theoretical perspectives and research frameworks suggest that buffering, self-organization, and learning abilities synergistically influence fishermen’s inclination to embrace ecological farming practices, as their interconnected dynamics foster a multitude of concurrent causal relationships characterized by various logical combinations. Conventional regression analysis methods, which concentrate on linear causal relationships, are constrained in their capacity to clearly delineate the intricate configurational effects among antecedent factors.30 Fuzzy Set Qualitative Comparative Analysis (fsQCA) accentuates the configurations of antecedent conditions that result in particular outcomes, exhibiting features such as relational asymmetry, multiple equivalences, and causal complexity. Nonetheless, since fsQCA evaluates the necessity or sufficiency of antecedent conditions exclusively from a qualitative standpoint, it can impact identification precision. Although Necessary Condition Analysis (NCA) is limited to identifying necessary conditions, its methodology provides a greater depth and accuracy by quantitatively depicting “the extent to which a condition must be fulfilled to be deemed necessary for achieving a specific level of outcome,” thus effectively addressing the inherent limitations of qualitative comparative analysis.31 This paper adopts fuzzy-set qualitative comparative analysis (fsQCA) as the principal research method for examining sufficient conditions, while employing NCA as a supplementary approach to investigate the inclination of retired fishermen to adopt ecological farming models within the tripartite configurations of buffering, self-organization, and learning.

Figure 1
Figure 1.Research Framework

Data collection, measurement and calibration

Data collection

The dataset originates from the 2021 “tracking survey of fishermen impacted by the Yangtze River fishing ban.” The sample consists of 409 households of retired fishermen from 38 cities and counties in Sichuan, Chongqing, Hunan, Jiangxi, Anhui, and Jiangsu. Following the exclusion of incomplete questionnaires, 397 valid samples were procured, yielding an effective sample rate of 97.07%. The geographical distribution of the sampled fishermen is depicted in Table 1. As for the provincial distribution, the percentages are as follows: Hunan Province constitutes 18.89%, Jiangsu Province 27.21%, Jiangxi Province 11.84%, Anhui Province 13.85%, Sichuan Province 13.6%, and Chongqing City 14.61%. We employed SPSS to test the reliability and validity of the questionnaire data. The reliability analysis yielded a Cronbach’s α coefficient of 0.830, indicating high data reliability.

Table 1.Geographical Distribution of the Sample Fishermen
Provinces City/district/
county
Sample size Percentage(%) Provinces City/district/
county
Sample size Percentage(%)
Hunan
75
Yuanjiang 11 0.15 Jiangsu
108
Sihong 21 0.19
Hanshou 10 0.13 Xuyi 16 0.15
Xiangyin 9 0.12 Jingjiang 13 0.12
Anxiang 8 0.11 Yixing 11 0.10
Heshan 7 0.09 Wujiang 10 0.09
Taojiang 7 0.09 Jiangdu 9 0.08
Junshan 6 0.08 Wujin 8 0.07
Miluo 5 0.07 Hongze 7 0.07
Nan county 5 0.07 Jiangyin 7 0.07
Liuyang 4 0.05 Wuzhong 6 0.06
Linxiang 3 0.04 Jiangxi
47
Poyang 17 0.36
Chongqing
58
Yunyang 14 0.24 Duchang 14 0.30
Hechuan 12 0.21 Yugan 9 0.19
Jiangjin 10 0.17 Xinjian 7 0.15
Fuling 9 0.16 Anhui
55
Anqing 16 0.29
Yubei 8 0.13 Wuhu 15 0.27
Beibei 5 0.09 Huangshan 10 0.18
Sichuan
54
Fushun 37 0.69 Tongling 8 0.15
Ziyang 17 0.31 Chizhou 6 0.11

Regarding validity testing, the KMO value was 0.745, suitable for factor analysis. Bartlett’s test showed an accompanying probability value below the significance level (p<0.05), suggesting acceptable model data validity. Variance inflation factor tests were performed to avoid multicollinearity that could inflate standard errors associated with estimated parameters. The VIF values are ≤ 2.312, demonstrating no multicollinearity among variables, allowing for regression analysis to proceed effectively. Table 2 quantifies the correlation coefficients among various factors influencing fishermen’s inclination to adopt ecological farming practices. It indicates that all conditional variables significantly correlate with the outcome variable, corroborating our research hypotheses.

Table 2.Correlation factors influencing retired fishermen’s willingness to adopt ecological farming
Variables Willingness to adopt Livelihood capital Subsidy benefits Policy awareness Neighbourhood trust Technical training Information exchange
Willingness to adopt 1
Livelihood capital 0.257 ** 1
Subsidy benefits 0.344 ** 0.321 ** 1
Policy awareness 0.308 ** 0.209 ** 0.442 ** 1
Neighbourhood Trust 0.469 ** 0.312 ** 0.304 ** 0.230 ** 1
Technical Training 0.462 ** 0.238 ** 0.121 ** 0.220 ** 0.323 ** 1
Information Exchange 0.404 ** 0.224 ** 0.399 ** 0.309 ** 0.356 ** 0.275 ** 1

Note: ** means p<0.01, two-tailed test

Measurement and calibration

In the framework of fuzzy-set qualitative comparative analysis (fsQCA), each condition and outcome is denoted by a unique set, within which each case is endowed with membership scores across various sets.32 These membership scores are determined through a process known as calibration.33 Calibration can be classified into two distinct categories: direct and indirect. Direct calibration entails a structured assignment process that relies on predefined qualitative anchors, which include fully affiliated, completely unaffiliated, and the crossover point.34 Conversely, indirect calibration involves classifying cases based on their sample membership levels, with subsequent assignment of varying membership scores to optimize the analysis.33,35,36 According to the specific characteristics of variable types, direct calibration is applied to livelihood capital within the buffering ability of condition variables. In contrast, indirect calibration is utilized for outcome variables, such as fishermen’s inclination to adopt ecological farming practices, and condition variables including self-organization ability, learning ability in relation to subsidy benefits, policy awareness, neighborhood trust, technical training, and information exchange.

Outcome variable

The willingness of retired fishermen to adopt ecological farming practices is examined as the outcome. Based on the fishermen’s intentions regarding the adoption of ecological farming methods, the results are represented using fuzzy set membership scores: a score of “1” is assigned for “very willing,” “0.75” for “relatively willing,” “0.5” for “neutral towards adoption,” “0.25” for “not considering at this stage,” and a score of “0” for “unwilling to adopt.”

Condition variables

Buffering ability - livelihood capital. The direct calibration method was employed to assess and calibrate the results of the five capitals related to fishermen’s livelihoods. The standards used for this process were the 0.95 quantile (complete membership), the 0.5 quantile (threshold point), and the 0.05 quantile (complete non-membership). The procedure is as follows.

First, a livelihood capital index evaluation system was constructed, the evaluation index scores were assigned, and the entropy weight method was used to determine the index weights (Table 3).

Table 3.Retired fishermen’s buffering ability - evaluation index of livelihood capital
Target Layer Guideline layer Subguideline layer Index level Indicator meaning and score assignment Weight
Livelihood
resilience
Buffering
ability
Natural capital
(N)
N1 Aquaculture area of pond(mu) N1=0(1); 0<N1≤1(2); 1<N1≤3(3); 3<N1≤5 (4); N1>5 (5) 0.120
N2 Cultivated land and forest area (mu) N2=0(1); 0<N2≤1(2); 1<N2≤3(3); 3<N2≤5 (4); N2>5 (5) 0.143
Physical capital
(P)
P1 Types of household durable goods Types of household appliances, common or medium to large vehicles owned:
P1=0(1); P1=1(3); P1=2(5)
0.125
P2 Per capita residential area Ratio of residential area to household size:
P2 < 10 (1), 10≤P2 < 20 (2), 20≤P2 < 30 (3), 30≤P2 < 50 (4), P2≥50 (5)
0.070
Social capital
(S)
S1 Degree of familiarity with current neighbors after retiring Very unfamiliar (1); not very familiar (2); general (3); relatively familiar (4); very familiar (5) 0.065
S2 Number of contacts with government organizations after retiring Very few (1); less (2); general (3); more (4); a lot (5) 0.060
S3 Participation in community/village group activities Never participate (1); rarely participate (2); participate occasionally (3); regularly participate (4); always participate (5) 0.054
Financial capital
(F)
F1 Annual household income after retiring
(10,000 yuan)
F1<5 (1); 5≤F1<10 (2); 10≤F1<20 (3); 20≤F1<30 (4); F1≥30 (5) 0.109
F2 Financial Support
( the kind of insurance)
F2=0(1); F2=1(3); F2=2(5) 0.074
Human capital
(H)
H1 Education level Below primary school (1); primary (2); junior high school (3); high school (4); above high school (5) 0.091
H2 Number of labor force in households H2=0(1); 1≤H2≤2(2); 3≤H2≤4(3); 5≤H2≤6(4); H2≥7(5) 0.032
H3 Health status Frequent illness (1); occasional illness (2); rare illness (3); relatively healthy (4); very healthy (5) 0.057
  1. Based on the standardized value Rij (the score assignment of the JTH index of the i fisherman), the proportion of the unit i index value in the JTH index is calculated: Pij

    Pij=Rij/ni=1Rij

  2. Calculate the entropy value of the JTH index: ej

    ej=1/lnnni=1Pijln(Pij)

  3. Calculate the difference coefficient of the JTH index: gj

    gj=1ej

  4. Calculate the weight of JTH index: wj

    wj=1ej(gj)/mi=11ej(gj)

  5. Calculate the composite score of the i fisherman’s livelihood capital: si

    si=mi=1(Rijwj)

The direct calibration method established the thresholds for the comprehensive scores of fishermen’s livelihood capital, setting the 95th and 5th percentiles as fully affiliated (5.32) and completely unaffiliated (3.6). The score corresponding to the 50th percentile was designated as the crossover point (4.45) for calibration purposes. The measurement results are re-evaluated in the indirect calibration method based on qualitative assessments.34 Depending on the research question and substantial knowledge of data and fundamental theories, fuzzy set membership scores for five-point scale variables using the indirect calibration method,37 considering differences in data types among various variables and outcomes. Thresholds commonly employed include 0, 0.25, 0.5, 0.75, and 1.38 Results are presented in Table 4.

Table 4.Calibration of conditional variable data
Condition variables Indicator meaning Calibration results
Buffering ability Livelihood capital Livelihood capital composite score Fully affiliation (5.32); crossover point (4.45); completely unaffiliated (3.6)
Self-organization
ability
Subsidy
benefits
"Have you received the compensation for the vessel network certificate, transitional living allowances, pension and medical insurance subsidies and agricultural production (ecological farming) subsidies provided by the government?" "All" (1); "three kinds" (0.75); "two kinds" (0.5); " one kind" (0.25); "Neither" (0)
Policy
awareness
"How concerned are you about ecological compensation policies and agricultural production policies adopted by the government?" "Very concerned" (1); "somewhat concerned" (0.75); "fairly informed" (0.5); "occasionally attentive" (0.25); "never attentive" (0)
Neighbourhood trust "Will other retired fishermen in the fishing village engaging in ecological farming have a neighborhood effect on your livelihood choices?" "Very impactful" (1); "comparative impact" (0.75); "general" (0.5); "not much impact" (0.25);"not impact" (0)
Learning
ability
Technical training "How often do you participate in government-organized training on production techniques related to ecological farming?" "Always participate" (1); "frequently participate" (0.75); "occasionally participate" (0.5); "rarely involved" (0.25); "Never participate" (0)
Information exchange "How often do you exchange information with others, such as ecological farming technology and the price of agricultural products?" "Always Communicate" (1); "Frequently Communicate" (0.75); "Occasionally Communicate" (0.5); "Rarely Communicate" (0.25); "Never Communicate" (0)

Results

NCA necessary condition analysis

In the Necessary Condition Analysis (NCA) method, a condition is considered necessary for an outcome if the effect size (d) is not less than 0.1 and the Monte Carlo simulation permutation test indicates that the effect size is significant.39,40 Table 5 presents the results of effect sizes calculated using both CR and CE estimation methods. None of the six antecedent conditions simultaneously meet the effect size and significance requirements. Therefore, they are not deemed necessary for fishermen’s willingness to adopt ecological farming practices.

Table 5.Retired fishermen’s ecological farming willingness-analysis of necessary conditions for NCA method
Conditions Methods Effect Size (d) P value Precision Upper limit area
(ceiling zone)
Range
(scope)
Livelihood capital CR 0.010 0.039 99.30% 0.009 0.92
CE 0.016 0.014 100% 0.015 0.92
Subsidy benefits CR 0.000 1.000 100% 0.000 0.89
CE 0.000 1.000 100% 0.000 0.89
Policy awareness CR 0.000 1.000 100% 0.000 0.85
CE 0.000 1.000 100% 0.000 0.85
Neighbourhood trust CR 0.000 1.000 100% 0.000 0.85
CE 0.000 1.000 100% 0.000 0.85
Technical training CR 0.003 0.050 100% 0.003 0.85
CE 0.006 0.050 100% 0.005 0.85
Information exchange CR 0.011 0.245 100% 0.010 0.89
CE 0.022 0.245 100% 0.020 0.89

Note: 0.0≤ d < 0.1: “low level”, 0.1≤ d < 0.3: “medium level”, 0.3≤ d < 0.5 or d≥ 0.5: “high level”.

Table 6 further reports on the calculation results of bottleneck levels. The “bottleneck level” refers to a specific threshold within which certain values (%) must be achieved to achieve a particular level of overall observed outcomes.31,41 For instance, to reach 90% of fishermen’s willingness to adopt ecological farming practices within the observation range, it requires a livelihood capital level of 3.0%, technical training at 6.1%, and information exchange at 7.2%. The other three antecedent conditions do not exhibit any bottleneck levels.

Table 6.Bottleneck level (%) analysis of NCA method
Fishermen's willingness to adopt ecological farming Livelihood capital Subsidy benefits Policy awareness Neighbourhood trust Technical training Information exchange
0 NN NN NN NN NN NN
10 NN NN NN NN NN NN
20 NN NN NN NN NN NN
30 NN NN NN NN NN NN
40 NN NN NN NN NN NN
50 0.0 NN NN NN NN NN
60 0.8 NN NN NN NN 1.4
70 1.5 NN NN NN NN 3.6
80 2.3 NN NN NN 5.4 NN
90 3.0 NN NN NN 6.1 7.2
100 3.8 NN NN NN 8.3 9.8

Note: upper limit regression analysis CR; NN= unnecessary.

QCA Necessary condition analysis

The qualitative comparative analysis (QCA) method is to examine whether individual condition variables, including their logical negations, constitute necessary conditions for the willingness of retired fishermen to adopt ecological farming practices.42 The degree of consistency in fuzzy sets is selected as the measurement criterion for necessity, with the calculation formula presented as follows:

Consistency ((XiYi)=[min(Xi,Yi)]/(Xi)

In equation 6, Xi and Yi are the membership degrees of individual i in combinations X and Y respectively, and the consistency value ranges from 0 to 1. When the consistency exceeds 0.9, it is deemed that this condition is a necessary condition for the outcome.35,43 Table 7 presents the results of calculating the required conditions for fishermen’s willingness to adopt ecological farming based on fsQCA 3.0. It can be observed that all conditions exhibit a consistency lower than 0.9, which aligns with the findings from NCA analysis, indicating that there are no necessary conditions influencing fishers’ willingness to adopt ecological farming practices following fishing bans.

Table 7.Analysis of necessary conditions for QCA method
Condition variable Retired fishermen have strong willingness to adopt ecological farming Retired fishermen have weak willingness to adopt ecological farming
Consistency Coverage Consistency Coverage
Subsistence capital 0.520 0.560 0.628 0.622
~ Livelihood capital 0.649 0.655 0.556 0.516
Subsidy benefits 0.603 0.621 0.601 0.569
~ Subsidy benefits 0.582 0.613 0.599 0.581
Policy awareness 0.693 0.605 0.732 0.587
~ Policy awareness 0.527 0.681 0.507 0.603
Neighbourhood trust 0.553 0.581 0.624 0.603
~Neighbourhood Trust 0.622 0.643 0.566 0.538
Technical Training 0.459 0.541 0.588 0.637
~ Technical Training 0.692 0.646 0.576 0.495
Information exchange 0.851 0.553 0.886 0.530
~Information Exchange 0.277 0.725 0.253 0.609

Note: ~ indicates non- logical.

Conditional configuration adequacy analysis

The sufficiency of configurational conditions is the core discussion of the fsQCA method.44 From a set-theoretic perspective, it explores whether the configuration represented by multiple conditions constitutes a subset of the outcome set. When selecting consistency to measure the sufficiency of configurations, the sufficiency level should not be lower than 0.75.29,32 The sample size determines the assignment of frequency thresholds. The frequency threshold is set at 1 for small to medium samples, while for large samples, it should exceed 1.45 Considering both sample size and case arrangement in the truth table, we selected a consistency threshold of 0.80 and a frequency threshold of 2.

The outcomes of the fuzzy-set qualitative comparative analysis (fsQCA) present three solution types, each with its own level of complexity: complex solutions, parsimonious solutions, and intermediate solutions.41 Typically, contemporary research tends to report on intermediate solutions, while delineating core conditions from peripheral conditions in tandem with parsimonious solutions. Conditions that manifest in both the parsimonious and intermediate solutions are designated as core conditions. Conversely, those exclusive to the intermediate solution are categorized as peripheral conditions.46The configuration analysis results regarding fishermen’s willingness to adopt ecological farming are presented in Table 8.

Table 8.Capacity configuration of retired fishermen’s willingness to adopt ecological farming
Fishermen’s strong willingness to adopt ecological farming Fishermen’s weak willingness to adopt ecological farming
Self-organization
Dominant
Self-organization - Learning
Driven
Buffering - Learning
Driven
Learning
Inhibition
Self-organization - Learning
Inhibition
Buffering - self-organization Inhibition
Conditional Configuration Configuration 1 Configuration 2 Configuration 3 Configuration 4 Configuration 5 Configuration 6
Livelihood Capital
Subsidy benefits
Policy awareness
Neighborhood trust
Technical training
Information exchange
Consistency 0.785 0.803 0.792 0.816 0.798 0.837
Raw coverage 0.284 0.252 0.309 0.190 0.167 0.231
Unique coverage 0.077 0.116 0.140 0.076 0.080 0.152
Consistency of solution 0.771 0.793
Coverage of solution 0.623 0.656

Note: ● or ● if the condition exists, ⊗or⊗ if the condition does not exist; ● or ⊗ is the core condition, and ● or ⊗ is the edge condition. Blank indicates that the condition can be present or absent.

Configuration (path) with a strong willingness of fishermen to adopt ecological farming

Table 8 presents three driving pathways for fishermen’s willingness to adopt ecological farming. The consistency levels of both individual and overall solutions exceed 0.75, with the overall solution demonstrating a consistency of 0.771. This indicates that in cases where retired fishermen are strongly willing to engage in ecological farming, 77.1% express such intentions post-retirement from fishing. The coverage of the overall solution is 0.623, signifying that these three conditional configurations can explain 62.3% of the cases characterized by a strong willingness to adopt ecological farming among fishermen. These three configurations as sufficient combinations of conditions for fostering a robust willingness among fishermen towards ecological practices in farming. Based on these conditional configurations, further identification reveals differentiated pathways influenced by buffering, self-organization, and learning regarding fishermen’s willingness to adopt ecological farming.

  1. Self-organization is dominant. Configuration 1 elucidates the pivotal role played by subsidy benefits and policy awareness. In the context of fishermen’s inclination to embrace ecological farming practices, heightened policy awareness and a perception of governmental subsidies can surmount the constraints imposed by buffering and learning conditions. The instances elucidated by configuration 1 predominantly cluster in counties situated along the lower reaches of the Yangtze River and in comparatively developed eastern counties. These areas extend subsidies to retired fishermen per criteria applicable to land-lost farmers,5 while also committing substantial resources to promoting agricultural technology and policy advocacy, thereby augmenting fishermen’s comprehension of ecological farming. As a representative region, Jiangsu Province boasts a considerable cohort of retired fishermen and significant retirement obligations. Initially, during the inception of fishing bans, fishermen generally endorsed the prohibition of fishing in key areas of the Yangtze River. Still, they were deficient in requisite knowledge about agricultural production support policies and ecological farming assistance programs. Local governments have augmented fishermen’s awareness of environmental farming through promotional endeavors centered on reward-and-subsidy policies. The consistency for this pathway configuration is 0.785, with unique coverage at 0.077 and raw coverage at 0.284. This signifies that this pathway can account for approximately 28.4% of instances where fishermen exhibit a robust willingness. Moreover, approximately 7.7% of instances wherein fishermen are inclined to engage in ecological farming can exclusively be attributed to this pathway.

  2. Self-organization-learning driven. In Configuration 2, the pivotal role is played by neighbourhood trust, with subsidies benefits and information exchange serving as supplementary factors. The cases elucidated by this conditional configuration predominantly concentrate on remote fishing villages situated in the western regions of China and the upper reaches of the Yangtze River. These villages are frequently situated in geographically isolated areas, characterized by relatively weak foundations for aquaculture production, coupled with limited government support coverage,47 which somewhat impedes the dissemination of ecological farming models. Neighborly interaction and shared communication have become essential conduits for fishermen to acquire information. Thus, their interactive networks constitute critical social capital for the survival and development of mobile populations within these villages. Fishermen endowed with robust social trust may be influenced by their peers to enhance their willingness to adopt ecological farming, thereby generating a neighbor effect. For example, fishermen from County F in Sichuan Province mentioned that after ceasing fishing activities, they learned from local fishermen about job opportunities at an integrated rice-fish farming demonstration base where they could earn wages and receive industry dividends at year-end. The concept of “medium rice + regenerated rice” can be succinctly described as “one crop, two harvests.” Following the harvesting of the main crop of rice by the end of July each year, the dormant axillary buds on the stubble can regenerate under specific conditions. Approximately two months later, these buds will develop into panicles, facilitating an additional harvest. The former refers to medium rice, while the latter is referred to as regenerated rice. Owing to the capacity of “medium rice + regenerated rice” to enhance the cropping index and stabilize the overall yield of rice, this area promotes a “medium rice + regenerated rice + fish” green ecological farming model that aids fishermen in transitioning towards environmentally sustainable practices while achieving collective prosperity. In H District of Chongqing City, initiatives promoting simultaneous rice-shrimp cultivation have been implemented to augment fishermen’s incomes. Capitalizing on high-standard farmland construction opportunities, this district has actively developed 23,000 acres dedicated to rice-shrimp farming involving 46 major operators. After retiring from fishing activities, local fishermen can join village cooperatives to access relevant information and assist during peak production periods. The consistency score for this driving path configuration is 0.803 with an original coverage rate of 0.252; it accounts for approximately 25.2% of cases demonstrating a strong willingness among fishermen to adopt ecological farming.For instance, Bangladesh has actively promoted integrated agri-aquaculture systems. In the Ganges-Brahmaputra Delta, local fishers utilize seasonal monsoon floods for rice-fish co-cultivation, transitioning to vegetable farming during the dry season. Non-governmental organizations (NGOs) provide cooperative training for fishers and facilitate microfinance initiatives to support eco-friendly aquaculture practices.

  3. Buffering-learning driven. In Configuration 3, the pivotal roles are occupied by livelihood capital and technical training, with information exchange acting as a complementary function. In areas where fishermen have a higher level of livelihood capital, even with low policy awareness and diminished trust in external entities and government subsidies, supportive learning conditions can still motivate fishermen to actively respond to external disruptions and increase their inclination to seek employment. The consistency of this configuration is 0.792, with an original coverage rate of 0.309. Examples that can be elucidated by Configuration 3 encompass the three provinces along the Yangtze River’s middle reaches: Hunan, Jiangxi, and Anhui. Initially, this region possesses significant natural advantages. The middle reaches of the Yangtze River constitute a primary production base for staple grains in China, endowed with abundant water resources and favorable climatic conditions for agricultural production, owing to concurrent rainfall and heat.2 The proportion of individuals transitioning into other forms of employment who were previously engaged in farming exceeds 60%. Secondly, government initiatives to augment fishermen’s capital endowments protect their productive activities. This includes optimizing service systems to enhance both material and financial capital for fishermen48—such as acquiring agricultural machinery, upgrading basic irrigation infrastructure in fishing villages, providing direct financial subsidies, and offering credit support. Moreover, efforts are made to enhance technical training for fishermen to elevate human capital levels through disseminating knowledge on production operations and refined management practices. Community organizations also play a vital role by establishing cooperatives or mutual aid groups that connect social capital with ecological farming interests among fishermen.9 This reduces information costs while increasing organizational capacity within these communities. For example, the “Encouraging Ecological Practices” initiative necessitates a combination of rich natural assets alongside robust infrastructure and proficient collaborative techniques. Given that retired fishermen often encounter challenges such as lower educational attainment or slower skill acquisition rates post-retirement from fishing activities, active participation in ecological cultivation technology training becomes crucial for enhancing operational skills. As a representative case study: County N in Hunan invited experts to deliver lectures on aquaculture knowledge while exploring digital empowerment strategies using new media platforms like big data to facilitate learning among local fishermen.2 In B Township of Anhui Province, training methods integrated indoor technical instruction with on-site guidance. Experts initially provided explanations on livestock and poultry farming, disease prevention, and the techniques for mugwort cultivation.49 They distributed technical guidance manuals and promoted policies to support fishermen. Subsequently, they led the fishermen in hands-on practice in the fields. Meanwhile, Y County’s government in Jiangxi has integrated retired fishermen into community management frameworks while coordinating education, health care services alongside housing security measures, which collectively enhance their livelihood capitals. On the other hand, fishermen have proactively engaged in learning courses on eel farming and Ganpo mushroom cultivation,50 thereby enhancing their willingness to adopt ecological practices in agriculture and aquaculture. In Vietnam, fishers have adopted rice-fish integrated farming, particularly in the Mekong Delta region, where technically skilled fishers combine rice cultivation with aquaculture to establish a circular ecosystem, thereby reducing reliance on chemical fertilizers and pesticides. Additionally, some fishers with stronger adaptive livelihoods have diversified into eco-tourism services, showcasing traditional fishing culture or offering recreational angling experiences.

Configuration (Path) of fishermen’s weak willingness to adopt ecological farming

As depicted in Table 8, three distinct pathways culminate in the observed outcomes. Each path, along with the aggregate consistency of the solutions, surpasses 0.75, signifying that the antecedent variables possess a robust explanatory capability for the results. Furthermore, the aggregate coverage rate is 0.656, indicating that these configurational pathways elucidate 65.6% of the cases. Drawing upon the core conditions encapsulated within these pathways, the three identified types influencing fishermen’s diminished inclination to embrace ecological farming are: learning inhibition (Configuration 4), self-organization—learning inhibition (Configuration 5), and buffering—self-organization inhibition (Configuration 6).

An examination of these three categories reveals that buffering, self-organizational, and learning abilities are pivotal constraints that influence retired fishermen’s inclination to participate in ecological farming. Initially, a substantial base of livelihood capital is essential for augmenting the propensity for ecological farming adoption. The absence of adequate human, physical, social, financial, and natural capital resources among fishermen significantly heightens their vulnerability.20 This resource reduction undermines their confidence in pursuing ecological farming for livelihood advantages. Subsequently, self-organizational ability is pivotal in establishing subjective intentions towards ecological farming among fishermen. When self-organizational abilities are diminished, reliance on a diverse array of government incentive policies may be necessary to stimulate fishermen’s willingness to adopt ecological farming. Concurrently, within the context of interactions involving institutional policies and social networks, should fishermen find it challenging to enhance their motivation for technology adoption through spontaneous or collective actions, their self-organizational abilities will be insufficient in reinforcing their inclination towards ecological farming. Learning ability is crucial for fostering farmers’ willingness to adopt eco-friendly farming methodologies. It also serves as a prerequisite for engaging in such agricultural models. Should fishermen demonstrate a lack of initiative in learning or possess inadequate information literacy skills, it becomes arduous for them to cultivate intrinsic motivations towards adopting ecological farming practices.

Potential substitution relationship between conditions

The comparative analysis of condition configurations 1-3 allows for the further identification of potential substitutive relationships among buffering, self-organization, and learning abilities. Firstly, by comparing condition configurations 1 and 2, in regions where fishermen have a higher sense of entitlement to ecological farming subsidies, the level of policy awareness among fishermen (self-organization) can substitute for the combination of neighborly trust (self-organization) and information exchange (learning), as illustrated in Figure 2. Secondly, the comparison between condition configurations 2 and 3 indicates that in areas with strong information exchange capabilities and high levels of information literacy among fishermen, the combination of subsidy benefits perceived by fishermen (self-organization) and neighborly trust (self-organization) can serve as a substitute for the combination of livelihood capital accumulation (buffering) and proactive technical training engagement (learning), thereby enhancing fishermen’s willingness to engage in ecological farming, as shown in Figure 3.

图片1
Figure 2.Substitution Relationship between Self-organizing Capacity and “Self-organizing + Learning”
图片2
Figure 3.Substitution Relationship between Self-organizing Capacity and “Buffering + Learning”

The potential substitutive relationship among buffering, self-organization, and learning conditions indicates that under specific circumstances, the capacity for self-organization can exert effects typically associated with the combination of the other two abilities, as illustrated in Figures 2 and 3. The interdependence and complementarity of three conditions—subsidy benefits, policy awareness, and neighborhood trust—synergistically explain outcomes.

Fishermen procure technical and policy-related information via governmental promotional initiatives and community engagement efforts,51 thereby establishing their foundational comprehension of production methodologies and subsidy frameworks. This comprehension is subsequently molded by their assessment of the perceived advantages conferred by subsidies and the insights imparted by friends or kinfolk concerning the risks and rewards inherent in these models. As a result, they evaluate the applicability and sustainability of ecological farming technologies to ascertain their inclination towards adopting such practices.

Figure 2 elucidates that heightened awareness of agricultural policies is positively associated with increased governmental dedication to enacting these policies. Consequently, this heightened awareness increases farmers’ satisfaction with the policies and a greater inclination to adopt ecological farming technologies. In contrast to the unilateral decision-making process that is often based on individual perceptions among fishermen, the establishment of trust between neighboring fishers significantly bolsters confidence in the adoption of ecological farming methodologies. To some extent, a significant level of information transparency and trust among fishermen can reduce risk perceptions and foster consensus regarding livelihood choices.23 Figure 3 delineates that fishermen engage in ecological farming through two distinct approaches: “social partnership” or “independent contracting.” The “social partnership” model necessitates the active involvement of governments in various aspects, such as policy support, financial resources, technology transfer, etc., to encourage selected fishermen to spearhead efforts in ecological farming. Those who achieve higher yields disseminate their experiences to others, thereby expanding the demonstration effects and facilitating the establishment of “catch-to-culture” production bases while exploring partnerships that involve “base + retired fishers.” Conversely, the “independent contracting” approach is employed when fishermen leverage buffering and learning abilities to compensate for the insufficient self-organizational capacity to enhance interest in ecological farming practices. Sufficient livelihood capital provides an objective foundation for engaging in ecological farming and partially addresses gaps resulting from weak perceptions regarding subsidy benefits.

Additionally, acquiring knowledge about pond disinfection techniques, seedling selection, feed management, and disease prevention strategies effectively enhances farmers’ comprehension of eco-friendly practices while mitigating constraints imposed by inadequate neighborly influence. Fishermen independently utilize natural water surface contracts alongside land cultivation techniques for rice-shrimp/rice-fish entrepreneurial ventures. Both pathways ultimately converge to increase farmers’ willingness to adopt sustainable practices.

Discussion and Conclusion

Yangtze River retired fishermen typically exhibit characteristics of diminished livelihood capital, including “advanced age, limited educational attainment, and absence of land or alternative skills.” Having traditionally depended on aquatic resources, these individuals often possess survival skills to their fishing expertise.43 To mitigate the risks associated with their livelihoods, they tend to seek employment primarily in agriculture, forestry, animal husbandry, and fishery.52 Ecological farming not only aids in poverty alleviation and wealth creation for these fishermen but also represents a sustainable and circular low-carbon production model that can yield benefits for both ecological conservation and economic development. Consequently, local governments throughout China encourage fishermen to explore new avenues towards higher-quality employment while enhancing ecological benefits. With supportive conditions, a concerted effort is to promote the development of integrated environmental farming systems within these communities.

To further investigate the impact of livelihood resilience on the willingness of retired fishermen to adopt ecological farming practices, this study examines variations among different groups of fishermen characterized by distinct attributes and regions with varying levels of economic development. Specifically, a heterogeneity analysis from two perspectives: generational differences and regional economic development levels. According to generational difference theory, fishermen at various age stages exhibit differences in values, knowledge, skills, and physical capabilities. These differences may influence how livelihood resilience affects the willingness of retired fishermen to adopt ecological farming practices. Therefore, based on the age differences among households and actual samples of fishermen, those born before 1980 with an education level up to junior high school are categorized as the “older generation” group; all other samples are classified as the “younger generation” group for our analysis. Secondly, regions with varying levels of economic development display differences in living standards and labor market activity. Such differences can also affect how livelihood resilience influences retired fishermen’s willingness to adopt ecological farming practices. Consequently, based on regional economic development disparities—specifically whether local per capita GDP exceeds that year’s average per capita GDP in China—we classify samples above this mean into a “high economic development region” group and those below it into a “low economic development region” group for our analysis.

Additionally, considering that sample sizes after grouping may be relatively small, potentially impacting parameter estimates’ accuracy, this study employs Bootstrap methods for repeated sampling alongside OLS estimation techniques for regression analysis. The control variables in this study encompass individual, family, and regional factors. The separate control variables include age and gender, while the family control variables comprise the proportion of labor force participation and the dependency ratio. The regional control variable pertains to the level of economic development (see Tables 9 and 10).

Table 9.Regression results on the impact of livelihood resilience on ecological farming willingness among retired fishermen from the perspective of intergenerational differences
Variables Ecological farming willingness
The groups of new-generation retired fishermen The groups of older-generation retired fishermen
Livelihood resilience 0.0514 0.5237***
(0.0403) (0.0315)
Control variables Controlled Controlled
County and district level fixed effects Controlled Controlled
Observation index 102 295

Note: 1. *** indicates a significance level of 1%. 2.The values in parentheses represent robust standard errors.

Table 10.Grouped regression results of regional economic development disparities
Variables Regions with high economic development levels Regions with low economic development levels
Livelihood resilience 0.0982 0.3527***
(0.0409) (0.0326)
Control variables Controlled Controlled
County and district level fixed effects Controlled Controlled
Observation index 118 279

Note: 1.*** indicates a significance level of 1%. 2.The values in parentheses represent robust standard errors.

Table 9 reports the regression results regarding the impact of livelihood resilience on the ecological farming willingness of retired fishermen, categorized as either new-generation or old-generation groups. It is evident that, in contrast to the new-generation fishermen who are not significantly affected, livelihood resilience has a significant positive effect on the willingness of old-generation fishermen to engage in ecological farming at a 1% statistical level. This suggests that livelihood resilience primarily influences the adoption intentions among retired fishermen belonging to the older generation. A possible explanation for this phenomenon is that older fishermen often face limitations such as inadequate knowledge and skills and lower cultural literacy levels compared to their younger counterparts. Additionally, they tend to have a stronger attachment to their local communities. Under these dual constraints—capability and emotional ties—older fishermen encounter substantial challenges in accessing development opportunities. Furthermore, factors such as declining physical strength and health issues may hinder their ability to participate in agricultural labor production. Therefore, enhancing livelihood resilience can give them greater confidence in employment opportunities.

Table 10 reports the regression results regarding the impact of livelihood resilience on the ecological farming willingness of retired fishermen in regions with high and low economic development levels. It is evident that, unlike the unaffected group in high economic development areas, livelihood resilience significantly influences the ecological farming willingness of retired fishermen in low economic development areas at a 1% statistical level. This suggests that livelihood resilience has a more pronounced effect on this demographic within lower economic contexts. A possible explanation for this phenomenon is that in regions with higher economic development, retired fishermen benefit from improved living standards and an active labor market, which enhances their capacity to adapt. Conversely, even if fishermen possess a strong desire for growth in areas with lower economic development levels, they often find themselves trapped in relative poverty due to a lack of adaptive policies, developmental opportunities, and geographical constraints. The government’s implementation of diversified ecological compensation measures bolsters their livelihood resilience and addresses these fishermen’s developmental needs while facilitating better opportunities for re-employment.

This investigation examines the inclination of retired fishermen from representative provinces along the Yangtze River to engage in ecological farming after implementing a fishing moratorium, utilizing fsQCA to analyze conditional configurations. It delves into the interplay of six conditional variables—namely, livelihood capital, subsidy benefits, policy awareness, neighborhood trust, technical training, and information exchange—on the willingness of these fishermen to embrace an “ecological farming” lifestyle. The study uncovers the central conditions and intricate mechanisms that shape fishermen’s intentions to adopt ecological farming. The research culminates in the following conclusions:

  1. The necessity analysis conducted through NCA and fsQCA demonstrates that buffering, self-organization, and learning abilities, in isolation, are insufficient to yield explanatory outcomes. This implies that individual conditions do not restrict fishermen’s inclination towards “ecological farming”. A pronounced propensity for ecological farming is fostered through three distinct avenues: a self-organization-dominant pathway, a self-organization and learning-driven pathway, and a buffering and learning-driven pathway. The inclination of fishermen towards ecological farming emerges due to the combined influence of multiple conditions, where various variables interact to forge paths towards adoption, with different approaches converging towards analogous outcomes. In particular scenarios, an increased focus by fishermen on ecological farming policies positively correlates with the extent to which subsidy resources benefit them. The synergy of these two factors can surmount the constraints imposed by buffering and learning elements, thereby augmenting fishermen’s inclination to adopt such practices. When self-organizational ability is constrained, enhancements in fishermen’s livelihood capital, encouragement to actively participate in government-organized training programs, and reinforcement of information communication can also collaboratively augment their inclination.

  2. The relationship between fishermen’s robust and feeble inclinations to adopt ecological farming exhibits causal asymmetry. Three categories of driving factors contribute to fishermen’s tepid adoption inclination regarding ecological farming: inhibition of learning ability, inhibition of self-organization and learning ability, and inhibition of buffering and self-organization ability. A comparison of these three driving types reveals that buffering ability, self-organization ability, and learning ability are all critical constraints on the inclination of retired fishermen to engage in ecological farming.

  3. The potential substitutive relationship among buffering, self-organization, and learning conditions indicates that the three conditions under self-organizational ability play a more significant role. However, under specific circumstances, self-organizational ability can equivalently substitute for the conditions of the other two abilities in a manner that enhances fishermen’s inclination to adopt through a “different paths leading to the same destination” approach.

  4. As rational economic agents, fishermen are direct stakeholders in policies concerning fishing bans. When ecological farming presents environmental and financial benefits, fishermen may contemplate transitioning towards ecological farming to maximize their gains. Consequently, the government underscores the development of new pathways for environmental farming. In various contexts, the impact of livelihood resilience on the inclination of fishermen in the Yangtze River Basin of China to adopt ecological farming primarily concentrates on two groups: the older generation of fishermen and those from regions with lower economic development levels.

Based on the conclusions drawn above, we can derive the following insights.

The “visible hand” service function should employ a range of communication channels, including informational brochures, flyers, and television broadcasts, to enhance the promotion of aquaculture policies. This will improve fishermen’s foundational comprehension of these initiatives. Concurrently, it is imperative to concentrate on elucidating critical elements of particular concern to fishermen, such as subsidy ratios and methodologies. Moreover, providing consumption credit loans and interest subsidies for those actively engaging in ecological farming is essential. This ensures that fishermen can participate in these activities with confidence and security.

Furthermore, the potential interplay among buffering, self-organization, and learning underscores the indispensable nature of these three abilities for the willingness of fishermen. It is necessary to augment fishermen’s livelihood capital and fully utilize the synergistic effects of their existing capital endowments. Incentive measures to guide fishermen in achieving a rational allocation of capital factors pertinent to their willingness to engage in ecological farming. Refining subsidy programs for aquaculture by considering a blend of one-time and annual subsidies, as well as direct and indirect support during implementation, is crucial. This approach will enhance the perceived benefits of policies while focusing on incentive policies that ensure momentum for ecological farming. Fishermen must overcome passive attitudes such as “going through the motions” or reliance on others. They must shift their mindset and actively engage with various government policies and news releases, enhancing their awareness.

Additionally, they should proactively expand their local social networks and community interactions to strengthen neighborhood effects. Moreover, training content should be accessible while being flexible regarding timing, location, and format. This will increase fishermen’s interest in learning. Strengthening information network infrastructure is vital for broadening access opportunities related to ecological farming. Fishermen can quickly acquire comprehensive information by actively participating in village-level exchange meetings and listening to experience-sharing sessions from demonstration households engaged in sustainable practices.

Lastly, the governments of provinces along the Yangtze River should formulate supportive policies for ecological farming based on their specific circumstances and the reasonable demands of local fishermen, adopting a “localized” approach. Moderately enhancing the government’s environmental compensation policy can improve the precision of promoting the willingness of retired fishermen in the Yangtze River Basin to adopt ecological farming practices. In economically underdeveloped areas that were previously impoverished, it is essential to focus on developing green ecological industries based on local natural resource endowments, thereby driving employment and skills training for the local population. Regarding subsidies, it may adopt an annual subsidy approach to enhance perceived benefits while appropriately balancing minimum standards with variable coefficients. This strategy aims to reduce psychological disparities among fishermen and mitigate risks associated with comparison pressures.

Additionally, under an information-sharing framework, efforts should be made to incorporate high-quality resources from highly developed regions into local services, maximizing synergistic support effects. Furthermore, increasing the supply of diversified ecological compensation for older generations of retired fishermen will facilitate improvements in their development capabilities and income potential and enhance the quality of life in their communities. This approach aims to strengthen the effectiveness of poverty alleviation efforts among local fishermen.


Acknowledgments

General Project of National Social Science Fund of China (22BGL274); Special Project for the Construction of Modern Agricultural Industry Technology System “CARS-46 National Characteristic Freshwater Fish Industry Technology System.”

Authors’ Contribution

Methodology: Jianming Zheng (Equal), Xueming Wang (Equal). Writing – original draft: Jianming Zheng (Equal), Xueming Wang (Equal). Data curation: Jianming Zheng (Equal), Xueming Wang (Equal). Software: Jianming Zheng (Equal), Xueming Wang (Equal). Conceptualization: Jianming Zheng (Equal), Xueming Wang (Equal), Yang Yang (Equal). Writing – review & editing: Yang Yang (Equal), Qijun Jiang (Equal). Supervision: Yang Yang (Equal), Qijun Jiang (Equal). Funding acquisition: Qijun Jiang (Lead).

Competing of Interest – COPE

The authors report there are no competing interests to declare.

Ethical Conduct Approval – IACUC

Authors have complied with the Convention on Biological Diversity and the Convention on the Trade in Endangered Species of Wild Fauna and Flora.

All authors and institutions have confirmed this manuscript for publication.

Data Availability Statement

All are available upon reasonable request.