The Bayelsa State Government identified 41 fishing camps, ports, and communities as being within the spill-affected zone, classifying them into 17 “heavily impacted” and 24 “impacted” settlements. Heavily impacted camps and ports are those located within an estimated 5 km radius of the Aiteo Santa Barbara South Well-1 wellhead along the Santa Barbara River and adjacent creeks; impacted communities lie beyond this boundary but within the broader spill influence zone. The full classification is presented in Table 1, contextualized within the study’s community selection framework.

It should be noted that the classification criteria were implied rather than formally stated. The wellhead spill point at Worikumakiri was deserted at the time of assessment, as was the Pipeline settlement across the Santa Barbara River. Several settlements listed by the government were found to be misspelled, absent from National Population Commission census records, or abandoned following the spill. Of the 41 identified settlements, eight were ultimately surveyed during the field assessment, selected as representative of the biophysical and human environment within the spill-affected zone.

Table 1. Classification of spill-impacted fishing camps, ports, and communities in the Santa Barbara well-1 spill area, Nembe LGA, as provided by the bayelsa state government.

Source: Bayelsa State Government list, 2022. Note: *Wellhead site, deserted at the time of study; **Uninhabited/deserted.

The study adopted a mixed-methods research design within the participatory rural appraisal (PRA) framework, combining qualitative and quantitative data collection techniques. This approach is well-established in socioeconomic baseline and social impact assessment (SIA) studies, particularly in complex riverine environments where structured questionnaires alone cannot adequately capture the nuances of livelihood systems and community experiences [9][12][13].

Field data collection covered eight fishing camps, ports, and communities. Four motorised fibre boats with 75 HP engines were deployed for site access. The structured questionnaire comprised five thematic sections: 1) respondent sociodemographic characteristics (age, sex, marital status, education, household size); 2) occupation, fishing experience, gear ownership, and pre-spill income and expenditure; 3) access to social infrastructure (water, electricity, education, health); 4) reported post-spill impacts on fisheries, income, and assets; and 5) observations on environmental conditions and community responses. It used a mix of closed-ended (multiple-choice, Likert-scale) and short open-ended items. The following PRA techniques were employed:

a)Focus Group Discussions (FGDs):Ten FGDs were conducted across the eight communities, targeting fishers, women traders, community leaders, and mixed groups. These discussions provided detailed qualitative data on livelihood systems, spill impacts, coping strategies, and community perceptions.

b)Key Informant Interviews (KIIs):Semi-structured KIIs were conducted with community heads, women leaders, youth representatives, and local traditional rulers to capture expert community perspectives on pre- and post-spill conditions.

c)Community-wide meetings:Six community-wide meetings combined general interaction sessions with information verification exercises.

d)Structured questionnaire administration:Eighty-two (82) copies of a structured questionnaire were administered to adult residents across the surveyed communities using clustered and simple random sampling. Within each settlement, households were approached along the linear riverbank settlement pattern at a fixed skip interval set by the field team in proportion to the visible household count. Where the selected household was absent or declined, the immediately adjacent household was substituted. One adult respondent per household, preferably the household head or, in their absence, the most senior adult present, was interviewed. Eighty-one (81) were retrieved and usable; one was discarded for incomplete data.

e)Transect walks and ground-truthing:These were used to corroborate community claims, document environmental conditions photographically, and verify the presence of infrastructure, facilities, and spill evidence.

It is important to note that fieldwork was conducted in April 2022, approximately five months after the 5 November 2021 blowout. Consequently, pre-spill income, catch volumes, gear values, and asset holdings were reconstructed from respondent recall rather than measured against contemporaneous baseline records. This recall basis is revisited where relevant in the results and discussion.

The Bayelsa State Government provided a list of the spill-affected areas at the pre-field briefing, identifying 41 fishing camps, ports, and communities within the spill influence zone, classified into 17 “heavily impacted” and 24 “impacted” settlements (Table 1). This classification served as the primary basis for defining the study’s spatial scope and guided community selection. The eight surveyed communities were selected purposively from the 41-settlement list using the following explicit criteria: 1) classification by the Bayelsa State Government as “heavily impacted”, with priority given to settlements within the 5 km radius of the wellhead; 2) physical accessibility at the time of fieldwork, as several listed settlements had been abandoned following the spill and could not be reached safely by the field boats; 3) continued habitation, evidenced by the presence of residents available to participate in interviews, FGDs, and community meetings; 4) coverage of the gradient from the wellhead outward along the Santa Barbara River, from Worikumakiri at the wellhead to the more seaward settlements of Owukubu and Obioku, so that the sample captured both the most heavily contaminated zone and the wider spill influence area; and 5) verifiable identity against census and administrative records, since several settlements on the government list were misspelled or absent from National Population Commission records. A minimum community-wide meeting and at least one FGD were held in every selected settlement, and questionnaire numbers per community (Table 2) were set in rough proportion to the adult resident population encountered on arrival, which explains why Shellkiri (26) and Obioku (15) account for the largest shares, while the deserted Worikumakiri yielded only a single opportunistic interview.

Table 2. Questionnaire coverage of the surveyed communities.

Source: Field Survey, 2022.

Secondary data were obtained from the 1991 and 2006 National Population Commission (NPC) census reports, National Bureau of Statistics (NBS) publications, Niger Delta Development Commission (NDDC) reports, and established socioeconomic literature on the Niger Delta. Population projections to 2021 were calculated using the exponential growth model: P n = P o × ( 1 + r ) 2 , where P_o is the base population (1996 figures derived from the 1991 census), r is the annual growth rate (2.9%), and n is the number of years elapsed. This approach is consistent with widely used population projection methods for sub-national planning in Nigeria [5][6].

Following the social impact assessment indicator framework advocated by Vanclay [14] and subsequently operationalized in resource development assessment contexts [15], three primary socioeconomic indicators were assessed, selected for their definitional clarity, data availability, robustness, scalability, and inclusiveness: 1) livelihood and fisheries activities; 2) income derived from fisheries; and 3) visual, aesthetic, and other observable environmental damage. These criteria ensure that each indicator has an unambiguous, measurable definition; that it is spatially and temporally stable; that data can be collected at multiple geographical levels; and that diverse community groups, including women, indigenous fisherfolk, and non-fishing members of the fisheries supply chain, are captured [16].

Descriptive statistical methods, which include means, percentages, and frequency distributions, were used to analyse quantitative questionnaire data. Qualitative data from the FGDs and KIIs were transcribed from field notebooks and audio notes into expanded written transcripts immediately after each session. Transcripts were coded manually using an inductive-then-deductive thematic analysis: an initial read generated open codes around recurring topics (e.g., “catch decline”, “gear damage”, “shellfish loss”, “market disruption”, “emotional strain”), which were then grouped under the three pre-specified indicator domains—livelihood/fisheries, income, and observable damage. Data triangulation was pursued across three tracks: 1) convergence between questionnaire percentages and themes arising in FGDs and KIIs; 2) corroboration of community reports through transect walks and photographic ground-truthing at affected sites; and 3) cross-checking of population and demographic figures against NPC and NBS records. Where questionnaire, FGD, and field-observation data diverged on a given point, that divergence is flagged in the results and discussion rather than resolved by fiat. Six levels of aggregation were employed: national, regional (Niger Delta), state, LGA, settlement, and household.

Several limitations of this assessment should be acknowledged. First, the questionnaire sample of 81 respondents was drawn from only eight of the 41 settlements on the Bayelsa State Government list, and community selection was purposive rather than probabilistic; the quantitative findings are therefore indicative of conditions in the surveyed communities rather than statistically representative of the entire spill-affected zone. Second, several listed settlements, notably Worikumakiri at the wellhead and the Pipeline settlement, had been abandoned by the time of fieldwork, which means the most acutely impacted populations are under-represented in, or wholly absent from, the dataset. Third, the assessment lacked an independent pre-spill baseline; pre-spill income, catch volumes, gear values, and asset holdings were reconstructed from respondent recall five months after the incident and were not verified against independent fisheries landing records, bank transaction data, or asset registers. Fourth, the income figures presented are self-reported field estimates, and some cells combine data from separate sub-questions (e.g., primary versus secondary occupation earnings), which limits their direct comparability. Fifth, environmental-damage observations were made visually at the surveyed locations and were not paired with laboratory analysis of water, sediment, or tissue samples within this SIA component of the PSIA. These limitations shape the claims this paper can legitimately support and are reflected in the framing of the results, discussion, and recommendations.

The study communities are predominantly inhabited by the Nembe Ijaw, an ethnic group whose culture, governance systems, and livelihoods are deeply rooted in riverine and coastal ecosystems. Christianity is the dominant religion, with approximately 97% of surveyed respondents identifying as Christian; the remainder practiced traditional religion. Traditional governance is structured hierarchically, from the Amanyanabo (paramount king) through the Council of Chiefs to community-level Village Heads, Community Development Committees, and youth and women’s wings. Land tenure follows a patrilineal system, with communal land managed by community elders and family lands distributed among compound members for the limited farming practiced in the area.

Social amenities across the riverine communities are severely deficient, which is a reflection of the broader infrastructure deficit in Bayelsa State’s rural interior. Educational facilities are limited to poorly equipped primary schools in a few communities, with secondary schools only accessible in the mainland towns of Ogbolomabiri and Bassambiri; only six secondary schools serve the entire Nembe LGA. No electricity supply exists in any of the riverine settlements, and households depend on hurricane lamps and private generators. Potable water is effectively unavailable for most: 53.1% of respondents rely on rainwater harvesting, and approximately one-third source water from uncovered, shallow, hand-dug wells. Healthcare is restricted to a single Primary Health Centre at Obioku with no resident doctor, supplemented by the Nembe Comprehensive Health Centre and General Hospital serving the broader LGA population. A 12-passenger speedboat from the riverine communities to Nembe town costs up to ₦2000 and takes between 45 minutes and an hour. The picture that emerges is one of marginalised communities with very limited capacity to absorb the additional shock of a major oil spill on their resource base.

The 2006 National Population Census recorded Bayelsa State’s total population at 1,704,515, with Nembe LGA contributing 130,966 persons (approximately 7.7% of the state total). Based on the state’s inter-census growth rate of 2.9% per annum [6], Nembe LGA’s population was projected to be approximately 201,505 by 2021, and Bayelsa State’s at approximately 2,627,987 [5]. Table 3 presents the population profile of the spill-affected communities.

Table 3. Population estimates for selected spill-affected communities in Nembe LGA (1991-2021 projection).

Sources: NPC [6][18][20]; NBS [5]. Note: Projection using exponential growth model at 2.9% p.a. from 1996 base. *Communities visited during PSIA fieldwork; **Name may be a variant of a listed settlement.

The age-sex structure of household populations in the surveyed communities conforms to the broad-based pyramidal pattern typical of the Niger Delta and Nigeria more broadly. Children aged 0 - 18 years comprised approximately 48.6% of household members; those in the productive age bracket (19 - 59 years) constituted 47.8%; and the elderly (60+ years) accounted for 3.4%. The dependency ratio is 1.08, meaning that on average each working adult supports at least one dependent. This young, growing population has significant implications for education, employment, and the long-term productivity of households impacted by the spill.

The sex distribution among respondents showed a slight male preponderance (56.2% male, 43.8% female), with males constituting 55.4% of the overall household population. In 1991, the state-wide sex ratio was nearly equal; a marginal increase in male representation in recent decades may reflect outward female migration to market centres for fish trading.

Table 4 summarises the key sociodemographic characteristics of respondents and their households. The majority of respondents (47.1%) were married, with 47.8% of adult males in polygamous households, a pattern consistent with the Nembe tradition of augmenting household labour for fishing through family size. The average number of children born to married women was six, with household sizes predominantly in the 11 - 15-member range, consistent with the well-documented pattern of large household sizes in Bayelsa State [17][18].

Table 4. Sociodemographic profile of respondents.

Source: Field Survey, 2022.

Educational attainment in the study area was modest but not negligible. Approximately 37.8% of respondents had secondary education, 23.3% primary education, 13.3% tertiary qualifications, and about 9% had no formal education at all. Among respondents’ children, 48.8% were enrolled in primary school and 31.1% in secondary school, with the majority attending institutions in the Nembe mainland towns, and parents bearing the costs of accommodation and commuting. This education-access burden compounds the economic vulnerability of households already reliant on volatile fisheries incomes.

The closure of the Shellkiri community primary school following the spill, with teachers still drawing salaries while absent from their posts, is a telling detail. It typifies the systemic neglect of educational infrastructure in spill-affected riverine communities and represents a measurable non-income cost of the incident that rarely appears in impact assessments.

Housing quality across the surveyed settlements is predominantly poor: 43.8% of respondents live in wooden or plank-built houses, 25% in bamboo or stick-framed dwellings, with only a minority in concrete block structures. Two-thirds own their homes; one-third rent, which is notable given the remoteness of these communities. Savings behaviour is severely constrained, with over 51.9% of respondents reporting no savings at all, a consequence of large household sizes, high food expenditure (consuming 64.6% of the weekly budget), and the complete absence of banking facilities in the riverine settlements.

4.4.1. Occupation and Fisheries Dependence

Artisanal fisheries are the near-total economic base of the study communities. Over 93.5% of the resident population was engaged in fishing and fisheries-related activities, including direct capture fishing, fish processing, fish trading, canoe carving, and net repair. This level of fisheries dependence is consistent with findings from comparable studies in coastal Niger Delta communities [7][10]. The artisanal fisheries system relies on wooden and fiber canoes (6 - 13 m long), motorized with 25 - 75 HP outboard engines, and operated with gill nets, cast nets, beach seines, hooks, and traps. Fishing is conducted year-round, with the dry season (September-May) being the more productive period. Deep-sea fishing excursions extended 10 - 25 fathoms (approximately 5 - 15 km) into the Atlantic Ocean, particularly from the more seaward communities of Sunnykiri, Sandkiri, Tweni, Owukubu, and Obioku.

The gender division of labour is clearly defined. Men carry out capture fishing; women and older children process, dry, smoke, and trade fish in urban markets at Nembe Waterside, Creek Road Market in Port Harcourt, and Swali Market in Yenagoa. This integration of women into the supply chain means they are directly and immediately exposed to any reduction in male fishing output, which is precisely what happened after the spill. Fishing experience among respondents was substantial: 53.5% had been in the occupation for over 20 years, and a further 29.4% for 16 - 20 years.

4.4.2. Income Levels and Household Expenditure

Pre-spill income data, gathered through self-reported recall during FGDs and KIIs approximately five months after the spill and therefore subject to the limitations of retrospective estimation, reveals significant but variable earnings from the fisheries sector. In the Tweni community, fishers reported making approximately ₦30,000 from a single morning expedition, with the potential to earn ₦60,000 on a good day. At Sunnykiri, a three-man crew on a single deep-sea trip could bring in up to ₦70,000. Fishers at Sandkiri reported potential monthly earnings of up to ₦200,000 from big-net fishing, while at Owukubu, nearest the ocean, individual landings reportedly reached ₦100,000 on good days. Table 5 presents the broader income distribution.

Household expenditure was dominated by food, which consumed approximately 64.6% of the weekly family budget, followed by shelter/accommodation (10.5%) and education (9.4%). These figures closely align with national NBS data reporting 57.2% of household spending devoted to food in the 2009/10 period [19]. The high food expenditure, combined with large household sizes and the complete absence of local banking, explains why over half of all respondents reported no savings, a financial fragility that makes these communities acutely vulnerable to the kind of sudden income shock that oil spills deliver [2].

Table 5. Monthly income distribution of respondents.

Source: Field Survey, 2022. Note: The majority (87.5%) of household heads spend over ₦5000 weekly on family needs. Over 51.9% have no savings. Data are self-reported estimates from field interviews.

4.5.1. Impact on Fisheries and Livelihoods

The Aiteo Santa Barbara South Well-1 blowout contaminated the Santa Barbara River, adjacent creeks, and the inshore coastal zone with crude oil over 33 days. In all eight surveyed communities, 100% of respondents reported a significant reduction in fish catch per unit effort (CPUE) following the incident. This 100% figure reflects a uniform respondent-reported perception of severe decline in returns per fishing trip relative to pre-spill conditions, rather than a measured zero-catch outcome. In the immediate weeks after the blowout, FGD participants described two overlapping experiences that together make up this figure: (i) an outright inability to fish in heavily contaminated stretches of water and oiled creek mouths, and (ii) substantially reduced catches per trip in the less-affected areas where fishing continued. CPUE was not measured here through standardized fisheries landing logs; rather, it was captured through respondent comparison between pre- and post-spill trip outcomes, triangulated with community meeting accounts and direct observation of oiled nets and idle canoes. This is consistent with Nwosu et al. [10], who demonstrated a statistically significant negative relationship between oil spill volume and fish production in the Niger Delta over a 35-year period (1981-2015), and echoes what Elum et al. [1] documented on fisheries productivity decline as a dominant socioeconomic impact of oil exploitation in the region.

What community discussants described in the field made the numbers concrete. Younger fishers now travel further out to sea and spend longer hours in the water just to bring home catches that once required far less effort. At Carltonkiri (Shellkiri), respondents stated that sardines, once the most plentiful catch in local waters, have entirely disappeared. At Tweni, fishers who once hauled 25 or more scores of fish per trip (with a score being 20 cards, each worth approximately ₦6,000) were now returning with considerably less. Taken together, these accounts point to a serious decline in nearshore fish populations and the degradation of spawning and feeding habitats due to crude oil contamination, a pattern widely reported across the Niger Delta oil spill literature [2][4].

The women’s livelihoods were also severely disrupted. The women’s leader of Carltonkiri, Mrs. Dio Jackson, stated that she and other women processors typically purchased 20 scores (or “casa”) or 18 - 30 cards of fish and generated up to ₦100,000 gross monthly income from trading in Nembe, Yenagoa, and Port Harcourt. Following the spill, she reported that even ₦20,000 was no longer feasible. The collection of periwinkles and other shellfish from mangrove creek beds, which was a critical supplementary income source for women and children, was rendered impossible by oil contamination of the mangrove zones.

4.5.2. Impact on Income

The income impacts of the wellhead blowout are multidimensional. Direct income loss arose from the inability to fish in contaminated waters, reduced CPUE in less-affected areas, and the destruction of fishing gear and equipment. Indirect income loss came from the interruption of the fish processing and trading supply chain, the contamination of shellfish beds, and the psychological impact on fishers’ willingness to continue operating in spill-affected zones.

A formally established pre-spill income baseline is essential for accurately measuring losses attributable to an oil spill. The absence of such data is, as Sam et al. [2] and Elum et al. [1] have both noted, a recurring shortcoming in post-impact assessments across Nigeria, and it is a shortcoming that demands systematic correction. It should be emphasised that the pre-spill income, catch, and asset figures reported here were reconstructed from respondent recall several months after the blowout, in the absence of independent verification against fisheries landing logs, bank records, or asset registers. As a result, the values are best read as indicative orders of magnitude for respondent-reported earnings rather than as validated loss estimates. What the field data did establish was that before the spill, the majority of respondents (46.6%) were earning above ₦50,000 per month from their primary occupations, and 35.8% reported annual gross earnings exceeding ₦500,000. These are not marginal figures. They are well above Nigeria’s recently revised minimum wage of ₦30,000, which offers some sense of the economic losses involved. The destruction of livelihoods at this income level has hit these communities considerably harder than national poverty benchmarks alone would suggest.

4.5.3. Visual and Aesthetic Impacts and Other Observable Damages

Table 6 summarizes the visible and reported impacts of the oil spill on the socioeconomic environment, as documented through community interactions, direct observation, and photographic evidence during the April 2022 fieldwork.

Table 6. Reported socioeconomic and environmental impacts of the Aiteo Santa Barbara South well-1 oil spill.

Sources: Field Survey, 2022; Community FGDs and KIIs.

Physical evidence of persistent crude oil contamination was documented at Worikumakiri (the wellhead location), where spilled oil remained visible five months after the incident. Oiled net samples shown by community members and oil-stained ponds observed at Sunnykiri, Tweni, and Inara-Kiri provided material corroboration of community claims. Psychosocial strain was captured in this assessment through two specific threads of the dataset rather than a clinical mental-health instrument: 1) questionnaire and FGD items on community well-being, worry about the future of fishing, and perceived fairness of the compensation process; and 2) recurring KII themes of anger, anxiety, resignation, and a sense of abandonment, which converged with the reported delay of compensation and the operator’s denial of claims. Food-security concerns, similarly, were derived from the combination of reported CPUE collapse, contamination of shellfish beds that ordinarily supplement household protein intake, and the 64.6% weekly household budget share already devoted to food. The claims made in this paper are deliberately limited to these reported and observed dimensions. This aligns with the broader literature on the psychosocial consequences of oil spill incidents in affected communities [3]. What the numbers cannot fully capture is the weight that came through in these conversations: a deep sense of abandonment felt by people who had already been marginalised long before the spill occurred.

The absence of a pre-spill socioeconomic baseline, including community-level income records, fisheries productivity indices, and asset registers, severely constrained this assessment’s ability to produce monetized estimates of income and livelihood losses. The Bayelsa State Government, NOSDRA, and oil operating companies should urgently establish and regularly update community-level socioeconomic baseline databases for all oil-bearing communities within active operating areas in OML 29 and adjacent leases. This is consistent with global best practice in environmental and social impact assessment [2][9].

The current compensation claims process was reported by community members to be delayed, opaque, and inadequate. A structured compensation framework should be developed and implemented, with clear eligibility criteria, transparent valuation methodologies, and enforceable timelines. The framework must extend beyond direct fishers to encompass women processors, net menders, canoe carvers, and traders within the fisheries supply chain, all of whom were demonstrably impacted by the spill. Compensation frameworks from comparable jurisdictions, including Canada’s Gulf of Mexico regime, offer useful reference points for developing a context-appropriate Nigerian model [1].

At the time of this assessment (April 2022, five months post-incident), visible crude oil contamination persisted at the wellhead site and adjacent areas. This represents an ongoing source of fisheries and livelihood damage and poses serious public health risks. Emergency and sustained remediation of contaminated water bodies, mangrove zones, and shorelines must be treated as a precondition for the recovery of fisheries and the restoration of community livelihoods. NOSDRA and the Nigeria Upstream Petroleum Regulatory Commission (NUPRC) should enforce compliance with the Environmental Guidelines and Standards for the Petroleum Industry in Nigeria (EGASPIN) remediation standards.

A comprehensive socioeconomic recovery plan must be developed for the spill-affected communities, addressing the multiple dimensions of livelihood disruption documented in this study. The plan should include: (i) short-term food security and income support for affected fishing households; (ii) replacement or compensation for destroyed fishing gear and equipment; (iii) restoration of educational and healthcare infrastructure disrupted by the spill; (iv) provision of alternative livelihood options during the fisheries recovery period; and (v) mental health and psychosocial support for community members experiencing distress. The plan should be developed with the meaningful participation of affected communities, including women’s groups, and implemented through a multi-stakeholder body comprising the Bayelsa State Government, NOSDRA, Aiteo, civil society organisations, and community representatives.

The Petroleum Industry Act (PIA) 2021, though providing an updated legislative framework for the Nigerian petroleum sector, requires robust implementing regulations that specifically address oil spill response, community compensation, and environmental remediation in the onshore Niger Delta. The Bayelsa State Government should advocate, through appropriate legislative and regulatory channels, for bespoke regulations that mandate pre-spill baseline assessments, enforce rapid JIV processes, and establish independent community compensation panels.