A Report on the Cameroon Fishery and Livelihood Sustainability Survey (CAMFISHLIST)
MuhamaduAwal1✉Emailwirajingmuhamadu@gmail.com
KindzekaWirajing1
RogerTsafackNanfosso1Emailroger.tsafack-nanfosso@univ-dschang.org
ArmandMboutchouangKountchou2Emailarmand.mboutchouang@univ-dschang.org
AliHaruna1Emailaliharuna504@gmail.com
AlangErnestWung1
WirajingAbdu1Emailernest.alang@univ-dschang.org
SamadFondzenyuy1Emailsamadabdu09876@gmail.com
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Department of Economic Policy AnalysisUniversity of DschangCameroon2Department of Public EconomicsUniversity of DschangCameroon
Muhamadu Awal Kindzeka Wirajing (Corresponding author)
Department of Economic Policy Analysis, University of Dschang, Cameroon
Email: wirajingmuhamadu@gmail.com
Roger Tsafack Nanfosso
Department of Economic Policy Analysis, University of Dschang, Cameroon
Email: roger.tsafack-nanfosso@univ-dschang.org
Armand Mboutchouang Kountchou
Department of Public Economics, University of Dschang, Cameroon
Email: armand.mboutchouang@univ-dschang.org
Ali Haruna
Email: aliharuna504@gmail.com
Department of economic policy analysis, University of Dschang, Cameroon
Alang Ernest Wung
Email: ernest.alang@univ-dschang.org
Department of Economic Policy Analysis, University of Dschang, Cameroon
Wirajing Abdu Samad Fondzenyuy
Email: samadabdu09876@gmail.com
Boys-choice mixed farming and vocational training, Kumbo, Cameroon
Faculty of Science, University of Buea, Cameroon
A Report on the Cameroon Fishery and Livelihood Sustainability Survey (CAMFISHLIST)
Abstract
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This report presents the findings of a large-scale household survey conducted across 25 fishing communities in Cameroon, which aims to assess the activities of the fishery sector and their role in enhancing livelihood sustainability. A total of 511 artisanal fishermen and fish farmers were surveyed across eight regions using structured questionnaires and field interviews. The study explores multiple dimensions of sustainability, including food security, health performance, household resilience to shocks, and environmental sustainability. Findings reveal that 56.2% of households are food secure, while 43.8% experience varying levels of food insecurity. The CMP ordered probit regression findings further reveal that fishery activities enhance their food security status and health performance. In terms of health, over 33% of households reported poor or uncomfortable health conditions, with 16% indicating excellent health. The average household income from fishery sales is notably higher among marine fishermen, with annual revenues exceeding 7 million FCFA for about 38% of respondents. Despite this economic contribution, only 9% of households are members of fishery cooperatives, and fewer than half have received any formal training, highlighting significant gaps in social and human capital. Furthermore, 56% of respondents report witnessing a decline in fish species, signalling environmental degradation and unsustainable fishing practices. The report also identifies substantial participation of immigrants and internally displaced persons in the sector, making it a key livelihood option in the context of regional conflict and food insecurity. Overall, the study provides empirical insights that are critical for policy formulation aimed at improving sustainable fisheries management, enhancing rural livelihoods, and supporting vulnerable populations. The findings have broader relevance for developing countries with similar socio-ecological contexts.Keywords:
Cameroon fisheries
Livelihood Sustainability
Survey report
Immigrants
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1. Introduction
The fishery sector is one of the foundations of rural development in Cameroon, given its rich productive base and great agro-ecological diversity (Beseng, 2019). Hundreds of starving immigrants seeking a means of subsistence have found safety in the Cameroonian fishing environment. These immigrants, mostly citizens of neighboring countries like Nigeria, Mali, and Niger, have fled terrorist threats and are looking for better opportunities elsewhere in order to address the dire hunger crisis. Thousands of internally displaced Cameroonians from the far northern regions are also found in this sector; they either moved towards the maritime south to escape the dire food situation or terrorist threads (Wirajing and Nanfosso, 2025b; Tekwombuo and Thorarensen, 2013). Fishing as an income-generating opportunity has significantly contributed to the country’s GDP and has provided a breath of fresh air to thousands of individuals as a means of reducing their food poverty levels and income inequality gaps. Though a huge disparity in income from fishery sales along the maritime zones among fishermen households has influenced the wellbeing and livelihood sustainability in this region, exacerbated by environmental shocks and climate variability. This problem is particularly severe during the non-harvest period when there are increased climatic shocks that are worsened by poor fishery practices, environmentally harmful fishing gear, and vessels that pollute water bodies and increase the ecosystem’s gaseous content.
The fishery sector is the fastest-growing animal-based food production sector in the world, particularly in Africa. It contributes to the sustainability of livelihoods for poor households, especially those in rural areas (Wirajing and Nanfosso, 2025a; Beseng, 2019). It most significant contributions are seen in aspects such as food and nutritional security, poverty alleviation, income generation for healthcare, and human capital development. However, fishery exploitation poses a threat to environmental livelihood due to the significant waste released into the environment as a result of poor management (FAO, 2012a). The impact of the fishery sector on the environment cannot be underestimated, especially when considering its role in generating income opportunities for households to improve their nutrition and health status. The management of fishery resources in Cameroon not only affects the environment but also the sustained long-term patterns of fishery supplies and exacerbates inequalities in fishery harvest. These inequalities result from poor fishery practices as well as government regulations through their fiscal tax system. This study considers the importance of fishery resources in enhancing households’ livelihood sustainability and also establish the means to help eliminate poor environmental strategies that harm fishery regenerative capacity, enhance biocapacity, and establish a balance in the different fishing localities. Considering the global patterns of food production and its shortages during the unprecedented COVID-19 pandemic, the fisheries sector, as a major source of animal protein, needs clear systematic principles and modalities that define its activities and management system for livelihood sustainability.
The Cameroon fishery sector registers on average about 300,000 metric tons of legal harvest annually of fish, with thousand tons of unregistered harvest. The artisanal fisheries sector is producing almost 90% of this quantity. Industrial fishing represents just about 5% of the production while aquaculture is also about 5%. Fishing and fish farming are practice in all the ten regions of Cameroon, but dominated by the three coastal zones of the South West, the Littoral and the South regions. Regarding aquaculture and fish farming, the North West region, the Centre, West and the East regions produce the highest fish in addition to the Litoral region, particularly due to the presence of fishery training centres in these regions (Tekwombuo and Thorarensen, 2013; Wirajing et al., 2025a). According to FAO statistics, the number of undernourished individuals decreased from 3.4 million to 1.5 million in 2020. Since the highest percentage of undernourished individuals’ lives in rural areas, where the fisheries potential in Cameroon can still be harnessed to improve their living conditions, it is crucial to conduct studies that explore how the sector can sustain these individuals' livelihoods. The fishery sector offers income-generating opportunities, enabling fishers and fish farmers in Cameroon to maintain their health through proper diets. This study thus employs a team of field agents to collect the necessary information from a sample of 511 fishermen and fish farmers’ households in eight different regions. The main purpose of this research is to examine fishery activities in Cameroon and the sector’s effects on livelihood sustainability.
Specifically, this survey aims:
To examine fishery activities in the Cameroon fishery sector, including in marine and inland environments. It also covers aquaculture and fish farming.
To study the effect of the fishery sector on household’s food insecurity prevalence in the Cameroon fishing communities.
To investigate the effect of the fishery sector on households’ health vulnerability exposures in the Cameroon fishing communities.
To assess the impact of fishery activities on sustainable fishery practices in the Cameroon fishery bodies.
To examine households vulnerabilities exposures to environmental shocks resulting from poor fishery practices.
The conceptual framework of the study is guided by the Department for International Development (DFID) report on sustainable livelihood and the FAO (2012) consultation report. Based on the sustainable livelihood approach documented by the DFID (1999), we highlight fishery-based livelihood that encompasses fishers’ household assets, fishing activities, strategies and the processes that link assets to fishing activities and the outcomes that procure sustainable livelihood (Ashley and Carney, 1999). The DFID (1999) documented five livelihood outcomes, which are: food security, well-being, income-generation, reduced vulnerability and the sustainable use of natural resources. These dimensions are grouped into three main aspects of economic, social and environmental livelihoods as presented in Fig. 1.
Fig. 1
Sustainable livelihood outcomes Source: Author’s construction from DFID (1999)
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The economic livelihood takes into consideration the income generation, employment opportunities and physical capital. These are used as means to attain social outcomes such as food security, poverty alleviation, healthcare coverage and a durable resilience system to shock exposure. The economic and social aspects in the fishery sector determine the fisher’s livelihood sustainability, while the environmental aspect considers fishery sustainability and its surrounding environment. The fishery-based livelihoods’ dimensions, as documented by DFID (1999) in their sustainable livelihoods reports and the FAO (2012c) consultation, guided the chosen indicators of livelihood in our study due to the report’s dynamism (Fig. 2).
THE CAMEROON FISHERY SECTOR
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Figure 2: The study’s orientation of livelihood outcome in Cameroon fishing communitiesThe results of this report have far-reaching implications for development practitioners and policymakers focused on fisheries, rural development, public health, and displacement management. By generating context-specific evidence on the food, health, and socio-economic conditions of fishing communities, particularly vulnerable and displaced populations, this work offers practical guidance for policy reforms. With its evidence-based approach, the study supports inclusive and sustainable livelihood strategies that can transform the lives of thousands across Cameroon’s coastal and inland communities, reinforcing both human and ecological resilience. First, it is the first in the Cameroon fishery literature to cover all the main fishing regions where fishing and fish farming are most prevalent, while proposing how the Ministry of Livestock and Fisheries should supervise to ensure proper fishery management for livelihood sustainability. Second, the study focuses on marine fishing, inland fishing, and aquaculture across 25 fishing communities. It acknowledges the diversity within the fishery sector and the various fishing communities involved. This approach highlights the sector's impact on livelihood sustainability, taking into account immigrants who fish along the coast, as well as many displaced Cameroonian fishermen and professional fish farmers. Thirdly, the study outlines strategies to enhance the livelihood adaptation capacities of households. This is particularly important for developing policies that help households adjust during periods of shock. This section aims to emphasise and provide constructive recommendations to the ministry.
2. Materials and methods
2.1 Survey organization and sampling
2.1.1 Training of field agents and fieldwork
To attain the objectives of the study, primary source data, both quantitative and qualitative, were collected from the field, using an experimental research design approach that includes analytical components for analysis. In preparation for the data collection exercise, field agents were selected, trained, and provided with the necessary tools. The training lasted over 10 days, from August 1, 2023, to August 10, 2023, and took place on the University of Dschang campus. This training aimed to help the field agents grasp the essential aspects of the exercise, including understanding the questionnaire, the data collection process, and how to use the Kobo Collect tool. The team consisted of 3 controllers and 10 principal surveyors. After the training program, the questionnaire underwent pre-testing. Adjustments were made to address any misunderstandings regarding question formulation, order, and other aspects. Once the questionnaire was finalized, data collection began on September 1, 2023, and ended on February 1st, 2024. The process started with interviews of immigrant fishermen in the Magba sub-division community and concluded with communities surrounding the Limbe Sea, primarily comprising Nigerians and Ghanaians.
2.1.2 Legal authorization and permits
To proceed with data collection, we encountered challenges during pre-testing due to respondents rejecting some questionnaires. To address this, we requested and received a letter of authorization from the Minister of Livestock and Fisheries (MINEPIA), which directed all regional delegations and fishing centres to assist and guide our field agents and introduce them to the fishermen's households. This was followed by support from regional delegates in the fisheries sector, who assigned sub-divisional delegates and various chiefs of centres to lead the survey agents in the field. Thanks to this collaboration, the process became much easier, as government personnel introduced us to the communities they monitor regarding the exploitation of fishery products. However, we still faced difficulties in certain areas, such as Magba, where some communities refused to participate, expressing that the government had no relevance to them and that they would not provide any information about their activities. Additionally, our field agents faced challenges in regions where the local population did not speak the official languages of French and English. In such cases, they had to find locals who could translate their various mother tongues before information could be collected.
2.1.3 Data treatment
During data collection, the controllers, who all had access to the data collection software, performed daily checks to ensure that the information was well entered. Where responses were not well entered, the concerned field agent(s) was/were signalled and asked to improve. Immediately after the data collection, the raw data were downloaded in the form of Excel for cleaning to commence. Immediately, the data was downloaded, and it was imported into STATA version 17.01 for codification and cleaning before usage. In the first instance, all identifiers of field agents and other individuals were removed and given other identities for the confidentiality of the dataset. This process is termed the data codification process. Second, there was the data cleaning process, wherein all indicators were cross-checked to ensure a balance in the dataset and missing values management. Currently, two versions of the dataset exist and are usable for any form of analysis: Excel formatted (cleaned and in CNS extension) and STATA format with dofiles available.
2.1.4 Sample size and response rate
The Slovins' formula to determine a sample size that is representable when the population size is known is adopted with an error margin of 4%. The quota and the purposive sampling techniques were adopted, considered the best when the respondents are all over the national territory, which requires significant clusters of the selected individuals to make it simpler for primary data collection. The focus of the present study is on artisanal fish farmers and fishermen. This proportion of actors in the fishery sector is significant as they produce almost 90% of fish stocks, with the industrial and the semi-industrial sectors producing just about 5% each. We further divide the sample into the different quotas presented in Table 1A. About 51% of these artisanal actors fish in marine bodies, 38.5% fish in extended inland environments like artificial and expanded dams (e.g Magba and Lom Panga ) and about 10.5% practice aquaculture. It should be noted that this is based on the author’s pretest and consultation with fisheries delegations.
Categories | Proportions (%) | Targeted sample size | Realised sample size | Response rate |
|---|---|---|---|---|
Marine fishing | 51% | 300 | 246 | 82% |
Inland fishing | 38.5% | 226 | 208 | 92% |
Aquaculture | 10.5% | 63 | 57 | 90% |
Total | 100% | 588 | 511 | Average rate = 88% |
Table 1 indicates that 588 households were targeted for interviews, and ultimately, 511 households participated, resulting in an effective response rate of 88%. Among those interviewed, 246 households were involved in marine fishing, while 208 households engaged in inland fishing in dams. Additionally, 57 individuals practised aquaculture exclusively, mostly residing in village centres, with some living in towns. The population in these regions is predominantly composed of internally displaced persons and immigrants from neighbouring countries. The fisheries distribution in Cameroon is not well documented, prompting us to obtain undocumented and unpublished information from fishery delegations and from the works of Tekwombuo and Thorarensen (2013) on fish ponds and the fisheries landscape in Cameroon to draw the sample distribution. The covered regions are presented in Fig. 3a while Fig. 3b demonstrates the various departments per region.
Figure 3A: Geographical Location and Surveyed Fishing Regions in Cameroon / Source: Authors’ computation using QGIS
Fig. 3b
The location based on the departments in the different regions
Source: Author’s computation
2.2 Estimation strategy
The study used descriptive analysis techniques to examine fishery production, income patterns, and the differences in livelihood outcomes among various groups in our sample. While understanding the impact of the fishery sector on livelihood sustainability outcomes of health, food insecurity, and fish species depletion, the study adopted the Conditional Mixed Process (CMP) Bivariate Ordered Probit, due to the estimation of ordered response models. This corresponds to health performance, food security, and species depletion indicators, which are rated on a scale of 4 to 5 points. The ratings range from "very poor" to "excellent" for health performance, from "food secure" to "food insecure" for food security prevalence, and from "no depletion" to "very high depletion" in terms of species sustainability (Wirajing et al., 2025). The ordinal nature of these livelihood indicators is not taken into account by unordered multinomial, nested Logit, or univariate Probit models, even though they can account for the categorical nature of the dependent variable. Undesirable characteristics of the multinomial Logit model include the independence of irrelevant alternatives and, in the case of multinomial Probit, the absence of a closed-form likelihood (Acheampong et al., 2022; Davidson and MacKinnon, 1984). This justifies the reason for adopting the ordered probit as it presents itself as the most popular model for ordered response data, as noted by Davidson and MacKinnon (1984). For each individual, the Ordered Probit model is specified as:
N (0,1) …… (1)
where Y∗ is the unobserved latent variable ranging from ranging from
to
,
and
represent vectors of coefficients. Xi represents a vector of the independent variables,
represents the random error term is the error term, assumed to be normally and identically distributed with mean zero and variance normalised to one. The dependent variable takes the value between 1 to 5 or to 4 for any livelihood outcome of health, food security and species depletion as presented in Eq. 2.
2
Where
represent the unknown threshold parameters of the dependent variable to be estimated.
includes K variables of individual-specific characteristics such as gender and age.
includes H variables indicating household characteristics, such as household income and size.
The probability of observing a particular livelihood outcome is demonstrated in Eq. 3, for 1 ≤ j ≤ I is given by:
=
(3)
where
is the cumulative distribution function for j. The presence of
leads to a maximum likelihood estimation framework. The log-likelihood function of the Ordered Probit is presented in Eq. 4. L stands for maximum likelihood of a household response or outcome with i-th responses.
4
where
(.) denotes the standard normal cumulative distribution function. So, based on the sample under study
, the log-likelihood function of the ordered Probit model is given in Eq. 5:
5
The log-likelihood function (5) is maximised with respect to the elements of
along with the cut-points from
, by an iterative procedure, to produce the maximum likelihood estimates of both sets of parameters.
For the resilience indicator which is a continuous variable computed using a factor analysis, we adopted the endogenous switching regression model. This endogenous switching regression model helps to address self-selection and endogeneity in the analysis process for households operating in the marine and inland fishing environments (Wirajing and Nanfosso, 2025b). It considers both observed and unobserved effects. This provides consistent estimates whose findings are presented in section 3.2.4.
3. Results
3.1 Descriptive statistics of the surveyed units
This section outlines the various units of the survey. The survey includes responses from 511 households across 25 different fishing communities, consisting of fishermen operating in either marine or inland environments, as well as fish farmers who are involved solely in aquaculture within tanks.
3.1.1 Surveyed respondents across the sectors
The fishing industry in Cameroon is categorised into three sectors: artisanal, industrial, and semi-industrial fishing. This study focuses on artisanal fisheries, which account for 90% of the fishery products harvested in the country. Artisanal fishing households operate in both marine and inland environments, as well as in cage aquaculture. In fishing communities across Cameroon, the majority of households engage in marine fishing, with only a small number practising aquaculture or fish farming, primarily due to the high costs associated with these activities. Out of 511 households interviewed, 246 capture their fish in the marine environment, 208 are inland fishermen, and 57 are aquaculturists. This is demonstrated in Table 2.
In various fishing communities, most captured fish come from marine environments. Only a few individuals engage in aquaculture, primarily located in cities, including the capital of the Centre region, as well as the West and Littoral regions. Those who practice aquaculture typically do so as a secondary activity, often owning businesses that provide income to support their efforts. Table 2 and Fig. 4A show the households surveyed, categorised by fishing type and region across the country. This presents the total number of respondents per region.
Fishing type/ category | Region of data collection | ||||||||
|---|---|---|---|---|---|---|---|---|---|
Adamawa | Centre | East | Littoral | Northwest | South | Southwest | West | Total | |
Marine fishermen households | 0 | 0 | 0 | 176 | 0 | 60 | 10 | 0 | 246 (48.1%) |
Inland fishermen households | 61 | 44 | 31 | 0 | 41 | 1 | 0 | 30 | 208 (40.7%) |
Fish farmers households | 0 | 7 | 15 | 13 | 5 | 0 | 2 | 15 | 57 (11.2%) |
Total | 61 | 51 | 46 | 189 | 46 | 61 | 12 | 45 | 511 |
Fig. 4A
Households representation across the different fishing categories
Source: Author’s computation from the United Nations Fisheries Training Program
Table 2 shows that the Littoral region has the highest number of fishermen households, with 189 respondents out of a total of 511. This region is one of the primary fishing zones in Cameroon, alongside the Southwest and Eastern regions. However, the sample size from the Southwest is limited due to increasing insecurity along the coast, where many fishermen's households are situated. Consequently, it has been challenging to conduct interviews, as the chiefs of fishing centres and government representatives have been unable to collaborate with the survey team due to security concerns. The Adamawa region also provides a significant sample for this study, including the villages of Wandjock and Tibati. Table 3 outlines the number of fishermen and aquafarmers who responded to the survey questions regarding their fishing activities by region. The 25 fishing communities are listed in Table 3, which shows the number of respondents, their proportions, and the regions where these communities are located.
survey region | Survey communities | Respondents | Percent |
|---|---|---|---|
Centre region | Bafia | 21 | 4.11 |
Ebebda | 4 | 0.78 | |
Mbalmayo | 25 | 4.89 | |
Obala | 2 | 0.39 | |
52 | 10.16 | ||
West region | Bati | 5 | 0.98 |
Magba barrage | 18 | 3.52 | |
Mamboko bord | 12 | 2.36 | |
Dschang | 1 | 0.20 | |
Fokue | 5 | 0.98 | |
Santchou | 4 | 0.78 | |
40 | 8.82 | ||
East | Bertoua | 15 | 2.94 |
Wami | 31 | 6.07 | |
46 | 9.01 | ||
Littoral | Douala 2 (Yupue) | 104 | 20.35 |
Douala 5 | 13 | 2.54 | |
Village de Muanko | 42 | 8.22 | |
Yoyo | 30 | 5.87 | |
189 | 36.98 | ||
Northwest | Kumbo | 5 | 0.98 |
Ndop | 41 | 8.02 | |
46 | 9 | ||
Southwest | Limbe | 10 | 1.96 |
Buea | 2 | 0.39 | |
12 | 2.35 | ||
South | Londji | 22 | 4.36 |
Mboamanga | 38 | 7.44 | |
60 | 11.8 | ||
Adamawa | Tibati | 40 | 7.83 |
Wandjock | 21 | 4.11 | |
61 | 11.94 | ||
Total | Total | 511 | 100.00 |
| Source: Author’s computation from the database | |||
3.1.2. Survey units across the formal sector of activity / national status
The fishery sector in Cameroon includes individuals from both the formal and informal sectors. Those in the formal sector possess fishing permits or licenses, while others operate without permits and engage in smuggling fish, often without the knowledge of the authorities. This distinction is important because fishing along the coast is heavily regulated. Figure 5 shows that 56.8% of households involved in the fishing industry do not possess fishing permits and operate in the informal sector. In contrast, only 43.2% of fishermen and fish farming households have the necessary permits. Hundreds of starving immigrants who are seeking a means of subsistence have found safety in the Cameroonian fishing environment. These immigrants, mostly citizens of neighbouring countries like Nigeria, Mali, and Niger, have fled terrorist threats and are looking for better opportunities elsewhere to address the dire hunger crisis. Cameroon home fishers and fish farmers represent 83.95% with immigrants and foreigners representing 16.05% (Fig. 4B).
Fig. 4
The formal fishery sector/national status of the respondents / Source: Author’s computation
3.2 Households fishing activities assessment
This section presents the households fishing activities, including the quantity of fish harvest and the income generated from fishery sales.
3.2.1. Quantity of fish harvested
Section 3.2.1 outlines the quantity of fish harvested by fishermen and fish farmers in the fishing communities of Cameroon. It compares the average fish catch across various fishing sectors, including marine environments, inland waters, and aquaculture practices. The data shows that individuals fishing in marine environments harvest an average of 3,960.543 kilograms of fish per year, while those fishing in inland environments average 3,001.332 kilograms annually. Aquaculturists, on average, harvest 1,908.368 kilograms per year. This information highlights why the marine fishing sector is regarded as the most significant in terms of fish production, as illustrated in Table 4, segment A. In addition, Table 4, segment B, shows the quantity of fish harvested in the fishing year 2023. It reveals that only 8.8% of individuals harvested less than 500 kilograms of fish annually, while 77% of households harvested more than 1,000 kilograms. Additionally, 21.3% of households harvested over 5,000 kilograms, and only 3.7% harvested more than 10000 kilograms in a year, with the highest reported amount being 19200 kilograms.
Segment A | Obs | Mean per group | Proportion (%) | ||
|---|---|---|---|---|---|
Quantity harvested by Marine fishermen | 245 | 3960.543 | 48% | ||
Quantity harvested by inland fishermen | 208 | 3001.332 | 40% | ||
Quantity harvested by aquaculturists | 57 | 1908.368 | 12% | ||
Total | 511 | 8870.243 | 100% | ||
Segment B | Obs | Mean per groups | Proportion (%) | ||
Fish quantity harvested in kilograms (kg) | 511 | 3339.975 | |||
Households with quantity harvested less than 500kg (Q < 500kg) | 45 | 234.178 | 8.8% | ||
Households with quantity harvested greater than 1000 (Q > 1000) | 395 | 4145.972 | 77% | ||
Households with quantity harvested greater than 2000 (Q > 2000) | 307 | 4877.782 | 60% | ||
Households with quantity harvested greater than 5000 (Q > 5000) | 109 | 7617.514 | 21.3% | ||
Households with quantity harvested greater than 7000 (Q > 7000) | 53 | 9626.962 | 10.3% | ||
Households with quantity harvested greater than 10000 (Q > 10000) | 19 | 12038.632 | 3.7% | ||
Households with quantity harvested greater than 12000 (Q > 12000) | 4 | 14625 | 0.74% | ||
Households with quantity harvested greater than 15000 (Q > 15000) | 1 | 19200 | 0.019% | ||
| Source: Author’s computation | |||||
3.2.2. Profit from fishery sales
Table 5 presents a description of the fishery income in the Cameroon fishing communities, indicating the number of households belonging to each income group in the sample of the study.
Segment A | Observations per groupings | Percentage (%) | Mean values of fish revenue | |||||
|---|---|---|---|---|---|---|---|---|
Fish revenue < 1million | 55 | 10.762% | 482572.73 | |||||
Fish revenue < 2million | 117 | 22.896% | 978094.02 | |||||
Fish revenue < 3million | 170 | 33.268% | 1451355.9 | |||||
Fish revenue < 4million | 209 | 40.92% | 1807614.8 | |||||
Fish revenue < 5million | 248 | 48.532% | 2208649.2 | |||||
Fish revenue < 7million | 305 | 59.686% | 2915544.3 | |||||
Fish revenue > 7million | 193 | 37.769% | 13592995 | |||||
Segment B: Income generation across fishery types | Obs | Mean | Min | Max | ||||
Fish revenue for households operating in marine environments | 244 | 9383612.7 | 112500 | 42000000 | ||||
Fish revenue for households operating in inland environments | 204 | 4876022.1 | 20000 | 21000000 | ||||
Fish revenue for aquaculturist households | 54 | 4747759.3 | 25000 | 27000000 | ||||
| Source: Authors’ computation using STATA | ||||||||
There are differences in the fish revenue levels of fishermen and fish farmers based on the type of fishing and the fishing communities they are involved in, including small and large-scale operations. After fisheries sales, segment A of Table 6 shows that 55 fishermen and fish farmers, or 10.76% of the sampled population, received less than one million FCFA in fisheries revenue in Cameroon during the previous 12 months. The majority of the respondents (59.68%) earned less than 7 million FCFA from their fishery sales, with 193 fishermen representing 37.76% of the sampled population exceeding 7 million FCFA. This is further elaborated in segment B of Table 5, which shows that households fishing in marine environments generate more revenue from fishery sales than those operating in inland bodies such as dams.
Additionally, households engaged in fish farming also earn substantial profits, with an average annual income of 4747759.3 FCFA, approximately 7,859 USD (Table 7). Households fishing in marine environments have the highest annual average revenue of 9383612.7 FCFA, equivalent to 15533 USD, based on the March 2024 conversion rate of 1 USD = 604.103599 XAF. This highlights the profitability of the sector. However, it is important to note that there are significant costs associated with the calculated revenue. Due to challenges in tracking expenses, fishermen typically only record the quantity of fish harvested. Operating in marine environments incurs considerable costs, particularly for fuel to power the boat engine and associated taxes.
3.2.3. Fishing efforts and fishing experience of the respondents
This section presents households' fishing efforts, experience and fish harvest cycle. Table 6 indicates that on average, individuals in this community fish 6.096 hours on fishing days. This varies across the different fishing sectors. In addition, individuals reported a fishing experience of 12.092 years on average. Also, fish farmers present an annual average of 3.646 production cycles.
Variable | Obs | Mean |
|---|---|---|
Fishing efforts per day (proxied in hourly basis) | 511 | 6.096 |
Fishing experience (In years) | 511 | 12.092 |
Fish production cycles per year for fish farmers | 113 | 3.646 |
| Source: Author’s computation | ||
Fig. 5
Fishing gear across the Cameroon fishing industry/ Source: Author’s computation
Figure 5 shows that the most popular type of fishing gear used in aquaculture, inland waters, and the marine environment is seine netting. In marine environments, 92% of respondents said they used seine netting; gill netting and traps came in second and third, with 76% and 61% of respondents, respectively. The least common and only found in marine environments are trawlers.
3.3 Livelihood sustainability outcomes
This section is presented in four different subsections. First, explains the households’ livelihood sustainability outcome indicators of food security, health performance and resilience capacity against shocks, and the environmental sustainability indicator of fishery regenerative capacity and fish species depletion in fisher bodies.
3.3.1. Households food security status
Table 7 presents the description of the questions used to measure food security, in their mean, standard deviation, minimum and maximum values. It presents the four pillars of food security that are combined to form the households’ food insecurity access prevalence (HFIAP). The questions presented in Table 7, are on the frequency of experiencing severe health conditions (Never = 0, rarely = 1, sometimes = 2, often = 3, most often = 4).
Variable | Obs | Mean | S. D | Min | Max |
|---|---|---|---|---|---|
Food access | |||||
Were you worried the household would not have access to sufficient food? | 511 | 1.487 | .716 | 1 | 4 |
Did households eat limited variety of food due to lack of resources? | 511 | 1.583 | .749 | 1 | 4 |
Did households eat some foods that was not desired due to lack of resources? | 511 | 1.712 | .878 | 1 | 4 |
Was there no food to eat of any kind in the household because of lack of resources? | 511 | 1.515 | .732 | 1 | 4 |
Food availability | |||||
Was there a case where the households go a whole day without eating? | 511 | 1.446 | .741 | 1 | 4 |
Did any household member have to eat fewer meals because of lack of resources | 511 | 1.603 | .824 | 1 | 4 |
Was there any anxiety that the budget would be insufficient to purchase preferred food? | 511 | 1.728 | .82 | 1 | 4 |
Did household members eat some foods that were considered just manageable? | 511 | 1.703 | .827 | 1 | 4 |
Food stability | |||||
Was there any experience of running out of food without money to buy? | 511 | 1.72 | .876 | 1 | 4 |
Did a member eat fewer meals due to the fear food will finish before having money to buy some? | 511 | 1.581 | .731 | 1 | 4 |
Was there a case, the food did not last for long and there was no means to get some food? | 511 | 1.685 | .826 | 1 | 4 |
Food usage | |||||
Did your households relied on only a few kind of low-cost foods? | 511 | 1.969 | .937 | 1 | 4 |
Did the households skip meals because of the financial constraint? | 511 | 1.603 | .78 | 1 | 4 |
Did any household member lose weight because of the reduced quantity of food eaten? | 511 | 1.701 | .811 | 1 | 4 |
| Source: Author’s computation | |||||
After being reclassified into four categories, the HFIAP is first summarised as a continuous indicator in accordance with the literature. A household without any insecurity issues would have a minimum value of 0 and a maximum value of 56 when the results of the 14 different questions used in this study are added together. The index is summed and then divided by the total number of questions, representing the mean. As a result of the division, the values obtained can only fall between 0 and 4, which aids in the HFIAP’s classification into distinct categories (Table 8). The current study classified values as follows: 0–1 as food secure, 1.1–2 as mildly food insecure, 2.1–3 as moderately insecure, and values above 3 as severely food insecure.
Frequency | Percent | |
|---|---|---|
1 Food secured | 287 | 56.160% |
2 Mildly food insecure | 112 | 21.920% |
3 Moderately insecure | 102 | 19.960% |
4 Severely food insecure | 10 | 1.960% |
Total | 511 | 100% |
| Source: Authors’ computation | ||
Table 8 presents the HFIAP of the households in the Cameroon fishing industry. It depicts that 56.160% of the sampled households were food secure. The households that were mildly, moderately and severely food insecure represent 21.92%, 19.96% and 1.96% of the sampled population, respectively, as proxied by the HFIAS. This presents a clearer indication of the food security levels of households, with more than 45% still food insecure and undernourished. The empirical findings in Table 9 indicate the nature of the effect of fishing characteristics on households’ food security levels. The findings displayed in Table 9 are those of the CMP Probit model, considering a global sample of all the fishermen and fish farmers’ households in the Cameroon fishing industry and the aquatic sector. Given that the values of an ordered Probit model do not necessarily reflect the amount of the effect on the dependent variable, the marginal effects of the corresponding models are examined in this section. The estimated model indicates that the Chi2 is significant at 1% with 115.5. The likelihood estimation parameter indicates that the model is a better fit when selecting the determinants of household food security and can be used for policy recommendations.
Marginal effect of ordered Probit model | ||||||
|---|---|---|---|---|---|---|
Variables | (Food secure) | (Mildly insecure) | (Moderately insecure) | (Severely insecure) | ||
Fish production | 0.0480** | -0.0129** | -0.0293** | -0.00584* | ||
(3.00) | (-2.87) | (-2.93) | (-2.45) | |||
Formal sector (1 = Having a permit/registered) | 0.160*** | -0.0429** | -0.0974*** | -0.0194** | ||
(4.14) | (-3.77) | (-4.03) | (-2.86) | |||
Control variables | Yes | Yes | Yes | Yes | ||
Observations | 511 | |||||
Version | 3 | |||||
Pseudo R2 | 0.107 | |||||
Chi2 | 0.0000 | |||||
Prob > chi2 | 115.5*** | |||||
Log-likelihood | -480.376 | |||||
Xmfx_y | 0.566 | |||||
***, ** and * denotes statistically significant variables at 1%, 5% and 10% levels, respectively.
Figures reported in parenthesis are Robust Standard Errors.
The findings presented in Table 9 indicate that a fisherman or a fish farmer who increases the quantity of fish harvest is more likely to ensure his household has sufficient food and is less likely to be among the severe food insecurity category. The Cameroon fishing industry, containing both immigrants and Cameroonians by nationality, sustains their livelihood and improves their dietary needs and nutrition security. The HFIAP indicator incorporates vulnerability dimension as well as resilience factors, covering food access, usage, availability and stability indicators. This outcome shows that the Cameroon sector can be relied upon to enhance food security. This outcome is consistent throughout the marginal effects of four modalities, indicated by the 3 negative modalities of food insecurity and a positive parameter for the food secure modality. Considering that only 56% of households are food secure in a 4-scale modality index, the nourishment of fishermen and fish farmers’ households still needs to be looked at, through the identification of important policy channels of integrating other sectors of activities into their livelihood categories. Specifically, a kilogram (kg) decrease in fish increases the chances of fishermen and fish farmers’ households being food insecure by 4.8%.
3.3.2 Households health performance
This section presents characteristics in terms of the percentage of households belonging to different health categories. It is presented in terms of mental, physical and the universal health.
Health performance | Frequency | Percent | Cum. |
|---|---|---|---|
Very poor health condition | 13 | 2.54 | 2.54 |
Poor health condition | 55 | 10.76 | 13.31 |
A neutral situation | 104 | 20.35 | 33.66 |
Good health condition | 254 | 49.71 | 83.37 |
Very good health condition | 85 | 16.63 | 100.00 |
Physical health | |||
Very poor health condition | 34 | 6.65 | 6.65 |
Poor health condition | 41 | 8.02 | 14.68 |
A neutral situation | 99 | 19.37 | 34.05 |
Good health condition | 193 | 37.77 | 71.82 |
Very good health condition | 144 | 28.18 | 100.00 |
Mental health | |||
Very poor health condition | 24 | 4.70 | 4.70 |
Poor health condition | 32 | 6.26 | 10.96 |
A neutral situation | 87 | 17.03 | 27.98 |
Good health condition | 244 | 47.75 | 75.73 |
Very good health condition | 124 | 24.27 | 100.00 |
Total | 511 | 100.00 | |
| Source: Computed by the author using STATA | |||
The health status of households in the Cameroon fishing communities is revealed by the descriptive statistics presented in Table 10. A total of 172 households, or 33.66% of the respondents, report being in poor or uncomfortable health, while 16% report being in excellent health. This may vary depending on the specific circumstances involving mental and physical health. The results indicate that 51 fishermen and fish farmers’ households suffer from mental stress and have been psychologically ill in the last 12 months. The findings further reveal that 368 households are in a good mental health condition. This indicates that the majority of the respondents are living healthy lives, though the number of those in poor conditions remains a concern.
Table 11 presents empirical findings indicating the nature of the influence of fishing and fish farming on households’ health status. The findings displayed in Table 11 are those of the Conditional Mixed Process (CMP) Ordered Probit model, considering a general health performance indicator. The marginal effects of the corresponding models are examined in this section because the values of a CMP baseline bivariate ordered Probit model do not always reflect the extent of the effect on the dependent variable. With 146.8, the estimated model shows that the Chi2 is significant at 1%. The likelihood estimation parameter indicated that the model can be used to recommend policies since it fits the households’ health status determinants better.
(A) | (1) | (2) | (3) | (4) | (5) | |
|---|---|---|---|---|---|---|
VARIABLES | Health performance | (Very poor Health) | (Poor Health) | (Neutral situation) | (Good Health) | (Very good health) |
Fishing revenue | 0.0915** | -0.00465* | -0.0116** | -0.0116** | 0.00823** | 0.0196** |
(0.0413) | (0.00239) | (0.00527) | (0.00530) | (0.00405) | (0.00882) | |
Fishery training | 0.341*** | -0.0173** | -0.0431*** | -0.0433*** | 0.0307*** | 0.0731*** |
(0.117) | (0.00685) | (0.0150) | (0.0153) | (0.0117) | (0.0251) | |
Control variabless | Yes | Yes | Yes | Yes | Yes | Yes |
Observations | 511 | 511 | 511 | 511 | 511 | 511 |
Prob > chi2 | 0.0000*** | |||||
Wald chi2(14) | 146.83 | |||||
Log pseudolikelihood | -581.17 | |||||
Pseudo R2 | 0.109 |
***, ** and * denotes statistically significant variables at 1%, 5% and 10% levels, respectively.
Figures reported in parenthesis are Robust Standard Errors.
The findings uncovered in Table 11 reveal that fishing revenue contributes to improving the health performance of fishermen and fish farmers’ households in the Cameroon fishing communities. The result from the marginal CMP model indicates that an increase in a unit FCFA of income generated from fishery sales by fishermen and fish farmers reduces their likelihood of being very poor and living in precarious health conditions by 0.46%. This is in line with a five-point rating of their perceived health performance, which denotes that a probability of 0.0196 (1.96% chance) is the likelihood of being in very good health condition. Consequently, fishing is their main source of income, which improves the food security status and overall health of households in fishing communities. Given that 66.64% of these households reported being in good health during the previous year, and that the three negative signs suppressing poor health indicators and the positive enhancing effects on good health all point to this outcome, which is consistent across the marginal effects of the five categories.
3.3.3 Households resilience capacity
Table 12 presents 9 sub-components that form the three resilience capacities of adaptability, absorptive and transformative capacities, in their mean, maximum and their minimum values.
Indicators of household resilience | Obs | Mean | S. D. | Min | Max | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Access to education infrastructure at the community level (1 = Yes, 0 = No) | 511 | .84 | .367 | 0 | 1 | ||||||||
Having access to electricity (1 = Yes, 0 = No) | 511 | .73 | .444 | 0 | 1 | ||||||||
Healthcare coverage program (1 = Yes, 0 = No) | 511 | .209 | .407 | 0 | 1 | ||||||||
Access to fishery training (1 = Yes, 0 = No) | 511 | .548 | .498 | 0 | 1 | ||||||||
Internet/mobile phone access (1 = Yes, 0 = No) | 511 | 3.871 | 1.853 | 1 | 8 | ||||||||
Access to basic services (ABS) factor score | 511 | 0 | .712 | -1.026 | 1.207 | ||||||||
Belonging to a fishing cooperative/union (1 = Yes) | 511 | .09 | .286 | 0 | 1 | ||||||||
Attended fishery training programs (1 = Yes, 0 = No) | 511 | .548 | .498 | 0 | 1 | ||||||||
Borrowings from group meetings/njangi houses (frequency from 1 to 5) | 511 | 3.26 | 1.49 | 1 | 5 | ||||||||
Did receive a remittance from a neighbour or from your locality (1 = Yes, 0 = No) | 511 | .456 | .499 | 0 | 1 | ||||||||
Did receive a subvention of any form from the government (1 = Yes, 0 = No) | 511 | .83 | .376 | 0 | 1 | ||||||||
social capital factor score | 511 | 0 | .486 | − .622 | 1.645 | ||||||||
Number of years in school (In years of schooling) | 511 | 7.589 | 5.889 | 0 | 25 | ||||||||
Having at least a first school certificate or a professional diploma (1 = yes, 0 = No) | 511 | .703 | .458 | 0 | 1 | ||||||||
Have received professional fishery training/formation (1 = yes, 0 = No) | 511 | .548 | .498 | 0 | 1 | ||||||||
Highest diploma in the household (1 = First school certificate,… 9 = PhD) | 491 | 4.206 | 2.099 | 1 | 9 | ||||||||
Highest diploma of the fisherman/fish farmer (1 = First school certificate, 9 = PhD | 511 | 2.654 | 1.909 | 1 | 9 | ||||||||
Internet usage for fishery research in any platform | 511 | .493 | .500 | 0 | 1 | ||||||||
Human capital factor score | 491 | 0 | .951 | -1.197 | 3.124 | ||||||||
Do you earn income from livestock (1 = Yes, it is a source of income, 0 = No) | 511 | .202 | .402 | 0 | 1 | ||||||||
Is agriculture a source of income to your household (1 = Yes, it is, 0 = No) | 511 | .658 | .475 | 0 | 1 | ||||||||
Are employment benefits an income source (1 = Yes, 0 = No) | 511 | .031 | .174 | 0 | 1 | ||||||||
Does your household depend on remittances as a source of income (1 = Yes, 0 = No) | 511 | .386 | .487 | 0 | 1 | ||||||||
Income from service/professional work services (1 = Yes, a source of income, 0 = No) | 511 | .317 | .466 | 0 | 1 | ||||||||
Income from rents and sale of equipment (1 = Yes, it is a source of income, 0 = No) | 511 | .104 | .305 | 0 | 1 | ||||||||
Income from fisheries (1 = Yes, it is a source of income, 0 = No) | 511 | .996 | .062 | 0 | 1 | ||||||||
Livelihood source diversification factor score | 511 | 0 | .499 | − .487 | 2.249 | ||||||||
Network service availability in the community (1 = Yes, 0 = No) | 511 | .708 | .455 | 0 | 1 | ||||||||
Exposure to the city (1 = Yes, 0 = No) | 511 | .691 | .463 | 0 | 1 | ||||||||
Belonging to a cooperative or a trade union (1 = Yes, 0 = No) | 511 | .09 | .286 | 0 | 1 | ||||||||
Access to information factor score | 511 | 0 | .979 | -1.508 | .675 | ||||||||
Taken a new job or invested more to improve livelihood | 511 | .656 | .476 | 0 | 1 | ||||||||
Request for aid to deal with difficulties | 511 | .456 | .499 | 0 | 1 | ||||||||
Taken loan to deal with difficulties and maintain food stocks (1 = Yes, 0 = No) | 511 | .235 | .424 | 0 | 1 | ||||||||
Adjusted the quantity of food to survive the price increase (1 = Yes 0 = No) | 511 | .691 | .463 | 0 | 1 | ||||||||
Preparedness and readiness | 511 | 0 | .698 | -1.403 | .67 | ||||||||
Satisfaction to the organization of fishery staffs (1 = Yes, 0 = No) | 511 | .806 | .396 | 0 | 1 | ||||||||
Existence of a fishery administrative centre/personnel (1 = Yes, 0 = No) | 511 | .74 | .439 | 0 | 1 | ||||||||
Support with fishing tools or any form of subvention (1 = Yes, 0 = No) | 511 | .83 | .376 | 0 | 1 | ||||||||
Community governance factor score | 511 | 0 | .91 | -1.775 | .516 | ||||||||
Aids to address food crisis (1 = Yes, 0 = No) | 511 | .386 | .487 | 0 | 1 | ||||||||
Remittances to address health issues (1 = Yes, 0 = No) | 511 | .456 | .499 | 0 | 1 | ||||||||
Did attend fishery training programs (1 = Yes, 0 = No) | 511 | .548 | .498 | 0 | 1 | ||||||||
Governance control or administrative control (1 = Yes, 0 = No) | 511 | .74 | .439 | 0 | 1 | ||||||||
Social safety nets | 511 | 0 | .569 | − .734 | .94 | ||||||||
Do you poses a fishery lining (1 = Yes, 0 = No) | 511 | .489 | .5 | 0 | 1 | ||||||||
Do you have a fishery trawler (1 = Yes, 0 = No) | 511 | .186 | .389 | 0 | 1 | ||||||||
Do you have a seine net (1 = Yes, 0 = No) | 511 | .957 | .203 | 0 | 1 | ||||||||
Do you have a gill net (1 = Yes, 0 = No) | 511 | .652 | .489 | 0 | 1 | ||||||||
Do you have fishing pots/traps (1 = Yes, 0 = No) | 511 | .542 | .499 | 0 | 1 | ||||||||
Do you have other fishing gear (1 = Yes, 0 = No) | 511 | .094 | .292 | 0 | 1 | ||||||||
Do you raise livestock (1 = Yes, 0 = No) | 511 | .202 | .402 | 0 | 1 | ||||||||
Do you practice agriculture (1 = Yes, 0 = No) | 511 | .658 | .475 | 0 | 1 | ||||||||
Households assets in fishing communities | 511 | 0 | .692 | − .565 | 2.281 | ||||||||
Table 12 reveals a mean of only 0.09 (9%) presently belonging to a fishing cooperative in Cameroon fishing communities. In addition, it reveals a 0.54 mean for having attended/participated in fishery training programs. This signifies an important dimension of social capital that only 9% of households in the 511 fishermen households belong to a cooperative or a fishing union that promotes fishermen’ activities. Similarly, another important social capital indicator is that of remittances received of any form, with the mean indicating that 45% of the households have benefited from remittances, indicating an important social capital contribution. For the human capital dimension, the average number of years for the fishermen or farmers is 7.589, with a maximum of 25 possessing a PhD degree. 70% accepted to possess at least a first school certificate of a professional diploma, with 30% accepting to never completed primary school and not have a professional degree.
Figure 6 indicates that households in maritime environments are more vulnerable to shocks, and have less access to social safety nets and basic services that could support their livelihood and help them build strong adaptive capacities against shocks from the environment and the socioeconomic system.
Fig. 6
Households’ resilience predictive margins in Cameroon fishing communities
(1) | (2) | |
|---|---|---|
VARIABLES | HRI (Marine environment) | HRI (Inland environments) |
Fish revenue | 0.0397*** | 0.0469*** |
(0.0266) | (0.0177) | |
Fishing efforts | 0.0188* | -0.0653*** |
(0.0108) | (0.0122) | |
Fishing authorization | 0.430*** | 0.385*** |
(0.0422) | (0.0426) | |
Control variables | Yes | Yes |
Observations | 483 | 483 |
chi2_c | 28.90 | 28.90 |
Log likelihood | -248.3 | -248.3 |
Wald chi2(11) | 199.9 | 199.9 |
Prob > chi2 | 0.0000*** | 0.0000*** |
Standard errors in parentheses / *** p < 0.01, ** p < 0.05, * p < 0.1
In Table 13, three key factors affecting the resilience of households in the fishing sector are examined. These factors include revenue from fishing sales, fishing authorisation or permit and fishing efforts. The study reveals that revenue from fishing sales has a positive and statistically significant impact on the resilience of households in fishing communities in Cameroon, both in marine and inland environments. The income derived from fishing enables households to maintain a stable food supply, access healthcare, and build economic resilience to withstand economic shocks, such as rising food prices due to events like the Ukraine-Russian war. These findings are consistent for both residents and immigrants, highlighting the vital role of the fishing industry as a source of livelihood for thousands of people in Cameroon and neighbouring countries. In this study, it is found that the amount of time spent (fishing efforts) has a positive impact on households’ resilience in marine environments and leads to a significant decrease in resilience capacity of households operating in inland environments. It was observed that spending an additional hour fishing in a marine environment can be more profitable, as there are more fish available compared to inland bodies of water. Additionally, having a fishing permit was found to enhance households’ resilience capacity in Cameroon’s fishing communities. This indicates that being registered and having a fishing permit contribute to increased resilience.
3.3.4. Fishery species sustainability
This section presents characteristics in terms of descriptive analysis of the variable used, explaining the fish species depletion responses from fishermen and fish farmers’ ecological footprint in fish farming. Table 14 presents responses on fish species depletion by 511 fishermen and fish farmers in 25 fishing communities in Cameroon.
Fishing type/environment | I have witnessed a decrease or loss of some fishery species | |||||
|---|---|---|---|---|---|---|
Strongly disagree | Disagree | Neutral | Agree | Strongly Agree | Total | |
Marine fishing | 37 | 25 | 44 | 99 | 41 | 246 |
Inland fishing | 27 | 18 | 39 | 83 | 41 | 208 |
Aquaculture | 6 | 17 | 15 | 15 | 4 | 57 |
Total | 70 | 60 | 98 | 197 | 86 | 511 |
Percentage | 13.69% | 11.74% | 19.18% | 38.55% | 16.83% | 100 |
| Source: Author’s computation | ||||||
Table 14 indicates that 56% of the respondents confirmed that they have witnessed a decrease in the quantity of fish or the disappearance of some fish species at their fishing sites in Cameroon. This represents 283 respondents in a sample size of 511 fishermen and fish farmers. In addition, only 25% of respondents disagreed with the loss of fish species or a decrease in fishery products, while 19% were doubtful on their assessment, as they neither saw an increase nor a decrease. Table 15 also presents other sustainability indicators, depicting that 74.5% households reported witnessing fish species depletion.
Did fishery species suffer from bacterial diseases in the past year? | |||||||
|---|---|---|---|---|---|---|---|
Freq. | Percent | Valid | Cum. | ||||
0 No | 381 | 74.560 | 74.560 | 74.560 | |||
1 Yes | 130 | 25.440 | 25.440 | 100.000 | |||
Total | 511 | 100.000 | 100.000 | ||||
Fish species were affected by insufficient feed | |||||||
Freq. | Percent | Valid | Cum. | ||||
2 Disagree | 63 | 12.330 | 12.330 | 12.330 | |||
3 Neutral | 117 | 22.900 | 22.900 | 35.230 | |||
4 Strongly disagree | 188 | 36.790 | 36.790 | 72.020 | |||
5 Strongly Agree | 143 | 27.980 | 27.980 | 100.000 | |||
Total | 511 | 100.000 | 100.000 | ||||
Fishing gear cause harm to fish species | |||||||
Freq. | Percent | Valid | Cum. | ||||
2 Disagree | 72 | 14.090 | 14.090 | 14.090 | |||
3 Neutral | 107 | 20.940 | 20.940 | 35.030 | |||
4 Strongly disagree | 200 | 39.140 | 39.140 | 74.170 | |||
5 Strongly Agree | 132 | 25.830 | 25.830 | 100.000 | |||
Total | 511 | 100.000 | 100.000 | ||||
| Source: Author’s computation | |||||||
The empirical results elucidating how fishing activities affect the sustainability of fisheries resources are presented in Table 16. The results of the ordered Probit model, taking into account the global sample in aquaculture, inland, and marine environments, are shown in Table 16. The marginal effects of the corresponding model are analyzed because the values of an ordered Probit model may not accurately reflect the magnitude of the effect on the dependent variable. According to the estimated model, the Chi2 has a significant value of 135.58 at 1%. The model fits the selection of the fishery sustainability determinants better, as indicated by the likelihood estimation parameter, and it can be used to recommend policies.
(1) | (2) | (3) | (4) | (5) | (5) | |
|---|---|---|---|---|---|---|
VARIABLES | Fish species depletion | No depletion | Lowly depleted | A neutral scenario | Highly Depleted | An extreme depletion |
Fishing efforts | 0.0716*** | -0.0132*** | -0.00627* | -0.00484*** | 0.00893*** | 0.0154*** |
(0.0177) | (0.00309) | (0.00327) | (0.000107) | (0.00340) | (0.00306) | |
Fish harvested | -0.00107 | 0.000198 | 9.35e-05 | 7.22e-05 | -0.000133 | -0.000230 |
(0.00233) | (0.000429) | (0.000230) | (0.000142) | (0.000309) | (0.000492) | |
Environmental stringency | -0.973*** | 0.180*** | 0.0853* | 0.0659*** | -0.121*** | -0.210*** |
(0.244) | (0.0426) | (0.0447) | (0.00169) | (0.0467) | (0.0423) | |
Control variables | Yes | Yes | Yes | Yes | Yes | Yes |
Observations | 510 | 510 | 510 | 510 | 510 | 510 |
Chi2 | 135.58 | 510 | 510 | 510 | 510 | 510 |
Prob > chi2 | 0.0000*** | -700.6 | -700.6 | -700.6 | -700.6 | -700.6 |
Log pseudolikelihood | -706.349 | 0.0887 | 0.0887 | 0.0887 | 0.0887 | 0.0887 |
Pseudo R2 | 0.0807 | 2.897 | 2.897 | 2.897 | 2.897 | 2.897 |
| Robust standard errors in parentheses | ||||||
| *** p < 0.01, ** p < 0.05, * p < 0.1 | ||||||
Table 16 displays the marginal effects of the ordered Probit model. It indicates that fishing efforts in the Cameroon fishery bodies, including marine, inland dams, and aquaculture, increase the likelihood of fishery depletion. This is possible, given that overfishing and the extinction of fish species can arise from excessive efforts made in fisheries bodies. This occurs more frequently in inland bodies of water, which have fewer species, compared to marine waters that host a greater diversity of fish species. When people fish for an hour longer in Cameroon waters, there is a 0.0154 probability that an extreme case of fish depletion will occur. Furthermore, a reduction of one hour in fishing effort by individuals in these fishing communities is associated with a decreased probability (P = 0.0132) of species depletion. The amount of fish that these small-scale fish farmers and artisanal fishermen harvest is negligible in relation to the depletion of fish species. Inland fishing logically has less impact on species depletion than marine fishing, particularly since it does not occur at high sea levels. Furthermore, the results suggest that the degree to which government officials in fishing communities enforce strict administrative controls also lessens the possibility of fishery depletion in fishing communities in Cameroon. There is a very low probability (P = 0.0210) of experiencing a very high fishery species depletion, with a more likely probability of no fishery species depletion (P = 0.180).
4. Conclusion and Policy Recommendation
4.1 Conclusions
This study assessed the activities of the fishery sector and their role in enhancing livelihood sustainability. It focused on livelihood outcomes, including food and nutrition security, health performance, fishery sustainability, and households’ resilience capacity. This is focused on the characteristics of 511 surveyed households engaged in fishing and fish farming across 25 fishing communities in Cameroon. The study employed descriptive analysis, conditional mixed process (CMP) probit, and bivariate probit models for the regression analysis. The empirical analysis indicates that individuals fishing in marine environments harvest an average of 3,960.543 kilograms of fish per year, while those fishing in inland environments average 3,001.332 kilograms annually. Aquaculturists, on average, harvest 1,908.368 kilograms per year. According to the survey results, fishing in Cameroon is a viable business, particularly during times of favourable harvests for marine fishermen's households. The average household income from fishery sales is notably higher among marine fishermen, with annual revenues exceeding 7 million FCFA for about 38% of respondents. Despite this economic contribution, only 9% of households are members of fishery cooperatives, and fewer than half have received any formal training, highlighting significant gaps in social and human capital.
The findings indicate that 56.2% of households in these communities are food secure, while 43.8% experience different levels of food insecurity. Specifically, 21.92% are mildly insecure, 19.96% are moderately insecure, and 1.96% are severely insecure, as measured by the Household Food Insecurity Access Scale (HFIAS). The CMP ordered probit regression findings further reveal that fishery activities enhance their food security status and health performance. Additionally, the survey reveals that 33.66% of respondents reported being in poor or uncomfortable health, while 16% classified their health as excellent. Overall, these findings suggest improved living conditions, although many households (46%) do not receive training to help them cope with environmental changes along the coast, leaving them vulnerable to shocks. For the regression analysis assessing the prevalence of food insecurity among households, the CMP ordered probit model was used. The findings indicate that the fishery sector contributes to enhancing food security by reducing the prevalence of food insecurity.
Additionally, the results reveal that income from fishery sales, measured in FCFA, lowers the likelihood of households experiencing poor physical and mental health outcomes, as shown in a CMP bivariate probit analysis. Furthermore, regarding resilience capacity, the empirical analysis demonstrates that revenue from fishing sales has a positive and statistically significant impact on the resilience of households in fishing communities in Cameroon, both in marine and inland environments.. In addition, the findings further reveal that regardless of their social origin as immigrants or citizens of Cameroon, income from fish sales enhances resilience. The results show that 56% of respondents have observed a decrease in the quantity of fish or the disappearance of certain fish species at their fishing sites in Cameroon. Moreover, the findings demonstrate that the quantity of fish harvested negatively affects fishery sustainability in marine environments than in inland waters. This discrepancy is attributed to inadequate supervision along the coast, highlighting the need for state intervention to promote sustainability.
4.2 Policy Recommendation
This study has the potential to significantly impact policy research aimed at improving the livelihoods of immigrants and internally displaced individuals, particularly those in fishing communities. By focusing solely on Cameroon, this research can also be relevant to other communities around the world that engage in fishing. Additionally, it highlights the importance of such studies in raising public awareness about fishing potential and how effective management of this resource can enhance livelihoods. The survey contains data that demonstrate the challenges faced by immigrant fishermen due to their national status. This study and the survey contribute to research that empirically shows how both immigrant fishermen and internally displaced individuals can find a sense of belonging in the region.
In light of the study’s conclusions and due to the sector’s significance, we advise policymakers to tighten environmental regulations and expand their oversight to guarantee sustainable fishing practices for future fish food security. In addition, from the findings indicating the importance of fishery training programs in reducing health vulnerabilities, we recommend that fishing delegations extend fishery training programs to teach eco-friendly fishing practices and supervise fishermen implementing them. Also, the government is called upon to subsidize by providing fishing equipment to fishermen and fish farmers to boost their activities, particularly for fish farmers as many abandoned the activity due to high operating costs and lack of funds. In light of the study’s conclusions and due to the sector’s significance, households are advised to focus on other activities in periods of non-harvest to maintain their adaptive capacity for heightened resilience. It is advised that policymakers maintain control over this industry to guarantee its sustainability since it is clear that it improves households’ livelihood sustainability.
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Appendix 1: Survey team
Coordination and general supervision:
Prof: Roger Tsafack Nanfosso
Dr. Armand Mboutchouang Kountchou
Dr. Wirajing Muhamadu Awal Kindzeka
Field agents:
Wirajing Muhamadu Awal Kindzeka
Tardzenyuy Fidelis
Ali Haruna
Eric Bongfen
Wirajing Usmaila
Kihla Bisharatu
Alang Ernest Wung
Mr. Dauda
Abdu Samad Fondzenyuy
Devine holyson
A
Fig. A1
The legal status of households in the Cameroon fishing sector
SURVEY QUESTIONNAIRE
A SURVEY ON CAMEROON FISHERIES AND LIVELIHOOD SUSTAINABILITY (CAMFISHLIST)
Presentation of the study: The answers that you will provide to the questions asked will be pooled and analysed globally for the writing of a Ph.D. theses whose purpose is to investigate the effect of the Cameroon fisheries sector on livelihood sustainability. The livelihood dimensions in these studies are: food security, health and education status and environmental livelihood inspired by the DFID (1990) and the FAO (2012) reports. Fisheries output has increased considerably since the introduction of the pond fishing system in 1948 in Cameroon. As a result of this growth, the sector recruits more than 240000 Cameroonians and contributes approximately more than 20% of animal protein in Cameroon. In this regard though with its environmental impact, we seek to know how it has really affected livelihoods sustainability in Cameroon.
Confidentiality: The information collected during this survey shall be kept confidential in accordance with Articles 13 and 14 of Law N°2020/010 of 20 July 2020 governing statistical activity in Cameroon. This information cannot be used for legal proceedings or economic repression.
NO | Questions and filters | Codes | |
|---|---|---|---|
0Q1 | Name of investigator | ||
0Q2 | Region of data collection 1. Centre 2. East 3. Littoral 4. Northwest 5. South 6. Southwest 7. West 8. Adamawa |___| | ||
0Q3 | Survey city: 1. Bamenda 2.Ndop 3.Kumbo 4. Bafoussam/Mbouda 5.Dschang 6.Foumban 7.Magba 7.. Bertoua 8. Buea 9.Limbe 5. Douala 6. Ebolowa 7. Yaoundé, 8. Ngaoundere |___|___| | ||
0Q4 | Survey location (village/quarter/neighbourhood) | ||
0Q5 | Date of interview Day|___|___|| Month|___|___| | ||
0Q6 | Type of fisheries 1.Semi-industrial 2. Artisanal |___| | ||
0Q7 | The type of fishing environment 1.Inland (pond culture) 2.Marine bodies (sea, ocean dams etc) |___| | ||
0Q8 | Have you been offered a fishing license 1.Yes 2.No If No skip to A1Q1 |___| | ||
0Q9 | At what level was this license permit issued? 1. Ministry 2. Regional office of fisheries 3. Divisional/Sub divisional level |___| | ||
Module 0: General Information
Module A1: Fish farmers households’ educational status
NO | Questions and filters | Codes | |||||
|---|---|---|---|---|---|---|---|
A1Q1 | Number of years in schooling of the fish farmer? | |__||__| | |||||
A1Q2 | A.What is your highest diploma? B. What is the highest diploma in the household | 1. No diploma 2. 1st school leaving 3. GCEO/CAP 4 = Probatoire/BP 5. GCEA/BAC | 6. HND/BTS/ 7.Bachelors 8. Masters and above 9. Others and specify (Specify).......................................... |
| |||
A1Q3 | How many people of schooling age do you have in your household in number? | |__||__| | |||||
A1Q4 | How many households’ members attend school in the last academic year who are not your children but under your care? | |__||__| | |||||
A1Q5 | Did any member of your household fail not to attend school regularly in the last academic year? 0. No 1. Yes If no skip to (A108) | |__| | |||||
A1Q6 | How many households’ members did not regularly attend school in the last academic year? | |__| | |||||
A1Q7 | Was this the main reason for not attending schooling the last academic year? 1. Yes 0. No | A. Illness/handicap B. Difficulties in paying fees C. Could not afford the transport fee D. Early marriages | E. Absence of trained teachers F. Poor school facilities G. Others (Specify)................................. | |___| | |||
A1Q8 | Did your households’ members have their school needs (textbooks, uniforms etc)? 1. Yes 2. No | |__| | |||||
A1Q9 | Was there any school dropped out in your household’ last year ? 1. Yes 2. No | |__| | |||||
A1Q10 | Did you finance households’ education from money gotten from fisheries sales? 1. Yes 2. No | |__| | |||||
A1Q11 | Did fishing contribute in the type of schools your households’ members attend? 1. Yes 2. No | |__| | |||||
A1Q12 | Did the educational performance of your households’ members improve in the last ac year? 1. Yes 2. No if No skip to A114 | |__| | |||||
A1Q13 | Did the fishery activities contribute to this performance in anyway e.g. School needs etc ? 0. No 1. Yes | |__| | |||||
A1Q14 | Do you have a child in the following levels of education? (If more than 1 at each level, select the child with the most years in school 1. Yes 2. No A. Primary………. B. Secondary ……….. C.Tertiary ……….. | |__| | |||||
A1Q15 | What was their average performances in terms of 1. Poor 2. Average 3. Good 4. Very good 5. Excellent A. Primary………. B. Secondary ……….. C. Tertiary ……….. | |__| | |||||
A1Q16 | Which sector is the child enrolled? 1. Private 2. Public 3. Mission school 4.Community school A. Primary………. B. Secondary ……….. C. Tertiary ……….. | |__| | |||||
A1Q17 | Which system/section is the school? 1. Anglo-Saxon 2. French-system 3.Bilingual A. Primary………. B. Secondary ……….. C. Tertiary ……….. | |__| | |||||
N | Assertion/Questions | Never | Rarely | Sometimes | Often | Most often | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
A201 | Food access | A. In the past 12 months, did you worry that your household would not have access to sufficient food? | |___| | |___| | |___| | |___| | |___| | |||||||||||||
B. In the past 12 months, did you or any household member have to eat a limited variety of foods due to a lack of resources? | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
C. In the past 12 months, did you or any household member have to eat some foods that you really did not want to eat because of a lack of resources to obtain other type of food? | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
D. In the past 12 months, was there ever no food to eat of any kind in your household because of lack of resources to get food? | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
A202 | Food availability | A. In the past 12 months, did you or any household member go a whole day and night without eating anything because there was not enough food? | |___| | |___| | |___| | |___| | |___| | |||||||||||||
B. In the past 12 months, did you or any other household member have to eat fewer meals in a day because there was not enough food? | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
C. Did you have any anxiety that the household food budget or food supply may be insufficient for a better food intake in the past 12 months? | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
D. In the past 12 months, were you or any household member not able to eat the kinds of foods you preferred because of a lack of resources? | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
A203 | Food Stability | A. In the past 12 months, was there any experience of running out of food, without money to obtain some in your household? | |___| | |___| | |___| | |___| | |___| | |||||||||||||
B. In the past 12 months, did you or any other household member have to eat fewer meals in a day because you are worry that food will run out before we have money to buy some? | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
C. The food we buy at times just didn't last, and there wasn't any money to get more. | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
A204 | Food usage | A. In the past 12 months, we most often relied on only a few kinds of low-cost food to feed the household? | |___| | |___| | |___| | |___| | |___| | |||||||||||||
B. In the last 12 months, did you or other members in your household ever cut the size of your meals or skip meals because there wasn’t enough money for food? | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
C. Sometimes people lose weight because they don’t have enough to eat. In the last 12 months, did you lose weight because there wasn’t enough food? | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
COVID/Ukraine/CAF/Food Security | ||||||||||||||||||||
N | Assertion/Questions | Strongly disagree | Disagree | Neutral | Agree | Strongly agree | ||||||||||||||
A2Q5 | Covid-19 | A. As a fish farmer, fisheries products helped to maintain my households’ food intake and nutrition level during the Covid-19 pandemic | |___| | |___| | |___| | |___| | |___| | |||||||||||||
B. The quarantine/confinement period during the Covid-wave did not affect the food stocks in your households | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
C. The Covid-19 did not hinder any household member from eating the kinds of foods he/she preferred because of a lack of resources | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
D. Your household’s members consumed more fish during the Covid-19 period than ever | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
A2Q6 | Ukraine-CAF | A. The Ukraine-Russia war affected your household’ food intake. | |___| | |___| | |___| | |___| | |___| | |||||||||||||
B. Fisheries products have helped your household to maintain the same food stocks during to the Ukraine Russia war? | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
C. My household consumption of fisheries products has helped to overcome the increase in prices of goods? | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
D. The quality and the quantity of foods consumed during the CAF in Cameroon was reduced because of increase in prices of foodstuffs. | |___| | |___| | |___| | |___| | |___| | |||||||||||||||
Module A3: Households’ Health
N | Assertion/Questions | Very poor | Poor | Some what | Good | Very good | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
A3Q1 | Performance | ___| | |___| | |___| | |___| | |___| | |||||||||
A. In the past 12 months, generally, would you say your quality of life was: | |___| | |___| | |___| | |___| | |___| | ||||||||||
B. In general, how would you rate your physical health | |___| | |___| | |___| | |___| | |___| | ||||||||||
C. Rate your mental health, including your mood and your ability to think | |___| | |___| | |___| | |___| | |___| | ||||||||||
Health access | Never | Rarely | Sometimes | Most often | Always | ||||||||||
A302 | Health care | A. How often do you stay informed with current health care advancements? | |___| | |___| | |___| | |___| | |___| | ||||||||
B. In the past 12 months, How often do your household members go for check-up: | |___| | |___| | |___| | |___| | |___| | ||||||||||
C. how often do the member of your household receive health care coverage program. | |___| | |___| | |___| | |___| | |___| | ||||||||||
Heart failure | |||||||||||||||
A3Q3 | A. How often do your experience shortness of breath in activity | |___| | |___| | |___| | |___| | |___| | |||||||||
B. How often do your experience shortness of breath at rest | |___| | |___| | |___| | |___| | |___| | ||||||||||
C. How often do your experience breath difficulty when sleeping | |___| | |___| | |___| | |___| | |___| | ||||||||||
A3Q4 |
Do you have any kind of healthcare coverage, including health insurance, programs with Heath maintenance Organs for medical care? | |___| | |||||||||||||
A3Q5 |
Was there a time during the last 12 months when you needed to see a doctor, but could not because of the cost? | |___| | |||||||||||||
A3Q6 | Was any case of illness registered in the household in the last 12 months? 1. Yes 2. No ◊ if no skip A3Q4 |___| | ||||||||||||||
A3Q7 | If Yes, which type of sickness? A. B. C. See code ◊ S | ||||||||||||||
A3Q8 |
Did he/she consult? 1. Yes 2. No ◊ | |___| | |||||||||||||
A3Q9 |
Who did (Name) consult last time? | ||||||||||||||
A3Q10 |
In which sector did he/she consult? 1. Public 2. Para public | |___| | |||||||||||||
A3Q11 |
What was the main reason of this choice? See codes ◊ C | |___| | |||||||||||||
A3Q12 |
Did the situation improve with time? | |___| | |||||||||||||
A3Q13 |
How do you appreciate your present state of health? | |___| | |||||||||||||
A3Q14 |
Did the income from fisheries sales helped to maintain your health care During the Covid-19 period? | |___| | |||||||||||||
A3Q15 |
Does fishing make you happy? | |___| | |||||||||||||
A3Q16 |
Appreciate your happiness level as a fish farmer ? 1. Very poor | |___| | |||||||||||||
A3Q17 | Estimate your households daily meals ………… In numbers | ||||||||||||||
| Code W: Health services providers 01 = Pharmacist 02= Medical doctor 03 = Health personnel (Midwife nurse) 04 = Traditional healer 05 = Religious (e.g. pastors, imams etc) 06 = Others …Specify | Code C: Choice 01 = Affordable Cost 02= Proximity 03 = Family decision 04 = Custom/belief 05 = Quality of services 06 = Relations 07 = Others | |||||||||||||
B1: Fisheries information
B1Q1 | For how long have you been practicing fishing (in years) | |
|---|---|---|
B1Q2 | Have you sold fish for income generation? | 1 = YES (continue below) 2 = NO (skip to B104) |
B1Q3 | Approximately how much of your total household income is from selling farmed fish? | 1 = None 2 = A small amount 3 = Some of it 4 = Most of it 5 = Almost all |
B1Q4 | Approximately, how many fish production cycles have you completed in the last 12 months? | Number |
B1Q5 | In the past 12 months, approximately how much total fish was produce? | Kilograms (kg) |
B1Q6 | Approximately how much of your harvest did your household consume as food? | 1 = None 2 = A small amount 3 = Some of it 4 = Most of it 5 = Almost all |
B1Q7 | In the past 12months, have you employed a worker apart from a household member? | 1. Yes 2. No |
B1Q8 | How many people have you employed in your fishing activities? If no employee skip to B111 | In number |
B1Q9 | On average, how much do you pay each employee? | Amount in FCFA |
B1Q10 | Do you respect the minimum wage rate of Cameron? | 1. Yes 2.No |
B1Q11 | Rate the well-being of your employees.1. Very poor, 2. Poor 3..Neutral 4. Good 5. Verygood | |
B1Q12 | Are you part of any farmers association or a trade union | 1. Yes 2. No |
B1Q14-16. Income and sources
14. Is the following an important source of income to your household? 15. Which is the first important source of income 16. Which is the first important source of income 15. How much do you earn from this activity/activities? | Sources (1. Yes 2.No) | Amount |
1. Sale of fisheries products from marine environments | ||
2. Sale of fisheries products from ponds and cages | ||
3. Sale of agricultural products like crops | ||
4. Sales from livestock, e.g. poultry, cows etc. | ||
5. Sale or rent from land and equipment | ||
6. From services rendered (e.g. wages etc.) | ||
7. Remittances (aids) | ||
8. pension/employment benefits | ||
9. Others ……. specify |
Fish Species and Codes | Aquaculture Facility and system | Feed | How much did you produce? | Did you sell any from the last production cycle? | Sales of FISH | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Number and type of Fish species | Code: Facility | Average period before harvest in months | Feed source code | Quantity (kg) | 1 = YES, 2 = NO (skip to next species) | Quantity (kg) | Average price / Competition | |||||||
FISH SPECIES | B2Q1 | B2Q2 | B2Q3 | B2Q4 | B2Q5 | B2Q6 | B2Q7 | B2Q8 | B2Q9 | B2Q10 | ||||
A- tilapia | ||||||||||||||
B-Catfish | ||||||||||||||
C- Carp fish | ||||||||||||||
D- Bony Tongue | ||||||||||||||
E Banded Jewel | ||||||||||||||
F. Sneak head fish | ||||||||||||||
F. Others | ||||||||||||||
Fish species codes (B2Q2): 1 = Tilapia 7.Others 2 = Catfish 3 = Carp fish 4 = Bony Tongue 5 = Banded Jewel 6 = Sneak head fish | Facility codes (B2Q3): 1 = Fish pond 2 = Rice/fish intercrop 3 = Community fishery 4 = Cage fishing 5 = Other (please specify) | Feed type codes (B2Q4): 1 = Purchased feed 2 = Feed provided 3 = Homemade feed 4 = Trash fish only B2Q10. (Competition ratings) 1. Very low 2. Low 3. Neutral 4, High 5. Very High. | ||||||||||||
Fisheries gears/efforts | Codes | |||||||||||||
B2Q11 | How many hours do you fish per day? | |___| | ||||||||||||
B2Q14 | Does it cause loss or dead of fisheries after harvest for untargeted species? 1.Yes 2.No If No skip B2Q15 | |___| | ||||||||||||
B2Q14A | If yes, estimate in quantity (kilograms). | |||||||||||||
B2Q15. | Does it give by-catch during harvest ?1.Yes 2.No If No skip B2Q15 | |||||||||||||
B2Q15A | Estimate in kilograms (kg) | |___| | ||||||||||||
B2Q16 | Have you improved on how you use this gear since you began fishing 1.Yes 2.No | |||||||||||||
Fishing gears code G: 1. Seine fishing 2. Gill netting 3. Trawling 4. Pots/Traps 5. Lining 6. Spear gun/ poisoning 7. Others | ||||||||||||||
B2Q17 | Do you sell live/fresh fish to bulk buyers? 1.Yes 2.No | |||||||||||||
B2Q18 | What is the average price per live/fresh fish sold to bulk buyers? (FCFA) (per kg) | |||||||||||||
B2Q19 | What is the quantity sold of live/fresh fish? (In kg) | |||||||||||||
B2Q20 | Do you sell smoked fish to bulk buyers? 1.Yes 2.No | |||||||||||||
B2Q21 | What is the average price per smoked fish sold to bulk buyers? (FCFA) | |||||||||||||
B2Q22 | What is the quantity sold of smoked fish (In Kg) | |||||||||||||
B2Q23 | Estimate your pond size in meters A. Length ………. B. Width……………. | |||||||||||||
B3. Fisheries inputs and cost
Input Type and Code | Do you use [INPUT TYPE] in fish? 1 = YES 2 = NO ( > > next type) | What was the source? (Source code list) | If purchased, how much did you pay in total? (Riels) | |
|---|---|---|---|---|
If the household produced any type of fish (B2), complete the table below | code | |||
INPUT TYPE | A | B | ||
Setup cost (pond, facility, equipment, etc.) | B3Q1 | |||
Fingerlings | B3Q2 | |||
Commercial fish feed | B3Q3 | |||
Fertilizer or compost | B3Q4 | |||
Hired labour | B3Q5 | |||
Other (specify) | B3Q6 | |||
Source codes: 1 = Own (self-produced) 2 = Purchased | 3 = Provided free by another program (NGO or government) 4-Provided free by friend, neighbour, or family 5 = Others, specify.. | |||
How likely did you use these fish farming technologies ?
Code | Fishing technologies | Very unlikely | Unlikely | Neutral | likely | Very likely |
|---|---|---|---|---|---|---|
B3Q7 | Aquaculture in fish ponds | |||||
B3Q8 | Use of fingerlings | |||||
B3Q9 | Commercial fish feed | |||||
B3Q10 | Applications of fertilizer | |||||
B3Q11 | Use of lime | |||||
B3Q12 | Fencing fishing | |||||
B3Q13 | Internet of things | |||||
B3Q14 | Computer for recording fishery harvest | |||||
B3Q15 | Internet for fishery research | |||||
B3Q16 | Online marketing |
B4Q1. Do you feel you can improve your fish yield by adopting the new technologies (provided above) and modify your way of normal practice? | 1 = YES 2 = NO | |
|---|---|---|
B4Q2. Do you believe that there are barriers to fully adopt these aquaculture Technologies. | 1 = YES 2 = NO |
B4. Fisheries perception about prevailing technologies
Please indicate the extent of how difficult these barriers are
(from 1 = To no extend to 5 = A very large extent):
Barriers to adoption of new/improved farming practices or technologies | 1 = To no extent, 2 = To little extent3 = To some extent 4 = To a large extent 5 = To a very large extent | |
|---|---|---|
B4Q3 | Difficulties in accessing fingerlings | |
B4Q4 | High price of fingerlings | |
B4Q5 | Difficulties in accessing fish feed | |
B4Q6 | High cost of fish feed | |
B4Q7 | Selling price of fish in markets | |
B4Q8 | No fish markets | |
B4Q9 | Shortage of water | |
B4Q10 | I do not know the new technology | |
B4Q11 | I do not understand the new technology | |
B4Q12 | Adoption of the new technology does not make any differences | |
B4Q13 | The fish farming technology is not suitable to my operation. | |
B4Q14 | I cannot get credit needed to adopt the new technology. | |
B4Q15 | I do not own the land where I raise fish. | |
B4Q16 | My fish farming operation is too small. |
B5. Environmental livelihoods and Management control
N | Assertion/Questions | Strongly disagree | Disagree | Neutral | Agree | Strongly agree | ||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Environmental livelihood | ||||||||||||||||||||||||||||
B5Q1 | Ecological footprint | A. waste discharge from aquaculture production causes damages to the environment | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||
B. The production system for fisheries products in this region deplete freshwater supplies and/or degrade freshwater bodies. | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
C. The production system for these species in this region distorts habitat functionality | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
D. In general, the type of production have direct negative growth or ecological impacts on other animals | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
E. Fisheries species do suffer from viral or bacterial disease outbreaks. | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
F. The fisheries production system rely on chemical usage and are associated with risks that impacts the environment. | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
G. Fishing gears use for fishing cause harm to your fishery species | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
H. Fisheries species are mostly affected by insufficient feeds | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
I. Polluted water from fisheries pollutes neighbouring farmland | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
J. I harvest a large quantity of by-catch during the harvest period | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
K. There is always a high fish discards during fish harvest | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
B5Q2 | Kuznets /MSY | A. I practice unsustainable fishing by harvesting undersized species for the purpose of income generation. | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||
B. I have fished more than the quantity that can permit the species to replenish its population naturally. | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
C. I have witnessed a decrease of some fisheries species (population) in quantity. | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
D. In general, the method of harvesting is polluting the neighbouring land when irrigated. | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
E. I have registered depletion of fish species. | ||||||||||||||||||||||||||||
F. In the past 12 months, I have witnessed a land degradation (eroded, polluted,, less productive land or soil) | ||||||||||||||||||||||||||||
B5Q3 | Climate change | A. There has been an increase in the temperature in the environment in the past 12 months | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||
B. There was a sort of an increase in air pollution in the past 12 months. | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
C. There was an experience of landslide in the past 12months | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
D. Climate change threatened the health and safety of your households | |___| | |___| | |___| | |___| | |___| | |||||||||||||||||||||||
E. There was loss of land and air biodiversity / Depletion of species (land animals, birds, plants, trees, insects, mushrooms, seeds) | ||||||||||||||||||||||||||||
F. I witnessed water scarcity (reduced availability over extended periods) | ||||||||||||||||||||||||||||
G. There was a decreased overall precipitation in the last 12months | ||||||||||||||||||||||||||||
H. There was a drop in the water level (fisheries bodies dryness) | ||||||||||||||||||||||||||||
I. Fishery bodies were overflown by water during the rainy season (flood) | ||||||||||||||||||||||||||||
NO | Fisheries management and control | Codes | ||||||||||||||||||||||||||
B5Q4 | Have you received any training to efficiently manage your fisheries activities? 1. Yes 2. No i B506 | |___| | ||||||||||||||||||||||||||
B5Q5 | If yes from which organisation 1. Governments 2. Fellow fish farmer 3. NGO/FAO 4. Others (Specify).... | |___| | ||||||||||||||||||||||||||
B5Q6 | Are you aware of the measures put by the government to regulate fisheries activities? 1. Yes 2. No in no skip to B507 | |___| | ||||||||||||||||||||||||||
B5Q7 | How effective are these measures in improving fisheries management 1. Not effective 2. Neutral 3. Slightly effective 4.fairly effective 5. Very effective | |___| | ||||||||||||||||||||||||||
B5Q8 | Have you ever received any grant (support) from the government to boost your fisheries activities? 1. Yes 2. No If No, C101 | |__| | ||||||||||||||||||||||||||
B5Q9 | Did the subvention/support improve your fisheries productivity? 1. Yes 2. No If no skip to B5Q12 | |__| | ||||||||||||||||||||||||||
B5Q10 | To what extent did the subvention/motivation improve your fisheries productivity | 1. Very low 2. Below average | 3. Average 5. Above average 4. Neutral | |___| | ||||||||||||||||||||||||
B5Q11 | In a scale of 1 to 5, how do you rate your fishing activities: choosing between 1, Very low, 2; low 3; Neutral, 4;High, 5; Very High | A. Productivity ……. B. The profitability …..... | C. The species replenishment …….. D. management efficiency……… | |___| | ||||||||||||||||||||||||
B5Q12 | Do you use energy from renewable sources [such as electricity, heat or fuel like installation and maintenance of equipment (photovoltaic panels, solar panels, etc.) in your activities? 1. Yes 2. No | |__| | ||||||||||||||||||||||||||
B5Q13 | To ensure water energy and water efficiency [such as water leakage reduction, water recycling, rainwater catchments, low-energy and/or low-water using appliances, efficient energy transmissions, etc.], do you use it in you fisheries? 1. Yes 2. No | |__| | ||||||||||||||||||||||||||
B5Q14 | Do you apply strategies to control polluted water and air emissions [Such as waste water, fumes] in your fisheries? 1. Yes 2. No | |__| | ||||||||||||||||||||||||||
Module C: Financial and economic indicators
Financial inclusion | Never | Rarely | Sometimes | Most often | Always | ||
|---|---|---|---|---|---|---|---|
CQ1 | Access | A. How often do you use mobile money services? | |___| | |___| | |___| | |___| | |___| |
B. How often did you take a loan from a bank ? | |___| | |___| | |___| | |___| | |___| | ||
C. How often do your household take loans from MFI | |___| | |___| | |___| | |___| | |___| | ||
D. How often do your household take loan from a Njangi house? | |___| | |___| | |___| | |___| | |___| | ||
Financial and economic difficulties | Strongly disagree | Disagree | Neutral | Agree | Strongly agree | ||
CQ2 | Finance/ Livelihood | A. My household run out of food because of lack of finance. | |___| | |___| | |___| | |___| | |___| |
B. My household fail to go for check-up due to financial constraint. | |___| | |___| | |___| | |___| | |___| | ||
C. A household member failed to attend school in the last academic year due to financial constraints. | |___| | |___| | |___| | |___| | |___| | ||
CQ3 | Economics shocks | A. Increasing food prices reduces my households’ food stock/income | |___| | |___| | |___| | |___| | |___| |
B. Increased prices of agricultural or livestock inputs reduces household income | |___| | |___| | |___| | |___| | |___| | ||
C. There was an increase prices for agricultural your fishery products | |___| | |___| | |___| | |___| | |___| | ||
D. The household recorded unemployment in the last 12months. | |___| | |___| | |___| | |___| | |___| | ||
E. Loss of land/rental property/theft was registered in your household | |___| | |___| | |___| | |___| | |___| | ||
Coping strategies1. Yes 2. No | |||||||
4 | Have you taken up a new/additional job (casual labor, wage labor) to cope with increase prices 1. Yes 2. No | ||||||
5 | Have you reduced households’ food consumption 1. Yes 2. No | ||||||
6 | Have you taken a loan (borrow) to maintain food stocks 1. Yes 2. No | ||||||
7 | Did you receive help or remittances because of financia difficulties 1. YES 2. NO | ||||||
8 | Rate your households’ ability in a scale of 1–5 to dealing with price increase 1. very unable 2. unable 3. Neutral 4. Able 5. Very able | ||||||
9 | Does your household have access to electricity ? 1. YES 2. NO | ||||||
Module D. Demographic and cultural factors
NO | Questions and filters | Codes | |
|---|---|---|---|
DQ1 | What is your gender? 1. Male 2. Female | |___| | |
DQ2 | What is your age in years? 1. 18 to 24 2. 25 to 34 3. 35 to 44 4. 45 to 55 5. 55 and over | |__||__||__| | |
DQ3 | What is your marital status? 1. Single 2.Married 3.Widowed 4.Divorced 5.Free union | |__||__||__| | |
DQ4 | What is your current professional status 1. Unemployed 2. Student/ Apprentice (in training) 3. Employed4. Business owner 5. Others (Specify)......... | |__||__||__| | |
DQ5 | What is your religion? 1. Christianity 2. Islam 3. Other religion ……specify | |__||__||__| | |
DQ6 | What is your first language? 1. English 2. French 3. Others Specify: ………………………………………………………… | |___| | |
DQ7 | What is your region of origin? 1. Adamaoua 2. Centre. 3. East 4. Far North 5. Littoral 6. North 7. North west 8. West 9. South 10. South west 11. Other CEMAC 12. Nigeria 13. Other Africa 14. Other world: | |___| | |
DQ8 | What is your nationality 1. Cameroon 2. Nigeria, 3. Equatorial G. 4. Ghana 5. Others | |__|___| | |
DQ9 | What is your household size (number of people living in the house) | |__|___| | |
DQ10 | Income level : 1 = less than 50.000 2 = [50.000 ; 100.000[ 3 = [100.000 ; 150.000[ 4 = [150.000 ; 200.000[ 5 = [200.000 ; 250.000[ 6 = [250.000 ; 300.000[ 7 = [300.000 ; 350.000[ 8 = [350.000 ; 400.000[ 9=(> 500k | ||
Module E. Community level indicators
N | Questions in this section rates the level of infrastructures, governance and administrative control (In a scale of 1 to 5) Ranging from Very poor to very good. |
|---|---|
1 | The presence/qaulity of education infrastructures in the present fishing community. |
2 | The quality of road infrastructures linking the nearby city or linking the nearby towns |
3 | The quality of internet and mobile network services or the access to network services |
4 | The quality of health facilities or access to healthcare coverage programs |
5 | Does the community have access to electricity ?1. Yes 2.No |
6 | The strictness of fishery regulatory policies Ranges from strongly disagree to strongly agree in a scale from 1–5 |
7 | Are fishermen satisfy with the regulatory fishery policies ? 1. YES 2. NO |
Thank You for Participating!!!
1
The Slovins’ formula is as follows: n=
, where, n = The number or the size of the samples, N = Total population and e = error tolerance. It is applicable when the size of the population is known.
2
The regions highlighted in yellow were not included in the study, whereas the eight regions marked in red were covered. Cameroon is situated in Central Africa, at the junction of the Gulf of Guinea. It shares borders with Nigeria to the west, Chad to the north, the Central African Republic to the east, and Equatorial Guinea, Gabon, and the Republic of the Congo to the south.
3
NB: Fish revenue is proxied in FCFA (The Central African CFA franc). Presently, it value is relatively lower to other currencies and its conversion rate to USD in March 2024 is: 1 USD = 604.103599 XAF.
4
It is the sum of the first two categories of the mental health indicator. The case of “very poor” and “poor” health conditions. That is: 24 + 32 = 51 respondents.
5
The sum of the last 2 categories of the mental health condition (the “Good” and the “very good” modalities).
6
Category for each household. 1 = Food Secure, 2 = Mildly Food Insecure, 3 = Moderately Food Insecure, 4/5 = Severely Food Insecure
7
ENUMERATOR: In the table below, list all the species of fish the household have raised during the last production cycle. Then, for each species, ask the questions regarding production and sales.