Impacts of COVID-19 Pandemic on the small-pelagic fisheries in Davao Gulf, Philippines

Martha Elena Betancourt Aguirre^a, Edison Roi D. Macusi^b

^aInternational Masters of Science in Marine Biological Resources (IMBRSea)

^b Regional Integrated Coastal Resource Management Center (RIC-XI), Davao Oriental State College of Science and Technology, City of Mati, Davao Oriental, Philippines

Welcome to my Professional Practice site, here you will have a closer look on how COVID 19 impacted the small-scale fisheries in the Davao Gulf

Working remotely wasn't so bad!

Regional Integrated Coastal Resource Management Center: Remote work

Due to the COVID 19 Pandemic and the travel restrictions, I worked remotely during my Professional Practice from Faro, Portugal. I worked directly with Dr. Edison Macusi and his team from Regional Integrated Coastal Resource Management Center (RIC-XI)

Description of the Study Site

The Davao Gulf is located in the southern Philippines on the Island of Mindanao.

The water surface area is about 3087 km2 and tide in the area is predominantly semi-diurnal, with two high and two low water levels occurring in a day. Davao Gulf is a wide and deep (>1 km) and semi-enclosed basin located south of Mindanao Island.

Two major islands are located near the head of the gulf, which partly blocks the entry of tidal currents and the propagation of long gravity waves (Villanueva, 2018).

In this study, we propose that fisheries, social, economic and emotional factors influence the CPUE of the small scale fisheries in the Davao Gulf, and that they were greatly influenced by the COVID 19 pandemic.

HOW WE BEGAN THIS STUDY

Literature review

I began this Professional Practice by doing a literature review on articles about the Davao Gulf small-scale fisheries and COVID impact on fisheries. The aim was to analyze a database based on interviews to fishermen in the Davao Gulf.

Data cleaning

Some of the data of the interviews performed in the Philippines , was missing we had to delete some of the fisherman that didnt have complete data regarding catch or information on education, household size etc...

Data analysis

After cleaning the data, I began doing descriptive statistics and check the normal distribution on catch, age and other variables, after this exploratory analysis we began with the statistical analysis using R and SPSS.

Places of the Study Area

Data collection with respondents coming from six regions of fishing communities in the Davao Gulf. Study sites: Mabini, Pantukan, Samal, San Isidro, Toril, Governor Generoso, Sta. Maria, Sta. Cruz and Malita

Total of N =199 interviews

Data Analysis

Clean data: Removed outliers and streamlined data
Explore the data: plot catch/CPUE vs. other variables
Categorize data into specific information components: Sociodemographic, Economic, Fisheries and Emotional
Check for the normality of the data-> Transform log10 CPUE to meet normality, obtain regression factors of the four categories
Statistical Analysis: Multiple Linear Regression (MLR) between variables and Principal Component Analysis (PCA)

Descriptive Results

I obtained descriptive statistics on each the 14 variables studied from each of the four categories (variables listed on the diagram).

Histograms of the Sociodemographic category

For example the mean age of fishers reported was 42 years old and ranged from 15 to 82 years old. The youngest fishers are from Sta Maria (36 years old average) and the oldest fishers were from Toril (49 years old average). The same analysis was made to the other variables.

Boxplots of catches (kg) per fisherman in the Davao Gulf

The normal average catch per fisherman was 9.84 kg per trip, ranging from 0.4kg to 40 kg. The place with the highest catch was Governor Generoso with an average catch of 16 kg and the place with the least catch was Mabini with an average of 5 kg catch.

STATISTICAL ANALYSIS

Regression: dependent variable logCPUE and predictors variables were from the regression factors of the 4 different categories. Result of the first model performed using assumptions of ANOVA.

The outcome of the regression was statiscally significant <.001.

The economic and fisheries regression factors were stastically significant <.001

BINARY LOGISTIC REGRESSION

The binary logistic regression model was statistically significant, χ2(4) = 32.366, p < .0004. The model explained 20% (Nagelkerke R2) of the variance in the volume of catch and correctly classified 66.8% of catch volume.

The results for the binary logistic regression showed that the significant variables in the model were the proportion of fish sold, the cost of the fish and emotional frustration experienced by the fishers during COVID 19 Pandemic.

Discussion and Conclusions

The present study has attempted to understand how COVID 19 affected different variable that influence the small-scale fisheries in the Davao Gulf. The main finding in this study is the influence of the economic factors on the CPUE. On previous studies it was found that variables that influence CPUE were years of fishing, revenue and catch left for the family on a closed fishing season in the same area (Macusi et al. 2020). Even though revenue was not found significant in this present study, the economic factor might have a motivation in order to secure their households (Fabinyi et al., 2017). Already vulnerable small-scale fishers and communities that depend on them were affected by the COVID-19 pandemic.

With the COVID pandemic, there was a decline in fish prices and rise in transportation costs that led to lower fish supply and impact on the economic welfare of fishers (Ferrer et al. 2021). Also during the pandemic, small fishers were apprehended by maritime authorities for allegedly violating quarantine protocols (Mirasol, 2020; Miraflor, 2020) and local government units disobeyed the national order allowing fishing and the free-flow of fish amid the COVID-19 pandemic (Ocampo, 2020) During the months of March to May , lack of transportation reduced fish marketing and the closure of the ice plants and the hours of queues at checkpoints resulted in fish spoilage (Mirasol, 2020). It took a pandemic to highlight the importance of the fisheries, emphasizing the fishers’ role in maintaining food supply amid crisis (Ferrer et al. 2021).

This entire study would not have been possible without the enormous work Dr. Edison Macusi's and his team from the Regional Integrated Coastal Resource Management Center did. From interviews with small-scale fishermen, to data filtering and analysis.

There was a great contribution from the local fisherman and for me, I'm thankful for the opportunity and I hope to someday visit the Philippines and be able to conduct fieldwork myself.

Some behind the scenes photos I took during my Professional Practice work

Bibliography

Fabinyi, Michael, Wolfram H. Dressler, and Michael D. Pido. "Fish, trade and food security: moving beyond ‘availability’discourse in marine conservation." Human ecology 45.2 (2017): 177-188.
FAO. 2021. The impact of COVID-19 on fisheries and aquaculture food systems, possible responses: Information paper, November 2020. Rome. https://doi.org/10.4060/cb2537en
Ferrer, A. J. G., Pomeroy, R., Akester, M. J., Muawanah, U., Chumchuen, W., Lee, W. C., ... & Viswanathan, K. K. (2021). COVID-19 and Small-Scale Fisheries in Southeast Asia: Impacts and Responses. Asian Fisheries Science, 34, 99-113.
Macusi, E. D., Liguez, A. K. O., Macusi, E. S., & Digal, L. N. (2021). Factors influencing catch and support for the implementation of the closed fishing season in Davao Gulf, Philippines. Marine Policy, 130, 104578.
Mamauag, S.S., Ali~no, P.M., Martinez, R.J.S., Muallil, R.N., Doctor, M.V.A., Dizon, E.C., Geronimo, R.C., Panga, F.M., Cabral, R.B., 2013. A framework for vulnerability assessment of coastal fisheries ecosystems to climate change—tool for understanding resilience of fisheries (VA–TURF). Fish. Res. 147, 381–393.
Miraflor, M.B. 2020. Fishermen appeal for systematic gov’t solution. https://business.mb.com.ph/2020/05/24/fishermen-appeal-for-systematic-govt-solution/ (Accessed June 2021).
Mirasol, P. 2020. Farmers and fisherfolk share Covid-19 stories from the field. https://www.bworldonline.com/sparkup-community-farmers-and-fisherfolk-share-covid-19-stories-from-the-field/ (Accessed June 2021)
Mofijur, M., Fattah, I. R., Alam, M. A., Islam, A. S., Ong, H. C., Rahman, S. A., ... & Mahlia, T. M. I. (2020). Impact of COVID-19 on the social, economic, environmental and energy domains: Lessons learnt from a global pandemic. Sustainable production and consumption.
Muallil, R.N., Mamauag, S.S., Cababaro, J.T., Arceo, H.O., Aliño, P.M., 2014. Catch trends in Philippine small-scale fisheries over the last five decades: the Fishers ׳ perspectives. Mar. Pol. 47, 110–117.
Ocampo, K.R. 2020. Año threatens action vs LGUs blocking goods. Philippine Daily Inquirer. https://newsinfo.inquirer.net/1249185/ano-threatens-action-vs-lgus-blocking-goods (Accessed June 2021)
Philippine Statistics Authority. 2017. Farmers, fishermen and children consistently posted the highest poverty incidence. https://psa.gov.ph/content/farmers-fishermen-and-children-consistently-posted-highest-poverty-incidence-among-basic

THANK YOU FOR VISITING MY WEBSITE

If you have more questions or need more information on this study send me an email: marthaelena.betancourt@imbrsea.eu

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