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timor.nutrients

DOI

This repository contains the code and analyses for the paper "Fishery nutrient profiles provide a practical tool for nutrition-sensitive fisheries management." The study models nutrient yields from small-scale fisheries in Timor-Leste, providing insights for nutrition-sensitive and sustainable fisheries management.

Overview

Authors

Lorenzo Longobardi, Gianna Bonis-Profumo, Hamza Altarturi, Jessica Bogard, Joctan Dos Reis Lopes, Jeppe Kolding, Villiam Sozinho, Alexander Tilley

Abstract

Small-scale fisheries are a crucial source of nutrient-dense aquatic foods in low- and middle-income countries (LMICs), yet practical tools to manage these fisheries to optimize nutritional outcomes in an ecosystem approach remain limited. We present an analytical framework and predictive model of fishery nutrient profiles under typical multispecies, multi-gear situations. Using six-years of catch data from Timor-Leste, we modelled how different fishing methods, habitats, vessel types and seasons influence the yield of nutrients of public health significance. Our results demonstrate that fishing method and habitat are strong predictors of catch nutritional profiles. Importantly, different combinations of fishing strategies can achieve similar nutritional outcomes, indicating complementary management pathways to enhance nutrient availability for communities while balancing ecological, economic, and human wellbeing goals. This replicable framework provides actionable insights for nutrition-sensitive fisheries management and offers data-driven guidance for policies aimed at improving food and nutrition security in LMICs.

Getting started

This repository is a R package and contains both the data used for the analysis and the code used to generate the results. In order to replicate the analyses you can clone the repo and run the code. You can also find the code associated to the results in this online report.

  • The data is stored in the Data Folder.
  • The code to reproduce results is available in the Code Folder as Rmarkdown files.