Optimizing the Estimation of Abandoned, Lost or Discarded Fishing Gear in Developing Countries: A Data-Driven, Behaviourally Corrected Method Using Economic and Survey Data

Abstract Abandoned, lost, or otherwise discarded fishing gear (ALDFG) is a persistent source of marine plastic pollution with ecological and economic impacts. Estimation methods in developing-country contexts often rely on self-reported survey metrics that are vulnerable to recall biases and unit misunderstandings, which can overstate ALDFG by factors of two to five. We present a transparent, transferable framework that integrates economic anchors (replacement and investment costs), survey‑validated gear masses, and behavioural corrections to improve ALDFG estimation. The six-step method comprises: (1) structured data collection and harmonization; (2) economic reasonability checks; (3) empirical price‑per‑kg derivation; (4) cost‑to‑mass conversion by gear type; (5) behavioural correction for availability and social desirability biases; and (6) sensitivity/uncertainty analysis with optional scaling. We demonstrate the approach with survey data from 1,500 fishers in three Vietnamese provinces. Sample‑reported annual replacement expenditures for nets (33.24 billion VND) are converted to mass lost using empirical price‑per‑kg, reconciling mismatches between per‑trip losses and annual costs. The framework differentiates nets and ropes, produces uncertainty bounds, and yields policy‑ready estimates at local or sectoral scales without publishing politically sensitive national totals. The method is transferable to other developing‑country fisheries and can inform design of retrieval, recycling, and extended producer responsibility schemes.