Fisheries management often relies on the monitoring of key lifehistory traits to assess, for instance, any potential harvest-related detrimental effects on a given fish stock (Rochet, 1998). Mortality, which can be estimated through different approaches (Lees et al., 2021;Miranda & Bettoli, 2007), constitutes a pivotal biodemographic component for stock status assessment and population dynamics modeling (Johnson & Zúñiga-Vega, 2009;Wikström et al., 2016). Accurately estimating mortality rates is thus of prime importance to avoid any misevaluation of a given fish stock status or potentially producing overoptimistic projections from relying on downwardly biased estimates (Goto et al., 2022). Here, we advocate that this situation may arise when the linear regression (LR) method of Ricker (1975) is used to estimate mortality from catch-curve data.