Harvest strategy approaches based around empirical indicators and/or control rules are
beginning to be accepted in a growing range of data-and capacity-poor fisheries. While …

Estimation of population abundances in the absence of good observational data are
notoriously difficult, yet urgently needed for biodiversity conservation and sustainable use of …

This study presents a Monte Carlo method (CMSY) for estimating fisheries reference points
from catch, resilience and qualitative stock status information on data‐limited stocks. It also …

The majority of global fish stocks lack adequate data to evaluate stock status using
conventional stock assessment methods. This poses a challenge for the sustainable …

The Mediterranean Sea is classified as a “data-poor” region in fisheries due to its low
number of assessed stocks given its biodiversity and number of exploited species. In this …

Fisheries science uses quantitative methods to inform management decisions that reflect
cultural preferences which, in turn, indirectly influence the states of ecosystems. To date, it …

The majority of the world's fisheries, by number, are data‐poor/limited, and there is a
growing body of literature pertaining to approaches to estimate data‐limited stock status …

The increasing need to account for the many factors that influence fish population dynamics,
particularly those external to the population, has led to repeated calls for an ecosystem …

Small-scale fisheries are an important source of food, income and cultural identity to millions
of people worldwide. Despite many fisher people observing declining catches, a lack of data …

The cost, complexity and the lack of technical capacity in many countries have made the
scientific assessment and sustainable management of data‐poor fisheries a persistent …