First, make sure that there really are no data. Many fisheries can benefit from data collected for other purposes. For example, in many coral reefs, seagrass systems, and mangrove forests scientists and students conduct visual surveys with SCUBA or snorkel gear to count fish. These data can be used to calculate total fish density (number of fish of all species counted in all transects divided by the area surveyed in the transects) and fish densities for species of particular importance or concern. For coral reefs in the Indian Ocean or Caribbean Sea, the total fish density can be compared to thresholds for coral reef health (Step 2) to estimate the status of the ecosystem and the impact of fishing (to see if fishing pressure should be reduced generally, for example by reducing the open season, imposing a size limit or catch limit, or restricting gear). The species-specific fish density numbers can be used to assess stock status if you have a time series extending to the beginning of the fishery, or if you have a well-complied with marine reserve that has similar habitat as the fishing grounds (Step 4). Another example of "hidden" fishery data are exports: countries usually keep fairly good records of exported goods, and if some of your species (e.g., lobster, conch, or shrimp) are mostly exported, the export numbers can be used as a proxy for catch (minus domestic consumption).

If there are truly no data at all for your fishery, then conduct a Productivity Susceptibility Analysis (Step 3) with your fishermen and local experts. It requires only fishermen's knowledge of the fish and their fishing techniques plus some life history parameters such as size at first maturity and maximum size. It's best to use local estimates of life history parameters, but if there are none you can use global estimates from You can also omit some of these life history parameters from the analysis if you cannot find them anywhere. The PSA will result in a vulnerability score for each species analyzed: if the score is above 2.2 it indicates a high risk of vulnerability to overfishing. Scores between 2 and 2.2 indicate cause for high concern, while scores between 1.8 and 2 merit moderate concern. Additionally, if susceptibility scores calculated in the PSA are higher than 2.3, precautionary action to reduce fishing mortality may be merited regardless of the overall vulnerability score. If no other data are available, you might recommend a reduction in fishing mortality through a seasonal closure, a size limit, a gear restriction, or a catch limit based only on the PSA analysis.

Put a data collection system in place. The most useful data to collect are size at maturity, maximum length, and the length composition of the catch (i.e., how many fish in a sample fall into each size category), in addition to monitoring the total catch and CPUE trends (see data collection guides). While multiple years of data are needed to get a good sense of stock status, just one year of data can be sufficient to initially estimate length-based sustainability indicators, fishing mortality, spawning potential ratio, and in-season fluctuation of the catch, when combined with targets and limits defined by managers/scientists/stakeholders, can be used to drive adaptive fisheries management (Step 6, 7, and 8 - 11).  Careful interpretation, including consideration of the fact that fish populations can vary a lot from one year to the next,  is the key for using data-limited methods like these.