Step 11: Implementation and Adaptation
Now that we have defined clear fishery management goals, chosen performance indicators and reference values, developed harvest control rules, and assessed the current status of our fishery and stock(s) with the available data, we are ready to choose harvest control measures (HCMs) that can effectively control fishing mortality and move the system towards our goals. HCMs can be thought of as the specific management actions that correspond to the general Harvest Control Rules (HCRs) set at Step 8. So, for example, if an HCR set at Step 8 says to “reduce fishing mortality” if the results of our analyses reveal a specific combination of performance indicator measurements (as discussed in Steps 6 and 7), the corresponding HCM that we might put into effect in response to those measurements could be to “reduce fishing mortality by reducing the Total Allowable Catch for the year by X%.”
There two main categories of harvest control measures (HCM): input controls and output controls (See Tables 1 and 2 below).
Input controls are aimed at controlling harvest indirectly, by reducing the efficiency with which fishermen can catch fish. They are often relatively easy to implement (because they require less monitoring, i.e. you don’t have to count all the fish that are caught), so they are often more appropriate for small scale fisheries that don’t produce much revenue (and hence have limited funding for monitoring and administration.
However, at the same time input controls may be easier for fishermen to cheat. Input controls sometimes also cause other problems both ecological and socioeconomic in nature. For example, size limits are quite common in many fisheries but can result in discarding the undersized fish at sea to avoid prosecution, which in turn results in higher fishing mortality. Gear restrictions such as a minimum mesh sizes are often used to prevent this, but if fishermen are motivated to maximize their catch, illegal gear is sometimes deployed resulting in catch of the prohibited size classes.
Other examples include: restrictions on engine horsepower, which can be circumvented by using multiple engines; restrictions on vessel size, which can be circumvented by increasing the number of fishing trips and the effectiveness of the gear; the implementation of fishing seasons, which can be rendered ineffectual by increases in fishing effort, either from existing fishermen fishing harder or from the entry of more fishermen; and spatial controls such as Marine Protected Areas (MPAs), which are often either too small to protect enough of the stock to control fishing mortality to a meaningful degree or so large that the boundaries are difficult to enforce. Good governance such as the allocation of secure catch or fishing territory privileges, including monitoring and accountability measures, can prevent these kinds of problems. For more guidance on implementing well-designed rights-based management systems, see our Catch Share Design Manuals. In principle, any governance system that is very effective at controlling actual fishing effort and preventing gaming behavior (i.e., clever ways to get around the regulations) should enable adjustment of fishing mortality using input controls.
Output controls, often called catch limits, directly control the amount of fish that are caught. They are generally more difficult to implement than input controls because the fish have to be counted through one or various monitoring and/or catch accounting efforts. This can be challenging if fishermen land fish at multiple sites and/or discard fish at sea. Output controls can also be ineffective in a number of ways. For example, if catch limits are imposed on large groups of fishermen, it is very challenging to count the number of fish that are caught rapidly enough to ensure that the catch limit is not overshot, resulting in too much fishing mortality. If catch limits are imposed on individual fishermen and incentives to maximize catch persist, violations of the individual catch limits (or “quotas”) can become commonplace, again resulting in too much overall fishing mortality. As is the case for input controls, output controls can also be made more effective through good governance (e.g., effective ways to hold fishermen accountable to catch limits, participatory decision-making processes, etc.) which generates incentives for fishermen to comply with the catch limit.
Table 1. Description of common harvest control measures in fisheries. BMSY is the biomass associated with maximizing sustainable yield. FMSY is the fishing mortality associated with maximizing sustainable yield. SSB is the spawning stock biomass. (Table adapted from Liu et al 2016).
|Example Harvest Control Rule (HCR)||Type of Harvest Control Measure (HCM)||Method||Description|
|Maintain BMSY/ Preserve Target SSB||Output Control||Catch Limit||Sets an upper limit on how many fish can be removed by a fishery in a given time|
|Escapement Threshold||Allows a certain number of fish to escape a fishery before harvest|
|Bag or Trip Limit||Limits the number of fish that can be landed by an individual fisher or vessel on a single day or fishing trip|
|Size Limit||Sets minimum and/or maximum bounds on the size of fish that can be legally landed in a fishery|
|Sex-specific Limit||Similar to catch limits, but broken down by sex within a target species|
|Fish at FMSY||Input Control||Temporal Limit||Restricts the time period over which a fish can be legally landed|
|Gear/ Vessel Restrictions||Restricts the dimensions and characteristics of a gear or vessel allowed to participate in a fishery. May also restrict the quantity of gears allowed|
|Deployment Limit||Places a cap on the individual fishers' use of fixed gears|
Table 2. Harvest control control measures. Here we list the major types of fishing control measures that are used to achieve various kinds of fishery management objectives. The symbols indicate the degree to which each control measure is useful for achieving a specific objective.
Circles indicate that the HCM has been observed to have positive or negative effects, depending on context. Grey indicates that the HCM is not expected to have an effect on the objective, and black indicates a lack of data in the literature. The table represents impacts of HCMs on objectives that are well documented in the literature and is not designed to represent or include the impacts of HCMs on management objectives in every potential scenario. (Table adapted from Liu et al 2016).
Harvest Control Measures in a Multi-Species Fishery
Most of the HCMs discussed above can be used in a multispecies fishery as well as a single species fishery; however some measures may be more appropriate for multispecies fisheries. An important consideration in a multispecies fishery is the protection of “weak” or “constraining stocks.” These are the stocks that are in the poorest health, and/ or that have the highest vulnerability to the fishery, and which are thus at the highest risk of serial depletion. If weak stocks are valued fishery targets it may be that management measures are already being designed to catch these stocks sustainably. However if they are not among the primary or most valuable targets, and are perhaps just caught incidentally along with those targets, management may have to be more complex. If each stock in the multispecies fishery is managed with its own Total Allowable Catch (TAC) limit, for example, it may be necessary to close the whole fishery down when TACs for weak stocks are reached, even if there is TAC remaining for other species. Certain measures can be implemented to reduce the likelihood of a fishery closure for this reason, such as the creation of “risk pools” or programs where quota for weak stocks is shared among all the members of the fishery. See the EU Discard Reduction Manual for more guidance on these and other tactics to avoid depleting weak stocks and closing fisheries.
Harvest control measures that may be effective in multispecies fisheries include: Closed seasons, which can protect weak stocks if they are timed appropriately; closed areas, which can also protect weak stocks if they are sufficiently large and contain habitat suitable for weak stocks; and sharing information on where weak stocks are concentrated so that fishermen can avoid them can also reduce catches of weak stocks.
In addition, it may be possible to make certain changes to the way the fishery is prosecuted, and/or to the management measures implemented, to help avoid serial depletion. For example, it may be possible for fishermen to adjust their fishing practices or gear such that weak stocks are caught separately instead of together with stronger stocks. For more information on this, please contact us and ask for the white paper, “Managing Multispecies Fisheries.”
Lastly, some tools have been developed to evaluate different management options in multispecies fisheries contexts. For example, the “Mizer model” is a multispecies size spectrum model in R that can be used to study the effects of different multispecies management strategies. Mizer projects species' size distributions, abundance, and yield by accounting for both fish population growth and predator-prey interactions, providing a format for evaluating trade-offs between ecological and socioeconomic outcomes under different multispecies management scenarios, such as closed areas, fishing mortality limits on individual stocks, and fishing mortality limits on baskets of fish (see Step 5).
Harvest Control Measures (HCMs) can be combined to better achieve the goals of a given fishery management system. Figure 1 shows some common incentives and management challenges that may result from the application of a single HCM, as well as some potential solutions to those challenges, which often involve combining HCMs.
Figure 1. Examples of combining HCMs (Harvest Control Measures), rights-based management, and spatial management to tackle challenges associated with single HCMs. Single HCMs (pink boxes) can lead to incentives for ﬁshers that create management challenges (yellow and blue boxes), but can mitigated by combination with other strategies (green boxes). This ﬁgure shows just a few examples of combining HCMs, but others utilize a similar framework (Liu et al 2016).
For more detail on how to choose harvest control measures that are appropriate for your fishery, please carefully review Liu et al (2016) and Dowling et al (2016).
Fisheries management is always a dynamic process that must respond to fluctuations in environmental conditions, fishing behaviors, variable productivity of the resource, and changing market and economic conditions. In addition, data- and resource-limited fisheries managers must often make management decisions in the face of data gaps that create uncertainties around the appropriate actions to implement, and the likely outcomes of those actions. In these fisheries it is therefore even more important to implement an adaptive management program that allows fisheries managers and stakeholders to re-visit fisheries goals, re-evaluate progress towards those goals, and re-examine the management measures that have been put in place to reach those goals based on new data, observations about fishery conditions, and learning from the outcomes of previous management decisions. Thus, we recommend going through the 11 Step FISHE process on a periodic basis – annually at a minimum, but the appropriate period will depend on the individual patterns of the fishery and the target stock life cycles.
See the information and resources provided under the Collect More Data section of this website to learn about implementing and improving your data collection regime so that more and higher-quality data can inform each iteration of the FISHE process.