A Framework for Assessment of Harvested Fish Resources In
Total Page:16
File Type:pdf, Size:1020Kb
Resource Assessment Framework 45 5 DATA FOR RESOURCE ASSESSMENT 5.1 Continuous or Project-Based Data There are two general methods in which data are collected for resource assessment: continuous or project-based. Continuous data are repeatedly collected from a source or sources. The expression “monitoring” is frequently used to describe this type of activity. In contrast, project-based data are obtained for a particular research project and collected to test particular scientific hypotheses. Within resource assessment, continuous data collection methods (for catch, effort, ages and lengths) are frequently used because continuous data contain information about the dynamics18 of a fish population. Dynamic relationships are the basis of assessment models that are required to make quantitative forecasts of managerial decisions. Performance reporting commitments within the FMS are annual. Although there is no stated obligation that the data that are used to compile the reports would be updated every year, there would need to be some system in place that collected up-to-date information for the reports of managerial performance. The continuous data collection programs currently underway (relevant to resource assessment) in the NSW Department of Primary Industries are: the catch-effort reporting system; fishery-independent surveys for abalone; an observer and recruitment index project for rock lobster; the gamefish tournament monitoring program; and, some monitoring of the age and length structure of commercial landings. Project-based data have been collected for particular projects. Once that project is finished and written up, no more data are collected, though the methods are well documented enabling replication of that sampling design. Individual projects can yield information very valuable to resource assessment, particularly biological information such as growth, maturity and vulnerability. Creel surveys are another example of a project that provides a snapshot of recreational harvesting. Project based data are, however, often compromised in their utility within stock assessment because there are no time-series of observations that enable the longer-term dynamics of populations to be measured. Budgetary experience will make public administrators wary of continuous data-collection projects that can develop an expensive life of their own. In contrast, project-based data have clear endpoints and outcomes. Resource assessment requires both types of data. Many of the following types of data for resource assessment could be considered project-based when they are initially planned and researched, but they would become continuous if they were to remain operational in the long term (beyond 5-10 years). The challenge for the NSW Department of Primary Industries is to decide which types of data should be collected continuously and which should be the subject of further research and evaluation. 5.2 The Cost of Data Dollar costs will be the fundamental constraint on data collection (and the entire assessment process in general) because money is the easiest thing to measure and control. The other fundamental constraint is time. For the FMS to “work”, assessments must be completed within a timeframe appropriate for performance reporting. Although it is easy to argue that other components of this system, such as data being fully representative, should be given priority over time and money, this is not likely to be the reality, at least in the short term. The approach suggested here is to identify what can be done with the time and resources available and then continuously improve the representativeness of data over time. If, however, the data collection is so 18 A dynamic relationship describes the change of system state with time. NSW DPI - Fish. Res. Assess. Ser. 15 46 Resource Assessment Framework compromised by time and cost constraints that the data are essentially worthless, then alternative methods for managing and assessing these systems will need to be considered. When costing out the collection of data a “life-cycle” approach should be used where the costs include defining/refining sampling protocols, collecting information, data entry/checking and archival costs. The expenditure on data collection and analysis must be consistent with economic principles within ecological sustainability: all users of the resource could be expected to contribute to the costs of monitoring and assessment. It will be impossible to define a “perfect” data-collection strategy for this assessment strategy from the outset, there are simply too many unknowns. Qualitative cost-benefit analyses of various types of information can be completed quickly (such as table of pros and cons), but full quantitative analyses would be complex and time-consuming. It is beyond the scope of this document to provide accurate cost estimates of various data collection programs for resource assessment, but a general sense of the relative costs of various sources will be indicated. A representation of the approximate cost and value for resource assessment is presented in Figure 5. The exact nature of any particular project and species will, of course, determine the cost and likely benefits for resource assessment. Justifications of the approximate positions of data-sources within this plot are given below. High Fishery Independent Tagging Surveys Programs Creel Surveys t s o Observer Data C (survey-based) e Logbook v i Programs t a l Tournament Re Monitoring Observer Data Sampling (risk-based) at Ports Effort Data Catch Data Low Low Value Within High Resource Assessment Figure 5. A representation of the relative costs and value of various sources of data for resource assessment in NSW. These sources of data are discussed in more detail in the text. Many of these sources of data will have values beyond resource assessment that justify their collection. The relative location of any type of data-source on this plot will depend upon the life-history of the species and the scope of the project that collected that information. 5.3 Role of “Basic Biological” Information in Resource Assessment Basic biological information such as information on growth, maturity, selectivity, movement and mortality is valuable and sometimes crucial when applying input controls such as minimum legal lengths, closed seasons and closed areas. That said, these controls are always somewhat “blunt” and the marginal value of more detailed information may be small. NSW DPI - Fish. Res. Assess. Ser. 15 Resource Assessment Framework 47 Understanding growth, maturity, selectivity, movement and mortality will also improve our interpretation of indicators. For example, understanding variability of length at age improves our interpretation of length data. Knowledge of length and, to a lesser extent, age at maturity is a critical factor in specifying a minimum legal length. Understanding the growth of individuals is crucial when estimating mortality rates from length data. Any system to prioritise species for stock assessment needs to consider the basic life history of the animal. Low growth rate species must be given higher assessment priority than high growth rate species of similar commercial/recreational value, as they are simply higher managerial risk. Such comments are supported by the risk assessments being undertaken in the EIS. There will be some species in NSW where there is insufficient biological information to make such judgments in regard to growth, maturity and mortality. These species have or will be identified and given a high priority for such studies. Obtaining such information is relatively inexpensive. 5.4 Sources of Data for Resource Assessment 5.4.1 Commercial Catch and Effort Data Use of fishery-dependent CPUE data could not be described as international best-practice in higher valued fisheries but would probably be considered acceptable for the lower valued stocks that occur in NSW. There are examples of fisheries that have been well managed with fishery- dependent CPUE data and others that have been badly managed with expensive survey data. An understanding of the behaviour of the fish and the fleet can dramatically improve our ability to understand the relative value and usefulness of CPUE data. Records of commercial landings from LCatch/ComCatch exist for many species but these records do not account for: pre-1984 data; recreational harvesting; discard mortality; or illegal harvesting. There exists within the NSW Department of Primary Industries enough expertise to identify the strengths and weaknesses of this database quite quickly. Pre-1984 data is available in other databases for some species (but not generally at the level of individual fisher activity) and relevant catch-effort information is held by Commonwealth agencies (e.g. AFZIS). As assessment priorities are determined, there will need to be an identification of a credible time- series of effort from 1984-199719 (e.g. mesh netting in the EG fishery) or an acknowledgement that such a time-series is not useful. Similar steps will have to be taken for the post 1997 data, but this should be more straightforward as there was more satisfactory recording of effort data. This latter window will have to be the baseline for many species. If adding effort information degrades the robustness of the indicator of abundance (from the default of using landings data alone) then it will not be used. This degradation will occur if there are systematic biases in the effort data. The catch records database is currently subject to a significant time lag (~6-12 months). Consideration needs to be given to developing mechanisms to update this database more rapidly including the timely arrival of records from fishers. Catch records were an integral part of the value of the property right in these fisheries. Measures should be imposed if individual fishers do not take their responsibility in maintaining accurate records of landings seriously20. It is far more practical to check upon the quality of the catch data than the effort data. The Fish Receiver’s program (ss 117-120) could be used to validate that the total local purchases of a Receiver corroborate with the landings reported by fishers.