5.1 National requirements
5.2 Regional and sub-regional requirements
5.3 Shark fishery descriptions
5.4 Species identification
5.5 Stock identification and stock structure
5.6 Fishery monitoring
5.7 Data collection methods
5.8 Scientific research
5.9 Data management
5.10 Stock assessment
5.11 Adoption of Sustainable Development Reference System
5.12 Risk management and risk assessment
States should recognise that conservation and management of sharks requires the availability of sound scientific basis to assist fisheries managers and other stakeholders in making decisions. Therefore, they need to ensure appropriate research is undertaken into all aspects of fisheries including biology, ecology, technology, environmental science and economics.
States should promote the use of research results as a basis for setting management objectives, biological reference points, sustainability indicators, acceptable risk levels, time frames and performance criteria, as well as ensuring adequate linkages between applied research and fisheries management.
States should support the establishment of mechanisms, inter alia, to facilitate shark research and fishery monitoring at regional and sub-regional levels and should encourage the sharing of data and the results of such research between regions and sub-regions. Collaborative monitoring and research programmes to enable stock assessment of shared transboundary shark species should be established through RFMOs and bilateral and multilateral sub-regional arrangements. States should conform to agreed monitoring and research procedures and data resolution to ensure uniform approaches at the regional and sub-regional levels for shared transboundary shark stocks.
The Code of Conduct for Responsible Fisheries requires that policy decisions on regional, sub-regional, national or local fisheries be formulated and made in the full knowledge of the nature of the fisheries under consideration, including the different fishing groups or fleets and their composition, as well as the fishing grounds they use or propose to use.
Fisheries policy decisions should be made with the following information:
- interest groups, their features and their interests in the fishery,The fishery on any given stock may be simple, consisting of a single, relatively homogenous fleet. Alternatively, it may be complex, consisting of several fleet types ranging from, for example, sophisticated factory fleets to fleets of artisanal vessels, with each fleet using distinctive gear with distinct selectivity patterns or fishing different fishing grounds.- the economic factors related to the fishery, particularly the economic and social dependence of the different interest groups on the fishery,
- details of costs and benefits to the region, nation or local area from the fishery,
- the role of the fishery in providing employment for the different groups or communities,
- the alternative sources of employment and income for the different interest groups or communities,
- the current status of access to or ownership of the resources,
- the institutions currently involved in decision-making within the fishery, and
- an outline of the history of the fishery and the historical roles of the different interest groups within the fishery.
Data and information should be collected and analysed on each fleet such as:
- the number of vessels or units,
- their gear characteristics and the selectivity of the gear,
- any season patterns in the fishing,
- the locality of fishing in relation to the distribution of the stock and other fleets,
- any navigational and technological aids which assist in fishing, and
- other related factors.
Field guides should be prepared to enable species identification from whole animals, carcasses and, possibly, fins, skins, vertebrae and heads.
Any fisheries monitoring, research or management programme requires that the species composition of the catch can de determined. Apart from general taxonomic uncertainties associated with a large number of species of sharks and other chondrichthyans, common practices of heading, gutting, finning, skinning and filleting or excising livers at sea exacerbates the problem for identifying the species of a shark in the catch. Although ‘rapid genetics-based identification techniques’ based on electrophoretic and on nuclear and mitochondrial DNA techniques can be adopted for determining species, these techniques require expensive and time-consuming procedures which are usually not suitable for routine monitoring or surveillance. Hence, effective onshore monitoring and surveillance of the catch requires the sharks to be landed in a form that enables species identification.
Fishers should not be forced to land sharks whole, because sharks should be gutted and gilled as soon as practicable after capture to avoid degrading the quality of the meat and other products. One option that usually enables species, sex and partial length of a shark to be determined is to have regulations allowing sharks to be headed and gutted at sea but requiring the sharks to be landed ashore as carcasses with fins, skin, claspers and, where applicable, dorsal spines attached. Leaving the head attached, with removal of the gills, is an option where species identification from the carcass form is uncertain.
If there is a requirement for species identification for marketing or trade purposes, there will be a need to develop field guides based on fins and other body parts. There will also be legislative requirements to ensure that shark products (carcasses, meat, fins, skins, heads, vertebral columns, livers, liver oil and jaws) are clearly labelled with species name.
Stock identification and structure are integral components of fisheries stock assessment and are required for effective fisheries management and for ‘special management’ of species considered endangered or severely depleted. Stock identification and stock structure help determine the appropriate scale for development of monitoring and fishery harvest strategies or ‘special management’.
Genetic, phenotypic and tagging techniques are available for stock identification. Genetic variation between stocks can provide a direct basis for determining stock structure, as molecular genetic techniques can be a robust tool for identifying reproductive isolation between stocks. Higher levels of genetic variation and larger numbers of alleles in some mitochondrial and nuclear (microsatellite) DNA markers suggest that DNA-based techniques usually provide greater resolution than allozyme-based techniques. Phenotypic variation between stocks can provide an indirect basis for stock structure, and although it does not provide evidence of genetic isolation between stocks, phenotypic variation can indicate whether animals in different environmental regimes have undergone prolonged isolation. Phenotypic variation in meristic and morphological characters can be used for inferring stock structure. Also, in some cases, vertebral composition, in terms of elements such as calcium, strontium, carbon and oxygen, might provide a basis for distinguishing between separate nursery areas or between regionally separated stocks. Tag release-recapture and tag tracking data can also be used for stock identification, as well as for determining patterns of migration and rates of movement between separate regions of a fishery.
Overall stock size is of primary importance for any species or population, but the stock status can be more accurately assessed if account is taken of stock structuring by sex, size, age and stage of maturity of the sharks. This sort of structuring is common among shark species, and the recapture of tagged sharks at positions long distances from the positions of release indicates that many species are highly migratory. There is also evidence of mixing between genetically distinct populations. Such complex stock structuring, together with the practice of fishers targeting more than one species, complicate interpretation of CPUE and, without spatial disaggregation of the data, can cause CPUE to be an unreliable index of relative abundance. These complexities need to be accounted for in stock assessment models.
A single population with high rates of mixing between separate regions of a fishery (whether the population be homogenously distributed or highly structured) needs to be assessed and managed as a single stock. However, a single homogenously distributed population, with low rates of mixing between separate regions of a fishery, might be more appropriately assessed and managed as regionally separate sub-stocks. Spatially-separate populations, where there is minimal mixing, should normally be assessed and managed as separate sub-stocks, but the fleet dynamics of the fishery might necessitate the fishery to be assessed and managed as a single unit. On the other hand, in shark fisheries where there are marked spatial structuring and mixing between separate breeding populations, multi-stock models are required. Furthermore, where the rates of mixing between different regions of a fishery are high, spatially-structured models incorporating movement rates between separate regions of the fishery are required for stock assessment.
5.6.1 Catch: Landings and discards
5.6.2 Fishing effort
5.6.3 Index of abundance
5.6.4 Catch composition
Total catch in numbers or weight needs to be recorded or estimated because it represents removal of biomass and individuals from the ecosystem and is the fundamental impact fishing has on fish populations. Catch data are required for most stock assessment techniques and as a variable for monitoring fluctuations in the stock. Where both weight and numbers are recorded, mean weight of shark in the catch can be determined.
Catches should be broken down into categories with as much detail as possible. The priority should be by species, location and date. Further breakdown by sex and length of shark (or broad size category or maturity) enable application of sex-based and length-based stock assessment models.
Discarding of sharks dead or in poor condition has important biological implications and should always be recorded or estimated. Total catch consists of total landings and discards. Shark bycatches, whether retained or discarded, should also be recorded.
Transhipping of sharks at sea must be incorporated into any catch monitoring scheme; otherwise a considerable proportion of the catch may be unaccounted for. This might need to be monitored with on-board observers or contacts through the Flag State of the receiving vessel.
Sharks are often headed, gutted and finned before landed ashore and facility should exist for conversion to live weight equivalent units (also called nominal catch or whole or round weight) using appropriate conversion factors. Hence, wherever forms have provision for recording weight of catch, there must also be provision for reporting the form of the sharks (i.e. whole, headed and gutted carcass with fins on, headed and gutted carcass with fins off, fins only or liver only). Without this provision catch weights will be ambiguous.
Total landings can be obtained from logbooks, sales slips or interviews with fishers or intermediaries. Discard estimates can sometimes also be obtained from fishers. Data from on-board observers during fishing trips can be valuable where detailed trip information on discards and fishing locations are not available.
Fishing effort in stock assessments can be related to fishing mortality. To relate fishing effort to fishing mortality for use in stock assessment models, it is necessary to relate it very closely to specific gear use. This varies with gear. Units of fishing effort for gillnets are kilometre-lifts or kilometre-hours which requires recording total length of gillnets and soak time. Similarly units for hooks are hook-lifts and hook-hours which requires recording total number of hooks set and soak time. Soak time becomes invalid after baits are lost from the hooks. Soak times for gillnets and longlines with baited hooks have three phases: setting period, hauling period, and period between. Units for trawls are distance trawled, which can be determined from vessel positions at start and end of each haul or from trawl time and trawl speed. Species or group of species targeted should be recorded because this can greatly affect catch per unit effort (CPUE).
Height and mesh-size of gillnets, hook-size, average distance between hooks and baits, and trawl net dimensions and codend mesh-size should also be recorded. Power of vessel and presence of navigational aids such as Global Position Fixing and colour echo sounders are relevant to fishing power of vessels.
Recording species or group of species targeted allows fishing effort to be treated as targeted effort or non-targeted effort in stock assessments.
Fishery stock assessment requires a time series of an index of abundance that is proportional to stock size. For shark stocks these can be provided from fishery CPUEs and from fishery-independent survey data.
CPUE or catch rate is a valuable index for long-term monitoring of the fishery and is often used as an index of stock abundance, where some relationship is assumed between the index and the stock size. However, CPUE alone can be an unreliable index of stock size. There can be a problem with changes of fishing efficiencies or operational patterns over time; routine surveys of fishing gear should be adopted. Also, CPUE can be misleading in a fishery where fishers targeting aggregations of fish can provide high CPUE while the stock declines rapidly (hyperstability), or, conversely, fishers removing highly vulnerable aggregations in an otherwise diffusely distributed population can cause CPUE to decline much more rapidly than stock abundance (hyperdepletion). CPUE should be separate for each stock unit, fleet and gear type. Where there is complex stock structuring the data need to be spatially disaggregated. Some of the problems of differences in efficiency between vessels and changes in areas fished from year to year can be adjusted by standardisation of CPUEs using generalized linear models; however, standardizations require careful statistical consideration of the residual (error) structures of the data.
Fishery independent survey of fish density with a standard vessel using standard fishing gear can avoid some of the biases inherent in fishery CPUE data. Such surveys can be costly and require careful design, particularly if a stratified sampling design is adopted to improve precision.
Size and/or age data for male and female sharks, separately, provide information on stock structure. Male and female sharks and other chondrichthyans can be readily distinguished by the presence of claspers on males. In fisheries where fishers remove claspers at sea but leave the pelvic fins in tact on females the animals can be sexed, but where the pelvic fins are removed from both males and females then the animals can only be sexed by onboard observers.
Size composition data can be collected by sampling vessel catches. This requires a standardized length measurement for recording lengths of shark. Because sharks are usually headed, gutted and finned, the length measurement has to be a partial length. If the position of junction between caudal fin and body trunk is readily identifiable then the longest reliable partial length on the trunk that can be measured is from the posterior edge of the last gill-slit to the base of the tail. An alternative to the last gill-slit is the anterior margin of the base of the pectoral fin or, where pectoral fins are removed, the anterior margin the pectoral girdle. Other positions on a trunk used for defining partial lengths are the bases of dorsal fins. Where sharks are landed in size categories, it is necessary to sample all categories and to apply raising procedures that lead to accurate estimates of length composition in the catch.
Conversions from partial length of landed carcass to total length or fork length of shark are required to present data in terms of total length or fork length. If it is necessary to adopt more than one standard length measurement, the data should be converted to a single standardized length, ideally total length or fork length.
Age composition of the catch is determined from length-at-age data. This involves determining ages of sharks of known length within each of a number of length-classes covering the full size range of the animals in the catch to provide an age-length key. Age-length keys can be combined with the length-frequency composition of the catch to determine the age-composition of the catch. Ageing chondrichthyans involves counting growth-increment bands in sectioned or whole vertebrae or in other hard parts such as sectioned spines. Ideally age-length keys are determined each year because of continual changes in the age composition of the population.
5.7.1 Fishing registration data
5.7.2 Enumerators/Observers
5.7.3 Resource-user reporting
5.7.4 Fishery-independent survey
Data should be collected continuously or at intervals sufficiently frequent to give time series data. There are several data collection methods that can be applied.
Registers can be used for some variables to obtain complete enumeration through a legal requirement. It is a depository of information on fishing vessels, companies, gear, licences and individual fishers. Required data on vessels include vessel type, vessel size, gear type, country of origin, fish holding capacity, number of fishers, and engine horse power.
Fishing, fish processing and marketing companies are registered for various purposes. Fishing company registers should include data on number of vessels and details of vessels and fishing gear. Fish processing and marketing companies should provide data on type of processing, type of fish and capacity of processing and marketing.
Operators of fishing vessels and fishing gears should be required to hold a valid fishing licence. Unlike vessel registers, fishing licences tend to be issued for access to specific fisheries over a set period of time. Because licences have to be periodically renewed, they provide a useful way of updating information on vessels and fishing gear.
Vessel registers are complex systems requiring well-established administrative procedures supported by effective data communications, data storage and processing components. Being such they have certain types and size of fishing units such as industrial and semi-industrial fleets. Small-scale and subsistence fisheries involving large numbers of fishing units are often not part of a registering system.
Enumerators, also referred to as observers, can make direct measurements and undertake interviews and surveys using questionnaires either on fishing vessels, at landing sites at processing plants and in markets. Enumerators can collect catch (landings and discards) and fishing effort for selected vessels, biological data, bycatch data, environmental data, value and price of landings and trade data.
At-sea observers can collect catch and effort data, which can be cross checked against a vessel’s fishing logbook. Also, they can collect details of the fishing gear, fishing operations, and biological data (sex and length-frequency composition, stage of maturity, fecundity and breeding frequency) and can collect vertebral or dorsal-spine samples for subsequent laboratory ageing.
At landing sites, processing plants and markets, observers can collect landing data (quality, quantity, value and price), carcass form of landings (e.g. headed, gutted and finned), biological data (sex, length-frequency, and vertebral samples) of landing. If sharks are landed whole, stage of maturity and spines can also be collected. Processor and market data on species and quantities purchased can be used for validation of landings reported in logbooks.
Reporting attempts to provide complete enumeration by particular resource users. This involves the preparation of forms by fishing companies, fishers, fish processors, market operators, and sometimes trading companies and custom offices. These data collection methods are best suited to industrial and semi-industrial fisheries.
Fishing companies and fishers can provide basic data on catches and fishing effort, and the submission of such data on logbook forms and/or landings declarations can be made mandatory as a condition of the fishing licence. Logbook forms should contain detailed information on catch by species, individual fishing operations, including fishing grounds (depth and latitude and longitude coordinates or grid reference), type and amount of fishing gear deployed and duration of fishing operations. Landing declarations should be a summary of catch by species for individual fishing trips. Using available company records available in pre-processed computerised format can reduce the costs of collecting the data.
Confidentiality of information (such as fishing grounds) should be part of the agreement for data submission arrangements and statistical summaries made public should not contain information that can be related to an individual vessel or company. There are risks of under-reporting or over-reporting of quantities of catch and revenues from landings and there are risks of deliberate distortion of data, especially for those related to fishing grounds.
Processing factories and markets can be required to report quantities and value of shark received, processed and sold. They could also be required to provide the vessel of origin of the catch and data of sex and length-frequency composition of the sharks handled.
Off-loading catch in processed or whole form requires considerable attention to detail. In some circumstances, off-loading may proceed directly to a processing factory or cold store. Detailed landings can be recorded provided each batch is marked with its source (vessel name, trip identifier). These records also provide information on their output and sales, including destination and price.
Market transaction records can form a feasible way of collecting landings with complete enumeration, particularly in large fleets of small-scale vessels that land in central locations. This requires complete coverage by all invoices, sales slips and sales tallies. These forms should have provision for primary identifiers on the records are name of vessel (or vessels in the case of carrier vessels unloading from distant fleets) selling the catch, the date and trip number, and total weight, price and sale value by species, or species group. These sales records should be prepared in appropriately identified forms with multiple copies for distribution to the market administration, the seller (vessel or company), the buyer and the fisheries authority.
General sales records (market, factory processing and export data) can provide data on volume of sales and prices by product form (carcass, meat, fins, vertebral columns liver, liver-oil and skins). These are valuable for bio-economic analyses but can be of limited benefit for stock assessment if they cannot be related to vessel, fishing grounds, fishing effort or species of shark.
Trade data, which refers to information from customs or other sources of trade, can also provide information on socio-economic variables and, in some cases, information on landings. Information on exports and imports is published by most countries and is important where export and/or import taxes or royalties are payable, or export incentives given. At present, trade data are the only data available for estimating shark landings in many countries. Use of trade data quantities require appropriate conversions to estimate whole weight but the value of the trade data is reduced by the often ambiguity of the form of the product. To be of more use shark products should be specified by species, as frozen or dried, and as:
- whole,
- headed and gutted carcass with skin on and fins on,
- headed and gutted carcass with skin on and fins off,
- headed and gutted carcass with skin off and fins off,
- filleted meat only,
- heads only,
- head cartilage,
- vertebral cartilage,
- powdered cartilage,
- skin only,
- fins only,
- whole livers only, or
- liver-oil.
Surveys carried out using institutional research vessels or commercial fishing vessels at the level of stock, sub-stock or species can provide indices of stock abundance and distribution. These surveys require fishing with a standard vessel using standard fishing gear at predetermined fishing stations selected according to a fixed-grid, fixed-site or stratified random sampling design. Such surveys should provide, firstly, an estimate of average fish density (per area swept by a trawl net, or as fish encounters with longlines or gillnets) over the entire spatial range where the stock(s) might be found, and, secondly, mapping of the spatial distribution of density over the entire range.
A number of countries undertake regular fishery-independent survey of their trawl fisheries. The available survey data for the more valuable teleost species are regularly analysed but most of data available for sharks and other chondrichthyans have not been systematically analysed. Similarly, fishery-independent survey of tuna and tuna-like fishes have produced valuable bycatch data on sharks that have never been analysed. Hence, opportunities exist to provide indices of abundance for a number of species by analysing available data from these surveys. States and RFMOs should give priority to analysing these data.
Scientific research is required to measure variables from shark populations and their habitats, and from the fishing gear used to harvest sharks. Such research can be carried out using institutional research vessels or commercial fishing vessels. In addition to fishery-independent survey, scientific research methods can address various objectives, which need to be addressed at the level of species or, in some cases, stock or sub-stock.
One objective is to determine life-history parameters from biological data on sex and length-frequency composition, maturity stage of ovaries and oviducal glands, number and size of ova, and number and size of in utero eggs and/or embryos. Samples of vertebrae or dorsal spines should also be collected for subsequent laboratory ageing.
In a gillnet fishery, an objective is to determine how selectivity of gillnets varies with length of shark and mesh-size of gillnet, or, in a hook fishery, an objective is to determine how selectivity of hooks varies with length of shark and hook-size. Determining selectivity parameters requires experiments using gillnets with a range of mesh-sizes or using hooks with a range of hook-size.
In a trawl fishery, an objective is to determine whether bycatch abatement devices can be developed to reduce the catch or kill of shark species.
Laboratory procedures need to be developed for ageing sharks from, depending on species, whole or sectioned vertebrae or from other calcified parts such as sectioned dorsal spines present in some chondrichthyan groups. Also depending on species, the visible clarity of growth-increment bands in these structures require chemical staining and/or special illumination or microradiography to enable interpretation for age estimation.
Tagging programmes can be adopted for estimating growth, mortality and movement rates. Sharks can be successfully tagged with internal tags inserted through the body wall into the coelomic cavity (body cavity), with rototags inserted through the bases anteriorly of dorsal fins and with dart tags inserted between the basal cartilage of the dorsal fins. Dart tags inserted into the muscle issue have low retention rates. Whenever tagging programmes are undertaken, some double tagging should be undertaken to estimate tag retention rates. Also, injecting sharks with oxytetracycline or some other hard tissue stain provides a basis for validating assumptions on the periodicity of growth-increment bands in shark vertebrae and other hard parts adopted for ageing purposes.
Many species of shark have sites where they aggregate for mating or giving birth or they predictably travel along certain migration routes to these areas. It is important to identify these sites and routes as it might be necessary to provide special protection from fishing through closed areas or closed seasons to protect the breeding fish in the population. Scientific research methods can be applied to identify and monitor critical habitats.
In addition, species with well defined nursery areas, where the newborn and young animals are found, may need special protection from the effects of fishing and habitat degradation. The nursery areas are often in shallow inshore areas where they are vulnerable to the effects of habitat change caused by industrial, domestic and agricultural development in coastal and catchment areas. Also, aquaculture, ecotourism, spread of exotic organisms and pollution in the marine environment, and, in some regions of the world, global warming and ozone thinning can impact on the nursery areas. These changes should be carefully monitored.
Data must be held in their primary form and there is a need for long-term commitment to supporting data management application. The volume of raw primary data is often very large, and so can only be utilized effectively if it is maintained in a database management system. The functions of a database are to:
- ensure data conform to standard classifications,As computing power increases it is becoming progressively easier and less costly to store and process large primary data sets. It is important database developers be involved in the design of any data collection scheme.
- ensure validity of the data,
- ensure data integrity and internal consistency of the data,
- secure and maintain primary data,
- allow easy access to the data to facilitate its synthesis,
- allow different data sets to be integrated, thereby increasing their utility and value.
A decentralised database design can be integrated with other local databases to facilitate data management and data validation. Data entered and validated locally should be made accessible to the centralised database.
Monitoring and assessment of transboundary stocks will require regional sharing of data. This will require integrating data collected though different national fishery data collection programmes. Such integration is feasible under the following conditions.
States and RFMOs should undertake and fully document stock assessment of each of the important species taken in directed fisheries and should document trends in fisheries where sharks are taken as non-targeted species or as discarded bycatch.
The life history traits of sharks differ from those of most teleosts and invertebrates and are more like those of marine and terrestrial mammals, which are of K-selected animals. Hence, in many ways, the dynamics of shark fishery stocks have more in common with marine mammal populations than they do with fisheries based on teleost or invertebrate species. Hence, the application of fishery assessment models must be applied with care.
In the absence of time series data of catches and stock abundance indices, shark populations are assessed using either demographic analysis or yield per recruit analysis which ignore density-dependent regulation. Demographic analysis is the process by which age-specific mortality and natality rates are combined to produce estimates of the net reproductive rate, inter-generation period, and intrinsic (instantaneous) rate of increase. This involves the construction of a cohort or static life table for the population, based on reliable estimates of mortality, natality, and longevity and usually assumes a stable age distribution, equal sex ratios, and a constant recruitment rate. The method of demographic analysis was recently extended to incorporate density-dependent effects by allowing adult mortality to change with population size. Yield per recruit analysis is a simpler form of demographic analysis because it does not include reproductive rates; like demographic analysis it assumes recruitment is constant and independent of stock size.
Stock assessments should incorporate a time-series of total catch estimates in numbers or weight because it represents removal of biomass and individuals from the ecosystem and is the fundamental impact fishing has on fish populations. The assessments should also incorporate a time-series of abundance indices based on CPUE or fishery-independent surveys. Where time-series of catches and stock abundance indices are available, shark populations can be assessed using biomass dynamics models. These models make the assumptions that the rate of population increase responds immediately to changes in population density and that the rate of natural increase at a given density is independent of the age composition of the stock. Whilst these assumptions might be reasonable for the short-lived more highly productive species, they are most likely invalid for long-lived species of low productivity.
Delay-difference models have advantages over biomass dynamics models in that they can incorporate some biological information. However, neither biomass dynamics nor delay-difference models can incorporate all information on shark reproduction, and both assume ‘knife-edge selection’ which is not a valid assumption in gillnet or trawl fisheries.
The most appropriate assessment models for sharks are fully age-structured non-equilibrium models that can include time-series of catch and abundance indices, the demographic parameters for growth, reproduction and natural mortality, and fishing gear selectivity parameters. These models can be adapted to incorporate ancillary data such as mean size or mean weight of shark in the catch. They can also be readily adapted to incorporate alternative assumptions on density-dependent mechanisms operating through density-dependent natural mortality, fecundity or growth. These models can also be spatially structured to use spatially disaggregated data and to allow for movement of sharks between different regions of the fishery.
Complex stock structuring of a species requires the stocks to be assessed using a spatially-structured models with spatially-disaggregated data. In some cases multi-stock models are required. Stock assessment of a fishery applying spatially-aggregated models can give highly uncertain results. Allowing for spatial- and stock-structure and combining tag release-recapture data with catch, abundance indices and demographic parameters can markedly reduce uncertainty in assessment.
Assessment of stocks in some fisheries using spatially-structured models might require there to be separate breeding sub-populations but mixing at other life history stages. Such mixing sub-stocks might exhibit philopatry (‘home loving’) effected through ‘natal homing’ whereby pregnant female sharks return to their birth place. Under this hypothesis ‘stock’ can be defined as ‘a group of animals that have the same pupping grounds and same movement patterns’. If the females from different stocks mate randomly with males then ‘stock’ is likely to be memory based rather than genetically based.
For migratory species, spatially-structured models require estimates of movement rates between the various regions of a fishery. One approach involves estimating rates of movement between separate regions, where the rate of movement is the proportion of animals leaving one region to move to another region within a specified time-step. This approach treats the contribution of each tag independently and makes use of information from both the recaptured and non-captured tagged sharks. Data inputs to the model include total fishing effort within discrete time intervals for each type of fishing gear, the gear selectivity function of each fishing gear deployed in the fishery, and region, shark length and date at the time of release and the time of recapture.
Tag release-recapture programmes are often too limited in scale to determine the number of movement parameters required for a fully spatially-structured stock assessment model. One approach is to develop a range of feasible alternative movement hypotheses, which can be developed as simulation models tuned on the basis of varying assumed movement parameter values. These parameter values then can be used as either fixed values or as starting values, which are subsequently re-estimated, in a full spatially-structured stock assessment model.
There are advantages in establishing shark fisheries and shark conservation objectives within the ‘sustainable development reference system’ (SDRS), as described in the FAO Technical Guidelines for Responsible Fisheries No. 8, Indicators for sustainable development of marine capture fisheries. The SDRS provides a framework with the four ‘economic’, ‘social’, ‘ecological’, and ‘governance’ dimensions within which to establish ‘criteria’, set ‘objectives’ and organize related ‘indicators’ and their respective ‘reference points’ (or reference values).
An efficient SDRS selects, organizes and uses indicators to deliver meaningful information about the achievement of sustainable development and policy objectives (including their legal basis) at the desired scale. It is inexpensive and simple to compile and use. It optimizes the use of information, handles different levels of complexity and scales, and facilitates integration and aggregation of indicators. In addition, it provides information that is readily communicable to stakeholders, and can contribute directly to improved decision-making processes. The development of an SDRS involves five steps.
(i) Specifying the scope of the SDRS. For sharks, this might be establishing an SDRS for a target shark fishery, for shark bycatch in a fishery targeting non-shark species, or for a shark species requiring ‘special management’.(ii) Developing a framework for indicator development. The framework can take a structural approach representing the four dimensions of sustainable development. One favoured framework is the pressure-state-response framework, which considers the pressure imposed by human activities on some aspects of the system, the states of those aspects, and desired societal responses.
(iii) Specifying criteria, objectives, potential indicators and reference points. ‘Criteria’ represent those properties of a system that will be affected by the process of sustainable development. These are determined by the four dimensions of the SDRS and within each dimension, a number of criteria should be defined for the selection of objectives, indicators and reference points. Examples of criteria include harvest, harvest value and fishery net value for the economic dimension; employment, income, fishing tradition and protein consumption for the social dimension; relative abundance, exploitation rate and catch structure for the ecological dimension; and capacity to manage, transparency of process and compliance success for the governance dimension. Criteria enhance communication, transparency, effectiveness and accountability in natural resource management.
‘Indicators’ assist in the process of assessing the performance of fisheries policies and management at global, regional, sub-regional, national and sub-national levels. They provide a readily understood tool for describing the state of fisheries resources and fisheries activities and for assessing trends relating to SDRS objectives. Indicators play an important role in the communication of scientific results to decision-makers by providing for simple outputs from complex models. Where appropriate within an SDRS dimension, indicators should be developed by firstly identifying objectives, then specifying a model (either conceptual or numerical) of the scientific understanding of the system, and finally determining the variables from the model that indicate performance relative to the objectives and for which information is available or can easily be collected. Indicators must be scientifically valid in the sense that, according to our best scientific understanding, they are indicative of the objective they are intended to reflect and utilize the best scientific information available. Also, indicators should be feasible and cost effective and easily understood. Changes in indicator values over time cannot be meaningfully interpreted in relation to SDRS without considering them in relation to a reference value corresponding to an ‘objective’, which can be either a target or a constraint (limit) identified for the system.
‘Reference values’ are conventionally called ‘target reference points’ and ‘limit reference points’ (or ‘threshold reference points’). The process of developing and stating a set of ‘objectives’ that is accepted by all stakeholders is itself a major step in the achievement of sustainable development. An SDRS places objectives in perspective and can help make relationships and trade-offs between objectives explicit. For some criteria, objectives such as maintenance or rebuilding of the fish stock may be well defined international agreements, legislation or public expectation. Others may never have been clearly articulated.
‘Objectives’ relating to given criteria need to be identified at various levels of the system. Some objectives are implied by existing international agreements or national policies, but others need to be much more specific. Examples of objectives include maintenance of a shark stock or rebuilding of a shark stock. A more specific objective is to maintain the biomass of a stock at a level capable of supporting the optimal sustainable yield that has been specified in relation to two related biomass reference points: Blimit, a limit reference point indicating the lowest level of biomass compatible with sustainability of the resource, and Btarget, a reference point indicating the level of biomass considered appropriate for the fishery and aimed at for management.
(iv) Choosing a set of indicators and reference points. The framework, the criteria and the objectives relating to each criterion should jointly give an agreed representation of what sustainable development means for a fishery, and should usually make indicator and reference point development self evident. For example if the objective is to maintain fishing mortality at a set level, then the indicator and its reference point are immediately defined. Where the objectives are less quantitative, the indicators and reference points are more difficult to define. In general, indicators should be based on policy priorities, practicality, data availability, cost-effectiveness, understanding, accuracy and precision, robustness to uncertainty, scientific validity, acceptability to stakeholders, ability to communicate information, timeliness, legal foundation, and adequate documentation.
There are five steps in choosing indicators and reference points: (i) determine criteria and specific or implied objectives, (ii) develop a conceptual model of how the system works around which to organize them, (iii) determine what indicators and potential reference points are needed for assessing progress towards the objectives, (iv) consider feasibility, data availability, cost and other factors determining the practicality of implementing the indicators, and (v) document the methods used to calculate or specify the indicators.
(v) Specifying the method of aggregation and visualization. Indicators and their interpretation need to be presented in a form easily understood by the user. Indicators can be presented as a simple value, but to compare indicators within and between different systems rescaling will be necessary. This requires converting the indicator into a ratio to create a ‘relative reference point’. For example, if a reference value of mature biomass (e.g. initial mature biomass) is prescribed then the rescaled indicator would be a ratio (or proportion) of this value and would lie in the range 0-1. There are advantages in relating the scale of the indicator to value judgements (e.g. ‘good’, fair’, ‘poor’) on the extent societal objectives are met.
The ‘precautionary approach’ (see Section 1.4) and the Sustainable Development Reference System (see section 5.11) together provide a ‘risk management’ decision-making framework for conservation of shark species and management of shark fisheries. Making decisions involves risk of an undesirable outcome resulting from uncertainty. Accounting for uncertainty in conservation of species and management of fisheries requires ‘risk assessment’.
‘Risk assessment’ for a shark stock involves quantifying uncertainty in the results from an assessment model incorporating the population dynamics of the stock given the adopted model with all its implicit and explicit assumptions and given the available data. To assess risk, the model has to include stochastic components, where one or more parameters of the model are expressed as probability distributions and/or the data, such as a time series of abundance indices, are fitted to the model as probability distributions rather than as simply mean values.
When applied to a harvested shark population, ‘risk assessment’ is concerned, for example, with calculating the probability that the population size will fall below a specified level (‘biological reference point’). Here population size might be total biomass, mature biomass, total number of animals, number of recruits, number of births or some other quantity, usually expressed as a proportion of the initial (pre-fishing) population size. Under the SDRS, these are ‘indicators’ relating to stock abundance as a ‘criterion’, the ‘biological reference point’ would be a ‘limit reference point’ and/or ‘target reference point’, and the management ‘objective’ would be to maintain the population size above the specified ‘reference point’. For ‘risk management’, however, each ‘reference point’ needs to be expressed with a ‘level of risk’ and a ‘time period for the risk’. Together these provide an appropriate framework for ‘risk analysis’ for stock assessment and, through forward projections, for evaluation of alternative harvest strategies. It also provides a framework for developing decision rules agreed to through a consultation process. Subsequently, in the event that the agreed assessment model with the agreed data predicts the ‘indicator’ falls below the ‘reference point’ (the adverse event) at the nominated risk probability within a specified time period, management actions can then be promptly implemented the need for extensive consultation. An example of how this might work would be to implement agreed and prescribed changes to the adopted (current) harvest strategy for a shark fishery if say the assessment model predicted that within 7 years (adopted ‘time period’) the mature biomass of the stock had a 20% probability risk (adopted risk level) of falling to below 40% of initial mature biomass (adopted ‘limit reference point’).
