Browsing by Subject "krill"

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    Conditioning SMOM using the agreed calendar of observed changes in predator and krill abundance: a further step in the development of a management procedure for krill fisheries in area 48
    (2008) Plagányi, Éva E; Butterworth, Doug S
    The updated version of the Spatial Multi-species Operating Model (SMOM) of krill-predatorfishery dynamics described in an accompanying paper is conditioned using the WG-SAM set of reference observations for Area 48 (the SAM calendar). Results are presented for two implementations of SMOM, one with the time series of krill abundance fixed on input, and the other incorporating an explicit model of krill dynamics. Additional versions of SMOM that may need to be conditioned are discussed. In general the two SMOM implementations are broadly successful in reproducing the direction and timing of observed changes in predator abundance. The main method of conditioning involved estimating a shape parameter (the “steepness”) of the predator-prey interaction formulation. The steepness values estimated suggest that penguins respond sooner than other predators to decreasing levels of krill abundance. Given data on fish catches, the model estimates the starting (1970) fish abundance level, with results suggesting that fish populations in several of the SSMUs are much reduced compared to their 1970 levels. The conditioned operating models presented here constitute a further step towards the development of a spatially-structured Management Procedure (MP) for the krill fishery by contributing to the set of such operating models to be used to simulation test candidate MPs for robust performance. The next step involves agreeing the relative plausibilities (weights) for the different operating models. An outline of suggested future steps in the MP development process is discussed.
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    Consideration of multi-species interactions in the Antarctic—An initial model of the minke whale–blue whale–krill interaction
    (National Inquiry Services Centre, 2004) Mori, M; Butterworth, Doug S
    As a first step in investigating the major predator–prey interactions in the Antarctic, a model describing blue whales Balaenoptera musculus, minke whales Balaenoptera acutorostrata and krill Euphausia superba is developed. Blue and minke whales feed mainly on krill, and they share a similar feeding area near the Antarctic ice edge. In the early 20th century, the large baleen whales in the Antarctic were heavily harvested, some to near extinction. Blue whales were taken for almost 60 years, before being officially protected in 1964. Harvesting of the smaller minke whales commenced only in the 1970s, and the population probably increased during the mid 20th century, likely in response to increased krill abundance following the depletion of the large baleen whales. Recent studies show recoveries of some of these large baleen whale species in response to protection, and also a possible recent decrease in the stock of minke whales as the larger whales recover. This work investigates whether the abundance trends indicated by surveys and other information for these species can be explained by considering only harvesting and the predator–prey interactions between the two whale species and krill. Using historical catch data for blue and minke whales, a simple age-aggregated model including species interactions is fitted to survey abundance estimates. Uncertainties in the abundance estimates and the biological parameters are taken into account in the process by considering plausible ranges for their values. Abundance trends for the species can broadly be replicated by the model, provided the parameter values show certain features, including (i) that blue whales are able to maintain their birth and krill consumption rates until krill abundance drops to relatively low levels, and (ii) that both minke and blue whales show relatively fast rates of growth if krill is abundant, but that minke growth rate falls more rapidly as krill abundance drops. The model suggests two interesting features of the dynamics of these species. First, a substantial decrease in krill biomass from the 1970s to the 1990s as a result of the preceding rapid increase in minke whale abundance, and hence krill consumption, following the depletion of the larger baleen whales. Second, a recovery of blue whales despite the impact of minke whales on krill abundance and its resultant decrease, because blue whales are better able to tolerate decreased krill abundance. Future projections show a gradual increasing trend in blue whale abundance and a gradual decrease in minke abundance, with large amplitude oscillations superimposed. Long-term monitoring of biological parameters and abundance are essential to provide a basis for verification or otherwise of such predictions. Results presented here should be viewed qualitatively rather than quantitatively. However, for the future, refinement of the model structure and incorporation of age structure, data on some other major predator species that feed on krill and some spatial structure, is under consideration.
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    Consideration of multispecies interactions in the Antarctic: a preliminary model of the minke whale – blue whale – krill interaction
    (National Inquiry Services Centre, 2004) Mori, M; Butterworth, Doug S
    As a first step in investigating the major predator–prey interactions in the Antarctic, a model describing blue whales Balaenoptera musculus, minke whales Balaenoptera acutorostrata and krill Euphausia superba is developed. Blue and minke whales feed mainly on krill, and they share a similar feeding area near the Antarctic ice edge. In the early 20th century, the large baleen whales in the Antarctic were heavily harvested, some to near extinction. Blue whales were taken for almost 60 years, before being officially protected in 1964. Harvesting of the smaller minke whales commenced only in the 1970s, and the population probably increased during the mid 20th century, likely in response to increased krill abundance following the depletion of the large baleen whales. Recent studies show recoveries of some of these large baleen whale species in response to protection, and also a possible recent decrease in the stock of minke whales as the larger whales recover. This work investigates whether the abundance trends indicated by surveys and other information for these species can be explained by considering only harvesting and the predator–prey interactions between the two whale species and krill. Using historical catch data for blue and minke whales, a simple age-aggregated model including species interactions is fitted to survey abundance estimates. Uncertainties in the abundance estimates and the biological parameters are taken into account in the process by considering plausible ranges for their values. Abundance trends for the species can broadly be replicated by the model, provided the parameter values show certain features, including (i) that blue whales are able to maintain their birth and krill consumption rates until krill abundance drops to relatively low levels, and (ii) that both minke and blue whales show relatively fast rates of growth if krill is abundant, but that minke growth rate falls more rapidly as krill abundance drops. The model suggests two interesting features of the dynamics of these species. First, a substantial decrease in krill biomass from the 1970s to the 1990s as a result of the preceding rapid increase in minke whale abundance, and hence krill consumption, following the depletion of the larger baleen whales. Second, a recovery of blue whales despite the impact of minke whales on krill abundance and its resultant decrease, because blue whales are better able to tolerate decreased krill abundance. Future projections show a gradual increasing trend in blue whale abundance and a gradual decrease in minke abundance, with large amplitude oscillations superimposed. Long-term monitoring of biological parameters and abundance are essential to provide a basis for verification or otherwise of such predictions. Results presented here should be viewed qualitatively rather than quantitatively. However, for the future, refinement of the model structure and incorporation of age structure, data on some other major predator species that feed on krill and some spatial structure, is under consideration.
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    A first step towards modeling the krill-predator dynamics of the Antarctic ecosystem
    (Ccamlr Science, 2006) Mori, M; Butterworth, Doug S
    The history of human harvests of seals, whales, fish and krill in the Antarctic is summarised briefly, and the central role played by krill emphasised. The background to the hypothesis of a krill surplus in the mid-20th century is described, and the information on population and trend levels that has become available since the postulate was first advanced is discussed. The objective of the study is to determine whether predator–prey interactions alone can broadly explain observed population trends without the need for recourse to environmental change hypotheses. A model is developed including krill, four baleen whale (blue, fin, humpback and minke) and two seal (Antarctic fur and crabeater) species. The model commences in 1780 (the onset of fur seal harvests) and distinguishes the Atlantic/ Indian and Pacific Ocean sectors of the Southern Ocean in view of the much larger past harvests in the former. A reference case and six sensitivities are fitted to available data on predator abundances and trends, and the plausibility of the results and the assumptions on which they are based is discussed, together with suggested further areas for investigation. Amongst the key inferences of the study are that: (i) species interaction effects alone can explain observed predator abundance trends, though not without some difficulty; (ii) it is necessary to consider other species, in addition to baleen whales and krill, to explain observed trends – crabeater seals seemingly play an important role and constitute a particular priority for improved abundance and trend information; (iii) the Atlantic/ Indian Ocean sector shows major changes in species abundances, in contrast to the Pacific Ocean sector, which is much more stable; (iv) baleen whales have to be able to achieve relatively high growth rates to explain observed trends; and (v) Laws’ (1977) estimate of some 150 million tonnes for the krill surplus may be appreciably too high as a result of his calculations omitting consideration of density-dependent effects in feeding rates.
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    Open Access
    A first step towards modelling the krill–predator dynamics of the Antarctic ecosystem
    (2006) Mori, M; Butterworth, Doug S
    The history of human harvests of seals, whales, fish and krill in the Antarctic is summarised briefly, and the central role played by krill emphasised. The background to the hypothesis of a krill surplus in the mid-20th century is described, and the information on population and trend levels that has become available since the postulate was first advanced is discussed. The objective of the study is to determine whether predator–prey interactions alone can broadly explain observed population trends without the need for recourse to environmental change hypotheses. A model is developed including krill, four baleen whale (blue, fin, humpback and minke) and two seal (Antarctic fur and crabeater) species. The model commences in 1780 (the onset of fur seal harvests) and distinguishes the Atlantic/ Indian and Pacific Ocean sectors of the Southern Ocean in view of the much larger past harvests in the former. A reference case and six sensitivities are fitted to available data on predator abundances and trends, and the plausibility of the results and the assumptions on which they are based is discussed, together with suggested further areas for investigation. Amongst the key inferences of the study are that: (i) species interaction effects alone can explain observed predator abundance trends, though not without some difficulty; (ii) it is necessary to consider other species, in addition to baleen whales and krill, to explain observed trends – crabeater seals seemingly play an important role and constitute a particular priority for improved abundance and trend information; (iii) the Atlantic/ Indian Ocean sector shows major changes in species abundances, in contrast to the Pacific Ocean sector, which is much more stable; (iv) baleen whales have to be able to achieve relatively high growth rates to explain observed trends; and (v) Laws’ (1977) estimate of some 150 million tonnes for the krill surplus may be appreciably too high as a result of his calculations omitting consideration of density-dependent effects in feeding rates.
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    Reference observations for validating and tuning operating models for krill fishery management in area 48
    (2008) Hill, Simeon; Hinke, Jefferson; Plagányi, Eva; Watters, George
    In 2007 WG-SAM defined a set of reference observations for validating and tuning proposed models to evaluate krill catch allocation options for Area 48 (the SAM calendar). The observations, which were endorsed by WG-EMM, were largely qualitative and relative. We used available data to translate these observations into numerical terms (the numerical calendar). We provide spatially-resolved reference points for the density of krill, and the abundance of “generic” seals, penguins and whales in 1970, 2007 and at least one intermediate year. Recent work on baleen whales indicates a higher growth rate than that suggested by WG-SAM, so the numerical calendar for this taxon deviates from the SAM calendar. The numerical calendar is a partly subjective interpretation of limited data and should not be considered a definitive description of the relevant dynamics. This exercise resulted in population sizes for several taxa that are adjusted for asynchronous observations and are potentially more suitable for initialising models than those published in Hill et al (2007).
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    A Spatial Multi-species Operating Model (SMOM) of krill–predator interactions in small-scale management units in the Scotia Sea
    (2006) Plagányi, Éva E; Butterworth, Doug S
    A Spatial Multi-species Operating Model (SMOM) of the underlying krill-predator-fishery dynamics is developed in response to requests for scientific advice regarding the subdivision of the precautionary catch limit for krill among 15 small-scale management units (SSMUs) in the Scotia Sea to reduce the potential impact of fishing on land-based predators. The model is intended to complement the outputs from the KPFM. The model includes all 15 SSMUs and uses an annual timestep to update the numbers of krill in each of the SSMUs, as well as the numbers of predator species in each of these areas. The model currently includes only two predator groups (penguins and seals) but is configured so that there is essentially no upper limit on the number of predator species which can be included. Given the numerous uncertainties regarding the choice of parameter values, a Reference Set is used in preference to a single Reference Case operating model. The initial Reference Set used comprises 12 alternative combinations that essentially try to bound the uncertainty in the choice of survival estimates as well as the breeding success relationship. The model is coded in AD Model Builder and quickly generates large numbers of stochastic replicates to explore different hypotheses such as that related to the transport of krill. The SMOM developed here is intended for use as an operating model in a formal MP framework described in an accompanying paper. Different MPs are simulation tested with their performances being compared on the basis of an agreed set of performance statistics which essentially compare the risks of reducing the abundance of predators below certain levels, as well as comparing the variability in future average krill catches per SSMU associated with each MP.
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    Open Access
    A spatial multi-species operating model of the Antarctic Peninsula krill fishery and its impacts on land-breeding predators
    (2007) Plagányi, Éva E; Butterworth, Doug S
    The west coast rock lobster assessment of 20061 based on data to 2004 is updated to include data up to 2008. Over the last four years the exploitable biomass trend is upwards for Areas 7 and 8 and the resource as a whole, but downwards for Areas 5+6 and almost level for Areas 1+2 and 3+4. The overall increase since 2006 is significant at the 5% level. While better than median projections at the time the current OMP developed, the increase remains within the 95% probability intervals calculated at the time. An updated version of the Spatial Multi-species Operating Model (SMOM) of krillpredator-fishery dynamics is described. This has been developed in response to requests for scientific advice regarding the subdivision of the precautionary catch limit for krill among 15 small-scale management units (SSMUs) in the Scotia Sea, to reduce the potential impact of fishing on land-based predators. 2. The numerous uncertainties regarding the appropriate choice of parameter values in multi-species models is a major impediment. A pragmatic method proposed involves use of an operating model comprising alternative combinations that essentially try to bound the uncertainty in, for example, the choice of survival rate estimates as well as the functional relationships between predators and prey. 3. The operating model is assumed to simulate the “true” dynamics of the resource and is used to test decision rules for adjusting fishing activities (e.g. catch limits) based on field data forthcoming in the future. 4. An illustrative Management Procedure (MP) that includes a feedback structure is shown to perform better in terms of low risk to predators within each SSMU, than an approach lacking the ability to react and self-correct. 5. This modeling framework provides an example of a method for bounding some of the uncertainty associated with multi-species models used for management. Results are presented as probability envelopes rather than in point estimate form, giving a truer reflection of the uncertainty inherent in outcomes predicted on the basis of multi-species models, as well as highlighting how such probability envelopes could be narrowed given improved data on key parameters such as survival. Results are useful for evaluating the relative merits of different spatial allocations of krill catches. An example is given of 2 how such a framework can be used to develop a management scheme which includes feedback through management control rules.