*********** +++++++++++++++++++++ 070995B.BIO + Source: ONR Asia + *********** +++++++++++++++++++++ Contributory Categories: ENG, ENV Country: South Africa From: Meeting Program and Abstracts KEYWORDS: South Africa; Modelling, Natural Resources, Biology, Biological Oceanography +++++ 1995 WORLD CONFERENCE ON NATURAL RESOURCE MODELLING UNIVERSITY OF NATAL PIETERMARITZBURG, SOUTH AFRICA 5-10 JULY, 1995 Compiled by John Hearne Part III of V Marine related Abstracts: Biology-related in Parts III and IV +++++ 7 Items 1. METAPOPULATION DYNAMICS OF SESSILE MARINE ORGANISMS WITH A DISPERSIVE LARVAL PHASE - A MULTISPECIES SIMULATION STUDY. Robert Campbell' Tony Smith I , Alan Butler2 1. CSIRO Division of Fisheries, GPO Box 1538, Hobart, Tasmania, 7001, Australia 2. Department of Zoology, University of Adelaide, GPO Box 498, Adelaide, 5001, Australia The habitat of many species is not uniformly distributed over space, but occurs as discrete patches of suitable habitat. The populations which inhabit these discrete patches can be considered to be separate except to the extent that there is dispersal among the isolated habitats. Such a collection of populations is known as a metapopulation. We develop here a multispecies model to simulate the joint dynamics of a number of metapopulations, each composed of a number of populations of sessile organisms (eg. barnacles, ascidians, sponges, bryozoans) and which have a freely dispersed larval phase.Each population is confined to one of several habitats (or'patches') and consists of a number of individual organisms occupying the patch, though it is possible that some species may have become extinct on some patches. This situation may persist or change depending on the possibilities of dispersal and settlement of larvae onto this patch from the other patches. There is competition between organisms of the same and of different species for space within eachpatch. The effects of such competition will control both the growth of the organisms and recruitment via larval settlement, since both processes are usually limited by the availability of bare space on each patch. This dependence of growth and recruitment on the availability of vacant space provides the density dependence that leads to population regulation. A further feature of the model is the inclusion of a detailed within-patch sub-model with explicit spatial representation of individual organisms. This, together with the inclusion of multispecies interaction between metapopulations extends many previous studies of such systems. The model is used to investigate both the persistence of individual species with differing population dynamics and the processes which maintain overall species diversity (number and size of patches, spatial configuration, disturbances). The impact of differing kinds of management actions (removing patches, increasing levels of disturbance, altering dispersal between patches, introduction of new species) is also investigated. +++++ 2. PHYSICS ENVY IN STUDYING MOVEMENTS OF BIOTA CAN LEAD TO MALADJUSTED POPULATION MODELS. Ashley Mullen Inter-American Tropical Tuna Commission, c/o Scripps Institution of Oceanography, La Jolla, CA 92093 USA There are two forms to describe dispersion that can have very different solutions: closed systems tend towards uniformity in one case, while a heterogeneous solution may commonly arise from the other. In the case of living organisms, uniform density is the exception rather than the rule. The second form is therefore more sensible in most cases, then spatially variable dispersion provides a mechanism for aggregation. If a markov model is assumed for the movement of individuals, this imposes certain constraints on the change of spatial distribution. These constraints allow the coefficients of dispersion to be estimated iteratively given consecutive estimates of the spatial distribution of the population. One might have as much confidence in certain of the constraints on movement as in the estimates of distribution, and sometimes more. If so, then those constraints can be used to modify the estimates of abundance. This imparts something of the flavour of a Kalman filter to the procedure. In principle, the procedure could be applied to any mobile organism. It was developped to model the movement and redistribution of yellowfin tuna in the eastern Pacific Ocean. If time permits, some of the implications concerning the revised estimates for the distribution of yellowfin will be discussed. +++++ 3. TEACHING FISHERY MANAGEMENT CONCEPTS USING SIMULATION MODELLING AND IMAGES. R. Day, C. McNaught* and L. Sorgefti' Zoology Department, University of Melbourne, Parkville, Vic., 3052, Australia. *Academic Development Unit, La Trobe University, Bundoora, Vic., 3083, Australia. +Multimedia Development, 14 Horfield Avenue, Box Hill North, Vic., 3129, Australia. A graphical computer simulation of abalone fishery management (ABASIM), produced for fishers and managers by the South Australian Department of Fisheries was modified for teaching students by adding explanatory screens, as such simulations cannot themselves provide the context for learning. Evaluation trials showed students often focus on and learn the game rather than the contextual meaning of the simulation, and seldom refer to explanations of terms.Student responses and comments suggested that more interesting visual reference explanations and interactive explanation of issues was needed to attract attention to, and bring home the context. We used a multimedia package to develop ABMANAGER, which has interactive problem scenarios, with highlighted terms linked to reference explanations that incorporated pictures and cartoons. Preliminary evaluations show increased use and enhanced learning of the concepts in the reference explanations, and also that the better students appeared to develop anunderstanding of how the model related to the fisheries managemnent context. Students rated the reference material less interesting but more useful than the problem scenarios, and found the"open" simulation, where they could set up their own scenarios, less enjoyable. +++++ 4. A PREDICTIVE MODEL OF ILLEGAL FISHING Anthony T. Charles', R. Leigh Mazanyl and Melvin L. Cross Finance & Management Science, Saint Mary's University, Halifax, Canada I Department of Lconomics, Dalhousie University, Halifax, Canada The need for fishery management arises from the fact that in most cases, fishers wish to catch more, collectively, than is socially desirable in terms of conservation and inter-temporal equity. Management may attempt to restrict fishers' inputs (such as gear or labour usage) or their outputs (harvest levels), but in either case, there remains an inherent incentive to violate these restrictions. While enforcement efforts attempt to minimize such violations, no enforcement is perfect, and some level of illegal fishing activity is likely to occur. The model presented here seeks to predict the extent of such illegal fishing, by analysing the behavioral responses of individual profit-maximizing fishers to imperfectly-enforced regulations. For the two cases of input controls and of output controls, the fisher's optimal within-year harvesting strategy (including the "optimal" level of illegalactivity) is derived for a general case and a linear- quadratic specification of the model. +++++ 5. A FRAMEWORK FOR ANALYSING RETURNS FROM RESEARCH FOR FISHERY MANAGEMENT A. David McDonald and Anthony D.M. Smith Division of Fisheries CSIRO PO Box 1538 HOBART, TASMANIA 7001 AUSTRALIA Traditional methods for evaluating potential or actual returns from research and development include scoring methods, cost- benefit analysis and production-function approaches. These have often been used for quantitative assessments by researchers and in aggregated industry settings. The focus has been on comparative statics with limited attention paid to temporal dynamics or risk and uncertainty. The research reported in the present paper complements these traditional methods with the use of statistical decision analysis and Bayesian methods to account explicitly for risk and uncertainty and to capture some of the effects of information evolution. A measure of the expected returns from such research is proposed and illustrated by example. 6. THE MANAGEMENT PROCEDURE FOR SOUTH AFICAN PILCHARD AND SOME ALTERNATIVES. J A A de Oliveira Sea Fisheries Research Institute Private Bag X2 Rogge Bay 8012 Cape Town South Africa Management of the pilchard resource is presently a controversial issue within the pelagic fishing community of South Africa. The management procedure currently adopted for pilchard calculates directed and bycatch TACs separately. Directed catches of pilchard are mainly canned for human consumption, while bycatches are taken during fishing for anchovy and redeye, which are used primarily in the important fish meal and oil industry. In recent years the pilchard bycatch TAC has been placing severe restrictions on realising the anchovy TAC. The directed TAC is calculated as a proportion of the 1+ biomass survey result, while the bycatch TAC is the sum of two quantities. The first is a constant denoting the adult component of bycatch, and the second is a proportion of the anchovy TAC and denotes the juvenile component of bycatch. The pelagic industry claim that the current management procedure is inflexible and sets unrealistically low bycatch TACS. However, the industry also support the existing policy of encouraging growth of the pilchard resource. In order to introduce greater flexibility, it has been suggested that the industry be allowed to utilise their pilchard quotas for either directed catch or bycatch according to their needs. However, it has been calculated that, within the current management procedure, a 100% tradeoff of directed TAC for juvenile bycatch TAC will have to occur at the rate of 6.5: 1 so as to impose no increased risk of collapse of the resource, while maintaining similar levels of future growth. An alternative management procedure, where the juvenile component of bycatch is calculated independently of the anchovy TAC, has been considered; although moderately higher levels of bycatch could be achieved for the same risk of collapse, this would be at the expense of future growth. A management procedure with a constant juvenile bycatch component is also an attractive alternative; such a procedure initially achieves a higher bycatch allocation, but circumstances leading to a high anchovy-juvenile pilchard mix at sea could render it as inadequate as the other options. +++++ 7. DO PELAGIC FISH SCHOOLS CLUSTER? Gordon Swartzman Applied Physics Laboratory HN-10 University of Washington Seattle WA 98195 USA In this paper I review evidence, based on acoustic surveys conducted in the Bering Sea and in the California-Oregon- Washington Pacific Eastern Boundary Current, about the clustering of pelagic fish schools. I will discuss environmental conditions that appear to lead to larger school clusters. I will then review the implications of school clustering to 1. Fishery management 2. Foraging theory 3. Fishery Survey design 4. Fishing activity and strategy While these results are based on relatively short term examination of a limited number of ecosystems (2 or 3), it is tempting to generalize results to other coastal pelagic stocks because of the similarity of coastal conditions (e.g. upwelling or mixing along a shelf slope) that lead to school clustering. +++++ End Part III/V: Biology related abstracts continue in Part IV CMR Disclaimer================================================== This document could contain information all or part of which is or may be copyrighted in a number of countries. Therefore, commercial copying and/or further dissemination of this text is expressly prohibited without obtaining the permission of the copyright owner(s) except in the United States and other countries for certain personal and educational uses as prescribed by the "fair copy" provisions of that countries Copyright Statues. ================================================================ ************** END Msg. 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