Recent shifts towards ecosystem based fisheries management (EBFM) around the world have necessitated consideration of effects of fishing on a larger range of species than previously. Non-selective multispecies fisheries are particularly problematic for EBFM, as they can contribute to erosion of ecosystem structure. The trade-off between catch of productive commercial species and abundance of low-productivity species is unavoidable in most multispecies fisheries. A first step in evaluation of this trade-off is estimation of productivity of different species but this is often hampered by poor data. This thesis develops techniques for estimating productivity for data-limited species and aims to help clarify EBFM policy objectives for the fisheries of New South Wales (NSW), Australia. It begins with development of an age-structured model parameterised in terms of optimal harvest rate, UMSY. UMSY is a measure of productivity, comparable among species and easily communicated to managers. It also represents a valid threshold for prevention of overfishing. The model is used to derive UMSY for 54 Atlantic fish stocks for which recruitment parameters had previously been estimated. In most cases, UMSY was strongly limited by the age at which fish were first caught. However, for some species, UMSY was more strongly constrained by life history attributes. The model was then applied to twelve species of Australian deepwater dogshark (Order Squaliformes), known to have been severely depleted by fishing. Results showed that the range of possible values of UMSY for these species is very low indeed. These findings enabled a preliminary stock assessment for three dogsharks (Centrophorus spp.) currently being considered for threatened species listing. Preliminary results suggest they have been overfished and that overfishing continues. Finally, an Ecopath with Ecosim ecosystem model, representing the 1976 NSW continental slope, is used to illustrate trade-offs in implementation of fishing policies under alternative policy objectives. Results are compared with those of a biogeochemical ecosystem model (Atlantis) of the same system, built by scientists from CSIRO. While there were large differences in model predictions for individual species, they gave similar results when ranking alternative fishing policies, suggesting that ecosystem models may be useful for exploring broad-scale strategic management options.

Recent shifts towards ecosystem based fisheries management (EBFM) around the world have necessitated consideration of effects of fishing on a larger range of species than previously. Non-selective multispecies fisheries are particularly problematic for EBFM, as they can contribute to erosion of ecosystem structure. The trade-off between catch of productive commercial species and abundance of low-productivity species is unavoidable in most multispecies fisheries. A first step in evaluation of this trade-off is estimation of productivity of different species but this is often hampered by poor data. This thesis develops techniques for estimating productivity for data-limited species and aims to help clarify EBFM policy objectives for the fisheries of New South Wales (NSW), Australia. It begins with development of an age-structured model parameterised in terms of optimal harvest rate, UMSY. UMSY is a measure of productivity, comparable among species and easily communicated to managers. It also represents a valid threshold for prevention of overfishing. The model is used to derive UMSY for 54 Atlantic fish stocks for which recruitment parameters had previously been estimated. In most cases, UMSY was strongly limited by the age at which fish were first caught. However, for some species, UMSY was more strongly constrained by life history attributes. The model was then applied to twelve species of Australian deepwater dogshark (Order Squaliformes), known to have been severely depleted by fishing. Results showed that the range of possible values of UMSY for these species is very low indeed. These findings enabled a preliminary stock assessment for three dogsharks (Centrophorus spp.) currently being considered for threatened species listing. Preliminary results suggest they have been overfished and that overfishing continues. Finally, an Ecopath with Ecosim ecosystem model, representing the 1976 NSW continental slope, is used to illustrate trade-offs in implementation of fishing policies under alternative policy objectives. Results are compared with those of a biogeochemical ecosystem model (Atlantis) of the same system, built by scientists from CSIRO. While there were large differences in model predictions for individual species, they gave similar results when ranking alternative fishing policies, suggesting that ecosystem models may be useful for exploring broad-scale strategic management options.

Recent shifts towards ecosystem based fisheries management (EBFM) around the world have necessitated consideration of effects of fishing on a larger range of species than previously. Non-selective multispecies fisheries are particularly problematic for EBFM, as they can contribute to erosion of ecosystem structure. The trade-off between catch of productive commercial species and abundance of low-productivity species is unavoidable in most multispecies fisheries. A first step in evaluation of this trade-off is estimation of productivity of different species but this is often hampered by poor data. This thesis develops techniques for estimating productivity for data-limited species and aims to help clarify EBFM policy objectives for the fisheries of New South Wales (NSW), Australia. It begins with development of an age-structured model parameterised in terms of optimal harvest rate, UMSY. UMSY is a measure of productivity, comparable among species and easily communicated to managers. It also represents a valid threshold for prevention of overfishing. The model is used to derive UMSY for 54 Atlantic fish stocks for which recruitment parameters had previously been estimated. In most cases, UMSY was strongly limited by the age at which fish were first caught. However, for some species, UMSY was more strongly constrained by life history attributes. The model was then applied to twelve species of Australian deepwater dogshark (Order Squaliformes), known to have been severely depleted by fishing. Results showed that the range of possible values of UMSY for these species is very low indeed. These findings enabled a preliminary stock assessment for three dogsharks (Centrophorus spp.) currently being considered for threatened species listing. Preliminary results suggest they have been overfished and that overfishing continues. Finally, an Ecopath with Ecosim ecosystem model, representing the 1976 NSW continental slope, is used to illustrate trade-offs in implementation of fishing policies under alternative policy objectives. Results are compared with those of a biogeochemical ecosystem model (Atlantis) of the same system, built by scientists from CSIRO. While there were large differences in model predictions for individual species, they gave similar results when ranking alternative fishing policies, suggesting that ecosystem models may be useful for exploring broad-scale strategic management options. / Science, Faculty of / Resources, Environment and Sustainability (IRES), Institute for / Graduate

At the end of the 20th century, the combination of climatic and anthropogenic events resulted in hyper salinity conditions in the coastal wetland Ciénaga Grande de Santa Marta (CGSM), Colombia. Although salinity concentrations are generally related to the type and quantity of water entering and exiting a wetland and to its internal hydrological dynamics, there have been no up to date hydrological studies on the CGSM. Here we show how a water budget can be used as a first-order of approximation to describe the CGSM's hydrology, despite data limitations. We collected hydroclimatic data to calculate and analyze the fluxes of water entering and exiting CGSM and their corresponding uncertainties. We find that the water budget is mostly affected by the precipitation regime, a result connected to studies of regional El Niño/La Niña effects. Scenario analyses show that contribution of freshwater from the streams coming down from the Sierra Nevada Mountain Range on the eastern side of CGSM is currently larger than that of the channels draining from Magdalena River to the west, in contrast to the general focus on the western side. However, Monte Carlo simulations suggest that the eastern freshwater inflow is insignificant in affecting the hydrological response of CGSM. These results outline the need to (1) increase understanding of the internal connectivity and circulation of CGSM and (2) further investigate the effect of agriculture on the eastern side of CGSM.

付記する学位プログラム名: グローバル生存学大学院連携プログラム / 京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20341号 / 工博第4278号 / 新制||工||1662(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 寶 馨, 教授 立川 康人, 准教授 佐山 敬洋 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

L’évaluation et la gestion des stocks de poissons ont pour objectif d’atteindre une exploitation durable des ressources fournies par les océans. Si les progrès dans ce domaine sont bien réels pour certains stocks de grande importance commerciale, la situation est différente pour les stocks dits à données limitées. Souvent historiquement moins exploités, ces stocks ne bénéficient pas des mêmes ressources, tant économiques qu’humaines, pour réaliser une évaluation de stock permettant par la suite la mise en place de mesures de gestion. Ce travail s’appuie sur deux cas d’étude, le lieu jaune (Pollachius pollachius) et la seiche (Sepia officinalis), afin d’explorer des méthodologies d’évaluation de stocks adaptées aux situations de données limitées. Après une première partie introductive reprenant le contexte de l’évaluation des stocks et présentant les deux cas d’étude, une revue des méthodes d’évaluation de stocks à données limitées est proposée. Une troisième partie compare les résultats d’un modèle de biomasse à deux stades et d’un modèle multi-annuel de déplétion généralisé appliqués au stock de seiche de Manche. Une version améliorée du modèle de biomasse à deux stades codé en Bayésien est également présentée. Le travail se poursuit avec l’application d’un modèle d’analyse intégrée Stock Synthesis au stock de lieu jaune de mer Celtique. Les résultats sont comparés aux résultats de modèles plus simples nécessitant moins de données. Les résultats du modèle Stock Synthesis s’avèrent sensibles aux hypothèses sur la valeur de mortalité naturelle, dont le calcul dépend des paramètres de croissance du stock. La cinquième partie présente l’acquisition et le traitement de nouvelles données qui pourront permettre une meilleure estimation de l’état du stock de lieu jaune. Un modèle hiérarchique Bayésien est construit, permettant un transfert d’information entre trois stocks et la mise à jour des paramètres biologiques du lieu jaune. Le dernier chapitre conclut ce travail en reprenant les principaux résultats obtenus et en élargissant la discussion sur des perspectives de recherche. / The assessment and the management of fish stocks aim at achieving a sustainable exploitation of the resources provided by the oceans. While progress have been made in this field for some stocks of great commercial importance, the situation is different for the so-called “data limited” stocks. Often historically less exploited, these stocks do not benefit from the same economical resources nor workforce to conduct the stock assessments required to set management measures. This work is based on two case studies, pollack (Pollachius pollachius) and cuttlefish (Sepia officinalis). The aim is to investigate the stock assessment methods adapted to data-limited situations. A first introductive part presents the background of fish stock assessment as well as the two case studies. This first chapter is followed by a review of data-limited stock assessment methods. The third part compare the results of a two-stage biomass model with the results of a multi-annual generalized depletion model applied to the English Channel stock of cuttlefish. An improved version of the Bayesian two-stage biomass model is also presented. In the fourth part, a Stock Synthesis model based on integrated analysis methods is applied to the stock of pollack in the Celtic Seas Ecoregion. The results are compared to the results of simpler models which require less data. The Stock Synthesis model results are sensitive to the assumptions on the natural mortality value, which relies on the growth parameters of the stock. The fifth part presents the collection and analysis of new data which will allow a better estimate of pollack stock status. A Bayesian hierarchical model is constructed, allowing information transfer between three stocks and the update of pollack biological parameters. The last chapter concludes this work by summarizing the main results. The discussion is extended to the research perspectives.