Pelz, G. R. (1991). Lebensraum und Fischfauna der Grenzgewässer Mosel – Sauer – Our. Köln: Advanced Biology Verlagsgesellschaft.
Schlüsselwörter: Fisch, Verbreitung, Vorkommen, Kartierung
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Pedroli, J. - C., Zaugg, B., & Kirchhofer, A. (1991). Verbreitungsatlas der Fische und Rundmäuler der Schweiz. Neuchatel: Schweizerisches Zentrum für kartographische Erfassung der Fauna.
Schlüsselwörter: Fisch, Verbreitung, Gesamtwerk
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1991. (1991). Die Fische des Chiemsees. Prien: Columba Verlag.
Schlüsselwörter: Fisch, Arteninventar, See
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Fiedler, K. (1991). Lehrbuch der Speziellen Zoologie. Band II – Wirbeltiere. 2. Teil – Fische. Jena: Fischer Verlag.
Schlüsselwörter: Zoologie, Biologie, Ökologie, Taxonomie, Systematik, Fisch
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(1991). Kreis Herford: Fische der Fließgewässer. Herford: Amt für Landschaftsökologie.
Schlüsselwörter: Fisch, Verbreitung, Vorkommen, Kartierung
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Criddle, K. R. (1991). Modelling dynamic fish populations. Seattle, WA (USA): National Marine Fisheries Serv.
Zusammenfassung: A recently introduced multivariate state-space time-series modeling algorithm, system-theoretic time-series, can be used to create a particularly robust state-space representation. Combining the model approximation methodology with time-series modeling of the residuals in accurate models of short-run dynamics. The approximate structural modeling methodology is illustrated with single species models of yellowfin sole (Limanda aspera ) biomass, and multispecies models of Pacific halibut (Hippoglossus stenolepis ), yellowfin sole, and red king crab (Paralithodes camtschatica ) biomasses in the eastern Bering Sea. A final application of the approximate structural/system-theoretic time-series model includes walleye pollock (Theragra chalcogramma ), Pacific halibut, Pacific cod (Gadus macrocephalus ), yellowfin sole, and red king crab. (Prepared in cooperation with Alaska Univ., Fairbanks.)
Schlüsselwörter: fishery-biology; commercial-species; Limanda-aspera; Hippoglossus-stenolepis; Paralithodes-camtschatica; Theragra-chalcogramma; Gadus-macrocephalus; mathematical-models; biomass-; INE,-USA,-Alaska
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Diercking, R., & Wehrmann, L. (1991). Artenschutzprogramm: Fische und Rundmäuler in Hamburg. Hamburg: Umweltbehörde Hamburg.
Schlüsselwörter: Fisch, Vorkommen, Verbreitung, Kartierung
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Gerster, S. (1991). Hochrhein-Fischfauna im Wandel der Zeit. Interantionale Fischereikommision für den Hochrhein.
Schlüsselwörter: Fisch, Rhein
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Kaiser, M. S. (1991). Statistical models for limiting factors in ecology.
Zusammenfassung: For several decades, aquatic ecologists have debated differing viewpoints on the factors that control ecosystem productivity. Much of the controversy centers on the interpretation of empirical relationships between factors that limit the amount of energy transferred among trophic levels in aquatic ecosystems. The primary statistical tool used has been regression analysis, but such models often fail to explain a substantial portion of the variability observed. The suggestion has been made in the literature of aquatic ecology that regression models may be inappropriate, and that limiting factors may be better related to the maximum rather than mean response. Statistical models that account for the large variability in relationships between limiting factors and response variables at higher trophic levels and shift the focus from description of expected values to description of upper boundaries have not been developed. The goal of this project was to develop statistical models for the relationships between limiting factors and the maximum output of biological processes. A number of models may be formulated, one of the primary being Y sub(i) – gamma x sub(i)U sub(i) + sigma epsilon sub(i), where gamma > 0, U sub(i) similar to iid Beta ( alpha , beta ), the x's are considered fixed values on the real line, and the error terms, epsilon sub(i), are centered iid random variables. This model describes a triangular array of points lying between zero and a straight line with positive slope, a data pattern seen numerous times in the ecological literature. The response variable Y is an identifiable mixture of the random variable U, with the model representing a situation in which Y is observed but U is unobserved. Maximum likelihood estimates for the parameters ( alpha , beta , gamma , sigma ) may be computed using the EM algorithm. Estimation is based on maximization of the expected full-data likelihood where the expectation is taken with respect to the conditional density of U given Y. A portion of the dissertation is devoted to the confirmation of asymptotic properties as the response variable, Y sub(i)'s, are not identically distributed. A set of conditions depending on the identically distributed error terms is given for consistency and asymptotic normality of MLE's. The model specific conditions are met by a number of error densities. (DBO)
Schlüsselwörter: biological-production; energy-transfer; trophic-levels; aquatic-environment; statistical-analysis; limiting-factors; ecosystems-; ecology-
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Lehmann, J. (1991). Der Körperbau der wichtigsten mitteleuropäischen Süßwasserfische. Albaum: Landesanstalt für Fischerei Nordrhein-Westfalen.
Schlüsselwörter: Fisch, Morphometrie, Gesamtwerk
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