Models of harmful algal blooms
暂无分享,去创建一个
[1] P. Brasseur,et al. Data Assimilation: Tools for Modelling the Ocean in a Global Change Perspective , 1994 .
[2] D. Kamykowski. The simulation of a Southern California red tide using characteristics of a simultaneously-measured internal wave field , 1981 .
[3] D. Kamykowski. Possible interactions between phytoplankton and semidiurnal internal tides , 1974 .
[4] Joji Ishizaka,et al. Coupling of coastal zone color scanner data to a physical‐biological model of the southeastern U.S. continental shelf ecosystem: 2. An Eulerian model , 1990 .
[5] APPENDIX TO CHAPTER 12 – On a Class of Mathematical Models for Gymnodinium breve Red Tides , 1979 .
[6] W. Ebenhöh. Coexistence of an unlimited number of algal species in a model system , 1988 .
[7] M. Ghil,et al. Data assimilation in meteorology and oceanography , 1991 .
[8] J. Truscott. Environmental forcing of simple plankton models , 1995 .
[9] Percy L. Donaghay,et al. Toward a theory of biological‐physical control of harmful algal bloom dynamics and impacts , 1997 .
[10] A. White. Growth Inhibition Caused by Turbulence in the Toxic Marine Dinoflagellate Gonyaulax excavata , 1976 .
[11] Peter Franks,et al. Spatial patterns in dense algal blooms , 1997 .
[12] D. Anderson,et al. IDENTIFICATION OF GROUP‐ AND STRAIN‐SPECIFIC GENETIC MARKERS FOR GLOBALLY DISTRIBUTED ALEXANDRIUM (DINOPHYCEAE). II. SEQUENCE ANALYSIS OF A FRAGMENT OF THE LSU rRNA GENE 1 , 1994 .
[13] J. Verreth,et al. A Dynamic Simulation-Model for the Blooming of Oscillatoria- Agardhii in a Monomictic Lake , 1995 .
[14] Y. Ishida,et al. ANALYSIS OF ALEXANDRIUM (DINOPHYCEAE) SPECIES USING SEQUENCES OF THE 5.8S RIBOSOMAL DNA AND INTERNAL TRANSCRIBED SPACER REGIONS 1 , 1996 .
[15] D. Kamykowski. Laboratory experiments on the diurnal vertical migration of marine dinoflagellates through temperature gradients , 1981 .
[16] C. Scholin,et al. IDENTIFICATION OF CULTURED PSEUDO‐NITZSCHIA (BACILLARIOPHYCEAE) USING SPECIES‐SPECIFIC LSU rRNA‐TARGETED FLUORESCENT PROBES 1 , 1996 .
[17] Joji Ishizaka,et al. Coupling of coastal zone color scanner data to a physical‐biological model of the southeastern U.S. continental shelf ecosystem: 3. Nutrient and phytoplankton fluxes and CZCS data assimilation , 1990 .
[18] M. Kishi,et al. Population dynamics of ‘red tide’ organisms in eutrophicated coastal waters — Numerical experiment of phytoplankton bloom in the East Seto Inland Sea, Japan , 1986 .
[19] A. Moore,et al. Initialization and Data Assimilation in Models of the Indian Ocean , 1987 .
[20] Hans G. Othmer,et al. On the resonance structure in a forced excitable system , 1990 .
[21] M. R. Droop,et al. Vitamin B12 and Marine Ecology. IV. The Kinetics of Uptake, Growth and Inhibition in Monochrysis Lutheri , 1968, Journal of the Marine Biological Association of the United Kingdom.
[22] G. P. Cressman. AN OPERATIONAL OBJECTIVE ANALYSIS SYSTEM , 1959 .
[23] T. Wyatt,et al. Model which Generates Red Tides , 1973, Nature.
[24] J. M. Lewis,et al. The use of adjoint equations to solve a variational adjustment problem with advective constraints , 1985 .
[25] H. Redkey,et al. A new approach. , 1967, Rehabilitation record.
[26] M. Vernet,et al. EFFECTS OF SMALL‐SCALE TURBULENCE ON PHOTOSYNTHESIS, PIGMENTATION, CELL DIVISION, AND CELL SIZE IN THE MARINE DINOFLAGELLATE GOMAULAX POLYEDRA (DINOPHYCEAE) 1 , 1995 .
[27] G. E. Hutchinson,et al. The Balance of Nature and Human Impact: The paradox of the plankton , 2013 .
[28] J. Truscott,et al. Equilibria, stability and excitability in a general class of plankton population models , 1994, Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences.
[29] W. Thomas,et al. Effects of quantified small-scale turbulence on the dinoflagellate, Gymnodium sanguineum (splendens): contrasts with Gonyaulax (Lingulodinium) polyedra, and the fishery implication , 1992 .
[30] T. Yamamoto,et al. A numerical simulation of red tide formation , 1995 .
[31] L. Edler,et al. Dinoflagellate distribution in the Southeastern Kattegat during an autumn bloom , 1991 .
[32] Andrew F. Bennett,et al. Inverse Methods in Physical Oceanography: Bibliography , 1992 .
[33] Robert A. Armstrong,et al. Monitoring Ocean Productivity by Assimilating Satellite Chlorophyll into Ecosystem Models , 1995 .
[34] W. Mitsch,et al. Turbulence and phytoplankton diversity: A general model of the “paradox of plankton”☆ , 1979 .
[35] D. Anderson,et al. IDENTIFICATION OF GROUP‐ AND STRAIN‐SPECIFIC GENETIC MARKERS FOR GLOBALLY DISTRIBUTED ALEXANDRIUM (DINOPHYCEAE). I. RFLP ANALYSIS OF SSU rRNA GENES 1 , 1994 .
[36] E. Berdalet. EFFECTS OF TURBULENCE ON THE MARINE DINOFLAGELLATE GYMNODINIUM NELSONII 1 , 1992 .
[37] Eileen E. Hofmann,et al. A data assimilation technique applied to a predator-prey model , 1995 .
[38] M. Kishi,et al. Criterion for stability of phytoplankton patchiness using a Liapunov method , 1978 .
[39] W. Thomas,et al. Effects of turbulence intermittency on growth inhibition of a red tide dinoflagellate, Gonyaulax polyedra Stein , 1995 .
[40] S. Jørgensen,et al. Application of Ecological Modelling in Environmental Management , 1983 .
[41] Coexistence of any number of species in the Lotka-Volterra competitive system over two-patches , 1990 .
[42] W. Thomas,et al. Quantified small-scale turbulence inhibits a red tide dinoflagellate, Gonyaulax polyedra Stein , 1990 .
[43] Y. Sako,et al. RESTRICTION FRAGMENT LENGTH POLYMORPHISM OF RIBOSOMAL DNA INTERNAL TRANSCRIBED SPACER AND 5.8S REGIONS IN JAPANESE ALEXANDRIUM SPECIES (DINOPHYCEAE) 1 , 1994 .