User’s Guide to For2R: A Module of Fortran 95 Output Routines Compatible with the R Statistics Language

For2R is a collection of Fortran routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 For2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the For2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer For2R to others in the hope that they will find it useful. (PDF contains 31 pages)

PICES-GLOBEC International Program on Climate Change and Carrying Capacity

EXECUTIVE SUMMARY WORKSHOP OVERVIEW Introduction Goals and objectives of the workshop Organizing committee, participants, sponsors and venue Workshop activity NEMURO.FISH COUPLED WITH A POPULATION DYNAMICS MODEL (SAURY) Introduction One cohort case with no reproduction Two (overlapping) cohort scenario with no reproduction Two-cohort case with no reproduction and body size-dependent mortality Two-cohort case with reproduction and KL-dependent mortality Conclusions and future perspectives LAGRANGIAN MODEL OF NEMURO.FISH Tasks and members Description of model and preliminary results Future tasks COUPLING NEMURO TO HERRING BIOENERGETICS Overview Details of the NEMURO_Herring model Example simulation of NEMURO_Herring Future plans REFERENCES APPENDICES Workshop participants Workshop schedule Lagrangian model (FORTRAN program) (55 page document)

PICES-GLOBEC International Program on Climate Change and Carrying Capacity: Report of 2001 BASS/MODEL, MONITOR and REX Workshops, and the 2002 MODEL/REX Workshop

Table of Contents [pdf, 0.22 Mb] Executive Summary [pdf, 0.31 Mb] Report of the 2001 BASS/MODEL Workshop [pdf, 0.65 Mb] To review ecosystem models for the subarctic gyres Report of the 2001 MONITOR Workshop [pdf, 0.7 Mb] To review ecosystem models for the subarctic gyres Workshop presentations: Sonia D. Batten PICES Continuous Plankton Recorder pilot project Phillip R. Mundy GEM (Exxon Valdez Oil Spill Trustee Council`s "Gulf Ecosystem Monitoring" initiative) and U.S. GOOS plans in the North Pacific Ron McLaren and Brian O`Donnell A proposal for a North Pacific Action group of the international Data Buoy Cooperation Panel Gilberto Gaxiola-Castrol and Sila Najera-Martinez The Mexican oceanographic North Pacific program: IMECOCAL Sydney Levitus Building global ocean profile and plankton databases for scientific research Report of the 2001 REX Workshop [pdf, 1.73 Mb] On temporal variations in size-at-age for fish species in coastal areas around the Pacific Rim Workshop presentations: Brian J. Pyper, Randall M. Peterman, Michael F. Lapointe and Carl J. Walters [pdf, 0.33 Mb] Spatial patterns of covariation in size-at-age of British Columbia and Alaska sockeye salmon stocks and effects of abundance and ocean temperature R. Bruce MacFarlane, Steven Ralston, Chantell Royer and Elizabeth C. Norton [pdf, 0.4 Mb] Influences of the 1997-1998 El Niño and 1999 La Niña on juvenile Chinook salmon in the Gulf of the Farallones Olga S. Temnykh and Sergey L. Marchenko [pdf, 0.5 Mb] Variability of the pink salmon sizes in relation with abundance of Okhotsk Sea stocks Ludmila A. Chernoivanova, Alexander N. Vdoven and D.V. Antonenko [pdf, 0.3 Mb] The characteristic growth rate of herring in Peter the Great Bay (Japan/East Sea) Nikolay I. Naumenko [pdf, 0.5 Mb] Temporal variations in size-at-age of the western Bering Sea herring Evelyn D. Brown [pdf, 0.45 Mb] Effects of climate on Pacific herring, Clupea pallasii, in the northern Gulf of Alaska and Prince William Sound, Alaska Jake Schweigert, Fritz Funk, Ken Oda and Tom Moore [pdf, 0.6 Mb] Herring size-at-age variation in the North Pacific Ron W. Tanasichuk [pdf, 0.3 Mb] Implications of variation in euphausiid productivity for the growth, production and resilience of Pacific herring (Clupea pallasi) from the southwest coast of Vancouver Island Chikako Watanabe, Ahihiko Yatsu and Yoshiro Watanabe [pdf, 0.3 Mb] Changes in growth with fluctuation of chub mackerel abundance in the Pacific waters off central Japan from 1970 to 1997 Yoshiro Watanabe, Yoshiaki Hiyama, Chikako Watanabe and Shiro Takayana [pdf, 0.35 Mb] Inter-decadal fluctuations in length-at-age of Hokkaido-Sakhalin herring and Japanese sardine in the Sea of Japan Pavel A. Balykin and Alexander V. Buslov [pdf, 0.4 Mb] Long-term variability in length of walley pollock in the western Bering Sea and east Kamchtka Alexander A. Bonk [pdf, 0.4 Mb] Effect of population abundance increase on herring distribution in the western Bering Sea Sergey N. Tarasyuk [pdf, 0.4 Mb] Survival of yellowfin sole (Limanda aspera Pallas) in the northern part of the Tatar Strait (Sea of Japan) during the second half of the 20th century Report of the 2002 MODEL/REX Workshop [pdf, 1.2 Mb] To develop a marine ecosystem model of the North Pacific Ocean including pelagic fishes Summary and Overview [pdf, 0.4 Mb] Workshop presentations: Bernard A. Megrey, Kenny Rose, Francisco E. Werner, Robert A. Klumb and Douglas E. Hay [pdf, 0.47 Mb] A generalized fish bioenergetics/biomass model with an application to Pacific herring Robert A. Klumb [pdf, 0.34 Mb] Review of Clupeid biology with emphasis on energetics Douglas E. Hay [pdf, 0.47 Mb] Reflections of factors affecting size-at-age and strong year classes of herring in the North Pacific Shin-ichi Ito, Yutaka Kurita, Yoshioki Oozeki, Satoshi Suyama, Hiroya Sugisaki and Yongjin Tian [pdf, 0.34 Mb] Review for Pacific saury (Cololabis saira) study under the VENFISH project lexander V. Leonov and Gennady A. Kantakov [pdf, 0.34 Mb] Formalization of interactions between chemical and biological compartments in the mathematical model describing the transformation of nitrogen, phosphorus, silicon and carbon compounds Herring group report and model results [pdf, 0.34 Mb] Saury group report and model results [pdf, 0.46 Mb] Model experiments and hypotheses Recommendations [pdf, 0.4 Mb] Achievements and future steps Acknowledgements [pdf, 0.29 Mb] References [pdf, 0.32 Mb] Appendix 1. List of Participants [pdf, 0.32 Mb] Appendices 2-5. FORTRAN codes [pdf, 0.4 Mb] (Document pdf contains 182 pages)

User’s Guide to ADMB2R: A Set of AD Model Builder Output Routines Compatible with the R Statistics Language

ADMB2R is a collection of AD Model Builder routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 ADMB2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the ADMB2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer ADMB2R to others in the hope that they will find it useful. (PDF contains 30 pages)

User’s Guide to C2R: A Set of C Language Output Routines Compatible with the R Statistics Language

C2R is a collection of C routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 C2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the C2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer C2R to others in the hope that they will find it useful. (PDF contains 27 pages)