Some of this code has been under development since 1989, long before the widespread adoption of version control systems. An ad hoc directory numbering system was used to keep separate versions. The files here on github are an export of revision 3211 from the PFRP Subversion server, honmaguro.soest.hawaii.edu, at the University of Hawaii at Manoa.
Each directory has subdirectories for C++ source code (src), ADMB template files (tpl), documentation (docs), and various shell scripts, awk code and R code (scripts). Often these scripts are specific to the version in the parent directory.
Most directories and subdirectories have a Makefile, so it is usually only necessary to run make.
A provisional "work in progress" user manual is available at 25/docs/manuals/TagestUserMan.pdf.
The current "production" version, developed largely to analyze tagging data from the current SPC tagging project (PTTP). This code is a conversion of the code in directory 21 into an ADMB application using template classes to implement different code for constant (eg double) and variable (eg dvariable) objects. Eun Jung Kim's models of FAD attraction and stickiness are implemted here.
Multithread example using OpenMPI
Sibert's attempt to create satisfactory alternatives for handling errors in reporting effort, missing effort and errors in reporting recaptures. A dead end.
Revision of the directory 25 code without template classes and the
nerural network classes. Only the movemod simulator as been tested. It
implemented using variable types and the AUTODIF syntax
gradient_structure::set_NO_DERIVATIVES();
Code base with user written adjoint code, highly optimized to run on slower, memory deficient computers. At one time, it could be compiled under both both windows and linux. It is not compliant to current C++ standards. This code produced the results in Sibert and Hampton (2003).
Multihread example using pthreads and thread pool to implement threading of the adi algorithm and its adjoint.
Java native mode interface graphics to implement the tagmove visualizations. Developed and maintained by Johnoel Ancheta.
A worked example using data from the Skipjack Survey and Assessment Programme conducted by the South Pacific Commission between 1977 and 1987. The national identities in the tag return and fishing effort records have been obfuscated out of ``confidentiality'' concerns.
To build a functional run directory, type make at the command prompt.
This project began in about 1989. Over the years, a number of collaborators have contributed code and ideas.
Sibert, J.R., Hampton, J., Fournier, D., 1996. Skipjack movement and fisheries interaction in the Western Pacific. Second FAO Expert Consultation on Interactions of Pacific Tuna Fisheries, Shimizu, Japan.
Bills, Peter J. and John R. Sibert, 1997. Design of tag-recapture experiments for estimating yellowfin tuna stock dynamics, mortality, and fishery interactions. SOEST Publication 97-05, JIMAR Contribution 97-313, 80 pp.
Sibert, J.R., Hampton, J., Fournier, D.A., Bills, P.J., 1999. An advection-diffusion-reaction model for the estimation of fish movement parameters from tagging data, with application to skipjack tuna (Katsuwonus pelamis). Canadian Journal of Fisheries and Aquatic Sciences, 56: 925-938.
Adam, M.S., Sibert J., 2002. Population dynamics and movements of skipjack tuna (Katsuwonus pelamis) in the Maldivian fishery: analysis of tagging data from an advection-diffusion-reaction model. Aquat. Living Resour. 15: 13-23.
Sibert, J., Hampton, J., 2003. Mobility of tropical tunas and the implications for fisheries management. Marine Policy 27 (2003) 87-05.
Adam, M. Shiham and John R. Sibert, 2004. Use of neural networks with advection-diffusion-reaction models to estimate large-scale movements of skipjack tuna from tagging data. SOEST Publication 04-03, JIMAR Contribution 04-350,31 pp.