ShinyTropFish
- This app allows you to conduct a length-based stock assessment of your own data without requiring any R knowledge -
Disclaimer: The results of your analysis will be hosted up to 1 week on the server before being deleted. We do not take any responsibility over your data or results. It is possible to download the application and run if offline. Please see the "About" tab for further information.
Explore your data
Overall LFQ plots:
Number of length measurements per month:
Estimate growth parameters
Growth
Fitted parameters:
LFQ plot:
GA fitness plot:
Cohort plot:
Recruitment
Estimates:
Plot:
Estimate mortality rates
Fitted parameters:
LCCC plot:
Selectivity plot:
GOTCHA parameters:
GOTCH catch curve:
Estimate reference levels
YPR
Fitted parameters:
Yield per recruit plot:
Yield per recruit plot (F vs Lc):
Biomass per recruit plot (F vs Lc):
LB-SPR
Fitted parameters:
All results
All parameters
Growth
LFQ plot:
GA fitness plot:
Cohort plot:
Recruitment
Mortality rates
Gotcha parameters:
Reference levels
YPR
Yield per recruit
Biomass per recruit
LB-SPR
Scientific articles:
Mildenberger TK, Taylor MH, Kokkalis A, Pauly D. 2019, Fish stock assessment with length-frquency data: A novel app and best practices. Fisheries Research. doi:...
COMING
Mildenberger TK, Taylor MH, Wolff M. 2017, TropFishR: an R package for fisheries analysis with length‐frequency data. Methods Ecol Evol, 8: 1520-1527.
doi:10.1111/2041-210X.12791
Taylor MH, Mildenberger TK. 2017, Extending electronic length frequency analysis in R. Fish Manag Ecol. 2017;24:330–338.
https://doi.org/10.1111/fme.12232
Tutorials:
Mildenberger, TK. 2018. Length-frequency data for TropFishR.
Link
Taylor, MH. 2018. Using the TropFishR ELEFAN functions.
Link
Mildenberger, TK. 2017. Single-species fish stock assessment with TropFishR.
Link
ShinyTropFish
Shiny app for Tropical Fisheries Analysis in R. The click-based user interface for the R package TropFishR. TropFishR is a collection of fisheries models based on the FAO Manual "Introduction to tropical fish stock assessment" by Sparre and Venema (1998, 1999). Not only scientists working in the tropics will benefit from this new toolbox. The methods work with age-based or length-frequency data and assist in the assessment of data poor fish stocks. Overall, the package comes with 30 functions, 19 data sets and 10 s3 methods. All objects are documented and provide examples that allow reproducing the examples from the FAO manual.
Version
Version number: v0.1 (Beta)
News
This is the beta version of ShinyTropFish. You can find detailed descriptions of new features, bug fixes, other changes of specific package versions concerning
ShinyTropFish
and concerning
TropFishR
Installation for offline use
This application can be used offline. Please download the package from
GitHub
with devtools::install_github("tokami/ShinyTropFish") and run the R commands: require(ShinyTropFish) and runApp("apps/").
Citation
Please cite this application as:
Mildenberger TK, Taylor MH, Kokkalis A, Pauly D. 2019, Fish stock assessment with length-frquency data: A novel app and best practices. Fisheries Research. doi:...
COMING
Questions/Issues
In case you have questions or find bugs, please write an email to
Tobias Mildenberger
or post on
ShinyTropFish/issues
. If you want to be updated with the development of the application and underlying R package (TroFishR) or want to discuss with ShinyTropFish and TropFishR users and developers, follow the project on
ResearchGate
.
Developer team
Creator, Author, Maintainer
DTU AQUA
National Institute of Aquatic Resources
Technical University of Denmark
Kemitorvet
2800 Kgs. Lyngby
Denmark
Author
Thuenen Institute of Sea Fisheries
Herwigstrasse 31
27572 Bremerhaven
Germany
Author
DTU AQUA
National Institute of Aquatic Resources
Technical University of Denmark
Kemitorvet
2800 Kgs. Lyngby
Denmark
Author
Institute for the Oceans and Fisheries
The University of British Columbia
2202 Main Mall
Vancouver, British Columbia
Canada