Estimating Asymptotic Weight for Lake Trout

Application of the Lester Model to lake trout in Alaska lakes may be substantially improved by direct estimation of asymptotic weight $W_\infty$ when possible. In the computational framework presented by Lester, et al.,$W_\infty$ is estimated by means of a sequence of relationships: first, the relationship observed between lake area and asymptotic length observed in Canada; then, the aggregate relationship between length and weight observed in Canada.

We have data at a finer resolution: for 44 lakes, we have sampling data on 40,000+ individual lake trout (5,695 weights; 36,041 lengths; 1,494 ages), which can be used to gain inference on pairwise relationships between variables (5,695 paired length x weight observations from 29 lakes; 1,494 paired length x age observations from 19 lakes). Not only can the relationships between length and weight and between lake area and asymptotic length be estimated for Alaska, they can be estimated specifically for each of the 44 lakes and applied to additional lakes as appropriate, and parameters reported by Lester, et. al. may be incorporated as priors.

Implementation of an integrated model as outlined below allows simultaneous use of all available information, as well as appropriate propagation of all uncertainty in estimation.

Repository contents

/flat_data/

• lake_morphometry_25_12_23.csv gives lake-level data (area, latitude, etc)

• length_weight_25_12_23.csv gives fish-level data (length, weight, etc)

• all other .csv files are no longer current but are retained for checks.

/R/

The R scripts are intended to be run more or less in sequence as appropriate.

• 0_data_update_checks.R runs a sequence of checks that can be run whenever the lake-level or fish-level datasets are updated, hopefully alerting the user to any weirdness.

• 1_laketrout_data_import.R performs all data import AND the current data filters to create the dataset that is assumed to be clean and will be used going forward. Outputs of this script will be loaded by latter scripts in the sequence.

• 2_integrated_model_run.R is specific to running the integrated Bayesian model. It bundles the input data, defines the model itself, runs the model, saves the output, and that's it.

• 2a_LWmodel_exploration.R performs a sequence of checks to explore several candidate versions of the weight~length component of the model. It got a little out of control.

• 3_plotting_model_run.R loads the output created by script 2 and plots the output every way I could think of. It got even more out of control.

• /R/further_model_exploration/ is some stuff that further supplements script 2a, and will hopefully be cleaned out a bit.

/Rdata/

This is where .Rdata files to be loaded later will live

Report_draft.Rmd

This is the current working draft of the overall report! The output Word file will need lots of formatting and the contents will most likely be pasted into a ADFG report template.

flowchart1.pptx and flowchart1.jpg

The model in conceptual flowchart form. This should probably not live in the root directory

Appendix_LakePlots.Rmd

This creates many summary plots for all lakes of interest, and is kept contained to its own file, perhaps as a warning to others.

Winf_estimates.csv

This spreadsheet summarizes model inferences and data inputs for all lakes.

Reference

Lester, et al. citation