QFASA Robustness to Assumption Violations: Computer Code
December 12, 2022
Quantitative fatty acid signature analysis (QFASA; Iverson et al. 2004) has become a common method of estimating diet composition, especially for marine mammals, but the performance of the method has received limited investigation. Bromaghin et al. (In press) used computer simulation to compare the bias of several QFASA estimators and developed recommendations regarding estimator selection. Simulations were performed using a combination of R and Fortran code. An R script was used to prepare data inputs, call EstDiet.dll to estimate diet composition given data inputs, and organize estimation results. The R script file and all Fortran functions and subroutines associated with the dll file are included in the zip file available below. The R script was developed using R 3.1.2 (http://cran.r-project.org/) and the dll file was compiled using the Intel Parallel Studio XE 2013 Fortran Compiler, professional edition (https://software.intel.com/en-us/intel-parallel-studio-xe). Bromaghin et al. (2015) used the same dll file to estimate diet composition.
Citation Information
Publication Year | 2022 |
---|---|
Title | QFASA Robustness to Assumption Violations: Computer Code |
DOI | 10.5066/F7N877TK |
Authors | Jeffrey F Bromaghin |
Product Type | Software Release |
Record Source | USGS Asset Identifier Service (AIS) |
USGS Organization | Alaska Science Center |
Related
Assessing the Robustness of Quantitative Fatty Acid Signature Analysis to Assumption Violations (Supplementary Data)
This dataset contains fatty acid (FA) data expressed as mass percent of total FA for bearded seals, ringed seals and walrus. This is one of many datasets used in Bromaghin et al. 2016 (https://doi.org/10.1111/2041-210X.12456). These supplemental data were used in computer simulations to compare the bias of several quantitative fatty acid signature analysis (QFASA) estimators and develop...
Assessing the robustness of quantitative fatty acid signature analysis to assumption violations
Knowledge of animal diets can provide important insights into life history and ecology, relationships among species in a community and potential response to ecosystem change or perturbation. Quantitative fatty acid signature analysis (QFASA) is a method of estimating diets from data on the composition, or signature, of fatty acids stored in adipose tissue. Given data on signatures of...
Authors
Jeffrey F. Bromaghin, Suzanne M. Budge, Gregory W. Thiemann, Karyn D. Rode
Distance measures and optimization spaces in quantitative fatty acid signature analysis
Quantitative fatty acid signature analysis has become an important method of diet estimation in ecology, especially marine ecology. Controlled feeding trials to validate the method and estimate the calibration coefficients necessary to account for differential metabolism of individual fatty acids have been conducted with several species from diverse taxa. However, research into potential...
Authors
Jeffrey F. Bromaghin, Karyn D. Rode, Suzanne M. Budge, Gregory W. Thiemann
Related
Assessing the Robustness of Quantitative Fatty Acid Signature Analysis to Assumption Violations (Supplementary Data)
This dataset contains fatty acid (FA) data expressed as mass percent of total FA for bearded seals, ringed seals and walrus. This is one of many datasets used in Bromaghin et al. 2016 (https://doi.org/10.1111/2041-210X.12456). These supplemental data were used in computer simulations to compare the bias of several quantitative fatty acid signature analysis (QFASA) estimators and develop...
Assessing the robustness of quantitative fatty acid signature analysis to assumption violations
Knowledge of animal diets can provide important insights into life history and ecology, relationships among species in a community and potential response to ecosystem change or perturbation. Quantitative fatty acid signature analysis (QFASA) is a method of estimating diets from data on the composition, or signature, of fatty acids stored in adipose tissue. Given data on signatures of...
Authors
Jeffrey F. Bromaghin, Suzanne M. Budge, Gregory W. Thiemann, Karyn D. Rode
Distance measures and optimization spaces in quantitative fatty acid signature analysis
Quantitative fatty acid signature analysis has become an important method of diet estimation in ecology, especially marine ecology. Controlled feeding trials to validate the method and estimate the calibration coefficients necessary to account for differential metabolism of individual fatty acids have been conducted with several species from diverse taxa. However, research into potential...
Authors
Jeffrey F. Bromaghin, Karyn D. Rode, Suzanne M. Budge, Gregory W. Thiemann