Data and code to replicate: Diet analysis using generalized linear models derived from foraging processes using R package mvtweedie
Data files
Nov 08, 2021 version files 419.43 KB
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MDO.seabirdforagingarea.SST.csv
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Seabird.csv
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Wolf.csv
Abstract
Diet analysis integrates a wide variety of visual, chemical and biological identification of prey. Samples are often treated as compositional data, where each prey is analyzed as a continuous percentage of the total. However, analyzing compositional data results in analytical challenges, e.g., highly parameterized models or prior transformation of data. Here, we present a novel approximation involving a Tweedie generalized linear model (GLM). We first review how this approximation emerges from considering predator foraging as a thinned and marked point process (with marks representing prey species and individual prey size). This derivation can motivate future theoretical and applied developments. We then provide a practical tutorial for the Tweedie GLM using new package mvtweedie that extends capabilities of widely used packages in R (mgcv and ggplot2) by transforming output to calculate prey compositions. We demonstrate this approach and software using two examples. Tufted puffins (Fratercula cirrhata) provisioning their chicks on a colony in the northern Gulf of Alaska show decadal prey switching among sand lance and prowfish (1980-2000) and then Pacific herring and capelin (2000-2020), while wolves (Canis lupus ligoni) in Southeast Alaska forage on mountain goats and marmots in northern uplands and marine mammals in seaward island coastlines.
Usage notes
File list
Reproducible_script_R1.R
Wolf.csv
Seabird.csv
MDO.seabirdforagingarea.SST.csv
Description
Reproducible_script_R1.R – R script used to replicate all analysis and figures in main text and appendices. See comments at top for directions prior to running.
Wolf.csv - CSV file containing four columns used in the wolf metabarcoding case-study in Fig. 3 of the main text:
- “Latitude” -- Latitude of scat sample in Degree-decimals;
- “Longitude” -- Longitude of scat sample;
- “group” -- prey taxonomic group used in analysis;
- “Response” -- metabarcoding read count used as response variable.
Seabird.csv - CSV file containing three columns used in the seabird bill-load case-study in Fig. 2 of the main text:
- “Year” – Year AD for bill-load sample;
- “group” -- prey taxonomic group used in analysis;
- “Response” – bill-load count used as response variable.
MDO.seabirdforagingarea.SST.csv - CSV file containing two additional columns used in the seabird bill-load case-study in Fig. 2 of the main text:
- “Year” – Year AD, including all Years used in Fig. 2;
- “SST_mean” – average sea surface temperature near Middleton Island;