Shifts in the dietary diversity of river otters (Lontra canadensis) along habitat gradients in coastal rivers of southern Oregon

Read full text
Authors: Luke Stuntz, Rachael A. Orben
Cited by: 0

Abstract

This repository contains all raw data and scripts used in the manuscript "Shifts in the dietary diversity of river otters (Lontra canadensis) along habitat gradients in coastal rivers of southern Oregon", published in Journal of Mammalogy. Brief descriptions of each file are as follows: Raw Data scat_contents.csv: Presence/absence data for different prey taxa in all river otter scat samples, along with various covariates (year, site, distance to ocean, distance to estuary, flow volume, surface velocity, salinity). n = 675. measured_diagnostics.csv: Length in mm of randomly selected diagnostic features for three different prey taxa. n = 60. diagnostic_regression.csv: Regression coefficients for diagnostic feature to fork length calculation for three different prey taxa. See text for full details and references. R Scripts diversity_distance.R: Used to model Shannon diversity of prey items in river otter scat as a function of proximity to the ocean. mv_probit.r: Used to explicity model multidimensional scat contents data as a function of various habitat covariates using a multivariate probit model. nmds_bootstrapping: Used to perform non-metric multidimensional scaling and visualization of river otter diets across sites and habitat zones with a bootstrapping procedure. permanova.R: Used to perform PERMANOVA and PERMDISP2 analysis of beta diversity in river otter diets across river systems. preysize.R: Used to back calculate river otter prey size for three different prey taxa based on size of diagnostic features. summary_plots.R: Used to create various plots and visualizations included in the manuscript.

Fields of Study & Subjects

Wildlife Ecology and Conservation Marine animal studies overview Animal Ecology and Behavior Studies

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
17 February 2026
Language
EN
Document type
Dataset