dietr : an R package for calculating fractional trophic levels from quantitative and qualitative diet data
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PRIMARY RESEARCH PAPER
dietr: an R package for calculating fractional trophic levels from quantitative and qualitative diet data Samuel R. Borstein
Received: 11 December 2019 / Revised: 14 August 2020 / Accepted: 18 September 2020 Ó Springer Nature Switzerland AG 2020
Abstract This article introduces an R package, dietr, which calculates fractional trophic levels from quantitative diet item and qualitative food item data following the routine implemented in TrophLab within the open source R environment. dietr is easy to use and can quickly calculate trophic levels for many diet records. In addition to calculating trophic levels following the TrophLab routines, users can also specify a taxonomic hierarchy and estimate trophic levels at multiple taxonomic levels in a single call of a function. Additionally, dietr works well with FishBase data obtained in R using rfishbase and comes with premade databases of prey trophic levels that users can utilize for estimating trophic levels. dietr can also calculate several prey electivity indices. I provide information on dietr’s performance and provide a use case example of how dietr can be used on an empirical dataset. Trophic levels for hundreds of specimens can be calculated in a few seconds and the flexibility of dietr’s input allows users to easily calculate trophic levels from their own data.
Handling editor: Gideon Gal S. R. Borstein (&) Department of Ecology and Evolutionary Biology, University of Michigan, Biological Sciences Building 2020, Ann Arbor, MI 48109, USA e-mail: [email protected]
Keywords Trophic ecology Stomach contents analysis Feeding Electivity R package FishBase
Introduction Trophic levels of taxa are key for understanding a wide array of ecological processes, especially those shaping biological diversity (Post, 2002a). Studies utilizing trophic level data have provided valuable insights across a number of biological topics including macroevolution (Rojas et al., 2018; Borstein et al., 2019), ontogenetic changes in life-history (Wilbur et al., 1974; Mittelbach et al., 1988), ecological assembly (Leibold et al., 2004; Duffy et al., 2007; Marczak et al., 2007), food-web structure (Pimm et al., 1991; Williams & Martinez, 2004), fisheries management (Pauly et al., 1998; Essington et al., 2006), invasive species (Vander Zanden et al., 1999; Grosholz, 2002), and trophic modelling of ecosystems (Christensen & Pauly, 1992; Christensen & Pauly, 1993; Christensen & Walters, 2004). The main methods used to estimate trophic level are stomach contents analysis (Odum & Heald, 1975) or stable isotopes analysis (Post, 2002b). While both methods have their pros and cons, a discussion of which falls outside the scope of this paper, stomach contents are still commonly utilized to estimate trophic levels, either by themselves or in conjunction with stable isotope
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Hydrobiologia
analyses as they can be highly complementary (Post, 2002b; Rybczynski et al., 2008; Polito et al., 2011; Mancinelli et al., 20
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