This repository (tag ELE.2021.a.b) contains all code and most data for reproducing the analyses associated with two publications:
Stouffer & Novak (2021) Hidden layers of density dependence in consumer feeding rates. Ecology Letters (bioRxiv)
Novak & Stouffer (2021) Systematic bias in studies of consumer functional responses. Ecology Letters (bioRxiv)
Of direct relevance to the latter paper is Novak & Stouffer (2022) Geometric complexity and the information-theoretic comparison of functional-response models. Frontiers in Ecology & Evolution (bioRxiv), the code for which is on this Geometric Complexity repository.
Code committed subsequent to ELE.2021.a.b is work in progress.
Please email Daniel Stouffer (daniel.stouffer@canterbury.ac.nz) or Mark Novak (mark.novak@oregonstate.edu) with any questions.
The repository is mostly not split-up by publication because most code pertaining to "Systematic bias..." is also used in "Hidden layers...". Rather, it is primarily split-up by dataset type, distinguishing (1) functional-response datasets entailing variation in the abundance of both a (single) consumer species and its (single) resource species ("One_Predator_One_Prey") from (2) functional-response datasets entailing variation in the abundance of two resources but no variation in the abundance of the consumer ("One_Predator_Two_Prey").
Primarily for the calculation of Fisher Information Matrices, derivations of qualitative bias in functional-response parameter MLEs, and derivations of generalized functional-response models.
Contains a library of scripts used in the model-fitting and subsequent analyses of both One_Predator_One_Prey and One_Predator_Two_Prey datasets. Within each of the two latter folders, fit_all_datasets.R does as implied; otherwise use RUNME.R scripts.
Contains all functional-response datasets (for which permission for public posting was granted) used in the analyses. See data/README.md and the supplementary data tables in the supplementary materials of the publications for sources and citations.
Contains results used to generate Fig. 1 of "Systematic bias...".
Contains all other results, figures and tables.
All code is provided "as is" and without warranty. If you know of more efficient or elegant ways of doing anything (of which there are likely many), we’d love to learn from you.