DOI: 10.5061/dryad.2ngf1vhsh
title: Why we cannot always expect life history strategies to directly inform on sensitivity to environmental change

description: Speed of life and reproductive strategy form the two major axes that
 organize variation in life history strategies across plant and animal
 species. The position of a species along these axes can inform on their
 sensitivity to environmental change. This provides a tantalizing link
 between sets of traits and population responses to change, contained in a
 highly generalizable theoretical framework. The underlying mechanisms are
 assumed to be governed by life history tradeoffs at the individual level.
 Examples include the tradeoff between current and future reproductive
 success, and investing energy into growth versus reproduction. But the
 importance of such tradeoffs in structuring population-level responses to
 environmental change remains understudied. We aim to increase our
 understanding of the link between individual-level life history tradeoffs
 and the structuring of life history strategies across species, and if they
 link to population responses to environmental change. We find that the
 classical association between life history strategies and population
 responses to environmental change breaks down when accounting for
 individual-level tradeoffs and reproductive decisions. Projecting
 population responses to environmental change can therefore not always be
 inferred based on a limited set of species traits alone. We summarize our
 perspective and a way forward in a conceptual framework.
description: # Why we cannot always expect life history strategies to directly inform
 on sensitivity to environmental change --- The dataset provides the code
 to run DEB-IPM models used in the study in MATLAB and analyze PCA-results.
 ## Global description of the data and file structure The PCA zip.file
 contains a data table and R code to run the PCA analysis presented in the
 manuscript. The MATLAB zip.file contains all matlab files required to run
 the DEB-IPMS and perform perturbation analysis presented in the
 manuscript. **Detail PCA zip.file description** * PCA_table.xlsx contains
 the trait data and sensitivity values for all model species used as input
 for the PCA analysis. * PhyloPCA_Fish.R contains the code to run a PCA
 analysis using PCA_table.xlsx as input and correcting for phylogeny. *
 PhyloPCA_Fish_No_Phyl.R contains the code to run a PCA analysis using
 PCA_table.xlsx as input without correcting for phylogeny. *
 PhyloPCA_Fish_Body_size_correction.R contains the code to run a PCA
 analysis using PCA_table.xlsx as input and correcting for phylogeny and
 body size. * **Detail MATLAB zip.file description** * The subfolder
 Model_and_Parameter_files contains fifteen matlab files: * M1_parameters.m
 contains code describing the trait values for all iteroparous obligate
 breeders * M2_parameters.m contains code describing the trait values for
 all iteroparous skip breeders * M3_parameters.m contains code describing
 the trait values for all semelparous skip breeders *
 M1_iteroparous_obligate.m contains the code describing the life history
 functions for iteroparous obligate breeders * M2_iteroparous_skip.m
 contains the code describing the life history functions for iteroparous
 skip breeders * M3_semelparous_skip.m contains the code describing the
 life history functions for semelparous skip breeders *
 M1_stochseq_DEBIPM.m contains code describing the functions to estimate
 population growth rates for all iteroparous obligate breeders *
 M2_stochseq_DEBIPM.m contains code describing the functions to estimate
 population growth rates for all iteroparous skip breeders *
 M3_stochseq_DEBIPM.m contains code describing the functions to estimate
 population growth rates for all semelparous skip breeders *
 M1_stochseq_DEBIPMsens.m contains code describing the functions to
 estimate population sensitivity for all iteroparous obligate breeders *
 M2_stochseq_DEBIPMsens.m contains code describing the functions to
 estimate population sensitivity for all iteroparous skip breeders *
 M3_stochseq_DEBIPMsens.m contains code describing the functions to
 estimate population sensitivity for all semelparous skip breeders * *
 habit_matrix.m contains the code to initialize the habitat transition
 matrix * linspencer.m contains the code ensuring different colors per
 species in output figures * MeanVar.m contains the code to calculate the
 mean and variance of trait values in perturbation analysis * The subfolder
 Model_Run.m contains five matlab files to run model analysis using the
 files in the Model_and_Parameter_files folder as input * M1_stoch_run.m
 computes and generates figures of the population growth of all iteroparous
 obligate breeders over environmental autocorrelation. * M2_stoch_run.m
 computes and generates figures of the population growth of all iteroparous
 skip breeders over environmental autocorrelation. * M3_stoch_run.m
 computes and generates figures of the population growth of all semelparous
 skip breeders over environmental autocorrelation. * Perturb.m runs a
 perturbation analysis on trait importance for all species in all three
 DEB-IPM models. * MR_Functional_trait_response.m visualizes the outputs of
 Perturb.m ## Sharing/Access information This is a section for linking to
 other ways to access the data, and for linking to sources the data is
 derived from, if any. Links to other publicly accessible locations of the
 data: *NONE **Data collection** Functional trait data was derived from
 scientific literature and a full reference set is provided in table 1 of
 the manuscript. ## Code/Software This is an optional, freeform section for
 describing any code in your submission and the software used to run it.
 -MATLAB 2021A was used to run the DEB-IPMS -RStudio with R 4.2.1 was used
 to run R.