Data and code for: Nonlinear life table response analysis: Decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers

Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. In this study, we compare the relative efficacy of linear and second-order LTRE analyses in capturing changes in population growth rate caused by environmental driver changes. To explore this question, we analyze demographic data collected for three long-lived plant species: Ardisia escallonioides (Pascarella & Horvitz, 1998), Silene acaulis, and Bistorta vivipara (Doak & Morris, 2010). This repository includes data files containing vital rate (survival, growth, reproduction) observations or models for our three case studies, as well as an R script in which we use these ..., , , # Data and code for: Nonlinear life table response experiment analysis: decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers
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Access this dataset and code on Dryad: https://doi.org/10.5061/dryad.p8cz8w9wg

## Overview

The goal of the manuscript (O'Connell et al., 2024) supported by the data and code described here was to compare linear and second-order life table response experiment (LTRE) analyses in order to determine whether a second-order (i.e., nonlinear) LTRE better captures observed changes in population growth rate relative to the more commonly used linear approach. To investigate this question, we analyzed demographic data for three long-lived plant species: Ardisia escallonioides, Silene acaulis, and Bistorta vivipara. This repository contains data and vital rate models files for each of these three species as well as an R script where we calculate the linear and second-order LTRE values and generate the figures we present...