Data from: Advancing population ecology with integral projection models: a practical guide

Integral Projection Models (IPMs) use information on how an
individual's state influences its vital rates - survival, growth and
reproduction - to make population projections. IPMs are constructed from
regression models predicting vital rates from state variables (e.g., size
or age) and covariates (e.g., environment). By combining regressions of
vital rates, an IPM provides mechanistic insight into emergent ecological
patterns such as population dynamics, species geographic distributions, or
life history strategies. Here, we review important resources for building
IPMs and provide a comprehensive guide, with extensive R code, for their
construction. IPMs can be applied to any stage-structured population; here
we illustrate IPMs for a series of plant life histories of increasing
complexity and biological realism, highlighting the utility of various
regression methods for capturing biological patterns. We also present case
studies illustrating how IPMs can be used to predict species’ geographic
distributions and life history strategies. IPMs can represent a wide range
of life histories at any desired level of biological detail. Much of the
strength of IPMs lies in the strength of regression models. Many
subtleties arise when scaling from vital rate regressions to
population-level patterns, so we provide a set of diagnostics and
guidelines to ensure that models are biologically plausible. Moreover,
IPMs can exploit a large existing suite of analytical tools developed for
Matrix Projection Models.