Perspectives from animal demography on incorporating evolutionary mechanism into plant population dynamics

Abstract

8With a growing number of long-term, individual-based data on natural populations available, it 9 has become increasingly evident that environmental change affects populations through 10 complex, simultaneously occurring demographic and evolutionary processes. Analyses of 11 population-level responses to environmental change must therefore integrate demography and 12 evolution into one coherent framework. Integral projection models (IPMs), which can relate 13 genetic and phenotypic traits to demographic and population-level processes, offer a powerful 14 approach for such integration. However, a rather artificial divide exists in how plant and animal 15 population ecologists use IPMs. Here, I argue for the integration of the two sub-disciplines, 16 particularly focusing on how plant ecologists can diversify their toolset to investigate selection 17 pressures and eco-evolutionary dynamics in plant population models. I provide an overview of 18 approaches that have applied IPMs for eco-evolutionary studies and discuss a potential future 19 research agenda for plant population ecologists. Given an impending extinction crisis, a holistic 20 look at the interacting processes mediating population persistence under environmental change is 21 urgently needed.22 3 2014a). The relationship between vital rates and the continuous trait variable is typically 46 expressed with (generalized) linear models. For example, one can define individual size as the 47 trait and model size at time t +1 (z') as a function of size at time t (z) using a simple regression: 48 49 eqn. 1 50 The key flexibility of IPMs lies in the fact that demographic rates can also differ in time and 51 among different ages, stages, or environmental states (Ellner & Rees, 2006; Rees & Ellner, 52 2009); be made a function of intrinsic population processes such as density feedbacks (Metcalf et 53 al., 2008) or interactions with other species (Adler et al., 2010, 2012); and include static 54 phenotypic and genetic traits such as the genotype of an individual or mass at birth, which do not 55 change through time (see chapter 9 in Ellner et al., 2016; Vindenes & Langangen, 2015). 56 The demographic rates are then incorporated into a projection kernel , 57 describing, to follow the example above, the probability of z-sized individuals to transition to 58 size z' within one discrete time step. A full K consists of two subkernels: 59 eqn. 2 60 where describes the probability of a z-sized individual to survive and, conditional on 61 survival, grow to z', and describes the probability of a z-sized individual to produce 62offspring with a z' size distribution ( Fig. 1; Table 1). As the subkernels P and F describe a 63 continuous density distribution of z, integration is required to obtain z' at t+1. To achieve this 64 integration, a midpoint rule is typically applied, which discretizes the kernels into bins over a 65 range of z values bounded by the lowest (L) and highest (U) observed values. The kernel K is 66 4 then multiplied by n, the number of individuals in the si...