Implications of recurrent disturbance for genetic diversity

Abstract

Exploring interactions between ecological disturbance, species' abundances and community composition provides critical insights for ecological dynamics. While disturbance is also potentially an important driver of landscape genetic patterns, the mechanisms by which these patterns may arise by selective and neutral processes are not well-understood. We used simulation to evaluate the relative importance of disturbance regime components, and their interaction with demographic and dispersal processes, on the distribution of genetic diversity across landscapes. We investigated genetic impacts of variation in key components of disturbance regimes and spatial patterns that are likely to respond to climate change and land management, including disturbance size, frequency, and severity. The influence of disturbance was mediated by dispersal distance and, to a limited extent, by birth rate. Nevertheless, all three disturbance regime components strongly influenced spatial and temporal patterns of genetic diversity within subpopulations, and were associated with changes in genetic structure. Furthermore, disturbance-induced changes in temporal population dynamics and the spatial distribution of populations across the landscape resulted in disrupted isolation by distance patterns among populations. Our results show that forecast changes in disturbance regimes have the potential to cause major changes to the distribution of genetic diversity within and among populations. We highlight likely scenarios under which future changes to disturbance size, severity, or frequency will have the strongest impacts on population genetic patterns. In addition, our results have implications for the inference of biological processes from genetic data, because the effects of dispersal on genetic patterns were strongly mediated by disturbance regimes.

Keywords: Allele surfing; disturbance regimes; range expansion; recolonization; simulation.

Figure 1

Flowchart for the genetics, demography and disturbance simulation model. Model details are fully described in the text and Appendix S2. Note that in the case of nonoverlapping generations, as used in this paper, the initial population comprises new born individuals only. These become adults during the “Age” process.

Figure 2

Comparison of (A) kernel density estimates of H _T, F _ST and H _S from all scenarios together with analysis of the relative variation in three response variables explained by demographic and disturbance factors. Response variables for ANOVA analysis (R Core Team 2014) are relative variance explained for (B) Av. HT_T, (C) temporal coefficient of variation of F _ST (over 1000 generations) and (D) Av F _ST. For clarity, only factors and factor interaction explaining more than 2% of the variance are shown.

Figure 3

Two‐way interactions of disturbance treatments and mean dispersal distance (A, B, and C) of variation in F_ST (averaged over the last 1000 generations). Chart (D) shows the interaction of birth rate and disturbance size. Charts (E) and (F) show the interactions of disturbance severity with disturbance interval and size. These charts show values averaged over all parameters and replicates, except where otherwise indicated.

Figure 4

The relationship between transformed pairwise F _ST and log transformed distance for (A) undisturbed and (B) highly disturbed landscapes. For clarity, the scatter data for each replicate simulation is summarized as a Lowess regression (R Core Team). Chart (C) shows pairwise untransformed F_ST by distance class (Diniz‐Filho et al. 2013). In chart (D), significant values (P < 0.05) of correlation between genetic and spatial distance matrices are shown with a “+”, nonsignificant values are shown with open circles. The intersection of the dotted lines indicates the approximate patch size. These pairwise comparisons use 50, randomly selected sites at the end of each of the 12 replicate simulations. Consequently, there will be a greater variance between the 12 replicates shown here, than between the meta‐population F _ST averaged over 1000 generations used for analysis in Fig. 2. All examples use a birth rate of 3 and a dispersal distance of 0.25 unless otherwise indicated. For highly disturbed landscapes, the parameters are DI = 30 years; DS = 24 cells; SV = 1.

Figure 5

Temporal effects on F _ST of disturbance size, severity and birth rate. Charts show values averaged over all parameters and replicates, except where otherwise indicated.

Figure 6

Spatial genetic patterns produced through a combination of range expansion and recolonization. On the left‐hand side of the figure are shown patterns of heterozygosity and the most frequent allele for (1) recolonization of an isolated empty area from a surrounding population and (2) range expansion from an isolated population into an empty landscape. In each case, the two processes in combination produce the patterns on the centre‐right during the simulation. The pattern is more apparent if disturbance is disabled for a period of time sufficient for the entire landscape to be fully occupied (far right).