Inferring responses to climate dynamics from historical demography in neotropical forest lizards

Abstract

We apply a comparative framework to test for concerted demographic changes in response to climate shifts in the neotropical lowland forests, learning from the past to inform projections of the future. Using reduced genomic (SNP) data from three lizard species codistributed in Amazonia and the Atlantic Forest (Anolis punctatus, Anolis ortonii, and Polychrus marmoratus), we first reconstruct former population history and test for assemblage-level responses to cycles of moisture transport recently implicated in changes of forest distribution during the Late Quaternary. We find support for population shifts within the time frame of inferred precipitation fluctuations (the last 250,000 y) but detect idiosyncratic responses across species and uniformity of within-species responses across forest regions. These results are incongruent with expectations of concerted population expansion in response to increased rainfall and fail to detect out-of-phase demographic syndromes (expansions vs. contractions) across forest regions. Using reduced genomic data to infer species-specific demographical parameters, we then model the plausible spatial distribution of genetic diversity in the Atlantic Forest into future climates (2080) under a medium carbon emission trajectory. The models forecast very distinct trajectories for the lizard species, reflecting unique estimated population densities and dispersal abilities. Ecological and demographic constraints seemingly lead to distinct and asynchronous responses to climatic regimes in the tropics, even among similarly distributed taxa. Incorporating such constraints is key to improve modeling of the distribution of biodiversity in the past and future.

Keywords: Amazon Forest; Atlantic Forest; climate change; phylogeography; population genomics.

Fig. 1.

Phylogenetic relationships between sampled individuals. Relationships for A. punctatus (A and D), A. ortonii (B and E), and P. marmoratus (C and F) were inferred through SVD quartets (42) based on unlinked SNP data. Asterisks denote bootstrap support >0.70. Bars to the right of trees represent population genetic structure, inferred through sNMF (37). Western Amazonian samples are indicated in blue, eastern Amazonian samples in orange, and Atlantic Forest samples in pink. In the case of western Amazonian A. punctatus, two distinct genetic populations (light and dark blue) were inferred with sNMF. Given the availability of samples, and to avoid combining different genetic populations in a single spatial group, we did not include the western Amazonia samples indicated by dark blue in our demographic analyses.

Fig. S1.

Plots of the PC analyses and of the posterior distributions of model parameters in single-population analyses (Atlantic Forest I).

Fig. S2.

Plots of the PC analyses and of the posterior distributions of model parameters in single-population analyses (Atlantic Forest II).

Fig. S3.

Plots of the PC analyses and of the posterior distributions of model parameters in single-population analyses (eastern Amazonia).

Fig. S4.

Plots of the PC analyses and of the posterior distributions of model parameters in single-population analyses (western Amazonia).

Fig. S5.

Plots of the PC analyses and of the posterior distributions of model parameters in multi-population analyses based on the aSFS.

Fig. 2.

Predicted habitat suitability and genetic changes resulting from future climate change. (A–D) Species distribution models for the present time and 2080 for A. punctatus (A and B, respectively) and for A. ortonii (C and D, respectively). (E–H) Results from demographic and genetic modeling for the present time and 2080 for A. punctatus (E and F, respectively) and A. ortonii (G and H, respectively). (I and J) Projected plausible changes in genetic diversity by 2080 for A. punctatus (I) and A. ortonii (J). White dots in maps indicate the localities with empirical genetic data that were used for ABC parameter estimation. (K) Overview of demographic modeling extent (area enclosed by red line), SDM modeling extent along with vetted localities (blue, A. punctatus; black, A. ortonii), and historic distribution of the Atlantic Forest (depicted in dark gray).

Fig. S6.

Distributions of the posterior probabilities of each estimated demographic parameter. Maximum landscape carrying capacity (maxK) and long-term migration rate (m) for A. punctatus (A and B, respectively) and A. ortonii (C and D, respectively). The posterior mode (vertical black line), posterior (solid black line), and prior (solid gray line) distributions and postsampling regression adjustment (dashed gray line) are shown. The postsampling regression adjustment is shown to highlight how the general linear model procedure improved the parameter estimates (i.e., comparing the postsampling regression adjustment and posterior distribution) and to demonstrate that the summary statistics contained information relevant to estimating the parameters (i.e., contrasting the prior distribution and postsampling regression adjustment). All values are provided in log₁₀. Note that all parameters are estimated at the spatial resolution of simulations.