Population Divergence along a Genetic Line of Least Resistance in the Tree Species Eucalyptus globulus

Abstract

The evolutionary response to selection depends on the distribution of genetic variation in traits under selection within populations, as defined by the additive genetic variance-covariance matrix (G). The structure and evolutionary stability of G will thus influence the course of phenotypic evolution. However, there are few studies assessing the stability of G and its relationship with population divergence within foundation tree species. We compared the G-matrices of Mainland and Island population groups of the forest tree Eucalyptus globulus, and determined the extent to which population divergence aligned with within-population genetic (co)variation. Four key wood property traits exhibiting signals of divergent selection were studied—wood density, extractive content, and lignin content and composition. The comparison of G-matrices of the mainland and island populations indicated that the G-eigenstructure was relatively well preserved at an intra-specific level. Population divergence tended to occur along a major direction of genetic variation in G. The observed conservatism of G, the moderate evolutionary timescale, and close relationship between genetic architecture and population trajectories suggest that genetic constraints may have influenced the evolution and diversification of the E. globulus populations for the traits studied. However, alternative scenarios, including selection aligning genetic architecture and population divergence, are discussed.

Leaf Economic and Hydraulic Traits Signal Disparate Climate Adaptation Patterns in Two Co-Occurring Woodland Eucalypts

“…Second, the two species may differ in their patterns of climate adaptation due to different patterns of correlated evolutionary changes among the focal traits during species divergence (i.e., evolutionary integration [ 21 , 22 , 67 ]). In addition, for a given species, genetic constraints associated with genetic architecture within populations may have influenced the course of phenotypic evolution and adaptive diversification of the conspecific populations [ 68 , 69 , 70 ]. It is also possible that, within a species, differences among populations in natural selection may have shaped the genetic (co)variance patterns within populations over evolutionary time, thus leading to an alignment between genetic architecture and population trajectories [ 71 , 72 , 73 ].…”

Climate Adaptation, Drought Susceptibility, and Genomic-Informed Predictions of Future Climate Refugia for the Australian Forest Tree Eucalyptus globulus

“…Quantitative genetic studies of these trials identified significant popula-tion differentiation in numerous traits, which was summarised by partitioning the gene pool into 13 geographic races [49]. While there are likely evolutionary constraints [52], population differences have been shown to: occur at multiple geographic scales, from hundreds of metres [53,54] to hundreds of kilometres [49,55], be adaptive (i.e., significant population × environment interactions for growth in common garden trials, [32]), and even to have extended community-level consequences [56,57]. Numerous traits exhibit clines with latitude and climate as well as signals of divergent selection (Q ST > F ST ) [47,49,58,59].…”

“…The current adaptive differences among the E. globulus provenances are a result of historical selection and constraints [52]. Our RDA analysis allowed the identification of the independent climate vectors most likely to have historically contributed to shaping the genomic adaptation in these provenances.…”

Directional Selection on Tree Seedling Traits Driven by Experimental Drought Differs Between Mesic and Dry Populations

“…Tree adaptation to major environmental gradients such as aridity is polygenic and genome-wide (Kramer et al, 2015;Jordan et al, 2017;Steane et al, 2017), involves diverse functional traits (Alberto et al, 2013;Kremer et al, 2014), and potentially also genetic constraints (Bourne et al, 2017;Costa e Silva et al, 2020). Detecting adaptive changes in local populations of longlived organisms, such as forest trees, is difficult due to numerous factors (Alberto et al, 2013), including long-life cycles (Petit and Hampe, 2006), ontogenetic (Brunner et al, 2016) and plastic (Nicotra et al, 2010;McLean et al, 2014) changes in phenotype, superimposed on the normal selective filtering of mal-adapted inbred progeny during stand development (Koelewijn et al, 1999;Costa e Silva et al, 2011;Griffin et al, 2019).…”