Plasticity of functional traits varies clinally along a rainfall gradient in Eucalyptus tricarpa

Abstract

Widespread species often occur across a range of climatic conditions, through a combination of local genetic adaptations and phenotypic plasticity. Species with greater phenotypic plasticity are likely to be better positioned to cope with rapid anthropogenic climate changes, while those displaying strong local adaptations might benefit from translocations to assist the movement of adaptive genes as the climate changes. Eucalyptus tricarpa occurs across a climatic gradient in south-eastern Australia, a region of increasing aridity, and we hypothesized that this species would display local adaptation to climate. We measured morphological and physiological traits reflecting climate responses in nine provenances from sites of 460 to 1040 mm annual rainfall, in their natural habitat and in common gardens near each end of the gradient. Local adaptation was evident in functional traits and differential growth rates in the common gardens. Some traits displayed complex combinations of plasticity and genetic divergence among provenances, including clinal variation in plasticity itself. Provenances from drier locations were more plastic in leaf thickness, whereas leaf size was more plastic in provenances from higher rainfall locations. Leaf density and stomatal physiology (as indicated by δ 13 C and δ 18 O) were highly and uniformly plastic. In addition to variation in mean trait values, genetic variation in trait plasticity may play a role in climate adaptation.

Climate adaptation and ecological restoration in eucalypts

“…In particular, provenances of E. tricarpa from dry (but not wet) environments grew thicker leaves (with lower specific leaf area) in a dry field trial and thinner leaves in a wetter one, a feature likely to be of benefit in dry environments with variable rainfall (Figure 4; McLean et al 2014). On the other hand, provenances from wet environments were better able to adjust their leaf size than those from dry environments (Figure 4), possibly reflecting a greater importance of being able to produce large leaves when shaded in denser forests.…”

“…leaf traits such as specific leaf area and leaf size - Li et al 2000;Warren et al 2006;Stylianou 2011;McLean et al 2014). This variation could depend on the magnitude of climatic variation between provenance trials and sites of origin of provenances in each study; in some cases, variation in phenotypic plasticity appears to be genetically-based and associated with climate of origin (see below).…”

“…Towards this, the E. tricarpa studies mentioned above McLean et al 2014) have related putatively adaptive alleles with functional traits (Figure 6), and a population level association study is being undertaken for putatively adaptive alleles in E. microcarpa (R. Jordan, S. Dillon, A. Hoffman, S. Prober unpub. data).…”

The role of ecotypic variation and the environment on biomass and nitrogen in a dominant prairie grass

“…A positive RTR indicates the response is in the direction expected and the magnitude indicates the range in the response. This index has been used to reveal relationships between plasticity in leaf traits from populations originating across a rainfall gradient and the MAP in a population's region of origin (McLean et al 2014). When applied to biomass produced in a reciprocal common garden, this index can indicate the degree to which sensitivity of plant growth responds according to expectations of the environment or local adaptation, and is related to an environmental variable in a population's region of origin.…”

A Climate-Oriented Approach to Support Decision-Making for Seed Provenance in Ecological Restoration

“…This approach explicitly considers the directional nature of climate change (in contrast to the composite and admixture provenances). Furthermore, it capitalizes on naturally occurring genetic adaptation to warmer and drier/wetter conditions that may be present in the species local and regional gene pools along the climatic gradient (e.g., McLean et al, 2014;Steane et al, 2014Steane et al, , 2017aProber et al, 2015). Moreover, it is less affected by SDM uncertainty than the climate-predictive provenance, being able to hedge against uncertainty in SDMs projections.…”