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Natural ecosystems are under pressure from increasing abiotic and biotic stressors, including climate change and novel pathogens, which are putting species at risk of local extinction, and altering community structure, composition, and function. Here, we aim to assess adaptive variation in growth and fungal disease resistance within a foundation tree, Corymbia calophylla to determine local adaptation, trait heritability, and genetic constraints in adapting to future environments. Two experimental planting sites were established in regions of contrasting rainfall with seed families from 18 populations capturing a wide range of climate origins (~4000 individuals at each site). Every individual was measured in 2015 and 2016 for growth (height, basal diameter) and disease resistance to a recently introduced leaf blight pathogen (Quambalaria pitereka). Narrow-sense heritability was estimated along with trait covariation. Trait variation was regressed against climate-of-origin and multivariate models were used to develop predictive maps of growth and disease resistance. Growth and blight resistance traits differed significantly among populations, and these differences were consistent between experimental sites and sampling years. Growth and blight resistance were heritable, and comparisons between trait differentiation (QST) and genetic differentiation (FST) revealed that population differences in height and blight resistance traits are due to divergent natural selection. Traits were significantly correlated with climate-of-origin, with cool and wet populations showing the highest levels of growth and blight resistance. These results provide evidence that plants have adaptive growth strategies and pathogen defense strategies. Indeed, the presence of standing genetic variation and trait heritability of growth and blight resistance provide capacity to respond to novel, external pressures. The integration of genetic variation into adaptive management strategies, such as assisted gene migration and seed sourcing, may be used to provide greater resilience for natural ecosystems to both biotic and abiotic stressors.
Ahrens et al. 2019 Evol App raw dataRaw data for the plantation from years 2015 and 2016. Height (HT), Diameter (D), and Blight (BT) with the year of collection after the trait abbreviation. Here blight is the blight damage score, so to calculate blight resistance subtract 5 from the score (i.e. blight resistence = BL16 - 5). Unique identifier, row, column, and block (Rep) are provided. For Trial, CAL02 is Margaret River and CAL03 is Mount Barker.Ahrens_etal_2019_evolapp_marri_heritability.xlsx
standing genetic variation, trait evolution, Quambalaria shoot blight, <i>Eucalyptus </i>sensu lato, Holocene, Eucalyptus sensu lato, Corymbia calophylla, adaptive capacity
standing genetic variation, trait evolution, Quambalaria shoot blight, <i>Eucalyptus </i>sensu lato, Holocene, Eucalyptus sensu lato, Corymbia calophylla, adaptive capacity
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