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Visualising the environmental preferences of Pinus tecunumanii populations
Authors:J T Brawner  G R Hodge  R Meder  W S Dvorak
Institution:1. Commonwealth Scientific and Industrial Research Organisation, Division of Plant Industry, Queensland Bioscience Precinct, 306 Carmody Road, St. Lucia, QLD, 4067, Australia
2. Forest Industry Research Centre, University of the Sunshine Coast, 90 Sippy Downs Drive, Sippy Downs, QLD, 4556, Australia
3. Department of Forestry and Environmental Resources, Camcore, North Carolina State University, 2720 Faucette Drive, 3229 Jordan Hall Addition, Raleigh, NC, 27695-8008, USA
Abstract:A network of 92 pedigreed ex situ conservation plantings of Pinus tecunumanii, established as replicated progeny within provenance trials, is used to present a principal components-based analysis that illustrates the climatic preferences of 23 populations from the species’ native range. This meta-analysis quantifies changes in the relative productivity, assessed as individual-tree volume, of populations across climatic gradients and associates the preference of a population with increased volume production along the climatic gradient. Clustering and ordination on the matrix containing estimates of change in productivity for each population summarise differentials in productivity associated with climatic gradients. The preference of populations along principal components therefore reflects the adaptive profiles of populations, which may be used with breeding-value estimates from routine genetic evaluations to assist with the development of deployment populations targeting different environments. As well, the approach may be used to test whether the preference of a population, estimated as population loadings for growth differentials, is affected by the climate in the native range of the population. This relationship may be interpreted as an estimate of how much local climate shapes the adaptive profiles of populations. The amount and seasonality of precipitation most clearly differentiate the adaptive profiles of populations, with less variation in the population responses explained by temperature differentiation. As expected from type-B correlation estimates, most populations exhibited small changes in relative productivity across climatic gradients. However, patterns of similarities in adaptive profiles among populations were evident using spatial orientation to display population responses to the climatic variables experienced in the provenance trials. Clustering and ordination of population responses derived from empirical data served to identify populations that responded positively or negatively to climatic variables; this information may help guide conservation genetics efforts, direct the deployment of germplasm, or identify seed sources that are sensitive to changes in climatic variables. Linking response patterns to the climatic data from the native range of each population indicated little effect of local climate shaping adaptive profiles.
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