Dataset Information

Photosynthetic variation and responsiveness to CO2 in a widespread riparian tree.

ABSTRACT: Phenotypic responses to rising CO2 will have consequences for the productivity and management of the world's forests. This has been demonstrated through extensive free air and controlled environment CO2 enrichment studies. However intraspecific variation in plasticity remains poorly characterised in trees, with the capacity to produce unexpected trends in response to CO2 across a species distribution. Here we examined variation in photosynthesis traits across 43 provenances of a widespread, genetically diverse eucalypt, E. camaldulensis, under ambient and elevated CO2 conditions. Genetic variation suggestive of local adaptation was identified for some traits under ambient conditions. Evidence of genotype by CO2 interaction in responsiveness was limited, however support was identified for quantum yield (?). In this case local adaptation was invoked to explain trends in provenance variation in response. The results suggest potential for genetic variation to influence a limited set of photosynthetic responses to rising CO2 in seedlings of E. camaldulensis, however further assessment in mature stage plants in linkage with growth and fitness traits is needed to understand whether trends in ? could have broader implications for productivity of red gum forests.

SUBMITTER: Dillon S

PROVIDER: S-EPMC5749701 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Photosynthetic variation and responsiveness to CO2 in a widespread riparian tree.

Dillon Shannon S Quentin Audrey A Ivković Milos M Furbank Robert T RT Pinkard Elizabeth E

PloS one 20180102 1

Phenotypic responses to rising CO2 will have consequences for the productivity and management of the world's forests. This has been demonstrated through extensive free air and controlled environment CO2 enrichment studies. However intraspecific variation in plasticity remains poorly characterised in trees, with the capacity to produce unexpected trends in response to CO2 across a species distribution. Here we examined variation in photosynthesis traits across 43 provenances of a widespread, gene ...[more]

PMID: 29293528

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Project description:Identifying and predicting how species ranges will shift in response to climate change is paramount for conservation and restoration. Ecological niche models are the most common method used to estimate potential distributions of species; however, they traditionally omit knowledge of intraspecific variation that can allow populations to respond uniquely to change. Here, we aim to test how population X environment relationships influence predicted suitable geographic distributions by comparing aggregated population-level models with species-level model predictions of suitable habitat within population ranges and across the species' range. We also test the effect of two variable selection methods on these predictions-both addressing the possibility of local adaptation: Models were built with (a) a common set, and number, of predictors and, (b) a unique combination and number of predictors specific to each group's training extent. Our study addresses the overarching hypothesis that populations have unique environmental niches, and specifically that (1) species-level models predict more suitable habitat within the ranges of genetic populations than individual models built from those groups, particularly when compared models are built with the same set of environmental predictors; and (2) aggregated genetic population models predict more suitable habitat across the species' range than the species-level model, an = d this difference will increase when models are trained with individualized predictors. We found the species models predicted more habitat within population ranges for two of three genetic groups regardless of variable selection, and that aggregated population models predicted more habitat than species' models, but that individualized predictors increased this difference. Our study emphasizes the extent to which changes to model predictions depend on the inclusion of genetic information and on the type and selection of predictors. Results from these modeling decisions can have broad implications for predicting population-level ecological and evolutionary responses to climate change.

Dataset Information

Photosynthetic variation and responsiveness to CO2 in a widespread riparian tree.

Publications

Photosynthetic variation and responsiveness to CO2 in a widespread riparian tree.

Similar Datasets

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