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Abstract Local adaptation is a fundamental phenomenon in evolutionary biology, with relevance to formation of ecotypes, and ultimately new species, and application to restoration and species’ response to climate change. Reciprocal transplant gardens, a common garden in which ecotypes are planted among home and away habitats, are the gold standard to detect local adaptation in populations.This review focuses on reciprocal transplant gardens to detect local adaptation, especially in grassland species beginning with early seminal studies of grass ecotypes. Fast forward more than half a century, reciprocal gardens have moved into the genomic era, in which the genetic underpinnings of ecotypic variation can now be uncovered. Opportunities to combine genomic and reciprocal garden approaches offer great potential to shed light on genetic and environmental control of phenotypic variation. Our decadal study of adaptation in a dominant grass across the precipitation gradient of the US Great Plains combined genomic approaches and realistic community settings to shed light on controls over phenotype.Common gardens are not without limitations and challenges. A survey of recent studies indicated the modal study uses a tree species, three source sites and one growing site, focuses on one species growing in a monoculture, lasts 3 years, and does not use other experimental manipulations and rarely employs population genetic tools. Reciprocal transplant gardens are even more uncommon, accounting for only 39% of the studies in the literature survey with the rest occurring at a single common site. Reciprocal transplant gardens offer powerful windows into local adaptation when (a) placed across wide environmental gradients to encompass the species’ range; (b) conducted across timespans adequate for detecting responses; (c) employing selection studies among competing ecotypes in community settings and (d) combined with measurements of form and function which ultimately determine success in home and away environments.Synthesis. Reciprocal transplant gardens have been one of the foundations in evolutionary biology for the study of adaptation for the last century, and even longer in Europe. Moving forward, reciprocal gardens of foundational non‐model species, combined with genomic analyses and incorporation of biotic factors, have the potential to further revolutionize evolutionary biology. These field experiments will help to predict and model response to climate change and inform restoration practices.
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The accuracy of predicting maladaptation to new environments with genomic data
Abstract Rapid environmental change poses unprecedented challenges to species persistence. To understand the extent that continued change could have, genomic offset methods have been used to forecast maladaptation of natural populations to future environmental change. However, while their use has become increasingly common, little is known regarding their predictive performance across a wide array of realistic and challenging scenarios. Here, we evaluate the performance of currently available offset methods (gradientForest, the Risk‐Of‐Non‐Adaptedness, redundancy analysis with and without structure correction and LFMM2) using an extensive set of simulated data sets that vary demography, adaptive architecture and the number and spatial patterns of adaptive environments. For each data set, we train models using eitherall,adaptiveorneutralmarker sets and evaluate performance using in silico common gardens by correlating known fitness with projected offset. Using over 4,849,600 of such evaluations, we find that (1) method performance is largely due to the degree of local adaptation across the metapopulation (LA), (2)adaptivemarker sets provide minimal performance advantages, (3) performance within the species range is variable across gardens and declines when offset models are trained using additional non‐adaptive environments and (4) despite (1) performance declines more rapidly in globally novel climates (i.e. a climate without an analogue within the species range) for metapopulations with greaterLAthan lesserLA. We discuss the implications of these results for management, assisted gene flow and assisted migration.
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- Award ID(s):
- 2043905
- PAR ID:
- 10538161
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Molecular Ecology Resources
- Volume:
- 25
- Issue:
- 4
- ISSN:
- 1755-098X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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