Extant conifer species may be susceptible to rapid environmental change owing to their long generation times, but could also be resilient due to high levels of standing genetic diversity. Hybridisation between closely related species can increase genetic diversity and generate novel allelic combinations capable of fuelling adaptive evolution. Our study unravelled the genetic architecture of adaptive evolution in a conifer hybrid zone formed between
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Abstract Pinus strobiformis andP. flexilis . Using a multifaceted approach emphasising the spatial and environmental patterns of linkage disequilibrium and ancestry enrichment, we identified recently introgressed and background genetic variants to be driving adaptive evolution along different environmental gradients. Specifically, recently introgressed variants fromP. flexilis were favoured along freeze-related environmental gradients, while background variants were favoured along water availability-related gradients. We posit that such mosaics of allelic variants within conifer hybrid zones will confer upon them greater resilience to ongoing and future environmental change and can be a key resource for conservation efforts. -
Still, Christopher J. ; Rastogi, Bharat ; Page, Gerald F. M. ; Griffith, Dan M. ; Sibley, Adam ; Schulze, Mark ; Hawkins, Linnia ; Pau, Stephanie ; Detto, Matteo ; Helliker, Brent R. ( , New Phytologist)
Summary Canopy temperature
T canis a key driver of plant function that emerges as a result of interacting biotic and abiotic processes and properties. However, understanding controls onT canand forecasting canopy responses to weather extremes and climate change are difficult due to sparse measurements ofT canat appropriate spatial and temporal scales. Burgeoning observations ofT canfrom thermal cameras enable evaluation of energy budget theory and better understanding of how environmental controls, leaf traits and canopy structure influence temperature patterns. The canopy scale is relevant for connecting to remote sensing and testing biosphere model predictions. We anticipate that future breakthroughs in understanding of ecosystem responses to climate change will result from multiscale observations ofT canacross a range of ecosystems.