Edinburgh, Scotland, United Kingdom - TAIR

Predicting flowering time in changing
climates
In order to flower during favorable seasonal conditions, plants must integrate
and respond appropriately to multiple environmental signals, such as day length,
ambient temperature, and vernalization. However, little is known about the
balance and sensitivity of different pathways to complex environmental cues
under variable natural conditions in different climates and seasons, or how
natural variation in flowering genes is expressed in natural environments. To
measure the sensitivity of flowering time to perturbations in different signaling
pathways in natural seasonal environments, we grew a set of 320 Arabidopsis
ecotypes as well as mutants of key flowering time genes under natural conditions
in replicated field experiments in 5 sites spanning the species’ native European
climatic range. Using detailed temperature and light environments experienced
by plants throughout the growing season in each site, we have created a
genetically informed photothermal model of development which accurately
predicts time to bolting of flowering time mutants under field conditions, and
shows that flowering time in the field depends critically upon seasonal timing of
germination. In late summer and early autumn, germinating a week later can
cause a transition from rapid cycling to winter annual life histories. The model
predicts that the switch occurs earlier in the season for genotypes with high initial
vernalization requirements. To predict responses to future climate change, we
converted predicted air temperature from global climate models under a midrange
scenario of global warming into photothermal inputs to our model. The
model predicts that in Norwich, England, this predicted warming scenario for
2099 will cause a seasonal delay in the switch between rapid cycling and winter
annual life histories and reduced effects of natural genetic variation in the
strength of the initial vernalization requirement.
40
L15
Friday 10:00 - 10:30
Natural Variation
Johanna Schmitt1
Liana Burghardt1
Amity Wilczek1
Martha Cooper1
Stephen Welch2
1Brown University
Providence
RI
USA
2Kansas State University
Manhattan
KS
USA