| Abstract Detail
Molecular Ecology Ensing, David [1], Eckert, Christopher [2]. Inconsistent local adaptation despite strong genetic differentiation across a steep elevational gradient in growing season length. When species colonize latitudinal or elevational gradients of growing season length, natural selection should promote local adaptation in reproductive timing. In the Canadian Rocky Mountains, the annual Rhinanthus minor exhibits steep phenotypic clines in phenology across elevation due, in part, to what seems like adaptive genetic differentiation in the timing of flowering and fruit maturation. However, the species also responds to variation in season length with striking co-gradient plasticity that could erode local adaptation by facilitating gene flow. In each of two generations, we quantified local adaptation by reciprocally transplanting seeds among nine sites spanning ~1000m elevation and 2-fold variation in season length. Based on lifetime fitness, local adaptation was inconsistent, varying from strong local adaptation to strong local maladaptation. The hypothesis that rampant gene flow eroded adaptation among R. minor populations is inconsistent with substantial variation in fitness among source populations when planted at common sites, and with strong genetic differentiation (Fst = 0.18) at genome-wide SNPs. Although local adaptation is widely viewed as common, especially in sessile organisms, our results join growing evidence of inconsistent adaptation to variation in climate. What constrains climatic adaptation is emerging as a key question in this era of rapid global change.
1 - Agriculture & Agri-Foods Canada, Environmental Health, Box 5000, 4200 Highway 97, Summerland, BC, V0H 1Z0, Canada
2 - Department Of Biology, Department Of Biology, Queen's University, 116 Barrie Street, Kingston, ON, K7L 3N6, Canada
Keywords:
adaptation
phenology
global change
mountains
genetc differentiation
flowering phenology.
Presentation Type: Oral Paper
Session: MOL1, Molecular Ecology
Location: Virtual/Virtual
Date: Tuesday, July 28th, 2020
Time: 1:15 PM
Number: MOL1004
Abstract ID:592
Candidate for Awards:None |
