Meeting Abstract

S9.9  Friday, Jan. 7  Incorporating population variation in thermal niche properties into geographic range shift predictions ANGERT, AL*; SHETH, SN; Colorado State University; Colorado State University angert@mail.colostate.edu

Determining how species’ geographic ranges are governed by current climates and are likely to change in response to rapid climatic change poses a major biological challenge. Geographic ranges are often fragmented and may be composed of genetically differentiated populations that differ in thermal adaptations (Savolainen et al. 2007, Aitken et al. 2008, Kuo & Sanford 2009). Correlative distribution models, which relate occurrence data to climatic layers, enable projections of future range changes for many different organisms. Correlative models implicitly incorporate variation among populations into species-level environmental response curves. However, trade-offs between different aspects of performance, such as between high- and low-temperature tolerance or between maximal performance and performance breadth, suggest that performance of any given population is a subset of that of the species as a whole. Therefore, predictions based on species-level curves are likely to overestimate the species’ ability to persist at a given location (Chown et al. 2009). We examine whether consideration of population divergence and thermal trade-offs alters distribution projections for the scarlet monkeyflower, Mimulus cardinalis, a perennial herb of western North America. We measured genetically based differences in growth rate as a function of temperature for twelve populations collected from the range center to the northern range margin. We modeled thermal performance curves for each population and for the species as a whole. Parameters from performance curves were used to test for thermal performance trade-offs and to generate mechanistic distribution models. We discuss differences in distribution projections between models based on species-level and population-level thermal performance curves.