Genetic variation in Pinus strobiformis growth and drought tolerance from southwestern US populations.

The persistence of some tree species is threatened by combinations of novel abiotic and biotic stressors. To examine the hypothesis that Pinus strobiformis Engelm., a tree threatened by an invasive forest pathogen and a changing climate, exhibits intraspecific genetic variation in adaptive traits, we conducted a common garden study of seedlings at one location with two watering regimes using 24 populations. Four key findings emerged: (i) growth and physiological traits were low to moderately differentiated among populations but differentiation was high for some traits in water-stressed populations; (ii) seedlings from warmer climates grew larger, had higher stomatal density and were more water-use efficient (as measured by the carbon isotope ratio) than populations from colder climates; (iii) seedlings from the northern edge of the species' distribution had lower water-use efficiency, higher stomatal conductance, slower growth and longer survival in a lethal drought experiment compared with seedlings from more southern populations; and (iv) based on non-metric multidimensional scaling analyses, populations clustered into southern and northern groups, which did not correspond to current seed transfer zones. Our discovery of a clinal geographic pattern of genetic variation in adaptive traits of P. strobiformis seedlings will be useful in developing strategies to maintain the species during ongoing climate change and in the face of an invasive pathogen.

Integrating landscape genomics and spatially explicit approaches to detect loci under selection in clinal populations.

Uncovering the genetic basis of adaptation hinges on the ability to detect loci under selection. However, population genomics outlier approaches to detect selected loci may be inappropriate for clinal populations or those with unclear population structure because they require that individuals be clustered into populations. An alternate approach, landscape genomics, uses individual-based approaches to detect loci under selection and reveal potential environmental drivers of selection. We tested four landscape genomics methods on a simulated clinal population to determine their effectiveness at identifying a locus under varying selection strengths along an environmental gradient. We found all methods produced very low type I error rates across all selection strengths, but elevated type II error rates under "weak" selection. We then applied these methods to an AFLP genome scan of an alpine plant, Campanula barbata, and identified five highly supported candidate loci associated with precipitation variables. These loci also showed spatial autocorrelation and cline patterns indicative of selection along a precipitation gradient. Our results suggest that landscape genomics in combination with other spatial analyses provides a powerful approach for identifying loci potentially under selection and explaining spatially complex interactions between species and their environment.

Monitoring surface water chemistry near magnesium chloride dust suppressant treated roads in Colorado.

Magnesium chloride (MgCl2)-based dust suppression products are commonly used throughout western United States on nonpaved roads for dust suppression and road stabilization by federal, state, and county transportation agencies. The environmental implications of annually applying these products throughout spring and summer months on adjacent stream chemistry are not known. Sixteen streams were monitored biweekly for 1 to 2 yr in two Colorado counties for a suite of water quality variables up and downstream of nonpaved roads treated with MgCl2-based dust suppression products. Eight of 16 streams had significantly higher downstream than upstream concentrations of chloride or magnesium over the entire monitoring period (p