Analysis of the annual pollen integral in Albuquerque, New Mexico, shows a negative trend with temperatures for Juniper, Cottonwood, Elm, and Mulberry.

The goal of this study is to determine if the annual pollen integral (APIn) for the top tree allergens in the City of Albuquerque is correlated with meteorological variables. This analysis would be the first of its kind for this area. We used 17 consecutive years from 2004 to 2020 and data collected by the city of Albuquerque using a Spore Trap (Burkard) volumetric air sampler in a location designed to represent a typical desert environment. The pollen studied include Juniper, Elm, Ash, Cottonwood, and Mulberry. We found a negative linear correlation with early summer temperatures of the previous year and APIn for Elm, Cottonwood, and Mulberry, and early fall temperatures for Juniper. Linear regression models developed for Elm, Cottonwood, and Mulberry used the monthly mean maximum temperature for the month of June of the prior year as the independent variable to yield a R squared statistic (R 2) of 0.88, 0.91 and 0.78, respectively. For Juniper, the average monthly mean minimum temperature for the previous September and October served as the independent variable and yielded the R 2 value of 0.80. We also observed a positive trend for the annual maximum temperature over time and a negative trend for the total APIn. Summers in New Mexico are hot and dry, and they may be getting hotter and drier because of climate change. Our analysis predicts that climate change in this area may lead to reduced allergies if temperatures continue to increase and if precipitation patterns remain the same.

Genetic data improves niche model discrimination and alters the direction and magnitude of climate change forecasts.

Ecological niche models (ENMs) have classically operated under the simplifying assumptions that there are no barriers to gene flow, species are genetically homogeneous (i.e., no population-specific local adaptation), and all individuals share the same niche. Yet, these assumptions are violated for most broadly distributed species. Here, we incorporate genetic data from the widespread riparian tree species narrowleaf cottonwood (Populus angustifolia) to examine whether including intraspecific genetic variation can alter model performance and predictions of climate change impacts. We found that (1) P. angustifolia is differentiated into six genetic groups across its range from México to Canada and (2) different populations occupy distinct climate niches representing unique ecotypes. Comparing model discriminatory power, (3) all genetically informed ecological niche models (gENMs) outperformed the standard species-level ENM (3-14% increase in AUC; 1-23% increase in pROC). Furthermore, (4) gENMs predicted large differences among ecotypes in both the direction and magnitude of responses to climate change and (5) revealed evidence of niche divergence, particularly for the Eastern Rocky Mountain ecotype. (6) Models also predicted progressively increasing fragmentation and decreasing overlap between ecotypes. Contact zones are often hotspots of diversity that are critical for supporting species' capacity to respond to present and future climate change, thus predicted reductions in connectivity among ecotypes is of conservation concern. We further examined the generality of our findings by comparing our model developed for a higher elevation Rocky Mountain species with a related desert riparian cottonwood, P. fremontii. Together our results suggest that incorporating intraspecific genetic information can improve model performance by addressing this important source of variance. gENMs bring an evolutionary perspective to niche modeling and provide a truly "adaptive management" approach to support conservation genetic management of species facing global change.

Variability in flooding tolerance, growth and leaf traits in a Populus deltoides intraspecific progeny.

Climate change will increase the risk of flooding in several areas of the world where Populus deltoides Marshall (eastern cottonwood) is planted, so it would be desirable for this species to select for flooding tolerance. The aims of this work were to explore the variability in growth, leaf traits and flooding tolerance in an F1 full-sib intraspecific progeny of P. deltoides, to analyze the correlations of leaf and growth traits with flooding tolerance and to assess their suitability for use in breeding programs. Two-month-old parental clones and their progeny of 30 full-sib F1 genotypes were grown in pots and subjected to two treatments: (i) plants watered to field capacity (control) and (ii) plants flooded up to 10 cm above soil level for 35 days. Growth (height, diameter and biomass partition) and leaf traits (leaf size and number, specific leaf area, leaf senescence, abscission, stomatal conductance, carbon isotope discrimination, stomatal index) were measured. Flooding tolerance for each genotype was estimated as the ratio of the biomass of stressed plants to the biomass of control plants. Results showed segregation in terms of flooding tolerance in the F1 progeny. A significant genotype effect was found for leaf size and number, carbon isotopic discrimination and stomatal conductance, but it did not correlate with flooding tolerance. Height, diameter and root-to-shoot ratio had a positive phenotypic correlation with flooding tolerance, and there was a positive genetic correlation of height and diameter with biomass on both treatments. The narrow sense heritability values for the traits analyzed ranged from 0 to 0.56. We conclude that growth traits are more adequate than leaf traits for selection to increase flooding tolerance. A vigorous initial growth would increase flooding tolerance in young poplar plants.