Snowfall provides the majority of soil water in certain ecosystems of North America. We tested the hypothesis that snow depth variation affects soil water content, which in turn drives water potential (Ψ) and photosynthesis, over 10 years for two widespread shrubs of the western USA. Stem Ψ (Ψ stem) and photosynthetic gas exchange [stomatal conductance to water vapor (g s), and CO2 assimilation (A)] were measured in mid-June each year from 2004 to 2013 for Artemisia tridentata var. vaseyana (Asteraceae) and Purshia tridentata (Rosaceae). Snow fences were used to create increased or decreased snow depth plots. Snow depth on +snow plots was about twice that of ambient plots in most years, and 20 % lower on -snow plots, consistent with several down-scaled climate model projections. Maximal soil water content at 40- and 100-cm depths was correlated with February snow depth. For both species, multivariate ANOVA (MANOVA) showed that Ψ stem, g s, and A were significantly affected by intra-annual variation in snow depth. Within years, MANOVA showed that only A was significantly affected by spatial snow depth treatments for A. tridentata, and Ψ stem was significantly affected by snow depth for P. tridentata. Results show that stem water relations and photosynthetic gas exchange for these two cold desert shrub species in mid-June were more affected by inter-annual variation in snow depth by comparison to within-year spatial variation in snow depth. The results highlight the potential importance of changes in inter-annual variation in snowfall for future shrub photosynthesis in the western Great Basin Desert.

Models are simplified representations of more complex systems that help scientists structure the knowledge they acquire. As such, they are ubiquitous and invaluable in scientific research and communication. Because science education strives to make classroom activities more closely reflect science in practice, models have become integral teaching and learning tools woven throughout the Next Generation Science Standards (NGSS). Although model-based learning and curriculum are not novel in educational theory, only recently has modeling taken center stage in K–12 national standards for science, technology, engineering, and mathematics (STEM) classes. We present a variety of examples to outline the importance of various types of models and the practice of modeling in biological research, as well as the emphasis of NGSS on their use in both classroom learning and assessment. We then suggest best practices for creating and modifying models in the context of student-driven inquiry and demonstrate that even subtle incorporation of modeling into existing science curricula can help achieve student learning outcomes, particularly for English-language learners. In closing, we express the value of models and modeling in life beyond the classroom and research laboratory, and highlight the critical importance of “model literacy” for the next generation of scientists, engineers, and problem-solvers.