Sam, a Ph.D. student with the Sala Lab, was recently awarded the best oral presentation in Vegetation Science at the Ecological Society of America annual meeting in New Orleans. This prestigious award is dedicated to the advancement of Vegetation Science. Sam presented research from his Master’s thesis. His research surveyed over 50 sites across Wyoming to explore plant diversity in big sagebrush plant communities, from 100 square centimeters to 1000 square meters (five orders of magnitude in spatial scale). “Once we knew what the patterns of plant diversity were, we used a simulation model to explore how water moves through these ecosystems. With this soil water balance model (SOILWAT2) we were able to quantify when and where layers in the soil are wet- a critical question in how drylands function. We found that different kinds of plants were related to unique aspects of the soil water balance, deepening our understanding of how climate change might affect these communities,” explained Sam.
Plant communities are controlled by multiple, interacting ecological drivers that influence the frequency, abundance, and diversity of species. For many dryland ecosystems, soil water availability is the primary limiting resource that influences structure, function, and composition. We used intensive field sampling coupled with soil water balance modeling to explore the relative importance of biotic and abiotic variables on plant species richness at the landscape scale in dryland plant communities. We asked 1) what are the patterns of total and functional type richness? and 2) what are the relationships between total and functional type richness and macroclimatic, ecohydrological, and biotic conditions? We estimated species richness at multiple spatial scales in 48 dryland plant communities dominated by big sagebrush (Artemisia tridentata) and quantified richness and variability for total species and functional types at each spatial scale. We used multiple regression and model selection to determine whether climatic means, multiple metrics of soil moisture from a soil water balance model (SOILWAT2), or site-specific soil and vegetation variables were more related to total and functional type richness. With our top models, we used variance partitioning to determine the unique variability in total and functional type richness.
Richness was most variable at the smallest spatial scale (CV = 71%) and least variable at the largest spatial scale (CV = 10%). The three major functional types had almost equal variability at the 100 m2 spatial scale (grass CV = 12%, forb CV = 16%, shrub CV = 17%), but had unequal variability at the smallest spatial scale, 0.01m2 (grass CV = 83%, forb CV = 139%, shrub CV = 249%). We found that at the largest sampling scale (1000 m2), richness was more strongly related to ecohydrological variables than climate or biotic variables. Variance partitioning revealed that a large portion of variability in total community (~54%), grass (~40%), forb (~47%), and shrub (~25%) richness was explained by soil water variables. Including ecohydrological, macroclimatic, and biotic predictors in the same model did not substantially increase explanatory power beyond ecohydrological variables alone. Our results highlight the variability of species richness within plant communities that share a dominant species. Additionally, our findings reinforce the potentially greater explanatory power of soil water variables over climatic conditions in dryland plant communities, and offer insight as to which aspects of soil moisture may be most influential to species richness in big sagebrush communities.