COS 27-2 - Resource quantity and resource heterogeneity shape species richness and beta-diversity patterns in big sagebrush plant communities

Tuesday, August 8, 2017: 8:20 AM
B116, Oregon Convention Center
Kyle A. Palmquist1, Samuel E. Jordan2, John B. Bradford3, Daniel R. Schlaepfer1,4 and William K. Lauenroth1,2, (1)Department of Botany, University of Wyoming, Laramie, WY, (2)School of Forestry and Environmental Studies, Yale University, New Haven, CT, (3)Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, AZ, (4)Section of Conservation Biology, University of Basel, Basel, Switzerland

Resource availability is a longstanding explanation for differences in biodiversity across scales, with both the quantity and heterogeneity of resources influencing patterns, albeit through different mechanisms. Greater resource quantity can either support more species or decrease biodiversity through competitive dominance and exclusion. Resource heterogeneity often increases niche partitioning in space or time, thus promoting species coexistence. The current consensus is unclear on how resource quantity and heterogeneity shape different aspects of biodiversity (alpha and beta-diversity). To this end, we explore the relationships between resource quantity and heterogeneity and species richness and beta-diversity in 51 big sagebrush plant communities along several important resource axes in drylands: climate, soil texture, and soil water availability. Plant communities were sampled using plots where species identity was recorded at multiple spatial scales (0.01-1000m2). We calculated beta-diversity as 1- α/λ, where α = richness at 1m2 and λ = richness at 1000m2. To quantify resource heterogeneity, we calculated the CV for: climate and available soil water on an intra-annual and inter-annual basis and soil texture collected within 4 subplots. Model selection using AIC and additive variance partitioning were used to estimate the relative importance of resource quantity and heterogeneity in shaping species richness and beta-diversity patterns.


We found both resource quantity and heterogeneity influenced species richness and beta-diversity patterns, but resource quantity was more strongly associated with species richness than resource heterogeneity, while resource heterogeneity was a slightly better predictor of beta-diversity than resource quantity. Mean annual precipitation (MAP) was the best predictor of species richness (pearson’s r = 0.54, variance explained = 0.22), and within-plot variability in percent clay explained additional variance (pearson’s r = 0.36, variance explained = 0.07, shared variance explained by both = 0.07). Within-plot variability in percent clay (pearson’s r = 0.34, variance explained = 0.09) and mean percent sand (pearson’s r = 0.31, variance explained = 0.07) were the best predictors of beta-diversity, respectively. MAP, a metric of resource availability in drylands and the best predictor of species richness, was not correlated with beta-diversity (pearson’s r < 0.01). Our results generally suggest that species richness and beta-diversity are shaped by both resource quantity and resource heterogeneity. Documenting how mean environmental conditions and environmental heterogeneity relate to current species richness and beta-diversity patterns is critical for understanding how plant communities will respond to anticipated changes in environmental conditions.