How expected increases in climate variability will affect species diversity depends on the role of such variability in regulating the coexistence of competing species. Despite theory linking temporal environmental fluctuations with the maintenance of diversity, the importance of climate variability for stabilizing coexistence remains unknown because of a lack of appropriate long-term observations. Here, we analyze three decades of demographic data from a Kansas prairie to demonstrate that interannual climate variability promotes the coexistence of three common grass species. Specifically, we show that (i) the dynamics of the three species satisfy all requirements of ''storage effect'' theory based on recruitment variability with overlapping generations, (ii) climate variables are correlated with interannual variation in species performance, and (iii) temporal variability increases low-density growth rates, buffering these species against competitive exclusion. Given that environmental fluctuations are ubiquitous in natural systems, our results suggest that coexistence based on the storage effect may be underappreciated and could provide an important alternative to recent neutral theories of diversity. Field evidence for positive effects of variability on coexistence also emphasizes the need to consider changes in both climate means and variances when forecasting the effects of global change on species diversity.climate change ͉ competition ͉ grassland ͉ plant community ͉ population dynamics S trong climate variability characterizes ecosystems worldwide, and in many regions this variability is predicted to increase over the next century because of higher frequencies of severe storms and droughts (1, 2). The ecological impacts of increased climate variability are poorly understood (3), especially in comparison with threats posed by increasing mean temperatures (4,5). This gap in empirical research contrasts sharply with a considerable body of theory examining the effects of environmental fluctuations on the maintenance of species diversity (6-9).''Storage effect'' theory derives the conditions under which climate variability will have stabilizing or destabilizing effects on species coexistence (10). The temporal storage effect described in refs. 6 and 9 requires that three conditions be met. To satisfy condition 1, species must have long lifespans to buffer their populations against unfavorable years. For condition 2, species must differ in their response to climate variation. These speciesspecific responses to climate cause each species to experience relatively more intraspecific competition during its favorable years and more interspecific competition during its unfavorable years. Condition 3 requires that the effect of competition on each species must be more severe in years favorable for that species than in unfavorable years. When condition 2 is present, intraspecific competition will be more severe than interspecific competition. As a result, climate variability gives species an advantage when they become ra...

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[1] Many applications in river research and management rely upon two-dimensional (2D) numerical models to characterize flow fields, assess habitat conditions, and evaluate channel stability. Predictions from such models are potentially highly uncertain due to the uncertainty associated with the topographic data provided as input. This study used a spatial stochastic simulation strategy to examine the effects of topographic uncertainty on flow modeling. Many, equally likely bed elevation realizations for a simple meander bend were generated and propagated through a typical 2D model to produce distributions of watersurface elevation, depth, velocity, and boundary shear stress at each node of the model's computational grid. Ensemble summary statistics were used to characterize the uncertainty associated with these predictions and to examine the spatial structure of this uncertainty in relation to channel morphology. Simulations conditioned to different data configurations indicated that model predictions became increasingly uncertain as the spacing between surveyed cross sections increased. Model sensitivity to topographic uncertainty was greater for base flow conditions than for a higher, subbankfull flow (75% of bankfull discharge). The degree of sensitivity also varied spatially throughout the bend, with the greatest uncertainty occurring over the point bar where the flow field was influenced by topographic steering effects. Uncertain topography can therefore introduce significant uncertainty to analyses of habitat suitability and bed mobility based on flow model output. In the presence of such uncertainty, the results of these studies are most appropriately represented in probabilistic terms using distributions of model predictions derived from a series of topographic realizations.Citation: Legleiter, C. J., P. C. Kyriakidis, R. R. McDonald, and J. M. Nelson (2011), Effects of uncertain topographic input data on two-dimensional flow modeling in a gravel-bed river, Water Resour. Res., 47, W03518,

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