Extreme climatic events are predicted to increase in frequency and magnitude, but their ecological impacts are poorly understood. Such events are large, infrequent, stochastic perturbations that can change the outcome of entrained ecological processes. Here we show how an extreme flood event affected a desert rodent community that has been monitored for 30 years. The flood (i ) caused catastrophic, species-specific mortality; (ii ) eliminated the incumbency advantage of previously dominant species; (iii ) reset long-term population and community trends; (iv) interacted with competitive and metapopulation dynamics; and (v) resulted in rapid, wholesale reorganization of the community. This and a previous extreme rainfall event were punctuational perturbations-they caused large, rapid populationand community-level changes that were superimposed on a background of more gradual trends driven by climate and vegetation change. Captured by chance through long-term monitoring, the impacts of such large, infrequent events provide unique insights into the processes that structure ecological communities.desert rodents ͉ incumbency advantage ͉ punctuational dynamics

Abstract. The species abundance distribution (SAD) is one of the most studied patterns in ecology due to its potential insights into commonness and rarity, community assembly, and patterns of biodiversity. It is well established that communities are composed of a few common and many rare species, and numerous theoretical models have been proposed to explain this pattern. However, no attempt has been made to determine how well these theoretical characterizations capture observed taxonomic and global-scale spatial variation in the general form of the distribution. Here, using data of a scope unprecedented in community ecology, we show that a simple maximum entropy model produces a truncated log-series distribution that can predict between 83% and 93% of the observed variation in the rank abundance of species across 15 848 globally distributed communities including birds, mammals, plants, and butterflies. This model requires knowledge of only the species richness and total abundance of the community to predict the full abundance distribution, which suggests that these factors are sufficient to understand the distribution for most purposes. Since geographic patterns in richness and abundance can often be successfully modeled, this approach should allow the distribution of commonness and rarity to be characterized, even in locations where empirical data are unavailable.

Recent models of community assembly, structure, and dynamics have incorporated, to varying degrees, three mechanistic processes: resource limitation and interspecific competition, niche requirements of species, and exchanges between a local community and a regional species pool. Synthesizing 30 years of data from an intensively studied desert rodent community, we show that all of these processes, separately and in combination, have influenced the structural organization of this community and affected its dynamical response to both natural environmental changes and experimental perturbations. In addition, our analyses suggest that zero-sum constraints, niche differences, and metacommunity processes are inextricably linked in the ways that they affect the structure and dynamics of this system. Explicit consideration of the interaction of these processes should yield a deeper understanding of the assembly and dynamics of other ecological communities. This synthesis highlights the role that long-term data, especially when coupled with experimental manipulations, can play in assessing the fundamental processes that govern the structure and function of ecological communities.

Abstract. Rapid changes in climate and land use and the resulting shifts in species distributions and ecosystem functions have motivated the development of the National Ecological Observatory Network (NEON). Integrating across spatial scales from ground sampling to remote sensing, NEON will provide data for users to address ecological responses to changes in climate, land use, and species invasion across the United States for at least 30 years. Although NEON remote sensing and tower sensor elements are relatively well known, the biological measurements are not. This manuscript describes NEON terrestrial sampling, which targets organisms across a range of generation and turnover times, and a hierarchy of measurable biological states. Measurements encompass species diversity, abundance, phenology, demography, infectious disease, ecohydrology, and biogeochemistry. The continental-scale sampling requires collection of comparable and calibrated data using transparent methods. Data will be publicly available in a variety of formats and suitable for integration with other long-term efforts. NEON will provide users with the data necessary to address large-scale questions, challenge current ecological paradigms, and forecast ecological change.