All Together Now Environmental drivers, such as extreme weather events, impact population dynamics and can synchronize such dynamics across populations within a species. Given that many species depend on similar resources, such events might also be expected to synchronize dynamics across species, but the complexity of multispecies communities makes it difficult to reveal potential drivers in common. Hansen et al. (p. 313 ) took advantage of the simplicity of the year-round community on the high-arctic island of Spitsbergen to test for the presence of synchrony. Population fluctuations were synchronized across the three herbivore species (Svalbard reindeer, Svalbard rock ptarmigan, and sibling vole) and the single resident predator, the arctic fox, was in lagged synchrony. The driver of these fluctuations appears to be extreme winter rain-on-snow events that reduce the availability of winter forage due to ice cover.

Broad-scale environmental changes are altering patterns of natural selection in the wild, but few empirical studies have quantified the demographic cost of sustained directional selection in response to these changes. We tested whether population growth in a wild bird is negatively affected by climate change-induced phenological mismatch, using almost four decades of individual-level life-history data from a great tit population. In this population, warmer springs have generated a mismatch between the annual breeding time and the seasonal food peak, intensifying directional selection for earlier laying dates. Interannual variation in population mismatch has not, however, affected population growth. We demonstrated a mechanism contributing to this uncoupling, whereby fitness losses associated with mismatch are counteracted by fitness gains due to relaxed competition. These findings imply that natural populations may be able to tolerate considerable maladaptation driven by shifting climatic conditions without undergoing immediate declines.

A major question in ecology is how age-specific variation in demographic parameters influences population dynamics. Based on long-term studies of growing populations of birds and mammals, we analyze population dynamics by using fluctuations in the total reproductive value of the population. This enables us to account for random fluctuations in age distribution. The influence of demographic and environmental stochasticity on the population dynamics of a species decreased with generation time. Variation in age-specific contributions to total reproductive value and to stochastic components of population dynamics was correlated with the position of the species along the slow-fast continuum of life-history variation. Younger age classes relative to the generation time accounted for larger contributions to the total reproductive value and to demographic stochasticity in "slow" than in "fast" species, in which many age classes contributed more equally. In contrast, fluctuations in population growth rate attributable to stochastic environmental variation involved a larger proportion of all age classes independent of life history. Thus, changes in population growth rates can be surprisingly well explained by basic species-specific life-history characteristics. JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. Submitted December 17, 2012; Accepted June 19, 2013; Electronically published October 25, 2013 abstract: A major question in ecology is how age-specific variation in demographic parameters influences population dynamics. Based on long-term studies of growing populations of birds and mammals, we analyze population dynamics by using fluctuations in the total reproductive value of the population. This enables us to account for random fluctuations in age distribution. The influence of demographic and environmental stochasticity on the population dynamics of a species decreased with generation time. Variation in age-specific contributions to total reproductive value and to stochastic components of population dynamics was correlated with the position of the species along the slow-fast continuum of life-history variation. Younger age classes relative to the generation time accounted for larger contributions to the total reproductive value and to demographic stochasticity in "slow" than in "fast" species, in which many age classes contributed more equally. In contrast, fluctuations in population growth rate attributable to stochastic environmental variation involved a larger proportion of all age classes independent of * Corresponding author; e-mail: bernt.erik.sather@bio.ntnu.no.Am. Nat. 2013. Vol. 182, pp. 743-759. ᭧ 2013 by The University of Chicago. 0003-0147/2013/18206-54347$15.00. All rights reserved. DOI: 10.1086/67349...

Summary1. Studies of seasonality in ecological diversity rarely extend over more than a few years, and few studies of seasonal diversity have explicitly investigated the influence of environmental factors on seasonal community composition, especially in tropical communities. 2. Our 10 years of monthly sampling in Amazonian Ecuador yielded 20 996 individuals of 137 fruit-feeding butterfly species. Seasonal cycles of rainfall drive annual cycles in species diversity and community similarity. Undetermined processes operating most strongly during the dry season maintain species diversity and high community similarity across years. 3. Seasonal cycles in community diversity and similarity are superimposed on a gradual decline in similarity between community samples on a decadal time-scale because of long-term changes in species abundances. 4. Monitoring and analysis of changes in community composition over a range of time-scales can be used to refine models of community dynamics by incorporating environmental factors necessary to predict the ecological impact of future climate change.

Summary 1.Geographic gradients in population dynamics may occur because of spatial variation in resources that affect the deterministic components of the dynamics (i.e. carrying capacity, the specific growth rate at small densities or the strength of density regulation) or because of spatial variation in the effects of environmental stochasticity. To evaluate these, we used a hierarchical Bayesian approach to estimate parameters characterizing deterministic components and stochastic influences on population dynamics of eight species of ducks (mallard, northern pintail, blue-winged teal, gadwall, northern shoveler, American wigeon, canvasback and redhead ( Anas platyrhynchos , A. acuta , A. discors , A. strepera , A. clypeata , A. americana , Aythya valisineria and Ay. americana , respectively) breeding in the North American prairies, and then tested whether these parameters varied latitudinally. 2. We also examined the influence of temporal variation in the availability of wetlands, spring temperature and winter precipitation on population dynamics to determine whether geographical gradients in population dynamics were related to large-scale variation in environmental effects. Population variability, as measured by the variance of the population fluctuations around the carrying capacity K , decreased with latitude for all species except canvasback. This decrease in population variability was caused by a combination of latitudinal gradients in the strength of density dependence, carrying capacity and process variance, for which details varied by species. 3. The effects of environmental covariates on population dynamics also varied latitudinally, particularly for mallard, northern pintail and northern shoveler. However, the proportion of the process variance explained by environmental covariates, with the exception of mallard, tended to be small. 4. Thus, geographical gradients in population dynamics of prairie ducks resulted from latitudinal gradients in both deterministic and stochastic components, and were likely influenced by spatial differences in the distribution of wetland types and shapes, agricultural practices and dispersal processes. 5. These results suggest that future management of these species could be improved by implementing harvest models that account explicitly for spatial variation in density effects and environmental stochasticity on population abundance.