Effects of climate on population fluctuations of ibex

Predicting the effects of the expected changes in climate on the dynamics of populations require that critical periods for climate‐induced changes in population size are identified. Based on time series analyses of 26 Swiss ibex (Capra ibex) populations, we show that variation in winter climate affected the annual changes in population size of most of the populations after accounting for the effects of density dependence and demographic stochasticity. In addition, precipitation during early summer also influenced the population fluctuations. This suggests that the major influences of climate on ibex population dynamics operated either through loss of individuals during winter or early summer, or through an effect on fecundity. However, spatial covariation in these climate variables was not able to synchronize the population fluctuations of ibex over larger distances, probably due to large spatial heterogeneity in the effects of single climate variables on different populations. Such spatial variation in the influence of the same climate variable on the local population dynamics suggests that predictions of influences of climate change need to account for local differences in population dynamical responses to climatic conditions.     

The extended Moran effect and large-scale synchronous fluctuations in the size of great tit and blue tit populations

1. Synchronous fluctuations of geographically separated populations are in general explained by the Moran effect, i.e. a common influence on the local population dynamics of environmental variables that are correlated in space. Empirical support for such a Moran effect has been difficult to provide, mainly due to problems separating out effects of local population dynamics, demographic stochasticity and dispersal that also influence the spatial scaling of population processes. Here we generalize the Moran effect by decomposing the spatial autocorrelation function for fluctuations in the size of great tit Parus major and blue tit Cyanistes caeruleus populations into components due to spatial correlations in the environmental noise, local differences in the strength of density regulation and the effects of demographic stochasticity. 2. Differences between localities in the strength of density dependence and nonlinearity in the density regulation had a small effect on population synchrony, whereas demographic stochasticity reduced the effects of the spatial correlation in environmental noise on the spatial correlations in population size by 21.7% and 23.3% in the great tit and blue tit, respectively. 3. Different environmental variables, such as beech mast and climate, induce a common environmental forcing on the dynamics of central European great and blue tit populations. This generates synchronous fluctuations in the size of populations located several hundred kilometres apart. 4. Although these environmental variables were autocorrelated over large areas, their contribution to the spatial synchrony in the population fluctuations differed, dependent on the spatial scaling of their effects on the local population dynamics. We also demonstrate that this effect can lead to the paradoxical result that a common environmental variable can induce spatial desynchronization of the population fluctuations. 5. This demonstrates that a proper understanding of the ecological consequences of environmental changes, especially those that occur simultaneously over large areas, will require information about the spatial scaling of their effects on local population dynamics.     

Spatial heterogeneity in climate change effects decouples the long‐term dynamics of wild reindeer populations in the high Arctic

The ‘Moran effect’ predicts that dynamics of populations of a species are synchronized over similar distances as their environmental drivers. Strong population synchrony reduces species viability, but spatial heterogeneity in density dependence, the environment, or its ecological responses may decouple dynamics in space, preventing extinctions. How such heterogeneity buffers impacts of global change on large‐scale population dynamics is not well studied. Here, we show that spatially autocorrelated fluctuations in annual winter weather synchronize wild reindeer dynamics across high‐Arctic Svalbard, while, paradoxically, spatial variation in winter climate trends contribute to diverging local population trajectories. Warmer summers have improved the carrying capacity and apparently led to increased total reindeer abundance. However, fluctuations in population size seem mainly driven by negative effects of stochastic winter rain‐on‐snow (ROS) events causing icing, with strongest effects at high densities. Count data for 10 reindeer populations 8–324 km apart suggested that density‐dependent ROS effects contributed to synchrony in population dynamics, mainly through spatially autocorrelated mortality. By comparing one coastal and one ‘continental’ reindeer population over four decades, we show that locally contrasting abundance trends can arise from spatial differences in climate change and responses to weather. The coastal population experienced a larger increase in ROS, and a stronger density‐dependent ROS effect on population growth rates, than the continental population. In contrast, the latter experienced stronger summer warming and showed the strongest positive response to summer temperatures. Accordingly, contrasting net effects of a recent climate regime shift—with increased ROS and harsher winters, yet higher summer temperatures and improved carrying capacity—led to negative and positive abundance trends in the coastal and continental population respectively. Thus, synchronized population fluctuations by climatic drivers can be buffered by spatial heterogeneity in the same drivers, as well as in the ecological responses, averaging out climate change effects at larger spatial scales.     

Geographical variation in the influence of density dependence and climate on the recruitment of Norwegian moose

The effects of variation in climate on population dynamics are likely to differ within the distributional range of a species, yet the consequences of such regional variation on demography and population dynamics are rarely considered. Here we examine how density dependence and different climate variables affect spatio-temporal variation in recruitment rates of Norwegian moose using data collected over a large geographical area during the hunting season. After accounting for observation error by a Bayesian Markov chain Monte Carlo technique, temporal variation in recruitment rates was relatively independent of fluctuations in local population size. In fact, a positive relationship was as common as a density-dependent decrease in fecundity rates. In general, high recruitment rates were found during autumn 1 year after years with a warm February, and after a warm May or cold June in year t − 1 or in year t. Large regional variation was also found in the effects of some of the weather variables, especially during spring. These patterns demonstrate both direct and delayed effects of weather on the recruitment of moose that possibly operate through an effect of body mass on the proportion of the females that sexually mature as 1.5 or 2.5 years old.     

Geographical gradients in the population dynamics of North American prairie ducks

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.     

Individual‐based modelling of resource competition to predict density‐dependent population dynamics: a case study with white storks

Density regulation influences population dynamics through its effects on demographic rates and consequently constitutes a key mechanism explaining the response of organisms to environmental changes. Yet, it is difficult to establish the exact form of density dependence from empirical data. Here, we developed an individual‐based model to explore how resource limitation and behavioural processes determine the spatial structure of white stork Ciconia ciconia populations and regulate reproductive rates. We found that the form of density dependence differed considerably between landscapes with the same overall resource availability and between home range selection strategies, highlighting the importance of fine‐scale resource distribution in interaction with behaviour. In accordance with theories of density dependence, breeding output generally decreased with density but this effect was highly variable and strongly affected by optimal foraging strategy, resource detection probability and colonial behaviour. Moreover, our results uncovered an overlooked consequence of density dependence by showing that high early nestling mortality in storks, assumed to be the outcome of harsh weather, may actually result from density dependent effects on food provision. Our findings emphasize that accounting for interactive effects of individual behaviour and local environmental factors is crucial for understanding density‐dependent processes within spatially structured populations. Enhanced understanding of the ways animal populations are regulated in general, and how habitat conditions and behaviour may dictate spatial population structure and demographic rates is critically needed for predicting the dynamics of populations, communities and ecosystems under changing environmental conditions.     

Cyclicity and variability in prey dynamics strengthens predator numerical response: the effects of vole fluctuations on white stork productivity

Theory predicts that optimality of life-long investment in reproduction is, among other factors, driven by the variability and predictability of the resources. Similarly, during the breeding season, single resource pulses characterized by short periods and high amplitudes enable strong numerical responses in their consumers. However, it is less well established how spatio-temporal dynamics in resource supplies influence the spatio-temporal variation of consumer reproduction. We used the common vole (Microtus arvalis)—white stork (Ciconia ciconia) resource—consumer model system to test the effect of increased temporal variation and periodicity of vole population dynamics on the strength of the local numerical response of storks. We estimated variability, cycle amplitude, and periodicity (by means of direct and delayed density dependence) in 13 Czech and Polish vole populations. Cross-correlation between annual stork productivity and vole abundance, characterizing the strength of the local numerical response of storks, increased when the vole population fluctuated more and population cycles were shorter. We further show that the onset of incubation of storks was delayed during the years of higher vole abundance. We demonstrate that high reproductive flexibility of a generalist consumer in tracking the temporal dynamics of its resource is driven by the properties of the local resource dynamics and we discuss possible mechanisms behind these patterns.     

Density dependence and stochastic variation in a newly established population of a small songbird

Models describing fluctuations in population size should include both density dependence and stochastic effects. We examine the relative contribution of variation in parameters of the expected dynamics as well as demographic and environmental stochasticity to fluctuations in a population of a small passerine bird, the pied flycatcher, that was newly established in a Dutch study area. Using the theta-logistic model of density regulation, we demonstrate that the estimated quasi-stationary distribution including demographic stochasticity is close to the stationary distribution ignoring demographic stochasticity, indicating a long expected time to extinction. We also show that the variance in the estimated quasi-stationary distribution is especially sensitive to variation in the density regulation function. Reliable population projections must therefore account for uncertainties in parameter estimates which we do by using the population prediction interval (PPI). After 2 years the width of the 90% PPI was already larger than the corresponding estimated range of variation in the quasi-stationary distribution. More precise prediction of future population size than can be derived from the quasi-stationary distribution could only be made for a time span less than about five years.     

European butterfly populations vary in sensitivity to weather across their geographical ranges

Aim

The aim was to assess the sensitivity of butterfly population dynamics to variation in weather conditions across their geographical ranges, relative to sensitivity to density dependence, and determine whether sensitivity is greater towards latitudinal range margins.

Location

Europe.

Time period

1980–2014.

Major taxa studied

Butterflies.

Methods

We use long‐term (35 years) butterfly monitoring data from > 900 sites, ranging from Finland to Spain, grouping sites into 2° latitudinal bands. For 12 univoltine butterfly species with sufficient data from at least four bands, we construct population growth rate models that include density dependence, temperature and precipitation during distinct life‐cycle periods, defined to accommodate regional variation in phenology. We use partial R² values as indicators of butterfly population dynamics' sensitivity to weather and density dependence, and assess how these vary with latitudinal position within a species' distribution.

Results

Population growth rates appear uniformly sensitive to density dependence across species' geographical distributions, and sensitivity to density dependence is typically greater than sensitivity to weather. Sensitivity to weather is greatest towards range edges, with symmetry in northern and southern parts of the range. This pattern is not driven by variation in the magnitude of weather variability across the range, topographic heterogeneity, latitudinal range extent or phylogeny. Significant weather variables in population growth rate models appear evenly distributed across the life cycle and across temperature and precipitation, with substantial intraspecific variation across the geographical ranges in the associations between population dynamics and specific weather variables.

Main conclusions

Range‐edge populations appear more sensitive to changes in weather than those nearer the centre of species' distributions, but density dependence does not exhibit this pattern. Precipitation is as important as temperature in driving butterfly population dynamics. Intraspecific variation in the form and strength of sensitivity to weather suggests that there may be important geographical variation in populations' responses to climate change.     

Climate variation and regional gradients in population dynamics of two hole-nesting passerines

Latitudinal gradients in population dynamics can arise through regional variation in the deterministic components of the population dynamics and the stochastic factors. Here, we demonstrate an increase with latitude in the contribution of a large-scale climate pattern, the North Atlantic Oscillation (NAO), to the fluctuations in size of populations of two European hole-nesting passerine species. However, this influence of climate induced different latitudinal gradients in the population dynamics of the two species. In the great tit the proportion of the variability in the population fluctuations explained by the NAO increased with latitude, showing a larger impact of climate on the population fluctuations of this species at higher latitudes. In contrast, no latitudinal gradient was found in the relative contribution of climate to the variability of the pied flycatcher populations because the total environmental stochasticity increased with latitude. This shows that the population ecological consequences of an expected climate change will depend on how climate affects the environmental stochasticity in the population process. In both species, the effects will be larger in those parts of Europe where large changes in climate are expected.     

Population fluctuations and regulation in great snipe: a time-series analysis

1. During the last centuries, the breeding range of the great snipe Gallinago media has declined dramatically in the western part of its distribution. To examine present population dynamics in the Scandinavian mountains, we collected and analysed a 19-year time series of counts of great snipe males at leks in central Norway, 1987-2005. 2. The population showed large annual fluctuations in the number of males displaying at lek sites (range 45-90 males at the peak of the mating season), but no overall trend. 3. We detected presence of direct density-dependent mechanisms regulating this population. Inclusion of the density-dependent term in a Ricker-type model significantly improved the fit with observed data (evaluated with Parametric Bootstrap Likelihood Ratio tests and Akaike's Information Criterion for small sample size). 4. An analysis of (a number of a priori likely) environmental covariates suggests that the population dynamics were affected by conditions influencing reproduction and survival of offspring during the summer, but not by conditions influencing survival at the wintering grounds in Africa. This is in contrast to many altricial birds breeding in the northern hemisphere, and supports the idea that population dynamics of migratory nidifugous birds are more influenced by conditions during reproduction. 5. Inclusion of these external factors into our model improved the detectability of density dependence. This illustrates that allowing for external effects may increase statistical power of density dependence tests and thus be of particular importance in relatively short time series. 6. In our best model of the population dynamics, two likely density-independent offspring survival covariates explained 47.3% of the variance in great snipe numbers (predation pressure estimated by willow grouse reproductive success and food availability estimated by the amount of precipitation in June), whereas density dependence explained 35.5%. Demographic stochasticity and unidentified environmental stochasticity may account for the remaining 17.2%.     

Density dependence forces divergent population growth rates and alters occupancy patterns of a central place foraging Antarctic seabird

Density‐dependent regulation is an important process in spatio‐temporal population dynamics because it can alter the effects of synchronizing processes operating over large spatial scales. Most frequently, populations are regulated by density dependence when higher density leads to reduced individual fitness and population growth, but inverse density dependence can also occur when small populations are subject to higher extinction risks. We investigate whether density‐dependent regulation influences population growth for the Antarctic breeding Adélie penguin Pygoscelis adeliae. Understanding the prevalence and nature of density dependence for this species is important because it is considered a sentinel species reflecting the impacts of fisheries and environmental change over large spatial scales in the Southern Ocean, but the presence of density dependence could introduce uncertainty in this role. Using data on population growth and indices of resource availability for seven regional Adélie penguin populations located along the East Antarctic coastline, we find compelling evidence that population growth is constrained at some locations by the amount of breeding habitat available to individuals. Locations with low breeding habitat availability had reduced population growth rates, higher overall occupancy rates, and higher occupancy of steeper slopes that are sparsely occupied or avoided at other locations. Our results are consistent with evolutionary models of avian breeding habitat selection where individuals search for high‐quality nest sites to maximize fitness returns and subsequently occupy poorer habitat as population density increases. Alternate explanations invoking competition for food were not supported by the available evidence, but strong conclusions on food‐related density dependence were constrained by the paucity of food availability data over the large spatial scales of this region. Our study highlights the importance of incorporating nonconstant conditions of species–environment relationships into predictive models of species distributions and population dynamics, and provides guidance for improved monitoring of fisheries and climate change impacts in the Southern Ocean.     

Modelling non-additive and nonlinear signals from climatic noise in ecological time series: Soay sheep as an example

Understanding how climate can interact with other factors in determining patterns of species abundance is a persistent challenge in ecology. Recent research has suggested that the dynamics exhibited by some populations may be a non-additive function of climate, with climate affecting population growth more strongly at high density than at low density. However, we lack methodologies to adequately explain patterns in population growth generated as a result of interactions between intrinsic factors and extrinsic climatic variation in non-linear systems. We present a novel method (the Functional Coefficient Threshold Auto-Regressive (FCTAR) method) that can identify interacting influences of climate and density on population dynamics from time-series data. We demonstrate its use on count data on the size of the Soay sheep population, which is known to exhibit dynamics generated by nonlinear and non-additive interactions between density and climate, living on Hirta in the St Kilda archipelago. The FCTAR method suggests that climate fluctuations can drive the Soay sheep population between different dynamical regimes--from stable population size through limit cycles and non-periodic fluctuations.     

Time series analysis of climate‐related factors and their impact on a red‐listed noble crayfish population in northern Sweden

1. Global climate change is predicted to raise water temperatures and alter flow regimes in northern river systems. Climate‐related factors might have profound impacts on survival, reproduction and distribution of freshwater species such as red‐listed noble crayfish (Astacus astacus) in its northern limit of distribution. 2. In this study, noble crayfish capture data over 27 years from the River Ljungan, Sweden, were examined. Time series of catch per unit effort (CPUE) were analysed in relation to the North Atlantic Oscillation (NAO) index, regional weather factors and water flow. CPUE was assumed to reflect differences in population size. Two models were constructed to explore the relative impact of different climate factors and density dependence on variability of catch sizes. 3. The most parsimonious model for CPUE time series, explaining 72% of the variance in CPUE, included density‐dependent population dynamics of the crayfish and climate or weather factors. The specific effect from density dependence in the model was 37%, while climate/weather factors contributed with 35% of the variation. The most important climate/weather factors are variations in NAO index and water flow. Temperature did not improve the model fit to capture data. 4. The best model was evaluated using independent data sets that gave correlations between model predictions and data ranging from 0.44 to 0.53. The density dependence shows a time lag of 1 year, while climate variables show time lags from 2 to 6 years in relation to CPUE, indicating effects on different cohorts of the crayfish population. 5. Both density dependence and climatic factors play a significant role in population fluctuations of noble crayfish. A 6‐year time lag for NAO index is puzzling but indicates that some as yet unidentified factors related to NAO might act on the juvenile stages of the population. Water flow shows a 2‐year lag to the CPUE, and high flow in the river may affect adult survival. The reasons for fluctuation of crayfish catches in response to climate need to be identified, and fishing quotas should consider the different cohort sizes because of variation in environment. Reintroduction programmes for crayfish need to consider effects of climate change when designing management strategies.     

Combined effect of ENSO and SAM on the population dynamics of the invasive yellowjacket wasp in central Chile

The population dynamics of the yellowjacket wasp (Vespula germanica Fabricus) in central Chile were analyzed for the first time. Using a simple Ricker logistic model and adding the effects of local weather variables (temperature and precipitation) and large-scale climate phenomena as El Niño Southern Oscillation (ENSO) and the Southern Annular Mode (SAM), we modeled the interannual fluctuations in nest density. The best model according to the Bayesian information criterion (BIC) included 1-year-lag negative feedback combined with the positive additive effects of ENSO and SAM. According to this model, yellowjacket nest density was favored by warm and dry winters, which probably influenced the survival of overwintering queens. Large-scale climatic variables [Southern Oscillation Index (SOI) and SAM] described the effect of exogenous factors in wasp fluctuations better than local weather variables did. Our results emphasize the usefulness of climate indices and simple theoretical-based models in insect ecological research.     

Estimating the growth of a newly established moose population using reproductive value

Estimating the population growth rate and environmental stochasticity of long-lived species is difficult because annual variation in population size is influenced by temporal autocorrelations caused by fluctuations in the age-structure. Here we use the dynamics of the reproductive value to estimate the long-term growth rate s and the environmental variance of a moose population that recently colonized the island of Vega in northern Norway. We show that the population growth rate was high (ŝ=0.26). The major stochastic influences on the population dynamics were due to demographic stochasticity, whereas the environmental variance was not significantly different from 0. This supports the suggestion that population growth rates of polytocous ungulates are high, and that demographic stochasticity must be assessed when estimating the growth of small ungulate populations.     

Contrasting consequences of climate change for migratory geese: Predation,density dependence and carryover effects offset benefits of high‐arctic warming

Climate change is most rapid in the Arctic, posing both benefits and challenges for migratory herbivores. However, population‐dynamic responses to climate change are generally difficult to predict, due to concurrent changes in other trophic levels. Migratory species are also exposed to contrasting climate trends and density regimes over the annual cycle. Thus, determining how climate change impacts their population dynamics requires an understanding of how weather directly or indirectly (through trophic interactions and carryover effects) affects reproduction and survival across migratory stages, while accounting for density dependence. Here, we analyse the overall implications of climate change for a local non‐hunted population of high‐arctic Svalbard barnacle geese, Branta leucopsis, using 28 years of individual‐based data. By identifying the main drivers of reproductive stages (egg production, hatching and fledging) and age‐specific survival rates, we quantify their impact on population growth. Recent climate change in Svalbard enhanced egg production and hatching success through positive effects of advanced spring onset (snow melt) and warmer summers (i.e. earlier vegetation green‐up) respectively. Contrastingly, there was a strong temporal decline in fledging probability due to increased local abundance of the Arctic fox, the main predator. While weather during the non‐breeding season influenced geese through a positive effect of temperature (UK wintering grounds) on adult survival and a positive carryover effect of rainfall (spring stopover site in Norway) on egg production, these covariates showed no temporal trends. However, density‐dependent effects occurred throughout the annual cycle, and the steadily increasing total flyway population size caused negative trends in overwinter survival and carryover effects on egg production. The combination of density‐dependent processes and direct and indirect climate change effects across life history stages appeared to stabilize local population size. Our study emphasizes the need for holistic approaches when studying population‐dynamic responses to global change in migratory species.     

Population Growth and Demography of Common Loons in the Northern United States

ABSTRACT We used recent developments in theoretical population ecology to construct basic models of common loon (Gavia immer) demography and population dynamics. We parameterized these models using existing survival estimates and data from long-term monitoring of loon productivity and abundance. Our models include deterministic, 2-stage, density-independent matrix models, yielding population growth-rate estimates (λ) of 0.99 and 1.01 for intensively studied populations in our Wisconsin, USA, and New Hampshire, USA, study areas, respectively. Perturbation analysis of these models indicated that estimated growth rate is extremely sensitive to adult survival, as expected for this long-lived species. Also, we examined 20 years of count data for the 2 areas and evaluated support for a set of count-based models of population growth. We detected no temporal trend in Wisconsin, which would be consistent with fluctuation around an average equilibrium state but could also result from data limitations. For New Hampshire, the model set included varying formulations of density dependence and partitioning of stochasticity that were enabled by the annual sampling resolution. The best model for New Hampshire included density regulation of population growth and, along with the demographic analyses for both areas, provided insight into the possible importance of breeding habitat availability and the abundance of nonbreeding adults. Based on these results, we recommend that conservation organizations include nonbreeder abundance in common loon monitoring efforts and that additional emphasis be placed on identifying and managing human influences on adult loon survival.     

Estimating partial observability and nonlinear climate effects on stochastic community dynamics of migratory waterfowl

1. Understanding the impact of environmental variability on migrating species requires the estimation of sequential abiotic effects in different geographic areas across the life cycle. For instance, waterfowl (ducks, geese and swans) usually breed widely dispersed throughout their breeding range and gather in large numbers in their wintering headquarters, but there is a lack of knowledge on the effects of the sequential environmental conditions experienced by migrating birds on the long-term community dynamics at their wintering sites. 2. Here, we analyse multidecadal time-series data of 10 waterfowl species wintering in the Guadalquivir Marshes (SW Spain), the single most important wintering site for waterfowl breeding in Europe. We use a multivariate state-space approach to estimate the effects of biotic interactions, local environmental forcing during winter and large-scale climate during breeding and migration on wintering multispecies abundance fluctuations, while accounting for partial observability (observation error and missing data) in both population and environmental data. 3. The joint effect of local weather and large-scale climate explained 31·6% of variance at the community level, while the variability explained by interspecific interactions was negligible (<5%). In general, abiotic conditions during winter prevailed over conditions experienced during breeding and migration. Across species, a pervasive and coherent nonlinear signal of environmental variability on population dynamics suggests weaker forcing at extreme values of abiotic variables. 4. Modelling missing observations through data augmentation increased the estimated magnitude of environmental forcing by an average 30·1% and reduced the impact of stochasticity by 39·3% when accounting for observation error. Interestingly however, the impact of environmental forcing on community dynamics was underestimated by an average 15·3% and environmental stochasticity overestimated by 14·1% when ignoring both observation error and data augmentation. 5. These results provide a salient example of sequential multiscale environmental forcing in a major migratory bird community, which suggests a demographic link between the breeding and wintering grounds operating through nonlinear environmental effects. Remarkably, this study highlights that modelling observation error in the environmental covariates of an ecological model can be proportionally more important than modelling this source of variance in the population data.