Empirical evaluation of observation scale effects in community time series

Natural communities are highly complex and dynamic over time, with populations structured by numerous abiotic and biotic forces acting through direct and indirect pathways. Multispecies Autoregressive (MAR) modeling can be used to partition effects of variables that are interrelated and temporally autocorrelated in time series from natural systems. Here we address two main questions in applying MAR models to community time series. First, what is the effect of observation scale on interpretation of community dynamics? We used a 10‐year weekly planktonic time series from Lake Washington to construct multiple “biweekly” and “monthly” data sets, and compared resulting community interaction models. Direct abiotic effects and intraspecific autocorrelation were apparent using all data sets. Biotic interactions were more apparent using biweekly and monthly data, indicating that time lags longer than one week were necessary to detect numerical response to interspecific interactions. Second, we examined effects of dropping the winter months from our analyses to simulate the common practice of sampling only during the “growing season” in long‐term ecological studies. We found that biotic interactions remained similarly characterized in models using only non‐winter months, but that the importance of seasonal physical factors nearly disappeared in non‐winter models. Exclusion of winter data in sampling designs may therefore allow us to characterize biotic interactions, although it may not help us understand populations’ relationships to seasonal abiotic variables. The models supported many previous findings from experimental and qualitative investigations of Lake Washington community interactions, implying that MARs provided plausible characterizations of community dynamics, but some previously unconsidered relationships did emerge, such as the importance of cryptomonads and picoplankton for zooplankton growth. We conclude that explicit consideration of time lags in biotic response is necessary to understand relative importance of abiotic and biotic factors, and that sampling regime can therefore strongly influence our interpretations of community dynamics.     

Spatiotemporal dynamics in mountain grasslands: Species autocorrelations in space and time

Permanent plots with a fine scale recording system were used to trace the spatiotemporal process within two mountain grasslands in the Krkono?e Mts., Czech Republic. The analysis used autocorrelation over increasing lags in space and/or time. Moran'sI was used to measure the autocorrelation. There was a lot of variation between species both in spatial and temporal correlograms. The spatiotemporal pattern of species correlated well with the growth form of the species and the degree of its clonality. Clonally-growing species tended to have high clumping at distances of a few cells, whereas rosette species often did not show any clumping. The type of clonal growth (compact vs. long spacers) is well corrlated, with the temporal correlogram (species mobility). There is a relation between low mobility and high clumping at low distances. Attempts to explain the mechanisms of species coexistence in these grasslands should take into account the particular structure of the fine-scale dynamics of these communities of predominantly clonal plants. *** DIRECT SUPPORT *** A02DO006 00007     

Robustness to thermal variability differs along a latitudinal gradient in zooplankton communities

Determining how thermal variability will affect the structure, stability, and function of ecological communities is becoming increasingly important as global warming is predicted to affect not only average temperatures but also increase the frequency of long runs of high temperatures. Latitudinal differences in the responses of ecological communities to changes in their thermal regimes have also been predicted based on adaptations over evolutionary time to different thermal environments. We conducted an experiment to determine whether variability in temperature leads to consistent changes in community structure, temporal dynamics, and ecosystem functioning in laboratory analogues of natural freshwater supralittoral rock pool communities inhabited by meiofauna and zooplankton collected from sub‐Arctic, temperate, and tropical regions. Thermal variability of +4 °C around mean temperature led to increased extinction frequency, decreases in consumer abundance, increases in temporal variability of consumer abundance, and shifts from predominately negative interactions observed under constant temperature to positive interactions in the temperate and tropical communities but not in the sub‐Arctic communities. That sub‐Arctic zooplankton communities may be more robust to thermal variability than temperate or tropical communities’ supports recent studies on macrophysiological adaptations of species along latitudinal gradients and suggests that increasing thermal variability may have the greatest effects on community structure and function in tropical and temperate regions.     

Temporal variability in the diversity and composition of stream bacterioplankton communities

Bacterioplankton in freshwater streams play a critical role in stream nutrient cycling. Despite their ecological importance, the temporal variability in the structure of stream bacterioplankton communities remains understudied. We investigated the composition and temporal variability of stream bacterial communities and the influence of physicochemical parameters on these communities. We used barcoded pyrosequencing to survey bacterial communities in 107 streamwater samples collected from four locations in the Colorado Rocky Mountains from September 2008 to November 2009. The four sampled locations harboured distinct communities yet, at each sampling location, there was pronounced temporal variability in both community composition and alpha diversity levels. These temporal shifts in bacterioplankton community structure were not seasonal; rather, their diversity and composition appeared to be driven by intermittent changes in various streamwater biogeochemical conditions. Bacterial communities varied independently of time, as indicated by the observation that communities in samples collected close together in time were no more similar than those collected months apart. The temporal turnover in community composition was higher than observed in most previously studied microbial, plant or animal communities, highlighting the importance of stochastic processes and disturbance events in structuring these communities over time. Detailed temporal sampling is important if the objective is to monitor microbial community dynamics in pulsed ecosystems like streams.     

Effects of nonnative species on the stability of riverine fish communities

Despite the increasing ubiquity of biological invasions worldwide, little is known about the scale-dependent effects of nonnative species on real-world ecological dynamics. Here, using an extensive time series dataset of riverine fish communities across different biogeographic regions of the world, we assessed the effects of nonnative species on the temporal variability and synchrony in abundance at different organizational levels (population, metapopulation, community and metacommunity) and spatial scales (stream reach and river basin). At the reach scale, we found that populations of nonnative species were more variable over time than native species, and that this effect scaled up to the community level – significantly destabilizing the dynamics of riverine fish communities. Nonnative species not only contributed to reduced community stability, but also increased variability of native populations. By contrast, we found no effect of nonnative species dominance on local interspecific synchrony among native species. At the basin scale, nonnative metapopulations were again more variable than the native ones. However, neither native metapopulations nor metacommunities showed differences in temporal variability or synchrony as nonnative species dominance increased basin-wide. This suggests a ‘dilution effect’ where the contribution to regional stability of local native populations from sites displaying low levels of invasion reduced the destabilizing effects of nonnative species. Overall, our results indicate that accounting for the destabilizing effect of nonnative species is critical to understanding native species persistence and community stability.     

Inferring the Relative Resilience of Alternative States

Ecological systems may occur in alternative states that differ in ecological structures, functions and processes. Resilience is the measure of disturbance an ecological system can absorb before changing states. However, how the intrinsic structures and processes of systems that characterize their states affects their resilience remains unclear. We analyzed time series of phytoplankton communities at three sites in a floodplain in central Spain to assess the dominant frequencies or “temporal scales” in community dynamics and compared the patterns between a wet and a dry alternative state. The identified frequencies and cross-scale structures are expected to arise from positive feedbacks that are thought to reinforce processes in alternative states of ecological systems and regulate emergent phenomena such as resilience. Our analyses show a higher species richness and diversity but lower evenness in the dry state. Time series modeling revealed a decrease in the importance of short-term variability in the communities, suggesting that community dynamics slowed down in the dry relative to the wet state. The number of temporal scales at which community dynamics manifested, and the explanatory power of time series models, was lower in the dry state. The higher diversity, reduced number of temporal scales and the lower explanatory power of time series models suggest that species dynamics tended to be more stochastic in the dry state. From a resilience perspective our results highlight a paradox: increasing species richness may not necessarily enhance resilience. The loss of cross-scale structure (i.e. the lower number of temporal scales) in community dynamics across sites suggests that resilience erodes during drought. Phytoplankton communities in the dry state are therefore likely less resilient than in the wet state. Our case study demonstrates the potential of time series modeling to assess attributes that mediate resilience. The approach is useful for assessing resilience of alternative states across ecological and other complex systems.     

Effects of temporal variability of disturbance on the succession in marine fouling communities in northern-central Chile

We investigated the effects of temporal variability in a disturbance regime on fouling communities at two study sites in a northern-central Chilean bay. Fouling assemblages grown on artificial settlement substrata were disturbed by mechanical removal of biomass at different time intervals. Using one single disturbance frequency (10 disturbance events over 5 months) we applied 7 different temporal disturbance treatments: a constant disturbance regime (identical intervals between disturbance events), and 6 variable treatments where both variableness and sequences of intervals between disturbance events were manipulated. Two levels of temporal variableness (low and high, i.e. disturbance events were either dispersed or highly clumped in time) in the disturbance regime were applied by modifying the time intervals between subsequent disturbance events. To investigate the temporal coupling between disturbance events and other ecological processes (e.g. larval supply and recruitment intensity), three different sequences of disturbance intervals were nested in each of the two levels of temporal variableness. Species richness, evenness, total abundance, and structure of communities that experienced the various disturbance regimes were compared at the end of the experiment (15 days after the last disturbance event). Disturbance strongly influenced the community structure and led to a decrease in evenness and total abundance but not species richness. In undisturbed reference communities, the dominant competitor Pyura chilensis (Tunicata) occupied most available space while this species was suppressed in all disturbed treatments. Surprisingly, neither temporal variableness in the disturbance regime nor the sequence of intervals between disturbance events had an effect on community structure. Temporal variability in high disturbance regimes may be of minor importance for fouling communities, because they are dominated by opportunistic species that are adapted to rapidly exploit available space.     

The influence of habitat heterogeneity on freshwater bacterial community composition and dynamics

Multiple forces structure natural microbial communities, but the relative roles and interactions of these drivers are poorly understood. Gradients of physical and chemical parameters can be especially influential. In traditional ecological theory, variability in environmental conditions across space and time represents habitat heterogeneity, which may shape communities. Here we used aquatic microbial communities as a model to investigate the relationship between habitat heterogeneity and community composition and dynamics. We defined spatial habitat heterogeneity as vertical temperature and dissolved oxygen (DO) gradients in the water column, and temporal habitat heterogeneity as variation throughout the open-water season in these environmental parameters. Seasonal lake mixing events contribute to temporal habitat heterogeneity by destroying and re-creating these gradients. Because of this, we selected three lakes along a range of annual mixing frequency (polymictic, dimictic, meromictic) for our study. We found that bacterial community composition (BCC) was distinct between the epilimnion and hypolimnion within stratified lakes, and also more variable within the epilimnia through time. We found stark differences in patterns of epilimnion and hypolimnion dynamics over time and across lakes, suggesting that specific drivers have distinct relative importance for each community.     

Habitat heterogeneity and disturbance influence patterns of community temporal variability in a small temperate stream

Both habitat heterogeneity and disturbance can profoundly influence ecological systems at many levels of biological and ecological organization. However, the joint influences of heterogeneity and disturbance on temporal variability in communities have received little attention despite the intense homogenizing influence of human activity. I performed a field manipulation of substrate heterogeneity in a small New England stream, and measured changes in benthic macroinvertebrate communities for 100 days—a period that included both a severe drought and a flood. Generally, community variability decreased with increasing substrate heterogeneity. However, within sampling intervals, this relationship tended to fluctuate through time, apparently tracking changes in hydrology. At the beginning of the experiment, community temporal variability clearly decreased along a gradient of increasing substrate heterogeneity—a result consistent with an observational study performed the previous year. During the subsequent weeks, droughts and flooding created exceptionally high variability in both hydrology and benthic macroinvertebrate community structure resulting in the disappearance of this relationship. However, during the last weeks of the experiment when hydrologic conditions were relatively more stable, the negatively sloped relationship between community temporal variability and habitat heterogeneity reemerged and mimicked relationships observed both early in the experiment and in the previous year’s study. High habitat heterogeneity may promote temporal stability through several mechanisms including stabilization of resources and increased refugia from minor disturbances or predation. However, the results of this experiment suggest that severe disturbance events can create large-scale environmental variability that effectively swamps the influence of habitat heterogeneity, illustrating that a thorough understanding of community temporal variability in natural systems will necessarily consider sources of environmental variability at multiple spatial and temporal scales. Handling editor: L. M. Bini     

Hierarchical Dynamics of Ecological Communities: Do Scales of Space and Time Match?

Theory posits that community dynamics organize at distinct hierarchical scales of space and time, and that the spatial and temporal patterns at each scale are commensurate. Here we use time series modeling to investigate fluctuation frequencies of species groups within invertebrate metacommunities in 26 boreal lakes over a 20-year period, and variance partitioning analysis to study whether species groups with different fluctuation patterns show spatial signals that are commensurate with the scale-specific fluctuation patterns identified. We identified two groups of invertebrates representing hierarchically organized temporal dynamics: one species group showed temporal variability at decadal scales (slow patterns of change), whilst another group showed fluctuations at 3 to 5-year intervals (faster change). This pattern was consistently found across all lakes studied. A spatial signal was evident in the slow but not faster-changing species groups. As expected, the spatial signal for the slow-changing group coincided with broad-scale spatial patterns that could be explained with historical biogeography (ecoregion delineation, and dispersal limitation assessed through a dispersal trait analysis). In addition to spatial factors, the slow-changing groups correlated with environmental variables, supporting the conjecture that boreal lakes are undergoing environmental change. Taken together our results suggest that regionally distinct sets of taxa, separated by biogeographical boundaries, responded similarly to broad-scale environmental change. Not only does our approach allow testing theory about hierarchically structured space-time patterns; more generally, it allows assessing the relative role of the ability of communities to track environmental change and dispersal constraints limiting community structure and biodiversity at macroecological scales.     

Spatio-temporal community structure of peat bog benthic desmids on a microscale

Significant spatial variation in species composition of microphytobenthos often occurs at scales of decimetres. This microscale variation is typically more connected with dispersal-related events than to environmental factors. In this study, 4 microscale transects were delimited at 4 temperate lowland peat bog localities to investigate spatial and temporal microscale variations in benthic desmids (Desmidiales, Viridiplantae). Significant spatial autocorrelation was detected in most of the transects taken 3 times, in September and December 2010 and March 2011. The relative abundance of species data produced more pronounced spatial patterns than the presence?Cabsence data. Spatial autocorrelation mostly decreased during the winter period, possibly due to meteorological disturbances, resulting in less spatially structured phytobenthic community in the March transects. In most cases, spatial distance accounted for a significant part of the variation in a community structure, even in analyses that controlled for the effects of environmental and temporal factors. This indicated that pure spatial factors should be considered important for structuring phytobenthic communities, even across a temporal time span of 6?months. The reduced data sets that included only 25?% of the most frequented species produced very similar patterns in spatial and temporal autocorrelation as the full data sets. Consequently, we concluded that microscale variation of benthic desmids may be sufficiently represented by dynamics of the common species.     

Temporal dynamics of bird community composition: an analysis of baseline conditions from long-term data

Numerous anthropogenic activities threaten the biodiversity found on earth. Because all ecological communities constantly experience temporal turnover due to natural processes, it is important to distinguish between change due to anthropogenic impact and the underlying natural rate of change. In this study, we used data sets on breeding bird communities that covered at least 20 consecutive years, from a variety of terrestrial ecosystems, to address two main questions. (1) How fast does the composition of bird communities change over time, and can we identify a baseline of natural change that distinguishes primeval systems from systems experiencing varying degrees of human impact? (2) How do patterns of temporal variation in composition vary among bird communities in ecosystems with different anthropogenic impacts? Time lag analysis (TLA) showed a pattern of increasing rate of temporal compositional change from large-scale primeval systems to disturbed and protected systems to distinctly successional systems. TLA slopes of <0.04 were typical for breeding bird communities with natural turnover, while communities subjected to anthropogenic impact were characterised by TLA slopes of >0.04. Most of the temporal variability of breeding bird communities was explained by slow changes occurring over decades, regardless of the intensity of human impact. In most of the time series, medium- and short-wave periodicity was not detected, with the exception of breeding bird communities subjected to periodic pulses (e.g. caterpillar outbreaks causing food resource peaks).     

Trophic interactions affect the population dynamics and risk of extinction of basal species in food webs

This paper addresses effects of trophic complexity on basal species, in a Lotka–Volterra model with stochasticity. We use simple food web modules, with three trophic levels, and expose every species to random environmental stochasticity and analyze (1) the effect of the position of strong trophic interactions on temporal fluctuations in basal species’ abundances and (2) the relationship between fluctuation patterns and extinction risk. First, the numerical simulations showed that basal species do not simply track the environment, i.e. species dynamics do not simply mirror the characteristics of the applied environmental stochasticity. Second, the extinction risk of species was related to the fluctuation patterns of the species.More specifically, we show (i) that despite being forced by random stochasticity without temporal autocorrelation (i.e. white noise), there is significant temporal autocorrelation in the time series of all basal species’ abundances (i.e. the spectra of basal species are red-shifted), (ii) the degree of temporal autocorrelation in basal species time series is affected by food web structure and (iii) the degree of temporal autocorrelation tend to be correlated to the extinction risks of basal species.Our results emphasize the role of food web structure and species interactions in modifying the response of species to environmental variability. To shed some light on the mechanisms we compare the observed pattern in abundances of basal species with analytically predicted patterns and show that the change in the predicted pattern due to the addition of strong trophic interactions is correlated to the extinction risk of the basal species. We conclude that much remain to be understood about the mechanisms behind the interaction among environmental variability, species interactions, population dynamics and vulnerability before we quantitatively can predict, for example, effects of climate change on species and ecological communities. Here, however, we point out a new possible approach for identifying species that are vulnerable to environmental stochasticity by checking the degree of temporal autocorrelation in the time series of species. Increased autocorrelation in population fluctuations can be an indication of increased extinction risk.     

Towards understanding the organisation of metacommunities in highly dynamic ecological systems

Community ecology recognises today that local biological communities are not only affected by local biotic interactions and abiotic environmental conditions, but also by regional processes (e.g. dispersal). While much is known about how metacommunities are organised in space in terrestrial, marine and freshwater ecological systems, their temporal variations remain poorly studied. Here, we address the question of the dynamics of metacommunities in highly variable systems, using intermittent rivers (IRs), those rivers which temporarily stop flowing or dry up, as a model system. We first review how habitat heterogeneity in space and time influences metacommunity organisation. Second, we compare the metacommunities in IRs to those in perennial rivers (PRs) and develop the idea that IRs could undergo highly dynamic shifts due to the temporal variability in local and regional community processes. Third, we develop the idea that in IRs, metacommunities of the wet and dry phases of IRs are closely intertwined, thereby increasing even more their respective temporal dynamics. Last, we provide a roadmap to stimulate further conceptual and empirical developments of metacommunity research and identify possible applications for improving the management of IRs and other highly dynamic ecological systems. Synthesis Extensive research has examined the importance of local biotic interactions, environmental filtering, and regional processes on community assembly. Movement of organisms between sites, i.e. dispersal, is a major set of processes within this framework. However, subsequent metacommunity organisation also varies over time in ecosystems because habitat characteristics such as configuration and composition continuously shift. Intermittent rivers are an ideal set of systems to examine these ideas because these freshwater systems temporarily cease flowing thereby limiting dispersal events. We proposed the hypothesis that metacommunities in dynamic ecosystems will undergo frequent shifts in structure and composition in response to the temporal variability in environmental filtering and dispersal. In addition to providing a roadmap for developing a more dynamic perspective for community ecology, these framework provides direct insights for the management of intermittent rivers.     

Bacterial Succession on the Leaf Surface: A Novel System for Studying Successional Dynamics

Succession is a widely studied process in plant and animal systems, but succession in microbial communities has received relatively little attention despite the ubiquity of microorganisms in natural habitats. One important microbial habitat is the phyllosphere, or leaf surface, which harbors large, diverse populations of bacteria and offers unique opportunities for the study of succession and temporal community assembly patterns. To explore bacterial community successional patterns, we sampled phyllosphere communities on cottonwood (Populus deltoides) trees multiple times across the growing season, from leaf emergence to leaf fall. Bacterial community composition was highly variable throughout the growing season; leaves sampled as little as a week apart were found to harbor significantly different communities, and the temporal variability on a given tree exceeded the variability in community composition between individual trees sampled on a given day. The bacterial communities clearly clustered into early-, mid-, and late-season clusters, with early- and late-season communities being more similar to each other than to the mid-season communities, and these patterns appeared consistent from year to year. Although we observed clear and predictable changes in bacterial community composition during the course of the growing season, changes in phyllosphere bacterial diversity were less predictable. We examined the species–time relationship, a measure of species turnover rate, and found that the relationship was fundamentally similar to that observed in plant and invertebrate communities, just on a shorter time scale. The temporal dynamics we observed suggest that although phyllosphere bacterial communities have high levels of phylogenetic diversity and rapid turnover rates, these communities follow predictable successional patterns from season to season.     

Time-series forecasting offers novel quantitative measure to assess loud sound event in an urban park with restored prairie

Soundscape ecology and ecoacoustics study the spatiotemporal dynamics of a soundscape and how the dynamics reflect and influence ecological processes in the environment. Soundscape analysis methods employ acoustic recording units (ARUs) that collect acoustic data in study areas over time. Analyzing these data includes computation of several acoustic diversity indices developed to quantify species abundance, richness, or habitat condition through digital audio processing and algorithm adaptations for within-group populations. However, the success of specific indices is often dependent on habitat type and biota richness present and analyzing these data can be challenging due to temporal pseudo-replication. Time-series analytical methods address the inherent problems of temporal autocorrelation for soundscape analyses challenges. Animal population dynamics fluctuate in a variety of ways due to changes in habitat or natural patterns of a landscape and chronic noise exposure, with soundscape phenology patterns evident in terrestrial and aquatic environments. Historical phenological soundscape patterns have been used to predict expected soundscape patterns in long-term studies but limited work has explored how forecasting can quantify changes in short-term studies. We evaluate how forecasting from an acoustic index can be used to quantify change in an acoustic community response to a loud, acute noise. We found that the acoustic community of a Midwestern restored prairie had decreased acoustic community activity after a loud sound event (LSE), a Civil War Reenactment, mainly driven by observed changes in the bird community and quantified using two methods: an automated acoustic index and species richness. Time-series forecasting maybe considered an underutilized tool in analyzing acoustic data whose experimental design can be flawed with temporal autocorrelation. Forecasting using auto ARIMA with acoustic indices could benefit decision makers who consider ecological questions at different time scales.     

Species richness–variability relationships in multi-trophic aquatic microcosms

While species loss may affect the temporal variability of populations and communities differently in multi- versus single-trophic level communities, the nature of these differences are poorly understood. Here, we report on an experiment where we manipulated species richness of multi-trophic rock pool invertebrate communities to determine the effects of species richness, S, on the temporal variability of communities, populations, and individual species. As in single-trophic level studies, temporal variability in community abundance decreased with increasing species richness. However, in contrast to most studies in single-trophic level systems, temporal variability of populations also decreased as species richness increased. Furthermore, the variability of the constituent populations strongly correlated with variability of community abundance suggesting that, in rock pools, S affects community variability through its stabilizing effect on component populations. Our results suggest that species loss may affect population and community variability differently in multi-trophic versus single trophic level communities. If this is so, then the mechanisms proposed to underlie the effects of S on community variability in single-trophic communities may have to be supplemented by those that describe contributions to population stability in order to fully describe the patterns observed in multi-trophic communities.     

Spatio-temporal variation in Markov chain models of subtidal community succession

In this paper we ask whether succession in a rocky subtidal community varies in space and time, and if so how much affect that variation has on predictions of community dynamics and structure. We describe succession by Markov chain models based on observed frequencies of species replacements. We use loglinear analysis to detect and quantify spatio‐temporal variation in the transition matrices describing succession. The analysis shows that space and time, but not their interaction, have highly significant effects on transition probabilities. To explore the ecological importance of the spatio‐temporal variability detected in this analysis, we compare the equilibria and the transient dynamics among three Markov chain models: a time‐averaged model that includes the effects of space on succession, a spatially averaged model that include the effects of time, and a constant matrix that averages over the effects of space and time. All three models predicted similar equilibrium composition and similar rates of convergence to equilibrium, as measured by the damping ratio or the subdominant Lyapunov exponent. The predicted equilibria from all three models were very similar to the observed community structure. Thus, although spatial and temporal variation is statistically significant, at least in this system this variation does not prevent homogeneous models from predicting community structure.     

Can temporal covariation and autocorrelation in demographic rates affect population dynamics in a raptor species?

Theoretical studies suggest that temporal covariation among and temporal autocorrelation within demographic rates are important features of population dynamics. Yet, empirical studies have rarely focused on temporal covariation and autocorrelation limiting our understanding of these patterns in natural populations. This lack of knowledge restrains our ability to fully understand population dynamics and to make reliable population forecasts. In order to fill this gap, we used a long‐term monitoring (15 years) of a kestrel Falco tinnunculus population to investigate covariation and autocorrelation in survival and reproduction at the population level and their impact on population dynamics. Using Bayesian joint analyses, we found support for positive covariation between survival and reproduction, but weak autocorrelation through time. This positive covariation was stronger in juveniles compared with adults. As expected for a specialized predator, we found that the reproductive performance was strongly related to an index of vole abundance explaining 86% of the temporal variation. This very strong relationship suggests that the temporally variable prey abundance may drive the positive covariation between survival and reproduction in this kestrel population. Simulations suggested that the observed effect size of covariation could be strong enough to affect population dynamics. More generally, positive covariation and autocorrelation have a destabilizing effect increasing substantially the temporal variability of population size.