Population Synchrony Research Articles

California steelhead populations were regionally buffered and individually resistant to a severe multi-year drought

Weather extremes, such as drought, are predicted to be a strong determinant of species persistence under climate change. Yet predictions often fail to consider that variation in streamflow responses, variation in population dynamics, or adaptations to drought could buffer species against extremes. In this study, we examined the responses of eight California (USA) steelhead populations to a severe drought from 2012 to 2016. We observed that streamflows were highly synchronous across the region in all seasons and did not appear to buffer drought impacts. Population dynamics were variable across the region and did appear to buffer the region from drought impacts. Some populations had very low productivity for 4 years associated with the drought, while others had slightly below-average productivity for only 2 years. Population synchrony was associated with spring-smolt flow, temperature, and drought over time, but was not associated with winter-spawner or summer-juvenile drought, suggesting populations may be adapted to drought conditions. Our results highlight how regional buffering and adaptation can be important mechanisms against climate extremes both now and into the future.

STOCHASTICITY, SCALE, AND REFRACTION: DETERMINANTS OF POPULATION SYNCHRONY IN PARASITES OF CENTRARCHIDS IN J. STROM THURMOND LAKE, SOUTH CAROLINA.

Among-deme asynchrony has the potential to influence community richness and diversity by increasing the likelihood of regional persistence for a species. Parasites of Lepomis spp. collected from 4 localities at J. Strom Thurmond Lake, South Carolina over a 1-yr period were used to evaluate patterns of parasite population synchrony. Localities were separated by approximately 5 km to increase the likelihood that the parasites sampled represented different demes. Tylodelphys scheuringi and Crinicleidus longus, exhibited negative covariation between synchrony and among-locality distances. The degree of synchrony exhibited by Neoechinorhynchus cylindratis, Crepidostomum cornutum, and Clavunculus bifurcatus was associated with the degree of similarity in habitat structure between localities. Patterns of synchrony for Posthodiplostomum minimum and Spinitectus sp. were not associated with any of the habitat variables examined. The influence of habitat structure on parasite population synchrony, possibly through the refraction of large-scale environmental drivers, has the potential to produce asynchronous dynamics that are independent of the distance between demes, thereby promoting regional persistence by increasing the likelihood of rescue effects.

A unified quantification of synchrony in globally coupled populations with the Wiener order parameter.

We tackle the quantification of synchrony in globally coupled populations. Furthermore, we treat the problem of incomplete observations when the population mean field is unavailable, but only a small subset of units is observed. We introduce a new order parameter based on the integral of the squared autocorrelation function and demonstrate its efficiency for quantifying synchrony via monitoring general observables, regardless of whether the oscillations can be characterized in terms of the phases. Under condition of a significant irregularity in the dynamics of the coupled units, this order parameter provides a unified description of synchrony in populations of units of various complexities. The main examples include noise-induced oscillations, coupled strongly chaotic systems, and noisy periodic oscillations. Furthermore, we explore how this parameter works for the standard Kuramoto model of coupled regular-phase oscillators. The most significant advantage of our approach is its ability to infer and quantify synchrony from the observation of a small percentage of the units and even from a single unit, provided the observations are sufficiently long.

Interaction of acetylcholine and oxytocin neuromodulation in the hippocampus

A postulated role of subcortical neuromodulators is to control brain states. Mechanisms by which different neuromodulators compete or cooperate at various temporal scales remain an open question. We investigated the interaction of acetylcholine (ACh) and oxytocin (OXT) at slow and fast timescales during various brain states. Although these neuromodulators fluctuated in parallel during NREM packets, transitions from NREM to REM were characterized by a surge of ACh but a continued decrease of OXT. OXT signaling lagged behind ACh. High ACh was correlated with population synchrony and gamma oscillations during active waking, whereas minimum ACh predicts sharp-wave ripples (SPW-Rs). Optogenetic control of ACh and OXT neurons confirmed the active role of these neuromodulators in the observed correlations. Synchronous hippocampal activity consistently reduced OXT activity, whereas inactivation of the lateral septum-hypothalamus path attenuated this effect. Our findings demonstrate how cooperative actions of these neuromodulators allow target circuits to perform specific functions.

Dispersal synchronizes giant kelp forests.

Spatial synchrony is the tendency for population fluctuations to be correlated among different locations. This phenomenon is a ubiquitous feature of population dynamics and is important for ecosystem stability, but several aspects of synchrony remain unresolved. In particular, the extent to which any particular mechanism, such as dispersal, contributes to observed synchrony in natural populations has been difficult to determine. To address this gap, we leveraged recent methodological improvements to determine how dispersal structures synchrony in giant kelp (Macrocystis pyrifera), a global marine foundation species that has served as a useful system for understanding synchrony. We quantified population synchrony and fecundity with satellite imagery across 11 years and 880 km of coastline in southern California, USA, and estimated propagule dispersal probabilities using a high-resolution ocean circulation model. Using matrix regression models that control for the influence of geographic distance, resources (seawater nitrate), and disturbance (destructive waves), we discovered that dispersal was an important driver of synchrony. Our findings were robust to assumptions about propagule mortality during dispersal and consistent between two metrics of dispersal: (1) the individual probability of dispersal and (2) estimates of demographic connectivity that incorporate fecundity (the number of propagules dispersing). We also found that dispersal and environmental conditions resulted in geographic clusters with distinct patterns of synchrony. This study is among the few to statistically associate synchrony with dispersal in a natural population and the first to do so in a marine organism. The synchronizing effects of dispersal and environmental conditions on foundation species, such as giant kelp, likely have cascading effects on the spatial stability of biodiversity and ecosystem function.

Stabilizing effects of spatially heterogeneous disturbance via reduced spatial synchrony on a rocky shore community.

Understanding how synchronous species fluctuations affect community stability is a main research topic in ecology. Yet experimental studies evaluating how changes in disturbance regimes affect the synchrony and stability of populations and communities remain rare. We hypothesized that spatially heterogeneous disturbances of moderate intensity would promote metacommunity stability by decreasing the spatial synchrony of species fluctuations. To test this hypothesis, we exposed rocky shore communities of algae and invertebrates to homogeneous and gradient-like spatial patterns of disturbance at two levels of intensity for 4 years and used synchrony networks to characterize community responses to these disturbances. The gradient-like disturbance at low intensity enhanced spatial β diversity compared to the other treatments and produced the most heterogeneous and least synchronized network, which was also the most stable in terms of population and community fluctuations. In contrast, homogeneous disturbance destabilized the community, enhancing spatial synchronization. Intense disturbances always reduced spatial β diversity, indicating that strong perturbations could destabilize communities via biotic homogenization regardless of their spatial structure. Our findings corroborated theoretical predictions, emphasizing the importance of spatially heterogeneous disturbances in promoting stability by amplifying asynchronous spatial and temporal fluctuations in population and community abundance. In contrast to other networks, synchrony networks are vulnerable to the removal of most peripheral nodes, which are less synchronized, but may contribute more to stability than other nodes by dampening large fluctuations in species abundance. Our findings suggest that climate change and direct anthropogenic disturbance can compromise the stability of ecological communities through combined effects on diversity and synchrony, as well as further affecting ecosystems through habitat loss.

Understanding temporal variability across trophic levels and spatial scales in freshwater ecosystems.

A tenet of ecology is that temporal variability in ecological structure and processes tends to decrease with increasing spatial scales (from locales to regions) and levels of biological organization (from populations to communities). However, patterns in temporal variability across trophic levels and the mechanisms that produce them remain poorly understood. Here we analyzed the abundance time series of spatially structured communities (i.e., metacommunities) spanning basal resources to top predators from 355 freshwater sites across three continents. Specifically, we used a hierarchical partitioning method to disentangle the propagation of temporal variability in abundance across spatial scales and trophic levels. We then used structural equation modeling to determine if the strength and direction of relationships between temporal variability, synchrony, biodiversity, and environmental and spatial settings depended on trophic level and spatial scale. We found that temporal variability in abundance decreased from producers to tertiary consumers but did so mainly at the local scale. Species population synchrony within sites increased with trophic level, whereas synchrony among communities decreased. At the local scale, temporal variability in precipitation and species diversity were associated with population variability (linear partial coefficient, β = 0.23) and population synchrony (β = -0.39) similarly across trophic levels, respectively. At the regional scale, community synchrony was not related to climatic or spatial predictors, but the strength of relationships between metacommunity variability and community synchrony decreased systematically from top predators (β = 0.73) to secondary consumers (β = 0.54), to primary consumers (β = 0.30) to producers (β = 0). Our results suggest that mobile predators may often stabilize metacommunities by buffering variability that originates at the base of food webs. This finding illustrates that the trophic structure of metacommunities, which integrates variation in organismal body size and its correlates, should be considered when investigating ecological stability in natural systems. More broadly, our work advances the notion that temporal stability is an emergent property of ecosystems that may be threatened in complex ways by biodiversity loss and habitat fragmentation.

Spatial asynchrony and cross-scale climate interactions in populations of a coldwater stream fish.

Climate change affects populations over broad geographic ranges due to spatially autocorrelated abiotic conditions known as the Moran effect. However, populations do not always respond to broad-scale environmental changes synchronously across a landscape. We combined multiple datasets for a retrospective analysis of time-series count data (5-28 annual samples per segment) at 144 stream segments dispersed over nearly 1,000 linear kilometers of range to characterize the population structure and scale of spatial synchrony across the southern native range of a coldwater stream fish (brook trout, Salvelinus fontinalis), which is sensitive to stream temperature and flow variations. Spatial synchrony differed by life stage and geographic region: it was stronger in the juvenile life stage than in the adult life stage and in the northern sub-region than in the southern sub-region. Spatial synchrony of trout populations extended to 100-200 km but was much weaker than that of climate variables such as temperature, precipitation, and stream flow. Early life stage abundance changed over time due to annual variation in summer temperature and winter and spring stream flow conditions. Climate effects on abundance differed between sub-regions and among local populations within sub-regions, indicating multiple cross-scale interactions where climate interacted with local habitat to generate only a modest pattern of population synchrony over space. Overall, our analysis showed higher degrees of response heterogeneity of local populations to climate variation and consequently population asynchrony than previously shown based on analysis of individual, geographically restricted datasets. This response heterogeneity indicates that certain local segments characterized by population asynchrony and resistance to climate variation could represent unique populations of this iconic native coldwater fish that warrant targeted conservation. Advancing the conservation of this species can include actions that identify such priority populations and incorporate them into landscape-level conservation planning. Our approach is applicable to other widespread aquatic species sensitive to climate change.

Intraspecific variation in fruit production of African mahogany (Khaya anthotheca) in a semi‐deciduous East African rainforest

AbstractRestoring valuable timber trees is a necessary part of regaining many ecosystem services and products provided by degraded tropical forests. However, knowledge of seed production, a regeneration prerequisite, is limited for many tropical timber tree species. We studied the fruit production of African mahogany (Khaya anthotheca) in a semi‐deciduous rainforest in East Africa, to provide information for ecological restoration programs. First, we quantified population variability and synchrony in fruit production. Then, we assessed how reproductive status and output were influenced by tree size, neighbourhood crowding, exchangeable cations, liana presence, and crown exposure. We found fruit production at the population level was weakly synchronised, with high interannual variability at the population and individual levels. Tree size determined reproductive status. Individual quantity of fruit produced increased with tree size but decreased with neighbourhood crowding. Our results indicate that K. anthotheca does not meet the criteria for mast fruiting. Our findings suggest that reproductive output in mahogany is regulated by tree size and competition. In addition to active protection, thinning to reduce competition around seed trees may boost fruit production at the individual tree level to provide seed for forest enrichment.

The role of seasonal migration in spatial population synchrony.

Spatially synchronized population dynamics are common in nature, and understanding their causes is key for predicting species persistence. A main driver of synchrony between populations of the same species is shared environmental conditions, which cause populations closer together in space to be more synchronized than populations further from one another. Most theoretical and empirical understanding of this driver considers resident species. For migratory species, however, the degree of spatial autocorrelation in the environment may change across seasons and vary by their geographic location along the migratory route or on a nonbreeding ground, complicating the synchronizing effect of the environment. Migratory species show a variety of different strategies in how they disperse to and aggregate on nonbreeding grounds, ranging from completely shared nonbreeding grounds to multiple different ones. Depending on the sensitivity to environmental conditions off the breeding grounds, we can expect that migration and overwintering strategies will impact the extent and spatial pattern of population synchrony on the breeding grounds. Here, we use spatial population-dynamic modeling and simulations to investigate the relationship between seasonal environmental autocorrelation and migration characteristics. Our model shows that the effects of environmental autocorrelation experienced off the breeding ground on population synchrony depend on the number and size of nonbreeding grounds, and how populations migrate in relation to neighboring populations. When populations migrated to multiple nonbreeding grounds, spatial population synchrony increased with increasing environmental autocorrelation between nonbreeding grounds. Populations that migrated to the same place as near neighbors had higher synchrony at short distances than populations that migrated randomly. However, synchrony declined less across increasing distances for the random migration strategy. The differences in synchrony between migration strategies were most pronounced when the environmental autocorrelation between nonbreeding grounds was low. These results show the importance of considering migration when studying spatial population synchrony and predicting patterns of synchrony and population viability under global environmental change. Climate change and habitat loss and fragmentation may cause range shifts and changes in migratory strategies, as well as changes in the mean and spatial autocorrelation of the environment, which can alter the scale and patterns observed in spatial population synchrony.

Effects of local density dependence and temperature on the spatial synchrony of marine fish populations.

Disentangling empirically the many processes affecting spatial population synchrony is a challenge in population ecology. Two processes that could have major effects on the spatial synchrony of wild population dynamics are density dependence and variation in environmental conditions like temperature. Understanding these effects is crucial for predicting the effects of climate change on local and regional population dynamics. We quantified the direct contribution of local temperature and density dependence to spatial synchrony in the population dynamics of nine fish species inhabiting the Barents Sea. First, we estimated the degree to which the annual spatial autocorrelations in density are influenced by temperature. Second, we estimated and mapped the local effects of temperature and strength of density dependence on annual changes in density. Finally, we measured the relative effects of temperature and density dependence on the spatial synchrony in changes in density. Temperature influenced the annual spatial autocorrelation in density more in species with greater affinities to the benthos and to warmer waters. Temperature correlated positively with changes in density in the eastern Barents Sea for most species. Temperature had a weak synchronizing effect on density dynamics, while increasing strength of density dependence consistently desynchronised the dynamics. Quantifying the relative effects of different processes affecting population synchrony is important to better predict how population dynamics might change when environmental conditions change. Here, high degrees of spatial synchrony in the population dynamics remained unexplained by local temperature and density dependence, confirming the presence of additional synchronizing drivers, such as trophic interactions or harvesting.

How environmental drivers of spatial synchrony interact

Spatial synchrony, the tendency for populations across space to show correlated fluctuations, is a fundamental feature of population dynamics, linked to central topics of ecology such as population cycling, extinction risk, and ecosystem stability. A common mechanism of spatial synchrony is the Moran effect, whereby spatially synchronized environmental signals drive population dynamics and hence induce population synchrony. After reviewing recent progress in understanding Moran effects, we here elaborate a general theory of how Moran effects of different environmental drivers acting on the same populations can interact, either synergistically or destructively, to produce either substantially more or markedly less population synchrony than would otherwise occur. We provide intuition for how this newly recognized mechanism works through theoretical case studies and application of our theory to California populations of giant kelp. We argue that Moran interactions should be common. Our theory and analysis explain an important new aspect of a fundamental feature of spatiotemporal population dynamics.

Spatially varying plankton synchrony patterns at seasonal and interannual scales in a well‐connected shelf sea

AbstractSpatial population synchrony, defined as spatial covariation in population density fluctuations, exists across different temporal and spatial scales. Determining the degree of spatial synchrony is useful for inferring environmental drivers of population variability in the wake of climate change. In this study, we applied novel statistical methods to detect spatial synchrony patterns of Calanus finmarchicus on the Northeast U.S. Shelf at multiple spatiotemporal scales using unevenly distributed data. Our results reveal that C. finmarchicus subpopulations connected by advection are not necessarily in synchrony, indicating that the degree of synchrony is likely influenced by heterogeneity of local habitats. In addition, regionally synchronous environmental conditions (e.g., sea surface temperature) may not play as significant a role in influencing subregional population dynamics as was previously hypothesized. Overlooking the spatial heterogeneity of synchronous patterns at different time scales could lead to erroneous inferences of potential environmental drivers responsible for C. finmarchicus variability.

Trophic interactions between primary consumers appear to weaken during periods of synchrony

Our understanding of synchrony between populations from different taxonomic groups has been centered on predator–prey dynamics in simple systems but has rarely been examined in complex predator–prey systems. In addition to trophic interactions such as predator–prey dynamics, there is some evidence that exogenous factor such as climatic variation may facilitate synchrony between different taxonomic groups. Using three longitudinal datasets on quail (Colinus virginianus) and cotton rats (Sigmodon hispidus) we examined 1) the consistency of synchrony across time and space, 2) the relative influence of trophic interactions vs. exogenous factors on synchrony and 3) if trophic interactions were positively associated with synchrony between populations. We found evidence of consistent synchrony in cotton rat and bobwhite populations at both the site and regional levels. We found that trophic interactions between cotton rats and bobwhite were associated with relative synchrony between these populations, but these interactions appeared to weaken in years of greater synchrony. We did not find evidence that exogenous factors influenced relative synchrony at the regional level. Given the lack of a clear mechanistic explanation of the patterns observed in our data, we propose an alternative climate-mediated predation framework to explain synchrony in complex predator–prey systems. This framework includes both classic bottom-up theories of regulation while integrating trophic interactions via components of the shared predator hypothesis.

Generation time and seasonal migration explain variation in spatial population synchrony across European bird species.

Spatial population synchrony is common among populations of the same species and is an important predictor of extinction risk. Despite the potential consequences for metapopulation persistence, we still largely lack understanding of what makes one species more likely to be synchronized than another given the same environmental conditions. Generally, environmental conditions in a shared environment or a species' sensitivity to the environment can explain the extent of synchrony. Populations that are closer together experience more similar fluctuations in their environments than those populations that are further apart and are therefore more synchronized. The relative importance of environmental and demographic stochasticity for population dynamics is strongly linked to species' life-history traits, such as pace of life, which may impact population synchrony. For populations that migrate, there may be multiple environmental conditions at different locations driving synchrony. However, the importance of life history and migration tactics in determining patterns of spatial population synchrony have rarely been explored empirically. We therefore hypothesize that increasing generation time, a proxy for pace of life, would decrease spatial population synchrony and that migrants would be less synchronized than resident species. We used population abundance data on breeding birds from four countries to investigate patterns of spatial population synchrony in growth rate and abundance. We calculated the mean spatial population synchrony between log-transformed population growth rates or log-transformed abundances for each species and country separately. We investigated differences in synchrony across generation times in resident (n = 67), short-distance migrant (n = 86) and long-distance migrant (n = 39) bird species. Species with shorter generation times were more synchronized than species with longer generation times. Short-distance migrants were more synchronized than long-distance migrants and resident birds. Our results provide novel empirical links between spatial population synchrony and species traits known to be of key importance for population dynamics, generation time and migration tactics. We show how these different mechanisms can be combined to understand species-specific causes of spatial population synchrony. Understanding these specific drivers of spatial population synchrony is important in the face of increasingly severe threats to biodiversity and could be key for successful future conservation outcomes.

Sleep-like changes in neural processing emerge during sleep deprivation in early auditory cortex.

Insufficient sleep is commonplace in modern lifestyle and can lead to grave outcomes, yet the changes in neuronal activity accumulating over hours of extended wakefulness remain poorly understood. Specifically, which aspects of cortical processing are affected by sleep deprivation (SD), and whether they also affect early sensory regions, remain unclear. Here, we recorded spiking activity in the rat auditory cortex along with polysomnography while presenting sounds during SD followed by recovery sleep. We found that frequency tuning, onset responses, and spontaneous firing rates were largely unaffected by SD. By contrast, SD decreased entrainment to rapid (≥20Hz) click trains, increased population synchrony, and increased the prevalence of sleep-like stimulus-induced silent periods, even when ongoing activity was similar. Recovery NREM sleep was associated with similar effects as SD with even greater magnitude, while auditory processing during REM sleep was similar to vigilant wakefulness. Our results show that processes akin to those in NREM sleep invade the activity of cortical circuits during SD, even in the early sensory cortex.

Spring arrival of the common cuckoo at breeding grounds is strongly determined by environmental conditions in tropical Africa.

Failure to adapt migration timing to changes in environmental conditions along migration routes and at breeding locations can result in mismatches across trophic levels, as occurs between the brood parasitic common cuckoo Cuculus canorus and its hosts. Using satellite tracking data from 87 male cuckoos across 11 years, we evaluate why the cuckoo has not advanced its arrival to the UK. Across years, breeding ground arrival was primarily determined by timing of departure from stopover in West Africa before northward crossing of the Sahara. Together with high population synchrony and low apparent endogenous control of this event, this suggests that a seasonal ecological constraint operating here limits overall variation in breeding grounds arrival, although this event was itself influenced by carry-over from timing of arrival into tropical Africa. Between-year variation within individuals was, in contrast, mostly determined by northward migration through Europe, probably due to weather conditions. We find evidence of increased mortality risk for (a) early birds following migration periods positively impacting breeding grounds arrival, and (b) late birds, possibly suffering energy limitation, after departure from the breeding grounds. These results help identify areas where demands of responding to global change can potentially be alleviated by improving stopover quality.

Bursting Dynamics of Spiking Neural Network Induced by Active Extracellular Medium

We propose a mathematical model of a spiking neural network (SNN) that interacts with an active extracellular field formed by the brain extracellular matrix (ECM). The SNN exhibits irregular spiking dynamics induced by a constant noise drive. Following neurobiological facts, neuronal firing leads to the production of the ECM that occupies the extracellular space. In turn, active components of the ECM can modulate neuronal signaling and synaptic transmission, for example, through the effect of so-called synaptic scaling. By simulating the model, we discovered that the ECM-mediated regulation of neuronal activity promotes spike grouping into quasi-synchronous population discharges called population bursts. We investigated how model parameters, particularly the strengths of ECM influence on synaptic transmission, may facilitate SNN bursting and increase the degree of neuronal population synchrony.

Population synchrony indicates functional connectivity in a threatened sedentary butterfly

Dispersal is a key influence on species’ persistence, particularly in the context of habitat fragmentation and environmental change. Previously, residual population synchrony has been demonstrated to be an effective proxy for dispersal in mobile butterflies (Powney et al. 2012). Here, we highlight the utility and limitations of population synchrony as an indicator of functional connectivity and persistence, at a range of spatial scales, in a specialist, sedentary butterfly. While at the local scale, population synchrony is likely indicative of dispersal in the pearl-bordered fritillary, Boloria euphrosyne, over larger scales, habitat is likely to influence population dynamics. Although declines in local-scale synchrony conformed to typical movement in this species, synchrony showed no significant trend with distance when studied at larger (between-site) scales. By focusing on specific site comparisons, we draw the conclusion that heterogeneity in habitat successional stage drives asynchrony between sites at larger distances and is, therefore, likely to be a more important driver of population dynamics over large distances than dispersal. Within-site assessments of synchrony highlight differences in dispersal based on habitat type, with movement shown to be most inhibited between transect sections with contrasting habitat permeability. While synchrony has implications for metapopulation stability and extinction risk, no significant difference was found in average site synchrony between sites that had gone extinct during the study period and those remaining occupied. We demonstrate that population synchrony may be used to assess local-scale movement between sedentary populations, as well as to understand barriers to dispersal and guide conservation management.

Blow-Up Dynamics and Synchronization in Tri-Trophic Food Chain Models

Synchronization of food chain models is an intensely investigated area in dynamical systems. Two pioneering models in three species food chain systems exhibiting chaotic dynamics are the Hastings and Powell (HP) model and the Upadhyay and Rai (UR) model. These are known to synchronize, even though the top predators in the two models behave differently. In the current manuscript, we show that although the HP and UR models synchronize for certain initial conditions, they do not synchronize for arbitrarily large initial conditions due to the blow-up dynamics present in the UR model. Thus, the synchronization of these model systems is purely a local (in initial data) phenomenon. Interestingly, we find that a similar result holds for the modified UR model as well, which has global in-time solutions for any positive initial condition. Thus, the lack of synchrony could also be attributed to the difference in the top predator’s feeding preferences in the model systems. Our results have large-scale applications to population synchrony in tri-trophic food chains.