Metapopulations with habitat modification.

Across the tree of life, organisms modify their local environment, rendering it more or less hospitable for other species. Despite the ubiquity of these processes, simple models that can be used to develop intuitions about the consequences of widespread habitat modification are lacking. Here, we extend the classic Levins metapopulation model to a setting where each of n species can colonize patches connected by dispersal, and when patches are vacated via local extinction, they retain a "memory" of the previous occupant-modeling habitat modification. While this model can exhibit a wide range of dynamics, we draw several overarching conclusions about the effects of modification and memory. In particular, we find that any number of species may potentially coexist, provided that each is at a disadvantage when colonizing patches vacated by a conspecific. This notion is made precise through a quantitative stability condition, which provides a way to unify and formalize existing conceptual models. We also show that when patch memory facilitates coexistence, it generically induces a positive relationship between diversity and robustness (tolerance of disturbance). Our simple model provides a portable, tractable framework for studying systems where species modify and react to a shared landscape.

Habitat Heterogeneity, Environmental Feedbacks, and Species Coexistence across Timescales.

AbstractClassic ecological theory explains species coexistence in variable environments. While spatial variation is often treated as an intrinsic feature of a landscape, it may be shaped and even generated by the resident community. All species modify their local environment to some extent, driving changes that can feed back to affect the composition and coexistence of the community, potentially over timescales very different from population dynamics. We introduce a simple nested modeling framework for community dynamics in heterogeneous environments, including the possible evolution of heterogeneity over time due to community-environment feedbacks. We use this model to derive analytical conditions for species coexistence in environments where heterogeneity is either fixed or shaped by feedbacks. Among other results, our approach reveals how dispersal and environmental specialization interact to shape realized patterns of habitat association and demonstrates that environmental feedbacks can tune landscape conditions to allow the stable coexistence of any number of species. Our flexible modeling framework helps explain feedback dynamics that arise in a wide range of ecosystems and offers a generic platform for exploring the interplay between species and landscape diversity.

Pathways to global-change effects on biodiversity: new opportunities for dynamically forecasting demography and species interactions.

In structured populations, persistence under environmental change may be particularly threatened when abiotic factors simultaneously negatively affect survival and reproduction of several life cycle stages, as opposed to a single stage. Such effects can then be exacerbated when species interactions generate reciprocal feedbacks between the demographic rates of the different species. Despite the importance of such demographic feedbacks, forecasts that account for them are limited as individual-based data on interacting species are perceived to be essential for such mechanistic forecasting-but are rarely available. Here, we first review the current shortcomings in assessing demographic feedbacks in population and community dynamics. We then present an overview of advances in statistical tools that provide an opportunity to leverage population-level data on abundances of multiple species to infer stage-specific demography. Lastly, we showcase a state-of-the-art Bayesian method to infer and project stage-specific survival and reproduction for several interacting species in a Mediterranean shrub community. This case study shows that climate change threatens populations most strongly by changing the interaction effects of conspecific and heterospecific neighbours on both juvenile and adult survival. Thus, the repurposing of multi-species abundance data for mechanistic forecasting can substantially improve our understanding of emerging threats on biodiversity.

Experimental evolution of dispersal: Unifying theory, experiments and natural systems.

Dispersal is a central life history trait that affects the ecological and evolutionary dynamics of populations and communities. The recent use of experimental evolution for the study of dispersal is a promising avenue for demonstrating valuable proofs of concept, bringing insight into alternative dispersal strategies and trade-offs, and testing the repeatability of evolutionary outcomes. Practical constraints restrict experimental evolution studies of dispersal to a set of typically small, short-lived organisms reared in artificial laboratory conditions. Here, we argue that despite these restrictions, inferences from these studies can reinforce links between theoretical predictions and empirical observations and advance our understanding of the eco-evolutionary consequences of dispersal. We illustrate how applying an integrative framework of theory, experimental evolution and natural systems can improve our understanding of dispersal evolution under more complex and realistic biological scenarios, such as the role of biotic interactions and complex dispersal syndromes.

The interconnection between independent reactive control policies drives the stringency of local containment.

The lack of medical treatments and vaccines upon the arrival of the SARS-CoV-2 virus has made non-pharmaceutical interventions the best allies in safeguarding human lives in the face of the COVID-19 pandemic. Here we propose a self-organized epidemic model with multi-scale control policies that are relaxed or strengthened depending on the extent of the epidemic outbreak. We show that optimizing the balance between the effects of epidemic control and the associated socio-economic cost is strongly linked to the stringency of control measures. We also show that non-pharmaceutical interventions acting at different spatial scales, from creating social bubbles at the household level to constraining mobility between different cities, are strongly interrelated. We find that policy functionality changes for better or worse depending on network connectivity, meaning that some populations may allow for less restrictive measures than others if both have the same resources to respond to the evolving epidemic.

The geography of metapopulation synchrony in dendritic river networks.

Dendritic habitats, such as river ecosystems, promote the persistence of species by favouring spatial asynchronous dynamics among branches. Yet, our understanding of how network topology influences metapopulation synchrony in these ecosystems remains limited. Here, we introduce the concept of fluvial synchrogram to formulate and test expectations regarding the geography of metapopulation synchrony across watersheds. By combining theoretical simulations and an extensive fish population time-series dataset across Europe, we provide evidence that fish metapopulations can be buffered against synchronous dynamics as a direct consequence of network connectivity and branching complexity. Synchrony was higher between populations connected by direct water flow and decayed faster with distance over the Euclidean than the watercourse dimension. Likewise, synchrony decayed faster with distance in headwater than mainstem populations of the same basin. As network topology and flow directionality generate fundamental spatial patterns of synchrony in fish metapopulations, empirical synchrograms can aid knowledge advancement and inform conservation strategies in complex habitats.

The ecology of cancer differentiation therapy.

A promising, yet still under development approach to cancer treatment is based on the idea of differentiation therapy (DTH). Most tumours are characterized by poorly differentiated cell populations exhibiting a marked loss of traits associated to communication and tissue homeostasis. DTH has been suggested as an alternative (or complement) to cytotoxic-based approaches, and has proven successful in some specific types of cancer such as acute promyelocytic leukemia (APL). While novel drugs favouring the activation of differentiation therapies are being tested, several open problems emerge in relation to its effectiveness on solid tumors. Here we present a mathematical framework to DTH based on a well-known ecological model used to describe habitat loss. The models presented here account for some of the observed clinical and in vitro outcomes of DTH, providing relevant insight into potential therapy design. Furthermore, the same ecological approach is tested in a hierarchical model that accounts for cancer stem cells, highlighting the role of niche specificity in CSC therapy resistance. We show that the lessons learnt from metapopulation ecology can help guide future developments and potential difficulties of DTH.

Dispersal evolution in temporally variable environments: implications for plant range dynamics.

Dispersal-the movement of an individual from the site of birth to a different site for reproduction-is an ecological and evolutionary driver of species ranges that shapes patterns of colonization, connectivity, gene flow, and adaptation. In plants, the traits that influence dispersal often vary within and among species, are heritable, and evolve in response to the fitness consequences of moving through heterogeneous landscapes. Spatial and temporal variation in the quality and quantity of habitat are important sources of selection on dispersal strategies across species ranges. While recent reviews have evaluated the interactions between spatial variation in habitat and dispersal dynamics, the extent to which geographic variation in temporal variability can also shape range-wide patterns in dispersal traits has not been synthesized. In this paper, we summarize key predictions from metapopulation models that evaluate how dispersal evolves in response to spatial and temporal habitat variability. Next, we compile empirical data that quantify temporal variability in plant demography and patterns of dispersal trait variation across species ranges to evaluate the hypothesis that higher temporal variability favors increased dispersal at plant range limits. We found some suggestive evidence supporting this hypothesis while more generally identifying a major gap in empirical work evaluating plant metapopulation dynamics across species ranges and geographic variation in dispersal traits. To address this gap, we propose several future research directions that would advance our understanding of the interplay between spatiotemporal variability and dispersal trait variation in shaping the dynamics of current and future species ranges.

Genetic Diversity and Connectivity in Plant Species Differing in Clonality and Dispersal Mechanisms in Wetland Island Habitats.

In plants, long-distance dispersal is both attenuated and directed by specific movement vectors, including animals, wind, and/or water. Hence, movement vectors partly shape metapopulation genetic patterns that are, however, also influenced by other life-history traits such as clonal growth. We studied the relationship between area, isolation, plant-species richness, reproduction, and dispersal mechanisms with genetic diversity and divergence in 4 widespread wetland plant-species in a total of 20 island-like kettle-hole habitats surrounded by an intensive agricultural landscape. Our results showed that genetic parameters reflect the reproduction strategies with the highest genetic diversity being observed in the non-clonal, outcrossing Oenanthe aquatica compared to the clonal Lycopus europaeus, Typha latifolia, and Phragmites australis. Lycopus showed a positive relationship between genetic diversity and kettle-hole area, but a negative relationship with the number of neighboring kettle holes (less isolation). Genetic diversity increased with plant-species richness in the clonal species Phragmites and Lycopus; while it decreased in the non-clonal Oenanthe. Finally, genetic divergence and, therefore, connectivity differed between alternative dispersal strategies, where wind-dispersed Typha and Phragmites had a higher gene flow between the analyzed kettle holes compared with the insect-pollinated, hydrochorous Lycopus and Oenanthe. Our study provides information on genetic patterns related to reproduction and dispersal mechanisms of 4 common wetland species contributing to the understanding of the functioning of plant metacommunities occurring in kettle holes embedded in agricultural landscapes.

Lévy flight movements prevent extinctions and maximize population abundances in fragile Lotka-Volterra systems.

Multiple-scale mobility is ubiquitous in nature and has become instrumental for understanding and modeling animal foraging behavior. However, the impact of individual movements on the long-term stability of populations remains largely unexplored. We analyze deterministic and stochastic Lotka-Volterra systems, where mobile predators consume scarce resources (prey) confined in patches. In fragile systems (that is, those unfavorable to species coexistence), the predator species has a maximized abundance and is resilient to degraded prey conditions when individual mobility is multiple scaled. Within the Lévy flight model, highly superdiffusive foragers rarely encounter prey patches and go extinct, whereas normally diffusing foragers tend to proliferate within patches, causing extinctions by overexploitation. Lévy flights of intermediate index allow a sustainable balance between patch exploitation and regeneration over wide ranges of demographic rates. Our analytical and simulated results can explain field observations and suggest that scale-free random movements are an important mechanism by which entire populations adapt to scarcity in fragmented ecosystems.

An individual's propensity to disperse is dependent on the behavioral type of its peers but not its own behavioral type.

Intraspecific differences in the dispersal propensity of animals have been linked to interindividual variation in inherent tendencies (i.e., personality or behavioral type) that influence multiple aspects of an individual's behavior. Studies linking dispersal propensity and personality often (1) focus on defining behavioral tendencies with a single behavioral trait rather than multiple, (2) do not recognize that invertebrates may have behavioral tendencies that influence dispersal, and (3) do not consider how the behavioral type of other individuals affects the dispersal propensity of an individual. We documented multiple foraging behaviors of an aquatic predatory insect (Notonecta irrorata) and found that Notonecta individuals differ in their inherent behavioral tendency (i.e., degree of boldness); all foraging behaviors were correlated such that riskier behaviors were exhibited by the same individuals. We conducted an experiment in which we varied which behavioral types of Notonecta were placed in outdoor pools (passive, bold or both types present) and quantified how long it took for individuals to disperse. Passive and bold individuals had a similar propensity to disperse but the dispersal propensity of each behavioral type was influenced by the behavioral type of other conspecifics present in the pool. Our work reveals that (1) invertebrates have inherent behavioral tendencies that vary among individuals but these tendencies do not necessarily impact all of the behavior displayed by the individual (i.e., impact foraging but not dispersal) and (2) the inherent behavioral tendency of other individuals with which an animal co-occurs can affect habitat patch dynamics such as predation, competition, or colonization.

Chimpanzee (Pan troglodytes schweinfurthii) Population Spans Multiple Protected Areas in the Albertine Rift.

We used mitochondrial DNA to examine gene flow in a region of western Uganda that has received little attention regarding chimpanzee population dynamics. The area is critical to gene flow between isolated Democratic Republic of Congo populations and the rest of East Africa. None of the chimpanzees in each of the 4 protected areas under consideration (Toro-Semliki Wildlife Reserve, Semuliki National Park, Rwenzori Mountains National Park and Itwara Central Forest Reserve) are fully habituated. Therefore, it is not clear whether one or more populations have historically used this fragmented landscape for (1) regular ranging and/or (2) infrequent dispersal. We incorporated the published sequences of the first hypervariable region of the D-loop of the mitochondrial genome from 3 previously sampled sites (n = 39) while also contributing the first extensive genetic sampling of chimpanzees in Toro-Semliki (n = 80). Our goal was to generate a historical baseline model of metapopulation dynamics in this region and determine which, if any, of these protected areas forms a fragmented landscape for a single chimpanzee population. According to a discriminant analysis of principal components, the haplotypes at Toro-Semliki form a central cluster, and Itwara is its nearest genetic neighbor. Rwenzori Mountains National Park is the most distant neighbor of all protected areas. We performed an analysis of molecular variance for 14 different population models that divided the samples from the 4 protected areas into 2, 3 or 4 populations. The best fit model included 3 populations: Toro-Semliki Wildlife Reserve and Itwara Forest Reserve comprised a single population; Semuliki National Park and Rwenzori Mountains National Park formed 2 additional separate populations (variance among = 9%, p = 0.014). The results indicated that some protected areas comprised distinctive populations, while others formed a fragmented landscape for a population's ranging for foraging purposes. Therefore, the edges of a protected area do not always define a chimpanzee population. We propose a closer examination of those dynamics through renewed sampling. Advances in DNA extraction and next-generation sequencing will allow us to compare thousands of single nucleotide polymorphisms in the genomes of unhabituated chimpanzees living in each of these protected areas.

Accounting for ocean connectivity and hydroclimate in fish recruitment fluctuations within transboundary metapopulations.

Marine resources stewardships are progressively becoming more receptive to an effective incorporation of both ecosystem and environmental complexities into the analytical frameworks of fisheries assessment. Understanding and predicting marine fish production for spatially and demographically complex populations in changing environmental conditions is however still a difficult task. Indeed, fisheries assessment is mostly based on deterministic models that lack realistic parameterizations of the intricate biological and physical processes shaping recruitment, a cornerstone in population dynamics. We use here a large metapopulation of a harvested fish, the European hake (Merluccius merluccius), managed across transnational boundaries in the northwestern Mediterranean, to model fish recruitment dynamics in terms of physics-dependent drivers related to dispersal and survival. The connectivity among nearby subpopulations is evaluated by simulating multi-annual Lagrangian indices of larval retention, imports, and self-recruitment. Along with a proxy of the regional hydroclimate influencing early life stages survival, we then statistically determine the relative contribution of dispersal and hydroclimate for recruitment across contiguous management units. We show that inter-annual variability of recruitment is well reproduced by hydroclimatic influences and synthetic connectivity estimates. Self-recruitment (i.e., the ratio of retained locally produced larvae to the total number of incoming larvae) is the most powerful metric as it integrates the roles of retained local recruits and immigrants from surrounding subpopulations and is able to capture circulation patterns affecting recruitment at the scale of management units. We also reveal that the climatic impact on recruitment is spatially structured at regional scale due to contrasting biophysical processes not related to dispersal. Self-recruitment calculated for each management unit explains between 19% and 32.9% of the variance of recruitment variability, that is much larger than the one explained by spawning stock biomass alone, supporting an increase of consideration of connectivity processes into stocks assessment. By acknowledging the structural and ecological complexity of marine populations, this study provides the scientific basis to link spatial management and temporal assessment within large marine metapopulations. Our results suggest that fisheries management could be improved by combining information of physical oceanography (from observing systems and operational models), opening new opportunities such as the development of short-term projections and dynamic spatial management.

Marine reserves stabilize fish populations and fisheries yields in disturbed coral reef systems.

Marine reserve networks are increasingly implemented to conserve biodiversity and enhance the persistence and resilience of exploited species and ecosystems. However, the efficacy of marine reserve networks in frequently disturbed systems, such as coral reefs, has rarely been evaluated. Here we analyze a well-mixed larval pool model and a spatially explicit model based on a well-documented coral trout (Plectropomus spp.) metapopulation in the Great Barrier Reef Marine Park, Australia, to determine the effects of marine reserve coverage and placement (in relation to larval connectivity and disturbance heterogeneity) on the temporal stability of fisheries yields and population biomass in environmentally disturbed systems. We show that marine reserves can contribute to stabilizing fishery yield while increasing metapopulation persistence, irrespective of whether reserves enhance or diminish average fishery yields. However, reserve placement and the level of larval connectivity among subpopulations were important factors affecting the stability and sustainability of fisheries and fish metapopulations. Protecting a mix of disturbed and non-disturbed reefs, rather than focusing on the least-disturbed habitats, was the most consistently beneficial approach across a range of dispersal and reserve coverage scenarios. Placing reserves only in non-disturbed areas was the most beneficial for biomass enhancement, but had variable results for fisheries and could potentially destabilize yields in systems with well-mixed larval or those that are moderately fished. We also found that focusing protection on highly disturbed areas could actually increase variability in yields and biomass, especially when degraded reef reserves were distant and poorly connected to the meta-population. Our findings have implications for the design and implementation of reserve networks in the presence of stochastic, patchy environmental disturbances.

Occasional long distance dispersal increases spatial synchrony of population cycles.

Spatially separated populations of the same species often exhibit correlated fluctuations in abundance, a phenomenon known as spatial synchrony. Dispersal can generate spatial synchrony. In nature, most individuals disperse short distances with a minority dispersing long distances. The effect of occasional long distance dispersal on synchrony is untested, and theoretical predictions are contradictory. Occasional long distance dispersal might either increase both overall synchrony and the spatial scale of synchrony, or reduce them. We conducted a protist microcosm experiment to test whether occasional long distance dispersal increases or decreases overall synchrony and the spatial scale of synchrony. We assembled replicate 15-patch ring metapopulations of the protist predator Euplotes patella and its protist prey Tetrahymena pyriformis. All metapopulations experienced the same dispersal rate, but differed in dispersal distance. Some metapopulations experienced strictly short distance (nearest neighbour) dispersal, others experienced a mixture of short- and long distance dispersal. Occasional long distance dispersal increased overall spatial synchrony and the spatial scale of synchrony for both prey and predators, though the effects were not statistically significant for predators. As predicted by theory, dispersal generated spatial synchrony by entraining the phases of the predator-prey cycles in different patches, a phenomenon known as phase locking. Our results are consistent with theoretical models predicting that occasional long distance dispersal increases spatial synchrony. However, our results also illustrate that the spatial scale of synchrony need not match the spatial scale of the processes generating synchrony. Even strictly short distance dispersal maintained high spatial synchrony for many generations at spatial scales much longer than the dispersal distance, thanks to phase locking.

Can pathogens optimize both transmission and dispersal by exploiting sexual dimorphism in their hosts?

Pathogens often rely on their host for dispersal. Yet, maximizing fitness via replication can cause damage to the host and an associated reduction in host movement, incurring a trade-off between transmission and dispersal. Here, we test the idea that pathogens might mitigate this trade-off between reproductive fitness and dispersal by taking advantage of sexual dimorphism in their host, tailoring responses separately to males and females. Using experimental populations of Daphnia magna and its bacterial pathogen Pasteuria ramosa as a test-case, we find evidence that this pathogen can use male hosts as a dispersal vector, and the larger females as high-quality resource patches for optimized production of transmission spores. As sexual dimorphism in dispersal and body size is widespread across the animal kingdom, this differential exploitation of the sexes by a pathogen might be an unappreciated phenomenon, possibly evolved in various systems.

Use of stochastic patch occupancy models in the California red-legged frog for Bayesian inference regarding past events and future persistence.

Assessing causes of population decline is critically important to management of threatened species. Stochastic patch occupancy models (SPOMs) are popular tools for examining spatial and temporal dynamics of populations when presence-absence data in multiple habitat patches are available. We developed a Bayesian Markov chain method that extends existing SPOMs by focusing on past environmental changes that may have altered occupancy patterns prior to the beginning of data collection. Using occupancy data from 3 creeks, we applied the method to assess 2 hypothesized causes of population decline-in situ die-off and residual impact of past source population loss-in the California red-legged frog. Despite having no data for the 20-30 years between the hypothetical event leading to population decline and the first data collected, we were able to discriminate among hypotheses, finding evidence that in situ die-off increased in 2 of the creeks. Although the creeks had comparable numbers of occupied segments, owing to different extinction-colonization dynamics, our model predicted an 8-fold difference in persistence probabilities of their populations to 2030. Adding a source population led to a greater predicted persistence probability than did decreasing the in situ die-off, emphasizing that reversing the deleterious impacts of a disturbance may not be the most efficient management strategy. We expect our method will be useful for studying dynamics and evaluating management strategies of many species.

Uso de Modelos Estocásticos de Ocupación de Fragmentos de la Rana Californiana de Patas Rojas para la Inferencia Bayesiana con Respecto a Eventos Pasados y su Persistencia en el Futuro Resumen La evaluación de las causas de la declinación poblacional es de importancia crítica para el manejo de especies amenazadas. Los modelos estocásticos de ocupación de parches (SPOMs, en inglés) son herramientas populares para examinar las dinámicas espaciales y temporales de las poblaciones cuando están disponibles los datos de presencia-ausencia para múltiples parches de hábitat. Desarrollamos un método bayesiano de cadena de Markov que extiende a los SPOMs existentes al enfocarse en los cambios ambientales pasados que podrían haber alterado los patrones de ocupación previos al inicio de la recolección de datos. Con los datos de ocupación de tres arroyos, aplicamos este método para evaluar dos causas hipotéticas de la declinación poblacional - muerte in situ e impacto residual de causas anteriores de pérdida de una poblacion fuente - de la rana californiana de patas rojas. A pesar de no tener datos para 20 - 30 años entre el evento hipotético que derivó en la declinación poblacional y los primeros datos recolectados, pudimos discriminar entre las hipótesis, encontrando evidencia de que la muerte in situ incrementó en dos de los arroyos. Aunque los arroyos tuvieron un número comparable de segmentos ocupados, debido a diferentes dinámicas de colonización - extinción, nuestro modelo predijo una diferencia ocho veces mayor en las probabilidades de persistencia de las poblaciones hasta el 2030. La suma de una población fuente resultó en una mayor probabilidad de persistencia pronosticada que con la reducción de la muerte in situ, enfatizando que la reversión de los impactos dañinos de una perturbación puede no ser la mejor estrategia de manejo. Esperamos que nuestro método sea útil para el estudio de las dinámicas y para la evaluación de las estrategias de manejo de muchas especies.

Spatial aggregation of aquatic habitats affects oviposition patterns in Aedes mosquitoes.

Colonization, including oviposition, is an important driver of population and community dynamics both within and across habitat patches. Most research has focused on the roles of habitat availability or quality on colonization and its outcomes. However, the spatial distribution of habitats also likely affects these processes. We conducted field experiments in Georgia, USA, using clustered and dispersed arrays of equal numbers of oviposition patches to investigate how patch aggregation influenced oviposition by Aedes mosquitoes. We tested the effects of aggregation on: (1) the total number of eggs an array received, (2) the proportion of patches within an array that received eggs, and (3) the number of eggs per colonized patch. We compared results to predictions from three models (Field of Dreams, Propagule Redirection, and Excess Attraction), which vary in the degree to which arrays attract colonists and apportion those colonists among patches. Clustered arrays received 22% more eggs than dispersed arrays, with clustered patches significantly more likely to receive eggs. At the species level, A. albopictus responded more to clustering than did A. triseriatus. These results are inconsistent with Propagule Redirection, but support the Excess Attraction and Field of Dreams models. Although clustered arrays occupied a relatively small area, they attracted at least as many ovipositing mosquitoes as did dispersed arrays. However, the number of eggs per colonized patch did not differ between clustered and dispersed arrays. Therefore, density dependence among larvae, and hence the production of adult mosquitoes on a per-patch basis, should be similar in dispersed and clustered landscapes.

Number of Source Patches Required for Population Persistence in a Source-Sink Metapopulation with Explicit Movement.

We consider a simple metapopulation model with explicit movement of individuals between patches, in which each patch is either a source or a sink. We prove that similarly to the case of patch occupancy metapopulations with implicit movement, there exists a threshold number of source patches such that the population potentially becomes extinct below the threshold and established above the threshold. In the case where the matrix describing the movement of populations between spatial locations is irreducible, the result is global; further, assuming a complete mobility graph with equal movement rates, we use the principle of equitable partitions to obtain an explicit expression for the threshold. Brief numerical considerations follow.

Temporal scale of environmental correlations affects ecological synchrony.

Population densities of a species measured in different locations are often correlated over time, a phenomenon referred to as synchrony. Synchrony results from dispersal of individuals among locations and spatially correlated environmental variation, among other causes. Synchrony is often measured by a correlation coefficient. However, synchrony can vary with timescale. We demonstrate theoretically and experimentally that the timescale-specificity of environmental correlation affects the overall magnitude and timescale-specificity of synchrony, and that these effects are modified by population dispersal. Our laboratory experiments linked populations of flour beetles by changes in habitat size and dispersal. Linear filter theory, applied to a metapopulation model for the experimental system, predicted the observed timescale-specific effects. The timescales at which environmental covariation occurs can affect the population dynamics of species in fragmented habitats.