Spatial Scales of Population Synchrony in Predator-Prey Systems

Jarillo, Javier; Sæther, Bernt‐Erik; Engen, Steinar; Cao‐García, Francisco J.

doi:10.1086/706913

Cited by 23 publications

(21 citation statements)

References 91 publications

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“…A few studies considered the joint effects of stochastic perturbations and limit cycles. For instance, Vasseur and Fox (2007) showed that spatially correlated stochastic perturbations can dampen biomass oscillations but the effects of stochastic perturbations on metacommunities in the vicinity of equilibrium have only recently been studied Jarillo et al, 2020;. Our aim is to understand how density-dependent dispersal alters the Here, we propose to extend the model developed in , which describes a metacommunity with two patches sustaining Lotka-Volterra food chains, by integrating the densitydependent dispersal module proposed by .…”

Section: Introductionmentioning

confidence: 99%

Predator avoidance and foraging for food shape synchrony and response to perturbations in trophic metacommunities

Quévreux

Pigeault

Loreau

2021

Journal of Theoretical Biology

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The response of species to perturbations strongly depends on spatial aspects in populations connected by dispersal. Asynchronous fluctuations in biomass among populations lower the risk of simultaneous local extinctions and thus reduce the regional extinction risk. However, dispersal is often seen as passive diffusion that balances species abundance between distant patches, whereas ecological constraints, such as predator avoidance or foraging for food, trigger the movement of individuals. Here, we propose a model in which dispersal rates depend on the abundance of the species interacting with the dispersing species (e.g., prey or predators) to determine how density-dependent dispersal shapes spatial synchrony in trophic metacommunities in response to stochastic perturbations. Thus, unlike those with passive dispersal, this model with density-dependent dispersal bypasses the classic vertical transmission of perturbations due to trophic interactions and deeply alters synchrony patterns. We show that the species with the highest coefficient of variation of biomass governs the dispersal rate of the dispersing species and determines the synchrony of its populations. In addition, we show that this mechanism can be modulated by the relative impact of each species on the growth rate of the dispersing species. Species affected by several constraints disperse to mitigate the strongest constraints (e.g., predation), which does not necessarily experience the highest variations due to perturbations. Our approach can disentangle the joint effects of several factors implied in dispersal and provides a more accurate description of dispersal and its consequences on metacommunity dynamics.

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Section: Introductionmentioning

confidence: 99%

Predator avoidance and foraging for food shape synchrony and response to perturbations in trophic metacommunities

Quévreux

Pigeault

Loreau

2021

Journal of Theoretical Biology

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“…Theory predicts that, in bottom-up regulated food webs, spatial population synchrony of species should increase with trophic level, so any predator would have a larger spatial scale of population synchrony than its prey (Jarillo et al 2020). This result has been experimentally observed in bacterial communities (Kent et al 2007).…”

Section: Influence Of Species Interactions On Responses To Harvestingmentioning

confidence: 86%

“…This result has been experimentally observed in bacterial communities (Kent et al 2007). In such bottom-up regulated predator−prey systems, proportional harvesting of the prey increases the spatial scale of population synchrony of its predator while proportional harvesting of the predator reduces the scale of synchrony of its prey (Jarillo et al 2020). In general, increases in the spatial scale of population synchrony follow the directional propagation of fluctuations through food webs.…”

Section: Influence Of Species Interactions On Responses To Harvestingmentioning

confidence: 99%

Population responses to harvesting in fluctuating environments

et al. 2022

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Achieving sustainable harvesting of natural populations depends on our ability to predict population responses to the combined effects of harvesting and environmental fluctuations while accounting for other internal and external factors that influence population dynamics in time and space. Here, we review recent research showing how spatial patterns and interspecific interactions can influence population responses to harvesting in fluctuating environments. We highlight several pathways through which harvesting can, often inadvertently, influence the dynamics and resilience to environmental fluctuations of both harvested and surrounding non-harvested populations and species. For instance, spatial models have shown that harvesting is expected to influence the spatial synchrony of population fluctuations, both of the harvested species and its competitors, predators and prey, with implications for population extinction risk. Dispersal and interspecific interactions can cause responses to harvesting in areas and species that are not themselves harvested. Harvesting that selectively targets certain groups of individuals, either intentionally or through for example spatially biased harvesting, can amplify environmentally induced population fluctuations by biasing the population structure towards individuals that are more sensitive to environmental variation. On the other hand, harvesting can in some cases buffer populations against the density-dependent effects of harsh climatic conditions, which are probably more common than previously acknowledged. Recent advances in modeling are providing new predictions that are highly relevant under global warming and now need to be tested empirically. We discuss how knowledge of these pathways can be used to increase the sustainability of harvesting.

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“…1999), strength and source of density regulation (Engen 2017), trophic interactions (Jarillo et al. 2020), or habitat preference (Bellamy et al. 2003), are known to vary distinctively between the age classes of our study species (Olsen et al.…”

Section: Discussionmentioning

confidence: 98%

“…Trophic interactions can also promote spatial autocorrelation (Jarillo et al. 2020), for example through the presence of a nomadic predator regulating the vital rates of a prey population (Ims and Andreassen 2000, Vasseur and Fox 2009). In addition, because density regulatory processes influence dispersal rates and abundance dynamics, differences in density regulation among species and across time and space can influence spatial autocorrelation patterns (Lande et al.…”

Section: Introductionmentioning

confidence: 99%

Age‐dependent patterns of spatial autocorrelation in fish populations

Marquez

Sæther

Aanes

et al. 2021

Ecology

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The degree of spatial autocorrelation in population fluctuations increases with dispersal and geographical covariation in the environment, and decreases with strength of density dependence. Because the effects of these processes can vary throughout an individual’s lifespan, we studied how spatial autocorrelation in abundance changed with age in three marine fish species in the Barents Sea. We found large interspecific differences in age‐dependent patterns of spatial autocorrelation in density. Spatial autocorrelation increased with age in cod, the reverse trend was found in beaked redfish, while it remained constant among age classes in haddock. We also accounted for the average effect of local cohort dynamics, i.e. the expected local density of an age class given last year’s local density of the cohort, with the goal of disentangling spatial autocorrelation patterns acting on an age class from those formed during younger age classes and being carried over. We found that the spatial autocorrelation pattern of older age classes became increasingly determined by the distribution of the cohort during the previous year. Lastly, we found high degrees of autocorrelation over long distances for the three species, suggesting the presence of far‐reaching autocorrelating processes on these populations. We discuss how differences in the species’ life history strategies could cause the observed differences in age‐specific variation in spatial autocorrelation. As spatial autocorrelation can differ among age classes, our study indicates that fluctuations in age structure can influence the spatio‐temporal variation in abundance of marine fish populations.

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Spatial Scales of Population Synchrony in Predator-Prey Systems

Cited by 23 publications

References 91 publications

Predator avoidance and foraging for food shape synchrony and response to perturbations in trophic metacommunities

Predator avoidance and foraging for food shape synchrony and response to perturbations in trophic metacommunities

Population responses to harvesting in fluctuating environments

Age‐dependent patterns of spatial autocorrelation in fish populations

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