When can dispersal synchronize populations?

Goldwyn, Eli E.; Hastings, Alan

doi:10.1016/j.tpb.2007.11.012

Cited by 72 publications

(82 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We begin by neglecting the effects of demographic noise (section 2). As previously shown by Goldwyn and Hastings [11,13], there exist parameter regimes where dispersal alone supports both synchronous and asynchronous phase-locked states. Here we show how the existence of an asynchronous state effects the approach to synchrony when common external fluctuations are included.…”

supporting

confidence: 56%

“…The loss of prey due to predation also depends linearly on c with c > 1, which implies that the loss in prey population due to predation is faster than the gain in predators. Equations (1) can be nondimensionalised as in [11] to obtain, for the i-th population:…”

Section: The Rosenzweig-macarthur Modelmentioning

confidence: 99%

“…The phase-reduction method can then be used to analyze synchronization of an ensemble of oscillators by approximating the high-dimensional limit cycle dynamics as a closed system of equations for the corresponding phase variables [19,4]. Within the context of ecology, Goldwyn and Hastings have used the theory of weakly coupled phase oscillators to investigate various modes of synchronous and asynchronous phase-locking in predator-prey systems weakly coupled by dispersal [11,12]. They have also examined the joint effects of dispersal and environmental fluctuations, by simulating ensembles of predator-prey oscillators with diffusive or global coupling and spatially correlated Poisson inputs [13]; each predator-prey patch is described by the Rosenzweig and MacArthur (RM) model [35,17] Recently, a complementary approach to analyzing the effects of external fluctuations on the synchronization of predator-prey populations has been developed by Lai et.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Dispersal and noise: Various modes of synchrony in ecological oscillators

Bressloff

Lai

2012

J. Math. Biol.

View full text Add to dashboard Cite

We use the theory of noise-induced phase synchronization to analyze the effects of dispersal on the synchronization of a pair of predator-prey systems within a fluctuating environment (Moran effect). Assuming that each isolated local population acts as a limit cycle oscillator in the deterministic limit, we use phase reduction and averaging methods to derive a Fokker-Planck equation describing the evolution of the probability density for pairwise phase differences between the oscillators. In the case of common environmental noise, the oscillators ultimately synchronize. However the approach to synchrony depends on whether or not dispersal in the absence of noise supports any stable asynchronous states. We also show how the combination of correlated (shared) and uncorrelated (unshared) noise with dispersal can lead to a multistable steady-state probability density.

show abstract

supporting

confidence: 56%

Section: The Rosenzweig-macarthur Modelmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Dispersal and noise: Various modes of synchrony in ecological oscillators

Bressloff

Lai

2012

J. Math. Biol.

View full text Add to dashboard Cite

show abstract

“…We thus argue that regional environmental drivers were not preponderant in controlling phytoplankton phenology in the giant dendritic reservoir, although seasonal fluctuations of phytoplankton was often regarded as one of the important cyclic events in aquatic ecosystems, and was even emphasized as an important sign of regional climatic change. Dispersal among populations can reduce the size of relatively large populations and increase relatively small ones, and is often treated as an alternative explanation for synchrony (Paradis et al 1999;Goldwyn and Hastings 2008;Bunnell et al 2010). Compared to fish and other aquatic vertebrates, phytoplankton is largely an obligate passive disperser (Shurin et al 2009) and the incidence of dispersal is related to habitat type (lotic vs. lentic).…”

Section: Discussionmentioning

confidence: 99%

Patterns of asynchrony for phytoplankton fluctuations from reservoir mainstream to a tributary bay in a giant dendritic reservoir (Three Gorges Reservoir, China)

Cai

Shao

et al. 2011

Aquat Sci

View full text Add to dashboard Cite

Seasonal fluctuations of phytoplankton have often been regarded as one of the important cyclic events in aquatic ecosystems, and have even been emphasized as an important sign of regional climatic variability in limnology. However, few attempts have been made to examine synchrony for phytoplankton fluctuations among different habitats in a single reservoir system. The present study employed Spearman rank correlation analysis and the Mantel test to assess levels of synchrony for phytoplankton abundance and taxonomic composition from reservoir mainstream to a tributary bay (Xiangxi Bay) in a giant dendritic reservoir, China (Three Gorges Reservoir, TGR). At the selected scale, asynchronous patterns of phytoplankton were found when looking at total abundance and taxonomic composition, suggesting that regional drivers were not strong enough to synchronize phytoplankton fluctuations, and local regulators were predominant. As a riverine system, the mainstream of TGR had high levels of algal synchrony, while asynchronous patterns of phytoplankton were detected within Xiangxi Bay, which is characterized as a lacustrine system. The present study further confirmed that external hydrological disturbances strongly homogenize habitat conditions and synchronize phytoplankton fluctuations within the mainstream, while spatial divergence of phytoplankton succession depend on local habitat conditions within Xiangxi Bay. Moreover, low synchrony of phytoplankton between the mainstream and Xiangxi Bay is probably caused by spatial divergence of phytoplankton succession within Xiangxi Bay and the lack of succession in the rapidly flushed mainstream. Independently of these mechanisms possibly explaining phytoplankton fluctuations, the present study has also an applied perspective to the improvement of a long-term observation program in which phytoplankton trends at the mainstream scale could be compiled from the data set in a single site, while a set of sampling sites should be required at the Xiangxi Bay scale.

show abstract

“…Beside in-phase synchronization between spatially separated populations, where populations cycle in tune, a more subtle form, phase locking, has been suggested by ecological models for periodic and chaotically oscillating populations 7,11,[25][26][27] . Phase locking occurs when one (or more) oscillator influences a second oscillator in such a way that their phases oscillate in tune but that there is a constant difference in the phase of two oscillators 1,2 .…”

mentioning

confidence: 99%

Different types of synchrony in chaotic and cyclic communities

Becks

Arndt

2013

Nat Commun

View full text Add to dashboard Cite

Stability and persistence of populations is of great interest for management and conservation purposes. Spatial dynamics can have a crucial role in population stability via synchronization, and beneficial and detrimental effects on population persistence have been shown. Despite a theoretical understanding of synchronization, empirical data on synchrony of populations are restricted to systems that do not display the full spectrum of complex dynamics that may occur in nature (that is, chaos or quasiperiodicity). Here we show in experiments that the qualitative form of dynamic behaviour of chaotic and periodic oscillating communities did not change when unidirectionally coupled to oscillating driver communities. Driver and response populations were phase locked in cyclic communities, whereas chaotic communities showed only short periods of statistical coherencies. Our study provides the first empirical analysis of synchronization of chaotic communities and shows that the likelihood for chaos is not lowered in spatially explicit systems but that cyclic and chaotic systems differ in synchronization.

show abstract

When can dispersal synchronize populations?

Cited by 72 publications

References 25 publications

Dispersal and noise: Various modes of synchrony in ecological oscillators

Dispersal and noise: Various modes of synchrony in ecological oscillators

Patterns of asynchrony for phytoplankton fluctuations from reservoir mainstream to a tributary bay in a giant dendritic reservoir (Three Gorges Reservoir, China)

Different types of synchrony in chaotic and cyclic communities

Contact Info

Product

Resources

About