2000
DOI: 10.1046/j.1365-2656.2000.00380.x
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Cyclic dynamics in field vole populations and generalist predation

Abstract: Summary 1.A geographical gradient in the relative impact of generalist and specialist predators on small rodent populations has been hypothesized to be responsible for the gradient in cyclicity found in Fennoscandia. Population oscillations resulting from weasel±vole interactions are said to be dampened by the increasing stabilizing impact of generalist predators in southern Fennoscandia resulting from: (i) a greater abundance and diversity of predators sustained by alternative prey; (ii) the absence of signi®… Show more

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Cited by 186 publications
(211 citation statements)
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“…Spatio-temporal patterns can be partly revealed by measuring how the synchrony between the population dynamics of different sites varies with the distance between sites. To illustrate this we present analysis of data on the field vole populations in Kielder Forest (see Lambin et al (1998Lambin et al ( , 2000, Mackinnon et al (2001) and Bierman et al (2006) for more details of this system and more detailed analysis). The raw data consist of average population density estimates from abundance indices (see Lambin et al (2000) for a methodological description) for a range of sites, over the period [1984][1985][1986][1987][1988][1989][1990][1991][1992].…”
Section: Methods For Detecting Travelling Waves In Empirical Datamentioning
confidence: 99%
See 1 more Smart Citation
“…Spatio-temporal patterns can be partly revealed by measuring how the synchrony between the population dynamics of different sites varies with the distance between sites. To illustrate this we present analysis of data on the field vole populations in Kielder Forest (see Lambin et al (1998Lambin et al ( , 2000, Mackinnon et al (2001) and Bierman et al (2006) for more details of this system and more detailed analysis). The raw data consist of average population density estimates from abundance indices (see Lambin et al (2000) for a methodological description) for a range of sites, over the period [1984][1985][1986][1987][1988][1989][1990][1991][1992].…”
Section: Methods For Detecting Travelling Waves In Empirical Datamentioning
confidence: 99%
“…To illustrate this we present analysis of data on the field vole populations in Kielder Forest (see Lambin et al (1998Lambin et al ( , 2000, Mackinnon et al (2001) and Bierman et al (2006) for more details of this system and more detailed analysis). The raw data consist of average population density estimates from abundance indices (see Lambin et al (2000) for a methodological description) for a range of sites, over the period [1984][1985][1986][1987][1988][1989][1990][1991][1992]. These are the years for which evidence of periodic travelling waves is the strongest: more recent data are not so indicative of a unidirectional wave (see Bierman et al 2006 for details).…”
Section: Methods For Detecting Travelling Waves In Empirical Datamentioning
confidence: 99%
“…The field vole is common in these ephemeral habitats but completely absent from forested areas, which lack grass cover. Long-term monitoring has shown that field vole populations in the Kielder forest have cyclic dynamics with a 3-to 4-year period (34). Habitat patches are very similar in terms of vegetation and differ primarily in aspect.…”
Section: Methodsmentioning
confidence: 99%
“…In order to estimate density dependent parameters of vole population growth rates we fitted a seasonal log-linear auto-regressive model (Hansen et al 1999), where the proportion of quadrats yielding positive vole signs were used as a proxy for density (Lambin et al 2000). Observation error may cause bias in the estimation of densitydependence.…”
Section: Statistical Analysesmentioning
confidence: 99%
“…In this state-space framework, missing values from spring 2005 were estimated as a by-product of the model fitting process, hence they didn't contribute to inform about model fit. Earlier calibration work established that volesign detection probability is linearly related to vole density estimated by live-trapping (Lambin et al 2000), and it is also known that the log-linear model fitted has some robustness to non-linearities in the proxy for density (Tkadlec et al 2011). We used independent uninformative priors for all the parameters of the model.…”
Section: Observation Processmentioning
confidence: 99%