Population variability in space and time

Lundberg, Per; Ranta, Esa; Ripa, Jörgen; Kaitala, Veijo

doi:10.1016/s0169-5347(00)01981-9

Cited by 159 publications

(116 citation statements)

References 57 publications

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“…(Sielezniew et al 2012) Parameters presented include sample size within locality (N); number of alleles (A), allelic richness (R), observed and expected heterozygosity heterozygosity (H O and H E respectively), P value for HWE exact test for heterozygote deficiency/excess (ns indicates non-significant values exceeding 0.05), and fixation index (F IS ; Bonferroni corrected P value at α = 0.05, based on 900 randomisations, was 0.0011) Long-term trend in population size is the most evident predictor of extinction risk (Caughley 1994;Keith et al 2015). In the absence of a clear trend, the extent of population size fluctuations, serving as an inverse measure of stability, makes a useful indicator of population viability, as more fluctuating populations are more vulnerable to extinctions (Caughley 1994;Lundberg et al 2000;Nowicki 2017). However, the assessment of both trend as well as fluctuation level requires relatively long time series of quantitative data for a particular population, which are rarely available, especially in the case of insects (Schtickzelle and Baguette 2009;Nowicki 2017).…”

Section: Discussionmentioning

confidence: 99%

What keeps ‘living dead’ alive: demography of a small and isolated population of Maculinea (= Phengaris) alcon

Nowicki

Deoniziak

Dziekańska³

et al. 2018

J Insect Conserv

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Small and isolated populations are prone to future extinctions and thus perceived as 'living dead'. Although generally considered to be of low conservation value, their existence can still enhance species survival at the landscape scale through improving the connectivity of other populations and facilitating some (even if little) gene flow. We investigated the demography and genetic status of a tiny and highly isolated local population of Maculinea (= Phengaris) alcon near its distribution margin with the aim of identifying the features that allow it to persist. The study comprised intensive mark-recapture, surveys of Gentiana pneumonanthe foodplants and butterfly eggs laid on them, as well as genetic analyses. The population has been found to be characterised by low genetic diversity and estimated at only a few tens of individuals. The foodplant availability turned out to be the most obvious factor limiting M. alcon abundance. Nevertheless, the life expectancy of adult butterflies is fairly long, and their flight period very short, implying that most individuals occur within the same time window. Together with the relatively little protandry observed, i.e. almost synchronous emergence of males and females, this increases the chances of random mating among the individuals. Moreover, the butterflies move freely across the core habitat fragment. All things concerned, the effective population size is presumably not much lower than the recorded population size. Our findings provide guidelines for pinpointing those among 'living dead' populations that are likely to be the most persistent and thus worth conservation efforts aimed at preserving them.

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Section: Discussionmentioning

confidence: 99%

What keeps ‘living dead’ alive: demography of a small and isolated population of Maculinea (= Phengaris) alcon

Nowicki

Deoniziak

Dziekańska³

et al. 2018

J Insect Conserv

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“…In many cases, the population fluctuations in different habitats appear to be, to a certain extent, correlated; the phenomenon known as synchronization [85,87]. The example of aphids considered above is therefore by no means unique.…”

Section: Landscape Scale: Synchronization and Self-organizationmentioning

confidence: 99%

Multiscale approach to pest insect monitoring: Random walks, pattern formation, synchronization, and networks

Petrovskii

Petrovskaya

Bearup

2014

Physics of Life Reviews

104

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Pest insects pose a significant threat to food production worldwide resulting in annual losses worth hundreds of billions of dollars. Pest control attempts to prevent pest outbreaks that could otherwise destroy a sward. It is good practice in integrated pest management to recommend control actions (usually pesticides application) only when the pest density exceeds a certain threshold. Accurate estimation of pest population density in ecosystems, especially in agro-ecosystems, is therefore very important, and this is the overall goal of the pest insect monitoring. However, this is a complex and challenging task; providing accurate information about pest abundance is hardly possible without taking into account the complexity of ecosystems' dynamics, in particular, the existence of multiple scales. In the case of pest insects, monitoring has three different spatial scales, each of them having their own scale-specific goal and their own approaches to data collection and interpretation. In this paper, we review recent progress in mathematical models and methods applied at each of these scales and show how it helps to improve the accuracy and robustness of pest population density estimation.

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“…Temporal and spatial fluctuations in number of individuals are marked characteristics of all animal populations (Heino et al, 1997;Lundberg et al, 2000). Inspired by the seminal work of Elton & Nicholson (1942) and Moran (1953), the temporal dynamics in number of individuals from spatially distributed subpopulations are currently one of the main themes investigated by ecologists (Kendal et al, 2000;Ylikarjula et al, 2000;Grenouillet et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

Spatial synchrony of a highly endemic fish Assemblage (Segredo Reservoir, Iguaçu River, Paraná State, Brazil)

2005

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In this study, patterns of spatial synchrony in population fluctuations (cross-correlation) of an endemic fish assemblage of a Neotropical reservoir (Segredo Reservoir, Iguaçu River, Paraná State, Brazil) were reported. First, the level of population synchrony for 20 species was estimated. Second, population synchrony was correlated, using the Mantel test, with geographical distances among sites (n = 11) and also environmental synchrony (temperature). Nine species presented significant correlations between spatial synchrony and geographic distances (Astyanax sp. b, Astyanax sp. c, Pimelodus sp., Hoplias malabaricus, Crenicichla iguassuensis, Hypostomus derbyi, Hypostomus myersi, Rhamdia branneri, and R. voulezi). Considering the ecology of the species and the significant relationship between population and environmental synchronies, it seems that environmental stochasticity is the most plausible hypothesis in explaining the observed synchrony patterns.Key words: spatial synchrony, fish assemblage, reservoirs. RESUMOSincronia espacial de uma assembléia de peixes endêmica (reservatório de Segredo, rio Iguaçu, Paraná, Brasil)Neste estudo, os padrões de sincronia espacial de uma assembléia de peixes endêmica em um reservatório neotropical (reservatório de Segredo, rio Iguaçu, Paraná, Brasil) foram descritos. Primeiro, foi estimado o nível de sincronia (correlação entre as densidades ao longo do tempo) para 20 espécies. Segundo, a matriz de sincronia populacional foi correlacionada, utilizando o teste de Mantel, com a distância geográfica entre os locais (n = 11) e com a sincronia ambiental (temperatura da água). Nove espécies apresentaram correlações significativas entre sincronia espacial e distância geográfica (Astyanax sp. b, Astyanax sp. c, Pimelodus sp., Hoplias malabaricus, Crenicichla iguassuensis, Hypostomus derbyi, Hypostomus myersi, Rhamdia branneri e R. voulezi). Considerando a ecologia das espécies e a relação significativa entre a sincronia populacional e a sincronia ambiental, é possível inferir que estocasticidade ambiental é a hipótese mais plausível para explicar os padrões de sincronia detectados.Palavras-chave: sincronia espacial, assembléia de peixes, reservatórios.

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Population variability in space and time

Cited by 159 publications

References 57 publications

What keeps ‘living dead’ alive: demography of a small and isolated population of Maculinea (= Phengaris) alcon

What keeps ‘living dead’ alive: demography of a small and isolated population of Maculinea (= Phengaris) alcon

Multiscale approach to pest insect monitoring: Random walks, pattern formation, synchronization, and networks

Spatial synchrony of a highly endemic fish Assemblage (Segredo Reservoir, Iguaçu River, Paraná State, Brazil)

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