Population viability analyses in plants: challenges and opportunities

Menges, Eric S.

doi:10.1016/s0169-5347(99)01763-2

Cited by 310 publications

(291 citation statements)

References 36 publications

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“…Deze wijzigingen staan beschreven in Pouwels et al (2009b). Voor planten is moeilijker aan te geven wat de grootte van een stabiele populatie is, omdat deze vaak klonale groei kennen waardoor het lastig is om aan te geven wat een individu is (Honnay et al, 2005;Menges, 2000).…”

Section: Implementatieunclassified

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Pouwels

Eupen

Adrichem

et al. 2016

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Section: Implementatieunclassified

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Pouwels

Eupen

Adrichem

et al. 2016

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“…While the former approach can be technically difficult (especially when the joint probability distribution is not multivariate normal), the latter is readily implemented. The difficulty with using randomly generated lower-level vital rates is in adequately specifying (i) the appropriate parametric distribution for the particular vital rate (the shape of the random distribution used can strongly influence the results of stochastic projections in some cases; Bukowski et al, 1995;Hamed and Bedient, 1997;Menges, 2000), and (ii) specifying the appropriate variance term for each parameter (which requires decomposing estimated variance into process and sampling variance; this is also not easily done in some instances, especially for parameters which are not estimated based on a formal statistical model; Burnham et al, 1987). …”

Section: Entering Stochasticity In Matrix Modelsmentioning

confidence: 99%

Apparent differences in stochastic growth rates based on timing of census: a cautionary note

Cooch

Gauthier

Rockwell

2003

Ecological Modelling

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Matrix population models are increasingly used in both theoretical and applied analysis of population dynamics (Caswell, Matrix Population Models */Construction, Analysis, and Interpretation (2001) 722). The projected asymptotic growth rate from deterministic models, based on a single matrix, is invariant as to when in the annual cycle the population is censused (typically, either immediately prior to or after breeding). Thus, we expect that given a set of n matrices {A 1 , A 2 ,. . ., A n }, where each matrix A i corresponds to a given environmental state i , that the longterm expected stochastic growth rate calculated by the product of matrices selected at random from this set should not depend on whether the matrices in the set are configured based on either a pre-or post-breeding census. However, differences in stochastic growth rate as a function of the timing of the census can arise under conditions where there is significant covariance among the individual matrix elements. Using a seasonal (periodic) matrix modeling approach, we show that such differences are an artifact of how stochasticity is entered into the matrices, particularly when the matrices are structured based on a post-breeding census model. In such cases, the annual projection matrix for a given year is in fact a product of component seasonal matrices from two successive years. Failing to account for this when there is covariance among seasons will lead to a disparity in estimated stochastic growth rate when growth is calculated based on the product of random matrices, as is frequently done. We show that a seasonal matrix approach, where the seasonal matrices are explicitly subscripted for the appropriate year, eliminates the problem, and is a generally robust approach to stochastic modeling. #

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“…Sustainable use of natural resources can only be achieved with the introduction of plants, as well as cultivation, which is an important way to protect endangered plant species (Menges, 2000). Therefore, in recent decades of the last and at the beginning of this century, abroad, but also in Serbia and Slovenia great efforts had been made to develop a technology for gentian cultivation, especially in rural mountainous areas (Kušar and Baričević, 2006;Radanović et al, 2007b;2007c;Radanović, 2008;Franz, 2012;Radanović et al, 2013;Balijagić, 2013;González-López et al, 2014;Sand, 2015).…”

Section: Introductionmentioning

confidence: 99%

MORPHO - PHYSIOLOGICAL CHARACTERISTICS OF GENTIAN (Gentiana lutea L.) GENOTYPE SEEDLINGS FROM NATURAL POPULATIONS IN MONTENEGRO

Balijagic¹,

Bošković²,

Crnobarać³

et al. 2017

AgricultForest

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SUMMARYThe aim of this paper is to examine the possibility of gentian generative propagation, because the production of high-quality planting material is very important not only for the beginning of revitalization of this plant species in their natural habitat but also for its large-scale production in Montenegro. Cultivation of gentian, as well as other medicinal plants, represents a safe way for their protection and conservation in the wild. For the purpose of choosing the best population, seed samples from 9 natural habitats were collected in the mountains of the northern part of Montenegro. The field trial in which dynamics of gentian seedlings growth was monitored in the first and the second year of vegetation was set up by sowing of seeds collected in natural conditions at the locality Korita.The average fresh root weight of the sowed annual seeds was 0.17 g and the maximum weight had seedlings originating from the locality called Jovanova koliba. The average dry matter content in the roots was 29.18%. The average root length of biennial seedlings of the tested population was 14.6 cm and maximum length had seedlings originating from Prelija. The average root fresh weight of the analyzed population of biennial seedlings was 0.96 g and maximum weight had seedlings from Jovanova koliba (1.57 g).

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Population viability analyses in plants: challenges and opportunities

Cited by 310 publications

References 36 publications

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Apparent differences in stochastic growth rates based on timing of census: a cautionary note

MORPHO - PHYSIOLOGICAL CHARACTERISTICS OF GENTIAN (Gentiana lutea L.) GENOTYPE SEEDLINGS FROM NATURAL POPULATIONS IN MONTENEGRO

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