FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2071092103> ?p ?o ?g. }

• W2071092103 endingPage "285" @default.
• W2071092103 startingPage "271" @default.
• W2071092103 abstract "Markovian population models are used in conservation biology to find an accurate estimate of a population's extinction probability. Such models require handling of large transition matrices and calculations are thus extremely time-consuming when large populations have to be studied. To accomplish these problems, some authors have suggested to group together several states/sizes of the population. Unfortunately, this so-called binning frequently results in errors in estimates obtained. The main problem with binning is that it assumes that grouped states behave nearly identical with respect to the underlying stochastic population process and that so far binning methods implicitly violate this assumption. In this paper, we present a new binning method based on self-organizing Kohonen neural networks for time-homogeneous Markovian metapopulation models. The neural networks are used to analyse one-step transitions of the Markov chain in order to group only nearly identical states. We show that the new method is more qualified for the use in conservation than deterministic methods that we had discussed in a previous paper (first order Fibonacci binning, pairs binning). It reveals more accurate and more reliable estimates than these methods. Errors in estimated extinction probabilities that were introduced by binning did not exceed one order of magnitude and errors in the global population size did not exceed 30%. These errors in estimates correspond to a low inaccuracy in model parameter values of population growth and migration ranging from ±1 to ±10%. The reduction in the state space of the studied metapopulations ranged from 21 to 33% per subpopulation. The resulting decrease in computing time caused by our binning method is substantial particularly with regard to simulations tasks such as comparing the extinction risk of several populations or performing a detailed sensitivity analysis for model parameters assumed. The successful estimation of the extinction risk of eight natural butterfly populations demonstrates the applicability of our new binning method in conservation biology. A comparison of extinction probabilities and mean population sizes estimated by Monte Carlo simulations [Griebeler, E.M., Seitz, A., 2002. An individual based model for the conservation of the endangered Large Blue butterfly, Maculinea arion (Lepidoptera: Lycaenidae). Ecol. Model. 134, 343–356] with those obtained from the respective Markov chains for these butterfly populations revealed similar results on the accuracy of estimates and the reduction in transition matrices that were predicted by the comparative error analysis for binning methods." @default.
• W2071092103 created "2016-06-24" @default.
• W2071092103 creator A5012114797 @default.
• W2071092103 creator A5064558535 @default.
• W2071092103 date "2006-02-01" @default.
• W2071092103 modified "2023-10-03" @default.
• W2071092103 title "The use of Markovian metapopulation models: Reducing the dimensionality of transition matrices by self-organizing Kohonen networks" @default.
• W2071092103 cites W1537174689 @default.
• W2071092103 cites W1785878118 @default.
• W2071092103 cites W1965135509 @default.
• W2071092103 cites W1970150727 @default.
• W2071092103 cites W1976602614 @default.
• W2071092103 cites W1982344223 @default.
• W2071092103 cites W1983459530 @default.
• W2071092103 cites W1987234274 @default.
• W2071092103 cites W1991848143 @default.
• W2071092103 cites W2000532370 @default.
• W2071092103 cites W2002117208 @default.
• W2071092103 cites W2008968713 @default.
• W2071092103 cites W2014766160 @default.
• W2071092103 cites W2016867299 @default.
• W2071092103 cites W2023637201 @default.
• W2071092103 cites W2033534289 @default.
• W2071092103 cites W2051453726 @default.
• W2071092103 cites W2068410759 @default.
• W2071092103 cites W2083564808 @default.
• W2071092103 cites W2113986762 @default.
• W2071092103 cites W2132550267 @default.
• W2071092103 cites W2134994688 @default.
• W2071092103 cites W2142221995 @default.
• W2071092103 cites W2278205623 @default.
• W2071092103 cites W2327054641 @default.
• W2071092103 cites W2612166593 @default.
• W2071092103 cites W2763201952 @default.
• W2071092103 cites W3036192984 @default.
• W2071092103 cites W3142112479 @default.
• W2071092103 cites W321384525 @default.
• W2071092103 cites W65738273 @default.
• W2071092103 doi "https://doi.org/10.1016/j.ecolmodel.2005.06.004" @default.
• W2071092103 hasPublicationYear "2006" @default.
• W2071092103 type Work @default.
• W2071092103 sameAs 2071092103 @default.
• W2071092103 citedByCount "6" @default.
• W2071092103 countsByYear W20710921032014 @default.
• W2071092103 countsByYear W20710921032017 @default.
• W2071092103 crossrefType "journal-article" @default.
• W2071092103 hasAuthorship W2071092103A5012114797 @default.
• W2071092103 hasAuthorship W2071092103A5064558535 @default.
• W2071092103 hasConcept C101991246 @default.
• W2071092103 hasConcept C105795698 @default.
• W2071092103 hasConcept C111030470 @default.
• W2071092103 hasConcept C120665830 @default.
• W2071092103 hasConcept C121332964 @default.
• W2071092103 hasConcept C121864883 @default.
• W2071092103 hasConcept C144024400 @default.
• W2071092103 hasConcept C149923435 @default.
• W2071092103 hasConcept C159886148 @default.
• W2071092103 hasConcept C169733012 @default.
• W2071092103 hasConcept C189569837 @default.
• W2071092103 hasConcept C2778205388 @default.
• W2071092103 hasConcept C2908647359 @default.
• W2071092103 hasConcept C33923547 @default.
• W2071092103 hasConcept C41008148 @default.
• W2071092103 hasConcept C47559259 @default.
• W2071092103 hasConcept C98763669 @default.
• W2071092103 hasConceptScore W2071092103C101991246 @default.
• W2071092103 hasConceptScore W2071092103C105795698 @default.
• W2071092103 hasConceptScore W2071092103C111030470 @default.
• W2071092103 hasConceptScore W2071092103C120665830 @default.
• W2071092103 hasConceptScore W2071092103C121332964 @default.
• W2071092103 hasConceptScore W2071092103C121864883 @default.
• W2071092103 hasConceptScore W2071092103C144024400 @default.
• W2071092103 hasConceptScore W2071092103C149923435 @default.
• W2071092103 hasConceptScore W2071092103C159886148 @default.
• W2071092103 hasConceptScore W2071092103C169733012 @default.
• W2071092103 hasConceptScore W2071092103C189569837 @default.
• W2071092103 hasConceptScore W2071092103C2778205388 @default.
• W2071092103 hasConceptScore W2071092103C2908647359 @default.
• W2071092103 hasConceptScore W2071092103C33923547 @default.
• W2071092103 hasConceptScore W2071092103C41008148 @default.
• W2071092103 hasConceptScore W2071092103C47559259 @default.
• W2071092103 hasConceptScore W2071092103C98763669 @default.
• W2071092103 hasIssue "1-2" @default.
• W2071092103 hasLocation W20710921031 @default.
• W2071092103 hasOpenAccess W2071092103 @default.
• W2071092103 hasPrimaryLocation W20710921031 @default.
• W2071092103 hasRelatedWork W1509375917 @default.
• W2071092103 hasRelatedWork W1973755975 @default.
• W2071092103 hasRelatedWork W1973908629 @default.
• W2071092103 hasRelatedWork W2010639373 @default.
• W2071092103 hasRelatedWork W2043122210 @default.
• W2071092103 hasRelatedWork W2134309462 @default.
• W2071092103 hasRelatedWork W2758236869 @default.
• W2071092103 hasRelatedWork W2808557427 @default.
• W2071092103 hasRelatedWork W3041311580 @default.
• W2071092103 hasRelatedWork W4236565037 @default.
• W2071092103 hasVolume "192" @default.
• W2071092103 isParatext "false" @default.

• next