Rare plants distribution modeling using indirect environmental gradients

Dyakov, N. R.

doi:10.1134/s1067413615040074

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…The use of mathematical modeling for evaluation of the status of plant species threatened with extinction based on their distribution has been described in many papers (Aguilar‐Soto et al, 2015; Dyakov, 2015; McCune, 2016; Rosner‐Katz, 2018; Wang et al, 2015). Examples of the proposed models include statistical models (generalized linear models [GLM] Bolker et al, 2009, generalized additive models [GAM] Yee & Mitchell, 2009, regression tree models [RTM] Timilsina et al, 2013), dynamic models (DM; Renton et al, 2011), and stochastic models (SM; Ovaskainen & Meerson, 2010).…”

Section: Introductionmentioning

confidence: 99%

Bayesian network model informs on the impact of biotic and abiotic factors on the population characteristics of an endangered plant species

Sienkiewicz

Łaska

2022

Population Ecology

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Preservation of the endangered plant species requires knowledge of the impact of environmental factors on their populations. This study was undertaken to evaluate the potential of a Bayesian network (BN) model to analyze the impact of habitat conditions on the current characteristics of Pulsatilla patens (L.) Mill. population in NE Poland. The model was based on field data collected in 2011-2015 from 47 sites in the four largest forest complexes of NE Poland. The causal network between (1) the biotic and (2) abiotic factors as well as morphological-developmental features of individuals and demographic features of populations (20 attributes, 1573 records) was made using the BayesianSearch Algorithm in GeNIe 2.0. The results indicate that the greatest impact on the population features had the number of competing species in forest undergrowth and exposition of slopes. Diagnostic testing and sensitivity analysis revealed that these factors were the major variables determining the size of the population, developmental phase, and the size of individuals. Tenfold cross-validation revealed that this model was the most effective to analyze the impact of habitat conditions on the presence of generative shoots, developmental phase, and juvenile shoots. The optimal levels of factors following from the BN modeling of the impact of habitat conditions on the characteristics of the population will allow regular growth (size of individuals) and development (life cycle of individuals) of a given endangered species.

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Section: Introductionmentioning

confidence: 99%

Bayesian network model informs on the impact of biotic and abiotic factors on the population characteristics of an endangered plant species

Sienkiewicz

Łaska

2022

Population Ecology

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In defense of elemental currencies: can ecological stoichiometry stand as a framework for terrestrial herbivore nutritional ecology?

et al. 2022

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Bayesian belief networks: a potential tool for conservation planning of endangered plant species populations

Sienkiewicz

Łaska

2022

Journal of Plant Ecology

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Bayesian belief networks (BBN) have been increasingly used as a potential decision supporting tool useful in conservation management. We assessed the application of the BBN model to support management in conservation planning of Pulsatilla patens (L.) Mill., the endangered plant species on a European scale, as an example. The Bayesian network approach was used to develop a model of the impact of biotic and abiotic variables on the morphological-developmental features and demographic features of the population in NE Poland. Field data collected from the total number of 47 sites in the 4 largest forest complexes were used to develop a model using GeNIe 2.0. The diagnostic testing and sensitivity analysis indicated that the greatest impact on the population features was the number of competing species in the forest undergrowth. Validation has shown that the developed model is effective for evaluation of the impact of habitat conditions on the population features deciding about the reproduction of this taxon. The BBN model was also used to define optimal habitat conditions ensuring regular growth and development of P. patens. Finally, we indicated the protective treatment to help preserving the species considered. Therefore, the developed model is recommended as a potential tool to support decision-making aimed at the conservation planning of endangered plant species.

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Rare plants distribution modeling using indirect environmental gradients

Cited by 3 publications

References 21 publications

Bayesian network model informs on the impact of biotic and abiotic factors on the population characteristics of an endangered plant species

Bayesian network model informs on the impact of biotic and abiotic factors on the population characteristics of an endangered plant species

In defense of elemental currencies: can ecological stoichiometry stand as a framework for terrestrial herbivore nutritional ecology?

Bayesian belief networks: a potential tool for conservation planning of endangered plant species populations

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