Application of Bayesian networks in evaluation of current status and protection of Pulsatilla patens (L.) Mill.

Abstract

AbstractUnderstanding of the impact of environmental factors on endangered plant species provides a basis for assessment of the risk of their extinction in the near future. Of particular importance is the search for optimal environmental conditions to preserve the continued existence of endangered taxa. Thus, there is a need for a method based on mathematical modeling to connect the current status of an endangered plant species with changing environmental conditions. Using the basics of decision theory, we developed a mathematical model to assess the influence of changing habitat conditions on the current status and protection of Pulsatilla patens (L.) Mill., an endangered plant species in Europe, as an example. The mathematical model was based on the data from 43 sites in the 3 largest forest complexes in NE Poland from 2011 to 2014 (29 attributes, 1566 records). The graphical model showing significant cause‐and‐effect relations between morphological‐developmental features of individuals, demographic features of the populations, and physicochemical properties of the soil was built using the Bayesian networks in GeNIe 2.0 (University of Pittsburgh, Pittsburgh, Pennsylvania, USA). In the process of modeling with the Bayesian Search Algorithm, we also performed simulation, prediction, and optimization of the effects of selected environmental factors on growth and development of the endangered taxon. The diagnostic testing and sensitivity analysis revealed that the degree of soil acidification is the major variable determining the size of populations (number of individuals), developmental phase (juvenile, vegetative, flowering), and size of the individuals (height and diameter of ground rosette). Using the approach presented in this work, it was possible to identify a new habitat factor not known to be important at multiple scales for growth, development, and population dynamics of P. patens. The validation showed that the developed model is the most effective for evaluation of the impact of habitat conditions on the population features important for reproduction of this taxon. Therefore, the model proposed is recommended as a tool to support decision‐making aimed at conservation planning of the endangered plant species.