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Bilberry vs. cowberry in a Scots pine boreal forest: Exclusion or coexistence in a post-fire succession?

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  • Logofet, Dmitrii O.
  • Maslov, Alexander A.

Abstract

Although the famous competition exclusion principle was thoroughly elaborated in the framework of multispecies population models, its illustrations with field data were facing certain obstacles. The data we deal with were collected by 6 consecutive examinations of bilberry (Vaccinium myrtillus) and cowberry (V. vitis-idaea) presence/absence in 20 × 20 cm quadrats located along permanent transects in a Scots pine boreal forest. These data feature a great sample size (2000 quadrats×6 examinations) and a 5-year interval for each pair of examination/re-examination, and the data have enabled us to construct a Markov chain model for the fine-scale dynamics of these dominant species at the later stages of post-fire succession. The discrete-time nonautonomous model consists of the five time-dependent, one-step transition matrices that describe changes occurring in the quadrat status for the 5 years in the following 4 terms: species-free quadrat; bilberry alone, cowberry alone, both species. Calibrated on the data, each one-step transition matrix transforms the current distribution of quadrats among their statuses exactly to the next one observed and yields a steady-state distribution as its (time-specific) positive eigenvector. Step-by-step variations in the elements of transition matrices do affect the components of the corresponding eigenvectors, but do not change the dominance relationships among them.

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  • Logofet, Dmitrii O. & Maslov, Alexander A., 2019. "Bilberry vs. cowberry in a Scots pine boreal forest: Exclusion or coexistence in a post-fire succession?," Ecological Modelling, Elsevier, vol. 401(C), pages 134-143.
  • Handle: RePEc:eee:ecomod:v:401:y:2019:i:c:p:134-143
    DOI: 10.1016/j.ecolmodel.2018.10.002
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    References listed on IDEAS

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    1. Politi, Tiziano & Popolizio, Marina, 2015. "On stochasticity preserving methods for the computation of the matrix pth root," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 110(C), pages 53-68.
    2. Chuang, Chin-Wei & Lin, Chao-Yuan & Chien, Chang-Hai & Chou, Wen-Chieh, 2011. "Application of Markov-chain model for vegetation restoration assessment at landslide areas caused by a catastrophic earthquake in Central Taiwan," Ecological Modelling, Elsevier, vol. 222(3), pages 835-845.
    3. Logofet, Dmitrii O., 2013. "Projection matrices in variable environments: λ1 in theory and practice," Ecological Modelling, Elsevier, vol. 251(C), pages 307-311.
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    1. Logofet, Dmitrii O., 2019. "Bilberry vs. cowberry in a scots pine boreal forest. II. Alternate modes of prediction," Ecological Modelling, Elsevier, vol. 405(C), pages 43-50.
    2. Maslov, Alexander A. & Logofet, Dmitrii O., 2020. "Bilberry vs. cowberry in a Scots pine boreal forest: III. Another forest, another method, and similar conclusions," Ecological Modelling, Elsevier, vol. 431(C).
    3. Logofet, Dmitrii O. & Maslov, Alexander A., 2023. "Markov chain retrospective analysis or how to detect a position of the monitoring period in the course of postfire succession," Ecological Modelling, Elsevier, vol. 484(C).
    4. Frolov, Pavel & Shanin, Vladimir & Zubkova, Elena & Bykhovets, Sergey & Grabarnik, Pavel, 2020. "CAMPUS-S – The model of ground layer vegetation populations in forest ecosystems and their contribution to the dynamics of carbon and nitrogen. I. Problem formulation and description of the model," Ecological Modelling, Elsevier, vol. 431(C).

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