Research Article

Information Signals in the Forest: Field Modeling Approach in the Environmental Context

Volume: 8 Number: 2 January 15, 2026
TR EN

Information Signals in the Forest: Field Modeling Approach in the Environmental Context

Abstract

We develop a simplified yet efficient mathematical model to describe the processes of information transfer in various communication channels within forest ecosystems, including fungal mycelia-based networks, plant bioelectric fields, and the biotic pump mechanism. Studying the forest as a distributed informational system, we present diffusion-type partial differential equations for the spread of communication signals in these channels as continuous fields, rather than discrete elements in networks. Making the basic analysis of the solutions in the form of traveling waves for 1D and 2D, we demonstrate that in each channel, there is a competition between the spatial range of the signal spread and the speed of the signals: the fastest informational signal demonstrates the highest rate of spatial decay. This correlation reflects the fundamental necessity of having several channels for transmitting and processing information in distributed systems, such as a forest, with the absence of a single center for monitoring information processes. Each channel must compromise, whether it serves for fast informational signal speed for a short range with the high decay or provides the long-range signals, but with a sufficiently lower speed. The study of multiple competing information channels corresponding to different time scales of the ecosystem evolution emphasizes the need for an integrated approach to forest studies, taking into account the diverse contributions of various ecosystem components.

Keywords

Supporting Institution

Abdullah Gül University

Project Number

Yok

Ethical Statement

No

Thanks

No

References

  1. Abramowitz, M., & Stegun, I. (1972). Handbook of mathematical functions (10th ed.). Dover.
  2. Al-Nasser, M., Al-Mansour, Y., & Al-Sayid, N. (2024). The role of mycorrhizal fungi in forest ecosystem health. Journal of Selvicoltura Asean, 1(6), 271–281.
  3. Armada-Moreira, A., Dar, A. M., Zhao, Z., Cea, C., Gelinas, J., Berggren, M., Costa, A., Khodagholy, D., & Stavrinidou, E. (2023). Plant electrophysiology with conformable organic electronics: Deciphering the propagation of Venus flytrap action potentials. Science Advances, 9, eadh4443. https://doi.org/10.1126/sciadv.adh4443
  4. Barbosa-Caro, J. C., & Wudick, M. M. (2024). Revisiting plant electric signaling: Challenging an old phenomenon with novel discoveries. Current Opinion in Plant Biology, 79, 102528.
  5. Bock, B. M., Hoeksema, J. D., Johnson, N. C., & Gehring, C. A. (2025). Evidence for common fungal networks among plants formed by a Dark Septate Endophyte in Sorghum bicolor. Communications Biology, 8, 996.
  6. Boswell, G. P., & Hopkins, S. (2012). Mycelial response to spatiotemporal nutrient heterogeneity: A velocity-jump mathematical model. Fungal Ecology, 5(2), 124–136.
  7. Bunyard, P. (2020). Winds and rain: The role of the biotic pump. International Journal of Biosensors and Bioelectronics, 6(5), 113–115.
  8. Buffi, M., Kelliher, J. M., Robinson, A. J., Gonzalez, D., Cailleau, G., Macalindong, J. A., … Bindschedler, S. (2025). Electrical signaling in fungi: Past and present challenges. FEMS Microbiology Reviews, 49, fuaf009.

Details

Primary Language

English

Subjects

Modelling and Simulation

Journal Section

Research Article

Authors

Publication Date

January 15, 2026

Submission Date

September 8, 2025

Acceptance Date

November 1, 2025

Published in Issue

Year 2026 Volume: 8 Number: 2

APA
Borisenok, S. (2026). Information Signals in the Forest: Field Modeling Approach in the Environmental Context. International Journal of Informatics and Applied Mathematics, 8(2), 1-18. https://doi.org/10.53508/ijiam.1779879
AMA
1.Borisenok S. Information Signals in the Forest: Field Modeling Approach in the Environmental Context. IJIAM. 2026;8(2):1-18. doi:10.53508/ijiam.1779879
Chicago
Borisenok, Sergey. 2026. “Information Signals in the Forest: Field Modeling Approach in the Environmental Context”. International Journal of Informatics and Applied Mathematics 8 (2): 1-18. https://doi.org/10.53508/ijiam.1779879.
EndNote
Borisenok S (January 1, 2026) Information Signals in the Forest: Field Modeling Approach in the Environmental Context. International Journal of Informatics and Applied Mathematics 8 2 1–18.
IEEE
[1]S. Borisenok, “Information Signals in the Forest: Field Modeling Approach in the Environmental Context”, IJIAM, vol. 8, no. 2, pp. 1–18, Jan. 2026, doi: 10.53508/ijiam.1779879.
ISNAD
Borisenok, Sergey. “Information Signals in the Forest: Field Modeling Approach in the Environmental Context”. International Journal of Informatics and Applied Mathematics 8/2 (January 1, 2026): 1-18. https://doi.org/10.53508/ijiam.1779879.
JAMA
1.Borisenok S. Information Signals in the Forest: Field Modeling Approach in the Environmental Context. IJIAM. 2026;8:1–18.
MLA
Borisenok, Sergey. “Information Signals in the Forest: Field Modeling Approach in the Environmental Context”. International Journal of Informatics and Applied Mathematics, vol. 8, no. 2, Jan. 2026, pp. 1-18, doi:10.53508/ijiam.1779879.
Vancouver
1.Sergey Borisenok. Information Signals in the Forest: Field Modeling Approach in the Environmental Context. IJIAM. 2026 Jan. 1;8(2):1-18. doi:10.53508/ijiam.1779879

International Journal of Informatics and Applied Mathematics