Pest infestation is the most severe forestry biological disaster, causing not only huge economic losses worldwide but also damaging the ecological environment. Evaluating the mechanism and spatial structure changes of pest population distribution in forests scientifically is crucial for understanding and solving the problem of forest pest disasters. With the continuous deepening of research on the niche principle and spatial patterns of insect populations, a research orientation that emphasizes dynamic-multidimensional-three-dimensional and cross-disciplinary integration has become the trend in future forestry biological disaster research. Applying network science analysis methods to the field of forest pest research can help explore the distribution characteristics, affected areas, and temporal and spatial changes in the spread and transmission of forest pests, effectively curb their rampant spread, and provide scientific data support for predicting and forecasting forest pests. This will have far-reaching implications for the comprehensive implementation of integrated pest management strategies. In this paper, based on a spatial influence domain network model, we selected monitoring data of the globally quarantined harmful organism, American white moth in Liaoning Province from 2009 to 2013 as the data source. We constructed a complex network of American white moth pest relationships and focused on studying the overall network's indegree and outdegree network characteristic quantities, as well as the network evolution of the peak larval months and the average degree of the network.
| Published in | American Journal of Agriculture and Forestry (Volume 11, Issue 6) |
| DOI | 10.11648/j.ajaf.20231106.13 |
| Page(s) | 228-232 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2023. Published by Science Publishing Group |
American White Moth, Complex Network, Scale-Free Properties, Evolutionary Analysis
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APA Style
Xiaojuan, S., Ying, F., Jun, L. (2023). Analysis of the Evolution of Scale-Free Properties in the Complex Network of American White Moths in Liaoning Area. American Journal of Agriculture and Forestry, 11(6), 228-232. https://doi.org/10.11648/j.ajaf.20231106.13
ACS Style
Xiaojuan, S.; Ying, F.; Jun, L. Analysis of the Evolution of Scale-Free Properties in the Complex Network of American White Moths in Liaoning Area. Am. J. Agric. For. 2023, 11(6), 228-232. doi: 10.11648/j.ajaf.20231106.13
AMA Style
Xiaojuan S, Ying F, Jun L. Analysis of the Evolution of Scale-Free Properties in the Complex Network of American White Moths in Liaoning Area. Am J Agric For. 2023;11(6):228-232. doi: 10.11648/j.ajaf.20231106.13
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Download@article{10.11648/j.ajaf.20231106.13,
author = {Sun Xiaojuan and Feng Ying and Liu Jun},
title = {Analysis of the Evolution of Scale-Free Properties in the Complex Network of American White Moths in Liaoning Area},
journal = {American Journal of Agriculture and Forestry},
volume = {11},
number = {6},
pages = {228-232},
doi = {10.11648/j.ajaf.20231106.13},
url = {https://doi.org/10.11648/j.ajaf.20231106.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajaf.20231106.13},
abstract = {Pest infestation is the most severe forestry biological disaster, causing not only huge economic losses worldwide but also damaging the ecological environment. Evaluating the mechanism and spatial structure changes of pest population distribution in forests scientifically is crucial for understanding and solving the problem of forest pest disasters. With the continuous deepening of research on the niche principle and spatial patterns of insect populations, a research orientation that emphasizes dynamic-multidimensional-three-dimensional and cross-disciplinary integration has become the trend in future forestry biological disaster research. Applying network science analysis methods to the field of forest pest research can help explore the distribution characteristics, affected areas, and temporal and spatial changes in the spread and transmission of forest pests, effectively curb their rampant spread, and provide scientific data support for predicting and forecasting forest pests. This will have far-reaching implications for the comprehensive implementation of integrated pest management strategies. In this paper, based on a spatial influence domain network model, we selected monitoring data of the globally quarantined harmful organism, American white moth in Liaoning Province from 2009 to 2013 as the data source. We constructed a complex network of American white moth pest relationships and focused on studying the overall network's indegree and outdegree network characteristic quantities, as well as the network evolution of the peak larval months and the average degree of the network.
},
year = {2023}
}
TY - JOUR T1 - Analysis of the Evolution of Scale-Free Properties in the Complex Network of American White Moths in Liaoning Area AU - Sun Xiaojuan AU - Feng Ying AU - Liu Jun Y1 - 2023/11/17 PY - 2023 N1 - https://doi.org/10.11648/j.ajaf.20231106.13 DO - 10.11648/j.ajaf.20231106.13 T2 - American Journal of Agriculture and Forestry JF - American Journal of Agriculture and Forestry JO - American Journal of Agriculture and Forestry SP - 228 EP - 232 PB - Science Publishing Group SN - 2330-8591 UR - https://doi.org/10.11648/j.ajaf.20231106.13 AB - Pest infestation is the most severe forestry biological disaster, causing not only huge economic losses worldwide but also damaging the ecological environment. Evaluating the mechanism and spatial structure changes of pest population distribution in forests scientifically is crucial for understanding and solving the problem of forest pest disasters. With the continuous deepening of research on the niche principle and spatial patterns of insect populations, a research orientation that emphasizes dynamic-multidimensional-three-dimensional and cross-disciplinary integration has become the trend in future forestry biological disaster research. Applying network science analysis methods to the field of forest pest research can help explore the distribution characteristics, affected areas, and temporal and spatial changes in the spread and transmission of forest pests, effectively curb their rampant spread, and provide scientific data support for predicting and forecasting forest pests. This will have far-reaching implications for the comprehensive implementation of integrated pest management strategies. In this paper, based on a spatial influence domain network model, we selected monitoring data of the globally quarantined harmful organism, American white moth in Liaoning Province from 2009 to 2013 as the data source. We constructed a complex network of American white moth pest relationships and focused on studying the overall network's indegree and outdegree network characteristic quantities, as well as the network evolution of the peak larval months and the average degree of the network. VL - 11 IS - 6 ER -
Scientific Research Department, Liaoning Vocational College of Ecological Engineering, Shenyang, China
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