Analysis of the Evolution of Scale-Free Properties in the Complex Network of American White Moths in Liaoning Area

Sun Xiaojuan; Feng Ying; Liu Jun

doi:doi:10.11648/j.ajaf.20231106.13

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Analysis of the Evolution of Scale-Free Properties in the Complex Network of American White Moths in Liaoning Area

Sun Xiaojuan, Feng Ying^*, Liu Jun

Published in American Journal of Agriculture and Forestry (Volume 11, Issue 6)

Received: 7 October 2023 Accepted: 1 November 2023 Published: 17 November 2023

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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.

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

Keywords

American White Moth, Complex Network, Scale-Free Properties, Evolutionary Analysis

References

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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

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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

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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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@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}
}

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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  -

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Author Information

Sun Xiaojuan

Scientific Research Department, Liaoning Vocational College of Ecological Engineering, Shenyang, China
Feng Ying

Scientific Research Department, Liaoning Vocational College of Ecological Engineering, Shenyang, China

Contact Email
Liu Jun

Sankuaishi Forest Farm of Fushun County, Fushun, China

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Plain Text BibTeX RIS

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

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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

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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

Copy | 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}
}

Copy | Download

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  -

Copy | Download