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Exploring of Diverse Plant Communities and Adaptation to Drought Conditions Based on Advanced Logistics Model with Variable Growth.
Guo, Yining; Liang, Longxi; Liang, Wentao.
Afiliação
  • Guo Y; Department of Automation, Guangdong University of Technology, Xiaoguwei Street, Guangzhou, Guangdong, China.
  • Liang L; Department of Automation, Guangdong University of Technology, Xiaoguwei Street, Guangzhou, Guangdong, China.
  • Liang W; Department of Automation, Guangdong University of Technology, Xiaoguwei Street, Guangzhou, Guangdong, China.
Stud Health Technol Inform ; 308: 137-145, 2023 Nov 23.
Article em En | MEDLINE | ID: mdl-38007735
ABSTRACT
Bio reciprocal symbiosis is very common in nature, such as soybeans providing food for rhizobia, which uses atmospheric nitrogen to synthesize nitrogen to provide nutrients to soybeans. This paper proposes an advanced Logistic model that adjusts to changes in precipitation and an environmental capacity parameter that varies with the level of symbiosis. The aim is to precisely depict the symbiotic relationship between plants and the interplay among symbiosis, competition, and independent growth of each population in the plant community, as precipitation changes by adapting finite difference method and tertiary Hermit interpolation. The model in this paper offers a comprehensive understanding of how plant populations interact with one another, providing valuable insights into the dynamics of plant growth and development. This paper finally finds that a combination of woody and herbaceous plants had the highest growth rate and total biomass, while herbaceous-only plants required 7 times longer to reach environmental capacity. This paper also reveals that irregular weather patterns, and different levels of species biomass can have different impacts on the recovery time of plant communities after drought or damage, and different types of pollution can have various effects on the community's regeneration, while the effect of overgrazing is the smallest.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Plantas / Secas Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Plantas / Secas Idioma: En Ano de publicação: 2023 Tipo de documento: Article