Research of Grassland Ecosystems and Communities Based on A Cyclical Model
DOI:
https://doi.org/10.54097/zmadf992Keywords:
Cyclical model, TOPSIS method, Radial Basis Function Neural Network Algorithm, Simpson diversity indices, Shannon-Wiener indexes.Abstract
In grassland ecosystems, different plants rely on and interact with each other, as well as with their geographic space, so that an inseparable and interdependent plant community is formed. To figure out the evolution of plant communities and the interactions between different plant species under dry conditions, a cyclical plant community model is established from two aspects that vary with time. One part of the cyclical model is a model of plant environmental adaptability based on the TOPSIS method and the Radial Basis Function Neural Network Algorithm. To quantify the adaptation of plants to the environment, the Plant Life-Form Adaptation Index (PLFAI) is introduced and the growth of different species is calculated in the model. The other part of the model introduces a model of plant species diversity and ecological niche to analyze the ecological niche width and spatial distribution characteristics of different plants over time, which is based on the Simpson diversity indices and Shannon-Wiener indexes. The niche concept emphasizes the spatial and temporal changes of species and is more concerned about how environmental factors affect the niche and how species adapt and respond to these changes. Also, small influences of human activities are incorporated into the model's scope by giving samples of White Gaussian Noise. Those contributory factors are negligible but necessary. These parts summarize the plant ecological environment impact model, which can be used to study the long-term survival of plant communities. By studying and using the models above, it is easy to conclude the evolution of grassland plant communities and the interactions among plants under drought conditions.
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