A study of plant community stability in the lower Tarim River based on MLR and MLP and improved Morneau dynamics model

Authors

  • Yin Yuan

DOI:

https://doi.org/10.54097/hset.v63i.10803

Keywords:

NDVI; Multiple Linear Regression Prediction Model; MLP; Monod Models.

Abstract

Taking the lower reaches of Tarim River as the research area, drought adaptability and species number of plant communities were studied. Due to the simple, dry and water-scarce topography, the plant community structure in this region is relatively uncomplicated, so it is a good area for analysis. In this paper, Monod model, a macroscopical internal mechanism of long-term interaction between plant community and environment, is proposed. The Monod model is derived from the growth of microorganisms and therefore needs to be optimized when considering plants: self-inhibition characteristics are introduced to obtain an optimized mechanism model. Based on this model, the conditions to be met when the change rate of plant population density is positive are solved in this paper. Combined with the actual number of species, it is considered that the community needs at least three different plant species to benefit, and the situation caused by the increase of species is discussed. Different types of plants have different NDVI, so they have different effects on the model. In this paper, the analysis is divided into three types of plants, and the effect of changing drought frequency is considered. Since there are only two regions with different drought frequency and easy to be divided, this paper introduced multiple linear regression models in the two regions respectively, extracted the general model from the regression coefficient relationship between the two regions, and analyzed the NDVI regression coefficient of the two regions at the same time, to obtain the general rule of the effect of less drought on the number of species. Due to the lack of pollution data and habitat data in the study area, this paper derived a model of negative environmental factors from the mechanism model, and finally combined with the easily available pm2.5 index. Based on the established model, this paper hopes to help ensure community survival in terms of increasing resource growth rates and preserving diversity.

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References

Li Junli, Xiao Hao, Shen Zhanfeng, Bai Jie. Vegetation dynamics and its response to ecological water transfer in the lower reaches of Tarim River from 2013 to 2018[J]. Arid Zone Research, 2020, 37(04): 985-992.

Sun Tianyao, Li Xuemei, Xu Min, Zhang Mengsheng. Spatio-temporal pattern of vegetation coverage in the Tarim River Basin from 2000 to 2018[J]. Arid Land Geography, 2020, 43(02): 415-424.

He Rongxiao, Lei Jinrui, Yang Fan. Study on the correlation and spatial distribution characteristics between remote sensing vegetation index and plant diversity: a case study of the central urban area of Haikou City [J]. Guihaia, 2021, 41(03): 351-361.

Gao Qing, Ailixier Kuerban, Xiao Hao. Spatiotemporal changes of vegetation in the lower reaches of Tarim River[J]. Journal of Natural Resources, 2019, 34(03): 624-632.

Yang Qi. SVM prediction and classification of the minimum population reconstruction areas for wild plants on Hainan Island[D]. Hainan University, 2014.

Li Weihong, Zhou Honghua, Yang Xiaoming, Ding Hui. Response of aboveground biomass spatial distribution of grassland plant community to groundwater in arid desert area[J]. Acta Prataculturae Sinica, 2010, 19(05): 186- 195.

Laliberté, E., Norton, D. A., & Scott, D. (2013). Contrasting effects of productivity and disturbance on plant functional diversity at local and metacommunity scales. Journal of Vegetation Science, 24(5), 834-842.

Tilman, D., Reich, P. B., & Knops, J. M. (2006). Biodiversity and ecosystem stability in a decade-long grassland experiment. Nature, 441(7093), 629-632.

Isbell, F., Tilman, D., Polasky, S., Binder, S., & Hawthorne, P. (2013). Low biodiversity state persists two decades after cessation of nutrient enrichment. Nature, 494(7437), 231-234.

Adler, P. B., Seabloom, E. W., Borer, E. T., Hillebrand, H., Hautier, Y., Hector, A., ... & Grace, J. B. (2011). Productivity is a poor predictor of plant species richness. Science, 333(6050), 1750-1753.

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Published

08-08-2023