Chin J Plant Ecol

   

Spatial pattern of plantation biomass in different stand ages and its influencing factors in Beijing

Liu Xinyue1,Liping WANG2,Chunhe LIU2,Yanli Sun3,Peng LIU4,Yun TianXin JIAZha tianshan   

  • Received:2023-11-07 Revised:2024-04-25 Published:2024-05-07
  • Contact: Zha tianshan

Abstract: Abstract: Aims Elucidating the spatial pattern of plantation biomass and its influencing factors, and revealing optimum range of influencing factors is important for management of urban forest plantation. Methods We used the Biomass Expansion Factor to estimate plantation biomass based on forest inventory data in Beijing. Linear regression and polynomial fitting method were used to analyze the response of biomass to influencing factors. Random forest was used to predict the spatial distribution in biomass, and Geodetector was used to explore the spatial correlation between biomass and climatic, vegetation, topographical, and anthropogenic factors in different-aged stands. Important findings The results showed that the biomass increased with increasing of stand ages, being 35.22 Mg/hm2, 75.42 Mg/hm2, 88.71 Mg/hm2, 96.17 Mg/hm2, 148.59 Mg/hm2 for young, middle-aged, near-mature, mature and over-mature forests, respectively. Compared to topographical factors, climatic, vegetation, and anthropogenic factors had greater influence on biomass. The response of young forest biomass to influencing factors was different with other stand ages, due to more management measures in young forest. The nighttime lights, sunshine duration and precipitation were important factors influencing the spatial pattern of biomass, with 52.91%, 51.28% and 45.75% explaining power, respectively. The interactive effect of influencing factors on spatial pattern of biomass was greater than single factor. The influence of stand age on spatial pattern of biomass was small, while the explaining power of stand age interaction with precipitation, nighttime lights, gross domestic product and population intensity was more than 70%. The interaction among climatic, vegetation, topographical, and anthropogenic factors affected the overall spatial pattern of biomass. There was higher biomass, when temperature was 12.26-13.03℃, precipitation was 526.81-542.63 mm, sunshine duration was 2543.13-2602.80 h, and NDVI was 0.46-0.59. Therefore, the spatial pattern of biomass was caused by multiple factors. It is necessary to consider the site characteristics for obtaining higher biomass. These results would contribute to understanding the relationship between plantation biomass and influencing factors, and provide a scientific basis for management of plantation.

Key words: Plantation, Biomass, Spatial pattern, Geodetector