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Differences, Seasonal Variations and Influencing Factors of Soil CO₂ Concentration in Suburban Wasteland-Forestland-Grassland Ecosystems

SU Xiaoman, GUO Shuwen, LI Hongbo, LU Qiaogai, Lü Jiabao, LI Fang

Acta Scientiarum Naturalium Universitatis Pekinensis 2025, 61 (6): 1188-1200. DOI: 10.13209/j.0479-8023.2025.107

Abstract （1060）

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In order to study the differences, seasonal variations and influencing factors of soil CO₂ concentration in different ecosystems, we conducted annual fixed-point monitoring of soil CO₂ concentration, oxygen (O₂) levels, enzyme activities, and labile carbon/nitrogen indicators across suburban wasteland, forestland, and grassland ecosystems from March 2023 to February 2024. The results revealed that the grassland had the highest average annual CO₂ concentration, followed by the forest, with the wasteland having the lowest. The subsurface soil CO₂ concentration of each ecosystem was higher than that of surface layer. The soil CO₂ concentration of the three ecosystems was high in summer and low in winter, and was in the middle in spring and autumn. There were disparities in soil physical and chemical properties, carbon and nitrogen contents, and hydrolase activities among different ecosystems. In all ecosystems, the soil CO₂ concentration increased exponentially with rises in air temperature, soil temperature and water content, yet displayed an exponential negative correlation with oxygen concentration.

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Root Traits Variation in Inner Mongolia Grassland of China

MA Fang, ZENG Hui, LI Hongbo, MA Zeqing, GUO Dali

Acta Scientiarum Naturalium Universitatis Pekinensis 2019, 55 (2): 387-396. DOI: 10.13209/j.0479-8023.2019.003

Abstract （1925）

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The authors measured root morphological and architectural traits of 22 different dominant plant species across 16 Inner Mongolia grassland sites along soil water gradients, and analyzed the response of these root traits (diameter, length, SRL, RTD, BrIntensity and BrRatio) to four environmental factors (MAT, MAP, Soil N and Soil C). The results showed that variation of absorptive root diameter, tissue density and specific root length among different species was 7, 9, and 15 times, respectively. There was a significant positive correlation between root diameter and lateral root length, but negative correlation between root diameter and root branching intensity. Responses of both absorptive and non-absorptive roots to precipitation and soil nitrogen were species-specific. When using different combinations of root traits to describe plant adaptation strategies, different species’ root traits respond to environmental changes with different degrees and direction of variation, resulting in a diversity of plant adaptation strategies.

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Social Network Compression Based on the Importance of the Community Nodes

LI Hongbo,ZHANG Jianpei,YANG Jing,BAI Jinbo,CHU Yan,ZHANG Lejun

Acta Scientiarum Naturalium Universitatis Pekinensis

Abstract （1033）

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In response to the inadequacies of current graph compression methods, such as higher time complexity, dependence on experiences to set parameters, too many parameters to adjust, compression loss, ignoring the community structure of network, a social network compression method is proposed based on the importance of the community nodes. The method include community discovery algorithm (GS) based on greedy strategy and social network compression algorithm (SNC). Adopting topological potential theory GS algorithm is not only capable of discovering communities but also capable of mining important nodes in the communities. SNC algorithm takes communities as targets, achieves lossless compression while maintaining the connections between communities, and keeps important nodes in communities or basic community structure if necessary. The feasibility and effectiveness of the method are verified in experiments.

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