Different geomorphological units such as mountains, forests, fields, grasslands, sands and water, despite their distinct morphologies, are interconnected through micro-ecosystems that collectively maintain the balance of regional ecology. However, there is a lack of research concerning the spatial correlation among different landscape micro-ecosystems within a catchment area, hindering a comprehensive understanding of watershed systematic evolution across various landscape micro-ecosystems. To address this gap, seasonal variations in bacterial community structure and ecological network connectivity were investigated across different geomorphological units in the eastern Ulansuhai Lake Basin, North China. Water and soil samples were collected in May (beginning of the growing season, 23 samples) and November (end of the growing season, 20 samples) 2021. The diversity of bacterial communities within the Multi Geomorphological Unit System (MGUS) comprising “mountain, forest, field, grassland, sand and water” increased from May to November due to precipitation and human cultivation influences. Environmental characteristics, such as water and soil variations, exert a greater influence on bacterial community structure than differences in landscape units. The stability of the macro-ecological network structure within the MGUS was relatively high, with “water” playing a pivotal role in connectivity (the average betweenness centrality value of “water” was more than twice that of the other landscape samples). This led to the gradual emergence of deterministic processes in the construction of the bacterial community, shifting from stochastic processes (90.8 % drift effect in May) to biotic interactions (29.2 % heterogeneous selection in November). Furthermore, the bacterial community structure exhibited “macroscopic stability, with ‘water’ assuming a central role, while also showing microscopic variations, reflecting fluctuations in the contribution of dominant bacterial genera to the network structure over time”. Our study offers a core information analysis aimed at characterizing the temporal and spatial evolution of microbial community structure within an MGUS, thereby addressing a gap in microbial macroecology.
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