Byers Alexa K, Wakelin Steve A, Condron Leo, Black Amanda
Bioprotection Aotearoa, Lincoln University, P.O. Box 85084, Lincoln, 7647, New Zealand.
Scion, Riccarton, Christchurch, 8011, New Zealand.
Microb Ecol. 2025 Jan 7;87(1):167. doi: 10.1007/s00248-024-02487-9.
To understand the effects of agricultural land use change and management on soil carbon (C) cycling, it is crucial to examine how these changes can influence microbial soil C cycling. Network analysis can offer insights into the structure, complexity, and stability of the soil microbiome in response to environmental disturbances, including land use change. Using SparCC-based co-occurrence networks, we studied how land use change impacts the connectivity, complexity, and stability of microbial C-cycling gene networks across an agricultural mosaic landscape in Canterbury, New Zealand. The most densely connected networks were found in land uses that were under the most intensive agricultural management, or under naturally regenerating vegetation. The microbial C-cycling gene networks from both land uses presented high network connectivity, low modularity, and a low proportion of negative gene interactions. In contrast, microbial C-cycling genes from native forests, which had the most stable and undisturbed plant cover, had the lowest network connectivity, highest modularity, and a greater proportion of negative gene interactions. Although the differences in total soil C content between land uses were small, the large effects of land use on the network structure of microbial C-cycling genes may have important implications for long-term microbial soil C cycling. Furthermore, this research highlights the value of using microbial network analysis to study the metabolic gene interactions shaping the functional structure of soil microbial communities in a manner not typically captured by more traditional forms of microbial diversity analysis.
为了解农业土地利用变化与管理对土壤碳（C）循环的影响，研究这些变化如何影响土壤微生物碳循环至关重要。网络分析能够洞察土壤微生物群落响应包括土地利用变化在内的环境干扰时的结构、复杂性和稳定性。利用基于SparCC的共生网络，我们研究了土地利用变化如何影响新西兰坎特伯雷一个农业镶嵌景观中微生物碳循环基因网络的连通性、复杂性和稳定性。在农业管理最集约或自然恢复植被的土地利用类型中发现了连接最密集的网络。这两种土地利用类型的微生物碳循环基因网络均呈现出高网络连通性、低模块性和低比例的负基因相互作用。相比之下，原生森林中微生物碳循环基因的网络连通性最低、模块性最高且负基因相互作用比例更大，原生森林拥有最稳定且未受干扰的植被覆盖。尽管不同土地利用类型之间土壤总碳含量差异较小，但土地利用对微生物碳循环基因网络结构的巨大影响可能对土壤微生物长期碳循环具有重要意义。此外，本研究凸显了利用微生物网络分析来研究塑造土壤微生物群落功能结构的代谢基因相互作用的价值，而这是传统形式的微生物多样性分析通常无法捕捉到的。
