Community stability of free-living and particle-attached prokaryotes in
coastal waters across four seasons: insights from 9.5 years of weekly sampling

Marine microbial communities play a pivotal role in the sustain- ability of aquatic ecosystems by being instrumental in nutrient cycling, organic matter decomposition, and global biogeochemical processes (DeLong and Karl, 2005; Pomeroy etal., 2007). Given their fundamental ecological functions, disruptions in the stability of these microbial en- tities may lead to shifts in nutrient availability, alterations in food web dynamics, and cascading effects throughout the ecosystem (Allisonand Martiny, 2008; Lee et al., 2024). Stability in this context is shaped by complex patterns of interactions and co-occurrence among microbial taxa, which are influenced by biotic and abiotic factors, including sea- sonal environmental variations, such as temperature fluctuations and nutrient dynamics (Fuhrman et al., 2015; Needham and Fuhrman, 2016). These environmental drivers can alter microbial community composition and function, thereby modulating their capacity to support ecosystem processes. Understanding the dynamics underlying microbial stability is therefore crucial for predicting community responses to ongoing and future environmental changes, ultimately contributing to the conservation of marine ecosystem structure and function.
The analysis of microbial networks based on co-occurrence patterns, where nodes represent amplicon sequence variants (ASVs), unique sequences inferred from high-throughput sequencing data, and edges are considered potential interactions derived from correlations between them, is a valuable tool for estimating community stability and applying reductionist approaches to complex ecological relationships (Landi et al., 2018; Yang et al., 2024). From a topological perspective, computing the centrality of nodes within these networks allows identi- fication of keystone taxa that contribute to connectivity and stability, along with their specific ecological functions (e.g., connectors, module hubs, and network hubs). Based on this concept, the network can be conceptualized as a collection of modules—distinct groups of closely interconnected taxa—that indicate ecological processes, highlighting preferences for specific niches and habitats (Liu et al., 2022b). The response of each module to environmental changes may vary, even though species within a module generally favor particular ecological conditions, as the underlying drivers may differ (Cram et al., 2015). These insights, in turn, can provide the foundation for assessing mi- crobial community stability through the indices cohesion and robust- ness, both of which reflect resistance to external perturbations.
Cohesion and robustness are indices for estimating community sta- bility, serving as a measure of resistance to external perturbations. The cohesion index, derived from relative abundance and connectedness of ASVs, characterizes interspecific interactions, where negative cohesion values indicate a predominance of negative interspecific interactions (e. g., competition or antagonism), which can stabilize community dy- namics by mitigating fluctuations through negative feedback mecha- nisms (Herren and McMahon, 2017). In contrast, positive cohesion values suggest a predominance of positive interspecific interactions (e. g., mutualism or cooperation), which may amplify external disturbances and enhance fluctuations in community dynamics, potentially leading to instability. This index, therefore, serves as a proxy for a community's potential to buffer against external disturbances and maintain structural integrity. Robustness, in addition, provides a complementary measure of stability by assessing the degree of structural connectivity loss in mi- crobial co-occurrence networks (Xiao et al., 2022). This is evaluated through simulated random node removal, where taxa are removed one by one to quantify network fragmentation. Networks with higher robustness retain connectivity despite disturbances, whereas those with lower robustness experience rapid structural disintegration. Unlike resilience, which pertains to the rate of recovery following a distur- bance, these indices measure the ability to withstand structural changes, aligning more closely with resistance.
Due to the disparities in habitats and the resulting characteristic ecological adaptations, many studies on freshwater and marine micro- bial ecosystems classify prokaryotic communities into two groups: free- living (FL) and particle-attached (PA) communities (Wang et al., 2020). It is well-established that FL and PA microbiomes play distinct roles in marine ecosystems, with FL communities primarily involved in the turnover of dissolved organic carbon (DOC), and PA communities playing a key role in the degradation and attenuation of particulate organic carbon (POC) (Dang and Lovell, 2016; Pham etal., 2022; Salazar et al., 2015). These communities also exhibit differential responses to environmental factors, with FL microbiomes being more broadly influ- enced by water column physicochemical dynamics, whereas PA micro- biomes are more closely associated with particulate organic matter (POM) characteristics and fluxes (Zhang et al., 2007). Although much research has focused on the spatiotemporal variation and succession dynamics of these communities, their stability and the mechanisms that govern them have received less attention. The contrasting environ- mental conditions surrounding these two communities suggest potential differences in community stability patterns, keystone taxa, and regula- tory mechanisms. Tackling this critical gap is essential for a more comprehensive understanding of marine microbial ecology, necessi- tating extensive and longitudinal studies that incorporate these vari- ables to elucidate broader ecological implications.
The sampling point, Port Shelter, undergoes seasonal water mass replacement driven by monsoon-induced hydrodynamic shifts,including the exchange of coastal and oceanic waters (Wong et al., 2022). To date, many studies have revealed that the structure and function of microbial communities exhibit seasonal dynamics mainly driven by fluctuations in environmental factors, which have highlighted the importance of environmental influences on microbial communities. In this study, we aimed to address existing research gaps by assessing the stability of marine microbial communities across four seasons, with a focus on resistance, defined as the capacity of communities to withstand environmental disturbances (Grimm and Wissel, 1997). We quantified the resistance ofFL and PA communities in each season and investigated the underlying regulatory mechanisms, leveraging a long-term temporal dataset collected weekly over 9.5 years. Our analysis involved recon- structing microbial community networks across seasons to compare stability (i.e., resistance) and to elucidate its relationship with complexity. Additionally, using Structural Equation Models (Grace, 2006) and Random Forest models (Breiman,2001), we examined how biotic and abiotic factors regulate microbial community stability and verified the contribution of potential keystone taxa to microbial com- munity stability.
Based on a network analysis, we tested three key hypotheses: (1) FL and PA communities may have distinct compositions, each potentially harboring unique keystone taxa that contribute to their stability; (2) the stability of ecological networks may show seasonal trends, with more complex networks demonstrating higher stability, and these trends may reflect habitat-specific dynamics of FL and PA communities; and (3) the relative importance of biotic and abiotic factors in regulating stability may be influenced by habitat differences, with biotic factors playing a larger role in PA communities and abiotic factors more prominent in FL communities. This study can advance our understanding of marine mi- crobial community stability by providing detailed insights into the seasonal dynamics and niche differentiation of FL and PA prokaryotes, which not only bridges current knowledge gaps but also lays the groundwork for future studies exploring microbial stability in other marine contexts.