Soil organic matter (SOM) is the largest actively cycling reservoir of terrestrial carbon (C), and the majority of SOM in Earth's mineral soils (~65%) is mineral‐associated organic matter (MAOM). Thus, the formation and fate of MAOM can exert substantial influence on the global C cycle. To predict future changes to Earth's climate, it is critical to mechanistically understand the processes by which MAOM is formed and decomposed, and to accurately represent this process‐based understanding in biogeochemical and Earth system models. In this review, we use a trait‐based framework to synthesize the interacting roles of plants, soil micro‐organisms, and the mineral matrix in regulating MAOM formation and decomposition. Our proposed framework differentiates between plant and microbial traits that influence total OM inputs to the soil (‘feedstock traits’) versus traits that influence the proportion of OM inputs that are ultimately incorporated into MAOM (‘MAOM formation traits’). We discuss how these feedstock and MAOM formation traits may be altered by warming, altered precipitation and elevated carbon dioxide. At a planetary scale, these feedstock and MAOM formation traits help shape the distribution of MAOM across Earth's biomes, and modulate biome‐specific responses of MAOM to climate change. We leverage a global synthesis of MAOM measurements to provide estimates of the total amount of MAOM‐C globally (~840–1540 Pg C; 34%–51% of total terrestrial organic C), and its distribution across Earth's biomes. We show that MAOM‐C concentration is highest in temperate forests and grasslands, and lowest in shrublands and savannas. Grasslands and croplands have the highest proportion of soil organic carbon (SOC) in the MAOM fraction (i.e. the MAOM‐C:SOC ratio), while boreal forests and tundra have the lowest MAOM‐C:SOC ratio. Drawing on our trait framework, we then review experimental data and posit the effects of climate change on MAOM pools in different biomes. We conclude by discussing how MAOM is integrated into soil C models, and how feedstock and MAOM formation traits may be included in these models. We also summarize the projected fate of MAOM under climate change scenarios (Representative Concentration Pathways 4.5 and 8.5) and discuss key model uncertainties. Read the free Plain Language Summary for this article on the Journal blog.

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Predicting and mitigating changes in soil carbon (C) stocks under global change requires a coherent understanding of the factors regulating soil organic matter (SOM) formation and persistence, including knowledge of the direct sources of SOM (plants vs. microbes). In recent years, conceptual models of SOM formation have emphasized the primacy of microbial-derived organic matter inputs, proposing that microbial physiological traits (e.g., growth efficiency) are dominant controls on SOM quantity.

The physical and chemical changes that accompany permafrost thaw directly influence the microbial communities that mediate the decomposition of formerly frozen organic matter, leading to uncertainty in permafrost-climate feedbacks. Although changes to microbial metabolism and community structure are documented following thaw, the generality of post-thaw assembly patterns across permafrost soils of the world remains uncertain, limiting our ability to predict biogeochemistry and microbial community responses to climate change. Based on our review of the Arctic microbiome, permafrost microbiology, and community ecology, we propose that Assembly Theory provides a framework to better understand thaw-mediated microbiome changes and the implications for community function and climate feedbacks. This framework posits that the prevalence of deterministic or stochastic processes indicates whether the community is well-suited to thrive in changing environmental conditions. We predict that on a short timescale and following high-disturbance thaw (e.g., thermokarst), stochasticity dominates post-thaw microbiome assembly, suggesting that functional predictions will be aided by detailed information about the microbiome. At a longer timescale and lower-intensity disturbance (e.g., active layer deepening), deterministic processes likely dominate, making environmental parameters sufficient for predicting function. We propose that the contribution of stochastic and deterministic processes to post-thaw microbiome assembly depends on the characteristics of the thaw disturbance, as well as characteristics of the microbial community, such as the ecological and phylogenetic breadth of functional guilds, their functional redundancy, and biotic interactions. These propagate across space and time, potentially providing a means for predicting the microbial forcing of greenhouse gas feedbacks to global climate change.