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Disturbances fundamentally alter ecosystem functions, yet predicting their impacts remains a key scientific challenge. While the study of disturbances is ubiquitous across many ecological disciplines, there is no agreed-upon, cross-disciplinary foundation for discussing or quantifying the complexity of disturbances, and no consistent terminology or methodologies exist. This inconsistency presents an increasingly urgent challenge due to accelerating global change and the threat of interacting disturbances that can destabilize ecosystem responses. By harvesting the expertise of an interdisciplinary cohort of contributors spanning 42 institutions across 15 countries, we identified an essential limitation in disturbance ecology: the word ‘disturbance’ is used interchangeably to refer to both the events that cause, and the consequences of, ecological change, despite fundamental distinctions between the two meanings. In response, we developed a generalizable framework of ecosystem disturbances, providing a well-defined lexicon for understanding disturbances across perspectives and scales. The framework results from ideas that resonate across multiple scientific disciplines and provides a baseline standard to compare disturbances across fields. This framework can be supplemented by discipline-specific variables to provide maximum benefit to both inter- and intra-disciplinary research. To support future syntheses and meta-analyses of disturbance research, we also encourage researchers to be explicit in how they define disturbance drivers and impacts, and we recommend minimum reporting standards that are applicable regardless of scale. Finally, we discuss the primary factors we considered when developing a baseline framework and propose four future directions to advance our interdisciplinary understanding of disturbances and their social-ecological impacts: integrating across ecological scales, understanding disturbance interactions, establishing baselines and trajectories, and developing process-based models and ecological forecasting initiatives. Our experience through this process motivates us to encourage the wider scientific community to continue to explore new approaches for leveraging Open Science principles in generating creative and multidisciplinary ideas. 

Differentiating the contributions of photosynthesis and respiration to the global carbon cycle is critical for improving predictive climate models. Carbonic anhydrase (CA) activity in leaves is responsible for the largest biosphere-atmosphere trace gas fluxes of carbonyl sulfide (COS) and the oxygen-18 isotopologue of carbon dioxide (CO18O) that both reflect gross photosynthetic rates. However, CA activity also occurs in soils and will be a source of uncertainty in the use of COS and CO18O as carbon cycle tracers until process-based constraints are improved. In this study, we measured COS and CO18O exchange rates and estimated the corresponding CA activity in soils from a range of biomes and land use types. Soil CA activity was not uniform for COS and CO2, and patterns of divergence were related to microbial community composition and CA gene expression patterns. In some cases, the same microbial taxa and CA classes catalyzed both COS and CO2 reactions in soil, but in other cases the specificity towards the two substrates differed markedly. CA activity for COS was related to fungal taxa and β-D-CA expression, whereas CA activity for CO2 was related to algal and bacterial taxa and α-CA expression. This study integrates gas exchange measurements, enzyme activity models, and characterization of soil taxonomic and genetic diversity to build connections between CA activity and the soil microbiome. Importantly, our results identify kinetic parameters to represent soil CA activity during application of COS and CO18O as carbon cycle tracers.

 

Microbial dynamics drive the biotic machinery of early soil evolution. However, integrated knowledge of microbial community establishment, functional associations, and community assembly processes in incipient soil is lacking. This study presents a novel approach of combining microbial phylogenetic profiling, functional predictions, and community assembly processes to analyze drivers of microbial community establishment in an emerging soil system. Rigorous submeter sampling of a basalt‐soil lysimeter after 2 years of irrigation revealed that microbial community colonization patterns and associated soil parameters were depth dependent. Phylogenetic analysis of 16S rRNA gene sequences indicated the presence of diverse bacterial and archaeal phyla, with high relative abundance of Actinomyceles on the surface and a consistently high abundance ofProteobacteria(Alpha,Beta,Gamma, andDelta) at all depths. Despite depth‐dependent variation in community diversity, predicted functional gene analysis suggested that microbial metabolisms did not differ with depth, thereby suggesting redundancy in functional potential throughout the system. Null modeling revealed that microbial community assembly patterns were predominantly governed by variable selection. The relative influence of variable selection decreased with depth, indicating unique and relatively harsh environmental conditions near the surface and more benign conditions with depth. Additionally, community composition near the center of the domain was influenced by high levels of dispersal, suggesting that spatial processes interact with deterministic selection imposed by the environment. These results suggest that for oligotrophic systems, there are major differences in the length scales of variation between vertical and horizontal dimensions with the vertical dimension dominating variation in physical, chemical, and biological features.