Between the land and ocean, diverse coastal ecosystems transform, store, and transport material. Across these interfaces, the dynamic exchange of energy and matter is driven by hydrological and hydrodynamic processes such as river and groundwater discharge, tides, waves, and storms. These dynamics regulate ecosystem functions and Earth's climate, yet global models lack representation of coastal processes and related feedbacks, impeding their predictions of coastal and global responses to change. Here, we assess existing coastal monitoring networks and regional models, existing challenges in these efforts, and recommend a path towards development of global models that more robustly reflect the coastal interface. T he coastal interface, where the land and ocean realms meet (e.g., estuaries, tidal wetlands, tidal rivers, continental shelves, and shorelines), is home to some of the most biologically and geochemically active and diverse systems on Earth 1. Although this interface only represents a small fraction of the Earth's surface, it supports a large suite of ecosystem services,

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 (COO) 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 COO as carbon cycle tracers until process-based constraints are improved. In this study, we measured COS and COO 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 CO, 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 CO 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 CO 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 COO as carbon cycle tracers.

The ability of soil to provide ecosystem services is dependent on microbial diversity, with 80-90 % of the processes in soil being mediated by microbes. There still exists a knowledge gap in the types of microorganisms present in soil and how soil management affects them. However, identification of microorganisms is severely limited by classical culturing techniques that have been traditionally used in laboratories. Metagenomic approaches are increasingly becoming common, with current high-throughput sequencing approaches allowing for more in-depth analysis. We conducted a preliminary analysis of bacterial diversity in soils from the longest continuously maintained no-till (NT) plots in the world (52 years) and in adjacent plow-till (PT) plots in Ohio, USA managed similarly except for tillage. Bacterial diversity was determined using a culture-independent approach of high-throughput pyrosequencing of the 16S rRNA gene. Proteobacteria and Acidobacteria were predominant in both samples but the NT soil had a higher number of reads, bacterial richness, and five unique phyla. Four unique phyla were observed in PT and 99 % of the community had relative abundance of <1 %. Plowing and secondary tillage tend to homogenize the soil and reduces the unique (i.e., diverse) microenvironments where microbial populations can reside. We conclude that tillage leads to fewer dominant species being present in soil and that these species contribute to a higher percentage of the total community.

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.

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