Search

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.

This article discusses the importance of ethical and inclusive engagement between non-Indigenous researchers and Indigenous communities in Arctic research. It acknowledges the historical mistreatment of Indigenous peoples by researchers and emphasizes the need to build respectful relationships. The article provides ten rules for researchers to follow, including researching the culture and history of the research site, understanding different approaches to knowledge production, and establishing reciprocal community relationships. It highlights the value of Indigenous knowledge and the need for collaboration with Indigenous communities for high-quality research outcomes. The document offers guidelines and best practices for researchers seeking to collaborate with Arctic Indigenous communities, emphasizing the importance of recognizing shared humanity, respectful contact methods, aligning research questions with community objectives, compensating Indigenous participants, and planning for the continuation of research and scientific engagement. The paper underscores the need for ethical collaboration that centers Indigenous sovereignty, empowerment, and self-determination, while respecting Indigenous communities and their land and resources. [Extracted from the article]

The magnitude of carbon (C) loss to the atmosphere via microbial decomposition is a function of the amount of C stored in soils, the quality of the organic matter, and physical, chemical and biological factors that comprise the environment for decomposition. The decomposability of C is commonly assessed by laboratory soil incubation studies that measure greenhouse gases mineralized from soils under controlled conditions. Here, we introduce the Soil Incubation Database (SIDb) version 1.0, a compilation of time series data from incubations, structured into a new, publicly available database of C flux (carbon dioxide, CO2, or methane, CH4). In addition to open access, the SIDb project also provides a platform for the development of tools for reading and analysis of incubation data as well as documentation for future use and development. In addition to introducing SIDb, we provide reporting guidance for database entry and the required variables that incubation studies need at minimum to be included in SIDb. A key application of this synthesis effort is to better characterize soil C processes in Earth system models, which will in turn reduce our uncertainty in predicting the response of soil C decomposition to a changing climate. We demonstrate a framework to fit curves to a number of incubation studies from diverse ecosystems, depths, and organic matter content using a built-in model development module that integrates SIDb with the existing SoilR package to estimate soil C pools from time series data. The database will help bridge the gap between site-level measurements, which are commonly used in incubation studies, and global remote-sensed data or data products derived from models aimed at assessing global-scale rates of decomposition and C turnover. [ABSTRACT FROM AUTHOR]