Effects of freeze-thaw cycles on soil greenhouse gas emissions: A systematic review

In the context of global warming, increasingly widespread and frequent freezing and thawing cycles (FTCs) will have profound effects on the biogeochemical cycling of soil carbon and nitrogen. FTCs can increase soil greenhouse gas (GHG) emissions by reducing the stability of soil aggregates, promoting the release of dissolved organic carbon, decreasing the number of microorganisms, inducing cell rupture, and releasing carbon and nitrogen nutrients for use by surviving microorganisms. However, the similarity and disparity of the mechanisms potentially contributing to changes in GHGs have not been systematically evaluated. The present study consolidates the most recent findings on the dynamics of soil carbon and nitrogen, as well as GHGs, in relation to FTCs. Additionally, it analyzes the impact of FTCs on soil GHGs in a systematic manner. In this study, particular emphasis is given to the following: (i) the reaction mechanism involved; (ii) variations in soil composition in different types of land (e.g., forest, peatland, farmland, and grassland); (iii) changes in soil structure in response to cycles of freezing temperatures; (iv) alterations in microbial biomass and community structure that may provide further insight into the fluctuations in GHGs after FTCs. The challenges identified included the extension of laboratory-scale research to ecosystem scales, the performance of in-depth investigation of the coupled effects of carbon, nitrogen, and water in the freeze-thaw process, and analysis of the effects of FTCs through the use of integrated research tools. The results of this study can provide a valuable point of reference for future experimental designs and scientific investigations and can also assist in the analysis of the attributes of GHG emissions from soil and the ecological consequences of the factors that influence these emissions in the context of global permafrost warming.

Alternative stable states, nonlinear behavior, and predictability of microbiome dynamics

BACKGROUND

Microbiome dynamics are both crucial indicators and potential drivers of human health, agricultural output, and industrial bio-applications. However, predicting microbiome dynamics is notoriously difficult because communities often show abrupt structural changes, such as "dysbiosis" in human microbiomes.

METHODS

We integrated theoretical frameworks and empirical analyses with the aim of anticipating drastic shifts of microbial communities. We monitored 48 experimental microbiomes for 110 days and observed that various community-level events, including collapse and gradual compositional changes, occurred according to a defined set of environmental conditions. We analyzed the time-series data based on statistical physics and non-linear mechanics to describe the characteristics of the microbiome dynamics and to examine the predictability of major shifts in microbial community structure.

RESULTS

We confirmed that the abrupt community changes observed through the time-series could be described as shifts between "alternative stable states" or dynamics around complex attractors. Furthermore, collapses of microbiome structure were successfully anticipated by means of the diagnostic threshold defined with the "energy landscape" analysis of statistical physics or that of a stability index of nonlinear mechanics.

CONCLUSIONS

The results indicate that abrupt microbiome events in complex microbial communities can be forecasted by extending classic ecological concepts to the scale of species-rich microbial systems. Video Abstract.

Core species and interactions prominent in fish-associated microbiome dynamics

BACKGROUND

In aquatic ecosystems, the health and performance of fish depend greatly on the dynamics of microbial community structure in the background environment. Nonetheless, finding microbes with profound impacts on fish's performance out of thousands of candidate species remains a major challenge.

METHODS

We examined whether time-series analyses of microbial population dynamics could illuminate core components and structure of fish-associated microbiomes in the background (environmental) water. By targeting eel-aquaculture-tank microbiomes as model systems, we reconstructed the population dynamics of the 9605 bacterial and 303 archaeal species/strains across 128 days.

RESULTS

Due to the remarkable increase/decrease of constituent microbial population densities, the taxonomic compositions of the microbiome changed drastically through time. We then found that some specific microbial taxa showed a positive relationship with eels' activity levels even after excluding confounding effects of environmental parameters (pH and dissolved oxygen level) on population dynamics. In particular, a vitamin-B₁₂-producing bacteria, Cetobacterium somerae, consistently showed strong positive associations with eels' activity levels across the replicate time series of the five aquaculture tanks analyzed. Network theoretical and metabolic modeling analyses further suggested that the highlighted bacterium and some other closely-associated bacteria formed "core microbiomes" with potentially positive impacts on eels.

CONCLUSIONS

Overall, these results suggest that the integration of microbiology, ecological theory, and network science allows us to explore core species and interactions embedded within complex dynamics of fish-associated microbiomes.  Video Abstract.

Changes in the analysis of temporal community dynamics data: a 29-year literature review

BACKGROUND

Understanding how biological communities change over time is of increasing importance as Earth moves into the Anthropocene. A wide variety of methods are used for multivariate community analysis and are variously applied to research that aims to characterise temporal dynamics in community composition. Understanding these methods and how they are applied is useful for determining best practice in community ecology.

METHODOLOGY

We reviewed the ecological literature from 1990 to 2018 that used multivariate methods to address questions of temporal community dynamics. For each paper that fulfilled our search criteria, we recorded the types of multivariate analysis used to characterise temporal community dynamics in addition to the research aim, habitat type, location, taxon and the experimental design.

RESULTS

Most studies had relatively few temporal replicates; the median number was seven time points. Nearly 70% of studies applied more than one analysis method; descriptive methods such as bar graphs and ordination were the most commonly applied methods. Surprisingly, the types of analyses used were only related to the number of temporal replicates, but not to research aim or any other aspects of experimental design such as taxon, or habitat or year of study.

CONCLUSIONS

This review reveals that most studies interested in understanding community dynamics use relatively short time series meaning that several, more sophisticated, temporal analyses are not widely applicable. However, newer methods using multivariate dissimilarities are growing in popularity and many can be applied to time series of any length.

Restoring fluvial forms and processes by gravel augmentation or bank erosion below dams: A systematic review of ecological responses

Aquatic biological communities have directly undergone human-induced changes. Altered hydrological and morphological processes in running waters have caused the degradation of main habitats for biotas and have disturbed ecosystem functionality. The latest advances in river restoration concerned the rise in far-reaching hydromorphological restoration actions that have been implemented below dams to reverse well-known negative impacts of anthropogenic pressures. Some authors emphasized the enhancement of sediment supply and habitat diversity using gravel augmentation or bank erosion to restore morphodynamics, and thus improve biodiversity. We explored the Web of Science database for empirical research papers that specifically addressed such hydromorphological river restoration actions. Articles were examined using a text-content analysis tool to determine the major concepts or ideas they deal with. It has also been proved as useful in defining interrelationships and degree of interdisciplinary. Results showed that a low number of published scientific articles exist about such projects, mainly condensed in the North hemisphere. Divergent ecological issues were highlighted by the word co-occurrence networks: (i) gravel augmentation was used to improve spawning habitats for fish of economic interest whereas (ii) erodible corridor was designed to safeguard natural riparian systems, approaching morphological goals of channel widening. Overall, ecological responses were consistent with those expected, leading however rather to functional shifts than richness increase. Gravel augmentation or bank erosion were not usually combined with in-channel structure management. However, this might be an option to consider since the biological communities seem to be sensitive during first restorations with such combination. This review demonstrates the value of word co-occurrence networks in exploring a high number of previous publications, keys for formulating guidance to manage gravel augmentation or bank erosion along ecological purposes.

Development of physical modelling tools in support of risk scenarios: A new framework focused on deep-sea mining

Deep-sea mining has gained international interest to provide materials for the worldwide industry. European oceans and, particularly, the Portuguese Exclusive Economic Zone present a recognized number of areas with polymetallic sulphides rich in metals used in high technology developments. A large part of these resources are in the vicinity of sensitive ecosystems, where the mineral extraction can potentially damage deep-ocean life services. In this context, technological research must be intensified, towards the implementation of environmental friendly solutions that mitigate the associated impacts. To reproduce deep-sea dynamics and evaluate the effects of the mining activities, reliable numerical modelling tools should be developed. The present work highlights the usefulness of a new framework for risk and impact assessment based on oceanographic numerical models to support the adoption of good management practices for deep-sea sustainable exploitation. This tool integrates the oceanic circulation model ROMS-Agrif with the semi-Lagrangian model ICHTHYOP, allowing the representation of deep-sea dynamics and particles trajectories considering the sediments physical properties. Numerical simulations for the North Mid-Atlantic Ridge region, revealed the ability of ROMS-Agrif to simulate real deep-sea dynamics through validation with in situ data. Results showed a strong diversity in the particle residence time, with a dependency on their density and size but also on local ocean conditions and bottom topography. The highest distances are obtained for the smaller and less dense particles, although they tend to be confined by bathymetric constrains and deposited in deepest regions. This work highlights the potential of this modelling tool to forecast laden plume trajectories, allowing the definition of risk assessment scenarios for deep-sea mining activities and the implementation of sustainable exploitation plans. Furthermore, the coupling of this numerical solution with models of biota inhabiting deep-sea vent fields into ecosystem models is discussed and outlined as cost-effective tools for the management of these remote ecosystems.