ABSTRACT
Targeted removal experiments are a powerful tool to assess the effects of plant species or (functional) groups on ecosystem functions. However, removing plant biomass in itself can bias the observed responses. This bias is commonly addressed by waiting until ecosystem recovery, but this is inherently based on unverified proxies or anecdotal evidence. Statistical control methods are efficient, but restricted in scope by underlying assumptions. We propose accounting for such biases within the experimental design, using a gradient of biomass removal controls. We demonstrate the relevance of this design by presenting (1) conceptual examples of suspected biases and (2) how to observe and control for these biases. Using data from a mycorrhizal association-based removal experiment, we show that ignoring biomass removal biases (including by assuming ecosystem recovery) can lead to incorrect, or even contrary conclusions (e.g. false positive and false negative). Our gradient design can prevent such incorrect interpretations, regardless of whether aboveground biomass has fully recovered. Our approach provides more objective and quantitative insights, independently assessed for each variable, than using a proxy to assume ecosystem recovery. Our approach circumvents the strict statistical assumptions of, for example, ANCOVA and thus offers greater flexibility in data analysis.
ABSTRACT
Thicker snowpacks and their insulation effects cause winter-warming and invoke thaw of permafrost ecosystems. Temperature-dependent decomposition of previously frozen carbon (C) is currently considered one of the strongest feedbacks between the Arctic and the climate system, but the direction and magnitude of the net C balance remains uncertain. This is because winter effects are rarely integrated with C fluxes during the snow-free season and because predicting the net C balance from both surface processes and thawing deep layers remains challenging. In this study, we quantified changes in the long-term net C balance (net ecosystem production) in a subarctic peat plateau subjected to 10 years of experimental winter-warming. By combining 210 Pb and 14 Cdating of peat cores with peat growth models, we investigated thawing effects on year-round primary production and C losses through respiration and leaching from both shallow and deep peat layers. Winter-warming and permafrost thaw had no effect on the net C balance, but strongly affected gross C fluxes. Carbon losses through decomposition from the upper peat were reduced as thawing of permafrost induced surface subsidence and subsequent waterlogging. However, primary production was also reduced likely due to a strong decline in bryophytes cover while losses from the old C pool almost tripled, caused by the deepened active layer. Our findings highlight the need to estimate long-term responses of whole-year production and decomposition processes to thawing, both in shallow and deep soil layers, as they may contrast and lead to unexpected net effects on permafrost C storage.
Subject(s)
Permafrost , Arctic Regions , Carbon , Ecosystem , SoilABSTRACT
The Northern high latitudes are warming twice as fast as the global average, and permafrost has become vulnerable to thaw. Changes to the environment during thaw leads to shifts in microbial communities and their associated functions, such as greenhouse gas emissions. Understanding the ecological processes that structure the identity and abundance (i.e., assembly) of pre- and post-thaw communities may improve predictions of the functional outcomes of permafrost thaw. We characterized microbial community assembly during permafrost thaw using in situ observations and a laboratory incubation of soils from the Storflaket Mire in Abisko, Sweden, where permafrost thaw has occurred over the past decade. In situ observations indicated that bacterial community assembly was driven by randomness (i.e., stochastic processes) immediately after thaw with drift and dispersal limitation being the dominant processes. As post-thaw succession progressed, environmentally driven (i.e., deterministic) processes became increasingly important in structuring microbial communities where homogenizing selection was the only process structuring upper active layer soils. Furthermore, laboratory-induced thaw reflected assembly dynamics immediately after thaw indicated by an increase in drift, but did not capture the long-term effects of permafrost thaw on microbial community dynamics. Our results did not reflect a link between assembly dynamics and carbon emissions, likely because respiration is the product of many processes in microbial communities. Identification of dominant microbial community assembly processes has the potential to improve our understanding of the ecological impact of permafrost thaw and the permafrost-climate feedback.
ABSTRACT
Since the publication of the original article, the authors noticed some errors in reference citation had been introduced throughout the paper. The following text contains excerpts from the original article and how they should appear with correct referencing. The publisher apologises for any inconvenience this has caused readers.
ABSTRACT
The decomposition of large stocks of soil organic carbon in thawing permafrost might depend on more than climate change-induced temperature increases: indirect effects of thawing via altered bacterial community structure (BCS) or rooting patterns are largely unexplored. We used a 10-year in situ permafrost thaw experiment and aerobic incubations to investigate alterations in BCS and potential respiration at different depths, and the extent to which they are related with each other and with root density. Active layer and permafrost BCS strongly differed, and the BCS in formerly frozen soils (below the natural thawfront) converged under induced deep thaw to strongly resemble the active layer BCS, possibly as a result of colonization by overlying microorganisms. Overall, respiration rates decreased with depth and soils showed lower potential respiration when subjected to deeper thaw, which we attributed to gradual labile carbon pool depletion. Despite deeper rooting under induced deep thaw, root density measurements did not improve soil chemistry-based models of potential respiration. However, BCS explained an additional unique portion of variation in respiration, particularly when accounting for differences in organic matter content. Our results suggest that by measuring bacterial community composition, we can improve both our understanding and the modeling of the permafrost carbon feedback.
Subject(s)
Bacteria/isolation & purification , Permafrost/microbiology , Aerobiosis , CarbonABSTRACT
The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential 'indicator' taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.
Subject(s)
Bacteria/classification , Bacterial Physiological Phenomena , Ecology , Microbiota , Soil Microbiology , Bacteria/genetics , Biodiversity , DNA, Bacterial/genetics , Ecosystem , High-Throughput Nucleotide Sequencing , Machine Learning , Microbial Interactions , Phylogeny , RNA, Ribosomal, 16S/genetics , SoilABSTRACT
Helictites--an enigmatic type of mineral structure occurring in some caves--differ from classical speleothems as they develop with orientations that defy gravity. While theories for helictite formation have been forwarded, their genesis remains equivocal. Here, we show that a remarkable suite of helictites occurring in Asperge Cave (France) are formed by biologically-mediated processes, rather than abiotic processes as had hitherto been proposed. Morphological and petro-physical properties are inconsistent with mineral precipitation under purely physico-chemical control. Instead, microanalysis and molecular-biological investigation reveals the presence of a prokaryotic biofilm intimately associated with the mineral structures. We propose that microbially-influenced mineralization proceeds within a gliding biofilm which serves as a nucleation site for CaCO3, and where chemotaxis influences the trajectory of mineral growth, determining the macroscopic morphology of the speleothems. The influence of biofilms may explain the occurrence of similar speleothems in other caves worldwide, and sheds light on novel biomineralization processes.