Bjarte Hannisdal

Correlating microbial community profiles with geochemical data in highly stratified sediments from the Arctic Mid-Ocean Ridge

Microbial communities and their associated metabolic activity in marine sediments have a profound impact on global biogeochemical cycles. Their composition and structure are attributed to geochemical and physical factors, but finding direct correlations has remained a challenge. Here we show a significant statistical relationship between variation in geochemical composition and prokaryotic community structure within deep-sea sediments. We obtained comprehensive geochemical data from two gravity cores near the hydrothermal vent field Loki’s Castle at the Arctic Mid-Ocean Ridge, in the Norwegian-Greenland Sea. Geochemical properties in the rift valley sediments exhibited strong centimeter-scale stratigraphic variability. Microbial populations were profiled by pyrosequencing from 15 sediment horizons (59,364 16S rRNA gene tags), quantitatively assessed by qPCR, and phylogenetically analyzed. Although the same taxa were generally present in all samples, their relative abundances varied substantially among horizons and fluctuated between Bacteria- and Archaea-dominated communities. By independently summarizing covariance structures of the relative abundance data and geochemical data, using principal components analysis, we found a significant correlation between changes in geochemical composition and changes in community structure. Differences in organic carbon and mineralogy shaped the relative abundance of microbial taxa. We used correlations to build hypotheses about energy metabolisms, particularly of the Deep Sea Archaeal Group, specific Deltaproteobacteria, and sediment lineages of potentially anaerobic Marine Group I Archaea. We demonstrate that total prokaryotic community structure can be directly correlated to geochemistry within these sediments, thus enhancing our understanding of biogeochemical cycling and our ability to predict metabolisms of uncultured microbes in deep-sea sediments.

Phanerozoic Earth System Evolution and Marine Biodiversity

Environmental factors, more so than sampling biases, drive trends in biological evolution observed in the fossil record. The Phanerozoic fossil record of marine animal diversity covaries with the amount of marine sedimentary rock. The extent to which this covariation reflects a geologically controlled sampling bias remains unknown. We show that Phanerozoic records of seawater chemistry and continental flooding contain information on the diversity of marine animals that is independent of sedimentary rock quantity and sampling. Interrelationships among variables suggest long-term interactions among continental flooding, sulfur and carbon cycling, and macroevolution. Thus, mutual responses to interacting Earth systems, not sampling biases, explain much of the observed covariation between Phanerozoic patterns of sedimentation and fossil biodiversity. Linkages between biodiversity and environmental records likely reflect complex biotic responses to changing ocean redox conditions and long-term sea-level fluctuations driven by plate tectonics.

Distinct microbial communities associated with buried soils in the Siberian tundra

Cryoturbation, the burial of topsoil material into deeper soil horizons by repeated freeze–thaw events, is an important storage mechanism for soil organic matter (SOM) in permafrost-affected soils. Besides abiotic conditions, microbial community structure and the accessibility of SOM to the decomposer community are hypothesized to control SOM decomposition and thus have a crucial role in SOM accumulation in buried soils. We surveyed the microbial community structure in cryoturbated soils from nine soil profiles in the northeastern Siberian tundra using high-throughput sequencing and quantification of bacterial, archaeal and fungal marker genes. We found that bacterial abundances in buried topsoils were as high as in unburied topsoils. In contrast, fungal abundances decreased with depth and were significantly lower in buried than in unburied topsoils resulting in remarkably low fungal to bacterial ratios in buried topsoils. Fungal community profiling revealed an associated decrease in presumably ectomycorrhizal (ECM) fungi. The abiotic conditions (low to subzero temperatures, anoxia) and the reduced abundance of fungi likely provide a niche for bacterial, facultative anaerobic decomposers of SOM such as members of the Actinobacteria, which were found in significantly higher relative abundances in buried than in unburied topsoils. Our study expands the knowledge on the microbial community structure in soils of Northern latitude permafrost regions, and attributes the delayed decomposition of SOM in buried soils to specific microbial taxa, and particularly to a decrease in abundance and activity of ECM fungi, and to the extent to which bacterial decomposers are able to act as their functional substitutes.

Disentangling rock record bias and common-cause from redundancy in the British fossil record

The fossil record documents the history of life, but the reliability of that record has often been questioned. Spatiotemporal variability in sedimentary rock volume, sampling and research effort especially frustrates global-scale diversity reconstructions. Various proposals have been made to rectify palaeodiversity estimates using proxy measures for the availability and sampling of the rock record, but the validity of these approaches remains controversial. Targeting the rich fossil record of Great Britain as a highly detailed regional exemplar, our statistical analysis shows that marine outcrop area contains a signal useful for predicting changes in diversity, collections and formations, whereas terrestrial outcrop area contains a signal useful for predicting formations. In contrast, collection and formation counts are information redundant with fossil richness, characterized by symmetric, bidirectional information flow. If this is true, the widespread use of collection and formation counts as sampling proxies to correct the raw palaeodiversity data may be unwarranted.

Phenotypic evolution in the fossil record : Numerical experiments

Stratophenetic data document phenotypic changes in a fossil lineage and play a vital role in reconciling contemporary microevolution with long‐term paleontological patterns. However, stratophenetic series represent multiscale geological and biological interactions, defying simple analysis and interpretation. A numerical model is presented that simulates stratophenetic series in shallow marine siliciclastic deposits. The model is driven by predictions of water depth, substrate properties, and sedimentation rate from a high‐resolution sedimentary basin fill model. Species abundance is modeled as a probability density peaked with respect to environmental preferences. The Price equation is used to model phenotypic evolution based on phenotype‐fitness covariance and drift. Preservation is a Poisson process controlled by population size, preservation probability, and sedimentation. Numerical experiments are used to investigate (1) the effects of sampling and depositional architecture on observed patterns and (2) the performance of various statistical tests in identifying evolutionary mode. As sample sizes decrease, the inaccuracy of sample mean values causes a stratophenetic pattern referred to as analytical stasis. Depositional architecture can cause nonrandom patterns through temporally irregular preservation, with the relative size and distribution of gaps being more important than the absolute size of gaps and overall completeness. For short series, statistical tests based on a random‐walk null hypothesis lose power and should be abandoned in favor of a multidimensional approach. A model of the data is needed that can account for confounding factors, and all available information on time and environment as well as phenotypic data should be incorporated and analyzed jointly, with a greater emphasis on quantifying uncertainty.

Inferring phenotypic evolution in the fossil record by Bayesian inversion

Abstract This paper takes an alternative approach to the problem of inferring patterns of phenotypic evolution in the fossil record. Reconstructing temporal biological signal from noisy stratophenetic data is an inverse problem analogous to subsurface reconstructions in geophysics, and similar methods apply. To increase the information content of stratophenetic series, available geological data on sample ages and environments are included as prior knowledge, and all inferences are conditioned on the uncertainty in these geological variables. This uncertainty, as well as data error and the stochasticity of fossil preservation and evolution, prevents any unique solution to the stratophenetic inverse problem. Instead, the solution is defined as a distribution of model parameter values that explain the data to varying degrees. This distribution is obtained by direct Monte Carlo sampling of the parameter space, and evaluated with Bayesian integrals. The Bayesian inversion is illustrated with Miocene stratigraphic data from the ODP Leg 174AX Bethany Beach borehole. A sample of the benthic foraminifer Pseudononion pizarrensis is used to obtain a phenotypic covariance matrix for outline shape, which constrains a model of multivariate shape evolution. The forward model combines this evolutionary model and stochastic models of fossil occurrence with the empirical sedimentary record to generate predicted stratophenetic series. A synthetic data set is inverted, using the Neighbourhood Algorithm to sample the parameter space and characterize the posterior probability distribution. Despite small sample sizes and noisy shape data, most of the generating parameter values are well resolved, and the underlying pattern of phenotypic evolution can be reconstructed, with quantitative measures of uncertainty. Inversion of a stratigraphic series into a time series can significantly improve our perception and interpretation of an evolutionary pattern.

Non-parametric inference of causal interactions from geological records

Quantification of drive-response relationships from geological records is challenged both by the complexity of the interactions and by indirect and uncertain proxy data. Here I demonstrate the use of information-theoretic techniques to detect causal relationships directly from incomplete and noisy time series. A non-parametric estimate of information transfer (IT) is used to quantify (1) the relative strength of statistical dependence among three variables, including nonlinear relationships, and (2) the directionality of coupling between two variables, compared to surrogate time series. Surrogates preserve the amplitudes and frequencies of the original data, and allow causation to be distinguished from correlation. Simple data pre-processing helps overcome biases related to non-stationarity. Causal inference involves a combination of the two IT calculations, and the method is sufficiently robust to sparse, irregular sampling to have geological applicability. Two case studies highlight some of the possibilities and limitations: (1) IT analysis of oxygen isotope records from Chinese speleothems against ice cores from Greenland and Antarctica suggests time-varying relative influence of the two hemispheres on monsoon intensity over the interval 40 to 10 Ka. IT from the Greenland record dominates except in the deep glacial phase, during which IT from the Antarctic record is more prominent. (2) IT analyses of Phanerozoic seawater isotope ratios capture long-term coupling between temperature (δ18O) and carbon cycling (δ13C), and between the cycling of carbon (δ13C) and sulfur (δ34S). Results suggest that the δ34S record contains an important signal for understanding Phanerozoic Earth system evolution. Although directional IT between proxies cannot be equated with direct causality, the method holds some promise as a data-driven approach to inferring causal interactions from geological records.

On the Relationship between Macrostratigraphy and Geological Processes: Quantitative Information Capture and Sampling Robustness

Spatial and temporal patterns in the sedimentary record are controlled by a wide range of forcing mechanisms. Macrostratigraphy uses the temporal ranges of gap‐bound rock packages, compiled separately for different geographic locations, to quantify these patterns. The total number of gap‐bound packages (D) and the rates of package initiation and truncation (p and q, respectively) distill depositional geometries into time series that preserve information on both the spatial extent and the temporal continuity of deposition. These macrostratigraphic quantities should, in principle, relate quantitatively to the underlying forcing mechanisms that govern sedimentation. Here, we use a numerical model of continental‐margin sedimentation to test the extent to which time‐varying forcing mechanisms, including subsidence, sediment supply, and sea level change, can be detected quantitatively by the application of macrostratigraphy. Spectral and information‐theoretic analyses of time series of D, p, and q show that (1) all three quantities contain significant information on the sea level change, sediment supply variability, and subsidence patterns specified in the model input and (2) they convey the relative strengths of multiple forcing processes and how the relative importance of these processes varies with temporal resolution. We also find that the process information of p, q, and D is very robust to incomplete spatial sampling of the deposits. Our results suggest that D, which reflects variations in the area of sediment coverage and its temporal persistence, may afford the single best macrostratigraphic quantity for capturing the entire range of forcing mechanisms. Macrostratigraphy thus extends many of the well‐known links between sequence architecture and sedimentary processes into a quantitative framework for statistical analyses of entire basin‐fill successions.

Detecting common-cause relationships with directional information transfer

Abstract Correlations between sedimentary rock and fossil records may involve a combination of rock-record sampling bias and common response to external forcing. Quantifying their relative importance from incomplete and uncertain proxy data is not trivial given the potential complexity of interactions among the underlying processes. This paper shows how a non-parametric method can be used to detect causal interactions directly from incomplete and irregular time series, by quantifying directional information transfer between variables. A numerical experiment illustrates how estimates of the relative strength, scale, and directionality of coupling can correctly distinguish a common-cause variable from a spurious relationship, even in cases where correlations are misleading. With a joint analysis of Phanerozoic rock and fossil records pending, the method is applied to oxygen, carbon, and sulphur stable isotope records from marine carbonates, identifying complex interactions between climatic changes and the cycling of carbon and sulphur over the Phanerozoic.

Clams and Brachiopods: Chips That Pass Out of Sight

Abstract Data from modern subtidal brachiopod-mollusk dominated death assemblages are used to investigate the effect of sieve size on taphonomic signature, comparing bivalves and brachiopods. The data comprise a total of 4439 specimens, mainly fragments (93%), sorted into five size fractions, and scored for four taphonomic variables: fragmentation, surface alteration, bioerosion, and encrustation. The taphonomic signatures of bivalve and brachiopod shells change as a function of sieve size, primarily from loss of encrusters on small, mobile fragments. Bivalves and brachiopods show significant differences (Wilcoxon rank-sum, α = 0.05) in taphonomic signature that become more pronounced in the fine fractions, mainly as a result of different levels of bioerosion. Bivalves seem to become fragmented after weakening from bioerosion, whereas brachiopods apparently are more prone to mechanical breakage. Thus, brachiopod shells may be shorter-lived in the coarse fractions and enter the fine fractions with less accumulated damage. Due to intrinsic taxonomic differences in the response to taphonomic processes, death assemblages with similar levels of taphonomic modification may have accumulated on different temporal scales. Comparative studies seeking taphonomic control must strive to use material from the same size fractions to avoid spurious results based on sampling procedure alone.