Synchronous records of pCO2 and Δ14C suggest rapid, ocean-derived pCO2 fluctuations at the onset of Younger Dryas

Just before the onset of the Younger Dryas (YD) cold event, several stomatal proxy-based pCO2 records have shown a sharp increase in atmospheric CO2 concentration (pCO2) of between ca 50 and 100 ppm, followed by a rapid decrease of similar or even larger magnitude. Here we compare one of these records, a high-resolution pCO2 record from southern Sweden, with the IntCal13 record of radiocarbon (Δ14C). The two records show broadly synchronous fluctuations at the YD onset. Specifically, the IntCal13 record documents decreasing Δ14C just before the YD onset when pCO2 peaks, consistent with a source of “old” CO2 from the deep ocean. We propose that this fluctuation occurred due to a major ocean flushing event. The cause of the flushing event remains speculative but could be related to the hypothesis of the glacial ocean as a thermobaric capacitor. We confirm that the earth system can produce such large multi-decadal timescale fluctuations in pCO2 through simulating an artificial ocean flushing event with the GENIE Earth System Model. We suggest that sharp transitions of pCO2 may have remained undetected so far in ice cores due to inter-firn gas exchange and time-averaging. The stomatal proxy record is a powerful complement to the ice core records for the study of rapid climate change.

Improving parameter learning of Bayesian nets from incomplete data

This paper addresses the estimation of parameters of a Bayesian network from incomplete data. The task is usually tackled by running the Expectation-Maximization (EM) algorithm several times in order to obtain a high log-likelihood estimate. We argue that choosing the maximum log-likelihood estimate (as well as the maximum penalized log-likelihood and the maximum a posteriori estimate) has severe drawbacks, being affected both by overfitting and model uncertainty. Two ideas are discussed to overcome these issues: a maximum entropy approach and a Bayesian model averaging approach. Both ideas can be easily applied on top of EM, while the entropy idea can be also implemented in a more sophisticated way, through a dedicated non-linear solver. A vast set of experiments shows that these ideas produce significantly better estimates and inferences than the traditional and widely used maximum (penalized) log-likelihood and maximum a posteriori estimates. In particular, if EM is adopted as optimization engine, the model averaging approach is the best performing one; its performance is matched by the entropy approach when implemented using the non-linear solver. The results suggest that the applicability of these ideas is immediate (they are easy to implement and to integrate in currently available inference engines) and that they constitute a better way to learn Bayesian network parameters.

Evaluating the use of testate amoebae for palaeohydrological reconstruction in permafrost peatlands

The melting of high-latitude permafrost peatlands is a major concern due to a potential positive feedback on global climate change. We examine the ecology of testate amoebae in permafrost peatlands, based on sites in Sweden (~ 200 km north of the Arctic Circle). Multivariate statistical analysis confirms that water-table depth and moisture content are the dominant controls on the distribution of testate amoebae, corroborating the results from studies in mid-latitude peatlands. We present a new testate amoeba-based water table transfer function and thoroughly test it for the effects of spatial autocorrelation, clustered sampling design and uneven sampling gradients. We find that the transfer function has good predictive power; the best-performing model is based on tolerance-downweighted weighted averaging with inverse deshrinking (performance statistics with leave-one-out cross validation: R2 = 0.87, RMSEP = 5.25 cm). The new transfer function was applied to a short core from Stordalen mire, and reveals a major shift in peatland ecohydrology coincident with the onset of the Little Ice Age (c. AD 1400). We also applied the model to an independent contemporary dataset from Stordalen and find that it outperforms predictions based on other published transfer functions. The new transfer function will enable palaeohydrological reconstruction from permafrost peatlands in Northern Europe, thereby permitting greatly improved understanding of the long-term ecohydrological dynamics of these important carbon stores as well as their responses to recent climate change.

Ecology of testate amoebae in an Amazonian peatland and development of a transfer function for palaeohydrological reconstruction

Tropical peatlands represent globally important carbon sinks with a unique biodiversity and are currently threatened by climate change and human activities. It is now imperative that proxy methods are developed to understand the ecohydrological dynamics of these systems and for testing peatland development models. Testate amoebae have been used as environmental indicators in ecological and palaeoecological studies of peatlands, primarily in ombrotrophic Sphagnum-dominated peatlands in the mid- and high-latitudes. We present the first ecological analysis of testate amoebae in a tropical peatland, a nutrient-poor domed bog in western (Peruvian) Amazonia. Litter samples were collected from different hydrological microforms (hummock to pool) along a transect from the edge to the interior of the peatland. We recorded 47 taxa from 21 genera. The most common taxa are Cryptodifflugia oviformis, Euglypha rotunda type, Phryganella acropodia, Pseudodifflugia fulva type and Trinema lineare. One species found only in the southern hemisphere, Argynnia spicata, is present. Arcella spp., Centropyxis aculeata and Lesqueresia spiralis are indicators of pools containing standing water. Canonical correspondence analysis and non-metric multidimensional scaling illustrate that water table depth is a significant control on the distribution of testate amoebae, similar to the results from mid- and high-latitude peatlands. A transfer function model for water table based on weighted averaging partial least-squares (WAPLS) regression is presented and performs well under cross-validation (r 2apparent=0.76,RMSE=4.29;r2jack=0.68,RMSEP=5.18. The transfer function was applied to a 1-m peat core, and sample-specific reconstruction errors were generated using bootstrapping. The reconstruction generally suggests near-surface water tables over the last 3,000 years, with a shift to drier conditions at c. cal. 1218-1273 AD

Spatial and temporal regulation of the pesticide dieldrin within industrial catchments

The river catchments of south Yorkshire support a very high density of wool processing industries. Dieldrin was once used as a moth proofing agent, as a sheep dip, and as a pesticide to protect wool fleeces during storage and transport, all of which caused pollution of these catchments due to textile processing. Weekly sampling of four of these rivers revealed two classes of dieldrin contamination: the Aire and Calder (the rivers which support very high concentrations of wool processing industries) had higher concentrations (averaging ~3 ng/l) than the Don and Trent (~1 ng/l). The average flux of dieldrin from these rivers into the Humber estuary was 9.8 g/day, with the Aire (of which the Calder is a tributary) and the Trent contributing almost equally, with a smaller contribution from the Don. The Trent has the highest average flow, explaining its large contribution to dieldrin flux. Less detailed sampling of rivers from the north Humber catchment which drain predominantly rural areas had dieldrin concentrations similar to the heavily industrialized southern catchment rivers. This suggests that dieldrin from agronomic and domestic usage may be more persistent than the pollution caused by textile processing industries. Evidence is presented to suggest that the principle dieldrin sources to the Humber catchments are sewage treatment plants, and that the dieldrin sources are in rapid equilibrium with the water column. (C) 2000 Elsevier Science B.V.

Use of bacterial whole-genome sequencing to investigate local persistence and spread in bovine tuberculosis

Mycobacterium bovis is the causal agent of bovine tuberculosis, one of the most important diseases currently facing the UK cattle industry. Here, we use high-density whole genome sequencing (WGS) in a defined sub-population of M. bovis in 145 cattle across 66 herd breakdowns to gain insights into local spread and persistence. We show that despite low divergence among isolates, WGS can in principle expose contributions of under-sampled host populations to M. bovis transmission. However, we demonstrate that in our data such a signal is due to molecular type switching, which had been previously undocumented for M. bovis. Isolates from farms with a known history of direct cattle movement between them did not show a statistical signal of higher genetic similarity. Despite an overall signal of genetic isolation by distance, genetic distances also showed no apparent relationship with spatial distance among affected farms over distances <5 km. Using simulations, we find that even over the brief evolutionary timescale covered by our data, Bayesian phylogeographic approaches are feasible. Applying such approaches showed that M. bovis dispersal in this system is heterogeneous but slow overall, averaging 2 km/year. These results confirm that widespread application of WGS to M. bovis will bring novel and important insights into the dynamics of M. bovis spread and persistence, but that the current questions most pertinent to control will be best addressed using approaches that more directly integrate WGS with additional epidemiological data.

Effective collision strengths for election impact excitation of Cl III

Effective collision strengths for electron-impact excitation of the phosphorus-like ion Cl III are presented for all fine-structure transitions among the levels arising from the lowest 23 LS states. The collisional cross sections are computed in the multichannel close-coupling R-matrix approximation, where sophisticated configuration-interaction wave functions are used to represent the target states. The 23 LS states are formed from the basis configurations 3s²3p³, 3s3p⁴, 3s²3p²3d, and 3s²3p²4s, and correspond to 49 fine-structure levels, leading to a total possible 1176 fine-structure transitions. The effective collision strengths, obtained by averaging the electron collision strengths over a Maxwellian distribution of electron velocities, are tabulated in this paper for all 1176 transitions and for electron temperatures in the ranges T(K)=7500-25,000 and log T(K)=4.4-5.4. The former range encompasses the temperatures of particular importance for application to gaseous nebulae, while the latter range is more applicable to the study of solar and laboratory-type plasmas. © 2001 Academic Press.

Effective collision strengths for fine-structure forbidden transitions among the 2s22p3 levels of Ne IV

Effective collision strengths for electron-impact excitation of the N-like ion NeIV are calculated in the close-coupling approximation using the multichannel R-matrix method. Specific attention is given to the 10 astrophysically important fine-structure forbidden transitions among the ⁴S^o, ²D^o and ²P^o levels in the 2s²2p³ ground-state configuration. The expansion of the total wavefunction incorporates the lowest 11 LS eigenstates of NeIV, consisting of eight n = 2 terms with configurations 2s²2p³, 2s2p⁴ and 2p⁵, together with three n = 3 states of configuration 2s²2p²3s. We present in graphical form the effective collision strengths obtained by thermally averaging the collision strengths over a Maxwellian distribution of velocities, for all 10 fine-structure transitions, over the range of electron temperatures log T(K) = 3.6 to log T(K) = 6.1 (the range appropriate for astrophysical applications). Comparisons are made with the earlier, less sophisticated close-coupling calculation of Giles, and excellent agreement is found in the limited temperature region where a comparison is possible [log T(K) = 3.7 to log 7(K) = 4.3]. At higher temperatures the present data are the only reliable results currently available.

Effective collision strengths for fine-structure forbidden transitions among the 3s 23p 3 levels of Ar IV

The multichannel R-matrix method is used to compute electron impact excitation collision strengths in Ar IV for all fine-structure transitions among the ⁴S°, ²D° and ²P° levels in the 3s ²3p ³ ground configuration. Included in the expansion of the total wavefunction are the lowest 13 LS target eigenstates of Ar iv formed from the 3s ²3p ³, 3s3p ⁴ and 3s ²3p ²3d configurations. The effective collision strengths, obtained by averaging the electron collision strengths over a Maxwellian distribution of electron velocities, are presented for all 10 fine-structure transitions over a wide range of electron temperatures of astrophysical interest (T _e = 2000-100 000 K). Comparisons are made with an earlier 7-state close-coupling calculation by Zeippen, Butler & Le Bourlot, and significant differences are found to occur for many of the forbidden transitions considered, in particular those involving the ⁴S° ground state, where discrepancies of up to a factor of 3 are found in the low-temperature region. © 1997 RAS.

A Review of Numerical Modelling of Wave Energy Converter Arrays

Large-scale commercial exploitation of wave energy is certain to require the deployment of wave energy converters (WECs) in arrays, creating ‘WEC farms’. An understanding of the hydrodynamic interactions in such arrays is essential for determining optimum layouts of WECs, as well as calculating the area of ocean that the farms will require. It is equally important to consider the potential impact of wave farms on the local and distal wave climates and coastal processes; a poor understanding of the resulting environmental impact may hamper progress, as it would make planning consents more difficult to obtain. It is therefore clear that an understanding the interactions between WECs within a farm is vital for the continued development of the wave energy industry.To support WEC farm design, a range of different numerical models have been developed, with both wave phase-resolving and wave phase-averaging models now available. Phase-resolving methods are primarily based on potential flow models and include semi-analytical techniques, boundary element methods and methods involving the mild-slope equations. Phase-averaging methods are all based around spectral wave models, with supra-grid and sub-grid wave farm models available as alternative implementations.The aims, underlying principles, strengths, weaknesses and obtained results of the main numerical methods currently used for modelling wave energy converter arrays are described in this paper, using a common framework. This allows a qualitative comparative analysis of the different methods to be performed at the end of the paper. This includes consideration of the conditions under which the models may be applied, the output of the models and the relationship between array size and computational effort. Guidance for developers is also presented on the most suitable numerical method to use for given aspects of WEC farm design. For instance, certain models are more suitable for studying near-field effects, whilst others are preferable for investigating far-field effects of the WEC farms. Furthermore, the analysis presented in this paper identifies areas in which the numerical modelling of WEC arrays is relatively weak and thus highlights those in which future developments are required.