Late Holocene sea-level changes and isostasy in western Denmark

Cores and exposed cliff sections in salt marshes around Ho Bugt, a tidal embayment in the northernmost part of the Danish Wadden Sea, were subjected to ¹⁴C dating and litho- and biostratigraphical analyses to reconstruct paleoenvironmental changes and to establish a late Holocene relative sea-level history. Four stages in the late Holocene development of Ho Bugt can be identified: (1) groundwater-table rise and growth of basal peat (from at least 2300 BC to AD 0); (2) salt-marsh formation (0 to AD 250); (3) a freshening phase (AD 250 to AD 1600?), culminating in the drying out of the marshes and producing a distinct black horizon followed by an aeolian phase with sand deposition; and (4) renewed salt-marsh deposition (AD 1600? to present). From 16 calibrated AMS radiocarbon ages on fossil plant fragments and 4 calibrated conventional radiocarbon ages on peat, we reconstructed a local relative sea-level history that shows a steady sea-level rise of 4 m since 4000 cal yr BP. Contrary to suggestions made in the literature, the relative sea-level record of Ho Bugt does not contain a late Holocene highstand. Relative sea-level changes at Ho Bugt are controlled by glacio-isostatic subsidence and can be duplicated by a glacial isostatic adjustment model in which no water is added to the world's oceans after ca. 5000 cal yr BP.     

Recent Rapid Regional Climate Warming on the Antarctic Peninsula

The Intergovernmental Panel on Climate Change (IPCC) confirmed that mean global warming was 0.6 ± 0.2 °C during the 20th century and cited anthropogenic increases in greenhouse gases as the likely cause of temperature rise in the last 50 years. But this mean value conceals the substantial complexity of observed climate change, which is seasonally- and diurnally-biased, decadally-variable and geographically patchy. In particular, over the last 50 years three high-latitude areas have undergone recent rapid regional (RRR) warming, which was substantially more rapid than the global mean. However, each RRR warming occupies a different climatic regime and may have an entirely different underlying cause. We discuss the significance of RRR warming in one area, the Antarctic Peninsula. Here warming was much more rapid than in the rest of Antarctica where it was not significantly different to the global mean. We highlight climate proxies that appear to show that RRR warming on the Antarctic Peninsula is unprecedented over the last two millennia, and so unlikely to be a natural mode of variability. So while the station records do not indicate a ubiquitous polar amplification of global warming, the RRR warming on the Antarctic Peninsula might be a regional amplification of such warming. This, however, remains unproven since we cannot yet be sure what mechanism leads to such an amplification. We discuss several possible candidate mechanisms: changing oceanographic or changing atmospheric circulation, or a regional air-sea-ice feedback amplifying greenhouse warming. We can show that atmospheric warming and reduction in sea-ice duration coincide in a small area on the west of the Antarctic Peninsula, but here we cannot yet distinguish cause and effect. Thus for the present we cannot determine which process is the probable cause of RRR warming on the Antarctic Peninsula and until the mechanism initiating and sustaining the RRR warming is understood, and is convincingly reproduced in climate models, we lack a sound basis for predicting climate change in this region over the coming century.     

Carboniferous diamictite dykes in the Falkland Islands

Sedimentary dykes hosted in ? Ordovician-Devonian strata on the Falkland Islands contain diamictite. The dykes, which are discordant to the host rocks, are sub-vertical, parallel-sided sheets formed by downward injection of a semi-fluidized sediment. On West Falkland palynomorphs present in 2 of the 11 dykes located demonstrate a Late Visean-Early Namurian age. This is older than the main Lafonian Diamictite Formation (Permian) and indicates that the dykes are a rare preservation of sediments formed during the main ice coverage of the Gondwana glaciation. Vitrinite reflectance from organic matter in the dykes indicates a shallow burial history (< 2–3 km) for the southwest Falkland Islands implying deposition of an incomplete or condensed sequence during Late Palaeozoic times, although the stratigraphical relationship of the dykes indicates that this may be extended back into the Mid Palaeozoic. The two diamictite dykes located on East Falkland are shown to be younger; probably Permian in age.     

Genetic significance of fluid inclusions in the CSA Cu–Pb–Zn deposit, Cobar, Australia

CSA mine exploits a ‘Cobar-type’ Cu–Pb–Zn±Au±Ag deposit within a cleaved and metamorphosed portion of the Cobar Supergroup, central New South Wales. The deposit comprises systems of ‘lenses’ that encompass veins, disseminations and semi-massive to massive Cu–Pb–Zn ores. The systems and contained lenses truncate bedding, are approximately coplanar with regional cleavage and similarly oriented shear zones and plunge parallel to the elongation lineation. Systems have extreme vertical continuity (>1000 m), short strike length (400 m) and narrow width (100 m), exhibit vertical and lateral ore-type variation and have alteration haloes. Models of ore formation include classical hydrothermalism, structurally controlled remobilisation and polymodal concepts; syntectonic emplacement now holds sway.Fluid inclusions were examined from quartz±sulphide veins adjacent to now-extracted ore, from coexisting quartz–sulphide within ore, and from vughs in barren quartz veins. Lack of early primary inclusions precluded direct determination of fluids associated with D₂–D₃ ore and vein emplacement. Similarly, decrepitation (by near-isobaric heating) of the two oldest secondary populations precluded direct determination of fluid phases immediately following D₂–D₃ ore and vein emplacement. Post-decrepitation outflow (late D₃ to early post-D₃) is recorded by monophase CH₄ inclusions. Entrained outflow of deeply circulated meteoric fluid modified the CH₄ system; modification is recorded by H₂O+CH₄ and H₂O+(trace CH₄) secondary populations and by an H₂O+(trace CH₄) primary population. The contractional tectonics (D₂–D₃) of ore emplacement was superseded by relaxational tectonics (D_4P) that facilitated meteoric water penetration and return flow.Under D₂ prograde metamorphism, entrapment temperatures (Tt) and pressures (Pt) for pre-decrepitation secondary inclusions are estimated as Tt300–330 °C and Pt1.5–2 kbar≈Plith (the lithostatic pressure). Decrepitation accompanied peak metamorphism (T350–380 °C) in mid- to late-D₃, while in late-D₃ to early post-D₃, essentially monophase CH₄ secondary inclusions were entrapped at Tt350 °C and Pt=1.5–2 kbar≈Plith. Subsequently, abundant CH₄ and entrained meteoric water were entrapped as H₂O+CH₄ secondaries under slowly decreasing temperature (Tt330–350 °C) and constant pressure (Pt1.5–2 kbar). Finally, with increasingly dominant meteoric outflow, H₂O+(trace CH₄) populations record decreasing temperatures (Tt>300 to <350 down to 275–300 °C) at pressures of Phydrostatic<Pt (1 kbar) <Plith (1.5 kbar).The populations of inclusions provide insight into fluid types, flow regimes and P–T conditions during parts of the deposit's evolution. They indirectly support the role of basin-derived CH₄ fluids in ore formation, but provide no insight into a basement-sourced ore-forming fluid. They fully support post-ore involvement of meteoric water. The poorly constrained entrapment history is believed to span 10 Ma from 395 to 385 Ma.     

Segmentation and kinematics of the North America‐Caribbean plate boundary offshore Hispaniola

We explored the submarine portions of the Enriquillo–Plantain Garden Fault zone (EPGFZ) and the Septentrional–Oriente Fault zone (SOFZ) along the Northern Caribbean plate boundary using high‐resolution multibeam echo‐sounding and shallow seismic reflection. The bathymetric data shed light on poorly documented or previously unknown submarine fault zones running over 200 km between Haiti and Jamaica (EPGFZ) and 300 km between the Dominican Republic and Cuba (SOFZ). The primary plate‐boundary structures are a series of strike‐slip fault segments associated with pressure ridges, restraining bends, step overs and dogleg offsets indicating very active tectonics. Several distinct segments 50–100 km long cut across pre‐existing structures inherited from former tectonic regimes or bypass recent morphologies formed under the current strike‐slip regime. Along the most recent trace of the SOFZ, we measured a strike‐slip offset of 16.5 km, which indicates steady activity for the past ~1.8 Ma if its current GPS‐derived motion of 9.8 ± 2 mm a^?1 has remained stable during the entire Quaternary.     

Inference and uncertainty of snow depth spatial distribution at the kilometre scale in the Colorado Rocky Mountains: the effects of sample size,random sampling,predictor quality,and validation procedures

Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km² sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R². Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R²) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R² (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R² scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R² skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R². The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd.