Illite K–Ar dating and crystal growth processes in diagenetic environments: a critical review

K–Ar dating of illitic minerals is commonly used in studies of diagenetic series applied to oil prospecting. In spite of a great number of specialized papers, some problems remain unresolved. These are mostly due to a misunderstanding of the argon accumulation process during illitization. Criteria for identifying detrital–authigenic mineral mixtures, crystal ripening, fast precipitation or continuous nucleation‐growth processes are discussed using K–Ar data available in the literature. Using different parameters, such as Δ_age (age_K–Ar ? age_strati), Δ_cryst (diagenetic age_K–Ar ? age_strati) or Δ_frac (age_{K–Arfraction} ?age_K–Arfinest), it is shown that the K–Ar age significance depends on the illite nucleation–growth processes. A ‘diagenetic age’ is obtained when these processes are rapid (the K₂O accumulation period is shorter than 2σ). If lower than this value, the K–Ar ratio depends on the proportions of new and old particles, respectively, which are controlled by the relative rates of nucleation, crystal growth and ripening.     

Sediment flux from a fjord during glacial periods, Isfjorden, Spitsbergen

Sediment has accumulated in Isfjorden, a deep fjord in Spitsbergen, at a rate of 1.7 km³/k.y. during the past 13 k.y. Between 200 ka and 13 ka the fjord was free of ice for 120 k.y. Assuming a similar sediment delivery rate during this ice-free time, 200 km³ of sediment would have accumulated in the fjord. An alternative calculation based on erosion rates suggests that 400 km³ could have been delivered to Isfjorden during this 120 k.y.Seismic studies have identified a 330 km³ package of sediment on the continental shelf and slope west of Isfjorden. This sediment is believed to have accumulated between 200 ka and 13 ka. Herein we argue that this is sediment that was originally deposited in the fjord, and that it was transferred to the shelf by glaciers in the 70 ka during which the fjord was occupied by ice. Calculations using a steady-state numerical model suggest that the sediment could have been moved in a deforming layer of subglacial till and in subglacial melt streams at rates of 7.6 × 10⁶ m³ a⁻¹ and 0.3 × 10⁶ m³ a⁻¹, respectively, resulting in a total flux of 7.9 × 10⁶ m³ a⁻¹. It is unlikely that much sediment was moved in a basal layer of dirty ice, as intense basal melting would have inhibited sediment entrainment.Of the time that glaciers occupied the fjord, 60% would have been required to evacuate the accumulated sediment. During the remaining time, the ice could have been deepening the fjord.     

What controls dead-ice melting under different climate conditions? A discussion

In the geological record, hummocky dead-ice moraines represent the final product of the melt-out of dead-ice. Processes and rates of dead-ice melting in ice-cored moraines and at debris-covered glaciers are commonly believed to be governed by climate and debris-cover properties. Here, backwasting rates from 14 dead-ice areas are assessed in relation to mean annual air temperature, mean summer air temperature, mean annual precipitation, mean summer precipitation, and annual sum of positive degree days. The highest correlation was found between backwasting rate and mean annual air temperature. However, the correlation between melt rates and climate parameters is low, stressing that processes and topography play a major role in governing the rates of backwasting. The rates of backwasting from modern glacial environments should serve as input to de-icing models for ancient dead-ice areas in order to assess the mode and duration of deposition.A challenge for future explorations of dead-ice environments is to obtain long-term records of field-based monitoring of melt progression. Furthermore, many modern satellite-borne sensors have high potentials for recordings of multi-temporal Digital Elevation Models (DEMs) for detection and quantification of changes in dead-ice environments. In recent years, high-accuracy DEMs from airborne laser scanning altimetry (LiDAR) are emerging as an additional data source. However, time series of high-resolution aerial photographs remain essential for both visual inspection and high-resolution stereographic DEM production.     

Diet shifts of Caribbean grunts (Haemulidae) and snappers (Lutjanidae) and the relation with nursery-to-coral reef migrations

The spatial size distribution of grunts and snappers have previously indicated the separation of juveniles in nursery habitats from the adults on the coral reef. This implies life cycle migrations from nursery habitats (such as seagrass beds and mangroves) to the coral reef. If diet shifts are related to such migrations, then the diets of these fish must change before or around the fish size at which such migrations take place. A wide size range of juveniles of two grunt species (Haemulon sciurus and Haemulon flavolineatum) and of two snapper species (Lutjanus apodus and Ocyurus chrysurus) were caught in seagrass beds and mangroves, and their gut contents identified and quantified. Regression analysis between fish size and dietary importance of small crustaceans showed a negative relationship in all four species. Positive relations were found for H. sciurus, L. apodus and O. chrysurus between fish length and the dietary importance of decapods, and for L. apodusand O. chrysurus between fish length and prey fish importance. Critical changes in the fish diets with fish size were examined by application of a Canonical Correspondence Analysis (CCA). The CCA yielded three clusters of size-classes of fishes with similar diets, and application of a Mantel test showed that each of these clusters had significantly different diets, and that each cluster diet was significantly specialised. The size at which a fish species ‘switched’ from one cluster to another was compared with size-at-maturity data and with the typical size at which these species migrate from the nursery habitats to the coral reef. H. sciurus and H. flavolineatum may be prompted to migrate from the nursery habitats to coral reef habitats because of dietary changes, or because of the development of the gonads. For L. apodus and O. chrysurus, a dietary changeover forms a more likely explanation for nursery-to-reef migrations than does sexual maturation because these species reach maturity at sizes much larger than the maximum size of individuals found in nursery habitats. Although other factors may theoretically initiate or promote the migration patterns, the results of this study indicate that ontogenetic dietary changes may crucially influence the nursery-to-coral reef migrations of these reef fish species.     

Eddy Diffusion Coefficients of Suspended Particulate Matter: Effects of Wind Energy Transfer and Stratification

Gross sedimentation rates (GSR) have been measured using sediment traps placed at nine different levels above the bed (0·3, 0·5, 0·8, 1·0, 2·0, 4·0, 6·0, 8·0 and 10·0 m). The sediment traps were deployed for 1·25 years and recovered 28 times during the study period. Low average GSR values of 5·5 g m^-2 day^-1 were obtained at 10·0 m, and high average GSR values of 114·8 g m^-2 day^-1 were obtained at 0·3 m. An expression for the eddy diffusion coefficient of suspended particulate matter (K_s), based on the measured GSR is given. The expression has been used for modelling of K_s at the different trap levels above the bed. High values (≈42 cm² s^-1) of K_s were obtained at the upper traps, whereas low values (≈2 cm² s^-1) were obtained near the bed. Comparison between level of turbulent energy in terms of shear stress at the boundaries of the water column, i.e. from the wind and the bed flow, showed that wind energy exceeded that of the bed flow by a factor 16. At 5·0 m K_s was positively correlated (r=0·66) to the eddy diffusion coefficient of momentum (K_m) derived from the wind energy transfer to the water, giving an average β of 0·5 for K_s =βK_m. The density difference between surface and bottom waters has been designated a parameter of stratification, and is discussed in relation to variations of K_s and K_m .