Ecophysiology of the saguaro cactus (Carnegiea gigantea) in the Saguaro National Monument: relationship to symptoms of decline

The purpose of this study was to examine physiological correlates to the phenomenon of epidermal browning and saguaro decline in Saguaro National Monument. Gas exchange characteristics, surface temperatures, and the extent of epidermal browning in tissues of both healthy and declining saguaro cacti (Carnegiea gigantea) at different solar orientations were examined in eight long-term monitoring plots in the Rincon Mountain District of the Saguaro National Monument near Tucson, Arizona during both wet and dry seasons and years.Daily maximum surface temperatures were greatest on west-oriented tissues, as predicted by a simple model. However, south- and south-west-oriented tissues showed the highest browning indices, suggesting that browning may be more related to cumulative thermal loading than to extreme late afternoon temperature events. During the wet season, maximum nocturnal CO₂uptake rates and total nocturnal CO₂uptake were negatively correlated with browning index. Uptake rates during dry seasons and dry years was minimal, and not related to browning indices. However, healthy tissues of saguaros that also had tissues with high browning indices had wet-season maximum CO₂uptake rates as high as saguaros without damaged tissues, suggesting that the browning is not systemic but rather is tissue- and angle-specific. Instantaneous measures of water-use efficiency did not vary significantly or predictably by angle, but rather were greatest during night-time and in tissues when CO₂uptake was greatest. We suggest that browning symptoms on cacti are most likely due to natural abiotic stress, and are unrelated to systemic pollution stress or increased UV-B radiation.     

High matrix interference affecting detection of PAH metabolites in bile of Atlantic hagfish (Myxine glutinosa) used for biomonitoring of deep-water oil production

The characteristic biology and wide distribution of hagfish species makes them relevant for use in pollution biomonitoring at great water depths, particularly in regions where deep-water oil production may take place. The exposure of fish to petrogenic contaminants can normally be detected from the level of polycyclic aromatic hydrocarbon (PAH) metabolites in bile fluid. Some of these metabolites are strong fluorophores, allowing analytical detection by means of simple fluorometric techniques such as fixed wavelength fluorescence (FF) and synchronous fluorescence scanning (SFS). In the present study bile from Atlantic hagfish (Myxine glutinosa) collected in pristine areas (Barents Sea and southwestern Norway) displayed strong bile fluorescence levels, suggesting the presence of PAH contaminants. However, gas-chromatography-mass spectrometry (GC-MS) analyses ruled out PAHs as the origin for this fluorescence signal. Rather, the bile of Myxine contains components resulting in unusually strong background fluorescence interfering at the wavelength pairs used for detection of PAH metabolites. Possible background for the observed matrix interference and implications for detection of PAH metabolites in hagfish is discussed.     

Updating of snow depletion curve with remote sensing data

A method for using remotely sensed snow cover information in updating a hydrological model is developed, based on Bayes' theorem. A snow cover mass balance model structure adapted to such use of satellite data is specified, using a parametric snow depletion curve in each spatial unit to describe the subunit variability in snow storage. The snow depletion curve relates the accumulated melt depth to snow‐covered area, accumulated snowmelt runoff volume, and remaining snow water equivalent. The parametric formulation enables updating of the complete snow depletion curve, including mass balance, by satellite data on snow coverage. Each spatial unit (i.e. grid cell) in the model maintains a specific depletion curve state that is updated independently. The uncertainty associated with the variables involved is formulated in terms of a joint distribution, from which the joint expectancy (mean value) represents the model state. The Bayesian updating modifies the prior (pre‐update) joint distribution into a posterior, and the posterior joint expectancy replaces the prior as the current model state. Three updating experiments are run in a 2400 km² mountainous region in Jotunheimen, central Norway (61°N, 9°E) using two Landsat 7 ETM+ images separately and together. At 1 km grid scale in this alpine terrain, three parameters are needed in the snow depletion curve. Despite the small amount of measured information compared with the dimensionality of the updated parameter vector, updating reduces uncertainty substantially for some state variables and parameters. Parameter adjustments resulting from using each image separately differ, but are positively correlated. For all variables, uncertainty reduction is larger with two images used in conjunction than with any single image. Where the observation is in strong conflict with the prior estimate, increased uncertainty may occur, indicating that prior uncertainty may have been underestimated. Copyright © 2006 John Wiley & Sons, Ltd.     

Evaluation of storage–discharge relationships and recession analysis-based distributed hourly runoff simulation in large-scale,mountainous and snow-influenced catchment

ABSTRACT

Evaluation of a recession-based “top-down” model for distributed hourly runoff simulation in macroscale mountainous catchments is rare in the literature. We evaluated such a model for a 3090 km² boreal catchment and its internal sub-catchments. The main research question is how the model performs when parameters are either estimated from streamflow recession or obtained by calibration. The model reproduced observed streamflow hydrographs (Nash-Sutcliffe efficiency up to 0.83) and flow duration curves. Transferability of parameters to the sub-catchments validates the performance of the model, and indicates an opportunity for prediction in ungauged sites. However, the cases of parameter estimation and calibration excluding the effects of runoff routing underestimate peak flows. The lower end of the recession and the minimum length of recession segments included are the main sources of uncertainty for parameter estimation. Despite the small number of calibrated parameters, the model is susceptible to parameter uncertainty and identifiability problems.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR A. Carsteanu