Environmental modeling of uranium interstitial compositions of non-stoichiometric oxides: experimental and theoretical analysis

Study of uranium interstitial compositions of non-stoichiometric oxides UO_2+x (x ∈ 0.1–0.02) in gas and condense phases has been presented, using various soft-ionization mass spectrometric methods such as ESI-, APCI-, and MALDI-MS at a wide dynamic temperature gradient (∈ 25–300 °C). Linearly polarized vibrational spectroscopy has been utilized in order to assign unambiguously, the vibrational frequencies of uranium non-stoichiometric oxides. Experimental design has involved xUO_2.66·yUO_2.33, xUO_2.66·yUO_2.33/SiO₂, xUO_2.66·yUO_2.33/SiO₂ (NaOH) and SiO₂/x′NaOH·y′UO₂(NO₃)₂·6H₂O, multicomponent systems (x = 1, y ∈ 0.1–1.0 and x′ = 1, y′ ∈ 0.1–0.6) as well as phase transitions UO₂(NO₃)₂·6H₂O → {U₄O₉(UO_2.25)} → U₃O₇(UO_2.33) → U₃O₈(UO_2.66) → {UO₃}, thus ensuring a maximal representativeness to real environmental conditions, where diverse chemical, geochemical and biochemical reactions, including complexation and sorption onto minerals have occurred. Experimental factors such as UV-irradiation, pH, temperature, concentration levels, solvent types and ion strength have been taken into consideration, too. As far as uranium speciation represents a challenging analytical task in terms of chemical identification diverse coordination species, mechanistic aspects relating incorporation of oxygen into UO _2+x form the shown full methods validation significantly impacts the field of environmental radioanalytical chemistry. UO₂ is the most commonly used fuel in nuclear reactors around the globe; however, a large non-stoichiometric range ∈ UO_1.65–UO_2.25 has occurred due to radiolysis of water on UO₂ surface yielding to H₂O₂, OH^·, and more. Each of those compositions has different oxygen diffusion. And in this respect enormous effort has been concentrated to study the potential impact of hazardous radionuclide on the environment, encompassing from the reprocessing to the disposal stages of the fuel waste, including the waste itself, the processes in the waste containers, the clay around the containers, and geological processes. In a broader sense, thereby, this study contributes to field of environmental analysis highlighting the great ability of various soft-ionization MS methods, particularly, MALDI-MS one, for direct assay of complex multicomponent heterogeneous mixtures at fmol–attomol concentration ranges, along with it the great instrumental features allowing, not only meaningful quantitative, but also structural information of the analytes, thus making the method indispensable for environmental speciation of radionuclides, generally.     

Parameter fitting in dynamic models

We consider the numerical approaches for the least squares estimation of the parameter vector p in the initial value problem y′ = g(t, y, p), y(t₀) = y₀(p) when observations are available on some or all components of the vector y(t). Special attention is paid to the development of techniques which, although not global, are less sensitive to initial parameter estimates than the standard approach employing the sensitivity equations. Experience indicates that interactive approaches can be very valuable when good starting parameter approximations are unavailable. We describe the main features of our interactive parameter fitting package PARFIT. This package contains standard techniques employing the sensitivity equations as well as special algorithms designed to improve poor parameter estimates. These special algorithms have been selected and developed with user interaction in mind. We describe in detail one special approach designed for the case when observations are not available on all state variables. An example (using computer generated observations) is presented to illustrate this approach. Finally, the power of an interactive approach is demonstrated with two examples involving attempts to model physically observed phenomena.     

Application of a Random Forest algorithm to predict spatial distribution of the potential yield of Ruditapes philippinarum in the Venice lagoon, Italy

We present a modelling framework that combines machine learning techniques and Geographic Information Systems to support the management of an important aquaculture species, Manila clam (Ruditapes philippinarum). We use the Venice lagoon (Italy), the first site in Europe for the production of R. philippinarum, to illustrate the potential of this modelling approach. To investigate the relationship between the yield of R. philippinarum and a set of environmental factors, we used a Random Forest (RF) algorithm. The RF model was tuned with a large data set (n = 1698) and validated by an independent data set (n = 841). Overall, the model provided good predictions of site-specific yields and the analysis of marginal effect of predictors showed substantial agreement among the modelled responses and available ecological knowledge for R. philippinarum. The most influent environmental factors for yield estimation were percentage of sand in the sediment, salinity, and water depth. Our results agree with findings from other North Adriatic lagoons. The application of the fitted RF model to continuous maps of all the environmental variables allowed estimates of the potential yield for the whole basin. Such a spatial representation enabled site-specific estimates of yield in different farming areas within the lagoon. We present a possible management application of our model by estimating the potential yield under the current farming distribution and comparing it to a proposed re-organization of the farming areas. Our analysis suggests a reduction of total yield is likely to result from the proposed re-organization.     

Theoretical analysis of change in forest carbon use efficiency with stand development: A case study on Hinoki Cypress (Chamaecyparis obtusa (Sieb. et Zucc.) Endl.) plantation from the seedling stage

Changes in carbon use efficiency (CUE), which is defined as the ratio of net primary production (NPP) to gross primary production (GPP), were estimated for the aerial parts of the Hinoki Cypress (Chamaecyparis obtusa (Sieb. et Zucc.) Endl.) with respect to stand development. The analysis incorporated previously published data from the early stages of stand development, namely the seedling stages of the cypress. For this analysis, a simple mathematical model to assess the changes in CUE was developed by incorporating data on physiological variables and mass of woody species. The CUE tended to increase with increases in the aboveground biomass of the stand, and then decreased gradually despite increases in the aboveground biomass. The CUE-value (0.28, 0.39) of the seedling stage was lower than that (0.33-0.58) of the young or mature trees. To examine the effect of physiological variables and mass on CUE, the ratios of the specific respiration rate to the specific photosynthetic rate (r/a) and the leaf biomass to the aboveground biomass or leaf mass ratio (y_L/y_T) were calculated. The low value of CUE at the seedling stage was due to the high ratio of specific respiration rate to specific photosynthetic rate r/a, but was not due to the high value of the leaf mass ratio y_L/y_T. In addition, the decline in CUE associated with older stages of stand development was due to the decreasing changes in y_L/y_T, and the r/a ratio did not influence the change in CUE.     

Photochemical indicators of ozone sensitivity: application in the Pearl River Delta,China

Surface O₃ production has a highly nonlinear relationship with its precursors. The spatial and temporal heterogeneity of O₃-NO _x -VOC-sensitivity regimes complicates the control-decision making. In this paper, the indicator method was used to establish the relationship between O₃ sensitivity and assessment indicators. Six popular ratios indicating ozone-precursor sensitivity, HCHO/NO _y , H₂O₂/ HNO₃, O₃/NO _y , O₃/NO _z , O₃/HNO₃, and H₂O₂/NO _z , were evaluated based on the distribution of NO_x- and VOC-sensitive regimes. WRF-Chem was used to study a serious ozone episode in fall over the Pearl River Delta (PRD). It was found that the south-west of the PRD is characterized by a VOCsensitive regime, while its north-east is NO _x -sensitive, with a sharp transition area between the two regimes. All indicators produced good representations of the elevated ozone hours in the episode on 6 November 2009, with H₂O₂/HNO₃ being the best indicator. The threshold sensitivity levels for HCHO/NO_y, H₂O₂/HNO₃, O₃/NO _y , O₃/NO _z , O₃/HNO₃, and H₂O₂/NO _z were estimated to be 0.41, 0.55, 10.2, 14.0, 19.1, and 0.38, respectively. Threshold intervals for the indicators H₂O₂/HNO₃, O₃/NO _y , O₃/NO _z , O₃/HNO₃, and H₂O₂/NO _z were able to identify more than 95% of VOC- and NO _x -sensitive grids. The ozone episode on 16 November 16 2008 was used to independently verify the results, and it was found that only H₂O₂/HNO₃ and H₂O₂/NO _z were able to differentiate the ozone sensitivity regime well. Hence, these two ratios are suggested as the most appropriate indicators for identifying fall ozone sensitivity in the PRD. Since the species used for indicators have seasonal variation, the utility of those indicators for other seasons should be investigated in the future work.

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Introducing effects of temperature and CO2 elevation on tree growth into a statistical growth and yield model

Impacts of elevated temperature and CO₂ on tree growth were introduced into a statistical growth and yield model for Finnish conditions based on corresponding predictions obtained from a physiological growth model. This one-way link between models was made by means of species-specific transfer functions describing the increase in stem volume growth of trees as a function of elevated temperature and CO₂, stand density and the tree's competition status in a stand of Scots pine (Pinus sylvestris), silver birch (Betula pendula) and Norway spruce (Picea abies). This method allows the inner dynamics of the statistical model to be followed when the impacts of temperature and CO₂ elevation on tree growth are introduced into the calculation of volume growth and further allocated between diameter and height growth. In this way compatibility with previous predictions of tree growth by means of statistical models and related model systems under current climatic conditions could be retained.The performance of the statistical model with species-specific transfer functions was evaluated by comparing its predictions with corresponding predictions given by a physiological model under conditions of elevated temperature and CO₂. These calculations revealed that the growth response of individual trees to elevated temperature and CO₂ can be introduced into the statistical model from a physiological growth model with an outcome that results in fairly satisfactory growth responses at the stand level as well.     

In the mixed world of predictive biology—Contradiction or support

Statistical prediction is a tool and aim in ecology and wildlife management and conservation. A prediction may either be supported by or contradicted by observations of an unknown set of observations. A contradiction occurs if the prediction is not included within the range of the unknown observations, i.e. the prediction misses the cloud of observations completely. Mixed-effects models, frequently used for statistical assessment of clustered data, carry information needed for calculating the probability of such contradictions. Here we present a new versatile statistic, the probability of contradiction (P (Contra)), that describes how often we would anticipate a new cluster of observations contradicting our predictions. Some benefits of P (Contra) are: (1) easy to calculate and intuitive interpretation, (2) comparability between datasets, (3) inclusion of residual correlation, (4) summary of the multitude of information from mixed models into one statistics, and (5) applicable to local mixed-effect models.     

Sociality,Bateman’s gradients,and the polygynandrous genetic mating system of round-tailed ground squirrels (<Emphasis Type="Italic">Xerospermophilus tereticaudus</Emphasis>)

Historically, most mammals have been classified as polygynous; although recent molecular evidence suggests that many mammals may be polygynandrous, particularly the ground-dwelling sciurids. We genotyped 351 round-tailed ground squirrels (Xerospermophilus tereticaudus) using seven microsatellite loci to determine paternity in 31 litters from 2004 to 2007. Polygyny was evident in all years except in 2007, when the population size was reduced. Multiple paternity occurred in the majority of litters (55%) with 2.5 ± 0.26 sires/litter (n = 31). Forty-nine percent of resident males (n = 114) sired offspring, and of males that sired offspring (n = 56) 27% sired young in multiple litters in a single breeding season. Litter size was positively correlated with the number of sires. Through an indirect analysis of paternity, we found 21 litters (68%) with an average relatedness of 0.5 or less. Males had a greater opportunity for sexual selection (I _s = 1.60) than females (I _s = 0.40); Bateman’s gradient was also greater in males (1.07 ± 0.04, n = 56) than females (0.82 ± 0.08, n = 31). The mating system in round-tailed ground squirrels defined through genetic analyses and Bateman’s gradients is polygynandrous compared to the previously suggested polygynous mating system as established by behavioral observations and fits within the predictions of the ground squirrel sociality models. Upon evaluating the predictions of the sociality models among sciurid species, we found a negative relationship between the level of sociality with litter size and the average percentage of multiple paternity within a litter. Thus, recent genetic information and reclassification of mating systems support the predictions of the ground-dwelling squirrel sociality models.     

Testing the robustness of primary production models in shallow coastal areas: a case study

In this paper we investigate the robustness of a dynamic model, which describes the dynamic of the seagrass Zostera marina, with respect to the inter-annual variability of the two main forcing functions of primary production models in eutrophicated environments. The model was previously applied to simulate the seasonal evolution of this species in the Lagoon of Venice during a specific year and calibrated against time series of field data. In the this paper, we present and discuss the results which were obtained by forcing the model using time series of site-specific daily values concerning the solar radiation intensity and water temperature. The latter was estimated by means of a regression model, whose input variable was a site-specific time series of the air temperature. The regression model was calibrated using a year-long time series of hourly observations. The Z. marina model was first partially recalibrated against the same data set that was used in the original paper. Subsequently, the model was forced using a 7-year-long time series of the driving functions, in order to check the reliability of its long-term predictions. Even though the calibration gave satisfactory results, the multi-annual trends of the output variables were found to be in contrast with the observed evolution of the seagrass biomasses. Since detailed information about the air temperature and solar radiation are often available, these findings suggest that the testing of the ecological consistency of the evolution of primary production models in the long term would provide additional confidence in their results, particularly in those cases in which the scarcity of field data does not allow one to perform a formal corroboration/validation of these models.     

Modeling compensated root water and nutrient uptake

Plant root water and nutrient uptake is one of the most important processes in subsurface unsaturated flow and transport modeling, as root uptake controls actual plant evapotranspiration, water recharge and nutrient leaching to the groundwater, and exerts a major influence on predictions of global climate models. In general, unsaturated models describe root uptake relatively simple. For example, root water uptake is mostly uncompensated and nutrient uptake is simulated assuming that all uptake is passive, through the water uptake pathway only. We present a new compensated root water and nutrient uptake model, implemented in HYDRUS. The so-called root adaptability factor represents a threshold value above which reduced root water or nutrient uptake in water- or nutrient-stressed parts of the root zone is fully compensated for by increased uptake in other soil regions that are less stressed. Using a critical value of the water stress index, water uptake compensation is proportional to the water stress response function. Total root nutrient uptake is determined from the total of active and passive nutrient uptake. The partitioning between passive and active uptake is controlled by the a priori defined concentration value c_max. Passive nutrient uptake is simulated by multiplying root water uptake with the dissolved nutrient concentration, for soil solution concentration values below c_max. Passive nutrient uptake is thus zero when c_max is equal to zero. As the active nutrient uptake is obtained from the difference between plant nutrient demand and passive nutrient uptake (using Michaelis–Menten kinetics), the presented model thus implies that reduced passive nutrient uptake is compensated for by active nutrient uptake. In addition, the proposed root uptake model includes compensation for active nutrient uptake, in a similar way as used for root water uptake. The proposed root water and nutrient uptake model is demonstrated by several hypothetical examples, for plants supplied by water due to capillary rise from groundwater and surface drip irrigation.     

Mathematical analysis of change in forest carbon use efficiency with stand development: A case study on Abies veitchii Lindl.

Changes in carbon use efficiency (CUE), which is defined as the ratio of net primary production (NPP) to gross primary production (GPP), were analyzed for Abies veitchii Lindl. forests with respect to stand development by developing a simple mathematical model incorporating data on physiological variables and leaf mass ratio. A decrease in CUE with stand development was successfully expressed as a function of stand biomass (y) based on the following three assumptions: (1) a power-law relationship between mean respiration and mean individual tree mass, (2) a power-functional relationship between mean gross primary production and mean individual tree mass, and (3) self-thinning relationship between stand biomass and density. Based on this model, a parameter of CUE–y relationship was defined, and it was clarified that CUE decrease with stand development is caused not by the ratio of specific respiration rate to specific gross photosynthetic rate, but by leaf mass ratio. Since CUE is high in young forests, helpful information on selecting woody species when planting seedlings was provided from the viewpoints of reducing CO₂ in the atmosphere and global warming.     

A proposal of an indicator for quantifying model robustness based on the relationship between variability of errors and of explored conditions

The evaluation of biophysical models is usually carried out by estimating the agreement between measured and simulated data and, more rarely, by using indices for other aspects, like model complexity and overparameterization. In spite of the importance of model robustness, especially for large area applications, no proposals for its quantification are available. In this paper, we would like to open a discussion on this issue, proposing a first approach for a quantification of robustness based on the variability of model error to variability of explored conditions ratio. We used modelling efficiency (EF) for quantifying error in model predictions and a normalized agrometeorological index (SAM) based on cumulated rainfall and reference evapotranspiration to characterize the conditions of application. Population standard deviations of EF and SAM were used to quantify their variability. The indicator was tested for models estimating meteorological variables and crop state variables. The values provided by the robustness indicator (I_R) were discussed according to the models’ features and to the typology and number of processes simulated. I_R increased with the number of processes simulated and, within the same typology of model, with the degree of overparameterization. No correlation were found between I_R and two of the most used indices of model error (RRMSE, EF). This supports its inclusion in integrated systems for model evaluation.     

Integrating soil carbon cycling with that of nitrogen and phosphorus in the watershed model SWAT: Theory and model testing

In this paper we describe and test a sub-model that integrates the cycling of carbon (C), nitrogen (N) and phosphorus (P) in the Soil Water Assessment Tool (SWAT) watershed model. The core of the sub-model is a multi-layer, one-pool soil organic carbon (S_C) algorithm, in which the decomposition rate of S_C and input rate to S_C (through decomposition and humification of residues) depend on the current size of S_C. The organic N and P fluxes are coupled to that of C and depend on the available mineral N and P, and the C:N and N:P ratios of the decomposing pools. Tillage explicitly affects the soil organic matter turnover rate through tool-specific coefficients. Unlike most models, the turnover of soil organic matter does not follow first order kinetics. Each soil layer has a specific maximum capacity to accumulate C or C saturation (S_x) that depends on texture and controls the turnover rate. It is shown in an analytical solution that S_x is a parameter with major influence in the model C dynamics. Testing with a 65-yr data set from the dryland wheat growing region in Oregon shows that the model adequately simulates the S_C dynamics in the topsoil (top 0.3 m) for three different treatments. Three key model parameters, the optimal decomposition and humification rates and a factor controlling the effect of soil moisture and temperature on the decomposition rate, showed low uncertainty as determined by generalized likelihood uncertainty estimation. Nonetheless, the parameter set that provided accurate simulations in the topsoil tended to overestimate S_C in the subsoil, suggesting that a mechanism that expresses at depth might not be represented in the current sub-model structure. The explicit integration of C, N, and P fluxes allows for a more cohesive simulation of nutrient cycling in the SWAT model. The sub-model has to be tested in forestland and rangeland in addition to agricultural land, and in diverse soils with extreme properties such high or low pH, an organic horizon, or volcanic soils.     

Predicting intertidal organism temperatures with modified land surface models

Animals and plants in the marine intertidal zone live at the interface between terrestrial and marine environments. This zone is likely to be a sensitive indicator of the effects of climate change in coastal ecosystems, because of several key characteristics including steep environmental gradients, rapid temperature changes during tide transitions, fierce competition for limited space, and a community of mostly sessile organisms. Here we describe a modular modeling approach using modifications to a meteorological land surface model to determine body temperatures of the ecologically dominant rocky intertidal mussel Mytilus californianus, as a tool that can be used as a proxy for ecological performance. We validate model results against in situ measurements made with biomimetic body temperature sensors. Model predictions lie within the range of variability of biomimetic measurements, based on observations over a 4-year period at sites along 1700 km of the US west coast from southern California (34.5°N) to northern Washington (48.4°N). Our modular approach can be easily applied to many situations in the intertidal zone, including bare rock, mussel, barnacle, and algal beds, salt-marsh grasses, and sand- and mud-flats, by modifying the “vegetation layer” in a standard meteorological land surface model. Biophysical models such as these, which link ecological processes to changing climates through predictions of body temperature, are essential for understanding biogeographic patterns of physiological stress and mortality risk.     

Information-theory approach to allometric growth of marine organisms

Allometric growth investigations are usually conducted by fitting the allometric model (L) (y, x are morphometric characters and b the allometric exponent), which is quite simple both conceptually and mathematically, and its parameters are easy to estimate by linear regression. However b is not necessarily constant and it may change either continuously or abruptly at specific breakpoints; thus, the simple L model quite often fails to describe allometric growth successfully. In the current context, a better alternative is proposed, based on Kullback–Leibler (K-L) information theory and multi-model inference (MMI). Allometric growth was investigated in eight marine species: the bivalves Pecten jacobaeus and Pinna nobilis, the squids Todarodes sagittatus and Todaropsis eblanae, the crab Pachygrapsus marmoratus (females), the ghost shrimp Pestarella tyrrhena (males), and the fishes Trachurus trachurus and Sparus aurata. In each of the eight species, a pair of body parts was measured and the allometric growth of one body part in relation to the other (reference dimension) was studied, by fitting five different candidate models including: the simple allometric model, two models assuming that b changed continuously and two other assuming that b had a breakpoint. For each species, the ‘best’ model was selected by minimizing the small-sample, bias-corrected form of the Akaike Information Criterion. To quantify the plausibility of each model, given the data and the set of five models, the ‘Akaike weight’ w _i of each model was calculated; based on w _i the average model was estimated for each case. MMI is beneficial, more robust, and may reveal more information than the classical approach. As demonstrated with the given examples, estimation of b from the linear model, when it was not supported by the data, revealed some characteristic pitfalls, such as concluding positive allometry when there is actually negative or vice versa, or reporting allometry when the data in reality support isometric growth or vice versa.     

多氯代苯并噻吩分子空间坐标指数与气相色谱保留时间的QSPR研究

运用Chem Office软件绘制37个多氯代苯并噻吩三维图,并得到对应的分子空间坐标Pi(xi,yi,zi)。以多氯代苯并噻吩分子的原子距离指数、分子空间特征指数、分子电性距离矢量、氯原子数为分子描述变量,采用多元线性回归和BP人工神经网络建立描述变量与多氯代苯并噻吩的气相色谱保留时间的QSPR模型。结果表明:多元线性回归建模相关系数R=0.9970,SD=2.1830,基于BP人工神经网络建立的模型R=0.9996,SD=0.3123。为多氯代苯并噻吩分子结构与物性的QSPR研究提供了新思路。     

Convexity in projection matrices: Projection to a calibration problem

Convexity, as a fundamental property of sets and functions defined on convex sets, plays an important role in many mathematical and applied disciplines, including extremal and optimal-control problems. We prove the set of all feasible projection matrices in a general class of matrix models for stage-structured population dynamics to be convex and the dominant eigenvalue (λ₁) of any projection 2 × 2 matrix to be either a convex, or a concave function on a simplex of the matrix first-row entries (i.e., stage-specific reproduction rates). The latter is also conjectured for the general n × n case. Though looking far from practical needs of matrix population models, this mathematical result has appeared to be quite useful in solving a practical problem to calibrate the projection matrix, i.e., to estimate all the stage-specific vital rates, from empirical data. The data from monitoring of individual life histories of marked plants on permanent sample plots during successive years enable direct calculation of the stage-specific survival and ontogenetic transition rates, but the rates of reproduction do remain uncertain as far as the parent plants can hardly be determined for the (not yet marked!) recruitment.     

Comprehensive evaluation of heavy metal contamination of sediment in Lake Dianchi by using modified AHP method and 137Cs dating

Through the use of general sampling and measurement by ¹³⁷ Cs dating, problems regarding the absence of monitoring data can easily be resolved. Further, weighted values need to be determined while Environment Quality Comprehensive Index (EQCI) is commonly used as applied in environmental quality comprehensive evaluation. In order to overcome the subjectivity in determining weights, the modified Analytical Hierarchy Process (AHP) method was designed. The modified AHP method involved the following key procedures: First, the parameters y _i1 and y _i2 were calculated based on the monitoring data; second, the factors were put in order according to the symbol and value of y _i1 and y _i2; third, the continuous odd integers, which represented the importance of factors, were given to factors according to their seating order; and, fourth, the factor weights were determined from the pair-wise comparison matrix calculated by the ratio of the given odd integers. Therefore, the weights were completely based on the monitoring data. In the present study, the comprehensive quality of sediments in five sections of Lake Dianchi were evaluated and the results indicated that the current contamination of sediments in each lake section is much more serious than at any other time in history.     

Metabolism,enzymic activities and cold adaptation in Antarctic mesopelagic fishes

Several species of Antarctic mesopelagic fishes that have different minimal depths of occurrence but the same environmental temperature were collected in November–December 1983 and in March 1986 between 0 and 1 000 m in the open water near the marginal ice zone in the vicinity of 60°S 40°W (1983) and 65°S 46°W (1986), and oxygen consumption rate (V _{O 2}) and the activity of two metabolic enzymes, lactate dehydrogenase (LDH, an indicator of the anaerobic potential of locomotory muscle) and citrate synthase (CS, an indicator of citric acid cycle activity or aerobic potential), were determined. In four dominant species, whole-individual oxygen-consumption rate (y, ml O₂ individual^–1 h^–1) varied with weight (X, g) according to the equation y=aX ^b, with b values falling between 0.889 and 1.029. The relation of weight-specific LDH activity (y, U g^–1 wet wt) with weight (x, g) was also described by the equation y=aX ^b, with b values varying between 0.229 and 1.025. Weight-specific CS activity declined with weight, with b values from-0.031 to-0.369. V _{2 O}, LDH activity and CS activity all declined markedly with increased species' minimum depth of occurrence (the depth below which 90% of a species' population lives). Comparisons with previous studies on ecologically equivalent species of the California Borderland indicate that depth-related decreases in metabolism are the result of adapted traits of deeper-living species, not declining temperature within the water column. The metabolic rate of Antarctic mesopelagic fishes is approximately twice that of California species at equivalent temperatures; similar rates were found at the normal habitat temperatures of the two groups. Thus, a well-developed compensation for temperature is present in the Antarctic fishes: cold adaptation. Differences in enzymic activity among species, and among different sized individuals of a species are related to differences in metabolic rate and locomotory capacity. Enzymic indices can be used to estimate metabolic rates and evaluate ecological parameters such as predatory strategies and niche separation.     

Development and application of “U.S.E.D.”: A hydroclimate lake stratification model

Two model types are currently in use to model the thermal stratification cycle in lakes and reservoirs: the eddy diffusion and the mixed layer (or integral energy) approaches. Here the former is analysed and developments are proposed to remove the empiricisms previously implicit in these models. These discussions permit the reformulation of K_H0 independently of current shear, together with an expression for R_i. The deduced formulae are in good agreement with observations. The newly formulated model (the University of Salford eddy diffusion model, U.S.E.D.) is subsequently used in simulations of lakes and reservoirs at different latitudes which are found to be in good agreement with observations without requiring inter-site calibration.