Nutrient transfer functions: the site of integration between feeding behaviour and nutritional physiology

Summary. We describe and extend a graphical approach to quantitative nutrition that focuses on the interplay between behavioural and physiological components of nutritional regulation. The site of integration is the nutrient transfer function, which is the function describing the time course of nutrient transfer between serially connected nutritional compartments (e.g., from the gut to the blood). The relationship between the shape of the nutrient transfer function and the temporal patterns of feeding determines the values of two key quantitative parameters of nutrition: the rate ('power') and the efficiency of nutrient acquisition. The approach can be extended to consider, in addition to the short-term behavioural and physiological decisions made by animals, some ecological determinants and longer-term, life history consequences of such decisions. Most importantly, this category of models can provide insights into the interplay among the various nutrients in an animal's diet. We illustrate this using hypothetical examples, and also present preliminary data for the power-efficiency relationships of protein and digestible carbohydrates in locusts. Finally, we consider existing evidence for the various means available to these and other insects for regulating such relationships. Received 24 September 1997; accepted 9 December 1997.     

Semi-parametric statistical approaches for space-time process prediction

The problem of estimation and prediction of a spatial-temporal stochastic process, observed at regular times and irregularly in space, is considered. A mixed formulation involving a non- parametric component, accounting for a deterministic trend and the effect of exogenous variables, and a parametric component representing the purely spatio-temporal random variation is proposed. Correspondingly, a two-step procedure, first addressing the estimation of the non- parametric component, and then the estimation of the parametric component is developed from the residual series obtained, with spatial-temporal prediction being performed in terms of suitable spatial interpolation of the temporal variation structure. The proposed model formula-tion, together with the estimation and prediction procedure, are applied using a Gaussian ARMA structure for temporal modelling to space-time forecasting from real data of air pollution concentration levels in the region surrounding a power station in northwest Spain.     

Modelling and assessment of South African elephant Loxodonta africana population persistence

The use of a quantitative population growth model to investigate the persistence of South African elephant populations is explored. The model provides quantitative assessments of population persistence and confidence intervals for estimated parameters based purely on population size estimates. The analysis supports the view that most of the larger populations in the region are secure. This view is further supported by a lack of density dependent effects in most of the recovering populations and the high population rates of increase observed. This predominantly positive prognosis is in contrast with that emerging from most of the rest of the African continent where the populations are under greater threat because of habitat restriction and direct human conflict. This preliminary assessment of elephant population persistence suggests that “viable” populations may lie between 400 and 6000 individuals. Although not inconsistent with information-greedy genetic and demographic models, the relationship between population growth versus genetic and demographic models should be further investigated. The implementation of a metapopulation management strategy towards these smaller populations is advocated. In addition, as all of the populations included in this analysis have been afforded some degree of protection since the 1920s, continued protection would be a prerequisite for their continued survival.     

Major and trace elements of selected pedons in the USA

Few studies of soil geochemistry over large geographic areas exist, especially studies encompassing data from major pedogenic horizons that evaluate both native concentrations of elements and anthropogenically contaminated soils. In this study, pedons (n = 486) were analyzed for trace (Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Zn) and major (Al, Ca, Fe, K, Mg, Na, P, Si, Ti, Zr) elements, as well as other soil properties. The objectives were to (i) determine the concentration range of selected elements in a variety of U.S. soils with and without known anthropogenic additions, (ii) illustrate the association of elemental source and content by assessing trace elemental content for several selected pedons, and (iii) evaluate relationships among and between elements and other soil properties. Trace element concentrations in the non-anthropogenic dataset (NAD) were in the order Mn > (Zn, Cr, Ni, Cu) > (Pb, Co) > (Cd, Hg), with greatest mean total concentrations for the Andisol order. Geometric means by horizon indicate that trace elements are concentrated in surface and/or B horizons over C horizons. Median values for trace elements are significantly higher in surface horizons of the anthropogenic dataset (AD) over the NAD. Total Al, Fe, cation exchange capacity (CEC), organic C, pH, and clay exhibit significant correlations (0.56, 0.74, 0.50, 0.31, 0.16, and 0.30, respectively) with total trace element concentrations of all horizons of the NAD. Manganese shows the best inter-element correlation (0.33) with these associated total concentrations. Total Fe has one of the strongest relationships, explaining 55 and 30% of the variation in total trace element concentrations for all horizons in the NAD and AD, respectively.     

METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL1

ABSTRACT: The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.     

Spatiotemporal variability of wet atmospheric nitrogen deposition to the Neuse River Estuary, North Carolina

Excessive nitrogen (N) loading to N-sensitive waters such as the Neuse River estuary (North Carolina) has been shown to promote changes in microbial and algal community composition and function (harmful algal blooms), hypoxia and anoxia, and fish kills. Previous studies have estimated that wet atmospheric deposition of nitrogen (WAD-N), as deposition of dissolved inorganic nitrogen (DIN: NO3-, NH3/NH4+) and dissolved organic nitrogen, may contribute at least 15% of the total externally supplied or "new" N flux to the coastal waters of North Carolina. In a 3-yr study from June 1996 to June 1999, we calculated the weekly wet deposition of inorganic and organic N at eleven sites on a northwest-southeast transect in the watershed. The annual mean total (wet DIN + wet organics) WAD-N flux for the Neuse River watershed was calculated to be 956 mg N/m2/yr (15026 Mg N/yr). Seasonally, the spring (March-May) and summer (June-August) months contain the highest total weekly N deposition; this pattern appears to be driven by N concentration in precipitation. There is also spatial variability in WAD-N deposition; in general, the upper portion of the watershed receives the lowest annual deposition and the middle portion of the watershed receives the highest deposition. Based on a range of watershed N retention and in-stream riverine processing values, we estimate that this flux contributes approximately 24% of the total "new" N flux to the estuary.     

Respiration and lipid content of the Arctic copepod<Emphasis Type="Italic"> Calanus hyperboreus</Emphasis> overwintering 1 m above the seafloor at 2,300 m water depth in the Fram Strait

In August 2000 high concentrations of the dominant herbivorous copepod Calanus hyperboreus were detected in the Arctic Fram Strait, west of Spitsbergen, 1 m above the seafloor at 2,290 m water depth. Individuals from that layer were sampled by a hyper-benthic net attached to the frame of an epi-benthic sledge. For comparison, the vertical distribution of C. hyperboreus in the water column was studied simultaneously by a multiple opening/closing net haul from 2,250 m depth to the surface. Maximum abundance was found close to the surface with 6.6 and 10.0 ind. m^?3 at 0–50 m and 50–100 m depth, respectively. However, the major fraction of the population (>40%) occurred between 1,000 and 1,500 m depth. In the deepest layer (2,000–2,250 m) abundance measured 2.2 ind. m^?3 and was twice as high as between 100 and 1,000 m depth. In comparison to individuals from surface waters, copepods from the hyper-benthic layer were torpid and did not react to mechanical stimuli. Stage CV copepodids and females from the deep sample contained 4–10% less lipid and showed significantly reduced respiration rates of 0.24 and 0.26 ml O₂ h^?1 g^?1 dry mass (DM) as compared to surface samples (0.49 and 0.43 ml O₂ h^?1 g^?1 DM). All these observations indicate that the hyper-benthic part of the population had already started a dormant overwintering phase at great depth. Based on the lipid deposits and energy demands, the potential maximum duration of the non-feeding dormant phase was estimated at 76–110 days for females and at 98–137 days for CV copepodids, depending on what indispensable minimum lipid content was assumed. In any case, the estimated times could not meet the necessary requirements for a starvation period of >6 months until the next phytoplankton bloom in the following spring. The ecological implications of these results are discussed with respect to the life cycle and eco-physiological adaptations of C. hyperboreus to its high-Arctic habitat.     

Layered sphere-shaped TiO2 capped with gold nanoparticles on structural defects and their catalysis of formaldehyde oxidation

We describe here a one-step method for the synthesis of Au/TiO₂ nanosphere materials, which were formed by layered deposition of multiple anatase TiO₂ nanosheets. The Au nanoparticles were stabilized by structural defects in each TiO₂ nanosheet, including crystal steps and edges, thereby fixing the Au–TiO₂ perimeter interface. Reactant transfer occurred along the gaps between these TiO₂ nanosheet layers and in contact with catalytically active sites at the Au–TiO₂ interface. The doped Au induced the formation of oxygen vacancies in the Au–TiO₂ interface. Such vacancies are essential for generating active oxygen species (*O⁻) on the TiO₂ surface and Ti^3 + ions in bulk TiO₂. These ions can then form Ti^3 +–O⁻–Ti^4 + species, which are known to enhance the catalytic activity of formaldehyde (HCHO) oxidation. These studies on structural and oxygen vacancy defects in Au/TiO₂ samples provide a theoretical foundation for the catalytic mechanism of HCHO oxidation on oxide-supported Au materials.