No abstract

We investigated a relatively unexplored area of soil science: the fitting of parameterized models to particle-size distribution (a subject more thoroughly explored in sedimentology). Comparative fitting of different models requires the use of statistical indices enabling rational selection of an optimum model, i.e., a model that balances the improvement in fit often achieved by increasing the number of parameters,/>, against model simplicity retained by minimizing p. Five models were tested on cumulative mass-size data for 71 texturally diverse New Zealand soils: a one-parameter (p = 1) Jaky model borrowed from geotechnics; the standard lognormal model (p = 2); two modified lognormal models (each withp= 3); and the bimodal lognormal model (p = 3). The Jaky and modified lognormal models have not previously been introduced into the soil science literature. Three statistical comparators were used: the coefficient of determination, R 2 ; the F statistic; and the C f statistic of Mallows. The bimodal model and one modified lognormal model (denoted ORL) best fit the data. The bimodal model gave a marginally better fit, but incorporates a sub-clay mode (untestable with the present data), so we adopted the ORL model as the physically best benchmark for comparison of other models. The simple Jaky oneparameter model gave a good fit to data for many of the soils, better than the standard lognormal model for 23 soils. The model comparison methods described have potential utility in other areas of soil science. The C p statistic is advocated as the best statistic for model selection.A FREQUENT NEED in soil science is to fit parameterized models to data. Examples include the fitting of adjustable, analytic functions to data for the soil moisture characteristic, hydraulic conductivity function, or PSD. Often several candidate models exist, posing the problem of choice. In general, algorithms for fitting such models minimize an aggregated discrepancy between observed and model-estimated data. A lower bound to this discrepancy is set by experimental errors in the observed data. Often (though not always), increasing/; in a model will improve the fit; however, increasing/? may sacrifice simplicity and utility of the model, and may simply be an empirical expedient for conforming the model to fit the data. The first test for admitting an additional parameter is to check for its statistical significance. This can be done via a Student's Mest or Wald test (Gallant, 1987). Failure in this test means the additional parameter overparameterizes the model. Also, if the aggregate error produced by the model is less than random experimental error, the model is again overparameterized, though in a different sense. Selection of an optimum model from a group thus requires use of a sensitive discriminating statistic. Here, an optimum model is defined as one selected by balancing the minimization of some objective function (measuring aggregate discrepancy) against minimization of p.We explored the application of new parametric Mallows (1...

Corticotropin-releasing hormone (CRH) is an important regulator of adrenocorticotropin (ACTH) secretion from pituitary corticotroph cells. The intracellular signaling system that underlies this process involves modulation of voltage-sensitive Ca2+ channel activity, which leads to the generation of Ca2+ action potentials and influx of Ca2+. However, the mechanisms by which Ca2+ channel activity is modulated in corticotrophs are not currently known. We investigated this process in a Hodgkin-Huxley-type mathematical model of corticotroph plasma membrane electrical responses. We found that an increase in the L-type Ca2+ current was sufficient to generate action potentials from a previously resting state of the model. The increase in the L-type current could be elicited by either a shift in the voltage dependence of the current toward more negative potentials, or by an increase in the conductance of the current. Although either of these mechanisms is potentially responsible for the generation of action potentials, previous experimental evidence favors the former mechanism, with the magnitude of the shift required being consistent with the experimental findings. The model also shows that the T-type Ca2+ current plays a role in setting the excitability of the plasma membrane, but does not appear to contribute in a dynamic manner to action potential generation. Inhibition of a K+ conductance that is active at rest also affects the excitability of the plasma membrane.

SUMMARYRumen and caecal digesta were collected, under anaesthetic, from eight sheep offered either hay, pelleted concentrate or pasture at the Johnston Memorial Laboratory, Lincoln University during 1991. Subsamples of digesta were incubated at 39 mC for 1 h after adjustment of pH within the range 0n5-12 by the addition of H # SO % or NaOH. The samples were centrifuged at 30 000 g for 30 min and magnesium (Mg) concentration measured in the 30 000 g supernatant fraction and in total digesta to assess Mg solubility. In rumen digesta, Mg solubility declined from 0n86 at pH 5 to 0n30 at pH 7 and differences in response between diets were small. Magnesium solubility in caecal digesta was generally higher than in ruminal digesta, and particularly at pH values 6. At pH 7 the difference was twofold. Moreover, differences were observed between diets in the rate of decline in solubility in caecal digesta with increasing pH. At pH 5, 0n90 of Mg from hay and concentrate diets was soluble compared with only 0n8 for pasture. At pH 7, Mg solubility in caecal digesta from hay and concentrate-fed animals was almost double that from pasture-fed animals (0n64 and 0n62 v. 0n36, respectively). The implications of the findings for Mg homoeostasis in ruminants are discussed.

No abstract