Improving wheat simulation capabilities in Australia from a cropping systems perspective - II. Testing simulation capabilities of wheat growth

To simulate cropping systems, crop models must not only give reliable predictions of yield across a wide range of environmental conditions, they must also quantify water and nutrient use well, so that the status of the soil at maturity is a good representation of the starting conditions for the next cropping sequence. To assess the suitability for this task a range of crop models, currently used in Australia, were tested. The models differed in their design objectives, complexity and structure and were (i) tested on diverse, independent data sets from a wide range of environments and (ii) model components were further evaluated with one detailed data set from a semi-arid environment. All models were coded into the cropping systems shell APSIM, which provides a common soil water and nitrogen balance. Crop development was input, thus differences between simulations were caused entirely by difference in simulating crop growth. Under nitrogen non-limiting conditions between 73 and 85% of the observed kernel yield variation across environments was explained by the models. This ranged from 51 to 77% under varying nitrogen supply. Water and nitrogen effects on leaf area index were predicted poorly by all models resulting in erroneous predictions of dry matter accumulation and water use. When measured light interception was used as input, most models improved in their prediction of dry matter and yield. This test highlighted a range of compensating errors in all modelling approaches. Time course and final amount of water extraction was simulated well by two models, while others left up to 25% of potentially available soil water in the profile. Kernel nitrogen percentage was predicted poorly by all models due to its sensitivity to small dry matter changes. Yield and dry matter could be estimated adequately for a range of environmental conditions using the general concepts of radiation use efficiency and transpiration efficiency. However, leaf area and kernel nitrogen dynamics need to be improved to achieve better estimates of water and nitrogen use if such models are to be use to evaluate cropping systems. (C) 1998 Elsevier Science B.V.

Asymmetry and duration dependence in Australian GDP and unemployment

The per iodic structure of business cycles suggests that significant asymmetries are present over different phases of the cycle. This paper uses markov regime-switching models with fixed and duration dependent transition probabilities to directly model expansions, contractions and durations in Australian GDP growth and unemployment growth. Evidence is found of significant asymmetry in growth rates across expansions and contractions for both series. GDP contractions exhibit duration dependence implying that as output recessions age the likelihood of switching into an expansion phase increases. Unemployment growth does not exhibit duration dependence in either phase. Evidence is also presented that non-linearities in unemployment growth are well explained by the asymmetries in the GDP growth cycle. The analysis suggests that recessions are periods of rapid and intense job destruction, that Australian unemployment tends to ratchet up in recessionary periods and, in contrast to US and UK studies, that shocks to Australian unemployment growth are more persistent in recessions than expansions. [E37 C5 C41].

Perforin and interferon-gamma activities independently control tumor initiation, growth, and metastasis

Perforin (pfp) and interferon-gamma (IFN-gamma) together in C57BL/6 (B6) and BALB/c mouse strains provided optimal protection in 3 separate tumor models controlled by innate immunity. Using experimental (B6, RM-1 prostate carcinoma) and spontaneous (BALB/c, DA3 mammary carcinoma) models of metastatic cancer, mice deficient in both pfp and IFN-gamma were significantly less proficient than pfp- or IFN-gamma -deficient mice in preventing metastasis of tumor cells to the lung. Pfp and IFN-gamma -deficient mice were as susceptible as mice depleted of natural killer (NK) cells in both tumor metastasis models, and IFN-gamma appeared to play an early role in protection from metastasis, Previous experiments in a model of fibrosarcoma induced by the chemical carcinogen methylcholanthrene indicated an important role for NK1.1(+) T cells, Herein, both pfp and IFN-gamma played critical and independent roles in providing the host with protection equivalent to that mediated by NK1.1+ T cells, Further analysis demonstrated that IFN-gamma, but not pfp, controlled the growth rate of sarcomas arising in these mice. Thus, this is the first study to demonstrate that host IFN-gamma, and direct cytotoxicity mediated by cytotoxic lymphocytes expressing pfp independently contribute antitumor effector functions that together control the initiation, growth, and spread of tumors in mice, (C) 2001 by The American Society of Hematology.

A technological and organisational explanation for the size distribution of firms

This paper combines insights from the literature on the economics of organisation with traditional models of market structure to construct a theory of equilibrium firm size heterogeneity under the assumption of a homogenous product industry. It is possible that configurations consisting entirely of small firms (run by entrepreneurs with limited attention) and with larger firms (using managerial techniques to substitute away these limits to allow increasing returns technologies to become profitable) can arise in equilibrium. However, there also exist equilibrium configurations with the co-existence of large and small firms. The efficiency properties of these respective equilibria are discussed. Finally, the implications of an expanding market size are considered.

Structural change, balance-of-payments constraint, and economic growth: evidence from the multisectoral Thirlwall`s law

This paper contributes to the literature on balance-of-payments constrained growth by investigating how structural change identified with changes in the sectoral composition of exports and imports affects the external constraint We test both the original and a multisectoral version of Thirlwall`s law for a sample of Latin American and Asian countries The original Thirlwall s law is found to hold for all sample countries except South Korea, whereas the multisectoral analogue holds for all of them As the sectoral composition of exports and imports is found to matter for growth we analyze the evolution of each country`s weighted trade income elasticities

Import substitution and economic growth

Despite Latin America`s dismal performance between the 1950s and 1980s, the region experienced strong capital deepening. We suggest that these facts can be explained as a consequence of the restrictive trade regime adopted at that time. Our framework is based on a dynamic Heckscher-Ohlin model, with scale economies in the capital-intensive sector. Initially, the economy is open and produces only the labor-intensive good. The trade regime is modeled as a move to a closed economy. The model produces results consistent with the Latin American experience. Specifically, a Sufficiently small Country experiences no long-run income growth, but an increase in capital. (C) 2009 Elsevier B.V. All rights reserved.

Ecosystem process models at multiple scales for mapping tropical forest productivity

Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

Applying linear time-varying constraints to econometric models: With an application to demand systems

When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.

Crotamine toxicity and efficacy in mouse models of melanoma

Objectives: Selective anticancer cell activity for both cell-penetrating and cationic antimicrobial peptides has previously been reported. As crotamine possesses activities similar to both of these, this study investigates crotamine`s anticancer toxicity in vitro and in vivo. Research design and methods: In vitro cancer cell viability was evaluated after treatment with 1 and 5 mu g/ml of crotamine. In vivo crotamine cytotoxic effects in C57Bl/6J mice bearing B16-F10 primary cutaneous melanoma were tested, with two groups each containing 35 mice. The crotamine-treated group received 1 mu g/day of crotamine per animal, subcutaneously which was well tolerated; the untreated group received a placebo. Results: Crotamine at 5 mu g/ml was lethal to B16-F10, Mia PaCa-2 and SK-Mel-28 cells and inoffensive to normal cells. In vivo crotamine treatment over 21 days significantly delayed tumor implantation, inhibited tumor growth and prolonged the lifespan of the mice. Mice in the crotamine-treated group survived at significantly higher rates (n = 30/35) than those in the untreated group (n = 7/35) (significance calculated with the Kaplan-Meier estimator). The average tumor weight in the untreated group was 4.60 g but was only about 0.27 g in the crotamine-treated mice, if detectable. Conclusions: These data warrant further exploration of crotamine as a tumor inhibition compound.

Comparison of different nonlinear functions to describe Nelore cattle growth

This work aims to compare different nonlinear functions for describing the growth curves of Nelore females. The growth curve parameters, their (co) variance components, and environmental and genetic effects were estimated jointly through a Bayesian hierarchical model. In the first stage of the hierarchy, 4 nonlinear functions were compared: Brody, Von Bertalanffy, Gompertz, and logistic. The analyses were carried out using 3 different data sets to check goodness of fit while having animals with few records. Three different assumptions about SD of fitting errors were considered: constancy throughout the trajectory, linear increasing until 3 yr of age and constancy thereafter, and variation following the nonlinear function applied in the first stage of the hierarchy. Comparisons of the overall goodness of fit were based on Akaike information criterion, the Bayesian information criterion, and the deviance information criterion. Goodness of fit at different points of the growth curve was compared applying the Gelfand`s check function. The posterior means of adult BW ranged from 531.78 to 586.89 kg. Greater estimates of adult BW were observed when the fitting error variance was considered constant along the trajectory. The models were not suitable to describe the SD of fitting errors at the beginning of the growth curve. All functions provided less accurate predictions at the beginning of growth, and predictions were more accurate after 48 mo of age. The prediction of adult BW using nonlinear functions can be accurate when growth curve parameters and their (co) variance components are estimated jointly. The hierarchical model used in the present study can be applied to the prediction of mature BW in herds in which a portion of the animals are culled before adult age. Gompertz, Von Bertalanffy, and Brody functions were adequate to establish mean growth patterns and to predict the adult BW of Nelore females. The Brody model was more accurate in predicting the birth weight of these animals and presented the best overall goodness of fit.

Models for genetic evaluation of Nelore cattle mature body weight

Records of 18,770 Nelore animals, born from 1975 to 2002, in 8 herds participating in the Nelore Cattle Breeding Program, were analyzed to estimate genetic parameters for mature BW. The mature BW were analyzed as a single BW taken closest to 4.5 yr of age for each cow in the data file, considering BW starting from 2 (W2Y_S), 3 (W3Y_S), or 4 (W4Y_S) yr of age or as repeated records, including all BW starting from 2 (W2Y_R), 3 (W3Y_R), or 4 (W4Y_R) yr of age. The variance components were estimated by restricted maximum likelihood, fitting univariate and bivariate animal models, including weaning weight. The heritability estimates were 0.29, 0.34, 0.36, 0.41, 0.44, and 0.46 for W2Y_S, W3Y_S, W4Y_S, W2Y_R, W3Y_R, and W4Y_R, respectively. The repeatability estimates for W2Y_R, W3Y_R, and W4Y_R were 0.59, 0.64, and 0.72, respectively. Larger accuracy values associated with the EBV were obtained in the repeated records models. The results indicated the bivariate repeated records model as the most appropriate for analyzing mature BW.