An application of the GLUE methodology for estimating the parameters of the INCA-N model

The conceptual and parameter uncertainty of the semi-distributed INCA-N (Integrated Nutrients in Catchments-Nitrogen) model was studied using the GLUE (Generalized Likelihood Uncertainty Estimation) methodology combined with quantitative experimental knowledge, the concept known as 'soft data'. Cumulative inorganic N leaching, annual plant N uptake and annual mineralization proved to be useful soft data to constrain the parameter space. The INCA-N model was able to simulate the seasonal and inter-annual variations in the stream-water nitrate concentrations, although the lowest concentrations during the growing season were not reproduced. This suggested that there were some retention processes or losses either in peatland/wetland areas or in the river which were not included in the INCA-N model. The results of the study suggested that soft data was a way to reduce parameter equifinality, and that the calibration and testing of distributed hydrological and nutrient leaching models should be based both on runoff and/or nutrient concentration data and the qualitative knowledge of experimentalist. (c) 2006 Elsevier B.V. All rights reserved.

Robust dynamics of Amazon dieback to climate change with perturbed ecosystem model parameters

Climate change science is increasingly concerned with methods for managing and integrating sources of uncertainty from emission storylines, climate model projections, and ecosystem model parameterizations. In tropical ecosystems, regional climate projections and modeled ecosystem responses vary greatly, leading to a significant source of uncertainty in global biogeochemical accounting and possible future climate feedbacks. Here, we combine an ensemble of IPCC-AR4 climate change projections for the Amazon Basin (eight general circulation models) with alternative ecosystem parameter sets for the dynamic global vegetation model, LPJmL. We evaluate LPJmL simulations of carbon stocks and fluxes against flux tower and aboveground biomass datasets for individual sites and the entire basin. Variability in LPJmL model sensitivity to future climate change is primarily related to light and water limitations through biochemical and water-balance-related parameters. Temperature-dependent parameters related to plant respiration and photosynthesis appear to be less important than vegetation dynamics (and their parameters) for determining the magnitude of ecosystem response to climate change. Variance partitioning approaches reveal that relationships between uncertainty from ecosystem dynamics and climate projections are dependent on geographic location and the targeted ecosystem process. Parameter uncertainty from the LPJmL model does not affect the trajectory of ecosystem response for a given climate change scenario and the primary source of uncertainty for Amazon 'dieback' results from the uncertainty among climate projections. Our approach for describing uncertainty is applicable for informing and prioritizing policy options related to mitigation and adaptation where long-term investments are required.

On the time for fold surfaces to order during the crystallization of polyethylene from the melt and its dependence on molecular parameters

New experiments underpin the interpretation of the basic division in crystallization behaviour of polyethylene in terms of whether or not there is time for the fold surface to order before the next molecular layer is added at the growth front. For typical growth rates, in Regime 11, polyethylene lamellae form with disordered {001} fold surfaces then transform, with lamellar thickening and twisting, towards the more-ordered condition found for slower crystallization in Regime 1, in which lamellae form with and retain {201} fold surfaces. Several linear and linear-low-density polyethylenes have been used to show that, for the same polymer crystallized alone or in a blend, the growth rate at which the change in initial lamellar condition occurs is reasonably constant thereby supporting the concept of a specific time for surfaces to attain the ordered {201}) state. This specific time, in the range from milliseconds to seconds, increases with molecular length, and in linear-low-density polymer, for higher branch contents. (c) 2006 Elsevier Ltd. All rights reserved.

Genetic parameters and evaluations from single- and multiple-trait analysis of dairy cow fertility and milk production

Genetic parameters and breeding values for dairy cow fertility were estimated from 62 443 lactation records. Two-trait analysis of fertility and milk yield was investigated as a method to estimate fertility breeding values when culling or selection based on milk yield in early lactation determines presence or absence of fertility observations in later lactations. Fertility traits were calving interval, intervals from calving to first service, calving to conception and first to last service, conception success to first service and number of services per conception. Milk production traits were 305-day milk, fat and protein yield. For fertility traits, range of estimates of heritability (h(2)) was 0.012 to 0.028 and of permanent environmental variance (c(2)) was 0.016 to 0.032. Genetic correlations (r(g)) among fertility traits were generally high ( > 0.70). Genetic correlations of fertility with milk production traits were unfavourable (range -0.11 to 0.46). Single and two-trait analyses of fertility were compared using the same data set. The estimates of h(2) and c(2) were similar for two types of analyses. However, there were differences between estimated breeding values and rankings for the same trait from single versus multi-trait analyses. The range for rank correlation was 0.69-0.83 for all animals in the pedigree and 0.89-0.96 for sires with more than 25 daughters. As single-trait method is biased due to selection on milk yield, a multi-trait evaluation of fertility with milk yield is recommended. (C) 2002 Elsevier Science B.V. All rights reserved.

Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture

Maize silage nutritive quality is routinely determined by near infrared reflectance spectroscopy (NIRS). However, little is known about the impact of sample preparation on the accuracy of the calibration to predict biological traits. A sample population of 48 maize silages representing a wide range of physiological maturities was used in a study to determine the impact of different sample preparation procedures (i.e., drying regimes; the presence or absence of residual moisture; the degree of particle comminution) on resultant NIR prediction statistics. All silages were scanned using a total of 12 combinations of sample pre-treatments. Each sample preparation combination was subjected to three multivariate regression techniques to give a total of 36 predictions per biological trait. Increased sample preparations procedure, relative to scanning the unprocessed whole plant (WP) material, always resulted in a numerical minimisation of model statistics. However, the ability of each of the treatments to significantly minimise the model statistics differed. Particle comminution was the most important factor, oven-drying regime was intermediate, and residual moisture presence was the least important. Models to predict various biological parameters of maize silage will be improved if material is subjected to a high degree of particle comminution (i.e., having been passed through a 1 mm screen) and developed on plant material previously dried at 60 degrees C. The extra effort in terms of time and cost required to remove sample residual moisture cannot be justified. (c) 2005 Elsevier B.V. All rights reserved.

Using near infrared reflectance spectroscopy (NIRS) to predict the biological parameters of maize silage

The microbial fermentability, ruminal degradability and digestibility of 48 maize silages were determined using in vitro gas production (GP), in situ degradability and in vitro digestibility procedures. The silages were produced from forage maize harvested throughout the summer of 1998, and represent a wide range of physiological maturities. Large variations among samples were observed for all biological parameters, with the exception of in vitro digestibility and the asymptote of in vitro GP. The potential of near infrared reflectance spectroscopy (NIRS) to predict the biological parameters measured was determined by regression of the biological data against the respective spectral profile. NIRS demonstrated only a moderate ability (R-2 > 0.60-0.80) to predict in vitro digestibility, modelled kinetics of gas production (excluding the asymptote of gas production) and the modelled ruminally soluble dry matter (DM) fraction. Calibration statistics for remaining biological parameters were unacceptably poor (R-2 = 0.60). (C) 2004 Elsevier B.V. All rights reserved.

Influence of vegetation on the local climate and hydrology in the tropics: sensitivity to soil parameters

Land use change with accompanying major modifications to the vegetation cover is widespread in the tropics, due to increasing demands for agricultural land, and may have significant impacts on the climate. This study investigates (1) the influence of vegetation on the local climate in the tropics; (2) how that influence varies from region to region; and (3) how the sensitivity of the local climate to vegetation, and hence land use change, depends on the hydraulic characteristics of the soil. A series of idealised experiments with the Hadley Centre atmospheric model, HadAM3, are described in which the influence of vegetation in the tropics is assessed by comparing the results of integrations with and without tropical vegetation. The sensitivity of the results to the soil characteristics is then explored by repeating the experiments with a differing, but equally valid, description of soil hydraulic parameters. The results have shown that vegetation has a significant moderating effect on the climate throughout the tropics by cooling the surface through enhanced latent heat fluxes. The influence of vegetation is, however, seasonally dependent, with much greater impacts during the dry season when the availability of surface moisture is limited. Furthermore, there are significant regional variations both in terms of the magnitude of the cooling and in the response of the precipitation. Not all regions show a feedback of vegetation on the local precipitation; this result has been related both to vegetation type and to the prevailing meteorological conditions. An important finding has been the sensitivity of the results to the specification of the soil hydraulic parameters. The introduction of more freely draining soils has changed the soil-moisture contents of the control, vegetated system and has reduced, significantly, the climate sensitivity to vegetation and by implication, land use change. Changes to the soil parameters have also had an impact on the soil hydrology and its interaction with vegetation, by altering the partitioning between fast and slow runoff processes. These results raise important questions about the representation of highly heterogeneous soil characteristics in climate models, as well as the potential influence of land use change on the soil characteristics themselves.

Relationships between transition period diet, metabolic parameters and fertility in lactating dairy cows

Cows in severe negative energy balance after calving have reduced fertility, mediated by metabolic signals influencing the reproductive system. We hypothesised that transition diet could alter metabolic status after calving, and thus influence fertility. Multiparous dairy cows were assigned to four transition groups 6 weeks pre-calving and fed: (a) basal control diet (n = 10); (b) basal diet plus barley (STARCH, n = 10); (c) basal diet plus Soypass (high protein, HiPROT, n = 11); or (d) no transition management (NoTRANS, n = 9). All cows received the same lactational diet. Blood samples, body weights and condition scores (BCS) were collected weekly. Fertility parameters were monitored using milk progesterone profiles and were not affected by transition diet. Data from all cows were then combined and analysed according to the pattern of post-partum ovarian activity. Cows with low progesterone profiles had significantly lower insulin-like growth factor-I (IGF-I) and insulin concentrations accompanied by reduced dry matter intakes (DMIs), BCS and body weight. Cows with prolonged luteal activity (PLA) were older and tended to have lower IGF-I. Analysis based on the calving to conception interval revealed that cows which failed to conceive (9/40) also had reduced IGF-I, BCS and body weight. Fertility was, therefore, decreased in cows which were in poor metabolic status following calving. This was reflected in reduced circulating IGF-I concentrations and compromised both ovarian activity and conception. There was little effect of the transition diets on these parameters. (C) 2003 Elsevier Science Inc. All rights reserved.