Leaf area index estimation with MODIS reflectance time series and model inversion during full rotations of Eucalyptus plantations

The leaf area index (LAI) of fast-growing Eucalyptus plantations is highly dynamic both seasonally and interannually, and is spatially variable depending on pedo-climatic conditions. LAI is very important in determining the carbon and water balance of a stand, but is difficult to measure during a complete stand rotation and at large scales. Remote-sensing methods allowing the retrieval of LAI time series with accuracy and precision are therefore necessary. Here, we tested two methods for LAI estimation from MODIS 250m resolution red and near-infrared (NIR) reflectance time series. The first method involved the inversion of a coupled model of leaf reflectance and transmittance (PROSPECT4), soil reflectance (SOILSPECT) and canopy radiative transfer (4SAIL2). Model parameters other than the LAI were either fixed to measured constant values, or allowed to vary seasonally and/or with stand age according to trends observed in field measurements. The LAI was assumed to vary throughout the rotation following a series of alternately increasing and decreasing sigmoid curves. The parameters of each sigmoid curve that allowed the best fit of simulated canopy reflectance to MODIS red and NIR reflectance data were obtained by minimization techniques. The second method was based on a linear relationship between the LAI and values of the GEneralized Soil Adjusted Vegetation Index (GESAVI), which was calibrated using destructive LAI measurements made at two seasons, on Eucalyptus stands of different ages and productivity levels. The ability of each approach to reproduce field-measured LAI values was assessed, and uncertainty on results and parameter sensitivities were examined. Both methods offered a good fit between measured and estimated LAI (R(2) = 0.80 and R(2) = 0.62 for model inversion and GESAVI-based methods, respectively), but the GESAVI-based method overestimated the LAI at young ages. (C) 2010 Elsevier Inc. All rights reserved.

MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass

The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m(3)/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests. (C) 2011 Elsevier Inc. All rights reserved.

DSC estimation of structural and textural parameters of SBA-15 silica using water probe

The aim of this study was to use DSC and X-ray diffraction measurements to determine the pore size and pore wall thickness of highly ordered SBA-15 materials. The DSC curves showed two endothermic events during the heating cycle. These events were due to the presence of water inside and outside of mesopores. The results of pore radius, wall thickness and pore volume measurements were in good agreement with the results obtained by nitrogen adsorption measurement, XRD and transmission electron microscopy.

Influence of Plasma Protein Binding on Pharmacodynamics: Estimation of In Vivo Receptor Affinities of beta Blockers Using a New Mechanism-Based PK-PD Modelling Approach

The objective of this investigation was to examine in a systematic manner the influence of plasma protein binding on in vivo pharmacodynamics. Comparative pharmacokinetic-pharmacodynamic studies with four beta blockers were performed in conscious rats, using heart rate under isoprenaline-induced tachycardia as a pharmacodynamic endpoint. A recently proposed mechanism-based agonist-antagonist interaction model was used to obtain in vivo estimates of receptor affinities (K(B),(vivo)). These values were compared with in vitro affinities (K(B),(vitro)) on the basis of both total and free drug concentrations. For the total drug concentrations, the K(B),(vivo) estimates were 26, 13, 6.5 and 0.89 nM for S(-)-atenolol, S(-)-propranolol, S(-)-metoprolol and timolol. The K(B),(vivo) estimates on the basis of the free concentrations were 25, 2.0, 5.2 and 0.56 nM, respectively. The K(B),(vivo)-K(B),(vitro) correlation for total drug concentrations clearly deviated from the line of identity, especially for the most highly bound drug S(-)-propranolol (ratio K(B),(vivo)/K(B),(vitro) similar to 6.8). For the free drug, the correlation approximated the line of identity. Using this model, for beta-blockers the free plasma concentration appears to be the best predictor of in vivo pharmacodynamics. (C) 2008 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:3816-3828, 2009

Evaluation of extractants for estimation of the phytoavailable trace metals in soils

Despite its environmental (and financial) importance, there is no agreement in the literature as to which extractant most accurately estimates the phytoavailability of trace metals in soils. A large dataset was taken from the literature, and the effectiveness of various extractants to predict the phytoavailability of Cd, Zn, Ni, Cu, and Pb examined across a range of soil types and contamination levels. The data suggest that generally, the total soil trace metal content, and trace metal concentrations determined by complexing agents (such as the widely used DTPA and EDTA extractants) or acid extractants (such as 0.1 M HCl and the Mehlich 1 extractant) are only poorly correlated to plant phytoavailability. Whilst there is no consensus, it would appear that neutral salt extractants (such as 0.01 M CaCl2 and 0.1 M NaNO3) provide the most useful indication of metal phytoavailability across a range of metals of interest, although further research is required.

Bioelectrical impedance analysis for the estimation of body composition in rats

Bioelectrical impedance analysis (BIA) was used to assess body composition in rats fed on either standard laboratory diet or on a high-fat diet designed to induce obesity. Bioelectrical impedance analysis predictions of total body water and thus fat-free mass (FFM) for the group mean values were generally within 5% of the measured values by tritiated water ((H2O)-H-3) dilution. The limits of agreement for the procedure were, however, large, approximately +/-25%, limiting the applicability of the technique for measurement of body composition in individual animals.

Cost-benefit analysis of alternative forms of hedgerow intercropping in the Philippine uplands

Considerable resources have been expended promoting hedgerow intercropping with shrub legumes to farmers in the Philippine uplands. Despite the resources committed to research and extension, persistent adoption by farmers has been limited to low cost versions of the technology including natural vegetation and grass strips. In this paper, cost-benefit analysis is used to compare the economic returns from traditional open-field maize farming with returns from intercropping maize between leguminous shrub hedgerows, natural vegetation strips and grass strips. An erosion/productivity model, Soil Changes Under Agroforestry, was used to predict the effect of erosion on maize yields. Key informant surveys with experienced maize farmers were used to derive production budgets for the alternative farming methods. The economic incentives revealed by the cost-benefit analysis help to explain the adoption of maize farming methods in the Philippine uplands. Open-field farming without hedgerows has been by far the most popular method of maize production, often with two or more fields cropped in rotation. There is little persistent adoption of hedgerow intercropping with shrub legumes because sustained maize yields are not realised rapidly enough to compensate farmers for establishment and maintenance costs. Natural vegetation and grass strips are more attractive to farmers because of lower establishment costs, and provide intermediate steps to adoption. Rural finance, commodity pricing and agrarian reform policies influence the incentives for maize farmers in the Philippine uplands to adopt and maintain hedgerow intercropping.

Cost functions and duality for stochastic technologies

Cost functions dual to stochastic production technologies are derived and their properties are discussed. These cost functions are shown to be consistent with expected-utility maximization without placing serious structural restrictions on the underlying technology.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

The cost of life expectancy and the implicit social valuation of life

A new method of estimating the economic value of life is proposed. Using cross-country data, an equation is estimated to explain life expectancy as a function of real consumption of goods and services. The associated cost function for life expectancy in terms of the prices of specific goods and services is used to estimate the cost of a reduction in age-specific mortality rates sufficient to save the life of one person. The cost of saving a life in OECD countries is as much as 1000 times that in the poorest countries. Ethical implications are discussed.

Cost-effectiveness analysis of humanitarian relief interventions: visceral leishmaniasis treatment in the Sudan

Spending by aid agencies on emergencies has quadrupled over the last decade, to over US$ 6 billion. To date, cost-effectiveness has seldom been considered in the prioritization and evaluation of emergency interventions. The sheer volume of resources spent on humanitarian aid and the chronicity of many humanitarian interventions call for more attention to be paid to the issue of 'value for money'. In this paper we present data from a major humanitarian crisis, an epidemic of visceral leishmaniasis (VL) in war-torn Sudan. The special circumstances provided us, in retrospect, with unusually accurate data on excess mortality, costs of the intervention and its effects, thus allowing us to express cost-effectiveness as the cost per Disability Adjusted Life Year (DALY) averted. The cost-effectiveness ratio, of US$ 18.40 per DALY (uncertainty range between US$ 13.53 and US$ 27.63), places the treatment of VL in Sudan among health interventions considered 'very flood value for money' (interventions of less than US$ 25 per DALY). We discuss the usefulness of this analysis to the internal management of the VL programme, the procurement of funds for the programme, and more generally, to priority setting in humanitarian relief interventions. We feel that in evaluations of emergency interventions attempts could be made more often to perform cost-effectiveness analyses, including the use of DALYs, provided that the outcomes of these analyses are seen in the broad context of the emergency situation and its consequences on the affected population. This paper provides a first contribution to what is hoped to become an international database of cost-effectiveness studies of health outcome such as the DALY.

Life-cycle preferences over consumption and health: when is cost-effectiveness analysis equivalent to cost-benefit analysis?

This paper studies life-cycle preferences over consumption and health status. We show that cost-effectiveness analysis is consistent with cost-benefit analysis if the Lifetime utility function is additive over time, multiplicative in the utility of consumption and the utility of health status, and if the utility of consumption is constant over time. We derive the conditions under which the lifetime utility function takes this form, both under expected utility theory and under rank-dependent utility theory, which is currently the most important nonexpected utility theory. If cost-effectiveness analysis is consistent with cost-benefit analysis, it is possible to derive tractable expressions for the willingness to pay for quality-adjusted life-years (QALYs). The willingness to pay for QALYs depends on wealth, remaining life expectancy, health status, and the possibilities for intertemporal substitution of consumption. (C) 1999 Elsevier Science B.V. All rights reserved.

Estimation of contribution of changes in classic risk factors to trends in coronary-event rates across the WHO MONICA Project populations

Background From the mid-1980s to mid-1990s, the WHO MONICA Project monitored coronary events and classic risk factors for coronary heart disease (CHD) in 38 populations from 21 countries. We assessed the extent to which changes in these risk factors explain the variation in the trends in coronary-event rates across the populations. Methods In men and women aged 35-64 years, non-fatal myocardial infarction and coronary deaths were registered continuously to assess trends in rates of coronary events. We carried out population surveys to estimate trends in risk factors. Trends in event rates were regressed on trends in risk score and in individual risk factors. Findings Smoking rates decreased in most male populations but trends were mixed in women; mean blood pressures and cholesterol concentrations decreased, body-mass index increased, and overall risk scores and coronary-event rates decreased. The model of trends in 10-year coronary-event rates against risk scores and single risk factors showed a poor fit, but this was improved with a 4-year time lag for coronary events. The explanatory power of the analyses was limited by imprecision of the estimates and homogeneity of trends in the study populations. Interpretation Changes in the classic risk factors seem to partly explain the variation in population trends in CHD. Residual variance is attributable to difficulties in measurement and analysis, including time lag, and to factors that were not included, such as medical interventions. The results support prevention policies based on the classic risk factors but suggest potential for prevention beyond these.