A modelling framework for the assessment of the impacts of alternative policy and management options on the sustainability of Finnish agrifood systems

Recently, a new project focussing on integrated assessment modelling of agrifood systems (IAM-Tools) has been launched at MTT Agrifood Research Finland to gather, evaluate, refine and develop these component models and to link tem in an IAM framework for Finnish conditions

Simulation of winter wheat yield and its variability in different climates of Europe: A comparison of eight crop growth models

We compared the performance of eight widely used, easily accessible and well-documented crop growth simulation models (APES, CROPSYST, DAISY, DSSAT, FASSET, HERMES, STICS and WOFOST) for winter wheat (Triticum aestivum L.) during 49 growing seasons at eight sites in northwestern, Central and southeastern Europe. The aim was to examine how different process-based crop models perform at the field scale when provided with a limited set of information for model calibration and simulation, reflecting the typical use of models for large-scale applications, and to present the uncertainties related to this type of model application. Data used in the simulations consisted of daily weather statistics, information on soil properties, information on crop phenology for each cultivar, and basic crop and soil management information. Our results showed that none of the models perfectly reproduced recorded observations at all sites and in all years, and none could unequivocally be labelled robust and accurate in terms of yield prediction across different environments and crop cultivars with only minimum calibration. The best performance regarding yield estimation was for DAISY and DSSAT, for which the RMSE values were lowest (1428 and 1603 kg ha−1) and the index of agreement (0.71 and 0.74) highest. CROPSYST systematically underestimated yields (MBE – 1186 kg ha−1), whereas HERMES, STICS and WOFOST clearly overestimated them (MBE 1174, 1272 and 1213 kg ha−1, respectively). APES, DAISY, HERMES, STICS and WOFOST furnished high total above-ground biomass estimates, whereas CROPSYST, DSSAT and FASSET provided low total above-ground estimates. Consequently, DSSAT and FASSET produced very high harvest index values, followed by HERMES and WOFOST. APES and DAISY, on the other hand, returned low harvest index values. In spite of phenological observations being provided, the calibration results for wheat phenology, i.e. estimated dates of anthesis and maturity, were surprisingly variable, with the largest RMSE for anthesis being generated by APES (20.2 days) and for maturity by HERMES (12.6). The wide range of grain yield estimates provided by the models for all sites and years reflects substantial uncertainties in model estimates achieved with only minimum calibration. Mean predictions from the eight models, on the other hand, were in good agreement with measured data. This applies to both results across all sites and seasons as well as to prediction of observed yield variability at single sites – a very important finding that supports the use of multi-model estimates rather than reliance on single model

Systematically missing confounders in individual participant data meta-analysis of observational cohort studies.

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohort

Leaf litter decomposition -- Estimates of global variability based on Yasso07 model

Litter decomposition is an important process in the global carbon cycle. It accounts for most of the heterotrophic soil respiration and results in formation of more stable soil organic carbon (SOC) which is the largest terrestrial carbon stock. Litter decomposition may induce remarkable feedbacks to climate change because it is a climate-dependent process. To investigate the global patterns of litter decomposition, we developed a description of this process and tested the validity of this description using a large set of foliar litter mass loss measurements (nearly 10 000 data points derived from approximately 70 000 litter bags). We applied the Markov chain Monte Carlo method to estimate uncertainty in the parameter values and results of our model called Yasso07. The model appeared globally applicable. It estimated the effects of litter type (plant species) and climate on mass loss with little systematic error over the first 10 decomposition years, using only initial litter chemistry, air temperature and precipitation as input variables. Illustrative of the global variability in litter mass loss rates, our example calculations showed that a typical conifer litter had 68% of its initial mass still remaining after two decomposition years in tundra while a deciduous litter had only 15% remaining in the tropics. Uncertainty in these estimates, a direct result of the uncertainty of the parameter values of the model, varied according to the distribution of the litter bag data among climate conditions and ranged from 2% in tundra to 4% in the tropics. This reliability was adequate to use the model and distinguish the effects of even small differences in litter quality or climate conditions on litter decomposition as statistically significant.Comment: 19 Pages, to appear in Ecological Modellin

Why do crop models diverge substantially in climate impact projections? A comprehensive analysis based on eight barley crop models

Robust projections of climate impact on crop growth and productivity by crop models are key to designing effective adaptations to cope with future climate risk. However, current crop models diverge strongly in their climate impact projections. Previous studies tried to compare or improve crop models regarding the impact of one single climate variable. However, this approach is insufficient, considering that crop growth and yield are affected by the interactive impacts of multiple climate change factors and multiple interrelated biophysical processes. Here, a new comprehensive analysis was conducted to look holistically at the reasons why crop models diverge substantially in climate impact projections and to investigate which biophysical processes and knowledge gaps are key factors affecting this uncertainty and should be given the highest priorities for improvement. First, eight barley models and eight climate projections for the 2050s were applied to investigate the uncertainty from crop model structure in climate impact projections for barley growth and yield at two sites: Jokioinen, Finland (Boreal) and Lleida, Spain (Mediterranean). Sensitivity analyses were then conducted on the responses of major crop processes to major climatic variables including temperature, precipitation, irradiation, and CO2, as well as their interactions, for each of the eight crop models. The results showed that the temperature and CO2 relationships in the models were the major sources of the large discrepancies among the models in climate impact projections. In particular, the impacts of increases in temperature and CO2 on leaf area development were identified as the major causes for the large uncertainty in simulating changes in evapotranspiration, above-ground biomass, and grain yield. Our findings highlight that advancements in understanding the basic processes and thresholds by which climate warming and CO2 increases will affect leaf area development, crop evapotranspiration, photosynthesis, and grain formation in contrasting environments are needed for modeling their impacts.Peer reviewe

The socio-demographic patterning of sexual risk behaviour: a survey of young men in Finland and Estonia

<p>Abstract</p> <p>Background</p> <p>Sexually transmitted infections (STIs) among the youth are an increasing challenge for public health in Europe. This study provided estimates of men's (18–25 years) sexual risk behaviour and self-reported STIs and their socio-demographic patterning in Finland and Estonia; two countries that are geographically close, but have very different STI epidemics.</p> <p>Method</p> <p>Nationally representative cross-sectional population surveys with comparable survey questions were used. Data from self-administered questionnaires for 1765 men aged 18–25 years in Finland (85% of the age cohort was included in the sampling frame, 95% of the sample responded) and 748 in Estonia, with a response rate of 43% respectively, were analysed. Socio-demographic patterning of multiple partners, condom use and self-reported STIs are presented was studied using multiple logistic regression analysis.</p> <p>Results</p> <p>The main findings focus on associations found within each country. In Finland, higher age, low education and to a lesser extent relationship with a non-steady partner increased the likelihood of reporting multiple lifetime-partners, while in Estonia only higher age and low education revealed this effect. In relation to unprotected intercourse, in Finland, higher age, low education and relationship status with a steady partner increased the likelihood of reporting unprotected intercourse. In Estonia, the same was observed only for relationship status. In Finland the likelihood of self-reported STIs increased by older age and lower education and decreased by being with a non-steady partner, while in Estonia, a non-significant increase in self-reported STIs was observed only in the older age group.</p> <p>Conclusion</p> <p>A clear socio-demographic patterning for sexual behaviour and self-reported STIs was revealed in Finland, but a less consistent trend was seen in Estonia. The findings of this study suggest that prevention strategies should focus in Finland on less educated singles and in Estonia on young men generally.</p

Inequalities in health and health service utilisation among reproductive age women in St. Petersburg, Russia: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Russian society has faced dramatic changes in terms of social stratification since the collapse of the Soviet Union. During this time, extensive reforms have taken place in the organisation of health services, including the development of the private sector. Previous studies in Russia have shown a wide gap in mortality between socioeconomic groups. There are just a few studies on health service utilisation in post-Soviet Russia and data on inequality of health service use are limited. The aim of the present study was to analyse health (self-rated health and self-reported chronic diseases) and health care utilisation patterns by socioeconomic status (SES) among reproductive age women in St. Petersburg.</p> <p>Methods</p> <p>The questionnaire survey was conducted in 2004 (n = 1147), with a response rate of 67%. Education and income were used as dimensions of SES. The association between SES and health and use of health services was assessed by logistic regression, adjusting for age.</p> <p>Results</p> <p>As expected low SES was associated with poor self-rated health (education: OR = 1.48; personal income: OR = 1.42: family income: OR = 2.31). University education was associated with use of a wider range of outpatient medical services and increased use of the following examinations: Pap smear (age-adjusted OR = 2.06), gynaecological examinations (age-adjusted OR = 1.62) and mammography among older (more than 40 years) women (age-adjusted OR = 1.98). Personal income had similar correlations, but family income was related only to the use of mammography among older women.</p> <p>Conclusions</p> <p>Our study suggests a considerable inequality in health and utilisation of preventive health service among reproductive age women. Therefore, further studies are needed to identify barriers to health promotion resources.</p