Abstract Background Increasing the use of forest harvest residues for bioenergy production reduces greenhouse emissions from the use of fossil fuels. However, it may also reduce carbon stocks and habitats for deadwood dependent species. Consequently, simple tools for assessing the trade-offs of alternative management practices on forest dynamics and their services to people are needed. The objectives of this study were to combine mapping and simulation modelling to investigate the effects of forest management on ecosystem services related to carbon cycle in the case of bioenergy production; and to evaluate the suitability of this approach for assessing ecosystem services at the landscape level. Stand level simulations of forest growth and carbon budget were combined with extensive multi-source forest inventory data across a southern boreal landscape in Finland. Stochastic changes in the stand age class distribution over the study region were simulated to mimic variation in management regimes. Results The mapping framework produced reasonable estimates of the effects of forest management on a set of key ecosystem service indicators: the annual carbon stocks and fluxes of forest biomass and soil, timber and energy-wood production and the coarse woody litter production over a simulation period 2012–2100. Regular harvesting, affecting the stand age class distribution, was a key driver of the carbon stock changes at a landscape level. Extracting forest harvest residues in the final felling caused carbon loss from litter and soil, particularly with combined aboveground residue and stump harvesting. It also reduced the annual coarse woody litter production, demonstrating negative impacts on deadwood abundance and, consequently, forest biodiversity. Conclusions The refined mapping framework was suitable for assessing ecosystem services at the landscape level. The procedure contributes to bridging the gap between ecosystem service mapping and detailed simulation modelling in boreal forests. It allows for visualizing ecosystem services as fine resolution maps to support sustainable land use planning. In the future, more detailed models and a wider variety of ecosystem service indicators could be added to develop the method.

In this study, quantitative models of the agricultural sector and nutrient transport and cycling are used to analyse the impacts in the Baltic Sea of replacing the current Greening measures of the EU’s Common Agricultural Policy with a package of investments in manure handling. The investments aim at improving nutrient utilization and reducing nitrogen leaching, based on the assumption that lagging farms and regions can catch up with observed good practice. Our results indicate that such investments could reduce nitrogen surpluses in agriculture by 18% and nitrogen concentrations in the Baltic Sea by 1 to 9% depending on the basin. The Greening measures, in contrast, are found to actually increase nitrogen leaching.

Interest in measuring forest biomass and carbon stock has increased as a result of the United Nations Framework Convention on Climate Change, and sustainable planning of forest resources is therefore essential. Biomass and carbon stock estimates are based on the large area estimates of growing stock volume provided by national forest inventories (NFIs). The estimates for growing stock volume based on the NFIs depend on stem volume estimates of individual trees. Data collection for formulating stem volume and biomass models is challenging, because the amount of data required is considerable, and the fact that the detailed destructive measurements required to provide these data are laborious. Due to natural diversity, sample size for developing allometric models should be rather large. Terrestrial laser scanning (TLS) has proved to be an efficient tool for collecting information on tree stems. Therefore, we investigated how TLS data for deriving stem volume information from single trees should be collected. The broader context of the study was to determine the feasibility of replacing destructive and laborious field measurements, which have been needed for development of empirical stem volume models, with TLS. The aim of the study was to investigate the effect of the TLS data captured at various distance (i.e. corresponding 25%, 50%, 75% and 100% of tree height) on the accuracy of the stem volume derived. In addition, we examined how multiple TLS point cloud data acquired at various distances improved the results. Analysis was carried out with two ways when multiple point clouds were used: individual tree attributes were derived from separate point clouds and the volume was estimated based on these separate values (multiple scan A), and point clouds were georeferenced as a combined point cloud from which the stem volume was estimated (multiple-scan B). This permitted us to deal with the practical aspects of TLS data collection and data processing for development of stem volume equations in boreal forests. The results indicated that a scanning distance of approximately 25% of tree height would be optimal for stem volume estimation with TLS if a single scan was utilized in boreal forest conditions studied here and scanning resolution employed. Larger distances increased the uncertainty, especially when the scanning distance was greater than approximately 50% of tree height, because the number of successfully measured diameters from the TLS point cloud was not sufficient for estimating the stem volume. When two TLS point clouds were utilized, the accuracy of stem volume estimates was improved: RMSE decreased from 12.4% to 6.8%. When two point clouds were processed separately (i.e. tree attributes were derived from separate point clouds and then combined) more accurate results were obtained; smaller RMSE and relative error were achieved compared to processing point clouds together (i.e. tree attributes were derived from a combined point cloud). TLS data collection and processing for the optimal setup in this study required only one sixth of time that was necessary to obtain the field reference. These results helped to further our knowledge on TLS in estimating stem volume in boreal forests studied here and brought us one step closer in providing best practices how a phase-shift TLS can be utilized in collecting data when developing stem volume models. (C) 2016 The Authors. Published by Elsevier B.V. on behalf of International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

In this study, the intravitreal pharmacokinetics of nanomaterials were investigated in vivo in rats and rabbits. Impact of particle size and shape (spherical, longitudinal) on ocular particle distribution and elimination was investigated with fundus camera, optical coherence tomography and ocular fluorophotometry. Differently sized particles showed prolonged ocular retention and remarkable differences in vitreal elimination, but size dependence was consistent, suggesting that other features have influence on their vitreal kinetics. We also demonstrate that liposomes are eliminated from the rabbit vitreous mainly via the anterior route. Simulation of drug concentrations after injection of intravitreal particles shows the importance of synchronized particle retention and drug release rate for efficient drug delivery. In conclusion, we provide kinetic insights in intravitreally administered nanoparticles to improve retinal drug delivery.

Background The current EU LULUCF regulation calls for member state-specific Forest Reference Levels (FRLs) for benchmark in the accounting of greenhouse gas emissions and removals of managed forest land during the compliance period (2021-2030). According to the technical guidance on developing and reporting the FRLs, it could be actualized by projecting a ratio of harvested to total available biomass. We tested how the initial age distribution may affect the aforementioned ratio by simulating the continuation of forest management based on several descriptive shapes of forest age class distribution. Results Our simulations suggest that when the FRLs are prepared by employing the harvest ratio and forest management is assumed strictly age dynamics driven, the shape of the initial forest age class distribution gives rise to computational sinks or sources of carbon in managed forest land. Harvests projected according to the ratio corresponded those resulting from the age dynamics only in the case of uniform age distribution. Conclusions The result calls for a better consideration of variation in initial states between countries when determining the future LULUCF regulation. Our exercise demonstrates how generic simulations in a standardized modeling framework could help in ex-ante impact assessment of proposed changes to the LULUCF regulation.

Learning scientific knowledge is largely based on understanding what are its key concepts and how they are related. The relational structure of concepts also affects how concepts are introduced in teaching scientific knowledge. We model here how students organise their knowledge when they represent their understanding of how physics concepts are related. The model is based on assumptions that students use simple basic linking-motifs in introducing new concepts and mostly relate them to concepts that were introduced a few steps earlier, i.e. following a genealogical ordering. The resulting genealogical networks have relatively high local clustering coefficients of nodes but otherwise resemble networks obtained with an identical degree distribution of nodes but with random linking between them (i.e. the configuration-model). However, a few key nodes having a special structural role emerge and these nodes have a higher than average communicability betweenness centralities. These features agree with the empirically found properties of students' concept networks. (C) 2017 Elsevier B.V. All rights reserved.

The threat of the new pandemic influenza A(H1N1)pdm09 imposed a heavy burden on the public health system in Finland in 2009-2010. An extensive vaccination campaign was set up in the middle of the first pandemic season. However, the true number of infected individuals remains uncertain as the surveillance missed a large portion of mild infections. We constructed a transmission model to simulate the spread of influenza in the Finnish population. We used the model to analyse the two first years (2009-2011) of A(H1N1)pdm09 in Finland. Using data from the national surveillance of influenza and data on close person-to-person (social) contacts in the population, we estimated that 6% (90% credible interval 5.1 – 6.7%) of the population was infected with A(H1N1)pdm09 in the first pandemic season (2009/2010) and an additional 3% (2.5 – 3.5%) in the second season (2010/2011). Vaccination had a substantial impact in mitigating the second season. The dynamic approach allowed us to discover how the proportion of detected cases changed over the course of the epidemic. The role of time-varying reproduction number, capturing the effects of weather and changes in behaviour, was important in shaping the epidemic.

We examine the diversity of strategies of modelling networks in (micro) economics and (analytical) sociology. Field-specific conceptions of what explaining (with) networks amounts to or systematic preference for certain kinds of explanatory factors are not sufficient to account for differences in modelling methodologies. We argue that network models in both sociology and economics are abstract models of network mechanisms and that differences in their modelling strategies derive to a large extent from field-specific conceptions of the way in which a good model should be a general one. Whereas the economics models aim at unification, the sociological models aim at a set of mechanism schemas that are extrapolatable to the extent that the underlying psychological mechanisms are general. These conceptions of generality induce specific biases in mechanistic explanation and are related to different views of when knowledge from different fields should be seen as relevant. (C) 2014 Elsevier Ltd. All rights reserved.