The role of tannic acid and sodium citrate in the synthesis of silver nanoparticles

We describe herein the significance of a sodium citrate and tannic acid mixture in the synthesis of spherical silver nanoparticles (AgNPs). Monodisperse AgNPs were synthesized via reduction of silver nitrate using a mixture of two chemical agents: sodium citrate and tannic acid. The shape, size and size distribution of silver particles were determined by UV–Vis spectroscopy, dynamic light scattering (DLS) and scanning transmission electron microscopy (STEM). Special attention is given to understanding and experimentally confirming the exact role of the reagents (sodium citrate and tannic acid present in the reaction mixture) in AgNP synthesis. The oxidation and reduction potentials of silver, tannic acid and sodium citrate in their mixtures were determined using cyclic voltammetry. Possible structures of tannic acid and its adducts with citric acid were investigated in aqueous solution by performing computer simulations in conjunction with the semi-empirical PM7 method. The lowest energy structures found from the preliminary conformational search are shown, and the strength of the interaction between the two molecules was calculated. The compounds present on the surface of the AgNPs were identified using FT-IR spectroscopy, and the results are compared with the IR spectrum of tannic acid theoretically calculated using PM6 and PM7 methods. The obtained results clearly indicate that the combined use of sodium citrate and tannic acid produces monodisperse spherical AgNPs, as it allows control of the nucleation, growth and stabilization of the synthesis process.This work was supported by the Polish Ministry of Science and Higher Education within Research Grant No. NN507 350435 and by the National Science Centre Poland Grant No. 2014/13/B/NZ5/01356

Significant increase in natural disturbance impacts on European forests since 1950

Over the last decades, the natural disturbance is increasingly putting pressure on European forests. Shifts in disturbance regimes may compromise forest functioning and the continuous provisioning of ecosystem services to society, including their climate change mitigation potential. Although forests are central to many European policies, we lack the long-term empirical data needed for thoroughly understanding disturbance dynamics, modeling them, and developing adaptive management strategies. Here, we present a unique database of >170,000 records of ground-based natural disturbance observations in European forests from 1950 to 2019. Reported data confirm a significant increase in forest disturbance in 34 European countries, causing on an average of 43.8 million m3 of disturbed timber volume per year over the 70-year study period. This value is likely a conservative estimate due to under-reporting, especially of small-scale disturbances. We used machine learning techniques for assessing the magnitude of unreported disturbances, which are estimated to be between 8.6 and 18.3 million m3/year. In the last 20 years, disturbances on average accounted for 16% of the mean annual harvest in Europe. Wind was the most important disturbance agent over the study period (46% of total damage), followed by fire (24%) and bark beetles (17%). Bark beetle disturbance doubled its share of the total damage in the last 20 years. Forest disturbances can profoundly impact ecosystem services (e.g., climate change mitigation), affect regional forest resource provisioning and consequently disrupt long-term management planning objectives and timber markets. We conclude that adaptation to changing disturbance regimes must be placed at the core of the European forest management and policy debate. Furthermore, a coherent and homogeneous monitoring system of natural disturbances is urgently needed in Europe, to better observe and respond to the ongoing changes in forest disturbance regimes

Stem Taper Approximation by Artificial Neural Network and a Regression Set Models

Variation in tree stem form depends on species, age, site conditions, etc. Stem taper models that estimate stem diameter at any height and volume should comply with this complexity. In the paper, we propose new methods taking into account both unbiased estimates and stem variability: (i) an expert model based on an artificial neural network (ANN) and (ii) a statistical model built using a regression tree (REG). We used the variable-exponent taper equation (STE) as a reference for these two models. Input data contain information about 2856 trees representing eight dominant forest-forming tree species in Poland (birch, beech, oak, fir, larch, alder, pine, and spruce). The trees were selected across stands varied in terms of age and site conditions. Based on the data, we built ANN and REG models and calculated both stem taper and tree volumes. The results show that ANN is a universal approach that offers the most precise estimation of stem diameter at a particular stem height for different tree species. The results for alder are an exception. In this case, the REG model performs slightly better than ANN. In terms of volume prediction, the ANN model provides the most accurate predictions for coniferous and beech. In general, flexibility and predictive performance of the ANN are better than REG and reference the STE equation

New approach to assess forest fragmentation based on multiscale similarity index

Forest fragmentation is a landscape-level process. After fragmentation, a larger forest area is changed into smaller, mostly isolated, and geometrically complex patches. Proper assessment of forest fragmentation requires addressing key aspects, including the continuous forest's size and shape, the integrity of the forest, and the interpatch spatial distance distribution of forest patches that are separated by nonforest land.The article presents a new approach to assessing the fragmentation of forests in a given area based on the similarity of a forested area's pattern to a pattern of a fully forested area. Jensen--Shannon similarity is used to create a measure of forest fragmentation. The proposed approach allows both the calculation of forest fragmentation at a given scale and the calculation of a multiscale fragmentation assessment as a single index. In addition, the proposed fragmentation index can be used to identify forest complexes better and assess their fragmentation.This approach is flexible, and applying it to other spatial phenomena, such as calculating multiscale fragmentation of urban or agricultural areas, is possible. The article presents the results of applying the proposed method to a test forest-covered region and to an area of the entire country (Poland). The calculations were made with a spatial resolution of 10 m. Moreover, we compared the results of the method to the FAD-APP index. The results show benefit of applying the proposed indicator to forested areas

Scaling issues in forest ecosystem management and how to address them with models

Scaling is widely recognized as a central issue in ecology. The associated cross-scale interactions and process transmutations make scaling (i.e. a change in spatial or temporal grain and extent) an important issue in understanding ecosystem structure and functioning. Moreover, current concepts of ecosystem stewardship, such as sustainability and resilience, are inherently scale-dependent. The importance of scale and scaling in the context of forest management is likely to further increase in the future because of the growing relevance of ecosystem services beyond timber production. As a result, a consideration of processes both below (e.g. leaf-level carbon uptake in the context of climate change mitigation) and above (e.g. managing for biodiversity conservation at the landscape scale) the traditional focus on the stand level is required in forest ecosystem management. Furthermore, climate change will affect a variety of ecosystem processes across scales, ranging from photosynthesis (tree organs) to disturbance regimes (landscape scale). Assessing potential climate change impacts on ecosystem services thus requires a multi-scale perspective. However, scaling issues have received comparatively little attention in the forest management community to date. Our objectives here are thus first, to synthesize scaling issues relevant to forest management and second, to elucidate ways of dealing with complex scaling problems by highlighting examples of how they can be addressed with ecosystem models. We have focused on three current management issues of particular importance in European forestry: (1) climate change mitigation through carbon sequestration, (2) multi-functional stand management for biodiversity and non-timber goods and services and (3) improving the resilience to natural disturbances. We conclude that taking into account the full spatiotemporal heterogeneity and dynamics of forest ecosystems in management decision-making is likely to make management more robust to increasing environmental and societal pressures. Models can aid this process through explicitly accounting for system dynamics and changing conditions, operationally addressing the complexity of cross-scale interactions and emerging properties. Our synthesis indicates that increased attention to scaling issues can help forest managers to integrate traditional management objectives with emerging concerns for ecosystem services and therefore deserves more attention in forestry

Significant increase in natural disturbance impacts on European forests since 1950

Over the last decades, the natural disturbance is increasingly putting pressure on European forests. Shifts in disturbance regimes may compromise forest functioning and the continuous provisioning of ecosystem services to society, including their climate change mitigation potential. Although forests are central to many European policies, we lack the long-term empirical data needed for thoroughly understanding disturbance dynamics, modeling them, and developing adaptive management strategies. Here, we present a unique database of >170,000 records of ground-based natural disturbance observations in European forests from 1950 to 2019. Reported data confirm a significant increase in forest disturbance in 34 European countries, causing on an average of 43.8 million m3 of disturbed timber volume per year over the 70-year study period. This value is likely a conservative estimate due to under-reporting, especially of small-scale disturbances. We used machine learning techniques for assessing the magnitude of unreported disturbances, which are estimated to be between 8.6 and 18.3 million m3/year. In the last 20 years, disturbances on average accounted for 16% of the mean annual harvest in Europe. Wind was the most important disturbance agent over the study period (46% of total damage), followed by fire (24%) and bark beetles (17%). Bark beetle disturbance doubled its share of the total damage in the last 20 years. Forest disturbances can profoundly impact ecosystem services (e.g., climate change mitigation), affect regional forest resource provisioning and consequently disrupt long-term management planning objectives and timber markets. We conclude that adaptation to changing disturbance regimes must be placed at the core of the European forest management and policy debate. Furthermore, a coherent and homogeneous monitoring system of natural disturbances is urgently needed in Europe, to better observe and respond to the ongoing changes in forest disturbance regimes