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The Hyrcanian forests of Iran are mainly managed with the single-selection silvicultural technique. Despite significant ecological benefits associated with selection cutting, this type of forest management leads towards more challenging situations where it is difficult to maintain and practice successful forestry than in even-aged systems. Therefore, this study provides relevant management tools in the form of models to estimate low growth levels in Hyrcanian forests. In the present study, estimation of the population growth rate and then the allowable cut rate of these forests using a matrix model have been calculated in the Gorazbon district. For this purpose, the data of 256 permanent sample plots measured during the years between 2003 and 2012, as well as the data recorded about the trees harvested according to the forestry plan, have been used. As a first step, the most frequently occurring tree species were divided into four groups (beech, hornbeam, chestnut-leaved oak, and other species). Compartments of the district were divided into two groups of logged and unlogged compartments. The purpose of this division was to estimate the allowable cut and compare its volume with the volumes of observed and predicted allowable cuts obtained from forestry plans. The results showed that the total operated allowable cut (OAC) in logged compartments was more than the estimated allowable cut (EAC). In unlogged compartments, the total predicted allowable cut (PAC) was more than EAC. A comparison of EAC and OAC showed that hornbeam has been harvested more than its potential. However, chestnut-leaved oak and other species group have depicted opposite trends. Our models provide important advancements for estimating allowable cut that can enhance the goal of practicing sustainable forestry.

Micro- and nanoscale patterned monolayers of plasmonic nanoparticles were fabricated by combining concepts from colloidal chemistry, self-assembly, and subtractive soft lithography. Leveraging chemical interactions between the capping ligands of pre-synthesized gold colloids and a polydimethylsiloxane stamp, we demonstrated patterning gold nanoparticles over centimeter-scale areas with a variety of micro- and nanoscale geometries, including islands, lines, and chiral structures (e.g., square spirals). By successfully achieving nanoscale manipulation over a wide range of substrates and patterns, we establish a powerful and straightforward strategy, nanoparticle chemical lift-off lithography (NP-CLL), for the economical and scalable fabrication of functional plasmonic materials with colloidal nanoparticles as building blocks, offering a transformative solution for designing next-generation plasmonic technologies.

AbstractCellulose and lignin nanoparticles are high‐value‐added products obtained from lignocellulosic biomasses through several steps of cellulose purification and lignin extraction. These steps drastically reduce the potential feedstock revenue when carried out as stand‐alone methodologies. To increase biomass yields, we describe here a strategy to design a biorefinery focused on producing cellulose and lignin nanoparticles as main products, but also aim to recover and benefit from other biomass components using only water‐based processes. Sequential pressurized liquid extractions and diluted acid and alkaline treatments were carried out to fractionate elephant grass biomass, yielding (for every 100 g of biomass): 30 g of cellulose pulp (converted to 9 g of cellulose nanocrystals and 9 g of cellulose nanofibers); 10 g of lignin (used to produce 8.5 g of stable colloidal lignin nanoparticles by probe‐sonication in water); 7.5 g of extractives (e.g. sterols and phenolics) and 23 g of xylose (converted to 4.1 g of furfural). Alternatively, to allow for the flexible use of the cellulose fraction in the proposed biorefinery, 22 g of glucose could be produced by enzymatic hydrolysis. The results demonstrate that water‐based processes are suitable for a holistic use of biomass, providing a comprehensive set of high‐value‐added co‐products that are renewable and cost‐effective chemical, cosmetic, food, polymer and pharmaceutical solutions.

AbstractWe study the propagation of cosmological gravitational wave (GW) backgrounds from the early radiation era until the present day in modified theories of gravity. Comparing to general relativity (GR), we study the effects that modified gravity parameters, such as the GW friction αMand the tensor speed excessαT, have on the present-day GW spectrum. We use both the WKB estimate, which provides an analytical description but fails at superhorizon scales, and numerical simulations that allow us to go beyond the WKB approximation. We show that a constantαTmakes relatively insignificant changes to the GR solution, especially taking into account the constraints on its value from GW observations by the LIGO-Virgo collaboration, whileαMcan introduce modifications to the spectral slopes of the GW energy spectrum in the low-frequency regime depending on the considered time evolution ofαM. The latter effect is additional to the damping or growth occurring equally at all scales that can be predicted by the WKB approximation. In light of the recent observations by pulsar timing array (PTA) collaborations, and the potential observations by future detectors such as SKA, LISA, DECIGO, BBO, or ET, we show that, in most of the cases, constraints cannot be placed on the effects ofαMand the initial GW energy density ℰ*GWseparately, but only on the combined effects of the two, unless the signal is observed at different frequency ranges. In particular, we provide some constraints on the combined effects from the reported PTA observations.

Suvilahti, a suburb of the city of Vaasa in western Finland, was the first area to use seabed sediment heat as the main source of heating for a high number of houses. Moreover, in the same area, a unique land uplift effect is ongoing. The aim of this paper is to solve the challenges and find opportunities caused by global warming by utilizing seabed sediment energy as a renewable heat source. Measurement data of water and air temperature were analyzed, and correlations were established for the sediment temperature data using Statistical Analysis System (SAS) Enterprise Guide 7.1. software. The analysis and provisional forecast based on the autoregression integrated moving average (ARIMA) model revealed that air and water temperatures show incremental increases through time, and that sediment temperature has positive correlations with water temperature with a 2-month lag. Therefore, sediment heat energy is also expected to increase in the future. Factor analysis validations show that the data have a normal cluster and no particular outliers. This study concludes that sediment heat energy can be considered in prominent renewable production, transforming climate change into a useful solution, at least in summertime.

AbstractA better understanding of how climate affects growth in tree species is essential for improved predictions of forest dynamics under climate change. Long-term climate averages (mean climate) and short-term deviations from these averages (anomalies) both influence tree growth, but the rarity of long-term data integrating climatic gradients with tree censuses has so far limited our understanding of their respective role, especially in tropical systems. Here, we combined 49 years of growth data for 509 tree species across 23 tropical rainforest plots along a climatic gradient to examine how tree growth responds to both climate means and anomalies, and how species functional traits mediate these tree growth responses to climate. We showed that short-term, anomalous increases in atmospheric evaporative demand and solar radiation consistently reduced tree growth. Drier forests and fast-growing species were more sensitive to water stress anomalies. In addition, species traits related to water use and photosynthesis partly explained differences in growth sensitivity to both long-term and short-term climate variations. Our study demonstrates that both climate means and anomalies shape tree growth in tropical forests, and that species traits can be leveraged to understand these demographic responses to climate change, offering a promising way forward to forecast tropical forest dynamics under different climate trajectories.

AbstractThermochemical biorefineries for the production of chemicals and materials can play an important role in the bioeconomy. However, their economic viability is often questioned under the premise of the economy of scale. This paper presents a regional, modular biorefinery concept for the production of the platform chemicals hydroxymethylfurfural (HMF), furfural and phenols from the lignocellulosic perennial miscanthus, which can be cultivated on marginal and degraded areas. The paper focuses on the question of the minimum selling price of HMF and the optimal plant size for this purpose, using the region of Baden‐Württemberg, Germany, as an example. Based on small pilot plant results, a scalable process simulation was created via AspenPlus. This allows different scenarios and process combinations of this multi‐output biorefinery concept to be compared with each other. Using this, a minimum sales price for the main product HMF is calculated using methods of dynamic investment cost calculation according to the net present value method. Based on this, the plant capacity was scaled. The scenarios and sensitivity analyses show that, with an accuracy of ±15%, regional biorefineries could already offer platform chemicals at prices of 2.21–2.90 EUR/kg HMF at the current stage of development. This corresponds to three to four times the price of today's comparative fossil base chemicals and is thus a competitive option from the authors’ point of view. The local biomass and the heat prices were identified as the main influencing factors. As a result, the selection of the location will have a decisive influence on the economic viability of such concepts in the case of further development and optimization of the process in first demonstration plants.