Alien species are colonizing mountain ecosystems and increasing their elevation ranges in response to ongoing climate change and anthropogenic disturbances, posing increasing threats to native ...species. However, how quickly alien species spread upward and what drives their invasion remains insufficiently understood. Here, using 26,952 occurrence records of 58 alien plant species collected over two centuries in the Czech Republic, we explored the elevation range and invasion speed of each alien species and the underlying factors driving these variables. We collected species traits relevant for invasion (e.g., clonality, flowering time, life span, invasion status, height, mycorrhizal type, native range, naturalized range, monoploid genome size, and Ellenberg-type indicator values for light, temperature, and nitrogen), human-associated factors (e.g., introduction pathways and the sum of economic use types), and minimum residence time. We explored the relationships between these factors and species’ elevation range and invasion speed using phylogenetic regressions. Our results showed that 58 alien species have been expanding upward along mountain elevations in the Czech Republic over the past two centuries. A stronger effect of species’ traits than human-associated factors has been revealed, e.g., clonality was a key trait supporting the invasion of alien species into the mountains, while human-associated factors showed no effect. Our findings highlight that the characteristics associated with rapid reproduction and spread are crucial for alien species’ invasion into montane regions. Identifying key drivers of this process is important for predicting the spatiotemporal dynamics of alien species in high-altitude ecosystems and thus employing apposite measures to reduce the threat to native plant species.
In the paper, the authors first inductively establish explicit formulas for derivatives of the arc sine function, then derive from these explicit formulas explicit expressions for a family of the ...Bell polynomials of the second kind related to the square function, and finally apply these explicit expressions to find explicit formulas for derivatives of some elementary functions.
Ethylene glycol (EG) and AlCl3 pretreated rice straw with 100% cellulose remained for enzymatic hydrolysis (94% glucose yield).
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•A novel ethylene glycol and aluminum chloride ...pretreatment was developed.•100% cellulose was recovered with removal of 88% lignin and 90% hemicellulose.•Specific surface area and pore volume increased by 7.3 and 6.8 times.•The enzyme adsorption ability of rice straw rose by 11-folds after pretreatment.•Glucose yield increased by 2 times that for original straw, reaching 94% at 24 h.
Rice straw was pretreated with ethylene glycol (EG) and AlCl3 for enzymatic hydrolysis. EG-AlCl3 pretreatment had an extremely good selectivity for component fractionation, resulting in 88% delignification and 90% hemicellulose removal, with 100% cellulose recovered or 76% (w/w) cellulose content in solid residue at 150 °C with 0.055 mol/L AlCl3. The pretreated residue (5%, w/v) presented a higher enzymatic hydrolysis rate (glucose yield increased 2 times to 94%) for 24 h at cellulase loading of 10 FPU/g. The hydrolysis behavior was correlated with the composition and structure of substrates characterized by SEM, FT-IR, BET, XRD and TGA. The enzyme adsorption ability of pretreated straw was 12-folds that for the original sample. EG-AlCl3 solution was further cycled for 3 times with 100% cellulose recovery but only 29% lignin removal due to the loss of AlCl3. EG-AlCl3 pretreatment is an efficient method with little loss of cellulose for lignocelluloses.
Sparse coding has received an increasing amount of interest in recent years. It is an unsupervised learning algorithm, which finds a basis set capturing high-level semantics in the data and learns ...sparse coordinates in terms of the basis set. Originally applied to modeling the human visual cortex, sparse coding has been shown useful for many applications. However, most of the existing approaches to sparse coding fail to consider the geometrical structure of the data space. In many real applications, the data is more likely to reside on a low-dimensional submanifold embedded in the high-dimensional ambient space. It has been shown that the geometrical information of the data is important for discrimination. In this paper, we propose a graph based algorithm, called graph regularized sparse coding, to learn the sparse representations that explicitly take into account the local manifold structure of the data. By using graph Laplacian as a smooth operator, the obtained sparse representations vary smoothly along the geodesics of the data manifold. The extensive experimental results on image classification and clustering have demonstrated the effectiveness of our proposed algorithm.
Greenhouses constitute a proven solution for coping with environmental degradation and for increasing both the quantity and quality of agricultural products. Appropriate carbon dioxide (CO2) control ...not only improves crop yield and quality but also reduces the carbon footprint of greenhouses. However, CO2 enrichment control in greenhouses is a dynamic, interactive and time-delayed process. In practice, optimal CO2 concentrations in the greenhouse are difficult to maintain because CO2 is confounded with temperature, humidity, light intensity, etc.; therefore, ambient CO2 concentrations in greenhouses are often suboptimal or excessive. This paper is a review of the current theoretical and applied studies of CO2 enrichment in greenhouses and discusses the advantages and limitations of various methods. The major points addressed are as follows: 1) the five sources of CO2 enrichment in greenhouses; 2) the monitoring and data processing of CO2 concentrations; and 3) the various methods for controlling automatic CO2 enrichment. This paper discusses new challenges and perspectives and suggests future studies and methods for a greenhouse CO2 enrichment system. A new symbiotic greenhouse system requiring sensible CO2 balance is also presented.
•Different sources of carbon dioxide (CO2) for greenhouse enrichment are discussed.•Control strategies for greenhouse CO2 enrichment are reviewed.•Research Challenges of CO2 control in the greenhouse are presented.•A new symbiosis greenhouse system requiring sensible CO2 balance is described.
Abstract
This article conducts simulation research on the power plant of hybrid electric vehicles. Through the strategy and logic control of the power system, the stable operation of the engine in ...the economic area is realized. The engine model can express the relationship between performance and operating point more clearly, and can better meet the real-time response requirements of the system. This paper establishes Simulink-Amesim joint simulation model and conducts simulation analysis. The results show that the curve of engine torque changing with speed basically conforms to the engine principle.
Glycerol and AlCl3 pretreated rice straw for enhancing high-solid enzymatic hydrolysis at low cellulase loadings with adding Tween 80.
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•Glycerol-AlCl3 pretreated rice straw at ...146.8 °C, 20 min, 0.08 M AlCl3.•It achieved 92% cellulose recovery, 83% lignin and 94% hemicellulose removal.•Destruction of straw structure was elucidated with many characterizations.•Glucose yield (74%) increased by 2.4 times that for original straw.•66% glucose yield at 3.3 FPU/g was obtained by adding Tween 80.
Rice straw was pretreated with glycerol and AlCl3 for enzymatic hydrolysis at low cellulase loadings. Based on a central composite design, 83% delignification, 94% hemicellulose removal, and 92% cellulose recovery (or 76% cellulose in solid residue) were achieved under the optimized pretreatment conditions (0.08 mol/L AlCl3 as catalyst at 146.8 °C for 20 min with 90% glycerol). During glycerol-AlCl3 pretreatment, the lignin-carbohydrate complex was depolymerized, resulting in the complex and recalcitrant construction of straw effectively being destroyed. The enzyme adsorption ability of pretreated straw was 16.5 times that for the original sample. After pretreatment, glucose yield was increased by 2.4 times to 74% for 48 h. Moreover, concentrated solid (15%) with low cellulase loading (3.3 FPU/g dry substrate) achieved 58.6% glucose yield, and further increased by 12% to 65.7% by adding Tween 80. Glycerol-AlCl3 pretreatment was a promising approach to realize high-concentrated solid hydrolysis for sugars at low cellulase loadings.
Magnetic self-assembly metal-organic frameworks (MOFs) were constructed for the co-production of biodiesel and hydrogen from waste oils. The highly active MOF nanoparticles were synthesized and ...catalyzed crude glycerol with 126.8% hydrogen yield in subcritical water (350 °C, 5 min). By coupling alkali with MOF-derived carriers, continuous process of fast production of biodiesel (with microwave heating at 90 °C in 15 min, 15:1 methanol/oil molar ratio and 9 wt.% catalyst dosage) and hydrogen (350 °C, 5 min) were achieved with yield of 95.3% biodiesel from waste oil (AV of 3.95 mg KOH) and 102.6% H2 from crude glycerol by-product, respectively. The nanoparticles were magnetically separated for 5 cycles with 95% biodiesel yield. Subsequently, the deactivated catalyst was used for hydrothermal gasification with 50% increasing in hydrogen yield. Characterization techniques showed active sites of MOF-derived nanoparticles were well dispersed with surface area increased by 3.9 times for highly efficient production of biodiesel and hydrogen. It revealed that MOF materials can be designed to make active catalysts and carriers for loading catalytic sites for biomass conversions to targeted biofuels.
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•Ni-MOF-derived catalysts were synthesized for hydrothermal H2 (126.8% yield).•Ni-MOF as magnetic carrier for its large surface area to load base for biodiesel.•Biodiesel from soybean oil reached 98.4% yield with 6 cycles (94.5%).•Biodiesel yield realized 95.3% from waste oil with 5 cycles (95.0%).•H2 yield achieved 102.6% from crude glycerol with deactivated catalyst in 5 min.
Wheat straw was ball milling pretreated with NaOH particles for enzymatic hydrolysis.
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•NaOH particles added during BM showed the best synergistic interaction effect.•NaOH-BM treatment ...decreased CrI and D50 by 1.1 and 6.9 - fold in 1 h, respectively.•Reducing-end concentration of cellulose increased by 3.8 times from 12.5 - 60.2 μM.•Glucose yield (82.4%) with 4 h NaOH BM treatment was 3.1 - fold that of raw straw.•Washing liquor was recycled for the re-treatment, reaching 99.4% glucose yield.
Wheat straw was pretreated using ball milling (BM) promoted by solid particles (NaOH, NaCl, citric acid). NaOH showed the best synergistic interaction effect, due to the breakage of β-1,4-glycosidic bonds among cellulose molecules by the alkali solid particles induced by BM. NaOH-BM pretreatment decreased the straw crystallinity from 46% to 21.4% and its average particle size from 398.3 to 50.6 μm in 1 h. After 4 h milling, the reducing-end concentration of cellulose increased by 3.8 times from 12.5 to 60.2 μM, with glucose yield increased by 2.1 times from 26.6% to 82.4% for 72 h enzymatic hydrolysis at cellulase loading of 15 FPU/g dry substrate. The pretreatment washing liquor was recycled for the re-treatment of partially pretreated biomass at 121 °C for 30 min, resulting in 99.4% glucose yield by enzymatic hydrolysis. BM assisted with alkali particles was an effective approach for improving biomass enzymatic saccharification.
Accurate estimation of regional and global patterns of ecosystem respiration (ER) is crucial to improve the understanding of terrestrial carbon cycles and the predictive ability of the global carbon ...budget. However, large uncertainties still exist in regional and global ER estimation due to the drawbacks of modeling methods. Based on eddy covariance ER data from 132 sites in China from 2002 to 2020, we established Intelligent Random Forest (IRF) models that integrated ecological understanding with machine learning techniques to estimate ER. The results showed that the IRF models performed better than semiempirical models and machine learning algorithms. The observed data revealed that gross primary productivity (GPP), living plant biomass, and soil organic carbon (SOC) were of great importance in controlling the spatiotemporal variability of ER across China. An optimal model governed by annual GPP, living plant biomass, SOC, and air temperature (IRF‐04 model) matched 93% of the spatiotemporal variation in site‐level ER, and was adopted to evaluate the spatiotemporal pattern of ER in China. Using the optimal model, we obtained that the annual value of ER in China ranged from 5.05 to 5.84 Pg C yr−1 between 2000 and 2020, with an average value of 5.53 ± 0.22 Pg C yr−1. In this study, we suggest that future models should integrate process‐based and data‐driven approaches for understanding and evaluating regional and global carbon budgets.
Plain Language Summary
With China already committing to achieve carbon neutrality before 2060, an accurate assessment of land carbon sink and its flux rate in China is an increasingly important area in global change ecology. In this essay, a high‐efficiency and accurate simulation method was introduced in this field; This method is particularly useful in the assessment of carbon sink and its flux rate in China by combining with reliable observation flux data. Using this new method, a reliable and reasonable value of carbon flux (ecosystem respiration) was obtained. Meanwhile, that method provides a better understanding of the mechanism governing the spatiotemporal variability of carbon flux. Therefore, this present study has gone some way toward enhancing our understanding of a comprehensive assessment and analysis of land carbon sink in China.
Key Points
A model integrating ecological knowledge and machine learning was established to estimate ecosystem respiration (ER) in China
The spatiotemporal patterns of ER are significantly affected by productivity, plant biomass, soil organic carbon, and air temperature
China's ER was estimated to be 5.53 ± 0.22 petagrams of carbon per year (Pg C yr−1) on average for the years 2000–2020
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