Wood trait preferences of Neotropical xylophagous beetles (Coleoptera: Cerambycidae).

Tree life history strategies are correlated with functional plant traits, such as wood density, moisture content, bark thickness, and nitrogen content; these traits affect the nutrients available to xylophagous insects. Cerambycid beetles feed on substrates that vary in these traits, but little is known about how they affect community composition. The goal of this project is to explore the community composition of two cerambycid subfamilies (Cerambycinae and Lamiinae) according to the wood traits in the wood they eat. In a salvage project conducted adjacent to the Panama Canal, trees were felled and exposed to Cerambycidae for oviposition. Disks from branches of differing thickness from the same plant individuals were used to calculate wood density, moisture content, and bark thickness in the field; nitrogen data were acquired offsite. Thick and thin branches tended to differ in wood trait values; therefore, data were analyzed separately in subsequent analyses. In thin branches, cerambycid abundance and species richness were higher in samples with less dense, moister wood, and thicker bark. Thick branches showed similar trends, but the wood traits accounted for little variability in beetle abundance or species richness. There were no significant regressions between beetle data and nitrogen. Cerambycines emerged more slowly, and from denser, drier wood, than lamiines. Cerambycines might be more drought-tolerant than lamiines, and therefore more resistant to the longer, more severe dry seasons that are predicted to occur due to climate change.

La historia de vida de los árboles se correlaciona con los rasgos funcionales de la planta, como la densidad de la madera, el contenido de humedad, el grosor de la corteza, y el contenido de nitrógeno; estos rasgos afectan los nutrientes disponibles para los insectos xilófagos. Los escarabajos cerambícidos se alimentan de sustratos que varían en estos rasgos, pero se sabe poco sobre cómo afectan la composición de la comunidad. El objetivo de este proyecto es explorarla composición comunitaria de dos subfamilias de cerambícidos (Cerambycinae y Lamiinae) según las características de la madera que consumen. En un proyecto de salvamento realizado junto al Canal de Panamá, se talaron árboles y se expusieron a Cerambycidae para la oviposición. Se usaron discos de ramas de diferente grosor de las mismas plantas para calcular la densidad de la madera, el contenido de humedad y el grosor de la corteza en el campo; los datos de nitrógeno fueron adquiridos fuera del sitio. Las ramas gruesas y delgadas tendieron a diferir en los valores de las características de la madera; por lo tanto, los datos se analizaron por separado en análisis posteriores. En ramas delgadas, la abundancia de cerambícidos y la riqueza de especies fueron mayores en muestras con madera menos densa, más húmeda y con corteza más gruesa. Las ramas gruesas mostraron tendencias similares, pero las características de la madera explicaron poca variabilidad en la abundancia de escarabajos o la riqueza de especies. No hubo regresión significativas entre los datos del escarabajo y el nitrógeno. Cerambycines surgieron más lentamente y de maderas más densas y secas que los lamiines. Cerambycines podrían ser más tolerantes a la sequía que lamiines y, por lo tanto, más resistentes a las estaciones secas más largas y severas que se prevé que ocurran debido al cambio climático.

Cellulose Nitrates-Blended Composites from Bacterial and Plant-Based Celluloses.

Cellulose nitrates (CNs)-blended composites based on celluloses of bacterial origin (bacterial cellulose (BC)) and plant origin (oat-hull cellulose (OHC)) were synthesized in this study for the first time. Novel CNs-blended composites made of bacterial and plant-based celluloses with different BC-to-OHC mass ratios of 70/30, 50/50, and 30/70 were developed and fully characterized, and two methods were employed to nitrate the initial BC and OHC, and the three cellulose blends: the first method involved the use of sulfuric-nitric mixed acids (MAs), while the second method utilized concentrated nitric acid in the presence of methylene chloride (NA + MC). The CNs obtained using these two nitration methods were found to differ between each other, most notably, in viscosity: the samples nitrated with NA + MC had an extremely high viscosity of 927 mPa·s through to the formation of an immobile transparent acetonogel. Irrespective of the nitration method, the CN from BC (CN BC) was found to exhibit a higher nitrogen content than the CN from OHC (CN OHC), 12.20-12.32% vs. 11.58-11.60%, respectively. For the starting BC itself, all the cellulose blends of the starting celluloses and their CNs were detected using the SEM technique to have a reticulate fiber nanostructure. The cellulose samples and their CNs were detected using the IR spectroscopy to have basic functional groups. TGA/DTA analyses of the starting cellulose samples and the CNs therefrom demonstrated that the synthesized CN samples were of high purity and had high specific heats of decomposition at 6.14-7.13 kJ/g, corroborating their energy density. The CN BC is an excellent component with in-demand energetic performance; in particular, it has a higher nitrogen content while having a stable nanostructure. The CN BC was discovered to have a positive impact on the stability, structure, and energetic characteristics of the composites. The presence of CN OHC can make CNs-blended composites cheaper. These new CNs-blended composites made of bacterial and plant celluloses are much-needed in advanced, high-performance energetic materials.

Enzymatic Activity of Soil on the Occurrence of the Endangered Beetle Cheilotoma musciformis (Coleoptera: Chrysomelidae) in Xerothermic Grasslands.

This work attempts to find the reasons for the rather limited range of occurrence of Cheilotoma musciformis in Poland, based on soil properties, which affects both the plant cover and the entomofauna. The aim of the study was to assess the influence of soil enzyme activity on the occurrence of Ch. musciformis in xerothermic grasslands in Southern Poland. The sites inhabited by the beetle were most often extensively grazed by farm animals or had recently been cleared of bushes. The control plots were in wasteland. The soils of most sites with Ch. musciformis were characterized by significantly higher activity of the tested enzymes and higher content of total organic carbon and total nitrogen, as well as lower pHKCl compared to the control sites. The higher enzymatic activity of soils in sites with the beetle than in the control sites may indicate the dependence of the occurrence of this beetle on the presence of patches of extensively grazed xerothermic grasslands. Grazing influences the behavior of preferred host plant species. Therefore, when planning active protection of xerothermic grasslands inhabited by Ch. musciformis, changes in the biochemical properties of the soil and vegetation structure should be taken into account.

Carbon content and other soil properties of near-surface peats before and after peatland restoration.

Peatland restoration usually aims at restarting the peatlands' function to store carbon within peat. The soil properties of the near-surface peat can give a first understanding of this process. Therefore, we sampled pH value, total organic carbon content (TOC), total nitrogen content (TN), C/N ratio as well as dry bulk density (BD), and describe the structure of near-surface peats in six restored fens in North-East Germany before (2002-2004) and after (2019-2021) restoration. Before restoration, the study sites showed peat degradation to various extents in their near-surface peats. pH values remained relatively stable over time. Comparing the degraded peat horizons, TOC increased significantly in four study sites, ranging from 35.7% to 47.8% in 2002-2004 and from 42.5% to 54.0% in 2019-2021. TN varied from 1.5% to 3.5% in 2002-2004 and from 1.8% to 3.2% in 2019-2021, but changes were only significant in one site, showing a slight decrease. In three sites, the increase in C/N ratio was significant, indicating lower nutrient availability. BD ranged from 0.08 to 0.48 g/cm3 in 2002-2004 and from 0.10 to 0.16 g/cm3 in 2019-2021, decreasing significantly in four sites. The structure of the degraded peat horizons changed after restoration to a more homogenous, sludge mass with larger re-aggregates. In three sites, new peat moss peat layers above the degraded soil horizon were present in 2019-2021, with a mean thickness of 6.8 to 36.1 cm. The structure was comparable to typical, slightly decomposed peat moss peat. Our findings suggest that within about 17 years after fen restoration, and thereby a water table rise close to surface, TOC of the near-surface peats increased to values that are typical for undisturbed peatlands. This indicates that restoration can lead to the re-establishment of peatlands as potential carbon sinks, with TOC within the near-surface peat as one key factor in this process. Further, we assume that the decrease in nutrient availability, decrease of BD, and new, undisturbed peat layers can favor the establishment of mire-specific biodiversity and support ecosystem services similar to near-natural mires.

Changes in microbial community structure related to biodegradation of eelgrass (Zostera marina).

Seagrass meadows produce organic carbon and deposit it on the seabed through the decaying process. Microbial activity is closely related to the process of eelgrass death and collapse. We investigated the microbial community structure of eelgrass during the eelgrass decomposition process by using a microcosm containing raw seawater and excised eelgrass leaves collected from a Zostera marina bed in Futtsu, Chiba Prefecture, Japan. The fast-growing microbes (i.e., Alphaproteobacteria, Gammaproteobacteria, and Flavobacteriia) rapidly adhered to the eelgrass leaf surface and proliferated in the first two weeks but gradually decreased the relative abundance as the months moved on. On the other hand, the slow-growing microbes (i.e., Cytophagia, Anaerolineae, Thaumarchaeota, and Actinobacteria) became predominant over the eelgrass surface late in the culture experiment (120, 180 days). The fast-growing groups of Gammaproteobacteria and Flavobacteriia appear to be closely related to the initial decomposition of eelgrass, especially the rapid decomposition of leaf-derived biopolymers. Changes in nitrogen content due to the bacterial rapid consumption of readily degradable organic carbon induced changes in the community structure at the early stage of eelgrass decomposition. In addition, shifts in the C/N ratio were driven by microbial community changes during later decomposition phases.

A study on the simultaneous determination of nitrogen content and 15N isotope abundance in plants using peak height intensities at m/z 28 and 29.

A method for simultaneous determination of nitrogen content and 15N isotope abundance in plants was established by Elemental analysis-gas isotope ratio mass spectrometry. Taking poplar leaves and l-glutamic acid as standards, nitrogen content was determined using the standard curve established by weighted least squares regression between the mass of nitrogen element and the total peak height intensity at m/z 28 and 29. Then the 15N isotope abundance was calculated with the peak height intensity at m/z 28 and 29. Through the comparison of several sets of experiments, the impact of mass discrimination effect, tin capsule consumables, isotope memory effect, and the quality of nitrogen on the results were assessed. The results showed that with a weight of 1/x2, the standard curve has a coefficient of determination (R2) of 0.9996. Compared to the traditional Kjeldahl method, the measured nitrogen content deviated less than 0.2 %, and the standard deviation (SD) was less than 0.2 %. Compared to the sodium hypobromite method, the 15N isotopic abundances differed less than 0.2 atom%15N, and the SD was less than 0.2 atom% 15N. The established method offers the advantages of being fast, simple, accurate, and high throughput, providing a novel approach for the simultaneous determination of nitrogen content and 15N isotope abundance in plant samples.

Using Machine Learning Methods Combined with Vegetation Indices and Growth Indicators to Predict Seed Yield of Bromus inermis.

Smooth bromegrass (Bromus inermis) is a perennial, high-quality forage grass. However, its seed yield is influenced by agronomic practices, climatic conditions, and the growing year. The rapid and effective prediction of seed yield can assist growers in making informed production decisions and reducing agricultural risks. Our field trial design followed a completely randomized block design with four blocks and three nitrogen levels (0, 100, and 200 kg·N·ha-1) during 2022 and 2023. Data on the remote vegetation index (RVI), the normalized difference vegetation index (NDVI), the leaf nitrogen content (LNC), and the leaf area index (LAI) were collected at heading, anthesis, and milk stages. Multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) regression models were utilized to predict seed yield. In 2022, the results indicated that nitrogen application provided a sufficiently large range of variation of seed yield (ranging from 45.79 to 379.45 kg ha⁻¹). Correlation analysis showed that the indices of the RVI, the NDVI, the LNC, and the LAI in 2022 presented significant positive correlation with seed yield, and the highest correlation coefficient was observed at the heading stage. The data from 2022 were utilized to formulate a predictive model for seed yield. The results suggested that utilizing data from the heading stage produced the best prediction performance. SVM and RF outperformed MLR in prediction, with RF demonstrating the highest performance (R2 = 0.75, RMSE = 51.93 kg ha-1, MAE = 29.43 kg ha-1, and MAPE = 0.17). Notably, the accuracy of predicting seed yield for the year 2023 using this model had decreased. Feature importance analysis of the RF model revealed that LNC was a crucial indicator for predicting smooth bromegrass seed yield. Further studies with an expanded dataset and integration of weather data are needed to improve the accuracy and generalizability of the model and adaptability for the growing year.

Persistent effects of swine manure biochar and biogas slurry application on soil nitrogen content and quality of lotus root.

Using swine manure biochar and biogas slurry in agriculture proves to be an effective strategy for soil improvement and fertilization. In this study, a pot trial on the growth of lotus root was conducted to investigate the persistent effects of applying 350°C swine manure biochar (1% and 2%) and biogas slurry (50% and 100%) on soil nitrogen nutrient and lotus root quality. The results showed that compared to chemical fertilizer alone (A0B0), swine manure biochar significantly increased soil nitrogen content after one year of application. The contents of total nitrogen (TN), alkali-hydrolyzed nitrogen (AHN), ammonium nitrogen (NH4 +-N), and nitrate nitrogen (NO3- -N) increased by 17.96% to 20.73%, 14.05% to 64.71%, 17.76% to 48.68% and 2.22% to 8.47%, respectively, during the rooting period. When swine manure biochar was present, the application of biogas slurry further elevated soil nitrogen content. The co-application of swine manure biochar and biogas slurry significantly increased soil nitrogen content, and the 100% nitrogen replacement with biogas slurry combined with 2% swine manure biochar (A2B2) treatment exhibited the most significant enhancement effect during whole plant growth periods. Soil enzyme activities, including soil protease (NPT), leucine aminopeptidase (LAP), b-glucosidase (ß-GC) and dehydrogenase (DHA), showed a tendency to increase and then decrease with the prolongation of lotus root fertility period, reaching the maximum value during the rooting period. Compared to A0B0, the treatment with 2% swine manure biochar had the most significant effect on enzyme activities and increased the lotus root's protein, soluble sugar, and starch contents. Nitrate content decreased with the application of 2% swine manure biochar as the amount of biogas slurry increased. In conclusion, swine manure biochar effectively improved soil nitrogen content, enzyme activity, and lotus root quality. Even after one year of application, 2% swine manure biochar had the best enhancement effect.

Assessing tea plantations biophysical and biochemical characteristics in Northeast India using satellite data.

Despite advancements in using multi-temporal satellite data to assess long-term changes in Northeast India's tea plantations, a research gap exists in understanding the intricate interplay between biophysical and biochemical characteristics. Further exploration is crucial for precise, sustainable monitoring and management. In this study, satellite-derived vegetation indices and near-proximal sensor data were deployed to deduce various physico-chemical characteristics and to evaluate the health conditions of tea plantations in northeast India. The districts, such as Sonitpur, Jorhat, Sibsagar, Dibrugarh, and Tinsukia in Assam were selected, which are the major contributors to the tea industry in India. The Sentinel-2A (2022) data was processed in the Google Earth Engine (GEE) cloud platform and utilized for analyzing tea plantations biochemical and biophysical properties. Leaf chlorophyll (Cab) and nitrogen contents are determined using the Normalized Area Over Reflectance Curve (NAOC) index and flavanol contents, respectively. Biophysical and biochemical parameters of the tea assessed during the spring season (March-April) 2022 revealed that tea plantations located in Tinsukia and Dibrugarh were much healthier than the other districts in Assam which are evident from satellite-derived Enhanced Vegetation Index (EVI), Modified Soil Adjusted Vegetation Index (MSAVI), Leaf Area Index (LAI), and Fraction of Absorbed Photosynthetically Active Radiation (fPAR), including the Cab and nitrogen contents. The Cab of healthy tea plants varied from 25 to 35 µg/cm2. Pearson correlation among satellite-derived Cab and nitrogen with field measurements showed R2 of 0.61-0.62 (p-value < 0.001). This study offered vital information about land alternations and tea health conditions, which can be crucial for conservation, monitoring, and management practices.

Monitoring of Nitrogen Concentration in Soybean Leaves at Multiple Spatial Vertical Scales Based on Spectral Parameters.

Nitrogen is a fundamental component for building amino acids and proteins, playing a crucial role in the growth and development of plants. Leaf nitrogen concentration (LNC) serves as a key indicator for assessing plant growth and development. Monitoring LNC provides insights into the absorption and utilization of nitrogen from the soil, offering valuable information for rational nutrient management. This, in turn, contributes to optimizing nutrient supply, enhancing crop yields, and minimizing adverse environmental impacts. Efficient and non-destructive estimation of crop LNC is of paramount importance for on-field crop management. Spectral technology, with its advantages of repeatability and high-throughput observations, provides a feasible method for obtaining LNC data. This study explores the responsiveness of spectral parameters to soybean LNC at different vertical scales, aiming to refine nitrogen management in soybeans. This research collected hyperspectral reflectance data and LNC data from different leaf layers of soybeans. Three types of spectral parameters, nitrogen-sensitive empirical spectral indices, randomly combined dual-band spectral indices, and "three-edge" parameters, were calculated. Four optimal spectral index selection strategies were constructed based on the correlation coefficients between the spectral parameters and LNC for each leaf layer. These strategies included empirical spectral index combinations (Combination 1), randomly combined dual-band spectral index combinations (Combination 2), "three-edge" parameter combinations (Combination 3), and a mixed combination (Combination 4). Subsequently, these four combinations were used as input variables to build LNC estimation models for soybeans at different vertical scales using partial least squares regression (PLSR), random forest (RF), and a backpropagation neural network (BPNN). The results demonstrated that the correlation coefficients between the LNC and spectral parameters reached the highest values in the upper soybean leaves, with most parameters showing significant correlations with the LNC (p < 0.05). Notably, the reciprocal difference index (VI6) exhibited the highest correlation with the upper-layer LNC at 0.732, with a wavelength combination of 841 nm and 842 nm. In constructing the LNC estimation models for soybeans at different leaf layers, the accuracy of the models gradually improved with the increasing height of the soybean plants. The upper layer exhibited the best estimation performance, with a validation set coefficient of determination (R2) that was higher by 9.9% to 16.0% compared to other layers. RF demonstrated the highest accuracy in estimating the upper-layer LNC, with a validation set R2 higher by 6.2% to 8.8% compared to other models. The RMSE was lower by 2.1% to 7.0%, and the MRE was lower by 4.7% to 5.6% compared to other models. Among different input combinations, Combination 4 achieved the highest accuracy, with a validation set R2 higher by 2.3% to 13.7%. In conclusion, by employing Combination 4 as the input, the RF model achieved the optimal estimation results for the upper-layer LNC, with a validation set R2 of 0.856, RMSE of 0.551, and MRE of 10.405%. The findings of this study provide technical support for remote sensing monitoring of soybean LNCs at different spatial scales.

Precise determination of the total nitrogen content in activated sludge by ultrasonic pre-treatment assisted wet method.

The study proposed a method for determining total nitrogen (TN) content in activated sludge by ultrasound pre-treatment assisted wet method. Based on the single-factor experiment, with the TN content as the response value, the response surface methodology was employed to examine the individual and interactive effects of three factors: the dilution multiple of the sludge mixture, ultrasonic time, and ultrasonic power. At the same time, the physico-chemical parameters and the digestion-oxidation parameters were optimised. The results indicated that the optimal parameters were as follows; sludge dilution multiple of 225 times, stirring rate of 400 r/min, ultrasonic time of 22 minutes, ultrasonic power of 720 W, and optimal added volume of potassium persulfate at 8 mL with a digestion time of 40 minutes. The relative standard deviation (RSD) for the parallel determination of TN in sludge samples using ultrasonic pre-treatment assisted wet method was ≤2.77%, with a spike recovery rate of 98.49-101.43%. The method, ultrasonic pre-treatment assisted wet method to determine TN concentration in activated sludge, was simpler to operate, more accurate.

Utilising the Nanozymatic Activity of Copper-Functionalised Mesoporous C3 N5 for Sensing Biomolecules.

Designing unique nanomaterials for the selective sensing of biomolecules is of significant interest in the field of nanobiotechnology. In this work, we demonstrated the synthesis of ordered Cu nanoparticle-functionalised mesoporous C3 N5 that has unique peroxidase-like nanozymatic activity for the ultrasensitive and selective detection of glucose and glutathione. A nano hard-templating technique together with the in-situ polymerisation and self-assembly of Cu and high N-containing CN precursor was adopted to introduce mesoporosity as well as high N and Cu content in mesoporous C3 N5 . Due to the ordered structure and highly dispersed Cu in the mesoporous C3 N5 , a large enhancement of the peroxidase mimetic activity in the oxidation of a redox dye in the presence of hydrogen peroxide could be obtained. Additionally, the optimised Cu-functionalised mesoporous C3 N5 exhibited excellent sensitivity to glutathione with a low detection limit of 2.0 ppm. The strong peroxidase activity of the Cu-functionalised mesoporous C3 N5 was also effectively used for the sensing of glucose with a detection limit of 0.4 mM through glucose oxidation with glucose oxidase. This unique Cu-functionalised mesoporous C3 N5 has the potential for detecting various molecules in the environment as well as for next-generation glucose and glutathione diagnostic devices.

Impact of Nitridation on Bias Temperature Instability and Hard Breakdown Characteristics of SiON MOSFETs.

We study how nitridation, applied to SiON gate layers, impacts the reliability of planar metal-oxide-semiconductor field effect transistors (MOSFETs) subjected to negative and positive bias temperature instability (N/PBTI) as well as hard breakdown (HBD) characteristics of these devices. Experimental data demonstrate that p-channel transistors with SiON layers characterized by a higher nitrogen concentration have poorer NBTI reliability compared to their counterparts with a lower nitrogen content, while PBTI in n-channel devices is negligibly weak in all samples independently of the nitrogen concentration. The Weibull distribution of HBD fields extracted from experimental data in devices with a higher N density are shifted towards lower values with respect to that measured in MOSFETs, and SiON films have a lower nitrogen concentration. Based on these findings, we conclude that a higher nitrogen concentration results in the aggravation of BTI robustness and HBD characteristics.

Variation in leaf photosynthetic capacity within plant canopies: optimization, structural, and physiological constraints and inefficiencies.

Leaf photosynthetic capacity (light-saturated net assimilation rate, AA) increases from bottom to top of plant canopies as the most prominent acclimation response to the conspicuous within-canopy gradients in light availability. Light-dependent variation in AA through plant canopies is associated with changes in key leaf structural (leaf dry mass per unit leaf area), chemical (nitrogen (N) content per area and dry mass, N partitioning between components of photosynthetic machinery), and physiological (stomatal and mesophyll conductance) traits, whereas the contribution of different traits to within-canopy AA gradients varies across sites, species, and plant functional types. Optimality models maximizing canopy carbon gain for a given total canopy N content predict that AA should be proportionally related to canopy light availability. However, comparison of model expectations with experimental data of within-canopy photosynthetic trait variations in representative plant functional types indicates that such proportionality is not observed in real canopies, and AA vs. canopy light relationships are curvilinear. The factors responsible for deviations from full optimality include stronger stomatal and mesophyll diffusion limitations at higher light, reflecting greater water limitations and more robust foliage in higher light. In addition, limits on efficient packing of photosynthetic machinery within leaf structural scaffolding, high costs of N redistribution among leaves, and limited plasticity of N partitioning among components of photosynthesis machinery constrain AA plasticity. Overall, this review highlights that the variation of AA through plant canopies reflects a complex interplay between adjustments of leaf structure and function to multiple environmental drivers, and that AA plasticity is limited by inherent constraints on and trade-offs between structural, chemical, and physiological traits. I conclude that models trying to simulate photosynthesis gradients in plant canopies should consider co-variations among environmental drivers, and the limitation of functional trait variation by physical constraints and include the key trade-offs between structural, chemical, and physiological leaf characteristics.

Spatial distribution and core community of diazotrophs in Biological soil crusts and subsoils in temperate semi-arid and arid deserts of China.

Introduction: Biological soil crusts (BSCs) are distributed in arid and semiarid regions, and they function as important microhabitats for nitrogen fixation. The diazotroph community is critical for nitrogen fixation in BSCs and their subsoils. However, little is known about the key groups in different types of BSCs and subsoils in temperate semi-arid or arid deserts. Methods: Here, we sampled three types of BSCs and their subsoils from the Inner Mongolian plateau, investigated the distribution characteristics of the diazotroph community by high-throughput sequencing, predicted keystone species using the molecular ecological network analyses pipeline (MENAP), and verified their close relationship with the available nitrogen (AN) content. Results: The results showed that available nitrogen content in BSCs was higher than that in subsoils in three different types of BSCs, and there were differences among seasons and according to the mean annual precipitation. The abundance of diazotrophs was higher in Cyano-BSCs, while diversity had no significant difference among BSCs and subsoils. Cyanobacteria and Proteobacteria, Nostocaceae and Scytonemataceae, Skermanella, Scytonema, Azohydromonas, Nostoc and Trichormus were the dominant phyla, families, and genera, respectively. The dominant groups belong to Skermanella, Scytonema, and Nostoc formed the core diazotroph community in the three types of BSCs and subsoils, and each had a close relationship with AN. Discussion: These results indicate that diazotrophs in BSCs and subsoils had high diversity, and the core diazotroph communities have a close relationship with nitrogen fixation and that they may be the main contributor to nitrogen fixing in BSCs and subsoils in temperate deserts.

Influence of Intensive and Super-Intensive Olive Grove Management on Soil Quality-Nutrients Content and Enzyme Activities.

Agricultural soil quality is an issue that has been widely debated in the literature in recent decades. Three olive grove areas (one in Lisbon and the others in Santarém, Portugal) with different management techniques (intensive and super-intensive) were selected. Nutrient concentrations and enzyme activities of soils were determined, as well as the C and N of litter and pruning waste (mulch) to estimate the influence of management techniques on the quality of olive grove soils and to assess the extent to which they are affected by organic covers and different cultivation intensities. Organic C and total N concentrations in soils of the intensive olive grove in Lisbon were the highest when compared with those in the intensive and super-intensive olive groves soils of Santarém. The concentrations of Ca, Mg, Na, and K were the main differences between the Lisbon olive groves and the other two from Santarém. Phosphatase, cellulase, and urease activities were related to the Na, extractable K, extractable P, Zn, Mn, organic C, and total N soil concentrations. Soil management and agricultural practices are determining factors for these enzymatic activities of Santarém olive groves, although climate conditions and soil properties play an important role in the soil enzymatic activities.

Effect of nitrogen application levels on photosynthetic nitrogen distribution and use efficiency in soybean seedling leaves.

BACKGROUND: Nitrogen nutrition is strongly associated with crop growth and development. Nitrogen application level affects leaf size as well as nitrogen content and distribution, and thus affects photosynthetic nitrogen-use efficiency (PNUE) and yield. In this study, soybean varieties "Jinyuan 55" and "Keshan 1" were treated with nitrogen as urea at: N0, 0 kg hm-2; N0.5, 60 kg hm-2; N1, 120 kg hm-2; and N1.5, 180 kg hm-2. We compared the effect of nitrogen level on plant morphology, biomass, photosynthetic physiology, nitrogen distribution, PNUE, and other soybean seedling leaf characteristics. RESULTS: Maximum carboxylation and electron transfer, net photosynthetic rates, and PNUE of both soybean varieties showed initial significant increases with increasing nitrogen application rate and subsequent stabilization. PNUE, carboxylation system components, electron transport components, and non-photosynthetic system distribution ratios in the photosynthetic system increased and subsequently decreased with increased nitrogen application rate. The nitrogen ratio between carboxylation and electron transport systems was positively correlated with PNUE in both soybean varieties. The nitrogen ratio in light-harvesting and non-photosynthetic systems showed a linear negative correlation with PNUE. CONCLUSIONS: Overall, an appropriate nitrogen level maintained a high photosynthetic nitrogen ratio, whereas low- or high-nitrogen conditions increased or decreased the nitrogen ratio in non-photosynthetic and photosynthetic systems, respectively, thus decreasing the PNUE and photosynthetic capacity. Moreover, increased nitrogen application rate led to a decreased nitrogen ratio in the light-harvesting system and an increased nitrogen ratio of electron transport and carboxylation systems. Our results provide a theoretical basis for optimizing leaf nitrogen distribution, determining optimum nitrogen levels, and promoting soybean seedling growth.

Leaf photosynthetic pigment as a predictor of leaf maximum carboxylation rate in a farmland ecosystem.

The leaf maximum rate of carboxylation (Vcmax) is a key parameter of plant photosynthetic capacity. The accurate estimation of Vcmax is crucial for correctly predicting the carbon flux in the terrestrial carbon cycle. Vcmax is correlated with plant traits including leaf nitrogen (Narea) and leaf photosynthetic pigments. Proxies for leaf chlorophyll (Chlarea) and carotenoid contents (Cararea) need to be explored in different ecosystems. In this study, we evaluated the relationship between leaf maximum rate of carboxylation (scaled to 25°C; Vcmax25) and both leaf Narea and photosynthetic pigments (Chlarea and Cararea) in winter wheat in a farmland ecosystem. Our results showed that Vcmax25 followed the same trends as leaf Chlarea. However, leaf Narea showed smaller dynamic changes before the flowering stage, and there were smaller seasonal variations in leaf Cararea. The correlation between leaf Vcmax25 and leaf Chlarea was the strongest, followed by leaf Cararea and leaf Narea (R2 = 0.69, R2 = 0.47 and R2 = 0.36, respectively). The random forest regression analysis also showed that leaf Chlarea and leaf Cararea were more important than leaf Narea for Vcmax25. The correlation between leaf Vcmax25 and Narea can be weaker since nitrogen allocation is dynamic. The estimation accuracy of the Vcmax25 model based on Narea, Chlarea, and Cararea (R2 = 0.75) was only 0.05 higher than that of the Vcmax25 model based on Chlarea and Cararea (R2 = 0.70). However, the estimation accuracy of the Vcmax25 model based on Chlarea and Cararea (R2 = 0.70) was 0.34 higher than that of the Vcmax25 model based on Narea (R2 = 0.36). These results highlight that leaf photosynthetic pigments can be a predictor for estimating Vcmax25, expanding a new way to estimate spatially continuous Vcmax25 on a regional scale, and to improve model simulation accuracy.

Stomatal, mesophyll and biochemical limitations to photosynthesis and their relationship with leaf structure over an elevation gradient in two conifers.

Photosynthetic responses across complex elevational gradients provides insight into fundamental processes driving responses of plant growth and net primary production to environmental change. Gas exchange of needles and twig water potential were measured in two widespread coniferous tree species, Pinus contorta and Picea engelmannii, over an 800-m elevation gradient in southeastern Wyoming, USA. We hypothesized that limitations to photosynthesis imposed by mesophyll conductance (gm) would be greatest at the highest elevation sites due to higher leaf mass per area (LMA) and that estimations of maximum rate of carboxylation (Vcmax) without including gm would obscure elevational patterns of photosynthetic capacity. We found that gm decreased with elevation for P. contorta and remained constant for P. engelmannii, but in general, limitation to photosynthesis by gm was small. Indeed, estimations of Vcmax when including gm were equivalent to those estimated without including gm and no correlation was found between gm and LMA nor between gm and leaf N. Stomatal conductance (gs) and biochemical demand for CO2 were by far the most limiting processes to photosynthesis at all sites along the elevation gradient. Photosynthetic capacity (A) and gs were influenced strongly by differences in soil water availability across the elevation transect, while gm was less responsive to water availability. Based on our analysis, variation in gm plays only a minor role in driving patterns of photosynthesis in P. contorta and P. engelmannii across complex elevational gradients in dry, continental environments of the Rocky Mountains and accurate modeling of photosynthesis, growth and net primary production in these forests may not require detailed estimation of this trait value.

Promising Energetic Polymers from Nanostructured Bacterial Cellulose.

This study investigated the nitration of nanostructured bacterial cellulose (NBC). The NBC, obtained using symbiotic Medusomyces gisevii Sa-12 as the microbial producer and then freeze-dried, was nitrated herein by two methods, the first using mixed sulphuric-nitric acids (MA) and the second using concentrated nitric acid in the presence of methylene chloride (NA+MC). The synthesized samples of NBC nitrates (NBCNs) exhibited 11.77-12.27% nitrogen content, a viscosity of 1086 mPa·s or higher, 0.7-14.5% solubility in an alcohol-ester mixture, and 0.002% ash. Scanning electron microscopy showed that the nitration compacted the NBC structure, with the original reticulate pattern of the structure being preserved in full. Infrared spectroscopy for the presence of functional nitro groups at 1658-1659, 1280, 838-840, 749-751 and 693-694 cm-1 confirmed the synthesis of cellulose nitrates in particular. Thermogravimetric and differential thermal analyses showed the resultant NBCNs to have a high purity and high specific heats of decomposition of 6.94-7.08 kJ/g. The NBCN samples differ conceptually from plant-based cellulose nitrates by having a viscosity above 1086 mPa·s and a unique 3D reticulate structure that is retained during the nitration. The findings suggest that the NBCNs can be considered for use in novel high-tech materials and science-driven fields distinct from the application fields of plant-based cellulose nitrates. The NBCN sample obtained with NA+MC has the ability to generate an organogel when it is dissolved in acetone. Because of the said property, this NBCN sample can find use as a classical adhesive scaffold and an energetic gel matrix for creating promising energetic polymers.