Primary Production and Nutrient Content in Two Salt Marsh

Seasonal variation patterns of aboveground and belowground biomass, net primary production, and nutrient accumulation were assessed in Atriplex portulacoides L. and Limoniastrum monopetalum (L.) Boiss. in Castro Marim salt marsh, Portugal. Sampling was conducted for five periods during 2001–2002 (autumn, winter, spring, summer, and autumn). This study indicates that both species have a clear seasonal variation pattern for both aboveground and belowground biomass. Mean live biomass was 2516 g m22 yr21 for L. monopetalum and 598 g m22 yr21 for A. portulacoides. Peak living biomass, in spring for both species, was three times greater in the former, 3502 g m22 yr21, than in the latter, 1077 g m22 yr21. For both the Smalley (Groenendijk 1984) and Weigert and Evans (1964) methods, productivity of L. monopetalum (2917 and 3635 g m22 yr21, respectively) was greater than that of A. portulacoides (1002 and 1615 g m22 yr21, respectively). Belowground biomass of L. monopetalum was 1.7 times greater than that of A. portulacoides. In spite of this, the root:shoot ratio for A. portulacoides was greater throughout the year. This shows that A. portulacoides allocates more biomass to roots and L. monopetalum to aerial components. Leaf area index was similar for both species, but specific leaf area of A. portulacoides was twice that of L. monopetalum. The greatest nutrient contents were found in leaves. Leaf nitrogen content was maximum in summer for both species (14.6 mg g21 for A. portulacoides and 15.5 mg g21 for L. monopetalum). Leaf phosphorus concentration was minimum in summer (1.1 mg g21 in A. portulacoides and 1.2 mg g21 in L. monopetalum). Leaf potassium contents in A. portulacoides were around three times greater than in L. monopetalum. Leaf calcium contents in L. monopetalum were three times greater than in A. portulacoides. There was a pronounced seasonal variation of calcium content in the former, while in the latter no clear variation was registered. Both species exhibited a decrease in magnesium leaf contents in the summer period. Manganese content in L. monopetalum leaves was tenfold that in A. portulacoides. Seasonal patterns of nutrient contents in A. portulacoides and L. monopetalum suggest that availability of these elements was not a limiting factor to biomass production

The Spatial Distribution of Absolute Skeletal Muscle Deoxygenation During Ramp-Incremental Exercise Is Not Influenced by Hypoxia.

Time-resolved near-infrared spectroscopy (TRS-NIRS) allows absolute quantitation of deoxygenated haemoglobin and myoglobin concentration ([HHb]) in skeletal muscle. We recently showed that the spatial distribution of peak [HHb] within the quadriceps during moderate-intensity cycling is reduced with progressive hypoxia and this is associated with impaired aerobic energy provision. We therefore aimed to determine whether reduced spatial distribution of skeletal muscle [HHb] was associated with impaired aerobic energy transfer during exhaustive ramp-incremental exercise in hypoxia. Seven healthy men performed ramp-incremental cycle exercise (20 W/min) to exhaustion at 3 fractional inspired O2 concentrations (FIO2): 0.21, 0.16, 0.12. Pulmonary O2 uptake (VO₂) was measured using a flow meter and gas analyser system. Lactate threshold (LT) was estimated non-invasively. Absolute muscle deoxygenation was quantified by multichannel TRS-NIRS from the rectus femoris and vastus lateralis (proximal and distal regions). VO₂peak and LT were progressively reduced (p < 0.05) with hypoxia. There was a significant effect (p < 0.05) of FIO2 on [HHb] at baseline, LT, and peak. However the spatial variance of [HHb] was not different between FIO2 conditions. Peak total Hb ([Hbtot]) was significantly reduced between FIO2 conditions (p < 0.001). There was no association between reductions in the spatial distribution of skeletal muscle [HHb] and indices of aerobic energy transfer during ramp-incremental exercise in hypoxia. While regional [HHb] quantified by TRS-NIRS at exhaustion was greater in hypoxia, the spatial distribution of [HHb] was unaffected. Interestingly, peak [Hbtot] was reduced at the tolerable limit in hypoxia implying a vasodilatory reserve may exist in conditions with reduced FIO2

Machine learning-driven web-post buckling resistance prediction for high-strength steel beams with elliptically-based web openings

Data availability: Data will be made available on request.Copyright © 2024 The Authors.. The use of periodical elliptically-based web (EBW) openings in high strength steel (HSS) beams has been increasingly popular in recent years mainly because of the high strength-to-weight ratio and the reduction in the floor height as a result of allowing different utility services to pass through the web openings. However, these sections are susceptible to web-post buckling (WPB) failure mode and therefore it is imperative that an accurate design tool is made available for prediction of the web-post buckling capacity. Therefore, the present paper aims to implement the power of various machine learning (ML) methods for prediction of the WPB capacity in HSS beams with (EBW) openings and to assess the performance of existing analytical design model. For this purpose, a numerical model is developed and validated with the aim of conducting a total of 10,764 web-post finite element models, considering S460, S690 and S960 steel grades. This data is employed to train and validate different ML algorithms including Artificial Neural Networks (ANN), Support Vector Machine Regression (SVR) and Gene Expression Programming (GEP). Finally, the paper proposes new design models for WPB resistance prediction. The results are discussed in detail, and they are compared with the numerical models and the existing analytical design method. The proposed design models based on the machine learning predictions are shown to be powerful, reliable and efficient design tools for capacity predictions of the WPB resistance of HSS beams with periodical (EBW) openings