Movement rules for juvenile steelhead: dynamic linking of movement behaviour to habitat and density

We incorporated explanatory factors including stream habitat type and fish density into individual‐based models with dynamic connections among adjacent habitat units to infer dispersal behaviour of juvenile steelhead Oncorhynchus mykiss in a Great Lakes watershed. We used mark–recapture data and an inverse modelling approach to estimate daily probability of steelhead moving out of a habitat unit, P(move), according to four competing models. The models used included (i) a null model where all fish had equal movement probability; (ii) a habitat‐dependent model where P(move) depended on the habitat type; (iii) a density‐dependent model of P(move); and (iv) a model where P(move) depended on both density and habitat type. The habitat‐dependent model provided the most parsimonious fit to the observed data according to Akaike's information criteria (AICc). In the null model, P(move) averaged 0.70, whereas P(move) averaged 0.75 in pools, 0.68 in riffles and 0.73 in runs in the habitat‐dependent model.     

Temperate zone coastal seascapes: seascape patterning and adjacent seagrass habitat shape the distribution of rocky reef fish assemblages

Landscape Ecology - Whilst the composition and arrangement of habitats within landscape mosaics are known to be important determinants of biodiversity patterns, the influence of seascape patterning...     

Unravelling the relationship between a seasonal environment and the dynamics of forage growth in grazed swards

It is well reported in the scientific literature that pastures can have similar net forage accumulation when managed with contrasting structures. However, we hypothesized that the dynamics of forage accumulation in grazed swards is linked to seasonal-environmental conditions. Marandu palisadegrass (Brachiaria brizantha [Hochst. ex A. Rich.] was used as the forage species model. The experimental treatments were four grazing heights (10, 20, 30 and 40 cm) allocated to experimental units according to a randomized complete block design with four replicates and evaluated throughout four contrasting environmental seasons (summer, autumn, winter–early spring and late spring). Under rainy and warm periods, greater net forage accumulation was observed in pastures maintained taller; on the contrary, during the mild and dry periods, net forage accumulation rate reduced as grazing height increased. Such patterns of responses were related to compensations between tiller population density and tissues flows during summer and late spring and the reduced capacity of taller canopies to compensate lower population with greater growth rates during autumn and winter–early spring. Grazed swards changed their patterns of forage growth as they transitioned from favourable to more abiotic stressful conditions, suggesting that seasonal adjustments in grazing intensities are necessary in order to maximize forage production.     

Analysis of Mycosporine-Like Amino Acids in Selected Algae and Cyanobacteria by Hydrophilic Interaction Liquid Chromatography and a Novel MAA from the Red Alga Catenella repens

Mycosporine-like amino acids (MAAs), a group of small secondary metabolites found in algae, cyanobacteria, lichens and fungi, have become ecologically and pharmacologically relevant because of their pronounced UV-absorbing and photo-protective potential. Their analytical characterization is generally achieved by reversed phase HPLC and the compounds are often quantified based on molar extinction coefficients. As an alternative approach, in our study a fully validated hydrophilic interaction liquid chromatography (HILIC) method is presented. It enables the precise quantification of several analytes with adequate retention times in a single run, and can be coupled directly to MS. Excellent linear correlation coefficients (R² > 0.9991) were obtained, with limit of detection (LOD) values ranging from 0.16 to 0.43 µg/mL. Furthermore, the assay was found to be accurate (recovery rates from 89.8% to 104.1%) and precise (intra-day precision: 5.6%, inter-day precision ≤6.6%). Several algae were assayed for their content of known MAAs like porphyra-334, shinorine, and palythine. Liquid chromatography-mass spectrometry (LC-MS) data indicated a novel compound in some of them, which could be isolated from the marine species Catenella repens and structurally elucidated by nuclear magnetic resonance spectroscopy (NMR) as (E)-3-hydroxy-2-((5-hydroxy-5-(hydroxymethyl)-2-methoxy-3-((2-sulfoethyl)amino)cyclohex-2-en-1-ylidene)amino) propanoic acid, a novel MAA called catenelline.     

Sorghum Pasta and Noodles: Technological and Nutritional Aspects

Plant Foods for Human Nutrition - Sorghum is a major cereal crop with various agronomic advantages, contains health-promoting compounds and is gluten-free. There is a growing tendency to use...     

Forage legumes in grass pastures in tropical Brazil and likely impacts on greenhouse gas emissions: A review

Beef cattle producers seldom use fertilizers for their pastures in tropical regions of Brazil. Slowly, this is changing but because of the need for repeated applications, N fertilizer is rarely applied. The introduction of a forage legume is an appropriate solution for this problem, but until recently adoption has been very low as the legumes generally have not persisted in the sward. We report research on how grazing management can affect the persistence of stoloniferous legumes in pastures of Brachiaria spp. and the problems of establishing and maintaining crown-forming legumes such as Stylosanthes spp. With suitable management, milk or bovine carcass yields can be equal or greater from mixed than from grass-alone pastures fertilized with 120 or 150 kg Nha^-1 year⁻¹. In addition to savings in CO₂ emissions from fossil fuels for the production and distribution of N fertilizers, nitrous oxide emissions from cattle excreta and legume residues are lower than those from N-fertilized brachiaria grass monocultures. Other studies indicate that enteric methane emissions from cattle may be mitigated when forage legumes are included in their diet. The use of forage legumes in mixed pastures for tropical regions is emerging as a feasible strategy to keep meat and milk production at acceptable levels with reduced greenhouse gas emission rates.     

New Approaches to Modeling Methyl Jasmonate Effects on Pomegranate Quality during Postharvest Storage

Adaptive neuro fuzzy inference system (ANFIS) and genetic algorithm–artificial neural network (GA-ANN) models were used to predict the effect of methyl jasmonate (at three levels 0, 0.01, and 0.1 mM) and storage time (0, 14, 28, 42, 56, 70, and 84 days) on quality parameters and physiological changes of pomegranate fruits during storage. Methyl jasmonate reduced chilling injury and improved quality characteristics of pomegranates during postharvest storage. The GA-ANN and ANFIS were fed with two inputs of methyl jasmonate and storage time. The results showed that GA-ANN predictions agreed with experimental data and the GA-ANN with 14 neurons in one hidden layer can predict physiological changes and quality parameters of pomegranate (weight loss, pH, chilling injury index, ion leakage, ethylene, respiration, polyphenols, anthocyanins, and total antioxidant activity) with correlation coefficients equal to 0.87. The ANFIS model was trained by a hybrid method and agreement between experimental data and ANFIS predictions was significant (r = 0.90).