Understanding the effects of the invasive plants on rural forest-dependent communities

Most of the studies on invasive species are disproportionately focused on their ecological effects and more investigations are needed to understand the effects of invasive plants on rural livelihoods. This study assesses the effects of the invasion of Mikania micrantha-an invasive vine-on the livelihoods of the buffer zone community forest users of Chitwan National Park, Nepal. In this study, the invasive plants are categorized based on their life-form (woody and non-woody) and mode of introduction (accidental or deliberate). The focus is on accidentally transported non-woody species. A household survey revealed that the invasion disproportionately affects the livelihoods of forest-dependent households. In addition, the livelihood effects of invasive plants are particularly determined by the suitability of the invasive plants to produce locally important forest products. © 2014 Steve Harrison, John Herbohn.

A clustering-based failure mode and effect analysis model and its application to the edible bird nest industry

Failure mode and effect analysis (FMEA) is a popular safety and reliability analysis tool in examining potential failures of products, process, designs, or services, in a wide range of industries. While FMEA is a popular tool, the limitations of the traditional Risk Priority Number (RPN) model in FMEA have been highlighted in the literature. Even though many alternatives to the traditional RPN model have been proposed, there are not many investigations on the use of clustering techniques in FMEA. The main aim of this paper was to examine the use of a new Euclidean distance-based similarity measure and an incremental-learning clustering model, i.e., fuzzy adaptive resonance theory neural network, for similarity analysis and clustering of failure modes in FMEA; therefore, allowing the failure modes to be analyzed, visualized, and clustered. In this paper, the concept of a risk interval encompassing a group of failure modes is investigated. Besides that, a new approach to analyze risk ordering of different failure groups is introduced. These proposed methods are evaluated using a case study related to the edible bird nest industry in Sarawak, Malaysia. In short, the contributions of this paper are threefold: (1) a new Euclidean distance-based similarity measure, (2) a new risk interval measure for a group of failure modes, and (3) a new analysis of risk ordering of different failure groups. © 2014 The Natural Computing Applications Forum.

The potential for indirect effects between co-flowering plants via shared pollinators depends on resource abundance, accessibility and relatedness

Co-flowering plant species commonly share flower visitors, and thus have the potential to influence each other's pollination. In this study we analysed 750 quantitative plant-pollinator networks from 28 studies representing diverse biomes worldwide. We show that the potential for one plant species to influence another indirectly via shared pollinators was greater for plants whose resources were more abundant (higher floral unit number and nectar sugar content) and more accessible. The potential indirect influence was also stronger between phylogenetically closer plant species and was independent of plant geographic origin (native vs. non-native). The positive effect of nectar sugar content and phylogenetic proximity was much more accentuated for bees than for other groups. Consequently, the impact of these factors depends on the pollination mode of plants, e.g. bee or fly pollinated. Our findings may help predict which plant species have the greatest importance in the functioning of plant-pollination networks.

Understanding the effects of crevice and galvanic corrosion for seawater desalination plants management

 This research revealed the differences that occur when two forms of corrosion occur simultaneously in comparison to the individual corrosions, crevice and galvanic. It was shown that two forms of corrosion can actually reduce the amount of damage caused in selected conditions.

Nanostructured liquid crystalline particle assisted delivery of 2,4-dichlorophenoxyacetic acid to weeds, crops and model plants

Routine agricultural practices are heavily dependent on the use of surfactants, many of which are toxic to humans and detrimental to the environment. In proof of concept work we have previously shown the potential of nanostructured liquid crystalline particles (NLCP) to safely interact with plant leaf cuticular surfaces with minimal impact on epicuticular waxes. Here we demonstrate the use of NLCP to effectively deliver the auxin herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) to plant leaves in laboratory and field studies. In the laboratory, the physiological stress responses of lupin, Lupinus angustifolius (L.) (Fabaceae) towards NLCP spray applications were shown to be much reduced in comparison with application of two common surfactants. Phytotoxicity assays of 2,4-D loaded NLCP were used to validate the herbicidal effects on Arabidopsis thaliana (L.) Heynth. (Brassicaceae) and established a similarity with that of surfactant assisted 2,4-D delivery when tested at a concentration of 0.1%. Field trials were conducted to test the efficacy of NLCP-assisted delivery of 2,4-D in comparison with commercial surfactants for the control of the invasive weed wild radish, Raphanus raphanistrum (L.) (Brassicaceae), in wheat, Triticum aestivum (L.) (Poaceae) crop fields. Compared against Estercide 800, a commercially available 2,4-D formulation, NLCP assisted delivery of 2,4-D was effective at low concentrations of 0.03% and 0.06%. The crop yield remained similar for all the tested concentrations and formulations of 2,4-D loaded NLCP and Estercide 800. This is the first report to directly show that, as an alternative to conventional methods, NLCP can be used under both laboratory and field conditions to successfully delivery an agrochemical.

Metal ion ligands in hyperaccumulating plants

Metal-hyperaccumulating plants have the ability to take up extraordinary quantities of certain metal ions without succumbing to toxic effects. Most hyperaccumulators select for particular metals but the mechanisms of selection are not understood at the molecular level. While there are many metal-binding biomolecules, this review focuses only on ligands that have been reported to play a role in sequestering, transporting or storing the accumulated metal. These include citrate, histidine and the phytosiderophores. The metal detoxification role of metallothioneins and phytochelatins in plants is also discussed.

Metabolite profiling reveals distinct changes in carbon and nitrogen metabolism in phosphate-deficient barley plants (Hordeum vulgare L.)

Plants modify metabolic processes for adaptation to low phosphate (P) conditions. Whilst transcriptomic analyses show that P deficiency changes hundreds of genes related to various metabolic processes, there is limited information available for global metabolite changes of P-deficient plants, especially for cereals. As changes in metabolites are the ultimate ‘readout’ of changes in gene expression, we profiled polar metabolites from both shoots and roots of P-deficient barley (Hordeum vulgare) using gas chromatography–mass spectrometry (GC-MS). The results showed that mildly P-deficient plants accumulated di- and trisaccharides (sucrose, maltose, raffinose and 6-kestose), especially in shoots. Severe P deficiency increased the levels of metabolites related to ammonium metabolism in addition to di- and trisaccharides, but reduced the levels of phosphorylated intermediates (glucose-6-P, fructose-6-P, inositol-1-P and glycerol-3-P) and organic acids (α-ketoglutarate, succinate, fumarate and malate). The results revealed that P-deficient plants modify carbohydrate metabolism initially to reduce P consumption, and salvage P from small P-containing metabolites when P deficiency is severe, which consequently reduced levels of organic acids in the tricarboxylic acid (TCA) cycle. The extent of the effect of severe P deficiency on ammonium metabolism was also revealed by liquid chromatography–mass spectrometry (LC-MS) quantitative analysis of free amino acids. A sharp increase in the concentrations of glutamine and asparagine was observed in both shoots and roots of severely P-deficient plants. Based on these data, a strategy for improving the ability of cereals to adapt to low P environments is proposed that involves alteration in partitioning of carbohydrates into organic acids and amino acids to enable more efficient utilization of carbon in P-deficient plants.