Influence of emergence timing of weeds on the establishment of woody natives and ground cover species

Les invasions biològiques són produïdes per espècies transportades per l'home fora de la regió d'origen a altres regions on s'estableixen i expandeixen. Són actualment de les majors causes de perduda de biodiversitat, amb el canvi d'usos del sòl, tret rellevant en zones insulars. Comprendre mecanismes de competència amb les espècies autòctones és clau per gestionar el problema. L’experiment evidencia diferències de creixement de 7 plantes natives australianes (3 espècies d’eucaliptus, 3 espècies d’acàcia, 1 pasturatge natiu), competint intraespecífica (entre mateixa espècie) i interespecíficament (acàcies o eucaliptus convivint amb pasturatge natiu) plantejant tres tractaments (sense males herbes, males herbes i males herbes a posteriori) per definir la naturalesa de la interacció dels diferents tipus funcionals d'espècies. S’analitzen tendències temporals de creixement de plàntules, així com la supervivència. S’ha detectat una moderada correlació entre taxes de creixement d’espècies i mida de la llavor, (p ≈ 0.6), així com una correlació entre la supervivència i la humitat del sòl (p ≈ 0.5); efectes estacionals. A curt termini i en escenari de primavera la convivència amb males herbes reporta creixement nul. Tractaments sense males herbes, presenten major supervivència en escenaris en competència interespecífica. A llarg termini les espècies amb major supervivència són les que conviuen amb pasturatge natiu i sense males herbes, indicant un efecte beneficiós en espècies millor adaptades a la sequera (E. loxophleba).

Internal promotion versus external recruitment: evidence in industrial plants

An analysis is carried out in a sample of 738 industrial plants of the determining factors in the use of internal promotion of blue-collar workers to middle managers and skilled technicians as against their external recruitment. The use of internal promotion is positively correlated with variables indicative of the efforts made by plants to measure employees' skills, and to a lesser extent, with the level of specificity of investments in human capital made by blue-collar workers. Contrary to what was expected, variables related with the use and efficiency of other incentive systems have no significant influence on the increased or decreased use of internal promotion. These results are initial evidence that internal promotions are used to protect and favour specific investments, especially those made by firms in order to discover their workers' skills.

Ultrastructural characterisation of the cell wall of Arabidopsis thaliana transgenic plants

The plant cell wall is a strong fibrillar network that gives each cell its stable shape. It is constituted by a network of cellulose microfibrils embedded in a matrix of polysaccharides, such as xyloglucans. To enlarge, cells selectively loosen this network. Moreover, there is a pectin-rich intercellular material, the middle lamella, cementing together the walls of adjacent plant cells. Xyloglucan endotransglucosylase/hydrolases (XTHs) are a group of enzymes involved in the reorganisation of the cellulose-xyloglucan framework by catalysing cleavage and re-ligation of the xyloglucan chains in the plant cell wall, and are considered cell wall loosening agents. In the laboratory, it has been isolated and characterised a XTH gene, ZmXTH1, from an elongation root cDNA library of maize. To address the cellular function of ZmXTH1, transgenic Arabidopsis thaliana plants over-expressing ZmXTH1 (under the control of the CaMV35S promoter) were generated. The aim of the work performed was therefore the characterisation of these transgenic plants at the ultrastructural level, by transmission electron microscopy (TEM).The detailed cellular phenotype of transgenic plants was investigated by comparing ultra-thin transverse sections of basal stem of 5-weeks old plants of wild type (Col 0) and 35S-ZmXTH1 Arabidopsis plants. Transgenic plants show modifications in the cell walls, particularly a thicker middle lamella layer with respect the wild type plants, supporting the idea that the overexpression of ZmXTH1 could imply a pronounced wall-loosening. In sum, the work carried out reinforces the idea that ZmXTH1 is involved in the cell wall loosening process in maize.  

Textural classification of land cover using support vector machines: an empirical comparison with parametric, non parametric and hybrid classifiers in the Bolivian Amazon

Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.

Safety in vicinity of industrials plants: risk assessment and land use planning

The aim of this book is to survey on different Land Use Planning and safety approaches in vicinity of industrial plants. As this research is associated with three broad fields of Land Use Planning, safety and security, the set principle is to avoid unnecessary and over detailed information, but including the useful ones to provide a comprehensive resource which can be applicable for several purposes. Besides, the proposed method, which is explained in Chapter 7, can initiate a new field for future of Land Use Planning in vicinity of industrial plants.

A Tool for optimum design of Waste Water Treatment Plants under uncertainty

L’objectiu principal és presentar un nou prototipus d’eina per al disseny de les plantes de tractament d’aigües residuals utilitzant models mecànics dinàmics quantificant la incertesa

Cross recurrence quantification for cover song identification

There is growing evidence that nonlinear time series analysis techniques can be used to successfully characterize, classify, or process signals derived from realworld dynamics even though these are not necessarily deterministic and stationary. In the present study we proceed in this direction by addressing an important problem our modern society is facing, the automatic classification of digital information. In particular, we address the automatic identification of cover songs, i.e. alternative renditions of a previously recorded musical piece. For this purpose we here propose a recurrence quantification analysis measure that allows tracking potentially curved and disrupted traces in cross recurrence plots. We apply this measure to cross recurrence plots constructed from the state space representation of musical descriptor time series extracted from the raw audio signal. We show that our method identifies cover songs with a higher accuracy as compared to previously published techniques. Beyond the particular application proposed here, we discuss how our approach can be useful for the characterization of a variety of signals from different scientific disciplines. We study coupled Rössler dynamics with stochastically modulated mean frequencies as one concrete example to illustrate this point.

Predictability of music descriptor time series and its application to cover song detection

Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. These descriptors cover different musical facets and are extracted from a large collection of real audio recordings comprising a variety of musical genres. Our findings show that music descriptor time series exhibit a certain predictability not only for short time intervals, but also for mid-term and relatively long intervals. This fact is observed independently of the descriptor, musical facet and time series model we consider. Moreover, we show that our findings are not only of theoretical relevance but can also have practical impact. To this end we demonstrate that music predictability at relatively long time intervals can be exploited in a real-world application, namely the automatic identification of cover songs (i.e. different renditions or versions of the same musical piece). Importantly, this prediction strategy yields a parameter-free approach for cover song identification that is substantially faster, allows for reduced computational storage and still maintains highly competitive accuracies when compared to state-of-the-art systems.

Chroma binary similarity and local alignment applied to cover song identification

We present a new technique for audio signal comparison based on tonal subsequence alignment and its application to detect cover versions (i.e., different performances of the same underlying musical piece). Cover song identification is a task whose popularity has increased in the Music Information Retrieval (MIR) community along in the past, as it provides a direct and objective way to evaluate music similarity algorithms.This article first presents a series of experiments carried outwith two state-of-the-art methods for cover song identification.We have studied several components of these (such as chroma resolution and similarity, transposition, beat tracking or Dynamic Time Warping constraints), in order to discover which characteristics would be desirable for a competitive cover song identifier. After analyzing many cross-validated results, the importance of these characteristics is discussed, and the best-performing ones are finally applied to the newly proposed method. Multipleevaluations of this one confirm a large increase in identificationaccuracy when comparing it with alternative state-of-the-artapproaches.

Prediction of the bulking phenomenon in wastewater treatment plants

The control and prediction of wastewater treatment plants poses an important goal: to avoid breaking the environmental balance by always keeping the system in stable operating conditions. It is known that qualitative information — coming from microscopic examinations and subjective remarks — has a deep influence on the activated sludge process. In particular, on the total amount of effluent suspended solids, one of the measures of overall plant performance. The search for an input–output model of this variable and the prediction of sudden increases (bulking episodes) is thus a central concern to ensure the fulfillment of current discharge limitations. Unfortunately, the strong interrelationbetween variables, their heterogeneity and the very high amount of missing information makes the use of traditional techniques difficult, or even impossible. Through the combined use of several methods — rough set theory and artificial neural networks, mainly — reasonable prediction models are found, which also serve to show the different importance of variables and provide insight into the process dynamics

Application of a support system to the design of wastewater treatment plants

This paper presents a case study that explores the advantages that can be derived from the use of a design support system during the design of wastewater treatment plants (WWTP). With this objective in mind a simplified but plausible WWTP design case study has been generated with KBDS, a computer-based support system that maintains a historical record of the design process. The study shows how, by employing such a historical record, it is possible to: (1) rank different design proposals responding to a design problem; (2) study the influence of changing the weight of the arguments used in the selection of the most adequate proposal; (3) take advantage of keywords to assist the designer in the search of specific items within the historical records; (4) evaluate automatically thecompliance of alternative design proposals with respect to the design objectives; (5) verify the validity of previous decisions after the modification of the current constraints or specifications; (6) re-use the design records when upgrading an existing WWTP or when designing similar facilities; (7) generate documentation of the decision making process; and (8) associate a variety of documents as annotations to any component in the design history. The paper also shows one possible future role of design support systems as they outgrow their current reactive role as repositories of historical information and start to proactively support the generation of new knowledge during the design process

The fossil record and evolution of freshwater plants: A review

Palaeobotany applied to freshwater plants is an emerging field of palaeontology. Hydrophytic plants reveal evolutionary trends of their own, clearly distinct from those of the terrestrial and marine flora. During the Precambrian, two groups stand out in the fossil record of freshwater plants: the Cyanobacteria (stromatolites) in benthic environments and the prasinophytes (leiosphaeridian acritarchs) in transitional planktonic environments. During the Palaeozoic, green algae (Chlorococcales, Zygnematales, charophytes and some extinct groups) radiated and developed the widest range of morphostructural patterns known for these groups. Between the Permian and Early Cretaceous, charophytes dominated macrophytic associations, with the consequence that over tens of millions of years, freshwater flora bypassed the dominance of vascular plants on land. During the Early Cretaceous, global extension of the freshwater environments is associated with diversification of the flora, including new charophyte families and the appearance of aquatic angiosperms and ferns for the first time. Mesozoic planktonic assemblages retained their ancestral composition that was dominated by coenobial Chlorococcales, until the appearance of freshwater dinoflagellates in the Early Cretaceous. In the Late Cretaceous, freshwater angiosperms dominated almost all macrophytic communities worldwide. The Tertiary was characterised by the diversification of additional angiosperm and aquatic fern lineages, which resulted in the first differentiation of aquatic plant biogeoprovinces. Phytoplankton also diversified during the Eocene with the development of freshwater diatoms and chrysophytes. Diatoms, which were exclusively marine during tens of millions of years, were dominant over the Chlorococcales during Neogene and in later assemblages. During the Quaternary, aquatic plant communities suffered from the effects of eutrophication, paludification and acidification, which were the result of the combined impact of glaciation and anthropogenic disturbance.

Antifungal compounds from plants

Due to the increase of the incidence of fungal infections in humans and the limitations of the available antimycotic drugs, among which the emergence of resistant strains, there is a need for the discovery of new antifungal agents. Plants, especially those used in Traditional Medicine, linked to an unmatched chemical diversity, either as pure compounds or as plant extracts, provide unlimited opportunities for the development of new antifungals. Inrecent years, compounds from different phytochemical groups have been described as having antifungal activity, including polyphenols, saponins, or peptides, among others, as well asessential oils and their constituents. After screening of ethnopharmacologically selected plants, mainly from Latin-America, followed by bio-guided isolation, our group hasdescribed the antifungal activity of different types of plant constituents, such as sesquiterpenes, triterpenes, flavonoids, lignans, fatty acids and essential oils.

Selenium uptake by edible plants from enriched peat.

As a constituent of selenoproteins, selenium (Se) is considered an essential element for human health.The main way that Se enters the body is via the consumption of vegetables, whose concentration of thiselement depends on soil Se content. We grew cabbage, lettuce, chard and parsley, in peat enriched in Seby means of the additive Selcote Ultra®and Na2SeO3and Na2SeO4. Total Se in plants was determinedby acidic digestion and Se speciation by an enzymatic extraction. Both were measured by ICP/MS. Theconcentration ranges were between 0.1 mg Se kg−1and 30 mg Se kg−1for plants grown in Selcote Ultra®media, and between 0.4 mg Se kg−1and 1606 mg Se kg−1for those grown in peat enriched with Se sodiumsalts. We found Se (IV), Se (VI) and SeMet in all the extracts. Peat fortified with Selcote Ultra®gave slightlyhigher Se concentration than natural content values. For plants grown with selenium sodium salts, Secontent increases with the Se added and part of the inorganic Se was converted mainly to SeMet. A highSe fortification can damage or inhibit plant growth. Cabbage showed the greatest tolerance to Se.

Enhanced Botrytis cinerea resistance of Arabidopsis plants grown in compost may be explained by increased expression of defense-related genes, as revealed by microarray analysis

Composts are the products obtained after the aerobic degradation of different types of organic matter waste and can be used as substrates or substrate/soil amendments for plant cultivation. There is a small but increasing number of reports that suggest that foliar diseases may be reduced when using compost, rather than standard substrates, as growing medium. The purpose of this study was to examine the gene expression alteration produced by the compost to gain knowledge of the mechanisms involved in compost-induced systemic resistance. A compost from olive marc and olive tree leaves was able to induce resistance against Botrytis cinerea in Arabidopsis, unlike the standard substrate, perlite. Microarray analyses revealed that 178 genes were differently expressed, with a fold change cut-off of 1, of which 155 were up-regulated and 23 were down-regulated in compost-grown, as against perlite-grown plants. A functional enrichment study of up-regulated genes revealed that 38 Gene Ontology terms were significantly enriched. Response to stress, biotic stimulus, other organism, bacterium, fungus, chemical and abiotic stimulus, SA and ABA stimulus, oxidative stress, water, temperature and cold were significantly enriched, as were immune and defense responses, systemic acquired resistance, secondary metabolic process and oxireductase activity. Interestingly, PR1 expression, which was equally enhanced by growing the plants in compost and by B. cinerea inoculation, was further boosted in compost-grown pathogen-inoculated plants. Compost triggered a plant response that shares similarities with both systemic acquired resistance and ABA-dependent/independent abiotic stress responses.