Taxonomic status of Hylomys parvus and Hylomys suillus (Insectivora: Erinaceidae): biochemical and morphological analyses

The genus Hylomys was thought to be represented by a single widespread species. Biochemical and morphometric analyses of several Southeast Asian populations reveal that Sumatra is inhabited by two distinct species, the dwarf gymnure (H. parvus) and the lesser gymnure (H. suillus). The absence of interbreeding between these two groups along with their relatively ancient common origins are documented by several diagnostic loci and a large Nei's genetic distance (D = 0.353 +/- 0.035). The dwarf gymnure has been reported only from the slopes of the Mt. Kerinci volcano in Sumatra, where the species lives at higher elevations than its potential competitor, the lesser gymnure. Other populations of Hylomys from Java, Borneo, and Malaysia are more closely related to the Sumatran sample of H. suillus, but they exhibit strong interpopulational genetic differentiation (D = 0.165 +/- 0.040) that may be accounted for by their isolated montane habitat. In addition, a principal-components analysis based on 16 measurements of the skull clearly separates adult specimens of both species. There is little overlap in the measurements between H. suillus (which is larger) and H. parvus. On Sumatra where both species may be sympatric, the notched space between premaxillary tips, soft texture of the fur, and more delicate skull and dentition are diagnostic of H. parvus.

Comparison of flag leaf and ear photosynthesis with biomass and grain yield of durum wheat under various water conditions and genotypes

Photosynthetic activity of cereals has traditionally been studied using leaves, thus neglecting the role of other organs such as ears. Here, we studied the effects of water status and genotypes on the photosynthetic activity of the flag leaf blade and the ear of durum wheat. The various parameters related to the photosynthetic activity were analysed in relation to the total above-ground plant biomass and grain yield at maturity. Four local varieties plus two cultivars adapted to the semiarid areas of South Morocco were grown in pots in a greenhouse. Five different water treatments were maintained from the beginning of stem elongation to maturity, when shoot biomass and grain yield were recorded. The net photosynthesis (A), stomatal conductance (gs) and transpiration (T) of the ear and the flag leaf were measured at anthesis. In both organs these factors decreased significantly with water deficit, whereas the A/T and A/gs ratios increased. The genotype effect was also significant for all traits studied. Whole-organ photosynthesis was much higher in the ear than in the flag leaf in well-watered conditions. As water stress developed, photosynthesis decreased less in the ear than in the flag leaf. Whole-ear photosynthesis correlated better than flag leaf photosynthesis with biomass and yield. Nevertheless, the relationships of the whole flag leaf with biomass and yield improved as the water stress became more severe, suggesting a progressive shift of yield from sink to source limitation. For all water regimes the ratios A/gs and A/T of the ear also showed a higher (negative) correlation with both biomass and yield than those of the flag leaf. The results indicate that the ear has a greater photosynthetic role than the flag leaf in determining grain yield, not only in drought but also in the absence of stress.

Nasopalatine duct cyst: report of 22 cases and review of the literature

Objectives: Nasopalatine duct cysts (NPDCs) are the most common developmental, epithelial and non-odontogenic cysts of the maxillae. The present study describes the clinicopathological characteristics of 22 NPDCs and discusses their etiology, incidence, treatment and prognosis, with a review of the literature on the subject. Study design: A retrospective observational study was made comprising a period of 36 years (1970-2006), and yielding a series of 22 patients with histopathological confirmation of NPDC. Surgical treatment was carried out under local anesthesia and comprised the dissection and removal of the cyst adopting a usually palatine approach, with the preparation of an enveloping flap from 1.4 to 2.4. Results: No statistically significant correlation was observed between the size of the lesion and patient age, although the size of the cyst differed according to patient gender, with a mean NPDC diameter of 16 mm in males and 12 mm in females. In no case did we observe root reabsorption or loss of vitality of the upper incisors following surgery. The X-ray image was rounded in 15 cases and heart-shaped in the remaining 7 cases. In the majority of cases panoramic X-rays and periapical and occlusal X-rays sufficed to identify the lesion, though computed tomography was used in cases of doubt. Conclusions: The etiology of NPDC is unclear. Simple surgical resection is recommended, followed by clinical and radiological control to ensure correct resolution of the case.

In situ aortobiiliac reconstruction of infected aneurysm using a single superficial femoral vein.

Objective: To demonstrate successful in situ aortoiliac reconstruction of an infected infrarenal aneurysm using one single superficial femoral vein (SFV). Methods: In situ reconstruction using the right SFV sutured in end-to-end anastomosis with the aorta and distally with the right common iliac artery and in end-to-side anastomosis with the left common iliac artery. Results: The operating time was less than reported for aortic in situ reconstruction with bilateral SFV harvesting. The duplex scan 3 months postoperatively showed permeability of the bypass without any anastomotic stenosis or pseudoaneurysm. The right common femoral, popliteal, and greater saphenous veins were patent without thrombus, and the patient did not complain about peripheral edema. Conclusions: The use of only one instead of both the SFVs for aortobiiliac in situ reconstruction might be a way to reduce operating time and allow autogenous venous reconstruction even in patients with limited availability of venous material.

Reconstruction Of Past Climate Conditions Over Central Europe From Groundwater Data

Here we present a 30 000 years low-resolution climate record reconstructed from groundwater data. The investigated site is located in the Bohemian Cretaceous Basin, in the corridor between the Scandinavian ice sheet and the Alpine ice field. Noble gas temperatures (NGT), obtained from groundwater data, preserved multicentennial temperature variability and indicated a cooling of at least 5-7 °C during the last glacial maximum (LGM). This is further confirmed by the depleted δ18O and δ2H values at the LGM. High excess air (ΔNe) at the end of the Pleistocene is possibly related to abrupt changes in recharge dynamics due to progression and retreat of ice covers and permafrost. These results agree with the fact that during the LGM permafrost and small glaciers developed in the inner valleys of the Giant Mountains (located in the watershed of the aquifers). A temporal decrease of deuterium excess from the pre-industrial Holocene to present days is linked to an increase of the air temperatures, and probably also to an increase of water pressure at the source region of precipitation over the past few hundred years

The lower Triassic anachronistic carbonate facies in space and time

The end-Permian mass extinction greatly affected the sedimentary record, but the sedimentary response was not limited to the Permian-Triassic boundary interval. This transformation extended to sedimentation that spanned the entire Early Triassic. Calcimicrobialites play an important role throughout this time interval, and at least four main events of anomalous carbonate deposition can be shown. A post-extinction calcimicrobial unit occurs above the extensive Permian skeletal carbonate platform exposed in the Taurus Mountains (southern Turkey), in south Armenia, north-west north and Central Iran along the Zagros Mountains. The calcimicrobial unit formed during the flooding of the platform that took place during the earliest Triassic. A similar calcimicrobialite formed during late Griesbachian to Dienerian time atop the shallow Permian skeletal carbonate platform largely exposed in south China. A third event occurred during the Early Olenekian on the first Mesozoic isolated pelagic plateau (Baid seamount, Oman Mountains). Here the change in carbonate sedimentation is reflected in the occurrence of thrombolites and carbonate seafloor fans. Near the end of Early Triassic time, unusual carbonate deposition is recorded both on an isolated pelagic plateau of the Western Tethys (Halstatt limestone of Dobrogea, Romania) and on the eastern Panthalassa margin of the western United States. In the western United States, the event is represented by stromatolites and thrombolites in the Virgin Limestone of the Moenkopi Formation and by seafloor fans in the middle and upper members of the Union Wash Formation. These unusual episodes of anomalous carbonate deposition illustrate a fundamental change in sedimentation that occurred in the aftermath of the end-Permian mass extinction.

Urotensin-II System in Genetic Control of Blood Pressure and Renal Function.

Urotensin-II controls ion/water homeostasis in fish and vascular tone in rodents. We hypothesised that common genetic variants in urotensin-II pathway genes are associated with human blood pressure or renal function. We performed family-based analysis of association between blood pressure, glomerular filtration and genes of the urotensin-II pathway (urotensin-II, urotensin-II related peptide, urotensin-II receptor) saturated with 28 tagging single nucleotide polymorphisms in 2024 individuals from 520 families; followed by an independent replication in 420 families and 7545 unrelated subjects. The expression studies of the urotensin-II pathway were carried out in 97 human kidneys. Phylogenetic evolutionary analysis was conducted in 17 vertebrate species. One single nucleotide polymorphism (rs531485 in urotensin-II gene) was associated with adjusted estimated glomerular filtration rate in the discovery cohort (p = 0.0005). It showed no association with estimated glomerular filtration rate in the combined replication resource of 8724 subjects from 6 populations. Expression of urotensin-II and its receptor showed strong linear correlation (r = 0.86, p<0.0001). There was no difference in renal expression of urotensin-II system between hypertensive and normotensive subjects. Evolutionary analysis revealed accumulation of mutations in urotensin-II since the divergence of primates and weaker conservation of urotensin-II receptor in primates than in lower vertebrates. Our data suggest that urotensin-II system genes are unlikely to play a major role in genetic control of human blood pressure or renal function. The signatures of evolutionary forces acting on urotensin-II system indicate that it may have evolved towards loss of function since the divergence of primates.

The persistence of lifestyles: rates and correlates of homicide in Western Europe from 1960 to 2010

This article analyses rates and correlates of homicide in 15 West European countries from 1960 to 2010. The results show that the levels of homicide in 2010 and the trends in homicide from 1960 to 2010 are not related to any of the traditional demographic and socioeconomic predictors of crime. Homicide victimization rates show an increase from the mid-1960s until the early 1990s, and a decrease since then. Victims of both genders and all group ages follow the same trend, except in the case of infanticide, which decreased during the whole period. These results do not support the hypothesis of a homicide trend driven by the evolution of victimization of young men in public space. The authors propose an explanation based on a lifestyle approach.

Historical reconstruction of polychlorinated biphenyl (PCB) exposures for workers in a capacitor manufacturing plant

We developed a semiquantitative job exposure matrix (JEM) for workers exposed to polychlorinated biphenyls (PCBs) at a capacitor manufacturing plant from 1946 to 1977. In a recently updated mortality study, mortality of prostate and stomach cancer increased with increasing levels of cumulative exposure estimated with this JEM (trend p values = 0.003 and 0.04, respectively). Capacitor manufacturing began with winding bales of foil and paper film, which were placed in a metal capacitor box (pre-assembly), and placed in a vacuum chamber for flood-filling (impregnation) with dielectric fluid (PCBs). Capacitors dripping with PCB residues were then transported to sealing stations where ports were soldered shut before degreasing, leak testing, and painting. Using a systematic approach, all 509 unique jobs identified in the work histories were rated by predetermined process- and plant-specific exposure determinants; then categorized based on the jobs' similarities (combination of exposure determinants) into 35 job exposure categories. The job exposure categories were ranked followed by a qualitative PCB exposure rating (baseline, low, medium, and high) for inhalation and dermal intensity. Category differences in other chemical exposures (solvents, etc.) prevented further combining of categories. The mean of all available PCB concentrations (1975 and 1977) for jobs within each intensity rating was regarded as a representative value for that intensity level. Inhalation (in microgram per cubic milligram) and dermal (unitless) exposures were regarded as equally important. Intensity was frequency adjusted for jobs with continuous or intermittent PCB exposures. Era-modifying factors were applied to the earlier time periods (1946-1974) because exposures were considered to have been greater than in later eras (1975-1977). Such interpolations, extrapolations, and modifying factors may introduce non-differential misclassification; however, we do believe our rigorous method minimized misclassification, as shown by the significant exposure-response trends in the epidemiologic analysis.

Statistically significant changes of antimüllerian hormone and inhibin levels during the physiologic menstrual cycle in reproductive age women.

OBJECTIVE: To define the dynamics of antimüllerian hormone (AMH) and inhibins during the physiologic menstrual cycle. DESIGN: Longitudinal study. SETTING: University hospital. PATIENT(S): 36 young, healthy, normal weight Caucasian women without medication. INTERVENTION(S): Normal ovulatory menstrual cycles were evaluated by regular blood sampling taken every other day and periovulatory every day. MAIN OUTCOME MEASURE(S): Serum concentrations of AMH, inhibin A and B, follicle-stimulating hormone (FSH), luteinizing hormone (LH), prolactin, estradiol, progesterone, and free testosterone were measured in all blood samples. RESULT(S): Median AMH levels are statistically significantly higher in the late follicular compared with ovulation or the early luteal phase. There are statistically significant correlations between both AMH and FSH, and AMH and free testosterone in all cycle phases. Inhibin A increases strongly in the late follicular phase and peaks at day LH + 4. Inhibin B shows a broad midfollicular and a sharp early luteal peak, the difference being statistically significant between day LH + 4 and the earlier time points and between day LH + 2 and day LH. Although there is a negative association between inhibin A or B and the body mass index (BMI), there is no correlation between AMH and the BMI. CONCLUSION(S): Levels of AMH show a statistically significant change during the menstrual cycle and may influence the circulating gonadotropin and steroid hormone levels.

Nasopalatine duct cyst: report of 22 cases and review of the literature

Objectives: Nasopalatine duct cysts (NPDCs) are the most common developmental, epithelial and non-odontogenic cysts of the maxillae. The present study describes the clinicopathological characteristics of 22 NPDCs and discusses their etiology, incidence, treatment and prognosis, with a review of the literature on the subject. Study design: A retrospective observational study was made comprising a period of 36 years (1970-2006), and yielding a series of 22 patients with histopathological confirmation of NPDC. Surgical treatment was carried out under local anesthesia and comprised the dissection and removal of the cyst adopting a usually palatine approach, with the preparation of an enveloping flap from 1.4 to 2.4. Results: No statistically significant correlation was observed between the size of the lesion and patient age, although the size of the cyst differed according to patient gender, with a mean NPDC diameter of 16 mm in males and 12 mm in females. In no case did we observe root reabsorption or loss of vitality of the upper incisors following surgery. The X-ray image was rounded in 15 cases and heart-shaped in the remaining 7 cases. In the majority of cases panoramic X-rays and periapical and occlusal X-rays sufficed to identify the lesion, though computed tomography was used in cases of doubt. Conclusions: The etiology of NPDC is unclear. Simple surgical resection is recommended, followed by clinical and radiological control to ensure correct resolution of the case.

Quantitative genetics of learning ability and resistance to stress in Drosophila melanogaster.

Even though laboratory evolution experiments have demonstrated genetic variation for learning ability, we know little about the underlying genetic architecture and genetic relationships with other ecologically relevant traits. With a full diallel cross among twelve inbred lines of Drosophila melanogaster originating from a natural population (0.75 < F < 0.93), we investigated the genetic architecture of olfactory learning ability and compared it to that for another behavioral trait (unconditional preference for odors), as well as three traits quantifying the ability to deal with environmental challenges: egg-to-adult survival and developmental rate on a low-quality food, and resistance to a bacterial pathogen. Substantial additive genetic variation was detected for each trait, highlighting their potential to evolve. Genetic effects contributed more than nongenetic parental effects to variation in traits measured at the adult stage: learning, odorant perception, and resistance to infection. In contrast, the two traits quantifying larval tolerance to low-quality food were more strongly affected by parental effects. We found no evidence for genetic correlations between traits, suggesting that these traits could evolve at least to some degree independently of one another. Finally, inbreeding adversely affected all traits.

Stochastic inversion of tracer test and electrical geophysical data to estimate hydraulic conductivities.

Quantifying the spatial configuration of hydraulic conductivity (K) in heterogeneous geological environments is essential for accurate predictions of contaminant transport, but is difficult because of the inherent limitations in resolution and coverage associated with traditional hydrological measurements. To address this issue, we consider crosshole and surface-based electrical resistivity geophysical measurements, collected in time during a saline tracer experiment. We use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology to jointly invert the dynamic resistivity data, together with borehole tracer concentration data, to generate multiple posterior realizations of K that are consistent with all available information. We do this within a coupled inversion framework, whereby the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration. To minimize computational expense, a facies-based subsurface parameterization is developed. The Bayesian-McMC methodology allows us to explore the potential benefits of including the geophysical data into the inverse problem by examining their effect on our ability to identify fast flowpaths in the subsurface, and their impact on hydrological prediction uncertainty. Using a complex, geostatistically generated, two-dimensional numerical example representative of a fluvial environment, we demonstrate that flow model calibration is improved and prediction error is decreased when the electrical resistivity data are included. The worth of the geophysical data is found to be greatest for long spatial correlation lengths of subsurface heterogeneity with respect to wellbore separation, where flow and transport are largely controlled by highly connected flowpaths.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

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).