936 resultados para Plant-environment relationships


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* Arbuscular mycorrhizal fungi (AMF) are plant symbionts that improve floristic diversity and ecosystem productivity. Many AMF species are generalists with wide host ranges. Arbuscular mycorrhizal fungi individuals are heterokaryotic, and AMF populations are genetically diverse. Populations of AMF harbor two levels of genetic diversity on which selection can act, namely among individuals and within individuals. Whether environmental factors alter genetic diversity within populations is still unknown. * Here, we measured genetic changes and changes in fitness-related traits of genetically distinct AMF individuals from one field, grown with different concentrations of available phosphate or different host species. * We found significant genotype-by-environment interactions for AMF fitness traits in response to these treatments. Host identity had a strong effect on the fitness of different AMF, unearthing a specificity of response within Glomus intraradices. Arbuscular mycorrhizal fungi individuals grown in novel environments consistently showed a reduced presence of polymorphic genetic markers, providing some evidence for host or phosphate-induced genetic change in AMF. * Given that AMF individuals can form extensive hyphal networks colonizing different hosts simultaneously, contrasting habitats or soil properties may lead to evolution in the population. Local selection may alter the structure of AMF populations and maintain genetic diversity, potentially even within the hyphal network of one fungus.

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Question: How do clonal traits of a locally dominant grass (Elymus repens (L.) Gould.) respond to soil heterogeneity and shape spatial patterns of its tillers? How do tiller spatial patterns constrain seedling recruitment within the community?Locations: Artificial banks of the River Rhone, France.Material and Methods: We examined 45 vegetation patches dominated by Elymus repens. During a first phase we tested relationships between soil variables and three clonal traits (spacer length, number of clumping tillers and branching rate), and between the same clonal traits and spatial patterns (i.e. density and degree of spatial aggregation) of tillers at a very fine scale. During a second phase, we performed a sowing experiment to investigate effects of density and spatial patterns of E. repens on recruitment of eight species selected from the regional species pool.Results: Clonal traits had clear effects - especially spacer length - on densification and aggregation of E. repens tillers and, at the same time, a clear response of these same clonal traits as soil granulometry changed. The density and degree of aggregation of E. repens tillers was positively correlated to total seedling cover and diversity at the finest spatial scales.Conclusions: Spatial patterning of a dominant perennial grass responds to soil heterogeneity through modifications of its clonal morphology as a trade-off between phalanx and guerrilla forms. In turn, spatial patterns have strong effects on abundance and diversity of seedlings. Spatial patterns of tillers most probably led to formation of endogenous gaps in which the recruitment of new plant individuals was enhanced. Interestingly, we also observed more idiosyncratic effects of tiller spatial patterns on seedling cover and diversity when focusing on different growth forms of the sown species.

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Polyamines (PAs) are small polycationic compounds present in all living organisms. Compelling evidences indicate a role for PAs in plant protection against stress. During the recent years, genetic, molecular and ‘omic’ approaches have been undertaken to unravel the role of PAs in stress signaling. Overall, results point to intricate relationships between PAs, stress hormone pathways and ROS signaling. Such cross-regulations condition stress signaling through the modulation of abscisic acid (ABA) and ROS amplification-loops. In this chapter we compile our recent findings which elucidate molecular mechanisms and signalingpathways by which PAs contribute to stress protection in plants.

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If you have ever flown in an airplane over Iowa, you would see that our woodlands are scattered along the rivers and streams and areas too steep to farm. You would also see a green carpet of trees within out cities and towns. Did you know the 90% of the over 2.7 million acres of forest in Iowa is owned by over 138,000 different private owners? Or that 30% of the land cover in a typical Iowa community if covered by trees? Trees are vital for the protection of our drinking water supply, critical for wildlife habitat, and help sustain employment of over 7,000 Iowans in the wood products industry. This booklet "20 Native trees to Plant" will help you gain a greater knowledge about Iowa's trees and forests. Learn about and enjoy Iowa's trees. Consider ways that you can improve our environment by planting and caring for Iowa's trees and forests.

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It's a fact. Landowners like the five couples featured in the publication have helped replant Iowa. In fact, Iowa's forests and dwindled from an original 7 million acres to only 1.4 million acres in 1974. The state now has 2.8 million acres, surpassing the acreage of woodlands more than a century ago.

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This publication is a guide to understanding the Iowa Department of Transportation’s roadside management programs. It offers descriptions of various landscape designs or planting styles used within or adjacent to Iowa’s highway rights-of-way, as well as various plant profiles. In addition, this guide will help you learn more about the value of plants and their contribution to our environment and society. This publication is written for persons having little or no formal training in botany, and technical terminology has been kept to the minimum necessary to maintain standards of accuracy and conciseness in the descriptions.

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Aim To evaluate the effects of using distinct alternative sets of climatic predictor variables on the performance, spatial predictions and future projections of species distribution models (SDMs) for rare plants in an arid environment. . Location Atacama and Peruvian Deserts, South America (18º30'S - 31º30'S, 0 - 3 000 m) Methods We modelled the present and future potential distributions of 13 species of Heliotropium sect. Cochranea, a plant group with a centre of diversity in the Atacama Desert. We developed and applied a sequential procedure, starting from climate monthly variables, to derive six alternative sets of climatic predictor variables. We used them to fit models with eight modelling techniques within an ensemble forecasting framework, and derived climate change projections for each of them. We evaluated the effects of using these alternative sets of predictor variables on performance, spatial predictions and projections of SDMs using Generalised Linear Mixed Models (GLMM). Results The use of distinct sets of climatic predictor variables did not have a significant effect on overall metrics of model performance, but had significant effects on present and future spatial predictions. Main conclusion Using different sets of climatic predictors can yield the same model fits but different spatial predictions of current and future species distributions. This represents a new form of uncertainty in model-based estimates of extinction risk that may need to be better acknowledged and quantified in future SDM studies.

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Résumé La diminution de la biodiversité, à toutes les échelles spatiales et sur l'ensemble de la planète, compte parmi les problèmes les plus préoccupants de notre époque. En terme de conservation, il est aujourd'hui primordial de mieux comprendre les mécanismes qui créent et maintiennent la biodiversité dans les écosystèmes naturels ou anthropiques. La présente étude a pour principal objectif d'améliorer notre compréhension des patrons de biodiversité végétale et des mécanismes sous jacents, dans un écosystème complexe, riche en espèces et à forte valeur patrimoniale, les pâturages boisés jurassiens. Structure et échelle spatiales sont progressivement reconnues comme des dimensions incontournables dans l'étude des patrons de biodiversité. De plus, ces deux éléments jouent un rôle central dans plusieurs théories écologiques. Toutefois, peu d'hypothèses issues de simulations ou d'études théoriques concernant le lien entre structure spatiale du paysage et biodiversité ont été testées de façon empirique. De même, l'influence des différentes composantes de l'échelle spatiale sur les patrons de biodiversité est méconnue. Cette étude vise donc à tester quelques-unes de ces hypothèses et à explorer les patrons spatiaux de biodiversité dans un contexte multi-échelle, pour différentes mesures de biodiversité (richesse et composition en espèces) à l'aide de données de terrain. Ces données ont été collectées selon un plan d'échantillonnage hiérarchique. Dans un premier temps, nous avons testé l'hypothèse élémentaire selon laquelle la richesse spécifique (le nombre d'espèces sur une surface donnée) est liée à l'hétérogénéité environnementale quelque soit l'échelle. Nous avons décomposé l'hétérogénéité environnementale en deux parties, la variabilité des conditions environnementales et sa configuration spatiale. Nous avons montré que, en général, la richesse spécifique augmentait avec l'hétérogénéité de l'environnement : elle augmentait avec le nombre de types d'habitats et diminuait avec l'agrégation spatiale de ces habitats. Ces effets ont été observés à toutes les échelles mais leur nature variait en fonction de l'échelle, suggérant une modification des mécanismes. Dans un deuxième temps, la structure spatiale de la composition en espèces a été décomposée en relation avec 20 variables environnementales et 11 traits d'espèces. Nous avons utilisé la technique de partition de la variation et un descripteur spatial, récemment développé, donnant accès à une large gamme d'échelles spatiales. Nos résultats ont montré que la structure spatiale de la composition en espèces végétales était principalement liée à la topographie, aux échelles les plus grossières, et à la disponibilité en lumière, aux échelles les plus fines. La fraction non-environnementale de la variation spatiale de la composition spécifique avait une relation complexe avec plusieurs traits d'espèces suggérant un lien avec des processus biologiques tels que la dispersion, dépendant de l'échelle spatiale. Dans un dernier temps, nous avons testé, à plusieurs échelles spatiales, les relations entre trois composantes de la biodiversité : la richesse spécifique totale d'un échantillon (diversité gamma), la richesse spécifique moyenne (diversité alpha), mesurée sur des sous-échantillons, et les différences de composition spécifique entre les sous-échantillons (diversité beta). Les relations deux à deux entre les diversités alpha, beta et gamma ne suivaient pas les relations attendues, tout du moins à certaines échelles spatiales. Plusieurs de ces relations étaient fortement dépendantes de l'échelle. Nos résultats ont mis en évidence l'importance du rapport d'échelle (rapport entre la taille de l'échantillon et du sous-échantillon) lors de l'étude des patrons spatiaux de biodiversité. Ainsi, cette étude offre un nouvel aperçu des patrons spatiaux de biodiversité végétale et des mécanismes potentiels permettant la coexistence des espèces. Nos résultats suggèrent que les patrons de biodiversité ne peuvent être expliqués par une seule théorie, mais plutôt par une combinaison de théories. Ils ont également mis en évidence le rôle essentiel joué par la structure spatiale dans la détermination de la biodiversité, quelque soit le composant de la biodiversité considéré. Enfin, cette étude souligne l'importance de prendre en compte plusieurs échelles spatiales et différents constituants de l'échelle spatiale pour toute étude relative à la diversité spécifique. Abstract The world-wide loss of biodiversity at all scales has become a matter of urgent concern, and improving our understanding of local drivers of biodiversity in natural and anthropogenic ecosystems is now crucial for conservation. The main objective of this study was to further our comprehension of the driving forces controlling biodiversity patterns in a complex and diverse ecosystem of high conservation value, wooded pastures. Spatial pattern and scale are central to several ecological theories, and it is increasingly recognized that they must be taken -into consideration when studying biodiversity patterns. However, few hypotheses developed from simulations or theoretical studies have been tested using field data, and the evolution of biodiversity patterns with different scale components remains largely unknown. We test several such hypotheses and explore spatial patterns of biodiversity in a multi-scale context and using different measures of biodiversity (species richness and composition), with field data. Data were collected using a hierarchical sampling design. We first tested the simple hypothesis that species richness, the number of species in a given area, is related to environmental heterogeneity at all scales. We decomposed environmental heterogeneity into two parts: the variability of environmental conditions and its spatial configuration. We showed that species richness generally increased with environmental heterogeneity: species richness increased with increasing number of habitat types and with decreasing spatial aggregation of those habitats. Effects occurred at all scales but the nature of the effect changed with scale, suggesting a change in underlying mechanisms. We then decomposed the spatial structure of species composition in relation to environmental variables and species traits using variation partitioning and a recently developed spatial descriptor, allowing us to capture a wide range of spatial scales. We showed that the spatial structure of plant species composition was related to topography at the coarsest scales and insolation at finer scales. The non-environmental fraction of the spatial variation in species composition had a complex relationship with several species traits, suggesting a scale-dependent link to biological processes, particularly dispersal. Finally, we tested, at different spatial scales, the relationships between different components of biodiversity: total sample species richness (gamma diversity), mean species .richness (alpha diversity), measured in nested subsamples, and differences in species composition between subsamples (beta diversity). The pairwise relationships between alpha, beta and gamma diversity did not follow the expected patterns, at least at certain scales. Our result indicated a strong scale-dependency of several relationships, and highlighted the importance of the scale ratio when studying biodiversity patterns. Thus, our results bring new insights on the spatial patterns of biodiversity and the possible mechanisms allowing species coexistence. They suggest that biodiversity patterns cannot be explained by any single theory proposed in the literature, but a combination of theories is sufficient. Spatial structure plays a crucial role for all components of biodiversity. Results emphasize the importance of considering multiple spatial scales and multiple scale components when studying species diversity.

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The objective of this work was to investigate the genotype-environment interaction in Mato Grosso State, MT. The relative importance of locations, years, sowing dates and cultivars and their interactions was analyzed from data collected in regional yield trials performed in a randomized complete block design with four replications, from 1994-1995 through 1999-2000, in nine locations and two sowing dates. Individual and pooled analyses of variance over years and locations were performed. Complementary analyses of variances partitioned MT State in two main and five smaller regions, respectively: North and South of Cuiabá; and MT-South-A (Pedra Preta area), MT-South-B (Rondonópolis and Itiquira), MT-East (Primavera do Leste and Campo Verde), MT-Central (Nova Mutum, Lucas do Rio Verde and Sorriso) and MT-Parecis (Campo Novo dos Parecis and Sapezal). Locations are relatively more important than years for yield testing soybeans in the MT State, therefore, investment should be made in increasing locations rather than years to improve experimental precision. Partitioning the MT State into regions has little impact on soybean yield testing results and, consequently, on the efficiency of the soybean breeding program in the State. Breeding genotypes with broad adaptation for the MT State is an efficient strategy for cultivar development.

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The remarkable plasticity of plant ontogeny is shaped by hormone pathways, which not only orchestrate intrinsic developmental programs, but also convey environmental inputs. Several classes of plant hormones exist, and among them auxin, brassinosteroid and gibberellin are central for the regulation of growth in general and of cell elongation in particular. Various growth phenomena can be modulated by each of the three hormones, in a sometimes synergistic fashion, suggesting physiological redundancy and/or crosstalk between the different pathways. Whether this means that they target a common and unique transcriptome module, or rather separate growth-promoting transcriptome modules, remains unclear, however. Nevertheless, while surprisingly few molecular mediators of direct crosstalk in the proper sense have been isolated, evidence is accumulating for complex cross-regulatory relations between hormone pathways at the level of transcription, as exemplified in root meristem growth. The growing number of available genome sequences from the green lineage offers first glimpses at the evolution of hormone pathways, which can aid in understanding the multiple relationships observed between these pathways in angiosperms. The available analyses suggest that auxin, gibberellin and brassinosteroid signalling arose during land plant evolution in this order, correlating with increased morphological complexity and possibly conferring increased developmental flexibility.

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PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

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Most studies of invasive species have been in highly modified, lowland environments, with comparatively little attention directed to less disturbed, high-elevation environments. However, increasing evidence indicates that plant invasions do occur in these environments, which often have high conservation value and provide important ecosystem services. Over a thousand non-native species have become established in natural areas at high elevations worldwide, and although many of these are not invasive, some may pose a considerable threat to native mountain ecosystems. Here, we discuss four main drivers that shape plant invasions into high-elevation habitats: (1) the (pre-)adaptation of non-native species to abiotic conditions, (2) natural and anthropogenic disturbances, (3) biotic resistance of the established communities, and (4) propagule pressure. We propose a comprehensive research agenda for tackling the problem of plant invasions into mountain ecosystems, including documentation of mountain invasion patterns at multiple scales, experimental studies, and an assessment of the impacts of non-native species in these systems. The threat posed to high-elevation biodiversity by invasive plant species is likely to increase because of globalization and climate change. However, the higher mountains harbor ecosystems where invasion by non-native species has scarcely begun, and where science and management have the opportunity to respond in time.

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The objective of this work was to compare phyllochron and leaf area on individual stalks of selected sugarcane (Saccharum officinarum) clones grown in a subtropical environment. A two-year field experiment was carried out in Santa Maria, RS, Brazil, during the 2007/2008 and 2008/2009 growing seasons. Three sugarcane clones were used: IAC 822045 (early), SP 711406 (median) and CB 4176 (late), in a complete randomized block design, with four replications. Expanded leaf and total leaf (tips) number were determined, and expanded leaf area was measured. The phyllochron (ºC day leaf-1) based on expanded and tip leaf number was estimated, using 10ºC as base temperature. Allometric relationships between individual area and number of expanded leaves were fitted. Phyllochron was analysed as a four-factor experiment: clone, growing season, phyllochron phase, and phyllochron type. The early clone had the greatest potential for growing in a subtropical climate because of higher leaf output and leaf area.

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The social Web environment cannot be explained without taking into account the use made by consumers of the web technologies in the field of e-commerce. Starting with a systematic background of the growing body of research on marketing and consumer behaviour on the Web; this article presents a critical review of the main contributions on this theme, integrating also the research field of consumer behaviour in the social Web environment. It concludes with some managerial guidelines for successful use of the social Web in the commercial activities and in the establishment of fruitful relationships between the consumers and the brand.

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The remarkable plasticity of their architecture allows plants to adjust growth to the environment and to overcome adverse conditions. Two examples of environmental stresses that drastically affect shoot development are imminent shade and high temperature. Plants in crowded environments and plants in elevated ambient temperature display very similar phenotypic adaptations of elongated hypocotyls in seedlings and elevated and elongated leaves at later developmental stages. The comparable growth responses to shade and high temperature are partly regulated through shared signaling pathways, of which the phytohormone auxin and the phytochrome interacting factors (PIFs) are important components. During both shade- and temperature-induced elongation growth auxin biosynthesis and signaling are upregulated in a PIF-dependent manner. In this review we will discuss recent progress in our understanding of how auxin mediates architectural adaptations to shade and high temperature.