997 resultados para plant optimization
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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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Community-level patterns of functional traits relate to community assembly and ecosystem functioning. By modelling the changes of different indices describing such patterns - trait means, extremes and diversity in communities - as a function of abiotic gradients, we could understand their drivers and build projections of the impact of global change on the functional components of biodiversity. We used five plant functional traits (vegetative height, specific leaf area, leaf dry matter content, leaf nitrogen content and seed mass) and non-woody vegetation plots to model several indices depicting community-level patterns of functional traits from a set of abiotic environmental variables (topographic, climatic and edaphic) over contrasting environmental conditions in a mountainous landscape. We performed a variation partitioning analysis to assess the relative importance of these variables for predicting patterns of functional traits in communities, and projected the best models under several climate change scenarios to examine future potential changes in vegetation functional properties. Not all indices of trait patterns within communities could be modelled with the same level of accuracy: the models for mean and extreme values of functional traits provided substantially better predictive accuracy than the models calibrated for diversity indices. Topographic and climatic factors were more important predictors of functional trait patterns within communities than edaphic predictors. Overall, model projections forecast an increase in mean vegetation height and in mean specific leaf area following climate warming. This trend was important at mid elevation particularly between 1000 and 2000 m asl. With this study we showed that topographic, climatic and edaphic variables can successfully model descriptors of community-level patterns of plant functional traits such as mean and extreme trait values. However, which factors determine the diversity of functional traits in plant communities remains unclear and requires more investigations.
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We evaluate the performance of different optimization techniques developed in the context of optical flow computation with different variational models. In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we de- velop the use of efficient multilevel schemes for computing the optical flow. More precisely, we evaluate the performance of a standard unidirectional mul- tilevel algorithm - called multiresolution optimization (MR/OPT), to a bidrec- tional multilevel algorithm - called full multigrid optimization (FMG/OPT). The FMG/OPT algorithm treats the coarse grid correction as an optimiza- tion search direction and eventually scales it using a line search. Experimental results on different image sequences using four models of optical flow com- putation show that the FMG/OPT algorithm outperforms both the TN and MR/OPT algorithms in terms of the computational work and the quality of the optical flow estimation.
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1. Accumulating evidence indicates that plant resistance against above-ground herbivores can be affected by the presence of arbuscular mycorrhizal fungi (AMF) in association with the host plant. Little is known, however, about how AMF composition can influence herbivore choice to feed on a particular plant. 2. Unravelling the preference-performance hypothesis in a multitrophic context is needed to expand our knowledge of complex multitrophic interactions in natural systems. If given mycorrhizal fungal genotypes increase attractiveness for a herbivore (reduced plant resistance), then the benefits of increased unpalatability provided by the mycorrhizal fungi (increased plant resistance) might be outweighed by the increased herbivore recruitment. 3. This was addressed by designing three experiments to test the effects of different AMF genotypes, inoculated either alone or in combination, to measure intraspecific AMF effects on plant resistance and insect herbivore preference. Using strawberry (Fragaria vesca L.) plants that were colonised by eight different combinations of Rhizophagus irregularis isolates, we measured effects on plant growth, insect growth and survival, as well as feeding preferences of a generalist herbivore caterpillar (Spodoptera littoralis Boisduval). 4. Overall, it was found that: (i) AMF influenced plant resistance in an AMF genotype-specific manner; (ii) some AMF inoculations decreased insect performance; (iii) insects preferentially chose to feed more on leaves originating from non-mycorrhizal plants; but also that (iv) in a whole plant bioassay, insects preferentially chose the biggest plant, regardless of their mycorrhizal status. 5. Therefore, AMF-mediated trade-offs between growth and resistance against herbivores have been shown. Such trade-offs, particularly driven by plant attractiveness to herbivores, buffer the positive effects of the mycorrhizal symbiosis on enhanced plant growth.
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Nitrogen supply and plant population are basic parameters for cereal-legume intercropping. In order to study plant population and nitrogen fertilizer effects on yield and yield efficiency of maize-bean intercropping, a field experiment was established. Three bean plant populations and three nitrogen levels were used. Maize dry matter accumulation decreased with increases in bean plant population. Competitive effect of intercrop beans on maize yields was high at higher plant populations, being decreased by nitrogen fertilizer; application of 50 kg ha-1 N was very efficient in increasing maize cob yield. Intercropping significantly decreased harvest index of beans in all plant population and nitrogen fertilizer situations. The efficiency of intercropping, compared to sole cropping, was evidenced by the values obtained for Land Equivalent Ratio (LER) for biomass, cob and pod yields that increased with increases in bean plant populations and nitrogen fertilizer levels.
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The objective of this study was to evaluate the efficiency of spatial statistical analysis in the selection of genotypes in a plant breeding program and, particularly, to demonstrate the benefits of the approach when experimental observations are not spatially independent. The basic material of this study was a yield trial of soybean lines, with five check varieties (of fixed effect) and 110 test lines (of random effects), in an augmented block design. The spatial analysis used a random field linear model (RFML), with a covariance function estimated from the residuals of the analysis considering independent errors. Results showed a residual autocorrelation of significant magnitude and extension (range), which allowed a better discrimination among genotypes (increase of the power of statistical tests, reduction in the standard errors of estimates and predictors, and a greater amplitude of predictor values) when the spatial analysis was applied. Furthermore, the spatial analysis led to a different ranking of the genetic materials, in comparison with the non-spatial analysis, and a selection less influenced by local variation effects was obtained.
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In Illinois and Iowa, the author finds that plants with approximately 750 employees have suffered the highest strike-frequency rate. Why at this size? Among other explanations, it is posited that in significantly smaller plants labor-management relations can be personalized-and tensions reduced-while in appreciably larger plants sophistication in dealing with disputes may, of necessity, have been developed. C. Fred Eisele is a graduate teaching assistant at the University of Iowa's College of Business Administration.
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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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Blowing and drifting of snow is a major concern for transportation efficiency and road safety in regions where their development is common. One common way to mitigate snow drift on roadways is to install plastic snow fences. Correct design of snow fences is critical for road safety and maintaining the roads open during winter in the US Midwest and other states affected by large snow events during the winter season and to maintain costs related to accumulation of snow on the roads and repair of roads to minimum levels. Of critical importance for road safety is the protection against snow drifting in regions with narrow rights of way, where standard fences cannot be deployed at the recommended distance from the road. Designing snow fences requires sound engineering judgment and a thorough evaluation of the potential for snow blowing and drifting at the construction site. The evaluation includes site-specific design parameters typically obtained with semi-empirical relations characterizing the local transport conditions. Among the critical parameters involved in fence design and assessment of their post-construction efficiency is the quantification of the snow accumulation at fence sites. The present study proposes a joint experimental and numerical approach to monitor snow deposits around snow fences, quantitatively estimate snow deposits in the field, asses the efficiency and improve the design of snow fences. Snow deposit profiles were mapped using GPS based real-time kinematic surveys (RTK) conducted at the monitored field site during and after snow storms. The monitored site allowed testing different snow fence designs under close to identical conditions over four winter seasons. The study also discusses the detailed monitoring system and analysis of weather forecast and meteorological conditions at the monitored sites. A main goal of the present study was to assess the performance of lightweight plastic snow fences with a lower porosity than the typical 50% porosity used in standard designs of such fences. The field data collected during the first winter was used to identify the best design for snow fences with a porosity of 50%. Flow fields obtained from numerical simulations showed that the fence design that worked the best during the first winter induced the formation of an elongated area of small velocity magnitude close to the ground. This information was used to identify other candidates for optimum design of fences with a lower porosity. Two of the designs with a fence porosity of 30% that were found to perform well based on results of numerical simulations were tested in the field during the second winter along with the best performing design for fences with a porosity of 50%. Field data showed that the length of the snow deposit away from the fence was reduced by about 30% for the two proposed lower-porosity (30%) fence designs compared to the best design identified for fences with a porosity of 50%. Moreover, one of the lower-porosity designs tested in the field showed no significant snow deposition within the bottom gap region beneath the fence. Thus, a major outcome of this study is to recommend using plastic snow fences with a porosity of 30%. It is expected that this lower-porosity design will continue to work well for even more severe snow events or for successive snow events occurring during the same winter. The approach advocated in the present study allowed making general recommendations for optimizing the design of lower-porosity plastic snow fences. This approach can be extended to improve the design of other types of snow fences. Some preliminary work for living snow fences is also discussed. Another major contribution of this study is to propose, develop protocols and test a novel technique based on close range photogrammetry (CRP) to quantify the snow deposits trapped snow fences. As image data can be acquired continuously, the time evolution of the volume of snow retained by a snow fence during a storm or during a whole winter season can, in principle, be obtained. Moreover, CRP is a non-intrusive method that eliminates the need to perform man-made measurements during the storms, which are difficult and sometimes dangerous to perform. Presently, there is lots of empiricism in the design of snow fences due to lack of data on fence storage capacity on how snow deposits change with the fence design and snow storm characteristics and in the estimation of the main parameters used by the state DOTs to design snow fences at a given site. The availability of such information from CRP measurements should provide critical data for the evaluation of the performance of a certain snow fence design that is tested by the IDOT. As part of the present study, the novel CRP method is tested at several sites. The present study also discusses some attempts and preliminary work to determine the snow relocation coefficient which is one of the main variables that has to be estimated by IDOT engineers when using the standard snow fence design software (Snow Drift Profiler, Tabler, 2006). Our analysis showed that standard empirical formulas did not produce reasonable values when applied at the Iowa test sites monitored as part of the present study and that simple methods to estimate this variable are not reliable. The present study makes recommendations for the development of a new methodology based on Large Scale Particle Image Velocimetry that can directly measure the snow drift fluxes and the amount of snow relocated by the fence.
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Agreed-upon procedures report on the Villisca Municipal Power Plant for the period January 1, 2014 through December 31, 2014
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The objective of this work was to evaluate the response of rangpur lime (Citrus limonia) to arbuscular mycorrhiza (Glomus intraradices), under P levels ranging from low to excessive. Plants were grown in three levels of soluble P (25, 200 and 1,000 mg kg-1), either inoculated with Glomus intraradices or left noninoculated, evaluated at 30, 60, 90, 120 and 150 days after transplanting (DAT). Total dry weight, shoot P concentration and specific P uptake by roots increased in mycorrhizal plants with the doses of 25 and 200 mg kg-1 P at 90 DAT. With 1,000 mg kg-1 P, mycorrhizal plants had a transient growth depression at 90 and 120 DAT, and nonmycorrhizal effects on P uptake at any harvesting period. Root colonization and total external mycelium correlated positively with shoot P concentration and total dry weight at the two lowest P levels. Although the highest P level decreased root colonization, it did not affect total external mycelium to the same extent. As a result, a P availability imbalance affected negatively the mycorrhizal symbiosis and, consequently, the plant growth.
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The objective of this work was to compare the relative efficiency of initial selection and genetic parameter estimation, using augmented blocks design (ABD), augmented blocks twice replicated design (DABD) and group of randomised block design experiments with common treatments (ERBCT), by simulations, considering fixed effect model and mixed model with regular treatment effects as random. For the simulations, eight different conditions (scenarios) were considered. From the 600 simulations in each scenario, the mean percentage selection coincidence, the Pearsons´s correlation estimates between adjusted means for the fixed effects model, and the heritability estimates for the mixed model were evaluated. DABD and ERBCT were very similar in their comparisons and slightly superior to ABD. Considering the initial stages of selection in a plant breeding program, ABD is a good alternative for selecting superior genotypes, although none of the designs had been effective to estimate heritability in all the different scenarios evaluated.
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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.
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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.