979 resultados para River spatial complexity
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Interspecific competition, life history traits, environmental heterogeneity and spatial structure as well as disturbance are known to impact the successful dispersal strategies in metacommunities. However, studies on the direction of impact of those factors on dispersal have yielded contradictory results and often considered only few competing dispersal strategies at the same time. We used a unifying modeling approach to contrast the combined effects of species traits (adult survival, specialization), environmental heterogeneity and structure (spatial autocorrelation, habitat availability) and disturbance on the selected, maintained and coexisting dispersal strategies in heterogeneous metacommunities. Using a negative exponential dispersal kernel, we allowed for variation of both species dispersal distance and dispersal rate. We showed that strong disturbance promotes species with high dispersal abilities, while low local adult survival and habitat availability select against them. Spatial autocorrelation favors species with higher dispersal ability when adult survival and disturbance rate are low, and selects against them in the opposite situation. Interestingly, several dispersal strategies coexist when disturbance and adult survival act in opposition, as for example when strong disturbance regime favors species with high dispersal abilities while low adult survival selects species with low dispersal. Our results unify apparently contradictory previous results and demonstrate that spatial structure, disturbance and adult survival determine the success and diversity of coexisting dispersal strategies in competing metacommunities.
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A report by the Iowa Department of Natural Resources on how the health of Iowa's River and Stream are today.
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Pollination syndromes involve convergent evolution towards phenotypes composed of specific scents, colours or floral morphologies that attract or restrict pollinator access to reward. How these traits might influence the distributions of plant species in interaction with pollinators has rarely been investigated. We sampled 870 vegetation plots in the western Swiss Alps and classified the plant species into seven blossom types according to their floral morphology (wind, disk, funnel, tube, bilabiate, head or brush). We investigated the environmental features of plots with functional diversity (FD) lower than expected by chance alone to detect potential pollination filtering and related the proportions of the seven blossom types to a combination of environmental descriptors. From these results, we inferred the potential effect of the pollinator on the spatial distribution of plant species. The vegetation plots with significantly lower FD of blossom types than expected by chance were found at higher altitudes, and the proportions of blossom types were strongly patterned along the same gradient. These results support a biotic filtering effect on plant species assemblages through pollination: disk blossoms became dominant at higher altitudes, resulting in a lower FD. In harsh conditions at high altitudes, pollinators usually decrease in activity, and the openness of the disk blossom grants access to any available pollinator. Inversely, bilabiate blossoms, which are mostly pollinated by bees, were more abundant at lower elevations, which are characterised by greater abundance and diversity of bees. Generalisation through openness of the blossom could be advantageous at high elevations, while specialisation could be a successful alternative strategy at lower elevations. The approach used in this study is purely correlative, and further investigations should be conducted to infer the nature of the causal relationship between plant and pollinator distributions.
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This monthly report from the Iowa Department of Transportation is about the water quality management of Iowa's rivers, streams and lakes.
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Introduction: Pain and beliefs have an influence on the patient's course in rehabilitation, pain causes fears and fears influence pain perception. The aim of this study is to understand pain and beliefs evolutions during rehabilitation taking into account of bio-psycho-social complexity.Patients and methods: 631 consecutive patients admitted in rehabilitation after a musculoskeletal traumatism were included and assessed at admission and at discharge. Pain was measured by VAS (Visual Analogical Scale), bio-psycho-social complexity by Intermed scale, and beliefs by judgement on Lickert scales. Four kinds of beliefs were evaluated: fear of a severe origin of pain, fear of movement, fear of pain and feeling of distress (loss of control). The association between the changes in pain and beliefs during the hospitalization was assessed by linear regressions.Results: After adjustment for gender, age, education and native language, patients with a decrease in pain during rehabilitation have higher probability of decreasing their fears. For the distress feeling, this relationship is weaker among bio-psycho-socially complex patients (odds-ratio 1.22 for each decreasing of 10mm/100 VAS) than among non-complex patients (OR 1.47). Patients with a pain decrease of 30% or more during hospitalization have higher probability of seeing their fears decrease, this relationship being stronger in complex patient for fear of a severe origin of pain.Discussion: The relationships between evolution of pain and beliefs move in the same direction. The higher a patient feels pain, the less they could be able to modify their dysfunctional beliefs. When the pain diminishes of 30% or more, the probability to challenge the beliefs is increased. The prognostic with regard to feeling of distress and fear of a severe origin of pain, is worse among bio-psycho-socially complex patients.
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In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.
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This paper reviews the role of alluvial soils in vegetated gravelly river braid plains. When considering decadal time scales of river evolution, we argue that it becomes vital to consider soil development as an emergent property of the developing ecosystem. Soil processes have been relatively overlooked in accounts of the interactions between braided river processes and vegetation, although soils have been observed on vegetated fluvial landforms. We hypothesise that soil development plays a major role in the transition (speed and pathway) from a fresh sediment deposit to a vegetated soil-covered landform. Disturbance (erosion and/or deposition), vertical sediment structure (process history), vegetation succession, biological activity and water table fluctuation are seen as the main controls on early alluvial soil evolution. Erosion and deposition processes may not only act as soil disturbing agents, but also as suppliers of ecosystem resources, because of their role in delivering and changing access (e.g. through avulsion) to fluxes of water, fine sediments and organic matter. In turn, the associated initial ecosystem may influence further fluvial landform development, such as through the trapping of fine-grained sediments (e.g. sand) by the engineering action of vegetation and the deposit stabilisation by the developing above and belowground biomass. This may create a strong feedback between geomorphological processes, vegetation succession and soil evolution which we summarise in a conceptual model. We illustrate this model by an example from the Allondon River (CH) and identify the research questions that follow.
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Background: Previous magnetic resonance imaging (MRI) studies in young patients with bipolar disorder indicated the presence of grey matter concentration changes as well as microstructural alterations in white matter in various neocortical areas and the corpus callosum. Whether these structural changes are also present in elderly patients with bipolar disorder with long-lasting clinical evolution remains unclear. Methods: We performed a prospective MRI study of consecutive elderly, euthymic patients with bipolar disorder and healthy, elderly controls. We conducted a voxel-based morphometry (VBM) analysis and a tract-based spatial statistics (TBSS) analysis to assess fractional anisotropy and longitudinal, radial and mean diffusivity derived by diffusion tensor imaging (DTI). Results: We included 19 patients with bipolar disorder and 47 controls in our study. Fractional anisotropy was the most sensitive DTI marker and decreased significantly in the ventral part of the corpus callosum in patients with bipolar disorder. Longitudinal, radial and mean diffusivity showed no significant between-group differences. Grey matter concentration was reduced in patients with bipolar disorder in the right anterior insula, head of the caudate nucleus, nucleus accumbens, ventral putamen and frontal orbital cortex. Conversely, there was no grey matter concentration or fractional anisotropy increase in any brain region in patients with bipolar disorder compared with controls. Limitations: The major limitation of our study is the small number of patients with bipolar disorder. Conclusion: Our data document the concomitant presence of grey matter concentration decreases in the anterior limbic areas and the reduced fibre tract coherence in the corpus callosum of elderly patients with long-lasting bipolar disorder.
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Around 11.5 * 106 m3 of rock detached from the eastern slope of the Santa Cruz valley (San Juan province, Argentina) in the first fortnight of January 2005. The rockslide?debris avalanche blocked the course, resulting in the development of a lake with maximum length of around 3.5 km. The increase in the inflow rate from 47,000?74,000 m3/d between April and October to 304,000 m3/d between late October and the first fortnight of November, accelerated the growing rate of the lake. On 12 November 2005 the dam failed, releasing 24.6 * 106 m3 of water. The resulting outburst flood caused damages mainly on infrastructure, and affected the facilities of a hydropower dam which was under construction 250 km downstream from the source area. In this work we describe causes and consequences of the natural dam formation and failure, and we dynamically model the 2005 rockslide?debris avalanche with DAN3D. Additionally, as a volume ~ 24 * 106 m3of rocks still remain unstable in the slope, we use the results of the back analysis to forecast the formation of a future natural dam. We analyzed two potential scenarios: a partial slope failure of 6.5 * 106 m3 and a worst case where all the unstable volume remaining in the slope fails. The spreading of those potential events shows that a new blockage of the Santa Cruz River is likely to occur. According to their modeled morphometry and the contributing watershed upstream the blockage area, as the one of 2005, the dams would also be unstable. This study shows the importance of back and forward analysis that can be carried out to obtain critical information for land use planning, hazards mitigation, and emergency management.
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Business organisations are excellent representations of what in physics and mathematics are designated "chaotic" systems. Because a culture of innovation will be vital for organisational survival in the 21st century, the present paper proposes that viewing organisations in terms of "complexity theory" may assist leaders in fine-tuning managerial philosophies that provide orderly management emphasizing stability within a culture of organised chaos, for it is on the "boundary of chaos" that the greatest creativity occurs. It is argued that 21st century companies, as chaotic social systems, will no longer be effectively managed by rigid objectives (MBO) nor by instructions (MBI). Their capacity for self-organisation will be derived essentially from how their members accept a shared set of values or principles for action (MBV). Complexity theory deals with systems that show complex structures in time or space, often hiding simple deterministic rules. This theory holds that once these rules are found, it is possible to make effective predictions and even to control the apparent complexity. The state of chaos that self-organises, thanks to the appearance of the "strange attractor", is the ideal basis for creativity and innovation in the company. In this self-organised state of chaos, members are not confined to narrow roles, and gradually develop their capacity for differentiation and relationships, growing continuously toward their maximum potential contribution to the efficiency of the organisation. In this way, values act as organisers or "attractors" of disorder, which in the theory of chaos are equations represented by unusually regular geometric configurations that predict the long-term behaviour of complex systems. In business organisations (as in all kinds of social systems) the starting principles end up as the final principles in the long term. An attractor is a model representation of the behavioral results of a system. The attractor is not a force of attraction or a goal-oriented presence in the system; it simply depicts where the system is headed based on its rules of motion. Thus, in a culture that cultivates or shares values of autonomy, responsibility, independence, innovation, creativity, and proaction, the risk of short-term chaos is mitigated by an overall long-term sense of direction. A more suitable approach to manage the internal and external complexities that organisations are currently confronting is to alter their dominant culture under the principles of MBV.
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This monthly report from the Iowa Department of Transportation is about the water quality management of Iowa's rivers, streams and lakes.
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What explains the spatial distribution of wages across US counties? I find that two of the most important factors are spatial technology diffusion and externalities due to the aggregate scale of production. One empirical finding supporting the importance of spatial technology diffusion is that average wages in a county decrease with the average level of schooling in neighboring counties when employment in the county and average wages in neighboring counties are held constant. All empirical results are obtained using anovel instrument for (endogenous) employment at the county-leveland take into account other factors (e.g. productivity-differencesacross states, climate) that may determine wages.
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Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.