14 resultados para mind change complexity

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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P>1. Proliferative kidney disease (PKD) is a disease of salmonid fish caused by the endoparasitic myxozoan, Tetracapsuloides bryosalmonae, which uses freshwater bryozoans as primary hosts. Clinical PKD is characterised by a temperature-dependent proliferative and inflammatory response to parasite stages in the kidney.;2. Evidence that PKD is an emerging disease includes outbreaks in new regions, declines in Swiss brown trout populations and the adoption of expensive practices by fish farms to reduce heavy losses. Disease-related mortality in wild fish populations is almost certainly underestimated because of e.g. oversight, scavenging by wild animals, misdiagnosis and fish stocking.;3. PKD prevalences are spatially and temporally variable, range from 0 to 90-100% and are typically highest in juvenile fish.;4. Laboratory and field studies demonstrate that (i) increasing temperatures enhance disease prevalence, severity and distribution and PKD-related mortality; (ii) eutrophication may promote outbreaks. Both bryozoans and T. bryosalmonae stages in bryozoans undergo temperature- and nutrient-driven proliferation.;5. Tetracapsuloides bryosalmonae is likely to achieve persistent infection of highly clonal bryozoan hosts through vertical transmission, low virulence and host condition-dependent cycling between covert and overt infections. Exploitation of fish hosts entails massive proliferation and spore production by stages that escape the immune response. Many aspects of the parasite's life cycle remain obscure. If infectious stages are produced in all hosts then the complex life cycle includes multiple transmission routes.;6. Patterns of disease outbreaks suggest that background, subclinical infections exist under normal environmental conditions. When conditions change, outbreaks may then occur in regions where infection was hitherto unsuspected.;7. Environmental change is likely to cause PKD outbreaks in more northerly regions as warmer temperatures promote disease development, enhance bryozoan biomass and increase spore production, but may also reduce the geographical range of this unique multihost-parasite system. Coevolutionary dynamics resulting from host-parasite interactions that maximise fitness in previous environments may pose problems for sustainability, particularly in view of extensive declines in salmonid populations and degradation of many freshwater habitats.

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Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species’ occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species’ occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change.

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Like other mountain areas in the world, the Hindu Kush-Himalayan (HKH) region is particularly vulnerable to climate change. Ongoing climate change processes are projected to have a high impact on the HKH region, and accelerated warming has been reported in the Himalayas. These climate change impacts will be superimposed on a variety of other environmental and social stresses, adding to the complexity of the issues. The sustainable use of natural resources is crucial to the long-term stability of the fragile mountain ecosystems in the HKH and to sustain the socio-ecological resilience that forms the basis of sustainable livelihoods in the region. In order to be prepared for these challenges, it is important to take stock of previous research. The ‘People and Resource Dynamics Project’ (PARDYP), implemented by International Centre for Integrated Mountain Development (ICIMOD), provides a variety of participatory options for sustainable land management in the HKH region. The PARDYD project was a research for development project that operated in five middle mountain watersheds across the HKH – two in Nepal and one each in China, India, and Pakistan. The project ran from 1996 to 2006 and focused on addressing the marginalisation of mountain farmers, the use and availability of water, issues relating to land and forest degradation and declining soil fertility, the speed of regeneration of degraded land, and the ability of the natural environment to support the growing needs of the region’s increasing population. A key learning from the project was that the opinion of land users is crucial to the acceptance (and, therefore, successful application) of new technologies and approaches. A major challenge at the end of every project is to promote knowledge sharing and encourage the cross-fertilization of ideas (e.g., in the case of PARDYP, with other middle mountain inhabitants and practitioners in the region) and to share lessons learned with a wider audience. This paper will highlight how the PARDYP findings, including ways of addressing soil fertility and water scarcity, have been mainstreamed in the HKH region through capacity building (international, regional, and national training courses), networking, and the provision of backstopping services. In addition, in view of the challenges in watershed management in the HKH connected to environmental change, the lessons learned from the PARDYP are now being used by ICMOD to define and package climate change proof technology options to address climate change adaptation.

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The conference on Global Change and the World’s Mountains held in Perth, Scotland, in 2010 offered a unique opportunity to analyze the state and progress of mountain research and its contribution to sustainable mountain development, as well as to reflect on required reorientations of research agendas. In this paper we provide the results of a three-step assessment of the research presented by 450 researchers from around the world. First, we determined the state of the art of mountain research and categorized it based on the analytical structure of the Global Land Project (GLP 2005). Second, we identified emerging themes for future research. Finally, we assessed the contribution of mountain research to sustainable development along the lines of the Grand Challenges in Global Sustainability Research (International Council for Science 2010). Analysis revealed that despite the growing recognition of the importance of more integrative research (inter- and transdisciplinary), the research community gathered in Perth still focuses on environmental drivers of change and on interactions within ecological systems. Only a small percentage of current research seeks to enhance understanding of social systems and of interactions between social and ecological systems. From the ecological systems perspective, a greater effort is needed to disentangle and assess different drivers of change and to investigate impacts on the rendering of ecosystem services. From the social systems perspective, significant shortcomings remain in understanding the characteristics, trends, and impacts of human movements to, within, and out of mountain areas as a form of global change. Likewise, sociocultural drivers affecting collective behavior as well as incentive systems devised by policy and decision makers are little understood and require more in-depth investigation. Both the complexity of coupled social– ecological systems and incomplete data sets hinder integrated systems research. Increased understanding of linkages and feedbacks between social and ecological systems will help to identify nonlinearities and thresholds (tipping points) in both system types. This presupposes effective collaboration between ecological and social sciences. Reflections on the Grand Challenges in Sustainability Research put forth by the International Council for Science (2010) reveal the need to intensify research on effective responses and innovations. This will help to achieve sustainable development in mountain regions while maintaining the core competence of mountain research in forecasting and observation.

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PURPOSE: Venlafaxine has shown benefit in the treatment of depression and pain. Worldwide data are extensively lacking investigating the outcome of chronic pain patients with depressive symptoms treated by venlafaxine in the primary care setting. This observational study aimed to elucidate the efficacy of venlafaxine and its prescription by Swiss primary care physicians and psychiatrists in patients with chronic pain and depressive symptomatology. SUBJECTS AND METHODS: We studied 505 patients with depressive symptoms suffering from chronic pain in a prospective naturalistic Swiss community based observational trial with venlafaxine in primary care. These patients have been treated with venlafaxine by 122 physicians, namely psychiatrists, general practitioners, and internists. RESULTS: On average, patients were treated with 143+/-75 mg (0-450 mg) venlafaxine daily for a follow-up of three months. Venlafaxine proved to be beneficial in the treatment of both depressive symptoms and chronic pain. DISCUSSION: Although side effects were absent in most patients, physicians might have frequently omitted satisfactory response rate of depression by underdosing venlafaxine. Our results reflect the complexity in the treatment of chronic pain in patients with depressive symptoms in primary care. CONCLUSION: Further randomized dose-finding studies are needed to learn more about the appropriate dosage in treating depression and comorbid pain with venlafaxine.

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By means of fixed-links modeling, the present study identified different processes of visual short-term memory (VSTM) functioning and investigated how these processes are related to intelligence. We conducted an experiment where the participants were presented with a color change detection task. Task complexity was manipulated through varying the number of presented stimuli (set size). We collected hit rate and reaction time (RT) as indicators for the amount of information retained in VSTM and speed of VSTM scanning, respectively. Due to the impurity of these measures, however, the variability in hit rate and RT was assumed to consist not only of genuine variance due to individual differences in VSTM retention and VSTM scanning but also of other, non-experimental portions of variance. Therefore, we identified two qualitatively different types of components for both hit rate and RT: (1) non-experimental components representing processes that remained constant irrespective of set size and (2) experimental components reflecting processes that increased as a function of set size. For RT, intelligence was negatively associated with the non-experimental components, but was unrelated to the experimental components assumed to represent variability in VSTM scanning speed. This finding indicates that individual differences in basic processing speed, rather than in speed of VSTM scanning, differentiates between high- and low-intelligent individuals. For hit rate, the experimental component constituting individual differences in VSTM retention was positively related to intelligence. The non-experimental components of hit rate, representing variability in basal processes, however, were not associated with intelligence. By decomposing VSTM functioning into non-experimental and experimental components, significant associations with intelligence were revealed that otherwise might have been obscured.

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Infectious diseases result from the interactions of host, pathogens, and, in the case of vector-borne diseases, also vectors. The interactions involve physiological and ecological mechanisms and they have evolved under a given set of environmental conditions. Environmental change, therefore, will alter host-pathogen-vector interactions and, consequently, the distribution, intensity, and dynamics of infectious diseases. Here, we review how climate change may impact infectious diseases of aquatic and terrestrial wildlife. Climate change can have direct impacts on distribution, life cycle, and physiological status of hosts, pathogens and vectors. While a change in either host, pathogen or vector does not necessarily translate into an alteration of the disease, it is the impact of climate change on the interactions between the disease components which is particularly critical for altered disease risks. Finally, climate factors can modulate disease through modifying the ecological networks host-pathogen-vector systems are belonging to, and climate change can combine with other environmental stressors to induce cumulative effects on infectious diseases. Overall, the influence of climate change on infectious diseases involves different mechanisms, it can be modulated by phenotypic acclimation and/or genotypic adaptation, it depends on the ecological context of the host-pathogen-vector interactions, and it can be modulated by impacts of other stressors. As a consequence of this complexity, non-linear responses of disease systems under climate change are to be expected. To improve predictions on climate change impacts on infectious disease, we suggest that more emphasis should be given to the integration of biomedical and ecological research for studying both the physiological and ecological mechanisms which mediate climate change impacts on disease, and to the development of harmonized methods and approaches to obtain more comparable results, as this would support the discrimination of case-specific versus general mechanisms

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Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

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This paper summarizes the results of an intercomparison project with Earth System Models of Intermediate Complexity (EMICs) undertaken in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). The focus is on long-term climate projections designed to 1) quantify the climate change commitment of different radiative forcing trajectories and 2) explore the extent to which climate change is reversible on human time scales. All commitment simulations follow the four representative concentration pathways (RCPs) and their extensions to year 2300. Most EMICs simulate substantial surface air temperature and thermosteric sea level rise commitment following stabilization of the atmospheric composition at year-2300 levels. The meridional overturning circulation (MOC) is weakened temporarily and recovers to near-preindustrial values in most models for RCPs 2.6-6.0. The MOC weakening is more persistent for RCP8.5. Elimination of anthropogenic CO2 emissions after 2300 results in slowly decreasing atmospheric CO2 concentrations. At year 3000 atmospheric CO2 is still at more than half its year-2300 level in all EMICs for RCPs 4.5-8.5. Surface air temperature remains constant or decreases slightly and thermosteric sea level rise continues for centuries after elimination of CO2 emissions in all EMICs. Restoration of atmospheric CO2 from RCP to preindustrial levels over 100-1000 years requires large artificial removal of CO2 from the atmosphere and does not result in the simultaneous return to preindustrial climate conditions, as surface air temperature and sea level response exhibit a substantial time lag relative to atmospheric CO2.

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Cocoa-based small-scale agriculture is the most important source of income for most farming families in the region of Alto Beni in the sub-humid foothills of the Andes. Cocoa is grown in cultivation systems of varying ecological complexity. The plantations are highly susceptible to climate change impacts. Local cocoa producers mention heat waves, droughts, floods and plant diseases as the main impacts affecting plants and working conditions, and they associate these impacts with global climate change. From a sustainable regional development point of view, cocoa farms need to become more resilient in order to cope with the climate change related effects that are putting cocoa-based livelihoods at risk. This study assesses agroecosystem resilience under three different cocoa cultivation systems (successional agroforestry, simple agroforestry and common practice monocultures). In a first step, farmers’ perceptions of climate change impacts were assessed and eight indicators of agroecological resilience were derived in a transdisciplinary process (focus groups and workshop) based on farmers’ and scientists’ knowledge. These indicators (soil organic matter, depth of Ah horizon, soil bulk density, tree species diversity, crop varieties diversity, ant species diversity, cocoa yields and infestation of cocoa trees with Moniliophthora perniciosa) were then surveyed on 15 cocoa farms and compared for the three different cultivation systems. Parts of the socio-economic aspects of resilience were covered by evaluating the role of cocoa cooperatives and organic certification in transitioning to more resilient cocoa farms (interviews with 15 cocoa farmers combined with five expert interviews). Agroecosystem resilience was higher under the two agroforestry systems than under common practice monoculture, especially under successional agroforestry. Both agroforestry systems achieved higher cocoa yields than common practice monoculture due to agroforestry farmers’ enhanced knowledge regarding cocoa cultivation. Knowledge sharing was promoted by local organizations facilitating organic certification. These organizations were thus found to enhance the social process of farmers’ integration into cooperatives and their reorientation toward organic principles and diversified agroforestry.

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This is the second part of a two-part paper which offers a new approach to the valuation of ecosystem goods and services. In the first part a simple pre-industrial model was introduced to show how the interdependencies between the three subsystems, society, economy and nature, influence values, and how values change over time. In this second part the assumption of perfect foresight is dropped. I argue that due to novelty and complexity ex ante unpredictable change occurs within the three subsystems society, economy and nature. Again the simple pre-industrial model, which was introduced in part 1, serves as a simple paradigm to show how unpredictable novel change limits the possibility to derive accurate estimates of values.

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Climate change affects increasingly the management of natural resources and has diverse impacts of environmental, social and economic nature. To take this complexity into account, climate change adaptation policies consider the principle of sustainable development. Sustainability is an integrative concept which should insure a long-term and multi-sectoral response to climate change. But the question appears if sustainable development is only retained at the conceptual level or effectively implemented in practice. This paper pursues this question by comparing three projects addressing natural hazard in Swiss mountains. The aim is to investigate how sustainable development is perceived by involved stakeholders and implemented in practice. Two dimensions are thus taken into account: the type of actors participating in these projects and their preferences and interests. The first dimension thus analyzes if diverse actors representing the environmental, economic and social arenas are integrated; the second dimension investigates if different interests and preferences in the sense of sustainability were incorporated in the design and implementation of climate change adaptation. Data were gathered through a standardized survey among all actors involved in the three projects. Preliminary results show that sustainability receives diverse weight and interest in the different cases.

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CONTEXT Complex steroid disorders such as P450 oxidoreductase deficiency or apparent cortisone reductase deficiency may be recognized by steroid profiling using chromatographic mass spectrometric methods. These methods are highly specific and sensitive, and provide a complete spectrum of steroid metabolites in a single measurement of one sample which makes them superior to immunoassays. The steroid metabolome during the fetal-neonatal transition is characterized by a) the metabolites of the fetal-placental unit at birth, b) the fetal adrenal androgens until its involution 3-6 months postnatally, and c) the steroid metabolites produced by the developing endocrine organs. All these developmental events change the steroid metabolome in an age- and sex-dependent manner during the first year of life. OBJECTIVE The aim of this study was to provide normative values for the urinary steroid metabolome of healthy newborns at short time intervals in the first year of life. METHODS We conducted a prospective, longitudinal study to measure 67 urinary steroid metabolites in 21 male and 22 female term healthy newborn infants at 13 time-points from week 1 to week 49 of life. Urine samples were collected from newborn infants before discharge from hospital and from healthy infants at home. Steroid metabolites were measured by gas chromatography-mass spectrometry (GC-MS) and steroid concentrations corrected for urinary creatinine excretion were calculated. RESULTS 61 steroids showed age and 15 steroids sex specificity. Highest urinary steroid concentrations were found in both sexes for progesterone derivatives, in particular 20α-DH-5α-DH-progesterone, and for highly polar 6α-hydroxylated glucocorticoids. The steroids peaked at week 3 and decreased by ∼80% at week 25 in both sexes. The decline of progestins, androgens and estrogens was more pronounced than of glucocorticoids whereas the excretion of corticosterone and its metabolites and of mineralocorticoids remained constant during the first year of life. CONCLUSION The urinary steroid profile changes dramatically during the first year of life and correlates with the physiologic developmental changes during the fetal-neonatal transition. Thus detailed normative data during this time period permit the use of steroid profiling as a powerful diagnostic tool.

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A frequent suggestion to increase individuals' willingness to take action on climate change and to support relevant policies is to highlight its proximal consequences, that is, those that are close in space and time. But previous studies that have tested this proximizing approach have not revealed the expected positive effects on individual action and support for addressing climate change. We present three lines of psychological reasoning that provide compelling arguments as to why highlighting proximal impacts of climate change might not be as effective a way to increase individual mitigation and adaptation efforts as is often assumed. Our contextualization of the proximizing approach within established psychological research suggests that, depending on the particular theoretical perspective one takes on this issue, and on specific individual characteristics suggested by these perspectives, proximizing can bring about the intended positive effects, can have no (visible) effect or can even backfire. Thus, the effects of proximizing are much more complex than is commonly assumed. Revealing this complexity contributes to a refined theoretical understanding of the role that psychological distance plays in the context of climate change and opens up further avenues for future research and for interventions.