975 resultados para Over adaptation


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With scientific consensus supporting a 4oC increase in global mean temperature over the next century and increased frequency of severe weather events, adaptation to climate change is critical. Given the dynamic and complex nature of climate change, a transdisciplinary approach toward adaptation can create an environment that supports knowledge sharing and innovation, improving existing strategies and creating new ones. The Ontario wine industry provides a case study to illustrate the benefits of this approach. We describe the formation and work of the Ontario Grape and Wine Research Network within this context, and present some preliminary results to highlight the opportunities for innovation that will drive the successful adaption of the Ontario grape and wine industry.

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Depuis la mise en place de la réforme, il y a plus de dix ans, les directions d’établissement sont tenues de trouver des solutions alternatives au redoublement, afin d’aider les élèves en difficulté à rattraper leur retard. C’est afin de répondre à cet impératif que la classe de prolongation de cycle a été mise en place dans les écoles secondaires. Des élèves en fin de 1er cycle, jugés incapables de poursuivre au cycle supérieur, y sont regroupés et pendant une année, ils bénéficient de mesures de soutien afin d’atteindre le niveau de compétence attendu (plus précisément en français en en mathématiques) pour pouvoir vivre un passage réussi au second cycle. Peu de résultats de recherches sont toutefois disponibles quant à l’efficacité de cette modalité. La présente étude vise donc à estimer l’incidence de deux modèles de prolongation de cycle (co-enseignement et avec enseignant unique), sur la motivation et l’adaptation psychosociale des élèves. Ainsi, les élèves qui expérimentent un modèle de co-enseignement demeurent en groupe fermé et sont accompagnés par trois enseignants titulaires qui se partagent la responsabilité de la quasi-totalité des composantes du programme de formation. Les élèves qui expérimentent un modèle avec enseignant unique demeurent eux aussi en groupe fermé, mais sont encadrés par une seule enseignante titulaire qui assume la responsabilité des enseignements en français et en mathématiques. Les autres matières sont enseignées par des spécialistes. Cent trente-quatre élèves au total, fréquentant trois écoles secondaires francophones montréalaises situées en milieu défavorisé, ont donc formé les groupes expérimentaux et témoins. En début et en fin d’année, les participants ont répondu à un questionnaire d’enquête mesurant l’évolution de leur motivation générale pour les apprentissages, de leur motivation spécifique aux disciplines, de leur adaptation psychosociale, de même que certaines facettes de leurs relations avec leurs pairs, leurs enseignants et leurs parents. Les résultats d’analyses de variance multivariées à mesures répétées (MANOVA) et des tests univariés subséquents permettent d’observer, chez les élèves qui ont expérimenté la prolongation de cycle en co-enseignement, une augmentation de leur sentiment de compétence général vis-à-vis l’école. De plus, leurs buts de performance-évitement et leur anxiété sociale ont diminué. Chez les élèves qui ont expérimenté la prolongation de cycle avec enseignant unique, ce même sentiment de compétence vis-à-vis l’école et celui spécifique au français ont augmenté. En revanche, ces derniers s’expriment plus négativement que leurs homologues en ce qui concerne leur intérêt général envers l’école, leur sentiment d’appartenance à leur école et leurs relations avec leurs pairs. Ces résultats indiquent donc que cette mesure a un effet mitigé sur la motivation et l’adaptation psychosociale des élèves. De plus, les quelques bénéfices perçus peuvent être la conséquence du fait de se retrouver dans un environnement scolaire moins compétitif. Cela dit, il apparaît important de préciser que les enseignants qui ont testé le modèle de co-enseignement en étaient à une première expérience. Leurs pratiques sont susceptibles de se bonifier, ce qui laisse croire que des résultats plus disparates pourraient éventuellement être observés entre ces deux modèles de prolongation. Par ailleurs, la pérennité des gains observés est inconnue. En conséquence, il conviendrait de poursuivre cette étude pour être en mesure de déterminer si ceux-ci sont durables dans le temps et afin de constater la pleine mesure de l’efficacité du modèle de prolongation de co-enseignement.

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Regional climate models are becoming increasingly popular to provide high resolution climate change information for impacts assessments to inform adaptation options. Many countries and provinces requiring these assessments are as small as 200,000 km2 in size, significantly smaller than an ideal domain needed for successful applications of one-way nested regional climate models. Therefore assessments on sub-regional scales (e.g., river basins) are generally carried out using climate change simulations performed for relatively larger regions. Here we show that the seasonal mean hydrological cycle and the day-to-day precipitation variations of a sub-region within the model domain are sensitive to the domain size, even though the large scale circulation features over the region are largely insensitive. On seasonal timescales, the relatively smaller domains intensify the hydrological cycle by increasing the net transport of moisture into the study region and thereby enhancing the precipitation and local recycling of moisture. On daily timescales, the simulations run over smaller domains produce higher number of moderate precipitation days in the sub-region relative to the corresponding larger domain simulations. An assessment of daily variations of water vapor and the vertical velocity within the sub-region indicates that the smaller domains may favor more frequent moderate uplifting and subsequent precipitation in the region. The results remained largely insensitive to the horizontal resolution of the model, indicating the robustness of the domain size influence on the regional model solutions. These domain size dependent precipitation characteristics have the potential to add one more level of uncertainty to the downscaled projections.

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Investing in global environmental and adaptation benefits in the context of agriculture and food security initiatives can play an important role in promoting sustainable intensification. This is a priority for the Global Environment Facility (GEF), created in 1992 with a mandate to serve as financial mechanism of several multilateral environmental agreements. To demonstrate the nature and extent of GEF financing, we conducted an assessment of the entire portfolio over a period of two decades (1991–2011) to identify projects with direct links to agriculture and food security. A cohort of 192 projects and programs were identified and used as a basis for analyzing trends in GEF financing. The projects and programs together accounted for a total GEF financing of US$1,086.8 million, and attracted an additional US$6,343.5 million from other sources. The value-added of GEF financing for ecosystem services and resilience in production systems was demonstrated through a diversity of interventions in the projects and programs that utilized US$810.6 million of the total financing. The interventions fall into the following four main categories in accordance with priorities of the GEF: sustainable land management (US$179.3 million), management of agrobiodiversity (US$113.4 million), sustainable fisheries and water resource management (US$379.8 million), and climate change adaptation (US$138.1 million). By aligning GEF priorities with global aspirations for sustainable intensification of production systems, the study shows that it is possible to help developing countries tackle food insecurity while generating global environmental benefits for a healthy and resilient planet.

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New Zealand is a nation of Migrants. Immigrants have played a significant role in the country’s economic growth and cultural development. With a population of four million people, New Zealand’s population is becoming increasingly culturally diverse. Almost one in five New Zealanders were born overseas, rising to one in three in its largest city, Auckland. Asians are the fastest growing ethnic group, increasing by around 140% since 1996. Indians account for 1.2% of the population (Statistics New Zealand, 2002). The Goan community in New Zealand is relatively small and its size is not formally recorded, however, anecdotally it appears to have grown to over 200 families in the Auckland area, with most arriving after 1996. For women who migrate, loneliness and isolation have been identified as the most ‘glaring’ experience and this is intensified by the loss of extended family networks when they migrate to a country where nuclear families are the norm (Leckie, 1995). The creation of new networks and maintenance of prior networks in new ways is crucial to the successful settlement and integration into a new country. This paper reports on how Goan, Indian women in Auckland, New Zealand used specific strategies to manage the adjustment to living in a new country. The findings reveal that participants used a variety of skills to settle in New Zealand such as cultivating a “can do” attitude, obtaining support and learning. These skills enabled them to move beyond their own culture and begin to take active part in New Zealand culture. However, this process was not immediate and the participants passed through a number of stages along a continuum of settlement and integration. These stages will be discussed below and situated within a body of literature.

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The impacts of climate change on nitrogen (N) in a lowland chalk stream are investigated using a dynamic modelling approach. The INCA-N model is used to simulate transient daily hydrology and water quality in the River Kennet using temperature and precipitation scenarios downscaled from the General Circulation Model (GCM) output for the period 1961-2100. The three GCMs (CGCM2, CSIRO and HadCM3) yield very different river flow regimes with the latter projecting significant periods of drought in the second half of the 21st century. Stream-water N concentrations increase over time as higher temperatures enhance N release from the soil, and lower river flows reduce the dilution capacity of the river. Particular problems are shown to occur following severe droughts when N mineralization is high and the subsequent breaking of the drought releases high nitrate loads into the river system. Possible strategies for reducing climate-driven N loads are explored using INCA-N. The measures include land use change or fertiliser reduction, reduction in atmospheric nitrate and ammonium deposition, and the introduction of water meadows or connected wetlands adjacent to the river. The most effective strategy is to change land use or reduce fertiliser use, followed by water meadow creation, and atmospheric pollution controls. Finally, a combined approach involving all three strategies is investigated and shown to reduce in-stream nitrate concentrations to those pre-1950s even under climate change. (c) 2006 Elsevier B.V. All rights reserved.

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Evolutionary theory suggests that divergent natural selection in heterogeneous environments can result in locally adapted plant genotypes. To understand local adaptation it is important to study the ecological factors responsible for divergent selection. At a continental scale, variation in climate can be important while at a local scale soil properties could also play a role. We designed an experiment aimed to disentangle the role of climate and ( abiotic and biotic) soil properties in local adaptation of two common plant species. A grass (Holcus lanatus) and a legume ( Lotus corniculatus), as well as their local soils, were reciprocally transplanted between three sites across an Atlantic-Continental gradient in Europe and grown in common gardens in either their home soil or foreign soils. Growth and reproductive traits were measured over two growing seasons. In both species, we found significant environmental and genetic effects on most of the growth and reproductive traits and a significant interaction between the two environmental effects of soil and climate. The grass species showed significant home site advantage in most of the fitness components, which indicated adaptation to climate. We found no indication that the grass was adapted to local soil conditions. The legume showed a significant home soil advantage for number of fruits only and thus a weak indication of adaptation to soil and no adaptation to climate. Our results show that the importance of climate and soil factors as drivers of local adaptation is species-dependent. This could be related to differences in interactions between plant species and soil biota.

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This paper investigates whether and to what extent a wide range of actors in the UK are adapting to climate change, and whether this is evidence of a social transition. We document evidence of over 300 examples of early adopters of adaptation practice to climate change in the UK. These examples span a range of activities from small adjustments (or coping) to building adaptive capacity, implementing actions and creating deeper systemic change in public and private organisations in a range of sectors. We find that adaptation in the UK has been dominated by government initiatives and has principally occurred in the form of research into climate change impacts. These actions within government stimulate a further set of actions at other scales in public agencies, regulatory agencies and regional government (or in the devolved administrations), though with little real evidence of climate change adaptation initiatives trickling down to local government level. The water supply and flood defence sectors, requiring significant investment in large scale infrastructure such as reservoirs and coastal defences, have invested more heavily in identifying potential impacts and adaptations. Economic sectors that are not dependent on large scale infrastructure appear to be investing far less effort and resources in preparing for climate change. We conclude that while the government-driven top-down targeted adaptation approach has generated anticipatory action at low cost, it may also have created enough niche activities to allow for diffusion of new adaptation practices in response to real or perceived climate change. These results have significant implications for how climate policy can be developed to support autonomous adaptors in the UK and other countries.

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Although the use of climate scenarios for impact assessment has grown steadily since the 1990s, uptake of such information for adaptation is lagging by nearly a decade in terms of scientific output. Nonetheless, integration of climate risk information in development planning is now a priority for donor agencies because of the need to prepare for climate change impacts across different sectors and countries. This urgency stems from concerns that progress made against Millennium Development Goals (MDGs) could be threatened by anthropogenic climate change beyond 2015. Up to this time the human signal, though detectable and growing, will be a relatively small component of climate variability and change. This implies the need for a twin-track approach: on the one hand, vulnerability assessments of social and economic strategies for coping with present climate extremes and variability, and, on the other hand, development of climate forecast tools and scenarios to evaluate sector-specific, incremental changes in risk over the next few decades. This review starts by describing the climate outlook for the next couple of decades and the implications for adaptation assessments. We then review ways in which climate risk information is already being used in adaptation assessments and evaluate the strengths and weaknesses of three groups of techniques. Next we identify knowledge gaps and opportunities for improving the production and uptake of climate risk information for the 2020s. We assert that climate change scenarios can meet some, but not all, of the needs of adaptation planning. Even then, the choice of scenario technique must be matched to the intended application, taking into account local constraints of time, resources, human capacity and supporting infrastructure. We also show that much greater attention should be given to improving and critiquing models used for climate impact assessment, as standard practice. Finally, we highlight the over-arching need for the scientific community to provide more information and guidance on adapting to the risks of climate variability and change over nearer time horizons (i.e. the 2020s). Although the focus of the review is on information provision and uptake in developing regions, it is clear that many developed countries are facing the same challenges. Copyright © 2009 Royal Meteorological Society

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It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UKMeteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is underestimated (over-estimated) over wet (dry) regions of southern Africa.

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Small propagules like pollen or fungal spores may be dispersed by the wind over distances of hundreds or thousands of kilometres,even though the median dispersal may be only a few metres. Such long-distance dispersal is a stochastic event which may be exceptionally important in shaping a population. It has been found repeatedly in field studies that subpopulations of wind-dispersed fungal pathogens virulent on cultivars with newly introduced, effective resistance genes are dominated by one or very few genotypes. The role of propagule dispersal distributions with distinct behaviour at long distances in generating this characteristic population structure was studied by computer simulation of dispersal of clonal organisms in a heterogeneous environment with fields of unselective and selective hosts. Power-law distributions generated founder events in which new, virulent genotypes rapidly colonized fields of resistant crop varieties and subsequently dominated the pathogen population on both selective and unselective varieties, in agreement with data on rust and powdery mildew fungi. An exponential dispersal function, with extremely rare dispersal over long distances, resulted in slower colonization of resistant varieties by virulent pathogens or even no colonization if the distance between susceptible source and resistant target fields was sufficiently large. The founder events resulting from long-distance dispersal were highly stochastic and exact quantitative prediction of genotype frequencies will therefore always be difficult.

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Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs. Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.

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This article considers ideas about the suitability of experimental, non-naturalist, narrative forms in theatre and television, through the example of a 1965 BBC2 adaptation of J. B. Priestley's 1939 play Johnson over Jordan. Using both textual analysis of the programme and research into the BBC production documentation, this essay explains how the circumstances and conditions of 1960s television adaptation and the star casting of Sir Ralph Richardson transformed Priestley's stage play. The TV adaptation achieved cosmic effects on an intimate scale, through inference and the imaginative integration of the studio space with dubbed sound.

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Many institutions across sub-Saharan Africa (SSA) and many funding agencies that support them are currently engaged in initiatives that are targeted towards adapting rainfed agriculture to climate change. This does, however, present some very real and complex research and policy challenges. Given to date the generally low impact of agricultural research across SSA on improving the welfare of rainfed farmers under current climatic conditions, a comprehensive strategy is required if the considerably more complex challenge of adapting agriculture to future climate change is to bear fruit. In articulating such a strategy, it is useful to consider the criteria by which current successful initiatives should be judged.

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We present a framework for prioritizing adaptation approaches at a range of timeframes. The framework is illustrated by four case studies from developing countries, each with associated characterization of uncertainty. Two cases on near-term adaptation planning in Sri Lanka and on stakeholder scenario exercises in East Africa show how the relative utility of capacity vs. impact approaches to adaptation planning differ with level of uncertainty and associated lead time. An additional two cases demonstrate that it is possible to identify uncertainties that are relevant to decision making in specific timeframes and circumstances. The case on coffee in Latin America identifies altitudinal thresholds at which incremental vs. transformative adaptation pathways are robust options. The final case uses three crop–climate simulation studies to demonstrate how uncertainty can be characterized at different time horizons to discriminate where robust adaptation options are possible. We find that impact approaches, which use predictive models, are increasingly useful over longer lead times and at higher levels of greenhouse gas emissions. We also find that extreme events are important in determining predictability across a broad range of timescales. The results demonstrate the potential for robust knowledge and actions in the face of uncertainty.