951 resultados para Climate-Vegetation Relationships
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Doutoramento em Engenharia Florestal - Instituto Superior de Agronomia - UL
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The importance of repair, maintenance, minor alteration, and addition (RMAA) works is increasing in many built societies. When the volume of RMAA works increases, the occurrence of RMAA accidents also increases. Safety of RMAA works deserves more attention; however, research in this important topic remains limited. Safety climate is considered a key factor that influences safety performance. The present study aims to determine the relationships between safety climate and safety performance of RMAA works, thereby offering recommendations on improving RMAA safety. Questionnaires were dispatched to private property management companies, maintenance sections of quasi-government developers and their subcontractors, RMAA sections of general contractors, small RMAA contractors, building services contractors and trade unions in Hong Kong. In total, data from 396 questionnaires were collected from RMAA workers. The sample was divided into two equal-sized sub-samples. On the first sub-sample SEM was used to test the model, which was validated on the second sub-sample. The model revealed a significant negative relationship between RMAA safety climate and incidence of self-reported near misses and injuries, and significant positive relationships between RMAA safety climate and safety participation and safety compliance respectively. Higher RMAA safety climate was positively associated with a lower incidence of self-reported near misses and injuries and higher levels of safety participation and safety compliance.
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We explored whether teams develop shared perceptions regarding the quantity and quality of information and the extent of participation in decision making provided in an environment of continuous change. In addition, we examined whether change climate strength moderated relationships between change climate level and team outcomes. We examined relationships among aggregated change information and change participation and aggregated team outcomes, including two role stressors (i.e., role ambiguity and role overload) and two indicators of well-being (i.e., quality of worklife and distress). Questionnaires were distributed in an Australian law enforcement agency and data were used from 178 teams. Structural equation modelling analyses, controlling for a marker variable, were conducted to examine the main effects of aggregated change information and aggregated change participation on aggregated team outcomes. Results provided support for a model that included method effects due to a marker variable. In this model, change information climate was significantly negatively associated with role ambiguity, role overload, and distress, and significantly positively associated with quality of worklife. Change participation climate was significantly positively associated with quality of worklife. Change climate strength did not moderate relationships among change climate level and team outcomes.
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Changes in global climate and land use affect important prolesses from evapotranspiration and groundwater recharge to carbon storage and biochemical cycling. Near surface soil moisture is pivotal to understand the consequences of these changes. However, the dynamic interactions between vegetation and soil moisture remain largely unresolved because it is difficult to monitor and quantify subsurface hydrologic fluxes at relevant scales. Here we use electrical resistivity to monitor the influence of climate and vegetation on root-zone moisture, bridging the gap between remotely-sensed and in-situ point measurements. Our research quantifies large seasonal differences in root-zone moisture dynamics for a forest-grassland ecotone. We found large differences in effective rooting depth and moisture distributions for the two vegetation types. Our results highlight the likely impacts of land transformations on groun ter recharge, streamflow, and land-atmosphere exchanges.
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A team’s climate for innovation has been shown to be important for innovation in management and work teams. This article investigates the relationship of team climate with project team innovation and performance in research and development organizations. It is argued that the relationship between team climate and innovation will be stronger for research teams than development teams as research teams have greater scope for creating novel and innovative ideas. A sample of 193 scientists and technologists in 20 research teams and 18 development teams were measured on their team’s climate for innovation, team performance, and six indicators of innovation. Research and development teams showed similar ratings for team climate and for measures of innovation. However, the relationships between team climate and individual and team innovation were stronger for research teams than development teams. These findings are significant for fostering innovativeness and innovation in knowledge work teams.
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There is an increasing need to understand what makes vegetation at some locations more sensitive to climate change than others. For savanna rangelands, this requires building knowledge of how forage production in different land types will respond to climate change, and identifying how location-specific land type characteristics, climate and land management control the magnitude and direction of its responses to change. Here, a simulation analysis is used to explore how forage production in 14 land types of the north-eastern Australian rangelands responds to three climate change scenarios of +3A degrees C, +17% rainfall; +2A degrees C, -7% rainfall; and +3A degrees C, -46% rainfall. Our results demonstrate that the controls on forage production responses are complex, with functional characteristics of land types interacting to determine the magnitude and direction of change. Forage production may increase by up to 60% or decrease by up to 90% in response to the extreme scenarios of change. The magnitude of these responses is dependent on whether forage production is water or nitrogen (N) limited, and how climate changes influence these limiting conditions. Forage production responds most to changes in temperature and moisture availability in land types that are water-limited, and shows the least amount of change when growth is restricted by N availability. The fertilisation effects of doubled atmospheric CO2 were found to offset declines in forage production under 2A degrees C warming and a 7% reduction in rainfall. However, rising tree densities and declining land condition are shown to reduce potential opportunities from increases in forage production and raise the sensitivity of pastures to climate-induced water stress. Knowledge of these interactions can be applied in engaging with stakeholders to identify adaptation options.
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Postglacial climate changes and vegetation responses were studied using a combination of biological and physical indicators preserved in lake sediments. Low-frequency trends, high-frequency events and rapid shifts in temperature and moisture balance were probed using pollen-based quantitative temperature reconstructions and oxygen-isotopes from authigenic carbonate and aquatic cellulose, respectively. Pollen and plant macrofossils were employed to shed light on the presence and response rates of plant populations in response to climate changes, particularly focusing on common boreal and temperate tree species. Additional geochemical and isotopic tracers facilitated the interpretation of pollen- and oxygen-isotope data. The results show that the common boreal trees were present in the Baltic region (~55°N) during the Lateglacial, which contrasts with the traditional view of species refuge locations in the south-European peninsulas during the glacial/interglacial cycles. The findings of this work are in agreement with recent paleoecological and genetic evidence suggesting that scattered populations of tree species persisted at higher latitudes, and that these taxa were likely limited to boreal trees. Moreover, the results demonstrate that stepwise changes in plant communities took place in concert with major climate fluctuations of the glacial/interglacial transition. Postglacial climate trends in northern Europe were characterized by rise, maxima and fall in temperatures and related changes in moisture balance. Following the deglaciation of the Northern Hemisphere and the early Holocene reorganization of the ice-ocean-atmosphere system, the long-term temperature trends followed gradually decreasing summer insolation. The early Holocene (~11,700-8000 cal yr BP) was overall cool, moist and oceanic, although the earliest Holocene effective humidity may have been low particularly in the eastern part of northern Europe. The gradual warming trend was interrupted by a cold event ~8200 cal yr BP. The maximum temperatures, ~1.5-3.0°C above modern values, were attained ~8000-4000 cal yr BP. This mid-Holocene peak warmth was coupled with low lake levels, low effective humidity and summertime drought. The late Holocene (~4000 cal yr BP-present) was characterized by gradually decreasing temperatures, higher lake levels and higher effective humidity. Moreover, the gradual trends of the late Holocene were probably superimposed by higher-frequency variability. The spatial variability of the Holocene temperature and moisture balance patterns were tentatively attributed to the differing heat capacities of continents and oceans, changes in atmospheric circulation modes and position of sites and subregions with respect to large water bodies and topographic barriers. The combination of physical and biological proxy archives is a pivotal aspect of this work, because non-climatic factors, such as postglacial migration, disturbances and competitive interactions, can influence reshuffling of vegetation and hence, pollen-based climate reconstructions. The oxygen-isotope records and other physical proxies presented in this work manifest that postglacial climate changes were the main driver of the establishment and expansion of temperate and boreal tree populations, and hence, large-scale and long-term vegetation patterns were in dynamic equilibrium with climate. A notable exception to this pattern may be the postglacial invasion of Norway spruce and the related suppression of mid-Holocene temperate forest. This salient step in north-European vegetation history, the development of the modern boreal ecosystem, cannot be unambiguously explained by current evidence of postglacial climate changes. The results of this work highlight that plant populations, including long-lived trees, may be able to respond strikingly rapidly to changes in climate. Moreover, interannual and seasonal variation and extreme events can exert an important influence on vegetation reshuffling. Importantly, the studies imply that the presence of diffuse refuge populations or local stands among the prevailing vegetation may have provided the means for extraordinarily rapid vegetation responses. Hence, if scattered populations are not provided and tree populations are to migrate long distances, their capacity to keep up with predicted rates of future climate change may be lower than previously thought.
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Ilmasto vaikuttaa ekologisiin prosesseihin eri tasoilla. Suuren mittakaavan ilmastoprosessit, yhdessä ilmakehän ja valtamerien kanssa, säätelevät paikallisia sääilmiöitä suurilla alueilla (mantereista pallopuoliskoihin). Tämä väistöskirja pyrkii selittämään kuinka suuren mittakaavan ilmasto on vaikuttanut tiettyihin ekologisiin prosesseihin pohjoisella havumetsäalueella. Valitut prosessit olivat puiden vuosilustojen kasvu, metsäpalojen esiintyminen ja vuoristomäntykovakuoriaisen aiheuttamat puukuolemat. Suuren mittakaavan ilmaston löydettiin vaikuttaneen näiden prosessien esiintymistiheyteen, kestoon ja levinneisyyteen keskeisten sään muuttujien välityksellä hyvin laajoilla alueilla. Tutkituilla prosesseilla oli vahva yhteys laajan mittakaavan ilmastoon. Yhteys on kuitenkin ollut hyvin dynaaminen ja muuttunut 1900-luvulla ilmastonmuutoksen aiheuttaessa muutoksia suuren mittakaavan ja alueellisten ilmastoprosessien välisiin sisäisiin suhteisiin.
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We make an assessment of the impact of projected climate change on forest ecosystems in India. This assessment is based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the dynamic global vegetation model IBIS for A2 and B2 scenarios. According to the model projections, 39% of forest grids are likely to undergo vegetation type change under the A2 scenario and 34% under the B2 scenario by the end of this century. However, in many forest dominant states such as Chattisgarh, Karnataka and Andhra Pradesh up to 73%, 67% and 62% of forested grids are projected to undergo change. Net Primary Productivity (NPP) is projected to increase by 68.8% and 51.2% under the A2 and B2 scenarios, respectively, and soil organic carbon (SOC) by 37.5% for A2 and 30.2% for B2 scenario. Based on the dynamic global vegetation modeling, we present a forest vulnerability index for India which is based on the observed datasets of forest density, forest biodiversity as well as model predicted vegetation type shift estimates for forested grids. The vulnerability index suggests that upper Himalayas, northern and central parts of Western Ghats and parts of central India are most vulnerable to projected impacts of climate change, while Northeastern forests are more resilient. Thus our study points to the need for developing and implementing adaptation strategies to reduce vulnerability of forests to projected climate change.
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Quantifying distributional behavior of extreme events is crucial in hydrologic designs. Intensity Duration Frequency (IDF) relationships are used extensively in engineering especially in urban hydrology, to obtain return level of extreme rainfall event for a specified return period and duration. Major sources of uncertainty in the IDF relationships are due to insufficient quantity and quality of data leading to parameter uncertainty due to the distribution fitted to the data and uncertainty as a result of using multiple GCMs. It is important to study these uncertainties and propagate them to future for accurate assessment of return levels for future. The objective of this study is to quantify the uncertainties arising from parameters of the distribution fitted to data and the multiple GCM models using Bayesian approach. Posterior distribution of parameters is obtained from Bayes rule and the parameters are transformed to obtain return levels for a specified return period. Markov Chain Monte Carlo (MCMC) method using Metropolis Hastings algorithm is used to obtain the posterior distribution of parameters. Twenty six CMIP5 GCMs along with four RCP scenarios are considered for studying the effects of climate change and to obtain projected IDF relationships for the case study of Bangalore city in India. GCM uncertainty due to the use of multiple GCMs is treated using Reliability Ensemble Averaging (REA) technique along with the parameter uncertainty. Scale invariance theory is employed for obtaining short duration return levels from daily data. It is observed that the uncertainty in short duration rainfall return levels is high when compared to the longer durations. Further it is observed that parameter uncertainty is large compared to the model uncertainty. (C) 2015 Elsevier Ltd. All rights reserved.
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Despite high vulnerability, the impact of climate change on Himalayan ecosystem has not been properly investigated, primarily due to the inadequacy of observed data and the complex topography. In this study, we mapped the current vegetation distribution in Kashmir Himalayas from NOAA AVHRR and projected it under A1B SRES, RCP-4.5 and RCP-8.5 climate scenarios using the vegetation dynamics model-IBIS at a spatial resolution of 0.5A degrees. The distribution of vegetation under the changing climate was simulated for the 21st century. Climate change projections from the PRECIS experiment using the HADRM3 model, for the Kashmir region, were validated using the observed climate data from two observatories. Both the observed as well as the projected climate data showed statistically significant trends. IBIS was validated for Kashmir Himalayas by comparing the simulated vegetation distribution with the observed distribution. The baseline simulated scenario of vegetation (1960-1990), showed 87.15 % agreement with the observed vegetation distribution, thereby increasing the credibility of the projected vegetation distribution under the changing climate over the region. According to the model projections, grasslands and tropical deciduous forests in the region would be severely affected while as savannah, shrubland, temperate evergreen broadleaf forest, boreal evergreen forest and mixed forest types would colonize the area currently under the cold desert/rock/ice land cover types. The model predicted that a substantial area of land, presently under the permanent snow and ice cover, would disappear by the end of the century which might severely impact stream flows, agriculture productivity and biodiversity in the region.
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A normalized difference vegetation index (NDVI) has been produced and archived on a 1° latitude by 1° longitude grid between 55°S and 75°N. The many sources of data errors in the NDVI include cloud contamination, scan angle biases, changes in solar zenith angle, and sensor degradation. Week-to-week variability, primarily caused by cloud contamination and scan angle biases, can be minimized by temporally filtering the data. Orbital drift and sensor degradation introduces interannual variability into the dataset. These trends make the usefulness of a long-term climatology uncertain and limit the usefulness of the NDVI. Elimination of these problems should produce an index that can be used for climate monitoring.