47 resultados para large geographical area
Resumo:
We compare the characteristics of synthetic European droughts generated by the HiGEM1 coupled climate model run with present day atmospheric composition with observed drought events extracted from the CRU TS3 data set. The results demonstrate consistency in both the rate of drought occurrence and the spatiotemporal structure of the events. Estimates of the probability density functions for event area, duration and severity are shown to be similar with confidence > 90%. Encouragingly, HiGEM is shown to replicate the extreme tails of the observed distributions and thus the most damaging European drought events. The soil moisture state is shown to play an important role in drought development. Once a large-scale drought has been initiated it is found to be 50% more likely to continue if the local soil moisture is below the 40th percentile. In response to increased concentrations of atmospheric CO2, the modelled droughts are found to increase in duration, area and severity. The drought response can be largely attributed to temperature driven changes in relative humidity. 1 HiGEM is based on the latest climate configuration of the Met Office Hadley Centre Unified Model (HadGEM1) with the horizontal resolution increased to 1.25 x 0.83 degrees in longitude and latitude in the atmosphere and 1/3 x 1/3 degrees in the ocean.
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Bushmeat is a large but largely invisible contributor to the economies of west and central African countries. Yet the trade is currently unsustainable. Hunting is reducing wildlife populations, driving more vulnerable species to local and regional extinction, and threatening biodiversity. This paper uses a commodity chain approach to explore the bushmeat trade and to demonstrate why an interdisciplinary approach is required if the trade is to be sustainable in the future.
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Suburban areas continue to grow rapidly and are potentially an important land-use category for anthropogenic carbon-dioxide (CO2) emissions. Here eddy covariance techniques are used to obtain ecosystem-scale measurements of CO2 fluxes (FC) from a suburban area of Baltimore, Maryland, USA (2002–2006). These are among the first multi-year measurements of FC in a suburban area. The study area is characterized by low population density (1500 inhabitants km−2) and abundant vegetation (67.4% vegetation land-cover). FC is correlated with photosynthetic active radiation (PAR), soil temperature, and wind direction. Missing hourly FC is gap-filled using empirical relations between FC, PAR, and soil temperature. Diurnal patterns show net CO2 emissions to the atmosphere during winter and net CO2 uptake by the surface during summer daytime hours (summer daily total is −1.25 g C m−2 d−1). Despite the large amount of vegetation the suburban area is a net CO2 source of 361 g C m−2 y−1 on average.
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During each of the late Pleistocene glacial–interglacial transitions, atmospheric carbon dioxide concentrations rose by almost 100 ppm. The sources of this carbon are unclear, and efforts to identify them are hampered by uncertainties in the magnitude of carbon reservoirs and fluxes under glacial conditions. Here we use oxygen isotope measurements from air trapped in ice cores and ocean carbon-cycle modelling to estimate terrestrial and oceanic gross primary productivity during the Last Glacial Maximum. We find that the rate of gross terrestrial primary production during the Last Glacial Maximum was about 40±10 Pg C yr−1, half that of the pre-industrial Holocene. Despite the low levels of photosynthesis, we estimate that the late glacial terrestrial biosphere contained only 330 Pg less carbon than pre-industrial levels. We infer that the area covered by carbon-rich but unproductive biomes such as tundra and cold steppes was significantly larger during the Last Glacial Maximum, consistent with palaeoecological data. Our data also indicate the presence of an inert carbon pool of 2,300 Pg C, about 700 Pg larger than the inert carbon locked in permafrost today. We suggest that the disappearance of this carbon pool at the end of the Last Glacial Maximum may have contributed to the deglacial rise in atmospheric carbon dioxide concentrations.
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Eddy covariance measurements of the turbulent sensible heat, latent heat and carbon dioxide fluxes for 12 months (2011–2012) are reported for the first time for a suburban area in the UK. The results from Swindon are comparable to suburban studies of similar surface cover elsewhere but reveal large seasonal variability. Energy partitioning favours turbulent sensible heat during summer (midday Bowen ratio 1.4–1.6) and latent heat in winter (0.05–0.7). A significant proportion of energy is stored (and released) by the urban fabric and the estimated anthropogenic heat flux is small but non-negligible (0.5–0.9 MJ m−2 day−1). The sensible heat flux is negative at night and for much of winter daytimes, reflecting the suburban nature of the site (44% vegetation) and relatively low built fraction (16%). Latent heat fluxes appear to be water limited during a dry spring in both 2011 and 2012, when the response of the surface to moisture availability can be seen on a daily timescale. Energy and other factors are more relevant controls at other times; at night the wind speed is important. On average, surface conductance follows a smooth, asymmetrical diurnal course peaking at around 6–9 mm s−1, but values are larger and highly variable in wet conditions. The combination of natural (vegetative) and anthropogenic (emission) processes is most evident in the temporal variation of the carbon flux: significant photosynthetic uptake is seen during summer, whilst traffic and building emissions explain peak release in winter (9.5 g C m−2 day−1). The area is a net source of CO2 annually. Analysis by wind direction highlights the role of urban vegetation in promoting evapotranspiration and offsetting CO2 emissions, especially when contrasted against peak traffic emissions from sectors with more roads. Given the extent of suburban land use, these results have important implications for understanding urban energy, water and carbon dynamics.
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So-called ‘radical’ and ‘critical’ pedagogy seems to be everywhere these days on the landscapes of geographical teaching praxis and theory. Part of the remit of radical/critical pedagogy involves a de-centring of the traditional ‘banking’ method of pedagogical praxis. Yet, how do we challenge this ‘banking’ model of knowledge transmission in both a large-class setting and around the topic of commodity geographies where the banking model of information transfer still holds sway? This paper presents a theoretically and pedagogically driven argument, as well as a series of practical teaching ‘techniques’ and tools—mind-mapping and group work—designed to promote ‘deep learning’ and a progressive political potential in a first-year large-scale geography course centred around lectures on the Geographies of Consumption and Material Culture. Here students are not only asked to place themselves within and without the academic materials and other media but are urged to make intimate connections between themselves and their own consumptive acts and the commodity networks in which they are enmeshed. Thus, perhaps pedagogy needs to be emplaced firmly within the realms of research practice rather than as simply the transference of research findings.
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This article critically explores the nature and purpose of relationships and inter-dependencies between stakeholders in the context of a parastatal chromite mining company in the Betsiboka Region of Northern Madagascar. An examination of the institutional arrangements at the interface between the mining company and local communities identified power hierarchies and dependencies in the context of a dominant paternalistic environment. The interactions, inter alia, limited social cohesion and intensified the fragility and weakness of community representation, which was further influenced by ethnic hierarchies between the varied community groups; namely, indigenous communities and migrants to the area from different ethnic groups. Moreover, dependencies and nepotism, which may exist at all institutional levels, can create civil society stakeholder representatives who are unrepresentative of the society they are intended to represent. Similarly, a lack of horizontal and vertical trust and reciprocity inherent in Malagasy society engenders a culture of low expectations regarding transparency and accountability, which further catalyses a cycle of nepotism and elite rent-seeking behaviour. On the other hand, leaders retain power with minimal vertical delegation or decentralisation of authority among levels of government and limit opportunities to benefit the elite, perpetuating rent-seeking behaviour within the privileged minority. Within the union movement, pluralism and the associated politicisation of individual unions restricts solidarity, which impacts on the movement’s capacity to act as a cohesive body of opinion and opposition. Nevertheless, the unions’ drive to improve their social capital has increased expectations of transparency and accountability, resulting in demands for greater engagement in decision-making processes.
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We explore the large spatial variation in the relationship between population density and burned area, using continental-scale Geographically Weighted Regression (GWR) based on 13 years of satellite-derived burned area maps from the global fire emissions database (GFED) and the human population density from the gridded population of the world (GPW 2005). Significant relationships are observed over 51.5% of the global land area, and the area affected varies from continent to continent: population density has a significant impact on fire over most of Asia and Africa but is important in explaining fire over < 22% of Europe and Australia. Increasing population density is associated with both increased and decreased in fire. The nature of the relationship depends on land-use: increasing population density is associated with increased burned are in rangelands but with decreased burned area in croplands. Overall, the relationship between population density and burned area is non-monotonic: burned area initially increases with population density and then decreases when population density exceeds a threshold. These thresholds vary regionally. Our study contributes to improved understanding of how human activities relate to burned area, and should contribute to a better estimate of atmospheric emissions from biomass burning.
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Sensible heat fluxes (QH) are determined using scintillometry and eddy covariance over a suburban area. Two large aperture scintillometers provide spatially integrated fluxes across path lengths of 2.8 km and 5.5 km over Swindon, UK. The shorter scintillometer path spans newly built residential areas and has an approximate source area of 2-4 km2, whilst the long path extends from the rural outskirts to the town centre and has a source area of around 5-10 km2. These large-scale heat fluxes are compared with local-scale eddy covariance measurements. Clear seasonal trends are revealed by the long duration of this dataset and variability in monthly QH is related to the meteorological conditions. At shorter time scales the response of QH to solar radiation often gives rise to close agreement between the measurements, but during times of rapidly changing cloud cover spatial differences in the net radiation (Q*) coincide with greater differences between heat fluxes. For clear days QH lags Q*, thus the ratio of QH to Q* increases throughout the day. In summer the observed energy partitioning is related to the vegetation fraction through use of a footprint model. The results demonstrate the value of scintillometry for integrating surface heterogeneity and offer improved understanding of the influence of anthropogenic materials on surface-atmosphere interactions.
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Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed.
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Reintroductions are used worldwide to mitigate biodiversity loss. One prominent case is a charismatic raptor of conservation concern, the Red Kite Milvus milvus. This species has been reintroduced across the UK over the last 25 years following its near extinction after centuries of persecution. The species was not expected to recolonize urban areas; its historical association with human settlements is attributed to scavenging on human waste and refuse, a resource now greatly reduced on the streets of modern Western cities. However, the species has become a common day-time visitor to a large conurbation centred on the town of Reading, southern England, approximately 20 km from the first English reintroduction site. Given a near-absence of breeding and roost sites, we investigated foraging opportunities and habitat associations that might explain use by Red Kites of this urban area. Surveys of discarded human foods and road-kill suggested that these could support at most 13−29 kites/day. Face-to-face surveys of a cross-section of residents revealed that 4.5% (equivalent to 4349 households) provided supplementary food for kites. Using estimates of per-household resource provision from another study, we calculated that this level is potentially sufficient to provision 142−320 kites, a substantial proportion of the total estimated to visit the conurbation each day (between 140 and 440). Road transects found positive associations between Red Kites and residential areas. We therefore suggest that the decision made by thousands of individuals to provide supplementary food for Red Kites is the primary factor explaining their day-time abundance in this urban area.
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Advances in our understanding of the large-scale electric and magnetic fields in the coupled magnetosphere-ionosphere system are reviewed. The literature appearing in the period January 1991–June 1993 is sorted into 8 general areas of study. The phenomenon of substorms receives the most attention in this literature, with the location of onset being the single most discussed issue. However, if the magnetic topology in substorm phases was widely debated, less attention was paid to the relationship of convection to the substorm cycle. A significantly new consensus view of substorm expansion and recovery phases emerged, which was termed the ‘Kiruna Conjecture’ after the conference at which it gained widespread acceptance. The second largest area of interest was dayside transient events, both near the magnetopause and the ionosphere. It became apparent that these phenomena include at least two classes of events, probably due to transient reconnection bursts and sudden solar wind dynamic pressure changes. The contribution of both types of event to convection is controversial. The realisation that induction effects decouple electric fields in the magnetosphere and ionosphere, on time scales shorter than several substorm cycles, calls for broadening of the range of measurement techniques in both the ionosphere and at the magnetopause. Several new techniques were introduced including ionospheric observations which yield reconnection rate as a function of time. The magnetospheric and ionospheric behaviour due to various quasi-steady interplanetary conditions was studied using magnetic cloud events. For northward IMF conditions, reverse convection in the polar cap was found to be predominantly a summer hemisphere phenomenon and even for extremely rare prolonged southward IMF conditions, the magnetosphere was observed to oscillate through various substorm cycles rather than forming a steady-state convection bay.
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A statistical-dynamical downscaling method is used to estimate future changes of wind energy output (Eout) of a benchmark wind turbine across Europe at the regional scale. With this aim, 22 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble are considered. The downscaling method uses circulation weather types and regional climate modelling with the COSMO-CLM model. Future projections are computed for two time periods (2021–2060 and 2061–2100) following two scenarios (RCP4.5 and RCP8.5). The CMIP5 ensemble mean response reveals a more likely than not increase of mean annual Eout over Northern and Central Europe and a likely decrease over Southern Europe. There is some uncertainty with respect to the magnitude and the sign of the changes. Higher robustness in future changes is observed for specific seasons. Except from the Mediterranean area, an ensemble mean increase of Eout is simulated for winter and a decreasing for the summer season, resulting in a strong increase of the intra-annual variability for most of Europe. The latter is, in particular, probable during the second half of the 21st century under the RCP8.5 scenario. In general, signals are stronger for 2061–2100 compared to 2021–2060 and for RCP8.5 compared to RCP4.5. Regarding changes of the inter-annual variability of Eout for Central Europe, the future projections strongly vary between individual models and also between future periods and scenarios within single models. This study showed for an ensemble of 22 CMIP5 models that changes in the wind energy potentials over Europe may take place in future decades. However, due to the uncertainties detected in this research, further investigations with multi-model ensembles are needed to provide a better quantification and understanding of the future changes.
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A truly variance-minimizing filter is introduced and its per for mance is demonstrated with the Korteweg– DeV ries (KdV) equation and with a multilayer quasigeostrophic model of the ocean area around South Africa. It is recalled that Kalman-like filters are not variance minimizing for nonlinear model dynamics and that four - dimensional variational data assimilation (4DV AR)-like methods relying on per fect model dynamics have dif- ficulty with providing error estimates. The new method does not have these drawbacks. In fact, it combines advantages from both methods in that it does provide error estimates while automatically having balanced states after analysis, without extra computations. It is based on ensemble or Monte Carlo integrations to simulate the probability density of the model evolution. When obser vations are available, the so-called importance resampling algorithm is applied. From Bayes’ s theorem it follows that each ensemble member receives a new weight dependent on its ‘ ‘distance’ ’ t o the obser vations. Because the weights are strongly var ying, a resampling of the ensemble is necessar y. This resampling is done such that members with high weights are duplicated according to their weights, while low-weight members are largely ignored. In passing, it is noted that data assimilation is not an inverse problem by nature, although it can be for mulated that way . Also, it is shown that the posterior variance can be larger than the prior if the usual Gaussian framework is set aside. However , i n the examples presented here, the entropy of the probability densities is decreasing. The application to the ocean area around South Africa, gover ned by strongly nonlinear dynamics, shows that the method is working satisfactorily . The strong and weak points of the method are discussed and possible improvements are proposed.
Resumo:
Understanding how wildlife responds to road and traffic is essential for effective conservation. Yet, not many studies have evaluated how roads influence wildlife in protected areas, particularly within the large iconic African National Parks where tourism is mainly based on sightings from motorized vehicles with the consequent development and intense use of roads. To reduce this knowledge gap, we studied the behavioral response and local spatial distribution of impala Aepyceros melampus along the heterogeneous (with variation in road surface type and traffic intensity) road-network of Kruger National Park (KNP, South Africa). We surveyed different types of roads (paved and unpaved) recording the occurrence of flight responses among sighted impala and describing their local spatial distribution (in relation to the roads). We observed relatively few flight responses (19.5% of 118 observations), suggesting impalas could be partly habituated to vehicles in KNP. In addition, impala local distribution is apparently unaffected by unpaved roads, yet animals seem to avoid the close proximity of paved roads. Overall, our results suggest a negative, albeit small, effect of traffic intensity, and of presence of pavement on roads on the behavior of impala at KNP. Future studies would be necessary to understand how roads influence other species, but our results show that even within a protected area that has been well-visited for a long time, wildlife can still be affected by roads and traffic. This result has ecological (e.g., changes in spatial distribution of fauna) and management implications (e.g., challenges of facilitating wildlife sightings while minimizing disturbance) for protected areas where touristic activities are largely based on driving.