998 resultados para forest futures


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Anticipating the future is increasingly being seen as a useful way to align, direct and improve current organizational strategy. Several such 'future studies' have been produced which envision various construction industry scenarios which result from technological and socio-economic trends and influences. Thirteen construction-related future studies are critically reviewed. Most studies fail to address the complexities and uncertainties of both the present and the future, and fail to explore the connections between global, local, construction-specific and more widespread factors. The methodological approaches used in these studies do not generate any significantly different advice or recommendations for the industry than those emerging from the much larger canon of non-future oriented construction research. As such, these reports are less about the future than the present. If future studies are to make a worthwhile contribution to construction, it is critical that they develop our appreciation of the practical ability of stakeholders to influence some aspects of the future and not others, and an awareness of the competing agendas and the relative benefits and disadvantages of specific futures within the construction sector. Only then can future studies provide insights and help in preparing for the opportunities and threats the future may bring.

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As Terabyte datasets become the norm, the focus has shifted away from our ability to produce and store ever larger amounts of data, onto its utilization. It is becoming increasingly difficult to gain meaningful insights into the data produced. Also many forms of the data we are currently producing cannot easily fit into traditional visualization methods. This paper presents a new and novel visualization technique based on the concept of a Data Forest. Our Data Forest has been designed to be used with vir tual reality (VR) as its presentation method. VR is a natural medium for investigating large datasets. Our approach can easily be adapted to be used in a variety of different ways, from a stand alone single user environment to large multi-user collaborative environments. A test application is presented using multi-dimensional data to demonstrate the concepts involved.

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As we increase our ability to produce and store ever larger amounts of data, it is becoming increasingly difficult to understand what the data is trying to tell us. Not all the data we are currently producing can easily fit into traditional visualization methods. This paper presents a new and novel visualization technique based on the concept of a Data Forest. Our Data Forest has been developed to be utilised by virtual reality (VR) systems. VR is a natural information medium. This approach can easily be adapted to be used in collaborative environments. A test application has been developed to demonstrate the concepts involved and a collaborative version tested.

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Current forest growth models and yield tables are almost exclusively based on data from mature trees, reducing their applicability to young and developing stands. To address this gap, young European beech, sessile oak, Scots pine and Norway spruce trees approximately 0 to 10 years old were destructively sampled in a range of naturally regenerated forest stands in Central Europe. Diameter at base and height were first measured in situ for up to 175 individuals per species. Subsequently, the trees were excavated and dry biomass of foliage, branches, stems and roots was measured. Allometric relations were then used to calculate biomass allocation coefficients (BAC) and growth efficiency (GE) patterns in young trees. We found large differences in BAC and GE between broadleaves and conifers, but also between species within these categories. Both BAC and GE are strongly age-specific in young trees, their rapidly changing values reflecting different growth strategies in the earliest stages of growth. We show that linear relationships describing biomass allocation in older trees are not applicable in young trees. To accurately predict forest biomass and carbon stocks, forest growth models need to include species and age specific parameters of biomass allocation patterns.

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Toxoplasma gondii é um protozoário parasita que infecta animais de sangue quente, incluindo seres humanos. Pequenos roedores e marsupiais têm papel importante na epidemiologia do T. gondii, pois são fontes de infecção para os felídeos domésticos e selvagens. Amostras de soro de 151 roedores e 48 marsupiais, capturados na Mata Atlântica, Estado de São Paulo, Sudeste do Brasil, foram analisadas para a pesquisa de anticorpos anti-T. gondii. Os anticorpos foram detectados pelo Teste de Aglutinação Modificada (MAT ≥ 25), com 8,6% (13/151) dos roedores e 10,4% (5/48) dos marsupiais soropositivos, com títulos variando de 25 a 6.400 e de 25 a 3.200, respectivamente, para os roedores e os marsupiais. Três das oito espécies de roedores (Akodon spp., Oligoryzomys nigripes e Rattus norvegicus) e uma das quatro espécies de marsupiais (Didelphis aurita) apresentaram animais positivos. A presença de anticorpos anti-T. gondii foi descrita pela primeira vez no roedor Oligoryzomys nigripes.

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