923 resultados para bio-indicator
Resumo:
Several methods for assessing the sustainability of agricultural systems have been developed. These methods do not fully: (i) take into account the multi‐functionality of agriculture; (ii) include multidimensionality; (iii) utilize and implement the assessment knowledge; and (iv) identify conflicting goals and trade‐offs. This paper reviews seven recently developed multidisciplinary indicator‐based assessment methods with respect to their contribution to these shortcomings. All approaches include (1) normative aspects such as goal setting, (2) systemic aspects such as a specification of scale of analysis, (3) a reproducible structure of the approach. The approaches can be categorized into three typologies. The top‐down farm assessments focus on field or farm assessment. They have a clear procedure for measuring the indicators and assessing the sustainability of the system, which allows for benchmarking across farms. The degree of participation is low, potentially affecting the implementation of the results negatively. The top‐down regional assessment assesses the on‐farm and the regional effects. They include some participation to increase acceptance of the results. However, they miss the analysis of potential trade‐offs. The bottom‐up, integrated participatory or transdisciplinary approaches focus on a regional scale. Stakeholders are included throughout the whole process assuring the acceptance of the results and increasing the probability of implementation of developed measures. As they include the interaction between the indicators in their system representation, they allow for performing a trade‐off analysis. The bottom‐up, integrated participatory or transdisciplinary approaches seem to better overcome the four shortcomings mentioned above.
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1. Species-based indices are frequently employed as surrogates for wider biodiversity health and measures of environmental condition. Species selection is crucial in determining an indicators metric value and hence the validity of the interpretation of ecosystem condition and function it provides, yet an objective process to identify appropriate indicator species is frequently lacking. 2. An effective indicator needs to (i) be representative, reflecting the status of wider biodiversity; (ii) be reactive, acting as early-warning systems for detrimental changes in environmental conditions; (iii) respond to change in a predictable way. We present an objective, niche-based approach for species' selection, founded on a coarse categorisation of species' niche space and key resource requirements, which ensures the resultant indicator has these key attributes. 3. We use UK farmland birds as a case study to demonstrate this approach, identifying an optimal indicator set containing 12 species. In contrast to the 19 species included in the farmland bird index (FBI), a key UK biodiversity indicator that contributes to one of the UK Government's headline indicators of sustainability, the niche space occupied by these species fully encompasses that occupied by the wider community of 62 species. 4. We demonstrate that the response of these 12 species to land-use change is a strong correlate to that of the wider farmland bird community. Furthermore, the temporal dynamics of the index based on their population trends closely matches the population dynamics of the wider community. However, in both analyses, the magnitude of the change in our indicator was significantly greater, allowing this indicator to act as an early-warning system. 5. Ecological indicators are embedded in environmental management, sustainable development and biodiversity conservation policy and practice where they act as metrics against which progress towards national, regional and global targets can be measured. Adopting this niche-based approach for objective selection of indicator species will facilitate the development of sensitive and representative indices for a range of taxonomic groups, habitats and spatial scales.
Resumo:
Methods for assessing the sustainability of agricultural systems do often not fully (i) take into account the multifunctionality of agriculture, (ii) include multidimensionality, (iii) utilize and implement the assessment knowledge and (iv) identify conflicting goals and trade-offs. This chapter reviews seven recently developed multidisciplinary indicator-based assessment methods with respect to their contribution to these shortcomings. All approaches include (1) normative aspects such as goal setting, (2) systemic aspects such as a specification of scale of analysis and (3) a reproducible structure of the approach. The approaches can be categorized into three typologies: first, top-down farm assessments, which focus on field or farm assessment; second, top-down regional assessments, which assess the on-farm and the regional effects; and third, bottom-up, integrated participatory or transdisciplinary approaches, which focus on a regional scale. Our analysis shows that the bottom-up, integrated participatory or transdisciplinary approaches seem to better overcome the four shortcomings mentioned above.
Resumo:
The likelihood that continuing greenhouse-gas emissions will lead to an unmanageable degree of climate change [1] has stimulated the search for planetary-scale technological solutions for reducing global warming [2] (“geoengineering”), typically characterized by the necessity for costly new infrastructures and industries [3]. We suggest that the existing global infrastructure associated with arable agriculture can help, given that crop plants exert an important influence over the climatic energy budget 4 and 5 because of differences in their albedo (solar reflectivity) compared to soils and to natural vegetation [6]. Specifically, we propose a “bio-geoengineering” approach to mitigate surface warming, in which crop varieties having specific leaf glossiness and/or canopy morphological traits are specifically chosen to maximize solar reflectivity. We quantify this by modifying the canopy albedo of vegetation in prescribed cropland areas in a global-climate model, and thereby estimate the near-term potential for bio-geoengineering to be a summertime cooling of more than 1°C throughout much of central North America and midlatitude Eurasia, equivalent to seasonally offsetting approximately one-fifth of regional warming due to doubling of atmospheric CO2[7]. Ultimately, genetic modification of plant leaf waxes or canopy structure could achieve greater temperature reductions, although better characterization of existing intraspecies variability is needed first.
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The absorption coefficient of a substance distributed as discrete particles in suspension is less than that of the same material dissolved uniformly in a medium—a phenomenon commonly referred to as the flattening effect. The decrease in the absorption coefficient owing to flattening effect depends on the concentration of the absorbing pigment inside the particle, the specific absorption coefficient of the pigment within the particle, and on the diameter of the particle, if the particles are assumed to be spherical. For phytoplankton cells in the ocean, with diameters ranging from less than 1 µm to more than 100 µm, the flattening effect is variable, and sometimes pronounced, as has been well documented in the literature. Here, we demonstrate how the in vivo absorption coefficient of phytoplankton cells per unit concentration of its major pigment, chlorophyll a, can be used to determine the average cell size of the phytoplankton population. Sensitivity analyses are carried out to evaluate the errors in the estimated diameter owing to potential errors in the model assumptions. Cell sizes computed for field samples using the model are compared qualitatively with indirect estimates of size classes derived from high performance liquid chromatography data. Also, the results are compared quantitatively against measurements of cell size in laboratory cultures. The method developed is easy-to-apply as an operational tool for in situ observations, and has the potential for application to remote sensing of ocean colour data.
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Worldwide, many people are zinc (Zn)-deficient. Dietary Zn intake can be increased by producing crops with higher concentrations of Zn in their edible portions. This can be achieved by applying Zn-fertilisers to varieties with an increased ability to acquire Zn and to accumulate Zn in their edible portions. Potato (Solanum tuberosum L.) is an important food crop and is, therefore, a target for bio-fortification with Zn. Field trials incorporating a core collection of 23 potato genotypes, performed over 4 years (2006 – 2009), indicated significant genotypic effects on tuber Zn concentration and suggested that tuber Zn concentration was influenced by environmental effects, but also found that genotype environment (G E) interactions were not significant. Tuber Zn concentrations averaged 10.8 mg kg–1 dry matter (DM), and the ratio between the lowest and the highest varietal tuber Zn-concentration averaged 1.76. Tuber Zn concentrations could be increased by foliar Zn-fertilisation. Tuber yields of ‘Maris Piper’ were unaffected by foliar applications of < 1.08 g Zn plant–1. The relationship between tuber Zn concentration and foliar Zn application followed a saturation curve, reaching a maximum at approx. 30 mg Zn kg–1 DM at a foliar Zn application rate of 1.08 g plant–1. Despite a 40-fold increase in shoot Zn concentration compared to the unfertilised controls following foliar Zn fertilisation with 2.16 g Zn plant–1, only a doubling in tuber Zn concentration was observed. This suggests that the biofortification of tubers with Zn was restricted by the limited mobility of Zn in the phloem. A significant positive linear relationship between tuber Zn concentration and tuber N concentration supported the hypothesis of co-transport of Zn and N-compounds in the phloem.
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The growing energy consumption in the residential sector represents about 30% of global demand. This calls for Demand Side Management solutions propelling change in behaviors of end consumers, with the aim to reduce overall consumption as well as shift it to periods in which demand is lower and where the cost of generating energy is lower. Demand Side Management solutions require detailed knowledge about the patterns of energy consumption. The profile of electricity demand in the residential sector is highly correlated with the time of active occupancy of the dwellings; therefore in this study the occupancy patterns in Spanish properties was determined using the 2009–2010 Time Use Survey (TUS), conducted by the National Statistical Institute of Spain. The survey identifies three peaks in active occupancy, which coincide with morning, noon and evening. This information has been used to input into a stochastic model which generates active occupancy profiles of dwellings, with the aim to simulate domestic electricity consumption. TUS data were also used to identify which appliance-related activities could be considered for Demand Side Management solutions during the three peaks of occupancy.
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Urban metabolism considers a city as a system with flows of energy and material between it and the environment. Recent advances in bio-physical sciences provide methods and models to estimate local scale energy, water, carbon and pollutant fluxes. However, good communication is required to provide this new knowledge and its implications to endusers (such as urban planners, architects and engineers). The FP7 project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) aimed to address this gap by illustrating the advantages of considering these issues in urban planning. The BRIDGE Decision Support System (DSS) aids the evaluation of the sustainability of urban planning interventions. The Multi Criteria Analysis approach adopted provides a method to cope with the complexity of urban metabolism. In consultation with targeted end-users, objectives were defined in relation to the interactions between the environmental elements (fluxes of energy, water, carbon and pollutants) and socioeconomic components (investment costs, housing, employment, etc.) of urban sustainability. The tool was tested in five case study cities: Helsinki, Athens, London, Florence and Gliwice; and sub-models were evaluated using flux data selected. This overview of the BRIDGE project covers the methods and tools used to measure and model the physical flows, the selected set of sustainability indicators, the methodological framework for evaluating urban planning alternatives and the resulting DSS prototype.
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It has been proposed that growing crop varieties with higher canopy albedo would lower summer-time temperatures over North America and Eurasia and provide a partial mitigation of global warming ('bio-geoengineering') (Ridgwell et al 2009 Curr. Biol. 19 1–5). Here, we use a coupled ocean–atmosphere–vegetation model (HadCM3) with prescribed agricultural regions, to investigate to what extent the regional effectiveness of crop albedo bio-geoengineering might be influenced by a progressively warming climate as well as assessing the impacts on regional hydrological cycling and primary productivity. Consistent with previous analysis, we find that the averted warming due to increasing crop canopy albedo by 0.04 is regionally and seasonally specific, with the largest cooling of ~1 °C for Europe in summer whereas in the low latitude monsoonal SE Asian regions of high density cropland, the greatest cooling is experienced in winter. In this study we identify potentially important positive impacts of increasing crop canopy albedo on soil moisture and primary productivity in European cropland regions, due to seasonal increases in precipitation. We also find that the background climate state has an important influence on the predicted regional effectiveness of bio-geoengineering on societally-relevant timescales (ca 100 years). The degree of natural climate variability and its dependence on greenhouse forcing that are evident in our simulations highlights the difficulties faced in the detection and verification of climate mitigation in geoengineering schemes. However, despite the small global impact, regionally focused schemes such as crop albedo bio-geoengineering have detection advantages.
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Biomass is an important source of energy in Thailand and is currently the main renewable energy source, accounting for 40% of the renewable energy used. The Department of Alternative Energy and E�ciency (DEDE), Ministry of Thailand, has been promoting the use of renewable energy in Thailand for the past decade. The new target for renewable energy usage in the country is set at 25% of the �nal energy demand in 2021. Thailand is the world’s fourth largest producer of cassava and this results in the production of signi�cant amounts of cassava rhizome which is a waste product. Cassava rhizome has the potential to be co-�red with coal for the production of heat and power. With suitable co-�ring ratios, little modi�cation will be required in the co-�ring technology. This review article is concerned with an investigation of the feasibility of co-�ring cassava rhizome in a combined heat and power system for a cassava based bio-ethanol plant in Thailand. Enhanced use of cassava rhizome for heat and power production could potentially contribute to a reduction of greenhouse gas emissions and costs, and would help the country to meet the 2021 renewable energy target.
Resumo:
Visual motion cues play an important role in animal and humans locomotion without the need to extract actual ego-motion information. This paper demonstrates a method for estimating the visual motion parameters, namely the Time-To-Contact (TTC), Focus of Expansion (FOE), and image angular velocities, from a sparse optical flow estimation registered from a downward looking camera. The presented method is capable of estimating the visual motion parameters in a complicated 6 degrees of freedom motion and in real time with suitable accuracy for mobile robots visual navigation.
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Concern that European forest biodiversity is depleted and declining has provoked widespread efforts to improve management practices. To gauge the success of these actions, appropriate monitoring of forest ecosystems is paramount. Multi-species indicators are frequently used to assess the state of biodiversity and its response to implemented management, but generally applicable and objective methodologies for species' selection are lacking. Here we use a niche-based approach, underpinned by coarse quantification of species' resource use, to objectively select species for inclusion in a pan-European forest bird indicator. We identify both the minimum number of species required to deliver full resource coverage and the most sensitive species' combination, and explore the trade-off between two key characteristics, sensitivity and redundancy, associated with indicators comprising different numbers of species. We compare our indicator to an existing forest bird indicator selected on the basis of expert opinion and show it is more representative of the wider community. We also present alternative indicators for regional and forest type specific monitoring and show that species' choice can have a significant impact on the indicator and consequent projections about the state of the biodiversity it represents. Furthermore, by comparing indicator sets drawn from currently monitored species and the full forest bird community, we identify gaps in the coverage of the current monitoring scheme. We believe that adopting this niche-based framework for species' selection supports the objective development of multi-species indicators and that it has good potential to be extended to a range of habitats and taxa.
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Near ground maneuvers, such as hover, approach and landing, are key elements of autonomy in unmanned aerial vehicles. Such maneuvers have been tackled conventionally by measuring or estimating the velocity and the height above the ground often using ultrasonic or laser range finders. Near ground maneuvers are naturally mastered by flying birds and insects as objects below may be of interest for food or shelter. These animals perform such maneuvers efficiently using only the available vision and vestibular sensory information. In this paper, the time-to-contact (Tau) theory, which conceptualizes the visual strategy with which many species are believed to approach objects, is presented as a solution for Unmanned Aerial Vehicles (UAV) relative ground distance control. The paper shows how such an approach can be visually guided without knowledge of height and velocity relative to the ground. A control scheme that implements the Tau strategy is developed employing only visual information from a monocular camera and an inertial measurement unit. To achieve reliable visual information at a high rate, a novel filtering system is proposed to complement the control system. The proposed system is implemented on-board an experimental quadrotor UAV and shown not only to successfully land and approach ground, but also to enable the user to choose the dynamic characteristics of the approach. The methods presented in this paper are applicable to both aerial and space autonomous vehicles.