882 resultados para Ecosystem indicators


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We present here an indicator of soil quality that evaluates soil ecosystem services through a set of 5 subindicators, and further combines them into a single general Indicator of Soil Quality (GISQ). We used information derived from 54 properties commonly used to describe the multifaceted aspects of soil quality. The design and calculation of the indicators were based on sequences of multivariate analyses. Subindicators evaluated the physical quality, chemical fertility, organic matter stocks, aggregation and morphology of the upper 5 cm of soil and the biodiversity of soil macrofauna. A GISQ combined the different subindicators providing a global assessment of soil quality. Research was conducted in two hillside regions of Colombia and Nicaragua, with similar types of land use and socio-economic context. However, soil and climatic conditions differed significantly. In Nicaragua, soil quality was assessed at 61 points regularly distributed 200 m apart on a regular grid across the landscape. In Colombia, 8 plots representing different types of land use were arbitrarily chosen in the landscape and intensively sampled. Indicators that were designed in the Nicaragua site were further applied to the Colombian site to test for their applicability. In Nicaragua, coffee plantations, fallows, pastures and forest had the highest values of GISQ (1.00; 0.80; 0.78 and 0.77, respectively) while maize crops and eroded soils (0.19 and 0.10) had the lowest values. Examination of subindicator values allowed the separate evaluation of different aspects of soil quality: subindicators of organic matter, aggregation and morphology and biodiversity of macrofauna had the maximum values in coffee plantations (0.89; 0.72 and 0.56, respectively on average) while eroded soils had the lowest values for these indicators (0.10; 0.31 and 0.33, respectively). Indicator formulae derived from information gained at the Nicaraguan sites were not applicable to the Colombian situation and site-specific constants were calculated. This indicator allows the evaluation of soil quality and facilitates the identification of problem areas through the individual values of each subindicator. It allows monitoring of change through time and can guide the implementation of soil restoration technologies. Although GISQ formulae computed on a set of data were only valid at a regional scale, the methodology used to create these indices can be applied everywhere.

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Digital videophotography, computer image analysis and physical measurements have been used to monitor sedimentation rates, coral cover, genera richness, rugosity and estimated recruitment dates of massive corals at three different sites in the Wakatobi Marine National Park, Indonesia, and on the reefs around Discovery Bay, Jamaica. Semi-structured interviews with key stakeholders in the Wakatobi Marine National Park indicated that coral mining was extensively practised, and is responsible for the absence of large non-branching corals on the Sampela reef Blast fishing is also practised in the Wakatobi Marine Park, and the authors, together with students, showed that blast fishing resulted in coral bleaching and not mortality of two Porites lutea colonies. In addition, we showed that monitoring of bleaching in Porites colonies induced by blast fishing could be a useful way of monitoring blast fishing practices in susceptible areas in the Indo-Pacific. The techniques used in this study are appropriate for use by volunteers with sufficient training, and provide excellent projects for dissertation students reading undergraduate degrees.

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The main objectives of this paper are to: firstly, identify key issues related to sustainable intelligent buildings (environmental, social, economic and technological factors); develop a conceptual model for the selection of the appropriate KPIs; secondly, test critically stakeholder's perceptions and values of selected KPIs intelligent buildings; and thirdly develop a new model for measuring the level of sustainability for sustainable intelligent buildings. This paper uses a consensus-based model (Sustainable Built Environment Tool- SuBETool), which is analysed using the analytical hierarchical process (AHP) for multi-criteria decision-making. The use of the multi-attribute model for priority setting in the sustainability assessment of intelligent buildings is introduced. The paper commences by reviewing the literature on sustainable intelligent buildings research and presents a pilot-study investigating the problems of complexity and subjectivity. This study is based upon a survey perceptions held by selected stakeholders and the value they attribute to selected KPIs. It is argued that the benefit of the new proposed model (SuBETool) is a ‘tool’ for ‘comparative’ rather than an absolute measurement. It has the potential to provide useful lessons from current sustainability assessment methods for strategic future of sustainable intelligent buildings in order to improve a building's performance and to deliver objective outcomes. Findings of this survey enrich the field of intelligent buildings in two ways. Firstly, it gives a detailed insight into the selection of sustainable building indicators, as well as their degree of importance. Secondly, it tesst critically stakeholder's perceptions and values of selected KPIs intelligent buildings. It is concluded that the priority levels for selected criteria is largely dependent on the integrated design team, which includes the client, architects, engineers and facilities managers.

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A proper method to assess contractor competitiveness is important both for assisting clients in the selection of proper contractors and for assisting contractors in the development of more competitive bidding strategies. Previous studies have identified various indicators for assessing contractor competitiveness, and several assessment methods have been introduced. Nevertheless, these studies are limited because they are unable to tell which indicators are more important in different market environments. This paper identifies the key competitiveness indicators �KCIs� for assessing contractor competitiveness in the Chinese construction market. An index value is used to indicate the relative significance of various competitiveness indicators based on which KCIs are identified. The data applied in this study are from a survey of the construction industry in mainland China. The research findings provide valuable information for both existing businesses and the construction professionals who plan to compete for construction works in the Chinese market. The study provides useful references for further studies that compare the KCIs used in the Chinese construction industry and those used in other construction industries.

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This paper identifies the indicators of energy efficiency assessment in residential building in China through a wide literature review. Indicators are derived from three main sources: 1) The existing building assessment methods; 2)The existing Chinese standards and technology codes in building energy efficiency; 3)Academia research. As a result, we proposed an indicator list by refining the indicators in the above sources. Identified indicators are weighted by the group analytic hierarchy process (AHP) method. Group AHP method is implemented following key steps: Step 1: Experienced experts are selected to form a group; Step 2: A survey is implemented to collect the individual judgments on the importance of indicators in the group; Step 3: Members’ judgments are synthesized to the group judgments; Step 4: Indicators are weighted by AHP on the group judgments; Step 5: Investigation of consistency estimation shows that the consistency of the judgment matrix is accepted. We believe that the weighted indicators in this paper will provide important references to building energy efficiency assessment.

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Aim. The aim of this study was to investigate whether a single soccer specific fitness test (SSFT) could differentiate between highly trained and recreationally active soccer players in selected test performance indicators. Methods. Subjects: 13 Academy Scholars (AS) from a professional soccer club and 10 Recreational Players (RP) agreed to participate in this study. Test 1-(V)over dotO(2) max was estimated from a progressive shuttle run test to exhaustion. Test 2-The SSFT was controlled by an automated procedure and alternated between walking, sprinting, jogging and cruise running speeds. Three activity blocks (1A, 2A and 3A) were separated by 3 min rest periods in which blood lactate samples were drawn. The 3 blocks of activity (Part A) were followed by 10 min of exercise at speeds alternating between jogging and cruise running (Part B). Results. Estimated (V)over dotO(2) max did not significantly differ between groups, although a trend for a higher aerobic capacity was evident in AS (p<0.09). Exercising heart rates did not differ between AS and RP, however, recovery heart rates taken from the 3 min rest periods were significantly lower in AS compared with RP following blocks 1A (124.65 b(.)min(-1) +/-7.73 and 133.98 b(.)min(-1) +/-6.63), (p<0.05) and 3A (129.91 b.min(-1) +/-10.21 and 138.85 b.min(-1) +/-8.70), (p<0.01). Blood lactate concentrations were significantly elevated in AS in comparison to RP following blocks 2A (6.91 mmol(.)l(-1) +/-2.67 and 4.74 mmol(.)l(-1) +/-1.28) and 3A (7.18 mmol(.)l(-1) +/-2.97 and 4.88 mmol(.)l(-1) +/-1.50), (p<0.05). AS sustained significantly faster average sprint times in block 3A compared with RP (3.18 sec +/-0.12 and 3.31 sec +/-0.12), (p<0.05). Conclusion. The results of this study show that highly trained soccer players are able to sustain, and more quickly recover from, high intensity intermittent exercise.

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By 2030, the world’s human population could rise to 8 billion people and world food demand may increase by 50%. Although food production outpaced population growth in the 20th century, it is clear that the environmental costs of these increases cannot be sustained into the future. This challenges us to re-think the way we produce food. We argue that viewing food production systems within an ecosystems context provides the basis for 21st century food production. An ecosystems view recognises that food production systems depend on ecosystem services but also have ecosystem impacts. These dependencies and impacts are often poorly understood by many people and frequently overlooked. We provide an overview of the key ecosystem services involved in different food production systems, including crop and livestock production, aquaculture and the harvesting of wild nature. We highlight the important ecosystem impacts of food production systems, including habitat loss and degradation, changes to water and nutrient cycles across a range of scales, and biodiversity loss. These impacts often undermine the very ecosystem services on which food production systems depend, as well as other ecosystem services unrelated to food. We argue that addressing these impacts requires us to re-design food production systems to recognise and manage the limitations on production imposed by the ecosystems within which they are embedded, and increasingly embrace a more multifunctional view of food production systems and associated ecosystems. In this way, we should be able to produce food more sustainably whilst inflicting less damage on other important ecosystem services.

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This paper examines the significance of widely used leading indicators of the UK economy for predicting the cyclical pattern of commercial real estate performance. The analysis uses monthly capital value data for UK industrials, offices and retail from the Investment Property Databank (IPD). Prospective economic indicators are drawn from three sources namely, the series used by the US Conference Board to construct their UK leading indicator and the series deployed by two private organisations, Lombard Street Research and NTC Research, to predict UK economic activity. We first identify turning points in the capital value series adopting techniques employed in the classical business cycle literature. We then estimate probit models using the leading economic indicators as independent variables and forecast the probability of different phases of capital values, that is, periods of declining and rising capital values. The forecast performance of the models is tested and found to be satisfactory. The predictability of lasting directional changes in property performance represents a useful tool for real estate investment decision-making.

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Pesticide risk indicators provide simple support in the assessment of environmental and health risks from pesticide use, and can therefore inform policies to foster a sustainable interaction of agriculture with the environment. For their relative simplicity, indicators may be particularly useful under conditions of limited data availability and resources, such as in Less Developed Countries (LDCs). However, indicator complexity can vary significantly, in particular between those that rely on an exposure–toxicity ratio (ETR) and those that do not. In addition, pesticide risk indicators are usually developed for Western contexts, which might cause incorrect estimation in LDCs. This study investigated the appropriateness of seven pesticide risk indicators for use in LDCs, with reference to smallholding agriculture in Colombia. Seven farm-level indicators, among which 3 relied on an ETR (POCER, EPRIP, PIRI) and 4 on a non-ETR approach (EIQ, PestScreen, OHRI, Dosemeci et al., 2002), were calculated and then compared by means of the Spearman rank correlation test. Indicators were also compared with respect to key indicator characteristics, i.e. user friendliness and ability to represent the system under study. The comparison of the indicators in terms of the total environmental risk suggests that the indicators not relying on an ETR approach cannot be used as a reliable proxy for more complex, i.e. ETR, indicators. ETR indicators, when user-friendly, show a comparative advantage over non-ETR in best combining the need for a relatively simple tool to be used in contexts of limited data availability and resources, and for a reliable estimation of environmental risk. Non-ETR indicators remain useful and accessible tools to discriminate between different pesticides prior to application. Concerning the human health risk, simple algorithms seem more appropriate for assessing human health risk in LDCs. However, further research on health risk indicators and their validation under LDC conditions is needed.