28 resultados para Ecosystem indicators

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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Major oil spills can have long-term impacts since oil pollution does not only result in acute mortality of marine organisms, but also affects productivity levels, predator-prey dynamics, and damages habitats that support marine communities. However, despite the conservation implications of oil accidents, the monitoring and assessment of its lasting impacts still remains a difficult and daunting task. Here, we used European shags to evaluate the overall, lasting effects of the Prestige oil spill (2002) on the affected marine ecosystem. Using δ15N and Hg analysis, we trace temporal changes in feeding ecology potentially related to alterations of the food web due to the spill. Using climatic and oceanic data, we also investigate the influence of North Atlantic Oscillation (NAO) index, the sea surface temperature (SST) and the chlorophyll a (Chl a) on the observed changes. Analysis of δ15N and Hg concentrations revealed that after the Prestige oil spill, shag chicks abruptly switched their trophic level from a diet based on a high percentage of demersal-benthic fish to a higher proportion of pelagic/semi-pelagic species. There was no evidence that Chl a, SST and NAO reflected any particular changes or severity in environmental conditions for any year or season that may explain the sudden change observed in trophic level. Thus, this study highlighted an impact on the marine food web for at least three years. Our results provide the best evidence to date of the long-term consequences of the Prestige oil spill. They also show how, regardless of wider oceanographic variability, lasting impacts on predator-prey dynamics can be assessed using biochemical markers. This is particularly useful if larger scale and longer term monitoring of all trophic levels is unfeasible due to limited funding or high ecosystem complexity.

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This paper attempts to provide an explanation of why reductionistic approaches are not adequate to tackle the urban sustainability issue in a consistent way. Concepts such as urban environmental carrying capacity and ecological footprint are discussed. Multicriteria evaluation is proposed as a general multidimensional framework for the assessment of urban sustainability. This paper deals with the following main topics: 1) definition of the concept of urban sustainability 2) discussion of relevant sustainability indicators 3) multicriteria evaluation as a framework for the assessment of urban sustainability 4) an illustrative example.

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Ecological economics is a recently developed field, which sees the economy as a subsystem of a larger finite global ecosystem. Ecological economists question the sustainability of the economy because of its environmental impacts and its material and energy requirements, and also because of the growth of population. Attempts at assigning money values to environmental services and losses, and attempts at correcting macroeconomic accounting, are part of ecological economics, but its main thrust is rather in developing physical indicators and indexes of sustainability. Ecological economists also work on the relations between property rights and resource management, they model the interactions between the economy and the environment, they study ecological distribution conflicts, they use management tools such as integrated environmental assessment and multi-criteria decision aids, and they propose new instruments of environmental policy.

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This paper presents an outline of rationale and theory of the MuSIASEM scheme (Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism). First, three points of the rationale behind our MuSIASEM scheme are discussed: (i) endosomatic and exosomatic metabolism in relation to Georgescu-Roegen’s flow-fund scheme; (2) the bioeconomic analogy of hypercycle and dissipative parts in ecosystems; (3) the dramatic reallocation of human time and land use patterns in various sectors of modern economy. Next, a flow-fund representation of the MUSIASEM scheme on three levels (the whole national level, the paid work sectors level, and the agricultural sector level) is illustrated to look at the structure of the human economy in relation to two primary factors: (i) human time - a fund; and (ii) exosomatic energy - a flow. The three levels representation uses extensive and intensive variables simultaneously. Key conceptual tools of the MuSIASEM scheme - mosaic effects and impredicative loop analysis - are explained using the three level flow-fund representation. Finally, we claim that the MuSIASEM scheme can be seen as a multi-purpose grammar useful to deal with sustainability issues.

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In this study we propose an application of the MuSIASEM approach which is used to provide an integrated analysis of Laos across different scales. With the term “integrated analysis across scales” we mean the generation of a series of packages of quantitative indicators, characterizing the performance of the socioeconomic activities performed in Laos when considering: (i) different hierarchical levels of organization (farming systems described at the level of household, rural villages, regions of Laos, the whole country level); and (ii) different dimensions of analysis (economic dimension, social dimension, ecological dimension, technical dimension). What is relevant in this application is that the information carried out by these different packages of indicators is integrated in a system of accounting which establishes interlinkages across these indicators. This is a essential feature to study sustainability trade-offs and to build more robust scenarios of possible changes. The multi-scale integrated representation presented in this study is based on secondary data (gathered in a three year EU project – SEAtrans and integrated by other available statistical sources) and it is integrated in GIS, when dealing with the spatial representation of Laos. However, even if we use data referring to Laos, the goal of this study is not that of providing useful information about a practical policy issue of Laos, but rather, to illustrate the possibility of using a multipurpose grammar to produce an integrated set of sustainability indicators at three different levels: (i) local; (ii) meso; (iii) macro level. The technical issue addressed is the simultaneous adoption of two multi-level matrices – one referring to a characterization of human activity over a set of different categories, and another referring to a characterization of land uses over the same set of categories. In this way, it becomes possible to explain the characteristics of Laos (an integrated set of indicators defining the performance of the whole country) in relation to the characteristics of the rural Laos and urban Laos. The characteristics of rural Laos, can be explained using the characteristics of three regions defined within Laos (Northern Laos, Central Laos and Southern Laos), which in turn can be defined (using an analogous package of indicators), starting from the characteristics of three main typologies of farming systems found in the regions.

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This study presents a first attempt to extend the “Multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM)” approach to a spatial dimension using GIS techniques in the Metropolitan area of Barcelona. We use a combination of census and commercial databases along with a detailed land cover map to create a layer of Common Geographic Units that we populate with the local values of human time spent in different activities according to MuSIASEM hierarchical typology. In this way, we mapped the hours of available human time, in regards to the working hours spent in different locations, putting in evidence the gradients in spatial density between the residential location of workers (generating the work supply) and the places where the working hours are actually taking place. We found a strong three-modal pattern of clumps of areas with different combinations of values of time spent on household activities and on paid work. We also measured and mapped spatial segregation between these two activities and put forward the conjecture that this segregation increases with higher energy throughput, as the size of the functional units must be able to cope with the flow of exosomatic energy. Finally, we discuss the effectiveness of the approach by comparing our geographic representation of exosomatic throughput to the one issued from conventional methods.

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The problem of waste management is causing growing concern due to increasing generation rates, the emissions into soil, water and air, the social conflicts derived from the election of disposal sites and the loss of resources and energy among others. In this work, an innovative methodology is used to enable a better understanding of the waste generation and management system in Italy. Two new waste indicators are built to complement the conventional indicators used by official statistics. Then a multi-scale analysis of the Density of Waste Disposed (DWD) is carried out to highlight the territorial diversity of waste performances and test its contribution to detect plausible risky areas. Starting from Italian regions, the scale down goes on to the provincial level and, only for the region of Campania, the municipal one. First, the analysis shows that the DWD is able to complement the information provided by the conventional waste indicators. Second, the analysis shows the limitations of using a unique institutional solution to waste management problems. In this sense the multi-scale analysis provides with a more realistic picture of Italian waste system than using a single scale.

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In recent years traditional inequality measures have been used to quite a considerable extent to examine the international distribution of environmental indicators. One of its main characteristics is that each one assigns different weights to the changes that occur in the different sections of the variable distribution and, consequently, the results they yield can potentially be very different. Hence, we suggest the appropriateness of using a range of well-recommended measures to achieve more robust results. We also provide an empirical test for the comparative behaviour of several suitable inequality measures and environmental indicators. Our findings support the hypothesis that in some cases there are differences among measures in both the sign of the evolution and its size. JEL codes: D39; Q43; Q56. Keywords: international environment factor distribution; Kaya factors; Inequality measurement

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The development of open educational resources (OERs) is becoming a strategic priority for governments and education institutions around the world, in response to funding cuts and rising costs in educational provision. In the United Kingdom, a government-sponsored Pilot Programme on Open Educational Recourses (JISC/HEA, 2009) was launched in 2009 with an initial budget of £5.7m. This paper reviews the key sustainability issues identified by the projects including the different approaches and models that have been adopted in order to sustain the continuing development and release of OER once funding has ended. The analysis also considers the challenges relating to the development and implementation of policies and processes for sustainable OER practice within institutions and among academics. The paper concludes by drawing on the experiences from the wider United Kingdom and international OER communities to develop a sustainable OER ecosystem model that can facilitate discussions on future development of OER initiatives.

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This paper proposes to promote autonomy in digital ecosystems so that it provides agents with information to improve the behavior of the digital ecosystem in terms of stability. This work proposes that, in digital ecosystems, autonomous agents can provide fundamental services and information. The final goal is to run the ecosystem, generate novel conditions and let agents exploit them. A set of evaluation measures must be defined as well. We want to provide an outline of some global indicators, such as heterogeneity and diversity, and establish relationships between agent behavior and these global indicators to fully understand interactions between agents, and to understand the dependence and autonomy relations that emerge between the interacting agents. Individual variations, interaction dependencies, and environmental factors are determinants of autonomy that would be considered. The paper concludes with a discussion of situations when autonomy is a milestone

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La localitat de Cumbe és una comunitat tradicional que es troba al tram baix del riu Jaguaribe situat a l’estat de Ceará (Brasil) i que ha viscut centenars d’anys a partir de les pràctiques extractives que es porten a terme a l’ecosistema del manglar. Fa 20 anys va aparèixer a la regió una nova economia basada en l’explotació intensiva. L’aqüicultura destinada a la cria de gamba està causant danys severs a l’ecosistema del manglar i perjudicant greument la font d’ingressos de moltes famílies, amenaçant la continuïtat de l’economia local i deteriorant la qualitat de vida de les persones que s’hi dediquen. A partir de l’observació personal i la immersió en aquesta societat s’ha detectat que l’economia tradicional està infravalorada pel govern i per les persones que donen suport a l’aqüicultura. Per aquest motiu s’han creat una sèrie d’indicadors, a partir de les activitats extractives del cranc, que posin en valor aquesta economia tradicional envers la nova economia emergent.

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This paper proposes a method to conduct inference in panel VAR models with cross unit interdependencies and time variations in the coefficients. The approach can be used to obtain multi-unit forecasts and leading indicators and to conduct policy analysis in a multiunit setups. The framework of analysis is Bayesian and MCMC methods are used to estimate the posterior distribution of the features of interest. The model is reparametrized to resemble an observable index model and specification searches are discussed. As an example, we construct leading indicators for inflation and GDP growth in the Euro area using G-7 information.

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Major coastal storms, associated with strong winds, high waves and intensified currents, and occasionally with heavy rains and flash floods, are mostly known because of the serious damage they can cause along the shoreline and the threats they pose to navigation. However, there is a profound lack of knowledge on the deep-sea impacts of severe coastal storms. Concurrent measurements of key parameters along the coast and in the deep-sea are extremely rare. Here we present a unique data set showing how one of the most extreme coastal storms of the last decades lashing the Western Mediterranean Sea rapidly impacted the deep-sea ecosystem. The storm peaked the 26th of December 2008 leading to the remobilization of a shallow-water reservoir of marine organic carbon associated with fine particles and resulting in its redistribution across the deep basin. The storm also initiated the movement of large amounts of coarse shelf sediment, which abraded and buried benthic communities. Our findings demonstrate, first, that severe coastal storms are highly efficient in transporting organic carbon from shallow water to deep water, thus contributing to its sequestration and, second, that natural, intermittent atmospheric drivers sensitive to global climate change have the potential to tremendously impact the largest and least known ecosystem on Earth, the deep-sea ecosystem.

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Major coastal storms, associated with strong winds, high waves and intensified currents, and occasionally with heavy rains and flash floods, are mostly known because of the serious damage they can cause along the shoreline and the threats they pose to navigation. However, there is a profound lack of knowledge on the deep-sea impacts of severe coastal storms. Concurrent measurements of key parameters along the coast and in the deep-sea are extremely rare. Here we present a unique data set showing how one of the most extreme coastal storms of the last decades lashing the Western Mediterranean Sea rapidly impacted the deep-sea ecosystem. The storm peaked the 26th of December 2008 leading to the remobilization of a shallow-water reservoir of marine organic carbon associated with fine particles and resulting in its redistribution across the deep basin. The storm also initiated the movement of large amounts of coarse shelf sediment, which abraded and buried benthic communities. Our findings demonstrate, first, that severe coastal storms are highly efficient in transporting organic carbon from shallow water to deep water, thus contributing to its sequestration and, second, that natural, intermittent atmospheric drivers sensitive to global climate change have the potential to tremendously impact the largest and least known ecosystem on Earth, the deep-sea ecosystem.

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Different components of global change can have interacting effects on biodiversity and this may influence our ability to detect the specific consequences of climate change through biodiversity indicators. Here, we analyze whether climate change indicators can be affected by land use dynamics that are not directly determined by climate change. To this aim, we analyzed three community-level indicators of climate change impacts that are based on the optimal thermal environment and averagelatitude of the distribution of bird species present at local communities. We used multiple regression models to relate the variation in climate change indicators to: i) environmental temperature; and ii) three landscape gradients reflecting important current land use change processes (land abandonment, fire impacts and urbanization), all of them having forest areas at their positive extremes. We found that, with few exceptions, landscape gradients determined the figures of climate change indicators as strongly as temperature. Bird communities in forest habitats had colder-dwelling bird species with more northerndistributions than farmland, burnt or urban areas. Our results show that land use changes can reverse, hide or exacerbate our perception of climate change impacts when measured through community-level climate change indicators. We stress the need of an explicit incorporation of the interactions between climate change and land use dynamics to understand what are current climate change indicators indicating and be able to isolate real climate change impacts