Dataset Information

Going beyond the Millennium Ecosystem Assessment: an index system of human well-being.

ABSTRACT: Understanding the linkages between ecosystem services (ES) and human well-being (HWB) is crucial to sustain the flow of ES for HWB. The Millennium Ecosystem Assessment (MA) provided a state-of-the-art synthesis of such knowledge. However, due to the complexity of the linkages between ES and HWB, there are still many knowledge gaps, and in particular a lack of quantitative indicators and integrated models based on the MA framework. To fill some of these research needs, we developed a quantitative index system to measure HWB, and assessed the impacts of an external driver--the 2008 Wenchuan Earthquake--on HWB. Our results suggest that our proposed index system of HWB is well-designed, valid and could be useful for better understanding the linkages between ES and HWB. The earthquake significantly affected households' well-being in our demonstration sites. Such impacts differed across space and across the five dimensions of the sub-index (i.e., the basic material for good life, security, health, good social relations, and freedom of choice and action). Since the conceptual framework is based on the generalizable MA framework, our methods should also be applicable to other study areas.

SUBMITTER: Yang W

PROVIDER: S-EPMC3661712 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Going beyond the Millennium Ecosystem Assessment: an index system of human well-being.

Yang Wu W Dietz Thomas T Kramer Daniel Boyd DB Chen Xiaodong X Liu Jianguo J

PloS one 20130522 5

Understanding the linkages between ecosystem services (ES) and human well-being (HWB) is crucial to sustain the flow of ES for HWB. The Millennium Ecosystem Assessment (MA) provided a state-of-the-art synthesis of such knowledge. However, due to the complexity of the linkages between ES and HWB, there are still many knowledge gaps, and in particular a lack of quantitative indicators and integrated models based on the MA framework. To fill some of these research needs, we developed a quantitative ...[more]

PMID: 23717635

Similar Datasets

Project description:Quantifying and comparing the scientific output of researchers has become critical for governments, funding agencies and universities. Comparison by reputation and direct assessment of contributions to the field is no longer possible, as the number of scientists increases and traditional definitions about scientific fields become blurred. The h-index is often used for comparing scientists, but has several well-documented shortcomings. In this paper, we introduce a new index for measuring and comparing the publication records of scientists: the pagerank-index (symbolised as π). The index uses a version of pagerank algorithm and the citation networks of papers in its computation, and is fundamentally different from the existing variants of h-index because it considers not only the number of citations but also the actual impact of each citation. We adapt two approaches to demonstrate the utility of the new index. Firstly, we use a simulation model of a community of authors, whereby we create various 'groups' of authors which are different from each other in inherent publication habits, to show that the pagerank-index is fairer than the existing indices in three distinct scenarios: (i) when authors try to 'massage' their index by publishing papers in low-quality outlets primarily to self-cite other papers (ii) when authors collaborate in large groups in order to obtain more authorships (iii) when authors spend most of their time in producing genuine but low quality publications that would massage their index. Secondly, we undertake two real world case studies: (i) the evolving author community of quantum game theory, as defined by Google Scholar (ii) a snapshot of the high energy physics (HEP) theory research community in arXiv. In both case studies, we find that the list of top authors vary very significantly when h-index and pagerank-index are used for comparison. We show that in both cases, authors who have collaborated in large groups and/or published less impactful papers tend to be comparatively favoured by the h-index, whereas the pagerank-index highlights authors who have made a relatively small number of definitive contributions, or written papers which served to highlight the link between diverse disciplines, or typically worked in smaller groups. Thus, we argue that the pagerank-index is an inherently fairer and more nuanced metric to quantify the publication records of scientists compared to existing measures.

Dataset Information

Going beyond the Millennium Ecosystem Assessment: an index system of human well-being.

Publications

Going beyond the Millennium Ecosystem Assessment: an index system of human well-being.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets