Fishery of the Goliath grouper, Epinephelus itajara (Teleostei: Epinephelidae) based on local ecological knowledge and fishery records in Yucatan, Mexico

The Goliath grouper, Epinephelus itajara, a large-bodied (similar to 2.5 m TL, > 400 kg) and critically endangered fish (Epinephelidae), is highly Vulnerable to overfishing. Although protected from fishing in many countries, its exploitation in Mexico is unregulated; a situation that puts its populations at risk. Fishery records of E. itajara are scarce, which prevents determination of its fishery status. This work aimed to elucidate the E itajara fishery in the northern Yucatan Peninsula by 1) analyzing available catch records and 2) interviewing veteran fishermen (local ecological knowledge) from two traditional landing sites: Dzilam de Bravo and Puerto Progreso. Historic fishery records from two fishing cooperatives were analyzed in order to elucidate the current situation and offer viable alternatives for conservation and management. Catches have decreased severely. Local knowledge obtained from fishermen represented a very important source of information for reconstructing the fisheries history of this species. Conservation measures that incorporate regional and international regulations on critically endangered fish species are suggested

Acquiring expert knowledge for the design of conceptual information systems

Conceptual Information Systems unfold the conceptual structure of data stored in relational databases. In the design phase of the system, conceptual hierarchies have to be created which describe different aspects of the data. In this paper, we describe two principal ways of designing such conceptual hierarchies, data driven design and theory driven design and discuss advantages and drawbacks. The central part of the paper shows how Attribute Exploration, a knowledge acquisition tool developped by B. Ganter can be applied for narrowing the gap between both approaches.

Transformation of local medicinal knowledge in the Andean Highlands: Case studies from Peru and Bolivia

In the Andean highlands, indigenous environmental knowledge is currently undergoing major changes as a result of various external and internal factors. As in other parts of the world, an overall process of erosion of local knowledge can be observed. In response to this trend, some initiatives that adopt a biocultural approach aim at actively strengthening local identities and revalorizing indigenous environmental knowledge and practices, assuming that such practices can contribute to more sustainable management of biodiversity. However, these initiatives usually lack a sound research basis, as few studies have focused on the dynamics of indigenous environmental knowledge in the Andes and on its links with biodiversity management. Against this background, the general objective of this research project was to contribute to the understanding of the dynamics of indigenous environmental knowledge in the Andean highlands of Peru and Bolivia by investigating how local medicinal knowledge is socially differentiated within rural communities, how it is transformed, and which external and internal factors influence these transformation processes. The project adopted an actor-oriented perspective and emphasized the concept of knowledge dialogue by analyzing the integration of traditional and formal medicinal systems within family therapeutic strategies. It also aimed at grasping some of the links between the dynamics of medicinal knowledge and the types of land use systems and biodiversity management. Research was conducted in two case study areas of the Andes, both Quechua-speaking and situated in comparable agro-ecological production belts - Pitumarca District, Department of Cusco (Southern Peruvian Highlands) and the Tunari National Park, Department of Cochabamba (Bolivian inner-Andean valleys). In each case study area, the land use systems and strategies of 18 families from two rural communities, their environmental knowledge related to medicine and to the local therapeutic flora, and an appreciation of the dynamics of this knowledge were assessed. Data were collected through a combination of disciplinary and participatory action-research methods. It was mostly analyzed using qualitative methods, though some quantitative ethnobotanical methods were also used. In both case studies, traditional medicine still constitutes the preferred option for the families interviewed, independently of their age, education level, economic status, religion, or migration status. Surprisingly and contrary to general assertions among local NGOs and researchers, results show that there is a revival of Andean medicine within the younger generation, who have greater knowledge of medicinal plants than the previous one, value this knowledge as an important element of their way of life and relationship with “Mother Earth” (Pachamama), and, at least in the Bolivian case, prefer to consult the traditional healer rather than go to the health post. Migration to the urban centres and the Amazon lowlands, commonly thought to be an important factor of local medicinal knowledge loss, only affects people’s knowledge in the case of families who migrate over half of the year or permanently. Migration does not influence the knowledge of medicinal plants or the therapeutic strategies of families who migrate temporarily for shorter periods of time. Finally, economic status influences neither the status of people’s medicinal knowledge, nor families’ therapeutic strategies, even though the financial factor is often mentioned by practitioners and local people as the main reason for not using the formal health system. The influence of the formal health system on traditional medicinal knowledge varies in each case study area. In the Bolivian case, where it was only introduced in the 1990s and access to it is still very limited, the main impact was to give local communities access to contraceptive methods and to vaccination. In the Peruvian case, the formal system had a much greater impact on families’ health practices, due to local and national policies that, for instance, practically prohibit some traditional practices such as home birth. But in both cases, biomedicine is not considered capable of responding to cultural illnesses such as “fear” (susto), “bad air” (malviento), or “anger” (colerina). As a consequence, Andean farmers integrate the traditional medicinal system and the formal one within their multiple therapeutic strategies, reflecting an inter-ontological dialogue between different conceptions of health and illness. These findings reflect a more general trend in the Andes, where indigenous communities are currently actively revalorizing their knowledge and taking up traditional practices, thus strengthening their indigenous collective identities in a process of cultural resistance.

Local environmental knowledge: a key input for the sustainable development of Andean mountain communities

Local knowledge is crucial to both human development and environmental conservation. This is especially the case in mountain regions, where a combination of remoteness, harsh climatic conditions, rich cultural heritage, and high biological diversity has led to the development of complex local environmental knowledge systems. In the Andes for instance, rural populations mainly rely on their own environmental knowledge to ensure their food security and health. Recent studies conducted within Quechua communities in Peru and Bolivia showed that this knowledge was both persistent and dynamic, and that it responded to socio-economic and environmental changes through cultural resistance and adaptation. As this paper argues, combining local knowledge and so-called scientific knowledge – especially in development projects – can lead to innovative solutions to the socio-environmental challenges facing mountain communities in our globalized world. Based on experiences from the Andes, this paper will provide concrete recommendations to policymakers and practitioners for integrating local knowledge into development and natural resource management initiatives.

Cooperation between expert knowledge and data mining discovered knowledge: Lessons learned

Expert systems are built from knowledge traditionally elicited from the human expert. It is precisely knowledge elicitation from the expert that is the bottleneck in expert system construction. On the other hand, a data mining system, which automatically extracts knowledge, needs expert guidance on the successive decisions to be made in each of the system phases. In this context, expert knowledge and data mining discovered knowledge can cooperate, maximizing their individual capabilities: data mining discovered knowledge can be used as a complementary source of knowledge for the expert system, whereas expert knowledge can be used to guide the data mining process. This article summarizes different examples of systems where there is cooperation between expert knowledge and data mining discovered knowledge and reports our experience of such cooperation gathered from a medical diagnosis project called Intelligent Interpretation of Isokinetics Data, which we developed. From that experience, a series of lessons were learned throughout project development. Some of these lessons are generally applicable and others pertain exclusively to certain project types.

Strategic knowledge serendipity and arbitrage & intellectual venture capitalists: An emerging breed of knowledge entrepreneurs; and Part II: Global and Local (GloCal) knowledge logistics for innovation and competitiveness. ACES Working Papers, August 2009

Strategic Knowledge: While entrepreneurship may occur as a natural result of personal drive, it occurs most often, most robustly and is most sustainable in an environment designed to encourage it. Potential entrepreneurs become active entrepreneurs when the conditions are most supportive of their commercial opportunities and their business thus helping channel the two key qualities they exhibit as individuals obsessed maniacs and clairvoyant oracles (Carayannis, GWU Lectures, 2000-2005) and (Carayannis et at, 2003a) towards the generation of sustainable wealth. So far, entrepreneurial scholars who turn into intellectual venture capitalists by founding knowledge-driven companies remain one of the least explored specie in the territory of entrepreneurship. GloCal: The increasing engagement of firms within global knowledge and production networks and their ability to source knowledge globally as well as locally (GloCally), for the development of innovation capacities will shape the future of UK's knowledge resources and its role in the global economy. Practices such as off-shoring R&D activities are widely adopted, creating challenging, and not very well understood, issues related to cross-country and inter-firm knowledge and technology flows. We seek to address the internationalisation and networking of research and innovation activities, including the roles and strategies of enterprises, universities, research centres, governments in a cross-country and inter-sectoral way, to assess the impact and the implications for sustaining and enhancing the competitiveness of UK firms and other British knowledge producers and users.

Global and local (GloCal) knowledge logistics for innovation and competitiveness. ACES Working Papers, August 2010

The increasing engagement of firms within global knowledge and production networks and their ability to source knowledge globally as well as locally (GloCally), for the development of innovation capacities will shape the future of UK's knowledge resources and its role in the global economy. Practices such as off-shoring R&D activities are widely adopted, creating challenging, and not very well understood, issues related to cross-country and inter-firm knowledge and technology flows. We seek to address the internationalisation and networking of research and innovation activities, including the roles and strategies of enterprises, universities, research centres, governments in a cross-country and inter-sectoral way, to assess the impact and the implications for sustaining and enhancing the competitiveness of UK firms and other British knowledge producers and users.

Capturing expert knowledge for threatened species assessments: a case study using NatureServe conservation status ranks

Assessments for assigning the conservation status of threatened species that are based purely on subjective judgements become problematic because assessments can be influenced by hidden assumptions, personal biases and perceptions of risks, making the assessment process difficult to repeat. This can result in inconsistent assessments and misclassifications, which can lead to a lack of confidence in species assessments. It is almost impossible to Understand an expert's logic or visualise the underlying reasoning behind the many hidden assumptions used throughout the assessment process. In this paper, we formalise the decision making process of experts, by capturing their logical ordering of information, their assumptions and reasoning, and transferring them into a set of decisions rules. We illustrate this through the process used to evaluate the conservation status of species under the NatureServe system (Master, 1991). NatureServe status assessments have been used for over two decades to set conservation priorities for threatened species throughout North America. We develop a conditional point-scoring method, to reflect the current subjective process. In two test comparisons, 77% of species' assessments using the explicit NatureServe method matched the qualitative assessments done subjectively by NatureServe staff. Of those that differed, no rank varied by more than one rank level under the two methods. In general, the explicit NatureServe method tended to be more precautionary than the subjective assessments. The rank differences that emerged from the comparisons may be due, at least in part, to the flexibility of the qualitative system, which allows different factors to be weighted on a species-by-species basis according to expert judgement. The method outlined in this study is the first documented attempt to explicitly define a transparent process for weighting and combining factors under the NatureServe system. The process of eliciting expert knowledge identifies how information is combined and highlights any inconsistent logic that may not be obvious in Subjective decisions. The method provides a repeatable, transparent, and explicit benchmark for feedback, further development, and improvement. (C) 2004 Elsevier SAS. All rights reserved.

Attributes of identity document credibility: A synthesis of expert knowledge

In broad terms — including a thief's use of existing credit card, bank, or other accounts — the number of identity fraud victims in the United States ranges 9-10 million per year, or roughly 4% of the US adult population. The average annual theft per stolen identity was estimated at $6,383 in 2006, up approximately 22% from $5,248 in 2003; an increase in estimated total theft from $53.2 billion in 2003 to $56.6 billion in 2006. About three million Americans each year fall victim to the worst kind of identity fraud: new account fraud. Names, Social Security numbers, dates of birth, and other data are acquired fraudulently from the issuing organization, or from the victim then these data are used to create fraudulent identity documents. In turn, these are presented to other organizations as evidence of identity, used to open new lines of credit, secure loans, “flip” property, or otherwise turn a profit in a victim's name. This is much more time consuming — and typically more costly — to repair than fraudulent use of existing accounts. ^ This research borrows from well-established theoretical backgrounds, in an effort to answer the question – what is it that makes identity documents credible? Most importantly, identification of the components of credibility draws upon personal construct psychology, the underpinning for the repertory grid technique, a form of structured interviewing that arrives at a description of the interviewee’s constructs on a given topic, such as credibility of identity documents. This represents substantial contribution to theory, being the first research to use the repertory grid technique to elicit from experts, their mental constructs used to evaluate credibility of different types of identity documents reviewed in the course of opening new accounts. The research identified twenty-one characteristics, different ones of which are present on different types of identity documents. Expert evaluations of these documents in different scenarios suggest that visual characteristics are most important for a physical document, while authenticated personal data are most important for a digital document. ^

Attributes of Identity Document Credibility: A Synthesis of Expert Knowledge

In broad terms — including a thief's use of existing credit card, bank, or other accounts — the number of identity fraud victims in the United States ranges 9-10 million per year, or roughly 4% of the US adult population. The average annual theft per stolen identity was estimated at $6,383 in 2006, up approximately 22% from $5,248 in 2003; an increase in estimated total theft from $53.2 billion in 2003 to $56.6 billion in 2006. About three million Americans each year fall victim to the worst kind of identity fraud: new account fraud. Names, Social Security numbers, dates of birth, and other data are acquired fraudulently from the issuing organization, or from the victim then these data are used to create fraudulent identity documents. In turn, these are presented to other organizations as evidence of identity, used to open new lines of credit, secure loans, “flip” property, or otherwise turn a profit in a victim's name. This is much more time consuming — and typically more costly — to repair than fraudulent use of existing accounts. This research borrows from well-established theoretical backgrounds, in an effort to answer the question – what is it that makes identity documents credible? Most importantly, identification of the components of credibility draws upon personal construct psychology, the underpinning for the repertory grid technique, a form of structured interviewing that arrives at a description of the interviewee’s constructs on a given topic, such as credibility of identity documents. This represents substantial contribution to theory, being the first research to use the repertory grid technique to elicit from experts, their mental constructs used to evaluate credibility of different types of identity documents reviewed in the course of opening new accounts. The research identified twenty-one characteristics, different ones of which are present on different types of identity documents. Expert evaluations of these documents in different scenarios suggest that visual characteristics are most important for a physical document, while authenticated personal data are most important for a digital document.

Comparing architectural styles for distributed expert knowledge modules in intelligent tutoring systems

Intelligent Tutoring Systems (ITSs) are computerized systems for learning-by-doing. These systems provide students with immediate and customized feedback on learning tasks. An ITS typically consists of several modules that are connected to each other. This research focuses on the distribution of the ITS module that provides expert knowledge services. For the distribution of such an expert knowledge module we need to use an architectural style because this gives a standard interface, which increases the reusability and operability of the expert knowledge module. To provide expert knowledge modules in a distributed way we need to answer the research question: ‘How can we compare and evaluate REST, Web services and Plug-in architectural styles for the distribution of the expert knowledge module in an intelligent tutoring system?’. We present an assessment method for selecting an architectural style. Using the assessment method on three architectural styles, we selected the REST architectural style as the style that best supports the distribution of expert knowledge modules. With this assessment method we also analyzed the trade-offs that come with selecting REST. We present a prototype and architectural views based on REST to demonstrate that the assessment method correctly scores REST as an appropriate architectural style for the distribution of expert knowledge modules.

Mapping of Submerged Aquatic Vegetation in Rivers From Very High Resolution Image Data, Using Object Based Image Analysis Combined with Expert Knowledge

The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.

Applicability of a distributed watershed pollution model in a data-poor environment in Santa Catarina State, Brazil

Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.