Abundance of mesozooplankton in the western part of the Black Sea in summer 2005 during Phase 2: Leg1 from the GEF Project

The sampling area was extended to the Western-South area off the Black Sea coast from Kaliakra cape toward the Bosforous. Samples were collected along four transects. The whole dataset is composed of 17 samples (from 10 stations) with data of mesozooplankton species composition abundance and biomass. Sampling for zooplankton was performed from bottom up to the surface at depths depending on water column stratification and the thermocline depth. These data are organized in the "Control of eutrophication, hazardous substances and related measures for rehabilitating the Black Sea ecosystem: Phase 2: Leg I: PIMS 3065". Data Report is not published. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Abundance of mesozooplankton in the western part of the Black Sea in autumn 1999 during the National Monitoring Programme

The dataset is based on samples collected in the summer of 1999 in the Western Black Sea in front of Bulgaria coast. The whole dataset is composed of 59 samples (from 24 stations of National Monitoring Grid) with data of mesozooplankton species composition abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Abundance of mesozooplankton in the western part of the Black Sea in spring 1997 during the National Monitoring Programme

The "15BO1997001" dataset is based on samples collected in the spring of 1997. The whole dataset is composed of 66 samples (from 27 stations of National Monitoring Sampling Grid) with data of zooplankton species composition, abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Biomass of mesozooplankton in the western part of the Black Sea in 1997 during the Cooperative Marine Science Program for the Black Sea (CoMSBlack)

The "15BO1997001" dataset is based on samples collected in the spring of 1997. The whole dataset is composed of 66 samples (from 27 stations of National Monitoring Sampling Grid) with data of zooplankton species composition, abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. The collected material was analysed using the method of Dimov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972 ). The biomass was estimated as wet weight by Petipa, 1959 (based on species specific wet weight). Wet weight values were transformed to dry weight using the equation DW=0.16*WW as suggested by Vinogradov & Shushkina, 1987. The collected material was analysed using the method of Dimov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972 ). The biomass was estimated as wet weight by Petipa, 1959 ussing standard average weight of each species in mg/m3. WW were converted to DW by equation DW=0.16*WW (Vinogradov ME, Sushkina EA, 1987).

Abundance of mesozooplankton in the western part of the Black Sea in summer 1991 during the NATO Programme Hydroblack

The "Hydroblack91" dataset is based on samples collected in the summer of 1991 and covers part of North-Western in front of Romanian coast and Western Black Sea (Bulgarian coasts) (between 43°30' - 42°10' N latitude and 28°40'- 31°45' E longitude). Mesozooplankton sampling was undertaken at 20 stations. The whole dataset is composed of 72 samples with data of zooplankton species composition, abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length Mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Abundance of mesozooplankton in the western part of the Black Sea in spring 2002 during the National Monitoring Programme of the Bulgarian Institute of Oceanography

The dataset is based on samples collected in the spring of 2002 in the Western Black Sea in front of Bulgaria coast. The whole dataset is composed of 76 samples (from 27 stations of National Monitoring Grid) with data of mesozooplankton species composition abundance and biomass. Sampling on zooplankton was performed from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Isotopic composition of ground ice, ebullition gases and thermokarst lake water, North America

Thermokarst lakes are thought to have been an important source of methane (CH4) during the last deglaciation when atmospheric CH4 concentrations increased rapidly. Here we demonstrate that meltwater from permafrost ice serves as an H source to CH4 production in thermokarst lakes, allowing for region-specific reconstructions of dD-CH4 emissions from Siberian and North American lakes. dD CH4 reflects regionally varying dD values of precipitation incorporated into ground ice at the time of its formation. Late Pleistocene-aged permafrost ground ice was the dominant H source to CH4 production in primary thermokarst lakes, whereas Holocene-aged permafrost ground ice contributed H to CH4 production in later generation lakes. We found that Alaskan thermokarst lake dD-CH4 was higher (-334 ± 17 per mil) than Siberian lake dD-CH4 (-381 ± 18 per mil). Weighted mean dD CH4 values for Beringian lakes ranged from -385 per mil to -382 per mil over the deglacial period. Bottom-up estimates suggest that Beringian thermokarst lakes contributed 15 ± 4 Tg CH4 /yr to the atmosphere during the Younger Dryas and 25 ± 5 Tg CH4 /yr during the Preboreal period. These estimates are supported by independent, top-down isotope mass balance calculations based on ice core dD-CH4 and d13C-CH4 records. Both approaches suggest that thermokarst lakes and boreal wetlands together were important sources of deglacial CH4.

Abundance of mesozooplankton in the western part of the Black Sea during the 2001 National Monitoring Programme of the Bulgarian Institute of Oceanography

The dataset is based on samples collected in the autumn of 2001 in the Western Black Sea in front of Bulgaria coast. The whole dataset is composed of 42 samples (from 19 stations of National Monitoring Grid) with data of mesozooplankton species composition abundance and biomass. Samples were collected in the layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Cenozoic sediments facies and geochemistry of ODP Hole 103-637A

The late Cenozoic deposits recovered at ODP Site 637 from the Iberian Abyssal Plain near the continental margin off northwestern Spain include three main facies groups. Turbidites are the dominant facies association (two-thirds of the total thickness), followed by pelagites (one-fourth), and subordinate amounts of contourites (one-tenth). Slump deposits occur locally in the upper Miocene and middle Pliocene. Turbidity currents and pelagic settling were the significant sediment depositional processes from the Pliocene to the Pleistocene, whereas bottom currents predominated during the late Miocene. Fine-grained, base-cut-out turbidites, normally starting with the Td division, are the most abundant sequence type. The pelagites include both carbonate-rich pelagic and hemipelagic facies. The two types of contourites, sandy and calcareous-rich or fine-grained terrigenous, record two types of bottom-current processes. The Cenozoic deposits at Site 637 show a general upward transition from contourites in the upper Miocene to turbidites in the Pliocene-Quaternary. The entire section is rhythmically bedded and has a poorly developed cyclic pattern defined by variations in the total carbonate content. The low sedimentation rates also show the same cyclicity, with lower values for the late Miocene and late Pliocene. This evolution reflects the predominant depositional processes and the dissolution of carbonates by a lower CCD during the late Miocene.

Biomass of mesozooplankton in the western part of the Black Sea in 1992 during the Cooperative Marine Science Program for the Black Sea (CoMSBlack)

The "CoMSBlack92" dataset is based on samples collected in the summer of 1992 along the Bulgarian coast including coastal and open sea areas. The whole dataset is composed of 79 samples (28 stations) with data of zooplankton species composition, abundance and biomass. Sampling for zooplankton was performed from bottom up to the surface at standard depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 ?m. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Sampling volume was estimated by multiplying the mouth area with the wire length. The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972 ). The biomass was estimated as wet weight by Petipa, 1959 (based on species specific wet weight). Wet weight values were transformed to dry weight using the equation DW=0.16*WW as suggested by Vinogradov & Shushkina, 1987. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. The biomass was estimated as wet weight by Petipa, 1959 ussing standard average weight of each species in mg/m**3.

Biomass of mesozooplankton in the western part of the Black Sea in summer 1991 during the NATO Programme Hydroblack

The "Hydroblack91" dataset is based on samples collected in the summer of 1991 and covers part of North-Western in front of Romanian coast and Western Black Sea (Bulgarian coasts) (between 43°30' - 42°10' N latitude and 28°40'- 31°45' E longitude). Mesozooplankton sampling was undertaken at 20 stations. The whole dataset is composed of 72 samples with data of zooplankton species composition, abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected materia was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). The biomass was estimated as wet weight by Petipa, 1959 (based on species specific wet weight). Wet weight values were transformed to dry weight using the equation DW=0.16*WW as suggested by Vinogradov & Shushkina, 1987. Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). The biomass was estimated as wet weight by Petipa, 1959 ussing standard average weight of each species in mg/m3. WW were converted to DW by equation DW=0.16*WW (Vinogradov ME, Sushkina EA, 1987).

Case Study of Applied LIP Approach/Activities in the Philippines The Training Services Enhancement Project for Rural Life Improvement (TSEP-RLI) Experience

TSEP-RLI was a technical cooperation project jointly conducted by GOP thru DA-Agricultural Training Institute (ATI) and GOJ thru JICA aimed at institutionalizing the training program for Rural Life Improvement (RLI) at the (ATI). As expected, farmers, fisherfolk, women, youth and extension agents were provided with efficient and effective training services from ATI leading to the improvement of quality of life in the rural areas through efforts of human resource development. The ATI- Bohol was chosen as the model center where participatory trials and various activities of the project were undertaken for five years. These activities were participatory surveys and data collection of on-farm and off-farm productive activities; planning workshop for RLI; feedbacking of survey results and action plans to the community and the Local Government Units (LGUs), and signing of Memorandum of Agreement between the Project and participating LGUs. The above activities were done to facilitate the planning and development of most effective and necessary rural life improvement activities, to confirm the willingness of the people to support and participate and to formalize the partnership between the Project and the LGUs. Since the concept of rural life covers a vast range of activities, a consensus had been reached that the total aspects of rural life be grasped in three spheres, namely, Production & Livelihood (P/L), Rural Living Condition (RLC) and Community Environment (C/E). The RLI for Ubi (Yam) Growers was one of the pilot activities undertaken in two pilot barangays and the target beneficiaries were members of the Rural Improvement Club (RIC- a group of organized women) with the LGU of the Municipality of Corella as the implementing partner. During the planning workshop, the barangay residents articulated their desire to promote production and processing of ubi (sphere on P/L - as the entry point), lack of nutritious food was one of the identified problem (sphere on RLC- expansion point) and environmental degradation such as deforestation, and soil erosion was another problem articulated by the community people (sphere on C/E- expansion point). Major activities that were undertaken namely, Ubi cooking contest, cooking/processing seminar, training courses on entrepreneurial development, ubi production and storage technology, packaging and product design, human resource development and simplified bookkeeping motivated the beneficiaries as well as developed and enhanced their skills & capabilities while strengthening their associations. Their participation to the 5 ubi festivals and other related activities had brought some impacts on their economic and rural life improvement activities. The seven principles of TSEP-RLI include the participatory process, holistic approach, dialogical approach, bottom -up training needs assessment, demand-driven approach, cost sharing approach and collaborative implementation with other agencies including LGUs and the community.

Migration as a rural development strategy and the migrants involved : an account of a migrants' hometown in Sichuan, China

This paper attempts to describe part of the history of Chinese rural migration to urban industrial areas. Using a case study of a township in Sichuan, the author examines a type of rural development which she defines as a "bottom-up" style strategy of regional development. Different types of social mobility are observed in the case study, and over its long history, migration in the township has offered diverse means of social mobility to the local peasants. The paper concludes by considering the diversity and limits of Chinese social mobility at this stage.

Exploiting goal independence in the analysis of logic programs

This paper illustrates the use of a top-down framework to obtain goal independent analyses of logic programs, a task which is usually associated with the bottom-up approach. While it is well known that the bottomup approach can be used, through the magic set transformation, for goal dependent analysis, it is less known that the top-down approach can be used for goal independent analysis. The paper describes two ways of doing the latter. We show how the results of a goal independent analysis can be used to speed up subsequent goal dependent analyses. However this speed-up may result in a loss of precisión. The influence of domain characteristics on this precisión is discussed and an experimental evaluation using a generic top-down analyzer is described.

A Method for Developing Ontologies from User-Generated Classication Systems

Abstract Web 2.0 applications enabled users to classify information resources using their own vocabularies. The bottom-up nature of these user-generated classification systems have turned them into interesting knowledge sources, since they provide a rich terminology generated by potentially large user communities. Previous research has shown that it is possible to elicit some emergent semantics from the aggregation of individual classifications in these systems. However the generation of ontologies from them is still an open research problem. In this thesis we address the problem of how to tap into user-generated classification systems for building domain ontologies. Our objective is to design a method to develop domain ontologies from user-generated classifications systems. To do so, we rely on ontologies in the Web of Data to formalize the semantics of the knowledge collected from the classification system. Current ontology development methodologies have recognized the importance of reusing knowledge from existing resources. Thus, our work is framed within the NeOn methodology scenario for building ontologies by reusing and reengineering non-ontological resources. The main contributions of this work are: An integrated method to develop ontologies from user-generated classification systems. With this method we extract a domain terminology from the classification system and then we formalize the semantics of this terminology by reusing ontologies in the Web of Data. Identification and adaptation of existing techniques for implementing the activities in the method so that they can fulfill the requirements of each activity. A novel study about emerging semantics in user-generated lists. Resumen La web 2.0 permitió a los usuarios clasificar recursos de información usando su propio vocabulario. Estos sistemas de clasificación generados por usuarios son recursos interesantes para la extracción de conocimiento debido principalmente a que proveen una extensa terminología generada por grandes comunidades de usuarios. Se ha demostrado en investigaciones previas que es posible obtener una semántica emergente de estos sistemas. Sin embargo la generación de ontologías a partir de ellos es todavía un problema de investigación abierto. Esta tesis trata el problema de cómo aprovechar los sistemas de clasificación generados por usuarios en la construcción de ontologías de dominio. Así el objetivo de la tesis es diseñar un método para desarrollar ontologías de dominio a partir de sistemas de clasificación generados por usuarios. El método propuesto reutiliza conceptualizaciones existentes en ontologías publicadas en la Web de Datos para formalizar la semántica del conocimiento que se extrae del sistema de clasificación. Por tanto, este trabajo está enmarcado dentro del escenario para desarrollar ontologías mediante la reutilización y reingeniería de recursos no ontológicos que se ha definido en la Metodología NeOn. Las principales contribuciones de este trabajo son: Un método integrado para desarrollar una ontología de dominio a partir de sistemas de clasificación generados por usuarios. En este método se extrae una terminología de dominio del sistema de clasificación y posteriormente se formaliza su semántica reutilizando ontologías en la Web de Datos. La identificación y adaptación de un conjunto de técnicas para implementar las actividades propuestas en el método de tal manera que puedan cumplir automáticamente los requerimientos de cada actividad. Un novedoso estudio acerca de la semántica emergente en las listas generadas por usuarios en la Web.