DETERMINANTS OF THE ADOPTION OF INTEGRATED SOIL FERTILITY MANAGEMENT TECHNOLOGIES IN MBALE DIVISION, KENYA

The agro-climatic conditions in western Kenya present the region as a food surplus area yet people are still reliant on food imports, with the region registering high poverty levels. Depletion of soil fertility and the resulting decline in agricultural productivity in Mbale division has led to many attempts to develop and popularize Integrated Soil Fertility Management (ISFM) technologies that could restore soil fertility. These technologies bridge the gap between high external inputs and extreme forms of traditional low external input agriculture. Some of the ISFM components used by farmers are organic and inorganic inputs and improved seeds. However, the adoption of these technologies is low. The study aimed to examine the factors that influence the adoption of ISFM technologies by smallholder farmers in Mbale division, Kenya. The study was conducted in 9 sub-locations in Mbale division. Purposive sampling was used in selecting the 80 farmers to get the data based on a farm-household survey. Self-administered questionnaires were used to collect data on the determinants of the adoption of ISFM technologies from the sampled farmers in the study area. The study sought to answer the research question: What factors influence the uptake of ISFM technologies by farmers in Mbale division? The hypothesis tested was that the adoption of ISFM technologies is not influenced by age, education, extension services, labour, off-farm income and farm size. Data was analyzed using descriptive statistics. Cross tabulation was used for examining the relationship between categorical (nominal or ordinal) variables, and the bivariate correlations procedure was used to compute the pair wise associations between scale or ordinal variables. Probit regression was used to predict the socio-economic factors influencing the adoption of ISFM technologies among smallholder farmers. Results of the study indicated that education of household head, membership in social groups, age of the household head, off-farm income and farm size were the variables that significantly influenced the adoption of ISFM technologies. The findings show that there is need for a more pro-poor focused approach to achieve sustainable soil fertility management among smallholder farmers. The findings will help farmers, extension officers, researchers and donors in identifying region-specific entry points that can help in developing innovative ISFM technologies.

The Effect of Private Management of Public Schools on Student Achievement in Bogotá, Colombia

During the last 15 years, the public school system in Bogotá, Colombia has maintained a concession system in which 25 schools are managed privately with exemptions to many of the rules required in the traditional schools -- This study uses the propensity score matching technique to examine whether students in the privately-managed schools have better scores on the Saber 11° examinations taken upon completion of secondary school -- The results for 251 schools indicates that students with comparable socioeconomic characteristics score considerably better on these tests in the privately-managed schools than in the traditional public schools -- Thus, there is evidence that the privately-managed public schools are a cost-effective alternative to the traditional public school

Traditional part-time grazing: a more sustainable sheep milk and cheese production in the Basque Country

[EN] The concept of sustainability when referring to food production rests, in general, on 3 main aspects: 1) respect for the environment; 2) economic and social benefits for all involved in production; and 3) production of sufficient quantity of quality food at an accessible price. In this contribution we focus on the main aspects of the traditional sheep's milk and cheese production (under the Denomination of Origin Idiazabal Cheese) in the Basque Country that contribute primarily to its sustainability. It is based on the local latxa or carranzana breeds of sheep, adapted to the mountainous terrain. The sheepherder takes advantage of local resources to reduce management costs by combining indoor dry forage and concentrates with outdoor grazing throughout lactation, according to local pasture availability, and thus avoiding having to buy large amounts of feed. This system facilitates recycling of manure, fertilising pastures and forest at the same time. Use of local breeds helps maintain biodiversity of sheep breeds. Cheese is produced industrially (44.5% of the total cheese produced in 2008) from milk of many flocks, or artisanally (38.3%) by the sheepherders with the milk from their own flocks. Transforming their own milk into cheese is advantageous for the following reasons: 1) higher economic returns as compared to selling the milk to cheese factories because cheese price directly sold to consumers is more competitive than industrial cheese sold in supermarkets; 2) increases the value of women's work (over 80% of the cheese makers are women) in the community and their self-esteem; 3) it creates rural jobs and contributes to rural development; 4) we have demonstrated both with experimental and commercial flocks that part-time grazing allows the sheepherder to obtain high yields of milk, and cheese, of high nutritional and functional quality. Currently a less sustainable, intensive sheep's milk production with foreign, imported breeds kept indoors constantly is gaining favour among milk producers because of its perceived higher economic profitability.

Limnology of Macrobrachium amazonicum grow-out ponds subject to high inflow of nutrient-rich water and different stocking and harvest management

We evaluated the water characteristics and particle sedimentation in Macrobrachium amazonicum (Heller 1862) grow-out ponds supplied with a high inflow of nutrient-rich water. Prawns were subject to different stocking and harvesting strategies: upper-graded juveniles, lower-graded juveniles, non-graded juveniles + selective harvesting and traditional farming (non-grading juveniles and total harvest only). Dissolved oxygen, afternoon N-ammonia and N-nitrate and soluble orthophosphate were lower in the ponds in comparison with inflow water through the rearing cycle. Ponds stocked with the upper population fraction of graded prawns showed higher turbidity, total suspended solids and total Kjeldahl nitrogen than the remaining treatments. An increase in the chemical oxygen demand:biochemical oxygen demand ratio from inlet (4.9) to pond (7.1-8.0) waters indicated a non-readily biodegradable fraction enhancement in ponds. The sedimentation mean rate ranged from 0.08 to 0.16 mm day(-1) and sediment contained >80% of organic matter. The major factors affecting pond ecosystem dynamic were the organic load (due to primary production and feed addition) and bioturbation caused by stocking larger animals. Data suggest that M. amazonicum grow-out in ponds subjected to a high inflow of nutrient-rich water produce changes in the water properties, huge accumulation of organic sediment at the pond bottom and non-readily biodegradable material in the water column. However, the water quality remains suitable for aquaculture purposes. Therefore, nutrient-rich waters, when available, may represent a source of unpaid nutrients, which may be incorporated into economically valued biomass if managed properly.

SYSTEM DYNAMICS MODELING AS A QUANTITATIVE-QUALITATIVE FRAMEWORK FOR SUSTAINABLE WATER RESOURCES MANAGEMENT: INSIGHTS FOR WATER QUALITY POLICY IN THE GREAT LAKES REGION

Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in the Great Lakes basin. The traditional linear thinking paradigm lacks the mental and organizational framework for sustainable development trajectories, and may lead to quick-fix solutions that fail to address key drivers of water resources problems. To facilitate holistic analysis of water resources systems, systems thinking seeks to understand interactions among the subsystems. System dynamics provides a suitable framework for operationalizing systems thinking and its application to water resources problems by offering useful qualitative tools such as causal loop diagrams (CLD), stock-and-flow diagrams (SFD), and system archetypes. The approach provides a high-level quantitative-qualitative modeling framework for "big-picture" understanding of water resources systems, stakeholder participation, policy analysis, and strategic decision making. While quantitative modeling using extensive computer simulations and optimization is still very important and needed for policy screening, qualitative system dynamics models can improve understanding of general trends and the root causes of problems, and thus promote sustainable water resources decision making. Within the system dynamics framework, a growth and underinvestment (G&U) system archetype governing Lake Allegan's eutrophication problem was hypothesized to explain the system's problematic behavior and identify policy leverage points for mitigation. A system dynamics simulation model was developed to characterize the lake's recovery from its hypereutrophic state and assess a number of proposed total maximum daily load (TMDL) reduction policies, including phosphorus load reductions from point sources (PS) and non-point sources (NPS). It was shown that, for a TMDL plan to be effective, it should be considered a component of a continuous sustainability process, which considers the functionality of dynamic feedback relationships between socio-economic growth, land use change, and environmental conditions. Furthermore, a high-level simulation-optimization framework was developed to guide watershed scale BMP implementation in the Kalamazoo watershed. Agricultural BMPs should be given priority in the watershed in order to facilitate cost-efficient attainment of the Lake Allegan's TP concentration target. However, without adequate support policies, agricultural BMP implementation may adversely affect the agricultural producers. Results from a case study of the Maumee River basin show that coordinated BMP implementation across upstream and downstream watersheds can significantly improve cost efficiency of TP load abatement.

Geospatial Data Indexing Analysis and Visualization via Web Services with Autonomic Resource Management

With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.

OpenDataHub: an open dataset management system

This thesis presents a cloud-based software platform for sharing publicly available scientific datasets. The proposed platform leverages the potential of NoSQL databases and asynchronous IO technologies, such as Node.JS, in order to achieve high performances and flexible solutions. This solution will serve two main groups of users. The dataset providers, which are the researchers responsible for sharing and maintaining datasets, and the dataset users, that are those who desire to access the public data. To the former are given tools to easily publish and maintain large volumes of data, whereas the later are given tools to enable the preview and creation of subsets of the original data through the introduction of filter and aggregation operations. The choice of NoSQL over more traditional RDDMS emerged from and extended benchmark between relational databases (MySQL) and NoSQL (MongoDB) that is also presented in this thesis. The obtained results come to confirm the theoretical guarantees that NoSQL databases are more suitable for the kind of data that our system users will be handling, i. e., non-homogeneous data structures that can grow really fast. It is envisioned that a platform like this can lead the way to a new era of scientific data sharing where researchers are able to easily share and access all kinds of datasets, and even in more advanced scenarios be presented with recommended datasets and already existing research results on top of those recommendations.

OpenDataHub: an open dataset management system

This thesis presents a cloud-based software platform for sharing publicly available scientific datasets. The proposed platform leverages the potential of NoSQL databases and asynchronous IO technologies, such as Node.JS, in order to achieve high performances and flexible solutions. This solution will serve two main groups of users. The dataset providers, which are the researchers responsible for sharing and maintaining datasets, and the dataset users, that are those who desire to access the public data. To the former are given tools to easily publish and maintain large volumes of data, whereas the later are given tools to enable the preview and creation of subsets of the original data through the introduction of filter and aggregation operations. The choice of NoSQL over more traditional RDDMS emerged from and extended benchmark between relational databases (MySQL) and NoSQL (MongoDB) that is also presented in this thesis. The obtained results come to confirm the theoretical guarantees that NoSQL databases are more suitable for the kind of data that our system users will be handling, i. e., non-homogeneous data structures that can grow really fast. It is envisioned that a platform like this can lead the way to a new era of scientific data sharing where researchers are able to easily share and access all kinds of datasets, and even in more advanced scenarios be presented with recommended datasets and already existing research results on top of those recommendations.

Irrigation management with remote sensing: Evaluating irrigation requirement for maize under Mediterranean climate condition

tWater use control methods and water resources planning are of high priority. In irrigated agriculture, theright way to save water is to increase water use efficiency through better management. The present workvalidates procedures and methodologies using remote sensing to determine the water availability in thesoil at each moment, giving the opportunity for the application of the water depth strictly necessaryto optimise crop growth (optimum irrigation timing and irrigation amount). The analysis is applied tothe Irrigation District of Divor, Évora, using 7 experimental plots, which are areas irrigated by centre-pivot systems, cultivated to maize. Data were determined from images of the cultivated surface obtainedby satellite and integrated with atmosphere and crop parameters to calculate biophysical indicatorsand indices of water stress in the vegetation—Normalized Difference Vegetation Index (NDVI), Kc, andKcb. Therefore, evapotranspiration (ETc) was estimated and used to calculate crop water requirement,together with the opportunity and the amount of irrigation water to allocate. Although remote sensingdata available from satellite imagery presented some practical constraints, the study could contribute tothe validation of a new methodology that can be used for irrigation management of a large irrigated area,easier and at lower costs than the traditional FAO recommended crop coefficients method. The remotesensing based methodology can also contribute to significant saves of irrigation water.

Enzymatic activity on sediments and nematode assemblage responses during seagrass beds habitat recovery following the disturbance of the traditional digging activity of bivalves harvesting.

Sediment digging is an anthropogenic activity connected to the exploitation of living resources in estuarine and marine environments. The knowledge on the functional responses of the benthic assemblages to the physical disturbance is an important baseline to understand the ecological processes of the habitat recovery and restoration and to develop tools for the management of the harvesting activities. To investigate the effects of the digging activity of the bivalves on Zostera noltii seagrass beds a manipulative field experiment was conducted that included the enzymatic activity of sediments and the associated nematode assemblages. Four plots (two undisturbed serving as control and two dug to collect bivalves - treatment) with 18 subplots were randomly located at seagrass beds in the Mira estuary at the SW coast of Portugal. Samples were randomly and unrepeatably collected from three subplots of each plot in five different occasions, before sediment digging (T0) up to six months after disturbance (T5). Microbial activity in sediments was assess by determining the extracelular enzymatic activity of six hydrolytic enzymes (sulfatase, phosphatase, b -N-acetilglucosaminidase, b-glucosidase, urease, protease) and two oxidoreductases (phenol oxidase and peroxidase). The microbial community status was also assessed through the measurement of dehydrogenase, which reflects microbial respiration. The nematode assemblages composition, biodiversity and trophic composition at different sampling occasions were also analyzed. The fluorometric and biochemical parameters analysed of the Z. noltii plants during the experimental period showed a recovery of the seagrass beds, and it was detected an increase of the enzymatic activity of the sediments after disturbance. The nematodes assemblages were similar in all sampling occasions. The seagrass beds and the nematodes assemblages associated showed a high resilience to the stress caused by the traditional bivalves digging activity. The obtained results allow the development of a management programme for the commercial fishing activity to maintain the good environmental status and minimized the secondary environmental effects on marine and estuarine habitats through the establishment of a baseline for the regulation of the harvesting frequency.

Development of super early genotypes for the dry bean (Phaseolus vulgaris) as affected by nitrogen management.

The super early genotypes (SEG) of dry bean (Phaseolus vulgaris L.) have a shorter life cycle (65-75 days) when compared with the season length of traditional cultivars (90-100 days). Timing of nitrogen top-dressing fertilization could be different because of this reduction in length of the SEG life cycle. This study aimed at characterizing, by using growth analysis and vegetation index, super early genotypes of dry bean development as affected by timing of nitrogen application. Field experiments were conducted in the 2014 and 2015 growing seasons in central Brazil with a randomized block experimental design with split plots scheme and four replicates. The plots comprised the dry bean genotypes (Colibri ? check cultivar, CNFC 15873, CNFC 15874, and CNFC 15875), and subplots comprised applications of N at different timings: 90 kg of N at sowing, 90 kg N at top-dressing; 45 kg of N at sowing plus 45 kg at top-dressing, with urea as the source of N. We also used a control treatment without N application. The CNFC 15874 super early genotype of dry bean had the higher grain yield (2776 kg ha-1) and differed from the CNFC 15873 genotype (2492 kg ha-1). Nitrogen fertilization allowed higher grain yield (2619 kg ha-1, when applied N at sowing, 2605 kg ha-1, when applied N at sowing and at top-dressing, and 2680 kg ha-1, when applied N at top-dressing) than the control, 2360 kg ha-1 (no N fertilization). The time of N fertilization in super early genotype of dry bean did not affect grain yield.