Geographic information system techniques were used in combination with remote sensing data to define the net commercial value of standing timber at two sites (Batouri and Bertoua) in the East province of Cameroon. Observed forest cover modifications for the two sites were assessed in relation to the commercial accessibility of the forest areas. Results showed that, in one site, half of the very high rent areas have already been logged indicating that the unlogged high rent area is scarce and the low rent or marginal forest area remains largely unlogged. However, this was not the case throughout the study area as shown by the observations at the other site. The two main species exploited were sapelli (Entandrophragma cylindricum) and Ayous Triplochiton scleroxylon.
Tag: mathematical models
Quantitative Support of Decision Making under Uncertainty
Supporting the quantitative analysis of binary welfare based decision making processes using Monte Carlo simulations. Decision support is given on two levels: (i) The actual decision level is to choose between two alternatives under probabilistic uncertainty. This package calculates the optimal decision based on maximizing expected welfare. (ii) The meta decision level is to allocate resources to reduce the uncertainty in the underlying decision problem, i.e to increase the current information to improve the actual decision making process. This problem is dealt with using the Value of Information Analysis. The Expected Value of Information for arbitrary prospective estimates can be calculated as well as Individual Expected Value of Perfect Information. The probabilistic calculations are done via Monte Carlo simulations. This Monte Carlo functionality can be used on its own.
The structure and pattern of global partnerships in the REDD+ mechanism
Projects for reducing emissions from deforestation and forest degradation (REDD+) have been initiated in developing countries, featuring partnerships with multiple actors under the global forest and climate change regime. Even though partnerships between stakeholders are crucial for ensuring successful project deliveries, there is a lack of knowledge about sectoral partnerships within and between stakeholders in REDD+ projects. This study aims to measure the structures and patterns of REDD+ project partnerships using an original, multi-stage social network theory approach with global- and regional-level centralization analyses using three major regions (Asia, Africa and South America), and configurations using exponential random graph modeling (ERGM). Using data on 480 REDD+ projects implemented in 57 countries, results show concentrated polycentric networks across several dominant actors, including USA-, Brazil- and China-based organizations. Statistical network modeling indicates that, overall, partnerships are less likely to be created between different organization categories (across-type bridging), but tend more towards cooperation with the same types (within-type bridging). Research institutes, however, produce distinctly different patterns, forming across-type partnerships with highly technical capacities. Comparisons of stakeholders at different stages of the REDD+ mechanism help in understanding the complete picture of REDD+ architecture. This study contributes by offering insights for designing future partnerships within REDD+ projects and suggests ways to improve multi-level collaboration and cooperation.
Cassava Production Efficiency in Southern Ethiopia: The Parametric Model Analysis
Due to capital constraints and land scarcity in developing countries, introducing new technology to boost productivity is difficult. As a result, working to improve cassava production efficiency is the best option available. Cassava is increasingly being used as a food source as well as an industrial raw material in the production of economic goods. This study estimates cassava production efficiency and investigates the causes of inefficiency in southern Ethiopia. Cross-sectional data from 158 households were collected using a systematic questionnaire. The Cobb-Douglas (CDs) stochastic frontier production model was used to calculate production efficiency levels. The computed mean result showed technical efficiency (TE), allocative efficiency (AE), and economic efficiency (EE) levels of 74, 90, and 66%, respectively. This demonstrated that existing farm resources could increase average production efficiency by 26, 10, and 34%, respectively. The study found that land size, urea fertilizer application, and cassava planting cut all had a positive and significant effect on cassava production. It was discovered that TE was more important than AE as a source of benefit for EE. Inefficiency effects modeled using the two-limit Tobit model revealed that household head age, level of education, cassava variety, extension contact, rural credit, off-farm activities involvement to generate income, and farm size were the most important factors for improving TE, AE, and EE efficiencies. As a result, policymakers in government should consider these factors when addressing inefficiencies in cassava production. It is especially important to provide appropriate agricultural knowledge through short-term training, to provide farmers with access to formal education, to access improved cassava varieties, and to support agricultural extension services.
Determinants of plant community along environmental gradients in Geramo forest, the western escarpment of the rift valley of Ethiopia
Detailed information on plant community types, distribution, and their relationships with various environmental gradients is crucial for understanding forest dynamics and sustainable forest management because plant community types are influenced by various environmental factors. Thus, this study was conducted to investigate plant community types and species diversity in relation to various environmental gradients in Geramo Forest, which is a remnant forest in the western escarpment of the Rift Valley of Ethiopia. Vegetation data were collected in 96 nested plots (20 × 20 m2 and five 1 ×1 m2) laid systematically at a distance of 250 m along 16 line transects, which were laid 300 m apart. Environmental and disturbance variables were also collected from each main plot. Agglomerative hierarchical cluster analysis and Canonical correspondence analysis (CCA) with R software were used to identify plant community types and analyze the relationship between plant community types and environmental variables, respectively. The Shannon Wiener diversity index was used to compute species diversity among community types. Five significantly different (p ≤ 0.001) plant community types were identified. The CCA results showed that species diversity and community composition among different community types were significantly influenced by altitude, disturbance, soil organic carbon, slope, soil available phosphorus, and pH, which revealed the compounded effect of various environmental factors on species richness, diversity, and evenness among plant community types. The study also identified a significant level of anthropogenic disturbance and a strong reliance of the local community on the forest in the research area. Therefore, it is recommended that sustainable forest conservation interventions be implemented through awareness creation and the promotion of community-based approaches.