Farmer land allocation for maize, groundnut and cotton production in Chipata District, Eastern Province, Zambia

Small-scale farmers in the Chipata District of Zambia rely on their farm fields to grow maize and groundnuts for food security. Cotton production and surplus food security crops are used to generate income to provide for their families. With increasing population pressure, available land has decreased and farmers struggle to provide the necessary food requirements and income to meet their family’s needs. The purpose of the study was to determine how a farmer can best allocate his land to produce maize, groundnuts and cotton when constrained by labor and capital resources to generate the highest potential for food security and financial gains. Data from the 2008-2009 growing season was compiled and analyzed using a linear programming model. The study determined that farmers make the most profit by allocating all additional land and resources to cotton after meeting their minimum food security requirements. The study suggests growing cotton is a beneficial practice for small-scale subsistence farmers to generate income when restricted by limited resources.

Land use/cover change using Remote Sensing and Geographic Information Systems : Pic Macaya National Park, Haiti

A post classification change detection technique based on a hybrid classification approach (unsupervised and supervised) was applied to Landsat Thematic Mapper (TM), Landsat Enhanced Thematic Plus (ETM+), and ASTER images acquired in 1987, 2000 and 2004 respectively to map land use/cover changes in the Pic Macaya National Park in the southern region of Haiti. Each image was classified individually into six land use/cover classes: built-up, agriculture, herbaceous, open pine forest, mixed forest, and barren land using unsupervised ISODATA and maximum likelihood supervised classifiers with the aid of field collected ground truth data collected in the field. Ground truth information, collected in the field in December 2007, and including equalized stratified random points which were visual interpreted were used to assess the accuracy of the classification results. The overall accuracy of the land classification for each image was respectively: 1987 (82%), 2000 (82%), 2004 (87%). A post classification change detection technique was used to produce change images for 1987 to 2000, 1987 to 2004, and 2000 to 2004. It was found that significant changes in the land use/cover occurred over the 17- year period. The results showed increases in built up (from 10% to 17%) and herbaceous (from 5% to 14%) areas between 1987 and 2004. The increase of herbaceous was mostly caused by the abandonment of exhausted agriculture lands. At the same time, open pine forest and mixed forest areas lost (75%) and (83%) of their area to other land use/cover types. Open pine forest (from 20% to 14%) and mixed forest (from18 to 12%) were transformed into agriculture area or barren land. This study illustrated the continuing deforestation, land degradation and soil erosion in the region, which in turn is leading to decrease in vegetative cover. The study also showed the importance of Remote Sensing (RS) and Geographic Information System (GIS) technologies to estimate timely changes in the land use/cover, and to evaluate their causes in order to design an ecological based management plan for the park.

Invasion patterns of emerald ash borer and European earthworms in forested ecosystems

Invasive and exotic species present a serious threat to the health and sustainability of natural ecosystems. These species often benefit from anthropogenic activities that aid their introduction and dispersal. This dissertation focuses on invasion dynamics of the emerald ash borer, native to Asia, and European earthworms. These species have shown detrimental impacts in invaded forest ecosystems across the Great Lakes region, and continue to spread via human-assisted long distance dispersal and by natural modes of dispersal into interior forests from areas of introduction. Successful forest management requires that the impact and effect of invasive species be considered and incorporated into management plans. Understanding patterns and constraints of introduction, establishment, and spread will aid in this effort. To assist in efforts to locate introduction points of emerald ash borer, a multicriteria risk model was developed to predict the highest risk areas. Important parameters in the model were road proximity, land cover type, and campground proximity. The model correctly predicted 85% of known emerald ash borer invasion sites to be at high risk. The model’s predictions across northern Michigan can be used to focus and guide future monitoring efforts. Similar modeling efforts were applied to the prediction of European earthworm invasion in northern Michigan forests. Field sampling provided a means to improve upon modeling efforts for earthworms to create current and future predictions of earthworm invasion. Those sites with high soil pH and high basal area of earthworm preferred overstory species (such as basswood and maples) had the highest likelihood of European earthworm invasion. Expanding beyond Michigan into the Upper Great Lakes region, earthworm populations were sampled across six National Wildlife Refuges to identify potential correlates and deduce specific drivers and constraints of earthworm invasion. Earthworm communities across all refuges were influenced by patterns of anthropogenic activity both within refuges and in surrounding ecoregions of study. Forest composition, soil pH, soil organic matter, anthropogenic cover, and agriculture proximity also proved to be important drivers of earthworm abundance and community composition. While there are few management options to remove either emerald ash borer or European earthworms from forests after they have become well established, prevention and early detection are important and can be beneficial. An improved understanding the factors controlling the distribution and invasion patterns of exotic species across the landscape will aid efforts to determine their consequences and generate appropriate forest management solutions to sustain ecosystem health in the presence of these invaders.

The effects of soil moisture, field-scale toposequential position, and slope on yields in irrigated upland rice fields in Flores, Comayagua, Honduras

Rice (Oryza sativa L.) is an important cash crop in Honduras because of the rice lobby’s size, willingness to protest, and ability to negotiate favorable price guarantees on a year-to-year basis. Despite the availability of inexpensive irrigation in the study area in Flores, La Villa de San Antonio, Comayagua, the rice farmers do not cultivate the crop using prescribed methods such as land leveling, puddling, and water conservation structures. Soil moisture (Volumetric Water Content) was measured using a soil moisture probe after the termination of the first irrigation within the tillering/vegetative, panicle emergence/flowering, post-flowering/pre-maturation and maturation stages. Yield data was obtained by harvesting on 1 m2 plots in each soil moisture testing site. Data was analyzed to find the influence of toposequential position along transects, slope, soil moisture, and farmers on yields. The results showed that toposequential position was more important than slope and soil moisture on yields. Soil moisture was not a significant predictor of rice yields. Irrigation politics, precipitation, and land tenure were proposed as the major explanatory variables for this result.