Using Bayesian Belief Networks to Identify Potential Compatibilities and Conflicts Between Development and Landscape Conservation

Experts with different land use interests often use differing definitions of land suitability that can result in competing land use decisions. We use Bayesian belief networks linked to GIS data layers to integrate empirical data and expert knowledge from two different land use interests (development and conservation) in Maine’s Lower Penobscot River Watershed. Using ground locations and digital orthoquads, we determined the overall accuracy of the resulting development and conservation suitability maps to be 82% and 89%, respectively. Overlay of the two maps show large areas of land suitable for both conservation protection and economic development and provide multiple options for mitigating potential conflict among these competing land users. The modeling process can be adapted to help prioritize and choose among different alternatives as new information becomes available, or as land use and land-use policies change. The current model structure provides a maximal coverage strategy that allows decision makers to target and prioritize several areas for protection or development and to set specific strategies in the face of changing ecological, social, or economic processes. Having multiple options can generate new hypotheses and decisions at more local scales or for more specific conservation purposes not yet identified by stakeholders and decision makers in the region. Subsequently, new models can be developed using the same process, but with higher resolution data, thereby helping a community evaluate the impacts of alternative land uses between different prioritized areas at finer scales

Impact of Demographic Trends on Future Development Patterns and the Loss of Open Space in the California Mojave Desert

During the post-World War II era, the Mojave Desert Region of San Bernardino County, California, has experienced rapid levels of population growth. Over the past several decades, growth has accelerated, accompanied by significant shifts in ethnic composition, most notably from predominantly White non-Hispanic to Hispanic. This study explores the impacts of changing ethnicity on future development and the loss of open space by modeling ethnic propensities regarding family size and settlement preferences reflected by U.S. Census Bureau data. Demographic trends and land conversion data were obtained for seven Mojave Desert communities for the period between 1990 and 2001. Using a spatially explicit, logistic regression-based urban growth model, these data and trends were used to project community-specific future growth patterns from 2000 to 2020 under three future settlement scenarios: (1) an historic scenario reported in earlier research that uses a Mojave-wide average settlement density of 3.76 persons/ha; (2) an existing scenario based on community-specific settlement densities as of 2001; and (3) a demographic futures scenario based on community-specific settlement densities that explicitly model the Region\u27s changing ethnicity. Results found that under the demographic futures scenario, by 2020 roughly 53% of within-community open space would remain, under the existing scenario only 40% would remain, and under the historic scenario model the communities would have what amounts to a deficit of open space. Differences in the loss of open space across the scenarios demonstrate the importance of considering demographic trends that are reflective of the residential needs and preferences of projected future populations

Sedimentation, vegetation and land use dynamics on the Brahmaputra-Jamuna floodplain, Bangladesh

This study investigated contemporary floodplain sedimentation, interactions between sediment, vegetation, and agricultural land use, and the potential utility for a Bayesian Network Decision Support System (BNDSS) to assist farmers in making better decisions concerning agricultural land use. The research was performed around Bara Bania Mouza (village) under Daulotpur Uazila in Manikgong district of the Brahmaputra-Jamuna floodplain in Bangladesh. This area was selected because it is representative of the young and active floodplain, where the land is flooded and receives overbank sediment deposition every year. The research employed exploratory data analysis and Bayesian approaches to identify and investigate causal relationships among the variables and so support probabilistic inferences. The study investigated two distinctly different types of monsoonal flood: a bonna (an abnormally large flood that occurred in 2007) and a barsho (a normal flood that occurred in 2008). Data on landforms, flood hydraulics, sediment dynamics (suspended sediment concentrations and sediment accumulation rates), and vegetation, rain-fed flooding, land use and farmers knowledge on soil suitability and cropping were collected through field surveys. The results establish how flow and sediment dynamics contrast as a function of landform and demonstrate that the thickness and calibre of deposited sediment strongly influence farmers' decisions on which and how many crops to cultivate on a given plot. Natural vegetation (e.g. sun grass) and certain agricultural crops were shown to have huge potential for use in slowing floodwater and trapping coarse grain sediment particles in buffer stripes. Marked contrasts were also observed between the characteristics of sediment deposited by rain-fed and river water flooding. Questionnaires and semi-structured interviews revealed that although farmers have profound knowledge on soil types and crop associations their methods are crude and little or no science is involved in the investigation of soil and sediment properties. Despite this, farmers' estimates of soil properties proved to be reasonably accurate with the estimate of particle size differing by only <15% from the results of laboratory particle size analysis. This suggests that the farmers' methods do give reliable indications of key soil attributes, but that they could be improved if scientific information was integrated with their local knowledge. A Bayesian approach provides a means of achieving this and the BNDSS developed in this study was found to produce good results when compared to field observations and backward propagation indicated that for better decision making it is crucial to consider both physical and socioeconomic variables. The findings of the research reported in this thesis show that sedimentation has major impacts on agricultural land use dynamics in the Brahmaputra-Jamuna floodplain and that both natural vegetation and agricultural crops significantly influence sediment movement and the way that deposition is distributed over the floodplain. In a wider context, flood, sediment, vegetation and agricultural land use dynamics are controlled by complex set of both physical and human phenomena that are challenging to describe, integrate, analyse and interpret in a single study. In light of this, it is not surprising that the findings presented in this thesis highlight important gaps in knowledge that need to be addressed through further research

Sedimentation, vegetation and land use dynamics on the Brahmaputra-Jamuna floodplain, Bangladesh

This study investigated contemporary floodplain sedimentation, interactions between sediment, vegetation, and agricultural land use, and the potential utility for a Bayesian Network Decision Support System (BNDSS) to assist farmers in making better decisions concerning agricultural land use. The research was performed around Bara Bania Mouza (village) under Daulotpur Uazila in Manikgong district of the Brahmaputra-Jamuna floodplain in Bangladesh. This area was selected because it is representative of the young and active floodplain, where the land is flooded and receives overbank sediment deposition every year. The research employed exploratory data analysis and Bayesian approaches to identify and investigate causal relationships among the variables and so support probabilistic inferences. The study investigated two distinctly different types of monsoonal flood: a bonna (an abnormally large flood that occurred in 2007) and a barsho (a normal flood that occurred in 2008). Data on landforms, flood hydraulics, sediment dynamics (suspended sediment concentrations and sediment accumulation rates), and vegetation, rain-fed flooding, land use and farmers knowledge on soil suitability and cropping were collected through field surveys. The results establish how flow and sediment dynamics contrast as a function of landform and demonstrate that the thickness and calibre of deposited sediment strongly influence farmers' decisions on which and how many crops to cultivate on a given plot. Natural vegetation (e.g. sun grass) and certain agricultural crops were shown to have huge potential for use in slowing floodwater and trapping coarse grain sediment particles in buffer stripes. Marked contrasts were also observed between the characteristics of sediment deposited by rain-fed and river water flooding. Questionnaires and semi-structured interviews revealed that although farmers have profound knowledge on soil types and crop associations their methods are crude and little or no science is involved in the investigation of soil and sediment properties. Despite this, farmers' estimates of soil properties proved to be reasonably accurate with the estimate of particle size differing by only <15% from the results of laboratory particle size analysis. This suggests that the farmers' methods do give reliable indications of key soil attributes, but that they could be improved if scientific information was integrated with their local knowledge. A Bayesian approach provides a means of achieving this and the BNDSS developed in this study was found to produce good results when compared to field observations and backward propagation indicated that for better decision making it is crucial to consider both physical and socioeconomic variables. The findings of the research reported in this thesis show that sedimentation has major impacts on agricultural land use dynamics in the Brahmaputra-Jamuna floodplain and that both natural vegetation and agricultural crops significantly influence sediment movement and the way that deposition is distributed over the floodplain. In a wider context, flood, sediment, vegetation and agricultural land use dynamics are controlled by complex set of both physical and human phenomena that are challenging to describe, integrate, analyse and interpret in a single study. In light of this, it is not surprising that the findings presented in this thesis highlight important gaps in knowledge that need to be addressed through further research