Adam Dixon, World Wildlife Fund United States, Washington dc, with Jessica Forrest and Stephan Ehl

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Adam Dixon, World Wildlife Fund - United States, Washington DC, with Jessica Forrest and Stephan Ehl

Map Competition essay

Adam P. Dixon

Planning for Conservation in the Ruvuma Landscape
In the map “Planning for Conservation in the Ruvuma Landscape,” I sought to present an initial graphic introduction to the concept of conservation planning though the display of the multiple criteria used to develop a final conservation plan. The final map, titled “Ecological Zones,” combines the complementary datasets into one comprehensive plan for conserving the unique biological heritage that the Ruvuma Landscape contains while addressing the needs of human development in the region. The Ecological Zones map was developed by displaying the most sensitive to the least sensitive conservation targets in the region. Sensitive habitat starts as Zone 1a, then megafauna and bird habitat are considered, as well as mangroves, riparian zones and areas of high carbon biomass. The final zones are areas that pose small risk to maintaining ecological integrity of the region.
The map audience was intended to be anyone interested in the concept of conservation planning. Without a basic background in the concepts of using multiple criteria, the map may be a little out of reach. However, the map should be available intellectually to anyone who might consider the concept of using multiple datasets to obtain a final outcome. It is arranged to be demonstrate this concept plainly, as well as to intone the process of conservation planning as the viewer continues to consider the significance of each map element.
I hoped to achieve a visually striking image of the complexity of geographic data needed to produce a scientifically defensible conservation plan. In the case of the Ruvuma Landscape there are a number of geographic features that make the challenge of conservation planning even more difficult. The landscape is bisected by the national boundaries of Mozambique to the south and Tanzania to the north. This in effect makes the challenge of coordinating conservation efforts difficult due to the differences in language, culture and the dedication of the government to the conserve natural resources. This also presents a cartographic challenge due to the inclusion of national boundaries and country name labels amongst the pile of other concepts needed to represented on the map. The width and grayscale of the country boundaries line was determined to be the best way to suggest that the conservation landscape is a transnational one, and that several countries form the geopolitical calculus of conservation planning in the region. The width and grayscale of the country boundaries were also intended not to distract from the fact that ecosystems do not have national boundaries. Nuance was critical in this choice and the many others I made throughout the development of this map.
Final touches to the map included processing outside of ArcGIS. I exported the map as several adobe .ai files so that I could add the background shadows to each of the criteria maps as well as the frame of extent globe in the upper right hand corner of the map. These nuances I believe elevated the idea that each of the criteria are separate from the final Ecolgical Zones map. It also made the map more visually appealing and the viewer more likely to consider each criterion.
Perhaps the biggest challenge was to sort the species, environmental, social, development, land cover and political data into a compelling visual arrangement without detracting from the importance of any one dataset, and most importantly without detracting from the final Ecological Zones map. Each label and legend was carefully placed to maintain consistency throughout the map. In addition, in order to insinuate the decision making process I positioned the datasets according to theme. The species datasets are more toward the left side of the map, the carbon biomass then land cover are placed near the middle, and the datasets that contain social and political are more toward the right side of the map. The human-elephant conflict and low development areas, human land use and roads and population datasets were purposely placed in the upper right-hand corner of the datasets to emphasize their importance and inclusion in conservation planning.
This map is being entered into the competition for best use of science because of its comprehensive inclusion of criteria used to develop a conservation plan. Landscape level planning comes from a combination of disciplines, and in this case a blend of ecological and social research to suggest the best way to advance the protection of the unique biological heritage of an area with high rates of poverty, low joblessness and inadequate development of public resources like clean water and health care. Furthermore, the map presents a concept that forms a prediction of how best to conserve the natural environment and challenges the viewer to develop reasons why the map is logical or why the map might not present enough evidence to make a convincing case for the study. Ultimately, there are multiple concepts presented in the map that are in need of further explanation, however, with a supplementary report lacking the viewer is compelled to seek more information about the concepts presented, and thus the map has succeeded in creating more curiosity about the idea of conservation planning and all of the criteria used. This is in essence the main factor making a map about science a visual success; it offers a basic explanation to make a compelling basis for each map element, but it also motivates and invites the viewer to learn more about the science that made the map possible.
Each criterion in the map is based on using geographic information science to develop a spatial representation of the theme. The habitat suitability models are based on a literature-based methodology for developing a prediction of species occurrence. Habitat suitability modeling has been a significant research area for the last decade in conservation ecology. The water sources data included with the Important Bird Area themed map were developed from the WWF and USGS Hydrosheds project which used SRTM data to create among other hydrological features, a global river network. The Elephant Zones map was developed using the habitat suitability model, a least-cost corridor analysis to model elephant movement in the region, radio collar data as well as point observation taken in several elephant studies in the region. The land cover dataset was based on a series of land cover analysis in the region based on separate datasets for Tanzania and Mozambique. An amalgamation of data was ultimately used to process the final land cover dataset.
The rest of the criteria delved more into the social sciences since they were based presenting data on population, human land use and concessions made to extractive industries such as oil and gas, timber and mining. Also extremely important is the delineation of protected area boundaries throughout the landscape. The decisions made on management protocols in these areas are critical to the ultimate success of conservation in the region. Further, comparing the protected areas to the ecological zones map, one can determine areas that may not have enough level of protection.
I assisted in many stages on the development of conservation planning the Ruvuma landscape and am excited to present the work to this map contest. I am proud of the work WWF has accomplished in this region and that my abilities as a new professional in the field of Conservation GIS were able to be utilized. I was unable to let the opportunity of using the data derived from this project to develop a final synopsis map describing the project as a whole pass and was compelled to create this map for entry into the map contest. Thanks.

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