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Table 1 – Listing of Countries in the Continent of South America and the Infrastructure datasets that have been collected in a period of six months in 2006. We continue to gather data. Countries with an asterisk (*) do not have TNC presence. Evaluating Infrastructure Information Throughout South America to Measure Human Impacts on Biodiversity Leonardo Sotomayor The Nature Conservancy, South America Conservation Region - Quito, Ecuador C. Impact of Infrastructure on Biodiversity Using a series of parameters to define the effects of each human activity (fire, conversion to agriculture, infrastructure and others) on coarse filter targets (South America Conservation Region, 2006), we were able to determine focal and peripheral effects on virtually all of the mapped terrestrial ecosystems (Sayre et al, 2005). Roads, railroads and populated places were used to create an accessibility model (figure 3). This set of infrastructure datasets were considered in this model to define travel times to a specific set of markets. In this case, we used all cities of more than 1000 inhabitants as our market locations (South America Conservation Region, 2006). Airports and dams were used in a separate analysis that considers the specific distances as effects from each of the infrastructure locations (South America Conservation Region, 2006). The combination of these two infrastructure components (accessibility and distance to infrastructure), and the addition of other human activities, produces a combined human impact map as represented in each occurrence of the coarse filter target (figure 4). Conclusions Infrastructure alone is not a considerable variable in determining habitat conversion. It is the secondary effects of road construction, for instance, that drives conversion of natural areas. Although we can represent infrastructure spatially, it is imperative that this data be reliable and documented to be interpreted. By organizing all of the necessary and appropriate spatial infrastructure data and their respective key attributes, data managers will be able to follow the established data parameters and standards. It is only then that we are able to perform in depth analyses that show the specific effects of human activity on natural habitats. Literature Cited - Curtin, Kevin, V. Noronha, M. Goodchild, S. Grisé. 2003. ArcGIS Transportation Data Model (UNETRANS). UCSB and ESRI. - Groves, Craig. 2003. Drafting a Conservation Blueprint. Island Press. - Reid, John and W. C. de Souza Jr. 2005. Infrastructure and Conservation Policy in Brazil. Conservation Biology 740-746, Vol. 19, No. 3. - Sayre, Roger, J. Bow, C. Josse. 2005. Modeling NatureServe’s Latin America and Caribbean Ecological Systems throughout South America. The Nature Conservancy. - South America Conservation Region. 2006. Biodiversity Threats Assessment. The Nature Conservancy - Wilke, David, E. Shaw, F. Rotberg, G. Morelli and P. Auzel. 2000. Roads Development and Conservation in the Congo. Conservation Biology 1614-1622, Vol. 14 No. 6 Acknowledgments Milena Ribeiro, Lucyana Barros, Eric Armijo, Marcelo Guevara, Marcelo Matsumoto, Andrew Jarvis, Glenn Hyman, Mauricio Castro, Jerry Touval For further information Please contact lsotomayor@tnc.org. More information on this and related projects can be obtained at www.conserveonline/workspaces/sacrgis. At this location you can find maps, reports and other posters presented by the South America Conservation Region GIS Staff. Introduction Although human-built infrastructure (roads, ports, railways, urban places and more) is not a direct cause of habitat conversion, but is rather a catalyst that facilitates access to natural areas (Reid and De Souza, 2005). Infrastructure information is a key component to measuring current and past impacts on biodiversity, as well as a useful indicator for possible expansion of human activity due to the construction of new infrastructure (Wilkie et al, 2000). Development of a current human impact (threat) map, applicability of infrastructure development as a conservation strategy and identification of specific effects of infrastructure on biodiversity, are a few of the applications that have been considered by traditional conservation planning (Groves et al, 2003). For these purposes, the South America GIS staff has compiled, organized and standardized a series of datasets on infrastructure from the countries where The Nature Conservancy has presence in the continent. In this poster we present a data structure model as well as two applications of infrastructure data to measure impacts on biodiversity. Materials and methods First, we compiled, standardized and documented infrastructure data gathered in 9 out of 13 countries in South America. Second, we performed a data inventory and determined possible sources to replace the missing data. Third, we created a data model based on current standards and populated the data in a GIS (Curtin, et al, 2003). We considered what are some of the key attributes that the infrastructure needs to have to be able to measure its impact on biodiversity. Fourth, we evaluated relative impact of infrastructure in coarse filter biodiversity targets. Finally, we designed a method to update this data model as new data becomes available. This infrastructure data inventory and analysis examples show the updated impact of human activity at a scale that can be used to analyze coarse filter targets at an ecoregional assessment scale, at political scales and also comprehensively across the continent. L. Sotomayor 2006 L. Sotomayor 2005 © M. Godfrey 2005 © Scott Warren © Charlie Ott Mark Godfrey © 2006 The Nature Conservancy Results A. Data compilation, documentation and inventory: We collected over 35 infrastructure datasets from 9 countries in South America (table 1). We documented metadata with as much information as was available for each dataset for all 35 datasets. Figure 2 maps roads as an example of the compilation. B. Infrastructure Data Model: Because of the variety of sources from each of the datasets, there was no consistency among attribute table. We defined a series a common set of key data attributes among each of the infrastructure datasets using references such as the ESRI data models (Curtin et al, 2003) (Table 2). Table 2 – Infrastructure and key attributes that describe the magnitude of likely impacts to biodiversity resulting from direct and indirect effects from the development of this infrastructure. Figure 2 – Map of all Roads in South America. This compilation includes all complete roads, roads of all orders and most are official compilations from their countries of origin. Figure 3 – Map of accessibility in South America. This continuous map shows how accessible a location is based on access to roads, elevation, slope and land cover type. Figure 4 – Vulnerability to human activities in South America. This map shows in red terrestrial ecosystems that are the most vulnerable due to human activity (threat). Draft – Nov. 2006 Draft – Nov. 2006