Geographic Information Systems (GIS) are essential tools for the analysis, modeling and display of spatially explicit coupled natural and human systems. Landscapes can be described as spatially heterogeneous geographic areas, often characterized by diverse land units interacting via social, ecological and physical processes at multiple spatial scales (Sanderson et al. 2002).. Thus, the integrative capacity of a GIS to combine data at multiple scales from a variety of sources into a single system, facilitates the emergence of new insights into social and ecological process and change responses, such as grower responses to climate change.
Geographic software, such as that supported in Atrium, is used to develop the geographic database, to provide convenient access to the data collection, and all the extraction of data for subsequent GIS analysis. Climate data will be uploaded in a GIS database in order to define a background project where other information will be added. The orchard manager interviews, historic and metabolomic data will be included in the database to gernerate layer attributes which are geographically referenced to the location of the orchard, or extent of the village/small town where they were collected. The analytical process will be guided by research questions which relate directly to the three Specific Aims of this project.
The analytical approach uses multi-scaled data ranging from local orchard interviews to Internet collected crowdsourced data to climate data. The initial products will be descriptive. The analyses will become increasingly quantitative and will be focused on the development of predictive models using ArcGIS and other mapping and analytical capabilities of Atrium. The descriptive analyses provide information such as the distribution of apple orchard biodiversity through space and time and the analysis of key landscape metrics (e.g., orchard size, land use of adjacent patches, distance to other orchards). The quantitative analyses and spatial modeling provide insights into the dynamics of orchards as combined social and ecological systems. Commonly used spatial statistics (e.g., cluster and hot spot analysis, Moran’s I and G-statistics) will be used to determine if spatial patterns and relationships exist (Issaks & Srivastava 1989, Mitchell 2005).
The Atrium system permits information dissemination to both the research team and other people who can benefit from the project’s data. For example, a user can query for a certain variety of apple and see a map showing where the apple variety is currently grown. This map can then be compared to where this apple variety potentially occurs since each variety is adapted to a specific environmental zone where appropriate climate features exist (Valentini et al. 2001) (even if other environmental factors may be limiting, e.g., soil, exposition).
GIS technology combines project data with an emerging variety of global data sets. Examples of external data include the environmental zone data (interpolated from sources such as Mitchell & Jones 2005) and the world anthropogenic biomes data (Ellis & Ramankutty 2008). The anthropogenic biomes show human-environmental interaction representations that cannot be directly observed from land cover data.
Some data, such as climate records, will be made available early in the project so that the climate variability will be known during the grower interviews. Data from the International Research Institute for Climate and Society (IRI) data library (iridl.ideo.columbia.edu/) will support this activity. It is expected that other regional and national spatial data sets will be used in subsequent analysis to refine the models.