The SPATIAL (Spatio-temporal Isotope Analytics Lab) Short Course represents a bridge between theory and measurement, introduced in ITCE Course 1, and regional-to-continental scale research. It builds on the skills and knowledge base developed in Course 1 or equivalent stable isotope biogeochemistry coursework to introduce current research themes in large-scale ecology and environmental Earth science, theoretical and technical aspects of assembling and working with large, spatially distributed datasets, and analytical and computational tools available to support such work. The course emphasizes stable isotopes as a research tool, and their unique capacity to address many ecological problems, but also stresses the integration of isotopes with other data types and methods within a geospatial framework.
Morning lectures focus on the theoretical underpinnings of spatial structure in a range of isotopic systems and how these are applied to address scientific challenges in multi-scale ecological, biogeochemical and Earth science research. Afternoon laboratory sessions introduce students to tools and techniques for working with spatially explicit environmental datasets, including geodata identification, acquisition, management, and analysis, using real data from published and unpublished sources.
Earth surface systems - Environmental, biological, and anthropogenic controls on ecological and biogeochemical structure
Fluid systems - Source, transport, and reactive process controls on the distribution of isotopic and other biogeochemical tracers
Animal systems (including humans) - Inference of behavior, physiology and movement from spatial data; animal influences on biogeochemical systems
The SPATIAL course will assume that incoming students are familiar with the fundamentals of isotopic fractionation in key Earth systems (water cycle, carbon cycle, nitrogen cycle, plant and animal systems). These topics will be reviewed briefly during relevant lectures, but not covered in detail. Graduates of ITCE Course 1 or individuals with equivalent experience will be given preference in admissions decisions. Experience with GIS or spatial analysis is not required but beneficial.
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