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Large-scale environmental changes are unfolding at an unprecedented pace, magnitude, and scale across the globe. These changes impact socio-ecological systems, including the natural capital that provides goods and services which society depends on. Tribal entities are especially prone to such changes. The natural resources that they have rights to, and on which cultural norms may be dependent on, are impacted by environmental stressors whose scale extend far beyond defined tribal jurisdictions.
The US Government (USG), through initiatives like the Climate Action Plan and the legally mandated National Climate Assessment, recognizes aspects of these challenges. The USG is also advocating better integration of US environmental observation assets and making those data freely web accessible for science, education, and management. There is also widespread recognition that we should align climate-adaptation options with the best available science and data.
The Tribal Lands Collaboratory (TLC) is an Esri-NEON collaboration to assemble existing technologies into a web-based workbench that enables multidisciplinary teams to perform integration, analysis, and interpretation of environmental data. Teams may comprise students, scientists, natural resource managers, and even the general public. The value-chain of transforming data to information and knowledge is captured at each step of the transformation to enable traceability and reproducibility.
Brian Wee, Ph.D.
Strategic Alliances
National Ecological Observatory Network (NEON), Inc.
2015-12-11
1. Mussel and barnacle beds have declined
2. Northern flickers arrive at breeding sites earlier, egg laying advanced (phenology change)
3. Increase mortality of conifers
Source: Impacts of Climate Change on Biodiversity, Ecosystems, and Ecosystem Services. Technical Input to the 2013 National Climate Assessment (7406884d)
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© 2012 National Ecological Observatory Network, Inc. All rights reserved. The National Ecological Observatory Network is a project sponsored by the National Science Foundation and managed under cooperative agreement by NEON, Inc. This material is based upon work supported by the National Science Foundation under the following grants: EF-1029808, EF-1138160, EF-1150319 and DBI-0752017. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.