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Section 5: Methods of Knowledge and Data Integration in Coupled Natural-Human Systems

Permanent URI for this collectionhttps://hdl.handle.net/10217/181746

This digital collection includes presentations, in English and Mongolian, given at the Building Resilience of Mongolian Rangelands conference held in 2015 for the topic: Methods of Knowledge and Data Integration in Coupled Natural-Human Systems.

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Browsing Section 5: Methods of Knowledge and Data Integration in Coupled Natural-Human Systems by Subject "traditional knowledge"

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    Integrating herder observations, meteorological data and remote sensing to understand climate change patterns and impacts across an eco-climatic gradient in Mongolia
    (Colorado State University. Libraries, 2015-06) Fernandez-Gimenez, M. E., author; Angerer, J. P., author; Allegretti, A. M., author; Fassnacht, S. R., author; Byamba, A., author; Chantsallkham, J., author; Reid, R., author; Venable, N. B. H., author; Nutag Action and Research Institute, publisher
    Mongolia has one of the strongest climate warming signals on Earth, and over 40% of the human population depends directly or indirectly on pastoral livestock production for their livelihoods. Thus, climate-driven changes in rangeland production will likely have a major effect on pastoral livelihoods. We examined patterns of climate change and rangeland production over 20 years in three ecological zones based on meteorological records, remote sensing and herder observations. We found the strongest trends in both instrument records and herder observations in the steppe zone, where summers are getting hotter and drier, winters colder, and rangeland production is declining. Instrument records and herder observations were most consistently aligned for total annual rainfall, and consensus among herders was greatest for changes in rainfall and production and lowest for temperature changes. We found more differences in herder observations between neighboring soums within the same ecozone than expected, suggesting the need for more fine-scale instrument observations to detect fine-scale patterns of change that herders observe.