Encounters Between Experiences and Measurements: The Role of Local Knowledge in Climate Change Research

Abstract

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Measurements meet human observations: integrating distinctive ways of knowing in the Pamir Mountains of Tajikistan to assess local climate change

“…Similar to the communities of Savnob and Roshorv, resource-based communities were shown to anticipate changes in temperature by using a set of ecological or sociocultural indicators, such as changes in the timing of agricultural activities, agricultural yields, livestock, infrastructure, or health (c.f. Ayanlade et al 2017;Kieslinger et al 2019;Klein et al 2014). Considering the frequency of reported impacts for each season in Savnob and Roshorv supports this argumentation (Fig.…”

“…ERA5 only showed a significant warming trend for summer, whereas community members identified autumn and winter as warming. Integrative studies in other regions also reported on different trend observations, which they argued with an existing scale mismatch between both knowledge systems (Fernández-Llamazares et al 2017;Kieslinger et al 2019). Whereas in our study a scale mismatch was prevented by downscaling ERA5 data to village-scale, the limited accuracy of the original ERA5 datasets due to missing insitu measurements still influences the spatial accuracy of downscaled temperature estimates and their significance measures.…”

“…As a last step, the linear trend analysis using the elevation corrected ERA5 dataset, was conducted. The trend magnitude and trend significance were derived using the Sen's slope estimator and the Mann Kendall test, respectively (Kendall 1975;Mann 1945;Sen 1968;Theil 1950).…”

“…Only few studies have adopted an integrated assessment of instrumental climate data and community observations in order to investigate in local scale climate processes. Studies can be found in South America (Fernández-Llamazares et al 2017;Kieslinger et al 2019;López et al 2017), the Arctic (Cuerrier et al 2015;Gearheard et al 2010;Rapinski et al 2018;Williams et al 2018), Africa (Ayanlade et al 2017;Kalanda-Joshua et al 2011;Meze-Hausken 2004;Simelton et al 2013), or the Himalaya (Gentle and Maraseni 2012;Klein et al 2014). While transdisciplinary approaches are conceptually and methodologically challenging, they appeared to be particularly promising in data-deficient environments, where local communities pursue subsistence-based livelihoods and closely anticipate changes in climate and environment over a sustain period.…”

“…Despite methodological challenges, studies concluded that the integration of instrumental data with peoples' observation can strengthen the understanding of local climate change in remote areas around the globe, and introduce new perspectives to the existing field of climate change research. Co-generated knowledge can ensure a sustainable development of local communities, strengthen their resilience towards climate change and support effective adaptation strategies and policies (Kieslinger et al 2019;Kalanda-Joshua et al 2011).…”