Changes in climate can be favorable as well as detrimental for natural and anthropogenic systems. Temperatures in Central Asia have risen significantly within the last decades whereas mean precipitation remains almost unchanged. However, climatic trends can vary greatly between different subregions, across altitudinal levels, and within seasons. Investigating in the seasonally and spatially differentiated trend characteristics amplifies the knowledge of regional climate change and fosters the understanding of potential impacts on social, ecological, and natural systems. Considering the known limitations of available climate data in this region, this study combines both high-resolution and long-term records to achieve the best possible results. Temperature and precipitation data were analyzed using Climatic Research Unit (CRU) TS 4.01 and NASA’s Tropical Rainfall Measuring Mission (TRMM) 3B43. To study long-term trends and low-frequency variations, we performed a linear trend analysis and compiled anomaly time series and regional grid-based trend maps. The results show a strong increase in temperature, almost uniform across the topographically complex study site, with particular maxima in winter and spring. Precipitation depicts minor positive trends, except for spring when precipitation is decreasing. Expected differences in the development of temperature and precipitation between mountain areas and plains could not be detected.
In mountain environments dimensions of climate change are unclear because of limited availability of meteorological stations. However, there is a necessity to assess the scope of local climate change, as the livelihood and food systems of subsistence-based communities are already getting impacted. To provide more clarity about local climate trends in the Pamir Mountains of Tajikistan, this study integrates measured climate data with community observations in the villages of Savnob and Roshorv. Taking a transdisciplinary approach, both knowledge systems were considered as equally pertinent and mutually informed the research process. Statistical trends of temperature and snow cover were retrieved using downscaled ERA5 temperature data and the snow cover product MOD10A1. Local knowledge was gathered through community workshops and structured interviews and analysed using a consensus index. Results showed, that local communities perceived increasing temperatures in autumn and winter and decreasing amounts of snow and rain. Instrumental data records indicated an increase in summer temperatures and a shortening of the snow season in Savnob. As both knowledge systems entail their own strengths and limitations, an integrative assessment can broaden the understanding of local climate trends by (i) reducing existing uncertainties, (ii) providing new information, and (iii) introducing unforeseen perspectives. The presented study represents a time-efficient and global applicable approach for assessing local dimensions of climate change in data-deficient regions.
Seasonal rounds are deliberative articulations of a community’s sociocultural relations with their ecological system. The process of visualizing seasonal rounds informs transdisciplinary research. We present a methodological approach forcommunities of enquiryto engagecommunities of practicethrough context-specific sociocultural and ecological relations driven by seasonal change. We first discuss historical précis of the concept of seasonal rounds that we apply to assess the spatial and temporal communal migrations and then describe current international research among Indigenous and rural communities in North America and Central Asia by the creation of a common vocabulary through mutual respect for multiple ways of knowing, validation of co-generated knowledge, and insights into seasonal change. By investigating the relationship between specific biophysical indicators and livelihoods of local communities, we demonstrate that seasonal rounds are an inclusive and participatory methodology that brings together diverse Indigenous and rural voices to anticipate anthropogenic climate change.
Communities in the Pamir Mountains of Central Asia are among the most vulnerable to climate change due to their geographic location and subsistence‐based livelihoods. Historically, ecological calendars supported their agropastoral lifestyles which provided anticipatory capacity to seasonal changes. Due to decades of Soviet colonization and socioecological transformations, knowledge of these ecological calendars fell into disuse. In 2016, Savnob and Roshorv, two villages in the Bartang Valley of Tajikistan, began the revitalization of these calendars using a participatory action research process through knowledge co‐generation. We undertook a comparative analysis to investigate the importance of context‐specificity to ensure food security and reduce their vulnerability to climate change. A preliminary analysis of the temperature regime and local language terms, relating to the positioning and quality of land, framed our methods‐of‐analysis. We compared the villagers' ecological calendars by focusing on indicator species, potentially threatening weather events, land‐use, livelihood activities, and the role of the vernal equinox. Despite their close geographic proximity, context‐specificity determined by distinct microecologies influences the timing and practice of these communities' livelihood activities. These villages have different dependencies on biotic and abiotic events, crops, and land‐use; all of which affect food security and survival. These differences contributed to mutual support between the two villages, increased the availability of food, and thereby, lowered their vulnerability to climate change. As Savnob's and Roshorv's ecological calendars are updated with changing climate, they can once again enhance their anticipatory capacity while reducing their vulnerability.