We propose to develop a Yukon-Kuskokwim Berry Outlook: a data- and observer-driven ecological monitoring and modeling framework that forecasts changes in berry habitat and abundance with climate and environmental change. Berry-producing plants are extremely important to human and wildlife communities of the Yukon-Kuskokwim (Y-K) Delta. Berry yield can be influenced by snow cover, rainfall, soil moisture, air temperature, availability of insect pollinators, and seasonal weather extremes; and berry habitat can be altered by more frequent tidal inundation, increased frequency of storm surges, and permafrost deterioration, all of which may be significantly impacted by climate change. In a recent survey of Alaskan environmental observers, 60% reported that the abundance of cloudberry (Rubus chamemorous), the most important berry species to their communities, had declined or become more variable in the past decade, and 76% reported similar changes in bog blueberry (Vaccinium uliginosum). Because of the magnitude and rapid rate of change in climate and climate impacts, the Y-K Delta is one of the most vulnerable regions in the north, yet we currently lack necessary tools and data to predict how the distribution and productivity of berry-producing plants may be altered by climate change. The Berry Outlook will be developed using Bayesian Network models that are ideal for representing ecological relationships in systems where quantitative data are complemented by local ecological knowledge (LEK), as is true in the Y-K Delta. Inputs to the models include LEK from previous sources and new collaborations, long-term ecological monitoring data, and key environmental drivers such as climate, snowpack, and tidal dynamics. This project will provide important information on the relationships among climate, land use changes, ecosystems, and village subsistence systems, in formats that can be used to address the implications of possible futures with local and regional decision makers. Phase II of this research will expand this project to include additional communities. Phase II will begin in 2019 to collect additional data that are needed to develop a mechanistic model of berry abundance and productivity and forecast potential future changes, as well as to increase our understanding of environmental pressures on berry abundance, distribution, and harvesting strategies as well as the socio-economic pressures driving adaptation.
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