LB 9-89 - BARRACUDA rural adaptation to climate change

Background/Question/Methods:

BARRACUDA (Biodiversity and Rural Response to Climate Change Using Data Analysis) is an interdisciplinary, multi-institution project seeking to understand how climate change will impact organisms in rural communities (including agriculture and conservation) and how rural human communities will adapt to these organismal responses. Using spatiotemporal data and stakeholder engagement are key methodological approaches. Theme 1 seeks to develop mechanistic models of range shifts, crop yields, and disease dynamics at policy-relevant spatiotemporal scales (kilometers and decades). Theme 2 seeks to understand in a national, spatially explicit way how agricultural and rural communities are resilient to and responding to climate change, and the cultural adaptation processes involved. Theme 3 seeks to develop tools that increase access to large, complex spatiotemporal data including Python and R packages for scientists and web-based browsing tools for stakeholders. Theme 4 seeks to understand how stakeholders can engage with complex spatiotemporal data in responding to climate change. Climate change and use of spatiotemporal data tie all the themes together.

Results/Conclusions:

Theme one demonstrated that carrying capacities across many sites can be estimated either from Bayesian estimation of parameters in stage-based demographic models or from curve fitting of population growth rate versus population size derived from short time series. Down-scaling efforts discovered and solved issues in applying theoretical continuous dispersal kernels to discrete pixelated rasters. Theme 2 found that crop switching has occurred on up to 10% of all US agricultural land in the last several years, and evidence suggests that farmers are shifting towards more thermophilic and drought tolerant crops. Land ownership and farm income show proportional correlation with cover crop adoption in small and medium farms; meanwhile, for large farms increasing cover crop adoption is associated with decreasing crop monoculture, farm income and land share. Conditions for the cultural evolution of group adaptive behaviors have also been identified. Theme 3 developed a SpaceTime Python library for merging heterogenous spatiotemporal data and manipulating them using a cube paradigm and provides web-based data-visualization. We also enumerated all cases of discretized temporal logic formalisms to enable spatio-temporal query in datacubes. Theme 4 has conducted iterative communications, rapport-building, and narrative dissemination structures, as well as industry-targeted outreach for community engagement and stakeholder buy-in.