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Abstract Climate change is triggering regional-scale alterations in vegetation including land cover change such as forest die-off. At sufficient magnitudes, land cover change from forest die-off in one region can change not only local climate but also vegetation including agriculture elsewhere via changes in larger scale climate patterns, termed an ‘ecoclimate teleconnection’. Ecoclimate teleconnections can therefore have impacts on vegetative growth in distant regions, but the degrees to which the impact decays with distance or directionally diffuses relative to the initial perturbation are general properties that have not been evaluated. We used the Community Earth system model to study this, examining the implications of tree die-off in 14 major US forested regions. For each case we evaluated the ecological impact across North America as a function of distance and direction from the location of regional tree die-off. We found that the effects on gross primary productivity (GPP) generally decayed linearly with distance, with notable exceptions. Distance from the region of tree die-off alone explained up to ∼30% of the variance in many regions. We also found that the GPP impact was not uniform across directions and that including an additional term to account for direction to regional land cover change from tree die-off was statistically significant for nearly all regions and explained up to ∼40% of the variance in many regions, comparable in magnitude to the influence of El Nino on GPP in the Western US. Our results provide novel insights into the generality of distance decay and directional diffusion of ecoclimate teleconnections, and suggest that it may be hard to identify expected impacts of tree die-off without case-specific simulations. Such patterns of distance decay, directional diffusion, and their exceptions are relevant for cross-regional policy that links forests and other agriculture (e.g. US Department of Agriculture). 

We use survey data collected from 12,037 US respondents to examine the extent to which the American public believes that political motives drive the manner in which scientific research is conducted and assess the impact that such beliefs have on COVID-19 risk assessments. We find that this is a commonly held belief and that it is negatively associated with risk assessments. Public distrust in scientists could complicate efforts to combat COVID-19, given that risk assessments are strongly associated with one’s propensity to adopt preventative health measures.