Climate model experiments of regional-scale tree die-off replaced by shrubs (all monthly data fields): Part 3

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). The data in this specific
dataset represents all variables from the simulations where trees were
replaced by shrubs at monthly averaged time resolution.