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 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 gross primary productivity 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 gross primary productivity in the Western US. Our results provide 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).

These data are climate model output from experiments described further in the relate manuscrip by Feng et al. Briefly, we conducted simulations using National Center for Atmospheric Research (NCAR) Community Earth System Model version 1.3 (CESM, https://www.cesm.ucar.edu/models). The CESM model couples Community Atmosphere Model version 5 (CAM5) (Neale et al 2012) to the Community Land Model (CLM4.5) (Oleson et al 2013), the CICE4 sea ice model (Hunke et al 2010), and implements a slab ocean with prescribed heat transport derived from a fully-coupled ocean-atmosphere simulation (Neale et al 2012). Further details about the parameterization of the component models can be found in the papers above, as well as in the technical documentation (Oleson et al 2013). Year 2000 land use conditions based on satellite observations (Lawrence and Chase 2007) were used in the model setup, and the atmospheric CO₂ concentration was set to be constant at 400 ppm as our simulations are intended to represent approximately present-day “equilibrium” conditions in a stable climate as discussed further below. The land model component calculates surface fluxes of energy, water, and momentum which are passed to the atmospheric model. Carbon fluxes are also calculated diagnostically, and leaf area dynamically responds to photosynthesis rates through allocation of fixed carbon to leaves. This allows both surface albedo and evapotranspiration rates to vary with climate as a function of atmospheric conditions, stomatal conductance per leaf area, and leaf area.

Model simulations were conducted at the spatial resolution of 1.9◦ latitude by 2.5◦ longitude for 100 years. Climate and terrestrial variables (e.g. global surface temperature, leaf area index) reach equilibrium after approximately 40 years of model spin up. The spin up period is discarded, and we then analyze time series for the remaining 60 years. This 60-year period can be considered “equilibrium” conditions, where variations over time represent samples over the expected internal variability of the climate system rather than a time series into the future. The CESM simulations were implemented on the NCAR Cheyenne supercomputing cluster (Computational and Information Systems Laboratory, 2017), sponsored by the National Science Foundation.

We conducted 15 simulations: a control with no tree die-off and 14 experimental simulations, each corresponding to the scenario of tree die-off in one of 14 most forested ecoregions in the United States (i.e. NE, MA, SE, GL, PP, AP, OZ, NR, SR, DS, GB, PN, PS, and TA Domains of the US National Ecological Observatory Network (NEON) as in Swann et al. 2018). In each experiment, all forested area in an ecoregion was replaced with C3 grass. Present-day tree abundance was based on satellite observations (Lawrence and Chase 2007). Thus the magnitude of tree die-off varies between experiments as a function of the present-day forest cover. 

References

• Hunke E C, Lipscomb W H, Turner A K, Jeffery N and Elliott S 2010 Cice: the los alamos sea ice model documentation and software user’s manual version 4.1 la-cc-06-012 T-3 Fluid Dynamics Group, Los Alamos National Laboratory 675 500
• Lawrence P J and Chase T N. Representing a new MODIS consistent land surface in the community land model (CLM 3.0). J. Geophys. Res.: Biogeosciences, 112(G1).
• Neale R B, Chen C-C, Gettelman A, Lauritzen P H, Park S, Williamson D L, Conley A J, Garcia R, Kinnison D, Lamarque J-F and Others 2012 Description of the NCAR community atmosphere model (CAM 5.0) NCAR Tech. Note NCAR/TN-486+STR 289
• Oleson K, Lawrence D M, Bonan G B and Drewniak B 2013 Technical description of version 4.5 of the Community Land Model (CLM)(No. NCAR/TN-503+ STR) UCAR: Boulder, CO, USA
• Swann A L S, Laguë M M, Garcia E S, Field J P, Breshears D D, Moore D J P, Saleska S R, Stark S C, Villegas J C, Law D J and Minor D M 2018 Continental-scale consequences of tree die-offs in North America: identifying where forest loss matters most Environ. Res. Lett. 13 055014