Data from: Changing climate may drive large shifts in vegetation zones of Oregon, USA

Anticipating plausible future ecosystem states is necessary for effective
ecosystem management. We use climate analog-based impact models and a
co-production process with land managers to project future vegetation
changes for the state of Oregon, United States (2041-2070, RCP 8.5) at a
management-relevant spatial resolution (270 meters). We explored multiple
analog-based methodologies, evaluated analog model performance with
contemporary validation, and leveraged climate analogs to assess
projection uncertainty by quantifying areas where multiple vegetation
trajectories are plausible under a single climate scenario. We find that
analog-based models performed well at reproducing landscape-level
vegetation composition, and moderately well at reproducing vegetation at
the pixel level. Our results suggest that 64 % of the study area will
experience future climate conditions that support different potential
natural vegetation types, and 59 % will experience climates corresponding
with different potential plant physiognomic types, compared to
reference-period conditions. We project a 60% reduction of mesic
conifer-dominated forests with transitions to mixed evergreen forest
types. We also project losses to dry forests, cold forests and parklands,
with commensurate expansions of shrublands, grasslands, and geographic
redistribution of dry forest types. We find that in many areas, several
vegetation trajectories are plausible under a single climate scenario.
Finally, we provide guidance for using future vegetation projections and
uncertainty outputs in management decisions using the Resist-Accept-Direct
(RAD) adaptation framework.