Data for: Predicting berry plant habitat under climate change in Bristol Bay, AK

Aim: Climate change is altering suitable habitat distributions of many
species in high latitudes. Fleshy fruit-producing plants (hereafter “berry
plants”), important in arctic food webs and as subsistence resources for
human communities, may be impacted, but their response to a warming and
increasingly variable climate at a landscape scale has not yet been
examined.  Here, we identified influential environmental
determinants of berry plant distribution and produced predictions on how
climate change might shift these distributions. Location: Bristol Bay and
Togiak NRCS Survey Areas, Alaska. Methods: We built species distribution
models using the Random Forests algorithm to identify key characteristics
and predict the spatial distribution of habitats suitable for five berry
plant species: Vaccinium uliginosum L., Empetrum nigrum L., Rubus
chamaemorus L., Vaccinium vitis-idaea L., and Viburnum edule (Michx.) Raf.
Then, we used future climate projections (2081-2100; representative
concentration pathways 4.5, 6.0, & 8.5) to predict shifts in
species’ suitable habitat distributions based on future climate
conditions. Results: The predicted amount and spatial patterns of suitable
habitat for the current time period were variable among species,
consistent with species’ diverse life history attributes and habitat
preferences. Future climate models predicted both positive and negative
changes to suitable habitat probability for all species; future binary
classification maps predicted net declines in suitable habitat area for
all species and climate scenarios tested. Models identified elevation,
soil characteristics, and January and July temperatures as important
drivers of suitable habitat distributions. Main conclusions: Our work
contributes to understanding the response of important berry plant species
to climate change at a landscape scale. Shifting and retracting
distributions may alter where communities have access to harvesting areas,
suggesting that access to these resources may become restricted in the
future. Our prediction maps may help inform climate adaptation planning as
communities anticipate shifting access to harvesting locations.