DOI: 10.5061/dryad.4qrfj6qbk
title: Data from: Northwest range shifts and shorter wintering period of an Arctic seabird in response to four decades of changing ocean climate

description: Climate change is altering the marine environment at a global scale, with
 some of the most dramatic changes occurring in Arctic regions.
 These changes may affect the distribution and migration patterns of marine
 species throughout the annual cycle. Species distribution models have
 provided detailed understanding of the responses of terrestrial species to
 climate changes, often based on observational data; biologging
 offers the opportunity to extend those models to migratory marine
 species that occur in marine environments where direct
 observation is difficult. We used species distribution modelling
 and tracking data to model past changes in the non-breeding
 distribution of thick-billed murres Uria lomvia from a colony in Hudson
 Bay, Canada, between 1982 and 2019. The predicted distribution of
 murres shifted during fall and winter. The largest shifts have occurred
 for fall migration, with range shits of 211 km west and 50
 km north per decade, compared with a 29 km shift west per decade
 in winter. Regions of range expansions had larger declines in sea
 ice cover, smaller increases in sea surface temperature, and
 larger increases in air temperature than regions where the range
 was stable or declining. Murres migrate in and out of Hudson Bay
 as ice forms each fall and melts each spring. Habitat in
 Hudson Bay has become available later into the fall and earlier
 in the spring, such that habitat in Hudson Bay was available for
 21 d longer in 2019 than in 1982. Clearly, marine climate is altering the
 distribution and annual cycle of migratory marine species that
 occur in areas with seasonal ice cover.
description: See paper for full methods describing data
 processing: https://doi.org/10.3354/meps13890
description: meps13890_SDM.RDS:<br> This is an R data file containing
 the species distribution model described in the paper. It is a train class
 object created with the caret package (version 6.0-84) and the ranger
 package (version 0.11.2) using (R version 3.6.1). 
 meps13890_sdm_model_train_data.csv: <br> Training data used
 in developing the species distribution model. Includes used and pseudo
 absence locations. Used locations are all 100 possible tracks calculated
 using the probGLS algorithm. Absence locations are randomly generated
 points paired with each possible location. Data include extracted
 environmental predictors at each location. Data fields are described
 in  meps13890_sdm_model_test_data.csv: <br>
 Training data used in developing the species distribution model. Includes
 used and pseudo absence locations. Used locations are all 100 possible
 tracks calculated using the probGLS algorithm. Absence locations are
 randomly generated points paired with each possible location. Data include
 extracted environmental predictors at each location.
 meps13890_data_description.csv:<br> Data descriptions for
 all columns in meps13890_sdm_model_train_data.csv and
 meps13890_sdm_model_test_data.csv
 meps13890_SDM_predictions:<br> Geotiff file with all
 predicted probability of occurrence values at 3-day intervals from
 1982-2019, for the area 115W to 5W and 30N to 80N. Make sure to keep the
 .xml file, which contains layer names (dates), with the .tif
 file.