Data from: Year-round spatiotemporal distribution of harbour porpoises within and around the Maryland wind energy area ...

• Main Authors: Wingfield, Jessica E., O'Brien, Michael, Lyubchich, Vyacheslav, Roberts, Jason J., Halpin, Patrick N., Rice, Aaron N., Bailey, Helen, O’Brien, Michael
• Format: Dataset
• Language: English
• Published: Dryad 2017
• Subjects: offshore windfarm; habitat modelling; Phocoena phocoena; spatiotemporal distribution; Impacts; C-POD; Harbour porpoise
• Online Access: https://dx.doi.org/10.5061/dryad.25256; https://datadryad.org/stash/dataset/doi:10.5061/dryad.25256

Offshore windfarms provide renewable energy, but activities during the construction phase can affect marine mammals. To understand how the construction of an offshore windfarm in the Maryland Wind Energy Area (WEA) off Maryland, USA, might impact harbour porpoises (Phocoena phocoena), it is essential to determine their poorly understood year-round distribution. Although habitat-based models can help predict the occurrence of species in areas with limited or no sampling, they require validation to determine the accuracy of the predictions. Incorporating more than 18 months of harbour porpoise detection data from passive acoustic monitoring, generalized auto-regressive moving average and generalized additive models were used to investigate harbour porpoise occurrence within and around the Maryland WEA in relation to temporal and environmental variables. Acoustic detection metrics were compared to habitat-based density estimates derived from aerial and boat-based sightings to validate the model predictions. ... : Data for analyzing occurrence of harbour porpoise foraging offshore of Maryland, USAThese data were collected using C-PODs at four sites offshore of Maryland, USA from November 2014 to May 2016. File contains a column for the date (dd/mm/yyyy), Julian Day, Day, Month, Year, the Hour (in EST), Buzz type (0 is non-foraging, 1 is foraging), the Site (1-4), and three columns used solely to create the Buzz type column (autovar, forR, and Sum_R).Foraging_Model.txtHourly acoustic detections of harbour porpoises offshore of Maryland, USAThese data were collected using C-PODs at four sites offshore of Maryland, USA from November 2014 to May 2016. Columns include the Day, Month, Year, Hour (EST), DPM_Porp (the number of minutes in each hour with a porpoise detection), DPH_Porp (presence (1) or absence (0) of a detection in each hour), autovar (for R use only), and the site (1-4).Temporal_Model.txtComparison of predicted porpoise densities and acoustic metricsPredicted porpoise densities are courtesy of Jason J. ...