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

Abstract

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. Harbour porpoises occurred significantly more frequently during January to May, and foraged significantly more often in the evenings to early mornings at sites within and outside the Maryland WEA. Harbour porpoise occurrence peaked at sea surface temperatures of 5°C and chlorophyll a concentrations of 4.5 to 7.4 mg m-3. The acoustic detections were significantly correlated with the predicted densities, except at the most inshore site. This study provides insight into previously unknown fine-scale spatial and temporal patterns in distribution of harbour porpoises offshore of Maryland. The results can be used to help inform future monitoring and mitigate the impacts of windfarm construction and other human activities.

Acoustic monitoring reveals the times and tides of harbor porpoise (Phocoena phocoena) distribution off central Oregon, U.S.A.

“…It is likely that our models would improve with the inclusion of information on dynamic environmental conditions and the distribution and abundance of prey species. Regardless, it is common for GAMs modeling cetacean occurrence at high resolution to explain only a small portion of the deviance (Best et al 2012, Forney et al 2012, and this is particularly true for temporal models , Temple et al 2016, Wingfield et al 2017.…”

Empirical evidence that large marine predator foraging behavior is consistent with area‐restricted search theory

“…The C‐PODs were moored approximately 3 m from the seabed attached to a 45‐kg anchor weight and were retrieved and redeployed approximately every 3 months (Wingfield et al. , Garrod et al. ).…”

“…Data were collected using C-PODs (Chelonia, Cornwall, UK), which detect and log odontocete echolocation clicks. The C-PODs were moored approximately 3 m from the seabed attached to a 45-kg anchor weight and were retrieved and redeployed approximately every 3 months (Wingfield et al 2017, Garrod et al 2018). These devices continuously monitor the frequency range 20-160 kHz, although they do not record the complete soundstream (details available online).…”

Presentation of Binning-Based Inter-Click Interval Data from Passive Acoustic Monitoring of Free-Ranging Harbour Porpoises (Phocoena Phocoena)

“…For example, simple bar graphs have been used effectively to display the relationship between inferred foraging and diel cycle. 12 ICI has also been modelled with temporal and environmental parameters, 28 or plotted with two way travel time to provide a proxy for distance to a target. 19 ICI data are presented most commonly as histograms, which display ICI frequency divided into specific bin widths; however, it has not been acknowledged widely in the literature that choice of bin width can have a large influence on relationships inferred visually from histograms.…”