Event Title

Maximizing surveillance through spatial characterization of marine mammal stranding hot spots in San Juan County, WA

Presentation Abstract

Spatial analyses of marine mammal stranding data can be used to identify stranding patterns including those associated with Unusual Mortality Events (UMEs). Despite the power of the tool, it has rarely been used to improve surveillance and monitoring. Using ArcGIS and SaTScan, we analyzed 12 years of stranding data from San Juan County, Washington to better understand patterns of carcass deposition. We plotted locations for 631 dead marine mammals that stranded from 2002-2014 and aggregated stranding events into 1000m segments of shoreline. Stranding “hot spots” included beach segments that had significantly higher carcass deposition according to the Getis-Ord Gi* statistic in ArcGIS or segments that were encompassed by significant spatial clusters using the discrete Poisson model in SatTScan. There was a greater frequency of pinniped strandings (84%) compared to cetacean strandings (16%), and there was 65% overlap between cetacean and pinniped hot spots. Hot spots were characterized for the locally abundant harbor seal (Phoca vitulina). We identified 52 hot spots in ArcGIS and 62 hot spots in SaTScan with 81% consistency between the two methods. High proximity to public pedestrian access points was a strong determining factor for significant hot spots, likely due to increased reporting effort in those areas. In addition to this potential reporting bias, beach segments with longer fetch distances and nearly level or gentle slopes were more likely to be hot spots and could prove to be ideal locations to survey to increase routine collection of quality pinniped carcasses for postmortem analysis and disease surveillance. In the case of UMEs or oil spills, targeting these locations could maximize carcass recovery with limited response effort. Other stranding networks in the region could use this methodology to identify local marine mammal hot spots and improve stranding response, especially during times of high expected mortality and low response resources.

Session Title

Posters: Species & Food Webs

Conference Track

SSE18: Posters

Conference Name

Salish Sea Ecosystem Conference (Seattle, WA : 2018)

Document Type

Event

SSEC Identifier

SSE18-105

Start Date

5-4-2018 11:30 AM

End Date

5-4-2018 1:30 PM

Type of Presentation

Poster

Contributing Repository

Digital content made available by University Archives, Heritage Resources, Western Libraries, Western Washington University.

Geographic Coverage

Salish Sea (B.C. and Wash.)

Rights

This resource is displayed for educational purposes only and may be subject to U.S. and international copyright laws. For more information about rights or obtaining copies of this resource, please contact University Archives, Heritage Resources, Western Libraries, Western Washington University, Bellingham, WA 98225-9103, USA (360-650-7534; heritage.resources@wwu.edu) and refer to the collection name and identifier. Any materials cited must be attributed to the Salish Sea Ecosystem Conference Records, University Archives, Heritage Resources, Western Libraries, Western Washington University.

Type

text

Language

English

Format

application/pdf

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Apr 5th, 11:30 AM Apr 5th, 1:30 PM

Maximizing surveillance through spatial characterization of marine mammal stranding hot spots in San Juan County, WA

Spatial analyses of marine mammal stranding data can be used to identify stranding patterns including those associated with Unusual Mortality Events (UMEs). Despite the power of the tool, it has rarely been used to improve surveillance and monitoring. Using ArcGIS and SaTScan, we analyzed 12 years of stranding data from San Juan County, Washington to better understand patterns of carcass deposition. We plotted locations for 631 dead marine mammals that stranded from 2002-2014 and aggregated stranding events into 1000m segments of shoreline. Stranding “hot spots” included beach segments that had significantly higher carcass deposition according to the Getis-Ord Gi* statistic in ArcGIS or segments that were encompassed by significant spatial clusters using the discrete Poisson model in SatTScan. There was a greater frequency of pinniped strandings (84%) compared to cetacean strandings (16%), and there was 65% overlap between cetacean and pinniped hot spots. Hot spots were characterized for the locally abundant harbor seal (Phoca vitulina). We identified 52 hot spots in ArcGIS and 62 hot spots in SaTScan with 81% consistency between the two methods. High proximity to public pedestrian access points was a strong determining factor for significant hot spots, likely due to increased reporting effort in those areas. In addition to this potential reporting bias, beach segments with longer fetch distances and nearly level or gentle slopes were more likely to be hot spots and could prove to be ideal locations to survey to increase routine collection of quality pinniped carcasses for postmortem analysis and disease surveillance. In the case of UMEs or oil spills, targeting these locations could maximize carcass recovery with limited response effort. Other stranding networks in the region could use this methodology to identify local marine mammal hot spots and improve stranding response, especially during times of high expected mortality and low response resources.