Maximizing surveillance through spatial characterization of marine mammal stranding hot spots

Abstract

Spatial analyses of marine mammal stranding data can be used to identify stranding patterns and improve surveillance and monitoring. Using ArcGIS and SaTScan, we analyzed 12 years (2002-2014) of dead beachcast marine mammals from San Juan County, Washington, to better understand patterns of carcass deposition. We plotted the locations for 631 dead marine mammals and aggregated strandings into 1,000 m segments of shoreline. "Hot spots" included beach segments with significantly higher carcass deposition according to the Getis-Ord Gi* statistic in ArcGIS or beach segments that were encompassed by significant spatial clusters using the discrete Poisson model in SatTScan. We identified 52 hot spots for harbor seals (Phoca vitulina) in ArcGIS and 62 hot spots in SaTScan with 81% agreement between methods. Carcass deposition showed a strong relationship with locations having high proximity to public pedestrian access points, suggesting increased reporting effort in those areas. Stranding frequency was also higher on beach segments with longer fetch and nearly level or gentle slopes. Beaches with these geomorphic characteristics, especially those without high proximity to public access, would be ideal locations to actively survey to improve high quality carcass collection during times of high expected mortality and limited resources.

Spatio-temporal analysis identifies marine mammal stranding hotspots along the Indian coastline

“…With data limitation arising from reporting bias, the patterns in the study emerge from a temporally disjunct dataset coming from various sources lacking homogeneity in the way information was obtained. The data was collected on an opportunistic basis rather than dedicated beach surveys, and thus the patterns obtained could be biased by factors which are likely to influence the behaviour of informants, such as the accessibility of the shore and weather conditions 70 , 71 and unequal sampling effort 72 . In the Indian context, differences in data availability also arises with kind of marine mammal research undertaken, such as by fishery biologists in the past 47 , 73 with focus in regions in proximity of the fishery institutions (such as Central Marine Fishery Research Institute), or other institutions (National Institute of Oceanography) or individual species or area focused efforts (e.g.…”

Trends in Propeller Strike-Induced Mortality in Harbor Seals (Phoca vitulina) of the Salish Sea

“…Numerous coastal, oceanographic, and meteorological forces influence carcass dispersal and final stranding sites (Olson et al 2020). Although stranding locations do not represent the exact location at which an animal was struck, spatial analyses showed that propeller strike cases were well distributed throughout the study area, with two significant spatial clusters: one of nine strandings in the innerisland shorelines of SJC (P¼0.03), and another of three strandings at Owen's Beach in SPS (P¼0.002; Fig.…”

Global assessment of shark strandings

“…To optimize resources and increase the chances of rescue, it is extremely important to identify places where marine animals strand the most. Through spatial analysis, it is possible to map locations with higher carcass deposition, signalling hotspots and directing surveillance and monitoring efforts (Olson et al, 2020). While shark stranding is a global phenomenon, stranding reports are likely biased towards areas where there is public access and high public traffic (such as piers).…”